diff --git a/python/pyproject.toml b/python/pyproject.toml index c7d9880ff..9cc6cde9c 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "niwrap" -version = "0.2.1" +version = "0.3.0" description = "Neuroimaging Python wrappers." authors = ["Child Mind Institute "] license = "LGPL-2.1" diff --git a/python/src/niwrap/afni/__init__.py b/python/src/niwrap/afni/__init__.py deleted file mode 100644 index dfd5a6058..000000000 --- a/python/src/niwrap/afni/__init__.py +++ /dev/null @@ -1,582 +0,0 @@ -""" -AFNI - -AFNI (Analysis of Functional NeuroImages) is a leading software suite of C, -Python, R programs and shell scripts primarily developed for the analysis and -display of multiple MRI modalities: anatomical, functional MRI (FMRI) and -diffusion weighted (DW) data. It is freely available (both as open source code -and as precompiled binaries) for research purposes. The software is made to run -on virtually any Unix system with X11 and Motif displays. Binary packages are -provided for MacOS and Linux systems such as Fedora, CentOS/Red Hat and Ubuntu -(which includes the Windows Subsystem for Linux). - -URL: https://afni.nimh.nih.gov/ -""" -# This file was auto generated by Styx. -# Do not edit this file directly. - -from .abids_json_info_py import * -from .abids_json_tool_py import * -from .abids_tool import * -from .adjunct_apqc_tsnr_general import * -from .adjunct_aw_tableize_roi_info_py import * -from .adjunct_calc_mont_dims_py import * -from .adjunct_combine_str_py import * -from .adjunct_is_label_py import * -from .adjunct_make_script_and_rst_py import * -from .adjunct_select_str_py import * -from .adjunct_simplify_cost import * -from .adjunct_suma_fs_mask_and_qc import * -from .adjunct_suma_fs_roi_info import * -from .adjunct_tort_plot_dp_align import * -from .adwarp import * -from .afni import * -from .afni_batch_r import * -from .afni_check_omp import * -from .afni_history import * -from .afni_open import * -from .afni_proc_py import * -from .afni_run_r import * -from .afni_system_check_py import * -from .aiv import * -from .align_epi_anat import * -from .analyze_trace import * -from .ap_run_simple_rest import * -from .apqc_make_html import * -from .apqc_make_tcsh_py import * -from .apsearch import * -from .auto_warp_py import * -from .balloon import * -from .bayes_view import * -from .bayesian_group_ana_py import * -from .brain_skin import * -from .build_afni_py import * -from .cat_matvec import * -from .ccalc import * -from .cifti_tool import * -from .cjpeg import * -from .clust_exp_hist_table_py import * -from .clust_exp_stat_parse_py import * -from .column_cat import * -from .compare_surfaces import * -from .convert_cdiflist_to_grads import * -from .convert_dset import * -from .convert_surface import * -from .convex_hull import * -from .count import * -from .create_icosahedron import * -from .dcm2niix_afni import * -from .dicom_hdr import * -from .dicom_hinfo import * -from .dicom_to_raw import * -from .dimon import * -from .djpeg import * -from .drive_suma import * -from .dsetstat2p import * -from .dtistudio_fiberto_segments import * -from .epi_b0_correct import * -from .examine_xmat import * -from .fat_mat2d_plot_py import * -from .fat_mat_sel_py import * -from .fat_mat_tableize import * -from .fat_mvm_gridconv_py import * -from .fat_mvm_prep import * -from .fat_mvm_scripter_py import * -from .fat_proc_align_anat_pair import * -from .fat_proc_axialize_anat import * -from .fat_proc_connec_vis import * -from .fat_proc_convert_dcm_anat import * -from .fat_proc_convert_dcm_dwis import * -from .fat_proc_decmap import * -from .fat_proc_dwi_to_dt import * -from .fat_proc_filter_dwis import * -from .fat_proc_imit2w_from_t1w import * -from .fat_proc_map_to_dti import * -from .fat_proc_select_vols import * -from .fat_roi_row import * -from .fatcat_matplot import * -from .fdrval import * -from .fftest import * -from .file_tool import * -from .fim2 import * -from .find_variance_lines import * -from .firdesign import * -from .float_scan import * -from .from3d import * -from .fsread_annot import * -from .gen_epi_review_py import * -from .gen_group_command import * -from .gen_ss_review_scripts import * -from .gen_ss_review_table_py import * -from .get_afni_model_prf import * -from .get_afni_model_prf_6 import * -from .get_afni_model_prf_6_bad import * -from .gifti_tool import * -from .gltsymtest import * -from .help_format import * -from .im2niml import * -from .images_equal import * -from .imand import * -from .imaver import * -from .imcalc import * -from .imcat import * -from .imcutup import * -from .imdump import * -from .immask import * -from .imreg import * -from .imrotate import * -from .imstack import * -from .imstat import * -from .imupsam import * -from .init_user_dotfiles_py import * -from .inspec import * -from .iso_surface import * -from .make_color_map import * -from .make_pq_script_py import * -from .make_random_timing_py import * -from .make_stim_times_py import * -from .map_icosahedron import * -from .map_track_id import * -from .mba import * -from .meica_py import * -from .myget import * -from .neuro_deconvolve_py import * -from .nicat import * -from .niccc import * -from .nifti_tool import * -from .niml_feedme import * -from .nsize import * -from .p2dsetstat import * -from .parse_fs_lt_log_py import * -from .plugout_drive import * -from .plugout_ijk import * -from .plugout_tt import * -from .plugout_tta import * -from .prompt_popup import * -from .prompt_user import * -from .pta import * -from .qdelaunay import * -from .qhull import * -from .quick_alpha_vals_py import * -from .quickspec import * -from .quickspec_sl import * -from .quotize import * -from .r_pkgs_install import * -from .rba import * -from .rbox import * -from .read_matlab_files_py import * -from .realtime_receiver import * -from .retro_ts_py import * -from .rmz import * -from .roi2dataset import * -from .roigrow import * -from .rotcom import * -from .rsfgen import * -from .rtfeedme import * -from .samp_bias import * -from .scale_to_map import * -from .serial_helper import * -from .sfim import * -from .slow_surf_clustsim_py import * -from .spharm_deco import * -from .spharm_reco import * -from .stimband import * -from .strblast import * -from .suma_change_spec import * -from .suma_glxdino import * -from .surf2_vol_coord import * -from .surf_clust import * -from .surf_dist import * -from .surf_dset_info import * -from .surf_extrema import * -from .surf_fwhm import * -from .surf_info import * -from .surf_layers import * -from .surf_localstat import * -from .surf_measures import * -from .surf_mesh import * -from .surf_patch import * -from .surf_qual import * -from .surf_retino_map import * -from .surf_smooth import * -from .surf_to_surf import * -from .surface_metrics import * -from .tedana_wrapper_py import * -from .tfim import * -from .timing_tool_py import * -from .to3d import * -from .tokens import * -from .trr import * -from .uber_align_test_py import * -from .uber_proc_py import * -from .uber_skel import * -from .uber_subject_py import * -from .un_warp_epi_py import * -from .uniq_images import * -from .v_1d_apar2mat import * -from .v_1d_astrip import * -from .v_1d_bandpass import * -from .v_1d_bport import * -from .v_1d_correlate import * -from .v_1d_dw_grad_o_mat__ import * -from .v_1d_flag_motion import * -from .v_1d_marry import * -from .v_1d_nlfit import * -from .v_1d_rplot import * -from .v_1d_sem import * -from .v_1d_tool_py import * -from .v_1d_tsort import * -from .v_1d_upsample import * -from .v_1dcat import * -from .v_1ddot import * -from .v_1deval import * -from .v_1dfft import * -from .v_1dgen_arma11 import * -from .v_1dgrayplot import * -from .v_1dmatcalc import * -from .v_1dnorm import * -from .v_1dplot import * -from .v_1dplot_py import * -from .v_1dsound import * -from .v_1dsum import * -from .v_1dsvd import * -from .v_1dtranspose import * -from .v_24swap import * -from .v_2d_im_reg import * -from .v_2dcat import * -from .v_2perm import * -from .v_2swap import * -from .v_3_droimaker import * -from .v_3d_aboverlap import * -from .v_3d_acost import * -from .v_3d_afnito3_d import * -from .v_3d_afnito_analyze import * -from .v_3d_afnito_nifti import * -from .v_3d_afnito_niml import * -from .v_3d_afnito_raw import * -from .v_3d_allineate import * -from .v_3d_amp_to_rsfc import * -from .v_3d_anhist import * -from .v_3d_anova import * -from .v_3d_anova2 import * -from .v_3d_anova3 import * -from .v_3d_attribute import * -from .v_3d_auto_tcorrelate import * -from .v_3d_autobox import * -from .v_3d_automask import * -from .v_3d_ball_match import * -from .v_3d_bandpass import * -from .v_3d_blur_in_mask import * -from .v_3d_blur_to_fwhm import * -from .v_3d_brain_sync import * -from .v_3d_brain_voyagerto_afni import * -from .v_3d_brick_stat import * -from .v_3d_clip_level import * -from .v_3d_clust_count import * -from .v_3d_clust_sim import * -from .v_3d_clusterize import * -from .v_3d_cm import * -from .v_3d_compare_affine import * -from .v_3d_conformist import * -from .v_3d_convolve import * -from .v_3d_cruiseto_afni import * -from .v_3d_deconvolve import * -from .v_3d_degree_centrality import * -from .v_3d_depth_map import * -from .v_3d_despike import * -from .v_3d_detrend import * -from .v_3d_dft import * -from .v_3d_diff import * -from .v_3d_dteig import * -from .v_3d_dtto_dwi import * -from .v_3d_dtto_noisy_dwi import * -from .v_3d_dwito_dt import * -from .v_3d_dwuncert import * -from .v_3d_ecm import * -from .v_3d_edu_01_scale import * -from .v_3d_eigs_to_dt import * -from .v_3d_empty import * -from .v_3d_entropy import * -from .v_3d_errts_cormat import * -from .v_3d_exchange import * -from .v_3d_extract_group_in_corr import * -from .v_3d_extrema import * -from .v_3d_fdr import * -from .v_3d_fft import * -from .v_3d_friedman import * -from .v_3d_fwhmx import * -from .v_3d_gen_feature_dist import * -from .v_3d_gen_priors import * -from .v_3d_getrow import * -from .v_3d_grayplot import * -from .v_3d_group_in_corr import * -from .v_3d_hist import * -from .v_3d_icc import * -from .v_3d_intracranial import * -from .v_3d_inv_fmri import * -from .v_3d_isc import * -from .v_3d_kruskal_wallis import * -from .v_3d_lfcd import * -from .v_3d_lme import * -from .v_3d_lmer import * -from .v_3d_local_acf import * -from .v_3d_local_bistat import * -from .v_3d_local_histog import * -from .v_3d_local_pv import * -from .v_3d_local_svd import * -from .v_3d_local_unifize import * -from .v_3d_localstat import * -from .v_3d_lomb_scargle import * -from .v_3d_lrflip import * -from .v_3d_lss import * -from .v_3d_mann_whitney import * -from .v_3d_mask_to_ascii import * -from .v_3d_match import * -from .v_3d_mean import * -from .v_3d_median_filter import * -from .v_3d_mema import * -from .v_3d_mepfm import * -from .v_3d_mse import * -from .v_3d_mss import * -from .v_3d_multi_thresh import * -from .v_3d_mvm import * -from .v_3d_mvm_validator import * -from .v_3d_net_corr import * -from .v_3d_nlfim import * -from .v_3d_normality_test import * -from .v_3d_notes import * -from .v_3d_nwarp_adjust import * -from .v_3d_nwarp_apply import * -from .v_3d_nwarp_cat import * -from .v_3d_nwarp_funcs import * -from .v_3d_nwarp_xyz import * -from .v_3d_overlap import * -from .v_3d_par2_afni import * -from .v_3d_periodogram import * -from .v_3d_pfm import * -from .v_3d_polyfit import * -from .v_3d_pval import * -from .v_3d_pvmap import * -from .v_3d_qwarp import * -from .v_3d_rank import * -from .v_3d_rankizer import * -from .v_3d_re_ho import * -from .v_3d_reg_ana import * -from .v_3d_remlfit import * -from .v_3d_retino_phase import * -from .v_3d_roistats import * -from .v_3d_row_fillin import * -from .v_3d_rprog_demo import * -from .v_3d_rsfc import * -from .v_3d_seg import * -from .v_3d_setup_group_in_corr import * -from .v_3d_sharpen import * -from .v_3d_signatures import * -from .v_3d_skull_strip import * -from .v_3d_slice_ndice import * -from .v_3d_space_time_corr import * -from .v_3d_spat_norm import * -from .v_3d_stat_clust import * -from .v_3d_surf2_vol import * -from .v_3d_surf_mask import * -from .v_3d_synthesize import * -from .v_3d_tagalign import * -from .v_3d_tcat import * -from .v_3d_tcorr1_d import * -from .v_3d_tcorr_map import * -from .v_3d_tcorrelate import * -from .v_3d_tfilter import * -from .v_3d_tfitter import * -from .v_3d_threeto_rgb import * -from .v_3d_tnorm import * -from .v_3d_tortoiseto_here import * -from .v_3d_toutcount import * -from .v_3d_toy_prog import * -from .v_3d_tproject import * -from .v_3d_tqual import * -from .v_3d_track_id import * -from .v_3d_trfix import * -from .v_3d_tsgen import * -from .v_3d_tshift import * -from .v_3d_tsmooth import * -from .v_3d_tsort import * -from .v_3d_tsplit4_d import * -from .v_3d_tstat import * -from .v_3d_tto1_d import * -from .v_3d_twoto_complex import * -from .v_3d_undump import * -from .v_3d_unifize import * -from .v_3d_upsample import * -from .v_3d_vec_rgb_to_hsl import * -from .v_3d_vol2_surf import * -from .v_3d_warp import * -from .v_3d_warp_drive import * -from .v_3d_wilcoxon import * -from .v_3d_winsor import * -from .v_3d_xclust_sim import * -from .v_3d_xyzcat import * -from .v_3d_zcat import * -from .v_3d_zcutup import * -from .v_3d_zeropad import * -from .v_3d_zipper_zapper import * -from .v_3d_zregrid import * -from .v_3danisosmooth import * -from .v_3daxialize import * -from .v_3dbucket import * -from .v_3dcalc import * -from .v_3dclust import * -from .v_3dcopy import * -from .v_3ddelay import * -from .v_3ddot import * -from .v_3ddot_beta import * -from .v_3dedge3 import * -from .v_3dedgedog import * -from .v_3dfim_ import * -from .v_3dfractionize import * -from .v_3dhistog import * -from .v_3dinfill import * -from .v_3dinfo import * -from .v_3dkmeans import * -from .v_3dmask_svd import * -from .v_3dmask_tool import * -from .v_3dmaskave import * -from .v_3dmaskdump import * -from .v_3dmatcalc import * -from .v_3dmatmult import * -from .v_3dmaxdisp import * -from .v_3dmaxima import * -from .v_3dmerge import * -from .v_3dnewid import * -from .v_3dnvals import * -from .v_3dpc import * -from .v_3drefit import * -from .v_3drename import * -from .v_3dresample import * -from .v_3dretroicor import * -from .v_3drotate import * -from .v_3dsvm import * -from .v_3dsvm_linpredict import * -from .v_3dto_xdataset import * -from .v_3dttest__ import * -from .v_3dvolreg import * -from .v_4swap import * -from .v__1d_diff_mag import * -from .v__2dwarper import * -from .v__2dwarper_allin import * -from .v__4_daverage import * -from .v__add_edge import * -from .v__afni_env import * -from .v__afni_orient2_raimap import * -from .v__afni_orient_sign import * -from .v__afni_r_package_install import * -from .v__afni_refacer_make_master import * -from .v__afni_refacer_make_onebig_a12 import * -from .v__afni_refacer_run import * -from .v__afni_run_me import * -from .v__align_centers import * -from .v__align_partial_oblique import * -from .v__anaticor import * -from .v__animal_warper import * -from .v__atlasize import * -from .v__auto_tlrc import * -from .v__build_afni_xlib import * -from .v__center_distance import * -from .v__chauffeur_afni import * -from .v__check_for_afni_dset import * -from .v__clip_volume import * -from .v__clust_exp_cat_lab import * -from .v__clust_exp_run_shiny import * -from .v__command_globb import * -from .v__compute_gcor import * -from .v__compute_oc_weights import * -from .v__deblank_file_names import * -from .v__demo_prompt import * -from .v__dice_metric import * -from .v__diff_files import * -from .v__diff_tree import * -from .v__djunct_4d_imager import * -from .v__djunct_4d_slices_to_3d_vol import * -from .v__djunct_anonymize import * -from .v__djunct_dwi_selector import * -from .v__djunct_edgy_align_check import * -from .v__djunct_modal_smoothing_with_rep import * -from .v__djunct_montage_coordinator import * -from .v__djunct_overlap_check import * -from .v__djunct_ssw_intermed_edge_imgs import * -from .v__do_examples import * -from .v__electro_grid import * -from .v__examine_gen_feat_dists import * -from .v__extract_meica_ortvec import * -from .v__fast_roi import * -from .v__fat_tract_colorize import * -from .v__find_afni_dset_path import * -from .v__fix_fssphere import * -from .v__float_fix import * -from .v__from_rai import * -from .v__fs_roi_label import * -from .v__fslabel2dset import * -from .v__get_afni_dims import * -from .v__get_afni_id import * -from .v__get_afni_orient import * -from .v__get_afni_prefix import * -from .v__get_afni_res import * -from .v__get_afni_version import * -from .v__get_afni_view import * -from .v__grad_flip_test import * -from .v__grayplot import * -from .v__help_afni import * -from .v__is_oblique import * -from .v__iso_masks import * -from .v__make_label_table import * -from .v__make_plug_diff import * -from .v__measure_bb_thick import * -from .v__measure_erosion_thick import * -from .v__measure_in2out import * -from .v__move_to_series_dirs import * -from .v__no_ext import * -from .v__no_pound import * -from .v__noisy_skull_strip import * -from .v__np import * -from .v__parse_afni_name import * -from .v__purify_1_d import * -from .v__quiet_talkers import * -from .v__radial_correlate import * -from .v__rename_panga import * -from .v__reorder import * -from .v__retino_proc import * -from .v__roi_corr_mat import * -from .v__roi_decluster import * -from .v__roi_modal_grow import * -from .v__scale_volume import * -from .v__script_check import * -from .v__shift_volume import * -from .v__show_dynamic_range import * -from .v__simulate_motion import * -from .v__skull_strip_touch_up import * -from .v__snapshot_volreg import * -from .v__spharm_examples import * -from .v__sswarper import * -from .v__statauxcode import * -from .v__suma_acknowledge import * -from .v__suma_align_to_experiment import * -from .v__suma_fsvol_to_brik import * -from .v__suma_make_spec_caret import * -from .v__suma_make_spec_fs import * -from .v__suma_make_spec_sf import * -from .v__suma_renumber_fs import * -from .v__suma_reprefixize_spec import * -from .v__surf_smooth_heat_07_examples import * -from .v__surf_to_vol_spackle import * -from .v__t1scale import * -from .v__thickness_master import * -from .v__time_diff import * -from .v__to_mni_awarp import * -from .v__to_mni_qwarpar import * -from .v__to_rai import * -from .v__update_afni_binaries import * -from .v__vol_center import * -from .v__xyz_to_ijk import * -from .vecwarp import * -from .waver import * -from .whirlgif import * -from .xmat_tool_py import * diff --git a/python/src/niwrap/afni/abids_json_info_py.py b/python/src/niwrap/afni/abids_json_info_py.py deleted file mode 100644 index c6c9e0185..000000000 --- a/python/src/niwrap/afni/abids_json_info_py.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ABIDS_JSON_INFO_PY_METADATA = Metadata( - id="29b15b0c3b3b92b7936e8e79bd8f79411f0e65a4.boutiques", - name="abids_json_info.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AbidsJsonInfoPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `abids_json_info_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def abids_json_info_py( - json_files: list[InputPathType], - tr_flag: bool = False, - te_flag: bool = False, - te_sec_flag: bool = False, - match_nii_flag: bool = False, - field_list: list[str] | None = None, - list_fields_flag: bool = False, - help_flag: bool = False, - runner: Runner | None = None, -) -> AbidsJsonInfoPyOutputs: - """ - A tool to extract information from BIDS formatted json files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - json_files: Specify .json file(s). - tr_flag: Print the TR from the json file in seconds, from the\ - 'RepetitionTime' field. - te_flag: Print out the 'EchoTime' field in milliseconds (the json file\ - stores it in seconds). - te_sec_flag: Print the 'EchoTime' field in seconds. - match_nii_flag: Check if there is a .nii or .nii.gz file that matches\ - the .json file (1 if the dataset is loadable). - field_list: Print any field or list of fields from the json file. - list_fields_flag: Print a list of the available fields from the .json\ - file. This must be the only argument specified. - help_flag: Show this help message and exit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AbidsJsonInfoPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ABIDS_JSON_INFO_PY_METADATA) - cargs = [] - cargs.append("abids_json_info.py") - cargs.extend([execution.input_file(f) for f in json_files]) - if tr_flag: - cargs.append("-TR") - if te_flag: - cargs.append("-TE") - if te_sec_flag: - cargs.append("-TE_sec") - if match_nii_flag: - cargs.append("-match_nii") - if field_list is not None: - cargs.extend([ - "-field", - *field_list - ]) - if list_fields_flag: - cargs.append("-list_fields") - if help_flag: - cargs.append("-help") - ret = AbidsJsonInfoPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ABIDS_JSON_INFO_PY_METADATA", - "AbidsJsonInfoPyOutputs", - "abids_json_info_py", -] diff --git a/python/src/niwrap/afni/abids_json_tool_py.py b/python/src/niwrap/afni/abids_json_tool_py.py deleted file mode 100644 index d54548f86..000000000 --- a/python/src/niwrap/afni/abids_json_tool_py.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ABIDS_JSON_TOOL_PY_METADATA = Metadata( - id="163838a0b8b6666cb97988dadc53cf5a09505323.boutiques", - name="abids_json_tool.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AbidsJsonToolPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `abids_json_tool_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def abids_json_tool_py( - input_file: InputPathType, - prefix: str, - del_json: str | None = None, - values_stay_str: bool = False, - runner: Runner | None = None, -) -> AbidsJsonToolPyOutputs: - """ - This script helps to manipulate json files in various ways. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: One file to convert. Enter NULL with -add_json to create\ - new json file. - prefix: Output file name. - del_json: Remove attribute (KEY) from the -input json file. - values_stay_str: Each numeric or str item gets saved as a str;\ - otherwise, guess at int and float. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AbidsJsonToolPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ABIDS_JSON_TOOL_PY_METADATA) - cargs = [] - cargs.append("abids_json_tool.py") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-prefix") - cargs.append(prefix) - if del_json is not None: - cargs.extend([ - "-del_json", - del_json - ]) - if values_stay_str: - cargs.append("-values_stay_str") - ret = AbidsJsonToolPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ABIDS_JSON_TOOL_PY_METADATA", - "AbidsJsonToolPyOutputs", - "abids_json_tool_py", -] diff --git a/python/src/niwrap/afni/abids_tool.py b/python/src/niwrap/afni/abids_tool.py deleted file mode 100644 index b353b8fc7..000000000 --- a/python/src/niwrap/afni/abids_tool.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ABIDS_TOOL_METADATA = Metadata( - id="be4cc3dea9c1ff2c94a88b9126da6ad487f347ca.boutiques", - name="abids_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AbidsToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `abids_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def abids_tool( - input_files: list[InputPathType], - copy_prefix: list[str] | None = None, - runner: Runner | None = None, -) -> AbidsToolOutputs: - """ - A tool to work with BIDS formatted datasets created with dcm2niix_afni or - dcm2niix, mainly to pull information from the matching JSON file and refit the - input dataset using 3drefit. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: At least one 3d+time dataset in NIFTI format. - copy_prefix: Copy both the NIFTI dataset(s) and matching .json file(s)\ - to PREFIX. Must have the same number of prefixes as datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AbidsToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ABIDS_TOOL_METADATA) - cargs = [] - cargs.append("abids_tool.py") - cargs.extend([execution.input_file(f) for f in input_files]) - if copy_prefix is not None: - cargs.extend([ - "-copy", - *copy_prefix - ]) - ret = AbidsToolOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ABIDS_TOOL_METADATA", - "AbidsToolOutputs", - "abids_tool", -] diff --git a/python/src/niwrap/afni/adjunct_apqc_tsnr_general.py b/python/src/niwrap/afni/adjunct_apqc_tsnr_general.py deleted file mode 100644 index 342bab5a1..000000000 --- a/python/src/niwrap/afni/adjunct_apqc_tsnr_general.py +++ /dev/null @@ -1,218 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_APQC_TSNR_GENERAL_METADATA = Metadata( - id="a70654cb187bdb9991d41a1bcb7827db58a9c4b0.boutiques", - name="adjunct_apqc_tsnr_general", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctApqcTsnrGeneralOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_apqc_tsnr_general(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def adjunct_apqc_tsnr_general( - montgap: str | None = None, - montcolor: str | None = None, - montx: str | None = None, - monty: str | None = None, - opacity: str | None = None, - blowup: str | None = None, - save_ftype: str | None = None, - set_dicom_xyz: list[str] | None = None, - set_ijk: list[str] | None = None, - set_subbricks: list[str] | None = None, - olay_alpha: str | None = None, - olay_boxed: str | None = None, - thr_olay: str | None = None, - ulay_range_nz: list[str] | None = None, - ulay_range: list[str] | None = None, - delta_slices: list[str] | None = None, - olay_disc_hot_range: list[str] | None = None, - olay_cont_max: str | None = None, - cbar_cont: str | None = None, - no_cor: bool = False, - no_sag: bool = False, - no_axi: bool = False, - echo: bool = False, - runner: Runner | None = None, -) -> AdjunctApqcTsnrGeneralOutputs: - """ - An adjunct program for making TSNR plots for APQC. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - montgap: Specify montage gap. - montcolor: Specify montage color. - montx: Specify montage x coordinate. - monty: Specify montage y coordinate. - opacity: Specify overlay opacity. - blowup: Specify blowup factor. - save_ftype: Specify save file type. - set_dicom_xyz: Set DICOM x, y, z coordinates. - set_ijk: Set IJK coordinates. - set_subbricks: Set sub-bricks. - olay_alpha: Specify overlay alpha. - olay_boxed: Specify boxed overlay. - thr_olay: Specify threshold for overlay. - ulay_range_nz: Specify non-zero range for underlay. - ulay_range: Specify range for underlay. - delta_slices: Specify delta slices. - olay_disc_hot_range: Specify discrete hot range for overlay. - olay_cont_max: Specify continuous max for overlay. - cbar_cont: Specify continuous color bar. - no_cor: No coronal view. - no_sag: No sagittal view. - no_axi: No axial view. - echo: Echo the command line arguments. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctApqcTsnrGeneralOutputs`). - """ - if set_dicom_xyz is not None and not (len(set_dicom_xyz) <= 3): - raise ValueError(f"Length of 'set_dicom_xyz' must be less than 3 but was {len(set_dicom_xyz)}") - if set_ijk is not None and not (len(set_ijk) <= 3): - raise ValueError(f"Length of 'set_ijk' must be less than 3 but was {len(set_ijk)}") - if set_subbricks is not None and not (len(set_subbricks) <= 3): - raise ValueError(f"Length of 'set_subbricks' must be less than 3 but was {len(set_subbricks)}") - if ulay_range_nz is not None and not (len(ulay_range_nz) <= 2): - raise ValueError(f"Length of 'ulay_range_nz' must be less than 2 but was {len(ulay_range_nz)}") - if ulay_range is not None and not (len(ulay_range) <= 2): - raise ValueError(f"Length of 'ulay_range' must be less than 2 but was {len(ulay_range)}") - if delta_slices is not None and not (len(delta_slices) <= 3): - raise ValueError(f"Length of 'delta_slices' must be less than 3 but was {len(delta_slices)}") - if olay_disc_hot_range is not None and not (len(olay_disc_hot_range) <= 2): - raise ValueError(f"Length of 'olay_disc_hot_range' must be less than 2 but was {len(olay_disc_hot_range)}") - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_APQC_TSNR_GENERAL_METADATA) - cargs = [] - cargs.append("adjunct_apqc_tsnr_general") - if montgap is not None: - cargs.extend([ - "-montgap", - montgap - ]) - if montcolor is not None: - cargs.extend([ - "-montcolor", - montcolor - ]) - if montx is not None: - cargs.extend([ - "-montx", - montx - ]) - if monty is not None: - cargs.extend([ - "-monty", - monty - ]) - if opacity is not None: - cargs.extend([ - "-opacity", - opacity - ]) - if blowup is not None: - cargs.extend([ - "-blowup", - blowup - ]) - if save_ftype is not None: - cargs.extend([ - "-save_ftype", - save_ftype - ]) - if set_dicom_xyz is not None: - cargs.extend([ - "-set_dicom_xyz", - *set_dicom_xyz - ]) - if set_ijk is not None: - cargs.extend([ - "-set_ijk", - *set_ijk - ]) - if set_subbricks is not None: - cargs.extend([ - "-set_subbricks", - *set_subbricks - ]) - if olay_alpha is not None: - cargs.extend([ - "-olay_alpha", - olay_alpha - ]) - if olay_boxed is not None: - cargs.extend([ - "-olay_boxed", - olay_boxed - ]) - if thr_olay is not None: - cargs.extend([ - "-thr_olay", - thr_olay - ]) - if ulay_range_nz is not None: - cargs.extend([ - "-ulay_range_nz", - *ulay_range_nz - ]) - if ulay_range is not None: - cargs.extend([ - "-ulay_range", - *ulay_range - ]) - if delta_slices is not None: - cargs.extend([ - "-delta_slices", - *delta_slices - ]) - if olay_disc_hot_range is not None: - cargs.extend([ - "-olay_disc_hot_range", - *olay_disc_hot_range - ]) - if olay_cont_max is not None: - cargs.extend([ - "-olay_cont_max", - olay_cont_max - ]) - if cbar_cont is not None: - cargs.extend([ - "-cbar_cont", - cbar_cont - ]) - if no_cor: - cargs.append("-no_cor") - if no_sag: - cargs.append("-no_sag") - if no_axi: - cargs.append("-no_axi") - if echo: - cargs.append("-echo") - ret = AdjunctApqcTsnrGeneralOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_APQC_TSNR_GENERAL_METADATA", - "AdjunctApqcTsnrGeneralOutputs", - "adjunct_apqc_tsnr_general", -] diff --git a/python/src/niwrap/afni/adjunct_aw_tableize_roi_info_py.py b/python/src/niwrap/afni/adjunct_aw_tableize_roi_info_py.py deleted file mode 100644 index 2e9a68764..000000000 --- a/python/src/niwrap/afni/adjunct_aw_tableize_roi_info_py.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_AW_TABLEIZE_ROI_INFO_PY_METADATA = Metadata( - id="a22785dcd6a5f1a8653a62de11c6b89177cc48a8.boutiques", - name="adjunct_aw_tableize_roi_info.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctAwTableizeRoiInfoPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_aw_tableize_roi_info_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Text file containing ROI count/size information""" - - -def adjunct_aw_tableize_roi_info_py( - output_file: str, - warped_atlas: InputPathType, - warped_mask: InputPathType, - reference_atlas: InputPathType, - reference_mask: InputPathType, - modesmooth_value: float, - runner: Runner | None = None, -) -> AdjunctAwTableizeRoiInfoPyOutputs: - """ - A simple helper function for the fat_proc scripts that generates a text file - containing ROI count/size information based on provided atlases and masks. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_file: Output file name. - warped_atlas: Warped atlas of interest, with subbrick selector if\ - necessary. - warped_mask: Mask for the warped atlas (same grid). - reference_atlas: Reference atlas (unwarped), with subbrick selector if\ - necessary. - reference_mask: Mask for the reference atlas (same grid). - modesmooth_value: Modesmooth value, from modal smoothing used after\ - warping. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctAwTableizeRoiInfoPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_AW_TABLEIZE_ROI_INFO_PY_METADATA) - cargs = [] - cargs.append("adjunct_aw_tableize_roi_info.py") - cargs.append(output_file) - cargs.append(execution.input_file(warped_atlas)) - cargs.append(execution.input_file(warped_mask)) - cargs.append(execution.input_file(reference_atlas)) - cargs.append(execution.input_file(reference_mask)) - cargs.append(str(modesmooth_value)) - ret = AdjunctAwTableizeRoiInfoPyOutputs( - root=execution.output_file("."), - outfile=execution.output_file(output_file), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_AW_TABLEIZE_ROI_INFO_PY_METADATA", - "AdjunctAwTableizeRoiInfoPyOutputs", - "adjunct_aw_tableize_roi_info_py", -] diff --git a/python/src/niwrap/afni/adjunct_calc_mont_dims_py.py b/python/src/niwrap/afni/adjunct_calc_mont_dims_py.py deleted file mode 100644 index 0c7f7716b..000000000 --- a/python/src/niwrap/afni/adjunct_calc_mont_dims_py.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_CALC_MONT_DIMS_PY_METADATA = Metadata( - id="f162a7b77e1f09f79b7724743697de50b8aa20ae.boutiques", - name="adjunct_calc_mont_dims.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctCalcMontDimsPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_calc_mont_dims_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def adjunct_calc_mont_dims_py( - help_: bool = False, - runner: Runner | None = None, -) -> AdjunctCalcMontDimsPyOutputs: - """ - A helper function for the fat_proc* scripts. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - help_: Display help information. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctCalcMontDimsPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_CALC_MONT_DIMS_PY_METADATA) - cargs = [] - cargs.append("adjunct_calc_mont_dims.py") - if help_: - cargs.append("-help") - ret = AdjunctCalcMontDimsPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_CALC_MONT_DIMS_PY_METADATA", - "AdjunctCalcMontDimsPyOutputs", - "adjunct_calc_mont_dims_py", -] diff --git a/python/src/niwrap/afni/adjunct_combine_str_py.py b/python/src/niwrap/afni/adjunct_combine_str_py.py deleted file mode 100644 index 829a24460..000000000 --- a/python/src/niwrap/afni/adjunct_combine_str_py.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_COMBINE_STR_PY_METADATA = Metadata( - id="a45fe06c2fd58fe9e7783f5a93c6f6403e1fcec4.boutiques", - name="adjunct_combine_str.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctCombineStrPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_combine_str_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_selector_file: OutputPathType - """The output file containing the new string selector""" - - -def adjunct_combine_str_py( - output_file: str, - upper_index: float, - string_selectors: list[str], - runner: Runner | None = None, -) -> AdjunctCombineStrPyOutputs: - """ - A simple helper function for fat_proc* scripts that processes string selectors - and outputs a new string selector. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_file: An output file name. - upper_index: An int that is the upper index for the selector (-1 means\ - to use the max number in the input strings). - string_selectors: One or more string selector strings of *goods* to\ - keep. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctCombineStrPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_COMBINE_STR_PY_METADATA) - cargs = [] - cargs.append("adjunct_combine_str.py") - cargs.append(output_file) - cargs.append(str(upper_index)) - cargs.extend(string_selectors) - ret = AdjunctCombineStrPyOutputs( - root=execution.output_file("."), - output_selector_file=execution.output_file(output_file), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_COMBINE_STR_PY_METADATA", - "AdjunctCombineStrPyOutputs", - "adjunct_combine_str_py", -] diff --git a/python/src/niwrap/afni/adjunct_is_label_py.py b/python/src/niwrap/afni/adjunct_is_label_py.py deleted file mode 100644 index bc1fd88f7..000000000 --- a/python/src/niwrap/afni/adjunct_is_label_py.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_IS_LABEL_PY_METADATA = Metadata( - id="3e0e8d04a186b3f9ae56d87ca56ef42ac5b38c81.boutiques", - name="adjunct_is_label.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctIsLabelPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_is_label_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def adjunct_is_label_py( - infile: InputPathType, - label: str, - runner: Runner | None = None, -) -> AdjunctIsLabelPyOutputs: - """ - A subsidiary script of the chauffeur_afni suite for label functionalities. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file for the adjunct_is_label script. - label: Output label generated by the script. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctIsLabelPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_IS_LABEL_PY_METADATA) - cargs = [] - cargs.append("adjunct_is_label.py") - cargs.append(execution.input_file(infile)) - cargs.append(label) - ret = AdjunctIsLabelPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_IS_LABEL_PY_METADATA", - "AdjunctIsLabelPyOutputs", - "adjunct_is_label_py", -] diff --git a/python/src/niwrap/afni/adjunct_make_script_and_rst_py.py b/python/src/niwrap/afni/adjunct_make_script_and_rst_py.py deleted file mode 100644 index e69867d49..000000000 --- a/python/src/niwrap/afni/adjunct_make_script_and_rst_py.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_MAKE_SCRIPT_AND_RST_PY_METADATA = Metadata( - id="daadacfd82293995379763ced20e0264a0572dbb.boutiques", - name="adjunct_make_script_and_rst.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctMakeScriptAndRstPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_make_script_and_rst_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - rst_file: OutputPathType - """Generated RST documentation file.""" - script_file: OutputPathType - """Generated script file.""" - output_directory: OutputPathType - """Output directory in Sphinx tree.""" - - -def adjunct_make_script_and_rst_py( - input_script: InputPathType, - prefix_rst: str, - prefix_script: str, - reflink: str, - execute_script: bool = False, - runner: Runner | None = None, -) -> AdjunctMakeScriptAndRstPyOutputs: - """ - Program to take a script with some special markup and turn it into both an RST - page and a script for the online Sphinx documentation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_script: Input script file with special markup. - prefix_rst: Output filename including any path of the RST/Sphinx file.\ - Must include file extension '.rst'. - prefix_script: Output filename of the script file. Should include file\ - extension such as '.tcsh'. - reflink: A string tag that will serve as the subdirectory name holding\ - images for the given demo, and the RST internal reference label. - execute_script: Flag to create the RST and script files, and also\ - execute the script. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctMakeScriptAndRstPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_MAKE_SCRIPT_AND_RST_PY_METADATA) - cargs = [] - cargs.append("adjunct_make_script_and_rst.py") - cargs.append("--input") - cargs.append(execution.input_file(input_script)) - cargs.append("--prefix_rst") - cargs.extend([ - "--prefix_rst", - prefix_rst - ]) - cargs.append("--prefix_script") - cargs.extend([ - "--prefix_script", - prefix_script - ]) - cargs.append("--reflink") - cargs.extend([ - "--reflink", - reflink - ]) - if execute_script: - cargs.append("--execute_script") - ret = AdjunctMakeScriptAndRstPyOutputs( - root=execution.output_file("."), - rst_file=execution.output_file(prefix_rst), - script_file=execution.output_file(prefix_script), - output_directory=execution.output_file(prefix_rst + "/media/" + reflink), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_MAKE_SCRIPT_AND_RST_PY_METADATA", - "AdjunctMakeScriptAndRstPyOutputs", - "adjunct_make_script_and_rst_py", -] diff --git a/python/src/niwrap/afni/adjunct_select_str_py.py b/python/src/niwrap/afni/adjunct_select_str_py.py deleted file mode 100644 index 986bd6e22..000000000 --- a/python/src/niwrap/afni/adjunct_select_str_py.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_SELECT_STR_PY_METADATA = Metadata( - id="51bd0c93e4c33858ebe75938263e1d88647851a7.boutiques", - name="adjunct_select_str.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctSelectStrPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_select_str_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def adjunct_select_str_py( - input_file: InputPathType, - num_bricks: float, - output_file: str, - runner: Runner | None = None, -) -> AdjunctSelectStrPyOutputs: - """ - A simple helper function for the fat_proc* scripts. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: File containing a list of integers. - num_bricks: The number N of bricks in the dataset (so max index is N-1). - output_file: Output file name. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctSelectStrPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_SELECT_STR_PY_METADATA) - cargs = [] - cargs.append("adjunct_select_str.py") - cargs.append(execution.input_file(input_file)) - cargs.append(str(num_bricks)) - cargs.append(output_file) - ret = AdjunctSelectStrPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_SELECT_STR_PY_METADATA", - "AdjunctSelectStrPyOutputs", - "adjunct_select_str_py", -] diff --git a/python/src/niwrap/afni/adjunct_simplify_cost.py b/python/src/niwrap/afni/adjunct_simplify_cost.py deleted file mode 100644 index 2cc3092dc..000000000 --- a/python/src/niwrap/afni/adjunct_simplify_cost.py +++ /dev/null @@ -1,58 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_SIMPLIFY_COST_METADATA = Metadata( - id="0291c293f6b2eaf6626f15fdc0c7c7079ef500e7.boutiques", - name="adjunct_simplify_cost", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctSimplifyCostOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_simplify_cost(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def adjunct_simplify_cost( - cost_function: str, - runner: Runner | None = None, -) -> AdjunctSimplifyCostOutputs: - """ - Simplifies a cost function name by removing the '+' and anything following it. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - cost_function: The cost function name to be simplified. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctSimplifyCostOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_SIMPLIFY_COST_METADATA) - cargs = [] - cargs.append("adjunct_simplify_cost.py") - cargs.append(cost_function) - ret = AdjunctSimplifyCostOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_SIMPLIFY_COST_METADATA", - "AdjunctSimplifyCostOutputs", - "adjunct_simplify_cost", -] diff --git a/python/src/niwrap/afni/adjunct_suma_fs_mask_and_qc.py b/python/src/niwrap/afni/adjunct_suma_fs_mask_and_qc.py deleted file mode 100644 index 3109c5cfe..000000000 --- a/python/src/niwrap/afni/adjunct_suma_fs_mask_and_qc.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_SUMA_FS_MASK_AND_QC_METADATA = Metadata( - id="9044663584933a336f19e159c18976b332d51c34.boutiques", - name="adjunct_suma_fs_mask_and_qc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctSumaFsMaskAndQcOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_suma_fs_mask_and_qc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - fs_parc_wb_mask: OutputPathType - """Whole brain mask based on the FS parcellation created by this script.""" - qc_image_00: OutputPathType - """QC image with overlay of brainmask.nii* volume in red and parcellated - subset in black.""" - qc_image_01: OutputPathType - """QC image with overlay of fs_parc_wb_mask.nii.gz.""" - qc_image_02: OutputPathType - """QC image with overlay of tissue segmentations.""" - qc_image_03: OutputPathType - """QC image with overlay of GM.""" - qc_image_04: OutputPathType - """QC image with overlay of WM.""" - qc_image_05: OutputPathType - """QC image with overlay of "2000" atlas parcellation.""" - - -def adjunct_suma_fs_mask_and_qc( - subj_id: str, - suma_dir: str, - no_clean: bool = False, - help_: bool = False, - hview: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> AdjunctSumaFsMaskAndQcOutputs: - """ - Script for quickly making some QC images for the SUMA/ directory created by - @SUMA_Make_Spec_FS after running FreeSurfer's recon-all. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subj_id: Subject ID. - suma_dir: SUMA/ directory output by AFNI's @SUMA_Make_Spec_FS. - no_clean: Do not remove temporary working subdirectory (default: remove\ - it). - help_: Show help. - hview: Show help in text editor. - version: Show version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctSumaFsMaskAndQcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_SUMA_FS_MASK_AND_QC_METADATA) - cargs = [] - cargs.append("adjunct_suma_fs_mask_and_qc") - cargs.append("-sid") - cargs.append(subj_id) - cargs.append("-suma_dir") - cargs.append(suma_dir) - if no_clean: - cargs.append("-no_clean") - if help_: - cargs.append("-help") - if hview: - cargs.append("-hview") - if version: - cargs.append("-ver") - ret = AdjunctSumaFsMaskAndQcOutputs( - root=execution.output_file("."), - fs_parc_wb_mask=execution.output_file("SUMA/fs_parc_wb_mask.nii.gz"), - qc_image_00=execution.output_file("SUMA/qc_00*.jpg"), - qc_image_01=execution.output_file("SUMA/qc_01*.jpg"), - qc_image_02=execution.output_file("SUMA/qc_02*.jpg"), - qc_image_03=execution.output_file("SUMA/qc_03*.jpg"), - qc_image_04=execution.output_file("SUMA/qc_04*.jpg"), - qc_image_05=execution.output_file("SUMA/qc_05*.jpg"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_SUMA_FS_MASK_AND_QC_METADATA", - "AdjunctSumaFsMaskAndQcOutputs", - "adjunct_suma_fs_mask_and_qc", -] diff --git a/python/src/niwrap/afni/adjunct_suma_fs_roi_info.py b/python/src/niwrap/afni/adjunct_suma_fs_roi_info.py deleted file mode 100644 index f1e55b285..000000000 --- a/python/src/niwrap/afni/adjunct_suma_fs_roi_info.py +++ /dev/null @@ -1,92 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_SUMA_FS_ROI_INFO_METADATA = Metadata( - id="88ddfb0a9b419a5d6b16e3d7b3d95644d89bfd80.boutiques", - name="adjunct_suma_fs_roi_info", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctSumaFsRoiInfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_suma_fs_roi_info(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - rois_2000_ft: OutputPathType - """Info for the '2000' parcellation.""" - rois_2009_ft: OutputPathType - """Info for the '2009' parcellation.""" - segs_2000_ft: OutputPathType - """Info for the '2000' parcellation brain mask and tissue/segmentations.""" - segs_2009_ft: OutputPathType - """Info for the '2009' parcellation brain mask and tissue/segmentations.""" - - -def adjunct_suma_fs_roi_info( - subject_id: str, - suma_directory: str, - help_: bool = False, - hview: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> AdjunctSumaFsRoiInfoOutputs: - """ - Script for making ROI stats for the SUMA/ directory created by - @SUMA_Make_Spec_FS after running FreeSurfer's recon-all. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subject_id: Subject ID. - suma_directory: SUMA directory output by AFNI's @SUMA_Make_Spec_FS. - help_: Show help. - hview: Show help in text editor. - version: Show version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctSumaFsRoiInfoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_SUMA_FS_ROI_INFO_METADATA) - cargs = [] - cargs.append("adjunct_suma_fs_roi_info") - cargs.extend([ - "-sid", - subject_id - ]) - cargs.extend([ - "-suma_dir", - suma_directory - ]) - if help_: - cargs.append("-help") - if hview: - cargs.append("-hview") - if version: - cargs.append("-ver") - ret = AdjunctSumaFsRoiInfoOutputs( - root=execution.output_file("."), - rois_2000_ft=execution.output_file("stats_fs_rois_2000_FT.1D"), - rois_2009_ft=execution.output_file("stats_fs_rois_2009_FT.1D"), - segs_2000_ft=execution.output_file("stats_fs_segs_2000_FT.1D"), - segs_2009_ft=execution.output_file("stats_fs_segs_2009_FT.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_SUMA_FS_ROI_INFO_METADATA", - "AdjunctSumaFsRoiInfoOutputs", - "adjunct_suma_fs_roi_info", -] diff --git a/python/src/niwrap/afni/adjunct_tort_plot_dp_align.py b/python/src/niwrap/afni/adjunct_tort_plot_dp_align.py deleted file mode 100644 index 4e0eef155..000000000 --- a/python/src/niwrap/afni/adjunct_tort_plot_dp_align.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADJUNCT_TORT_PLOT_DP_ALIGN_METADATA = Metadata( - id="e97404ae1ad4852f95795d417d56b26d0b94534a.boutiques", - name="adjunct_tort_plot_dp_align", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdjunctTortPlotDpAlignOutputs(typing.NamedTuple): - """ - Output object returned when calling `adjunct_tort_plot_dp_align(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - align_params: OutputPathType - """Text file containing 6 columns of data for the rigid-body alignment - parameters estimated by DIFFPREP.""" - enorm_file: OutputPathType - """Text file with 1 column of data, the Euclidean norm of the differences of - the rigid body alignment parameters.""" - plot_jpg: OutputPathType - """A plot of enorm and the alignment parameters in JPG format.""" - plot_svg: OutputPathType - """A plot of enorm and the alignment parameters in SVG format.""" - - -def adjunct_tort_plot_dp_align( - input_file: InputPathType, - output_prefix: str, - enorm_max: float | None = None, - enorm_hline: float | None = None, - no_svg: bool = False, - runner: Runner | None = None, -) -> AdjunctTortPlotDpAlignOutputs: - """ - Tool to display the rigid-body alignment parameters from TORTOISE's DIFFPREP, - useful for analyzing subject motion in DWI data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Name of DIFFPREP-produced file to parse, probably ending in\ - '_transformations.txt'. - output_prefix: Base of output files; can contain path information.\ - Should *not* include any extension. - enorm_max: Specify max value of y-axis of enorm plot in SVG image.\ - Useful for having a constant value across a study. - enorm_hline: Specify value of a horizontal, dotted, bright cyan line\ - for the enorm plot in SVG image. Can help with visualization. - no_svg: Opt to turn off even checking to plot an SVG version of the\ - figure. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdjunctTortPlotDpAlignOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADJUNCT_TORT_PLOT_DP_ALIGN_METADATA) - cargs = [] - cargs.append("adjunct_tort_plot_dp_align") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-prefix") - cargs.append(output_prefix) - cargs.append("-enorm_max") - if enorm_max is not None: - cargs.append(str(enorm_max)) - cargs.append("-enorm_hline") - if enorm_hline is not None: - cargs.append(str(enorm_hline)) - if no_svg: - cargs.append("-no_svg") - ret = AdjunctTortPlotDpAlignOutputs( - root=execution.output_file("."), - align_params=execution.output_file(output_prefix + "_align.1D"), - enorm_file=execution.output_file(output_prefix + "_enorm.1D"), - plot_jpg=execution.output_file(output_prefix + ".jpg"), - plot_svg=execution.output_file(output_prefix + ".svg"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADJUNCT_TORT_PLOT_DP_ALIGN_METADATA", - "AdjunctTortPlotDpAlignOutputs", - "adjunct_tort_plot_dp_align", -] diff --git a/python/src/niwrap/afni/adwarp.py b/python/src/niwrap/afni/adwarp.py deleted file mode 100644 index 088957c59..000000000 --- a/python/src/niwrap/afni/adwarp.py +++ /dev/null @@ -1,126 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADWARP_METADATA = Metadata( - id="22410e65c1361d9cb6b13a0fd56cc72bae69129b.boutiques", - name="adwarp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AdwarpOutputs(typing.NamedTuple): - """ - Output object returned when calling `adwarp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - header_output: OutputPathType | None - """Output dataset header file""" - brick_output: OutputPathType | None - """Output dataset brick file""" - - -def adwarp( - apar: InputPathType, - dpar: str, - prefix: str | None = None, - dxyz: float | None = None, - verbose: bool = False, - force: bool = False, - resam: str | None = None, - thr: str | None = None, - func: str | None = None, - runner: Runner | None = None, -) -> AdwarpOutputs: - """ - Resamples a 'data parent' dataset to the grid defined by an 'anat parent' - dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - apar: Set the anat parent dataset (nonoptional). - dpar: Set the data parent dataset (nonoptional). dset may contain a\ - sub-brick selector, e.g., -dpar 'dset+orig[2,5,7]'. - prefix: Set the prefix for the output dataset. Default is the prefix of\ - 'dset'. - dxyz: Set the grid spacing in the output dataset. Default is 1 mm. - verbose: Print out progress reports. - force: Write out result even if it means deleting an existing dataset.\ - Default is not to overwrite. - resam: Set resampling mode for all sub-bricks. Modes: NN (Nearest\ - Neighbor), Li (Linear Interpolation), Cu (Cubic Interpolation), Bk\ - (Blocky Interpolation). Default is Li for all sub-bricks. - thr: Set resampling mode for threshold sub-bricks. Modes: NN (Nearest\ - Neighbor), Li (Linear Interpolation), Cu (Cubic Interpolation), Bk\ - (Blocky Interpolation). - func: Set resampling mode for functional sub-bricks. Modes: NN (Nearest\ - Neighbor), Li (Linear Interpolation), Cu (Cubic Interpolation), Bk\ - (Blocky Interpolation). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AdwarpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADWARP_METADATA) - cargs = [] - cargs.append("adwarp") - cargs.extend([ - "-apar", - execution.input_file(apar) - ]) - cargs.extend([ - "-dpar", - dpar - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if dxyz is not None: - cargs.extend([ - "-dxyz", - str(dxyz) - ]) - if verbose: - cargs.append("-verbose") - if force: - cargs.append("-force") - if resam is not None: - cargs.extend([ - "-resam", - resam - ]) - if thr is not None: - cargs.extend([ - "-thr", - thr - ]) - if func is not None: - cargs.extend([ - "-func", - func - ]) - ret = AdwarpOutputs( - root=execution.output_file("."), - header_output=execution.output_file(prefix + ".HEAD") if (prefix is not None) else None, - brick_output=execution.output_file(prefix + ".BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADWARP_METADATA", - "AdwarpOutputs", - "adwarp", -] diff --git a/python/src/niwrap/afni/afni.py b/python/src/niwrap/afni/afni.py deleted file mode 100644 index 521b76d68..000000000 --- a/python/src/niwrap/afni/afni.py +++ /dev/null @@ -1,183 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_METADATA = Metadata( - id="40dab3442f2e18227072a94a9827898d65dc4372.boutiques", - name="afni", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - session_output: OutputPathType - """Output file for the session data""" - - -def afni_( - session_directories: str | None = None, - bysub: list[str] | None = None, - all_dsets: bool = False, - purge: bool = False, - posfunc: bool = False, - recursive: bool = False, - no1_d: bool = False, - nocsv: bool = False, - notsv: bool = False, - unique: bool = False, - orient: str | None = None, - noplugins: bool = False, - seehidden: bool = False, - allow_all_plugins: bool = False, - yesplugouts: bool = False, - debug_plugouts: bool = False, - noplugouts: bool = False, - skip_afnirc: bool = False, - layout: InputPathType | None = None, - niml: bool = False, - np: int | None = None, - npq: int | None = None, - npb: int | None = None, - com: str | None = None, - comsep: str | None = None, - runner: Runner | None = None, -) -> AfniOutputs: - """ - Tool for reading in sessions of 3D datasets and visualizing them. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - session_directories: Input session directories containing the datasets. - bysub: Gather all datasets corresponding to a single subject identifier. - all_dsets: Read in all datasets from all listed folders together. - purge: Conserve memory by purging unused datasets. - posfunc: Start up the color 'pbar' to use only positive function values. - recursive: Recursively search each session_directory for more session\ - subdirectories. - no1_d: Tells AFNI not to read *.1D timeseries files. - nocsv: Tells AFNI not to read *.csv files. - notsv: Tells AFNI not to read *.tsv files. - unique: Create a unique set of colors for each AFNI controller window. - orient: Orientation code for displaying x-y-z coordinates. - noplugins: Do not load plugins. - seehidden: Show hidden plugins. - allow_all_plugins: Do not hide plugins. - yesplugouts: Listen for plugouts. - debug_plugouts: Plugout code prints lots of messages (for debugging). - noplugouts: Do not listen for plugouts. - skip_afnirc: Do not read .afnirc file. - layout: Read initial windows layout from a file. - niml: Turn on listening for NIML-formatted data from SUMA. - np: Provide a port offset for multiple instances. - npq: Like -np but quieter in case of errors. - npb: Provide a block of port numbers. - com: Specify command strings to drive AFNI on startup. - comsep: Character to use as a separator for commands. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_METADATA) - cargs = [] - cargs.append("afni") - if session_directories is not None: - cargs.append(session_directories) - if bysub is not None: - cargs.extend([ - "-bysub", - *bysub - ]) - if all_dsets: - cargs.append("-all_dsets") - if purge: - cargs.append("-purge") - if posfunc: - cargs.append("-posfunc") - if recursive: - cargs.append("-R") - if no1_d: - cargs.append("-no1D") - if nocsv: - cargs.append("-nocsv") - if notsv: - cargs.append("-notsv") - if unique: - cargs.append("-unique") - if orient is not None: - cargs.extend([ - "-orient", - orient - ]) - if noplugins: - cargs.append("-noplugins") - if seehidden: - cargs.append("-seehidden") - if allow_all_plugins: - cargs.append("-DAFNI_ALLOW_ALL_PLUGINS=YES") - if yesplugouts: - cargs.append("-yesplugouts") - if debug_plugouts: - cargs.append("-YESplugouts") - if noplugouts: - cargs.append("-noplugouts") - if skip_afnirc: - cargs.append("-skip_afnirc") - if layout is not None: - cargs.extend([ - "-layout", - execution.input_file(layout) - ]) - if niml: - cargs.append("-niml") - if np is not None: - cargs.extend([ - "-np", - str(np) - ]) - if npq is not None: - cargs.extend([ - "-npq", - str(npq) - ]) - if npb is not None: - cargs.extend([ - "-npb", - str(npb) - ]) - if com is not None: - cargs.extend([ - "-com", - com - ]) - if comsep is not None: - cargs.extend([ - "-comsep", - comsep - ]) - ret = AfniOutputs( - root=execution.output_file("."), - session_output=execution.output_file("output_session.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_METADATA", - "AfniOutputs", - "afni_", -] diff --git a/python/src/niwrap/afni/afni_batch_r.py b/python/src/niwrap/afni/afni_batch_r.py deleted file mode 100644 index 5ce5a311d..000000000 --- a/python/src/niwrap/afni/afni_batch_r.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_BATCH_R_METADATA = Metadata( - id="e896a78243318c296dc1ffb8231df6aaa614c0da.boutiques", - name="AFNI_Batch_R", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniBatchROutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_batch_r(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_batch_r( - no_restore: bool = False, - save_workspace: bool = False, - no_readline: bool = False, - vanilla_mode: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> AfniBatchROutputs: - """ - Batch mode for executing R scripts in the AFNI environment. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - no_restore: Do not restore anything in the R workspace at startup. - save_workspace: Save the workspace at the end of the script execution. - no_readline: Disable reading input from the command line. - vanilla_mode: Run R without saving the workspace at the end, restoring\ - anything, reading the site file, or acting on startup files. - help_: Display this help message and exit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniBatchROutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_BATCH_R_METADATA) - cargs = [] - cargs.append("AFNI_Batch_R") - cargs.append("R") - cargs.append("CMD") - cargs.append("BATCH") - if no_restore: - cargs.append("--no-restore") - if save_workspace: - cargs.append("--save") - if no_readline: - cargs.append("--no-readline") - if vanilla_mode: - cargs.append("--vanilla") - cargs.append("--args") - if help_: - cargs.append("-help") - ret = AfniBatchROutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_BATCH_R_METADATA", - "AfniBatchROutputs", - "afni_batch_r", -] diff --git a/python/src/niwrap/afni/afni_check_omp.py b/python/src/niwrap/afni/afni_check_omp.py deleted file mode 100644 index e20428929..000000000 --- a/python/src/niwrap/afni/afni_check_omp.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_CHECK_OMP_METADATA = Metadata( - id="6453e60521723604a0b8ebb13d5840014b923b27.boutiques", - name="afni_check_omp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniCheckOmpOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_check_omp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_check_omp( - iterations: float | None = None, - runner: Runner | None = None, -) -> AfniCheckOmpOutputs: - """ - Tool to check the OpenMP multi-threading environment for AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - iterations: Number of iterations to run. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniCheckOmpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_CHECK_OMP_METADATA) - cargs = [] - cargs.append("afni_check_omp") - if iterations is not None: - cargs.append(str(iterations)) - ret = AfniCheckOmpOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_CHECK_OMP_METADATA", - "AfniCheckOmpOutputs", - "afni_check_omp", -] diff --git a/python/src/niwrap/afni/afni_history.py b/python/src/niwrap/afni/afni_history.py deleted file mode 100644 index 1f56c8bbe..000000000 --- a/python/src/niwrap/afni/afni_history.py +++ /dev/null @@ -1,187 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_HISTORY_METADATA = Metadata( - id="edc666d49dee4472b0b1cf696b099e8783b9115e.boutiques", - name="afni_history", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniHistoryOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_history(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_history( - verb_level: int | None = None, - check_date: str | None = None, - help_: bool = False, - history: bool = False, - list_authors: bool = False, - list_types: bool = False, - version: bool = False, - author: str | None = None, - level: int | None = None, - min_level: int | None = None, - program: str | None = None, - past_entries: int | None = None, - past_days: int | None = None, - past_months: int | None = None, - past_years: int | None = None, - type_: str | None = None, - html_: bool = False, - dline: bool = False, - reverse: bool = False, - show_field: str | None = None, - show_field_names: bool = False, - runner: Runner | None = None, -) -> AfniHistoryOutputs: - """ - Show AFNI updates per user, dates, or levels. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - verb_level: Request verbose output (LEVEL is from 0-6). - check_date: Check history against given date. If most recent\ - afni_history is older than the passed date, the distribution version\ - might be considered out of date. - help_: Show help information. - history: Show this program's history. - list_authors: Show the list of valid authors. - list_types: Show the list of valid change types. - version: Show this program's version. - author: Restrict output to the given author. - level: Restrict output to the given level. - min_level: Restrict output to at least level LEVEL. - program: Restrict output to the given program. - past_entries: Restrict output to final ENTRIES entries. - past_days: Restrict output to the past DAYS days. - past_months: Restrict output to the past MONTHS months. - past_years: Restrict output to the past YEARS years. - type_: Restrict output to the given TYPE (TYPE = 0..5, or strings\ - 'NEW_PROG', etc.). - html_: Add HTML formatting. - dline: Put a divider line between dates. - reverse: Reverse the sorting order (sort is by date, author, level,\ - program). - show_field: Restrict entry output to field FIELD. Valid FIELDs include:\ - all, firstline, day, month, year, date, author, program, level, type,\ - desc, verbtext. - show_field_names: List valid FIELD names for -show_field. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniHistoryOutputs`). - """ - if verb_level is not None and not (0 <= verb_level <= 6): - raise ValueError(f"'verb_level' must be between 0 <= x <= 6 but was {verb_level}") - if level is not None and not (1 <= level <= 5): - raise ValueError(f"'level' must be between 1 <= x <= 5 but was {level}") - if min_level is not None and not (1 <= min_level <= 5): - raise ValueError(f"'min_level' must be between 1 <= x <= 5 but was {min_level}") - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_HISTORY_METADATA) - cargs = [] - cargs.append("afni_history") - if verb_level is not None: - cargs.extend([ - "-verb", - str(verb_level) - ]) - if check_date is not None: - cargs.extend([ - "-check_date", - check_date - ]) - if help_: - cargs.append("-help") - if history: - cargs.append("-hist") - if list_authors: - cargs.append("-list_authors") - if list_types: - cargs.append("-list_types") - if version: - cargs.append("-ver") - if author is not None: - cargs.extend([ - "-author", - author - ]) - if level is not None: - cargs.extend([ - "-level", - str(level) - ]) - if min_level is not None: - cargs.extend([ - "-min_level", - str(min_level) - ]) - if program is not None: - cargs.extend([ - "-program", - program - ]) - if past_entries is not None: - cargs.extend([ - "-past_entries", - str(past_entries) - ]) - if past_days is not None: - cargs.extend([ - "-past_days", - str(past_days) - ]) - if past_months is not None: - cargs.extend([ - "-past_months", - str(past_months) - ]) - if past_years is not None: - cargs.extend([ - "-past_years", - str(past_years) - ]) - if type_ is not None: - cargs.extend([ - "-type", - type_ - ]) - if html_: - cargs.append("-html") - if dline: - cargs.append("-dline") - if reverse: - cargs.append("-reverse") - if show_field is not None: - cargs.extend([ - "-show_field", - show_field - ]) - if show_field_names: - cargs.append("-show_field_names") - ret = AfniHistoryOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_HISTORY_METADATA", - "AfniHistoryOutputs", - "afni_history", -] diff --git a/python/src/niwrap/afni/afni_open.py b/python/src/niwrap/afni/afni_open.py deleted file mode 100644 index 216527ff4..000000000 --- a/python/src/niwrap/afni/afni_open.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_OPEN_METADATA = Metadata( - id="011cf64aad17ae870a6340e6c6714d18cd8c6e43.boutiques", - name="afni_open", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniOpenOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_open(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_open( - files: list[InputPathType], - method: str | None = None, - editor: bool = False, - downloader: bool = False, - examinexmat: bool = False, - browser: bool = False, - readme: bool = False, - afniweb: bool = False, - global_help: bool = False, - gopts_help: bool = False, - help_: bool = False, - mini_help: bool = False, - extreme_help: bool = False, - h_view: bool = False, - h_web: bool = False, - runner: Runner | None = None, -) -> AfniOpenOutputs: - """ - A program to open various AFNI/SUMA files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: Input file(s) to be opened. - method: Method to open files (editor, downloader, browser, afni, suma,\ - 1dplot, ExamineXmat, iviewer, afniweb, readme). - editor: Same as -w editor. - downloader: Same as -w downloader. - examinexmat: Same as -w ExamineXmat. - browser: Same as -w browser. - readme: Same as -w readme. - afniweb: Same as -w afniweb. - global_help: Show help for global options. - gopts_help: Show help for global options. - help_: The entire help output. - mini_help: Mini help. - extreme_help: Extreme help. - h_view: Open help in text editor. - h_web: Open help in web browser. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniOpenOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_OPEN_METADATA) - cargs = [] - cargs.append("afni_open") - cargs.extend([execution.input_file(f) for f in files]) - if method is not None: - cargs.extend([ - "-w", - method - ]) - if editor: - cargs.append("-e") - if downloader: - cargs.append("-d") - if examinexmat: - cargs.append("-x") - if browser: - cargs.append("-b") - if readme: - cargs.append("-r") - if afniweb: - cargs.append("-aw") - if global_help: - cargs.append("-global_help") - if gopts_help: - cargs.append("-gopts_help") - if help_: - cargs.append("-help") - if mini_help: - cargs.append("-h") - if extreme_help: - cargs.append("-HELP") - if h_view: - cargs.append("-h_view") - if h_web: - cargs.append("-h_web") - ret = AfniOpenOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_OPEN_METADATA", - "AfniOpenOutputs", - "afni_open", -] diff --git a/python/src/niwrap/afni/afni_proc_py.py b/python/src/niwrap/afni/afni_proc_py.py deleted file mode 100644 index f67914d90..000000000 --- a/python/src/niwrap/afni/afni_proc_py.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_PROC_PY_METADATA = Metadata( - id="8fefd4e99e329e9d8b01b6efcda3bcc2c4a10756.boutiques", - name="afni_proc.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniProcPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_proc_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType | None - """All output files stored in the specified output directory.""" - - -def afni_proc_py( - dsets: list[InputPathType], - subj_id: str, - anat: InputPathType, - out_dir: str | None = None, - blocks: list[str] | None = None, - echo_times: list[float] | None = None, - stim_times: list[InputPathType] | None = None, - stim_files: list[InputPathType] | None = None, - copy_files: list[InputPathType] | None = None, - copy_anat: InputPathType | None = None, - regress_params: list[str] | None = None, - runner: Runner | None = None, -) -> AfniProcPyOutputs: - """ - Generate a tcsh script for an AFNI single subject processing stream. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dsets: Specify the EPI dataset files. (e.g. epi_run1+orig,\ - epi_run2+orig). - subj_id: Specify the subject ID for the script. - anat: Specify the anatomical dataset. - out_dir: Specify the output directory for the script. - blocks: Specify the processing blocks to apply (e.g. tshift volreg blur\ - mask scale regress). - echo_times: Specify echo times for multi-echo data processing. - stim_times: Specify files used for stimulus timing in -stim_times. - stim_files: Specify TR-locked stim files for 3dDeconvolve -stim_file\ - instead of -stim_times. - copy_files: Specify additional files to be copied to the results\ - directory. - copy_anat: Copy the anatomical dataset(s) to the results directory. - regress_params: Specify extra options for 3dDeconvolve. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniProcPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_PROC_PY_METADATA) - cargs = [] - cargs.append("afni_proc.py") - cargs.extend([execution.input_file(f) for f in dsets]) - cargs.append(subj_id) - if out_dir is not None: - cargs.append(out_dir) - if blocks is not None: - cargs.extend(blocks) - cargs.append(execution.input_file(anat)) - if echo_times is not None: - cargs.extend(map(str, echo_times)) - if stim_times is not None: - cargs.extend([execution.input_file(f) for f in stim_times]) - if stim_files is not None: - cargs.extend([execution.input_file(f) for f in stim_files]) - if copy_files is not None: - cargs.extend([execution.input_file(f) for f in copy_files]) - if copy_anat is not None: - cargs.append(execution.input_file(copy_anat)) - if regress_params is not None: - cargs.extend([ - "-regress_opts_3dD", - *regress_params - ]) - ret = AfniProcPyOutputs( - root=execution.output_file("."), - output_files=execution.output_file(out_dir + "/*") if (out_dir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_PROC_PY_METADATA", - "AfniProcPyOutputs", - "afni_proc_py", -] diff --git a/python/src/niwrap/afni/afni_run_r.py b/python/src/niwrap/afni/afni_run_r.py deleted file mode 100644 index 610fd43e7..000000000 --- a/python/src/niwrap/afni/afni_run_r.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_RUN_R_METADATA = Metadata( - id="c25de8aaab9b4faa0067fa6c9d3361eb1f13f7bf.boutiques", - name="afni_run_R", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniRunROutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_run_r(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_run_r( - r_script: InputPathType, - r_args: list[str], - runner: Runner | None = None, -) -> AfniRunROutputs: - """ - Run an R script with the specified arguments. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - r_script: R script to be executed. - r_args: Arguments to be passed to the R script. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniRunROutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_RUN_R_METADATA) - cargs = [] - cargs.append("afni_run_R") - cargs.append(execution.input_file(r_script)) - cargs.extend(r_args) - ret = AfniRunROutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_RUN_R_METADATA", - "AfniRunROutputs", - "afni_run_r", -] diff --git a/python/src/niwrap/afni/afni_system_check_py.py b/python/src/niwrap/afni/afni_system_check_py.py deleted file mode 100644 index e308dd05b..000000000 --- a/python/src/niwrap/afni/afni_system_check_py.py +++ /dev/null @@ -1,110 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AFNI_SYSTEM_CHECK_PY_METADATA = Metadata( - id="707dd8a3faf114c94899a8373ea46705cdf40480.boutiques", - name="afni_system_check.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AfniSystemCheckPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `afni_system_check_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def afni_system_check_py( - check_all: bool = False, - find_prog: str | None = None, - exact: str | None = None, - disp_num_cpu: bool = False, - disp_ver_matplotlib: bool = False, - dot_file_list: bool = False, - dot_file_show: bool = False, - dot_file_pack: str | None = None, - casematch: str | None = None, - data_root: str | None = None, - runner: Runner | None = None, -) -> AfniSystemCheckPyOutputs: - """ - Perform various system checks for figuring out AFNI installation issues. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - check_all: Perform all system checks. - find_prog: Search PATH for PROG. - exact: Search for PROG without wildcards in -find_prog. - disp_num_cpu: Display number of CPUs available. - disp_ver_matplotlib: Display matplotlib version (else 'None'). - dot_file_list: List all found dot files (startup files). - dot_file_show: Display contents of all found dot files. - dot_file_pack: Create a NAME.tgz package containing dot files. - casematch: Match case in -find_prog. - data_root: Search for class data under DDIR. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AfniSystemCheckPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AFNI_SYSTEM_CHECK_PY_METADATA) - cargs = [] - cargs.append("afni_system_check.py") - if check_all: - cargs.append("-check_all") - if find_prog is not None: - cargs.extend([ - "-find_prog", - find_prog - ]) - if exact is not None: - cargs.extend([ - "-exact", - exact - ]) - if disp_num_cpu: - cargs.append("-disp_num_cpu") - if disp_ver_matplotlib: - cargs.append("-disp_ver_matplotlib") - if dot_file_list: - cargs.append("-dot_file_list") - if dot_file_show: - cargs.append("-dot_file_show") - if dot_file_pack is not None: - cargs.extend([ - "-dot_file_pack", - dot_file_pack - ]) - if casematch is not None: - cargs.extend([ - "-casematch", - casematch - ]) - if data_root is not None: - cargs.extend([ - "-data_root", - data_root - ]) - ret = AfniSystemCheckPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AFNI_SYSTEM_CHECK_PY_METADATA", - "AfniSystemCheckPyOutputs", - "afni_system_check_py", -] diff --git a/python/src/niwrap/afni/aiv.py b/python/src/niwrap/afni/aiv.py deleted file mode 100644 index 2c5e32419..000000000 --- a/python/src/niwrap/afni/aiv.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AIV_METADATA = Metadata( - id="f1e32a1eded3e5ce036f0f095565af93c241ab76.boutiques", - name="aiv", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AivOutputs(typing.NamedTuple): - """ - Output object returned when calling `aiv(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def aiv( - input_images: list[InputPathType], - verbose: bool = False, - quiet: bool = False, - title: str | None = None, - port: float | None = None, - pad: str | None = None, - runner: Runner | None = None, -) -> AivOutputs: - """ - AFNI Image Viewer program. Shows the 2D images on the command line in an - AFNI-like image viewer. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_images: Input image files (e.g., img1.jpg, img2.bmp). - verbose: Print out the image filenames for progress tracking. - quiet: Run the program in quiet mode. - title: Specify the window title. - port: Listen to TCP/IP port for incoming images. - pad: Pad all input images to be the same size. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AivOutputs`). - """ - if port is not None and not (1024 <= port <= 65535): - raise ValueError(f"'port' must be between 1024 <= x <= 65535 but was {port}") - runner = runner or get_global_runner() - execution = runner.start_execution(AIV_METADATA) - cargs = [] - cargs.append("aiv") - if verbose: - cargs.append("-v") - if quiet: - cargs.append("-q") - if title is not None: - cargs.extend([ - "-title", - title - ]) - if port is not None: - cargs.extend([ - "-p", - str(port) - ]) - if pad is not None: - cargs.extend([ - "-pad", - pad - ]) - cargs.extend([execution.input_file(f) for f in input_images]) - ret = AivOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AIV_METADATA", - "AivOutputs", - "aiv", -] diff --git a/python/src/niwrap/afni/align_epi_anat.py b/python/src/niwrap/afni/align_epi_anat.py deleted file mode 100644 index d920ae4e5..000000000 --- a/python/src/niwrap/afni/align_epi_anat.py +++ /dev/null @@ -1,153 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ALIGN_EPI_ANAT_METADATA = Metadata( - id="8b0229305647603bf69640345954c0975124bb02.boutiques", - name="align_epi_anat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AlignEpiAnatOutputs(typing.NamedTuple): - """ - Output object returned when calling `align_epi_anat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - anat_aligned: OutputPathType - """A version of the anatomy that is aligned to the EPI""" - epi_aligned: OutputPathType - """A version of the EPI dataset aligned to the Anatomy""" - - -def align_epi_anat( - epi: InputPathType, - anat: InputPathType, - epi_base: str, - anat2epi: bool = False, - epi2anat: bool = False, - suffix: str | None = None, - add_edge: bool = False, - big_move: bool = False, - giant_move: bool = False, - ginormous_move: bool = False, - keep_rm_files: bool = False, - prep_only: bool = False, - ana_has_skull: typing.Literal["yes", "no"] | None = None, - epi_strip: typing.Literal["3dSkullStrip", "3dAutomask", "None"] | None = None, - volreg_method: typing.Literal["3dvolreg", "3dWarpDrive", "3dAllineate"] | None = None, - ex_mode: typing.Literal["quiet", "echo", "dry_run", "script"] | None = None, - overwrite: bool = False, - runner: Runner | None = None, -) -> AlignEpiAnatOutputs: - """ - Align EPI to anatomical datasets or vice versa. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - epi: EPI dataset to align or to which to align. - anat: Anatomical dataset to align or to which to align. - epi_base: Base sub-brick to use for alignment\ - (0/mean/median/max/subbrick#). - anat2epi: Align anatomical to EPI dataset (default). - epi2anat: Align EPI to anatomical dataset. - suffix: Append suffix to the original anat/epi dataset to use in the\ - resulting dataset names. - add_edge: Run @AddEdge script to create composite edge images. - big_move: Large displacement is needed to align the two volumes. - giant_move: Even larger movement required, uses cmass, two passes and\ - very large angles and shifts. - ginormous_move: Adds align_centers to giant_move. - keep_rm_files: Don't delete any of the temporary files created. - prep_only: Do preprocessing steps only without alignment. - ana_has_skull: Do not skullstrip anat dataset. - epi_strip: Method to remove skull for EPI data. - volreg_method: Time series volume registration method. - ex_mode: Command execution mode. - overwrite: Overwrite existing files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AlignEpiAnatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ALIGN_EPI_ANAT_METADATA) - cargs = [] - cargs.append("align_epi_anat.py") - cargs.extend([ - "-epi", - execution.input_file(epi) - ]) - cargs.extend([ - "-anat", - execution.input_file(anat) - ]) - cargs.extend([ - "-epi_base", - epi_base - ]) - if anat2epi: - cargs.append("-anat2epi") - if epi2anat: - cargs.append("-epi2anat") - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if add_edge: - cargs.append("-AddEdge") - if big_move: - cargs.append("-big_move") - if giant_move: - cargs.append("-giant_move") - if ginormous_move: - cargs.append("-ginormous_move") - if keep_rm_files: - cargs.append("-keep_rm_files") - if prep_only: - cargs.append("-prep_only") - if ana_has_skull is not None: - cargs.extend([ - "-anat_has_skull", - ana_has_skull - ]) - if epi_strip is not None: - cargs.extend([ - "-epi_strip", - epi_strip - ]) - if volreg_method is not None: - cargs.extend([ - "-volreg_method", - volreg_method - ]) - if ex_mode is not None: - cargs.extend([ - "-ex_mode", - ex_mode - ]) - if overwrite: - cargs.append("-overwrite") - ret = AlignEpiAnatOutputs( - root=execution.output_file("."), - anat_aligned=execution.output_file(pathlib.Path(anat).name + "+orig"), - epi_aligned=execution.output_file(pathlib.Path(epi).name + "+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ALIGN_EPI_ANAT_METADATA", - "AlignEpiAnatOutputs", - "align_epi_anat", -] diff --git a/python/src/niwrap/afni/analyze_trace.py b/python/src/niwrap/afni/analyze_trace.py deleted file mode 100644 index 7fc09db73..000000000 --- a/python/src/niwrap/afni/analyze_trace.py +++ /dev/null @@ -1,117 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANALYZE_TRACE_METADATA = Metadata( - id="3d880a6da4a3639545433e9f6739d09c2df6cf76.boutiques", - name="AnalyzeTrace", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AnalyzeTraceOutputs(typing.NamedTuple): - """ - Output object returned when calling `analyze_trace(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def analyze_trace( - tracefile: InputPathType, - max_func_lines: int | None = None, - suma_c: InputPathType | None = None, - max_err: int | None = None, - novolreg: bool = False, - noxform: bool = False, - setenv: str | None = None, - trace_: bool = False, - extreme_trace: bool = False, - nomall: bool = False, - yesmall: bool = False, - runner: Runner | None = None, -) -> AnalyzeTraceOutputs: - """ - A program to analyze SUMA (and AFNI's perhaps) stack output for functions that - return with RETURN without bothering to go on the stack. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tracefile: Trace output file obtained by redirecting the program’s\ - trace output. - max_func_lines: Set the maximum number of code lines before a function\ - returns. Default is no limit. - suma_c: FILE is a SUMA_*.c file. It is analyzed for functions that use\ - SUMA_RETURN without ENTRY. - max_err: Stop after encountering MAX_ERR errors reported in log.\ - Default is 5. Error key terms are: 'Error', 'error', 'corruption'. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - noxform: Same as -novolreg. - setenv: Set environment variable ENVname to be ENVvalue. Quotes are\ - necessary. - trace_: Turns on In/Out debug and Memory tracing. - extreme_trace: Turns on extreme tracing. - nomall: Turn off memory tracing. - yesmall: Turn on memory tracing (default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AnalyzeTraceOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANALYZE_TRACE_METADATA) - cargs = [] - cargs.append("AnalyzeTrace") - cargs.append(execution.input_file(tracefile)) - if max_func_lines is not None: - cargs.extend([ - "-max_func_lines", - str(max_func_lines) - ]) - if suma_c is not None: - cargs.extend([ - "-suma_c", - execution.input_file(suma_c) - ]) - if max_err is not None: - cargs.extend([ - "-max_err", - str(max_err) - ]) - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if setenv is not None: - cargs.extend([ - "-setenv", - setenv - ]) - if trace_: - cargs.append("-trace") - if extreme_trace: - cargs.append("-TRACE") - if nomall: - cargs.append("-nomall") - if yesmall: - cargs.append("-yesmall") - ret = AnalyzeTraceOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANALYZE_TRACE_METADATA", - "AnalyzeTraceOutputs", - "analyze_trace", -] diff --git a/python/src/niwrap/afni/ap_run_simple_rest.py b/python/src/niwrap/afni/ap_run_simple_rest.py deleted file mode 100644 index aa870261e..000000000 --- a/python/src/niwrap/afni/ap_run_simple_rest.py +++ /dev/null @@ -1,125 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AP_RUN_SIMPLE_REST_METADATA = Metadata( - id="1a513a80095d0ec1e3d0c42d6752fc35554360e8.boutiques", - name="ap_run_simple_rest", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ApRunSimpleRestOutputs(typing.NamedTuple): - """ - Output object returned when calling `ap_run_simple_rest(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - run_ap_script: OutputPathType | None - """afni_proc.py command script""" - proc_script: OutputPathType | None - """proc script (if AP is run)""" - proc_results_dir: OutputPathType | None - """proc results directory (if run)""" - text_output_files: OutputPathType - """Text output files from AP and proc scripts""" - - -def ap_run_simple_rest( - epi: list[InputPathType], - anat: InputPathType | None = None, - nt_rm: float | None = None, - run_ap: bool = False, - run_proc: bool = False, - subjid: str | None = None, - template: InputPathType | None = None, - compressor: str | None = None, - verb: float | None = None, - echo: bool = False, - runner: Runner | None = None, -) -> ApRunSimpleRestOutputs: - """ - Run a quick afni_proc.py analysis for QC. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - epi: EPI datasets. - anat: Single anatomical dataset. - nt_rm: Number of time points to remove from starts of runs. - run_ap: Run the afni_proc.py command. - run_proc: Run the proc script from afni_proc.py command. - subjid: Specify subject ID for file names. - template: Specify template for standard space. - compressor: Control automatic compression of *.BRIK files. - verb: Specify verbosity level. - echo: Same as verbosity level 3. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ApRunSimpleRestOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AP_RUN_SIMPLE_REST_METADATA) - cargs = [] - cargs.append("ap_run_simple_rest.tcsh") - if anat is not None: - cargs.extend([ - "-anat", - execution.input_file(anat) - ]) - cargs.append("-epi") - cargs.extend([execution.input_file(f) for f in epi]) - if nt_rm is not None: - cargs.extend([ - "-nt_rm", - str(nt_rm) - ]) - if run_ap: - cargs.append("-run_ap") - if run_proc: - cargs.append("-run_proc") - if subjid is not None: - cargs.extend([ - "-subjid", - subjid - ]) - if template is not None: - cargs.extend([ - "-template", - execution.input_file(template) - ]) - if compressor is not None: - cargs.extend([ - "-compressor", - compressor - ]) - if verb is not None: - cargs.extend([ - "-verb", - str(verb) - ]) - if echo: - cargs.append("-echo") - ret = ApRunSimpleRestOutputs( - root=execution.output_file("."), - run_ap_script=execution.output_file("run_ap_" + subjid) if (subjid is not None) else None, - proc_script=execution.output_file("proc." + subjid) if (subjid is not None) else None, - proc_results_dir=execution.output_file(subjid + ".results") if (subjid is not None) else None, - text_output_files=execution.output_file("out.*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AP_RUN_SIMPLE_REST_METADATA", - "ApRunSimpleRestOutputs", - "ap_run_simple_rest", -] diff --git a/python/src/niwrap/afni/apqc_make_html.py b/python/src/niwrap/afni/apqc_make_html.py deleted file mode 100644 index 89c052b21..000000000 --- a/python/src/niwrap/afni/apqc_make_html.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -APQC_MAKE_HTML_METADATA = Metadata( - id="07c116f696d041aa0735cff7c774be94af315e97.boutiques", - name="apqc_make_html", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ApqcMakeHtmlOutputs(typing.NamedTuple): - """ - Output object returned when calling `apqc_make_html(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def apqc_make_html( - qc_dir: str, - runner: Runner | None = None, -) -> ApqcMakeHtmlOutputs: - """ - Tool to generate HTML reports. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - qc_dir: Directory where QC files will be saved. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ApqcMakeHtmlOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(APQC_MAKE_HTML_METADATA) - cargs = [] - cargs.append("apqc_make_html.py") - cargs.append("-qc_dir") - cargs.append(qc_dir) - ret = ApqcMakeHtmlOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "APQC_MAKE_HTML_METADATA", - "ApqcMakeHtmlOutputs", - "apqc_make_html", -] diff --git a/python/src/niwrap/afni/apqc_make_tcsh_py.py b/python/src/niwrap/afni/apqc_make_tcsh_py.py deleted file mode 100644 index bdbb59c1a..000000000 --- a/python/src/niwrap/afni/apqc_make_tcsh_py.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -APQC_MAKE_TCSH_PY_METADATA = Metadata( - id="c8d624bec143f90b5f81c15e748a8504fff3f7c8.boutiques", - name="apqc_make_tcsh.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ApqcMakeTcshPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `apqc_make_tcsh_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - qc_html: OutputPathType - """Quality Control HTML file generated by APQC.""" - - -def apqc_make_tcsh_py( - uvar_json: InputPathType, - subj_dir: str, - review_style: str | None = None, - mot_grayplot_off: bool = False, - vstat_list: list[str] | None = None, - runner: Runner | None = None, -) -> ApqcMakeTcshPyOutputs: - """ - This program creates the single subject (ss) HTML review script - '@ss_review_html' which generates images and text for the afni_proc.py quality - control (APQC) HTML. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - uvar_json: Text file of user variables created by gen_ss_review.py that\ - catalogs important files in the results directory for the APQC. - subj_dir: Location of AP results directory (often '.', as this program\ - is often run from within the AP results directory). - review_style: The 'style' of the APQC HTML output HTML. Allowed\ - keywords are: {none, basic, pythonic}. Using 'pythonic' is recommended. - mot_grayplot_off: Turn off the grayplot generation. This option was\ - created for a specific case with a large dataset. Not recommended to\ - use generally. - vstat_list: Provide a list of label items to specify which volume's\ - images should appear in the vstat QC block. Each item should correspond\ - to subbrick label basename in the stats_dset. 'Full_Fstat' is always\ - included. If not used, default logic picks up to 5 items to show. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ApqcMakeTcshPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(APQC_MAKE_TCSH_PY_METADATA) - cargs = [] - cargs.append("apqc_make_tcsh.py") - cargs.extend([ - "-uvar_json", - execution.input_file(uvar_json) - ]) - cargs.extend([ - "-subj_dir", - subj_dir - ]) - if review_style is not None: - cargs.extend([ - "-review_style", - review_style - ]) - if mot_grayplot_off: - cargs.append("-mot_grayplot_off") - if vstat_list is not None: - cargs.extend([ - "-vstat_list", - *vstat_list - ]) - ret = ApqcMakeTcshPyOutputs( - root=execution.output_file("."), - qc_html=execution.output_file("qc_*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "APQC_MAKE_TCSH_PY_METADATA", - "ApqcMakeTcshPyOutputs", - "apqc_make_tcsh_py", -] diff --git a/python/src/niwrap/afni/apsearch.py b/python/src/niwrap/afni/apsearch.py deleted file mode 100644 index 8df6c8601..000000000 --- a/python/src/niwrap/afni/apsearch.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -APSEARCH_METADATA = Metadata( - id="daa8fa19d4d15fe37e1fd44af2f41bbb1e0649d7.boutiques", - name="apsearch", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ApsearchOutputs(typing.NamedTuple): - """ - Output object returned when calling `apsearch(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """File containing search results""" - - -def apsearch( - search_term: str, - file_output: InputPathType | None = None, - verbose: bool = False, - runner: Runner | None = None, -) -> ApsearchOutputs: - """ - A tool for searching applications. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - search_term: Term to search. - file_output: File to save the search results. - verbose: Print detailed information during search. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ApsearchOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(APSEARCH_METADATA) - cargs = [] - cargs.append("apsearch") - cargs.append(search_term) - if file_output is not None: - cargs.append(execution.input_file(file_output)) - if verbose: - cargs.append("-v") - ret = ApsearchOutputs( - root=execution.output_file("."), - output_file=execution.output_file(pathlib.Path(file_output).name) if (file_output is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "APSEARCH_METADATA", - "ApsearchOutputs", - "apsearch", -] diff --git a/python/src/niwrap/afni/auto_warp_py.py b/python/src/niwrap/afni/auto_warp_py.py deleted file mode 100644 index 4b8995731..000000000 --- a/python/src/niwrap/afni/auto_warp_py.py +++ /dev/null @@ -1,232 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -AUTO_WARP_PY_METADATA = Metadata( - id="717d1503884b0d326e79a7885336787157442069.boutiques", - name="auto_warp.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class AutoWarpPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `auto_warp_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def auto_warp_py( - base: InputPathType, - input_: InputPathType, - skull_strip_input: bool = False, - qblur: str | None = None, - qworkhard: str | None = None, - qw_opts: str | None = None, - keep_rm_files: bool = False, - prep_only: bool = False, - help_: bool = False, - hview: bool = False, - limited_help: bool = False, - option_help: bool = False, - version: bool = False, - ver: bool = False, - verb: bool = False, - save_script: bool = False, - skip_affine: bool = False, - skull_strip_base: bool = False, - ex_mode: str | None = None, - overwrite: bool = False, - suffix: str | None = None, - child_anat: str | None = None, - warp_dxyz: float | None = None, - affine_dxyz: float | None = None, - affine_input_xmat: str | None = None, - smooth_anat: bool = False, - smooth_base: bool = False, - unifize_input: bool = False, - output_dir: str | None = None, - followers: str | None = None, - affine_followers_xmat: str | None = None, - skullstrip_opts: str | None = None, - at_opts: str | None = None, - runner: Runner | None = None, -) -> AutoWarpPyOutputs: - """ - Nonlinear registration tool. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base: Name of reference or template volume. - input_: Name of dataset to be registered. - skull_strip_input: Do not skullstrip input dataset. - qblur: Specify 3dQwarp blurs for base and source volumes. - qworkhard: Set the two values for 3dQwarp's -workhard option. - qw_opts: Pass all of OPTS as extra options directly to 3dQwarp. - keep_rm_files: Don't delete any of the temporary files created. - prep_only: Do preprocessing steps only without alignment. - help_: Display help message. - hview: Display help message in a text editor. - limited_help: Display limited help message. - option_help: Display help for all available options. - version: Show version number and exit. - ver: Show version number and exit. - verb: Be verbose in messages and options. - save_script: Save executed script in given file. - skip_affine: Skip the affine registration process. - skull_strip_base: Do not skullstrip base/template dataset. - ex_mode: Command execution mode: quiet, echo, dry_run, script. - overwrite: Overwrite existing files. - suffix: Suffix to add to output files. - child_anat: Names of child anatomical datasets. - warp_dxyz: Resolution used for computing warp (cubic only). - affine_dxyz: Resolution used for computing initial transform (cubic\ - only). - affine_input_xmat: Affine transform to put input in standard space.\ - Special values are: 'AUTO' to use @auto_tlrc, 'ID' to do nothing,\ - 'FILE.1D' for a pre-computed matrix FILE.1D. - smooth_anat: Smooth anatomy before registration. - smooth_base: Smooth template before registration. - unifize_input: Unifize the input or not. - output_dir: Set directory for output datasets. - followers: Specify follower datasets. - affine_followers_xmat: Specify follower datasets' affine transforms. - skullstrip_opts: 3dSkullstrip miscellaneous options. - at_opts: @auto_tlrc miscellaneous options. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AutoWarpPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(AUTO_WARP_PY_METADATA) - cargs = [] - cargs.append("auto_warp.py") - cargs.append("-base") - cargs.append(execution.input_file(base)) - cargs.append("-input") - cargs.append(execution.input_file(input_)) - if skull_strip_input: - cargs.append("-skull_strip_input") - if qblur is not None: - cargs.extend([ - "-qblur", - qblur - ]) - if qworkhard is not None: - cargs.extend([ - "-qworkhard", - qworkhard - ]) - if qw_opts is not None: - cargs.extend([ - "-qw_opts", - qw_opts - ]) - if keep_rm_files: - cargs.append("-keep_rm_files") - if prep_only: - cargs.append("-prep_only") - if help_: - cargs.append("-help") - if hview: - cargs.append("-hview") - if limited_help: - cargs.append("-limited_help") - if option_help: - cargs.append("-option_help") - if version: - cargs.append("-version") - if ver: - cargs.append("-ver") - if verb: - cargs.append("-verb") - if save_script: - cargs.append("-save_script") - if skip_affine: - cargs.append("-skip_affine") - if skull_strip_base: - cargs.append("-skull_strip_base") - if ex_mode is not None: - cargs.extend([ - "-ex_mode", - ex_mode - ]) - if overwrite: - cargs.append("-overwrite") - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if child_anat is not None: - cargs.extend([ - "-child_anat", - child_anat - ]) - if warp_dxyz is not None: - cargs.extend([ - "-warp_dxyz", - str(warp_dxyz) - ]) - if affine_dxyz is not None: - cargs.extend([ - "-affine_dxyz", - str(affine_dxyz) - ]) - if affine_input_xmat is not None: - cargs.extend([ - "-affine_input_xmat", - affine_input_xmat - ]) - if smooth_anat: - cargs.append("-smooth_anat") - if smooth_base: - cargs.append("-smooth_base") - if unifize_input: - cargs.append("-unifize_input") - if output_dir is not None: - cargs.extend([ - "-output_dir", - output_dir - ]) - if followers is not None: - cargs.extend([ - "-followers", - followers - ]) - if affine_followers_xmat is not None: - cargs.extend([ - "-affine_followers_xmat", - affine_followers_xmat - ]) - if skullstrip_opts is not None: - cargs.extend([ - "-skullstrip_opts", - skullstrip_opts - ]) - if at_opts is not None: - cargs.extend([ - "-at_opts", - at_opts - ]) - ret = AutoWarpPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "AUTO_WARP_PY_METADATA", - "AutoWarpPyOutputs", - "auto_warp_py", -] diff --git a/python/src/niwrap/afni/balloon.py b/python/src/niwrap/afni/balloon.py deleted file mode 100644 index d2e6e57a2..000000000 --- a/python/src/niwrap/afni/balloon.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -BALLOON_METADATA = Metadata( - id="d51a9a16b7b5ef48e2f34c8e205b9eb2d6df6b2a.boutiques", - name="balloon", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class BalloonOutputs(typing.NamedTuple): - """ - Output object returned when calling `balloon(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def balloon( - tr: float, - num_scans: int, - event_times: InputPathType, - t_fall: list[float] | None = None, - runner: Runner | None = None, -) -> BalloonOutputs: - """ - Simulation of haemodynamic response using the balloon model. Based on the - theoretical model proposed by Buxton et al. (1998). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tr: Scan repetition time in seconds (TR), the interval at which the\ - output curve will be sampled. - num_scans: Number of scans (N), the output curve will comprise this\ - number of samples. - event_times: The name of a file containing the event timings, in\ - seconds, as ASCII strings separated by white space, with time 0 being\ - the time at which the initial scan occurred. - t_fall: Haemodynamic fall time in seconds (typically between 4s and\ - 6s). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `BalloonOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(BALLOON_METADATA) - cargs = [] - cargs.append("balloon") - cargs.append(str(tr)) - cargs.append(str(num_scans)) - cargs.append(execution.input_file(event_times)) - if t_fall is not None: - cargs.extend(map(str, t_fall)) - ret = BalloonOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "BALLOON_METADATA", - "BalloonOutputs", - "balloon", -] diff --git a/python/src/niwrap/afni/bayes_view.py b/python/src/niwrap/afni/bayes_view.py deleted file mode 100644 index a8ab33b73..000000000 --- a/python/src/niwrap/afni/bayes_view.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -BAYES_VIEW_METADATA = Metadata( - id="715b094d6153a447f9e56944e21b8af66039438f.boutiques", - name="bayes_view", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class BayesViewOutputs(typing.NamedTuple): - """ - Output object returned when calling `bayes_view(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def bayes_view( - input_folder: str, - help_: bool = False, - shiny_folder: str | None = None, - runner: Runner | None = None, -) -> BayesViewOutputs: - """ - Launch a shiny app to visualize RBA output files. The files must have the .RData - extension. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_folder: Path to a folder containing .RData files. - help_: Show help message. - shiny_folder: Use a custom shiny folder (for testing purposes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `BayesViewOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(BAYES_VIEW_METADATA) - cargs = [] - cargs.append("bayes_view") - cargs.append(input_folder) - if help_: - cargs.append("-help") - if shiny_folder is not None: - cargs.extend([ - "-ShinyFolder", - shiny_folder - ]) - ret = BayesViewOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "BAYES_VIEW_METADATA", - "BayesViewOutputs", - "bayes_view", -] diff --git a/python/src/niwrap/afni/bayesian_group_ana_py.py b/python/src/niwrap/afni/bayesian_group_ana_py.py deleted file mode 100644 index 5a58492fe..000000000 --- a/python/src/niwrap/afni/bayesian_group_ana_py.py +++ /dev/null @@ -1,149 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -BAYESIAN_GROUP_ANA_PY_METADATA = Metadata( - id="e49086bdbe64c248fa7b140fd8ae072e880fa9a7.boutiques", - name="BayesianGroupAna.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class BayesianGroupAnaPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `bayesian_group_ana_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - summary: OutputPathType | None - """Summary of the brmsfit object from R.""" - rhats: OutputPathType | None - """Rhats for each effect and x variable combination.""" - intercept_table: OutputPathType | None - """Table with the MedianEst, StdDev, 2.50%, 5%, 50%, 95%, and 97.50% of each - ROI for the Intercept term.""" - x_var_table: OutputPathType | None - """The same table as the Intercept but for the specified x variable.""" - - -def bayesian_group_ana_py( - data_table: InputPathType, - y_variable: str, - prefix: str | None = None, - x_variables: list[str] | None = None, - no_center: bool = False, - iterations: float | None = None, - chains: float | None = None, - control_list: str | None = None, - plot: bool = False, - more_plots: list[str] | None = None, - rdata: bool = False, - seed: float | None = None, - overwrite: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> BayesianGroupAnaPyOutputs: - """ - This program conducts Bayesian Group Analysis (BGA) on a list of regions of - interest (ROIs). Compared to the conventional univariate GLM, BGA pools and - shares the information across the ROIs in a multilevel system. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - data_table: Input text file containing the data table. - y_variable: Column name for the y variable. - prefix: Name of the output file. - x_variables: Column name(s) for the x variables. If not specified, only\ - the intercept will be added. - no_center: Disable centering on the x variables. Maybe useful if you\ - centered manually. - iterations: Number of total iterations per chain including warmup.\ - Default [1000]. - chains: Number of Markov chains. Default [4]. - control_list: Comma separated list of control parameters to pass to the\ - brm function. Default is the brm function defaults. - plot: Output box, fit, and posterior prediction plots. - more_plots: Output 'stanplots' given different types of plot names. - rdata: Save the R session workspace and data. - seed: Seed to generate random number. Default [1234]. - overwrite: Overwrites the output files. - help_: Show help message and exit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `BayesianGroupAnaPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(BAYESIAN_GROUP_ANA_PY_METADATA) - cargs = [] - cargs.append("BayesianGroupAna.py") - cargs.append(execution.input_file(data_table)) - cargs.append(y_variable) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if x_variables is not None: - cargs.extend([ - "-x", - *x_variables - ]) - if no_center: - cargs.append("-no_center") - if iterations is not None: - cargs.extend([ - "-iterations", - str(iterations) - ]) - if chains is not None: - cargs.extend([ - "-chains", - str(chains) - ]) - if control_list is not None: - cargs.extend([ - "-control_list", - control_list - ]) - if plot: - cargs.append("-plot") - if more_plots is not None: - cargs.extend([ - "-more_plots", - *more_plots - ]) - if rdata: - cargs.append("-RData") - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - if overwrite: - cargs.append("-overwrite") - if help_: - cargs.append("-help") - ret = BayesianGroupAnaPyOutputs( - root=execution.output_file("."), - summary=execution.output_file(prefix + "_summary.txt") if (prefix is not None) else None, - rhats=execution.output_file(prefix + "_rhats.csv") if (prefix is not None) else None, - intercept_table=execution.output_file(prefix + "_Intercept_table.csv") if (prefix is not None) else None, - x_var_table=execution.output_file(prefix + "_table.csv") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "BAYESIAN_GROUP_ANA_PY_METADATA", - "BayesianGroupAnaPyOutputs", - "bayesian_group_ana_py", -] diff --git a/python/src/niwrap/afni/brain_skin.py b/python/src/niwrap/afni/brain_skin.py deleted file mode 100644 index f4af35453..000000000 --- a/python/src/niwrap/afni/brain_skin.py +++ /dev/null @@ -1,172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -BRAIN_SKIN_METADATA = Metadata( - id="e13998cf44d59de6a5506224ec54d47b70b3bdd7.boutiques", - name="BrainSkin", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class BrainSkinOutputs(typing.NamedTuple): - """ - Output object returned when calling `brain_skin(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stitch_surface: OutputPathType - """A bunch of triangles for closing the surface.""" - initial_skin_surface: OutputPathType - """Initial skin surface""" - reduced_skin_surface: OutputPathType - """Reduced mesh version of initial skin surface.""" - inflated_skin_surface: OutputPathType - """Original surface inflated inside skin surface.""" - patching_voxels: OutputPathType - """Surface patching voxels.""" - surf_voxels: OutputPathType - """Voxels inside original surface""" - skin_voxels: OutputPathType - """Mix of ptchvox and surfvox.""" - infilled_voxels: OutputPathType - """Skin vox dataset filled in.""" - node_pairs_results: OutputPathType - """Results of computations for finding node pairs that span sulci.""" - inflating_surface_results: OutputPathType - """Results of computations for inflating initial surface inside skin - surface.""" - segments_display: OutputPathType - """Segments between node pairs spanning sulci.""" - - -def brain_skin( - surface: str, - skingrid_volume: InputPathType, - prefix: str, - plimit: float | None = None, - dlimit: float | None = None, - segdo: str | None = None, - voxelize: str | None = None, - infill: str | None = None, - out_file: InputPathType | None = None, - vol_hull: InputPathType | None = None, - no_zero_attraction: bool = False, - node_dbg: float | None = None, - runner: Runner | None = None, -) -> BrainSkinOutputs: - """ - A program to create an unfolded surface that wraps the brain (skin) and - Gyrification Indices. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Surface to smooth or the domain over which DSET is defined. - skingrid_volume: A high-res volume to provide a grid for voxelization\ - steps. - prefix: Prefix to use for variety of output files. - plimit: Maximum length of path along surface in mm for node pairing. - dlimit: Maximum length of Euclidean distance in mm for node pairing. - segdo: Output a displayable object file that contains segments between\ - paired nodes. - voxelize: Voxelization method. Choose from: slow: Sure footed but slow,\ - fast: Faster and works OK, mask: Fastest and works OK too (default). - infill: Infill method. Choose from: slow: proper infill, but not\ - needed, fast: brutish infill, all we need (default). - out_file: Output intermediary results from skin forming step. - vol_hull: Deform an Icosahedron to match the convex hull of a mask\ - volume. - no_zero_attraction: With vol_skin, the surface will try to shrink\ - aggressively, even if there is no promise of non-zero values below. - node_dbg: Output debugging information for node N for -vol_skin and\ - -vol_hull options. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `BrainSkinOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(BRAIN_SKIN_METADATA) - cargs = [] - cargs.append("BrainSkin") - cargs.append(surface) - cargs.extend([ - "-skingrid", - execution.input_file(skingrid_volume) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if plimit is not None: - cargs.extend([ - "-plimit", - str(plimit) - ]) - if dlimit is not None: - cargs.extend([ - "-dlimit", - str(dlimit) - ]) - if segdo is not None: - cargs.extend([ - "-segdo", - segdo - ]) - if voxelize is not None: - cargs.extend([ - "-voxelize", - voxelize - ]) - if infill is not None: - cargs.extend([ - "-infill", - infill - ]) - if out_file is not None: - cargs.extend([ - "-out", - execution.input_file(out_file) - ]) - if vol_hull is not None: - cargs.extend([ - "-vol_hull", - execution.input_file(vol_hull) - ]) - if no_zero_attraction: - cargs.append("-no_zero_attraction") - if node_dbg is not None: - cargs.extend([ - "-node_dbg", - str(node_dbg) - ]) - ret = BrainSkinOutputs( - root=execution.output_file("."), - stitch_surface=execution.output_file(prefix + ".stitch.gii"), - initial_skin_surface=execution.output_file(prefix + ".skin.gii"), - reduced_skin_surface=execution.output_file(prefix + ".skin_simp.gii"), - inflated_skin_surface=execution.output_file(prefix + ".skin.isotopic.gii"), - patching_voxels=execution.output_file(prefix + ".ptchvox+orig"), - surf_voxels=execution.output_file(prefix + ".surfvox+orig"), - skin_voxels=execution.output_file(prefix + ".skinvox+orig"), - infilled_voxels=execution.output_file(prefix + ".infilled+orig"), - node_pairs_results=execution.output_file(prefix + ".niml.dset"), - inflating_surface_results=execution.output_file(prefix + ".areas.niml.dset"), - segments_display=execution.output_file(prefix + ".1D.do"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "BRAIN_SKIN_METADATA", - "BrainSkinOutputs", - "brain_skin", -] diff --git a/python/src/niwrap/afni/build_afni_py.py b/python/src/niwrap/afni/build_afni_py.py deleted file mode 100644 index c2de012f7..000000000 --- a/python/src/niwrap/afni/build_afni_py.py +++ /dev/null @@ -1,143 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -BUILD_AFNI_PY_METADATA = Metadata( - id="ee4b7185c56e742278b295803c7a5885f8b4523b.boutiques", - name="build_afni.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class BuildAfniPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `build_afni_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - command_history_file: OutputPathType - """Command history file""" - screen_output_history: OutputPathType - """Screen output history file""" - - -def build_afni_py( - build_root: str, - clean_root: str | None = None, - git_branch: str | None = None, - git_tag: str | None = None, - git_update: str | None = None, - make_target: str | None = None, - makefile: str | None = None, - package: str | None = None, - prep_only: bool = False, - run_cmake: str | None = None, - run_make: str | None = None, - verbose_level: float | None = None, - version: bool = False, - runner: Runner | None = None, -) -> BuildAfniPyOutputs: - """ - Compile an AFNI package from the git repository. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - build_root: Root directory to use for git and building. - clean_root: Specify whether to clean up the build_root. Default is yes. - git_branch: Specify a branch to checkout in git. Default is master. - git_tag: Specify a tag to checkout in git. Default is LAST_TAG. - git_update: Specify whether to update git repo. Default is yes. - make_target: Specify target for make command. Default is itall. - makefile: Specify an alternate Makefile to build from. - package: Specify the desired package to build. - prep_only: Prepare to but do not run (c)make. - run_cmake: Choose whether to run a cmake build. Default is no. - run_make: Choose whether to run a make build. Default is yes. - verbose_level: Set the verbosity level. Default is 1. - version: Show the current version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `BuildAfniPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(BUILD_AFNI_PY_METADATA) - cargs = [] - cargs.append("build_afni.py") - cargs.append("-build_root") - cargs.append(build_root) - if clean_root is not None: - cargs.extend([ - "-clean_root", - clean_root - ]) - if git_branch is not None: - cargs.extend([ - "-git_branch", - git_branch - ]) - if git_tag is not None: - cargs.extend([ - "-git_tag", - git_tag - ]) - if git_update is not None: - cargs.extend([ - "-git_update", - git_update - ]) - if make_target is not None: - cargs.extend([ - "-make_target", - make_target - ]) - if makefile is not None: - cargs.extend([ - "-makefile", - makefile - ]) - if package is not None: - cargs.extend([ - "-package", - package - ]) - if prep_only: - cargs.append("-prep_only") - if run_cmake is not None: - cargs.extend([ - "-run_cmake", - run_cmake - ]) - if run_make is not None: - cargs.extend([ - "-run_make", - run_make - ]) - if verbose_level is not None: - cargs.extend([ - "-verb", - str(verbose_level) - ]) - if version: - cargs.append("-ver") - ret = BuildAfniPyOutputs( - root=execution.output_file("."), - command_history_file=execution.output_file(build_root + "/hist_commands.txt"), - screen_output_history=execution.output_file(build_root + "/screen_output_history.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "BUILD_AFNI_PY_METADATA", - "BuildAfniPyOutputs", - "build_afni_py", -] diff --git a/python/src/niwrap/afni/cat_matvec.py b/python/src/niwrap/afni/cat_matvec.py deleted file mode 100644 index 59ab2e669..000000000 --- a/python/src/niwrap/afni/cat_matvec.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CAT_MATVEC_METADATA = Metadata( - id="a2e1e224a82974ccf7750fe559ce685c6d44f16c.boutiques", - name="cat_matvec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CatMatvecOutputs(typing.NamedTuple): - """ - Output object returned when calling `cat_matvec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def cat_matvec( - matvec_spec: list[str], - four_by_four_format: bool = False, - runner: Runner | None = None, -) -> CatMatvecOutputs: - """ - Catenates 3D rotation+shift matrix+vector transformations. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - matvec_spec: Specifies the matrix transformation. Can take forms\ - described in the documentation. - four_by_four_format: Output matrix in augmented form (last row is 0 0 0\ - 1). This option does not work with -MATRIX or -ONELINE. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CatMatvecOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CAT_MATVEC_METADATA) - cargs = [] - cargs.append("cat_matvec") - if four_by_four_format: - cargs.append("-4x4") - cargs.extend(matvec_spec) - ret = CatMatvecOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CAT_MATVEC_METADATA", - "CatMatvecOutputs", - "cat_matvec", -] diff --git a/python/src/niwrap/afni/ccalc.py b/python/src/niwrap/afni/ccalc.py deleted file mode 100644 index 36ae6e86f..000000000 --- a/python/src/niwrap/afni/ccalc.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CCALC_METADATA = Metadata( - id="e76d49ddb6fb2569c3e43954471845bd902d1d58.boutiques", - name="ccalc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CcalcOutputs(typing.NamedTuple): - """ - Output object returned when calling `ccalc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def ccalc( - expr: str, - format_: str | None = None, - runner: Runner | None = None, -) -> CcalcOutputs: - """ - Command line calculator with formatted output options. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expr: Evaluate an expression specified on command line, return answer\ - and quit. - format_: Format output in a nice form. Choose from 'double', 'nice',\ - 'int', 'rint', 'cint', 'fint', or custom format string (e.g., %n.mf). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CcalcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CCALC_METADATA) - cargs = [] - cargs.append("ccalc") - if format_ is not None: - cargs.extend([ - "-form", - format_ - ]) - cargs.append("-eval") - cargs.extend([ - "-eval", - expr - ]) - ret = CcalcOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CCALC_METADATA", - "CcalcOutputs", - "ccalc", -] diff --git a/python/src/niwrap/afni/cifti_tool.py b/python/src/niwrap/afni/cifti_tool.py deleted file mode 100644 index b5de6460b..000000000 --- a/python/src/niwrap/afni/cifti_tool.py +++ /dev/null @@ -1,113 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CIFTI_TOOL_METADATA = Metadata( - id="fc2e3e53992537d6ba3769a1e46c322268b0206f.boutiques", - name="cifti_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CiftiToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `cifti_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output file for results""" - - -def cifti_tool( - input_file: InputPathType, - as_cext: bool = False, - disp_cext: bool = False, - eval_cext: bool = False, - eval_type: typing.Literal["has_data", "has_bdata", "num_tokens", "show", "show_names", "show_summary", "show_text_data"] | None = None, - output_file: str | None = None, - verbose_level: float | None = None, - verbose_read_level: float | None = None, - both_verbose_levels: float | None = None, - runner: Runner | None = None, -) -> CiftiToolOutputs: - """ - Example tool for reading/writing CIFTI-2 datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Specify input dataset. - as_cext: Process the input as just an extension. - disp_cext: Display the CIFTI extension. - eval_cext: Evaluate the CIFTI extension. - eval_type: Method for evaluation of axml elements. - output_file: Where to write output. - verbose_level: Set the verbose level. - verbose_read_level: Set verbose level when reading. - both_verbose_levels: Apply both -verb options. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CiftiToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CIFTI_TOOL_METADATA) - cargs = [] - cargs.append("cifti_tool") - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if as_cext: - cargs.append("-as_cext") - if disp_cext: - cargs.append("-disp_cext") - if eval_cext: - cargs.append("-eval_cext") - if eval_type is not None: - cargs.extend([ - "-eval_type", - eval_type - ]) - cargs.append("-output") - if output_file is not None: - cargs.extend([ - "-output", - output_file - ]) - if verbose_level is not None: - cargs.extend([ - "-verb", - str(verbose_level) - ]) - if verbose_read_level is not None: - cargs.extend([ - "-verb_read", - str(verbose_read_level) - ]) - if both_verbose_levels is not None: - cargs.extend([ - "-vboth", - str(both_verbose_levels) - ]) - ret = CiftiToolOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_file) if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CIFTI_TOOL_METADATA", - "CiftiToolOutputs", - "cifti_tool", -] diff --git a/python/src/niwrap/afni/cjpeg.py b/python/src/niwrap/afni/cjpeg.py deleted file mode 100644 index d94e135a4..000000000 --- a/python/src/niwrap/afni/cjpeg.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CJPEG_METADATA = Metadata( - id="c91bb799815c3c2fc8e175c9c148e01746ecf0ae.boutiques", - name="cjpeg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CjpegOutputs(typing.NamedTuple): - """ - Output object returned when calling `cjpeg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """The output JPEG file""" - - -def cjpeg( - outfile: str, - infile: InputPathType, - quality: float | None = None, - grayscale: bool = False, - optimize: bool = False, - baseline: bool = False, - progressive: bool = False, - runner: Runner | None = None, -) -> CjpegOutputs: - """ - Compresses an image file to a JPEG file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - outfile: Output JPEG file. - infile: Input image file. - quality: Quality of JPEG image (0-100). - grayscale: Create a grayscale JPEG file. - optimize: Optimize Huffman table. - baseline: Create a baseline JPEG file. - progressive: Create a progressive JPEG file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CjpegOutputs`). - """ - if quality is not None and not (0 <= quality <= 100): - raise ValueError(f"'quality' must be between 0 <= x <= 100 but was {quality}") - runner = runner or get_global_runner() - execution = runner.start_execution(CJPEG_METADATA) - cargs = [] - cargs.append("cjpeg") - if quality is not None: - cargs.extend([ - "-quality", - str(quality) - ]) - if grayscale: - cargs.append("-grayscale") - if optimize: - cargs.append("-optimize") - if baseline: - cargs.append("-baseline") - if progressive: - cargs.append("-progressive") - cargs.append(outfile) - cargs.append(execution.input_file(infile)) - ret = CjpegOutputs( - root=execution.output_file("."), - outfile=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CJPEG_METADATA", - "CjpegOutputs", - "cjpeg", -] diff --git a/python/src/niwrap/afni/clust_exp_hist_table_py.py b/python/src/niwrap/afni/clust_exp_hist_table_py.py deleted file mode 100644 index f6e5019fe..000000000 --- a/python/src/niwrap/afni/clust_exp_hist_table_py.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CLUST_EXP_HIST_TABLE_PY_METADATA = Metadata( - id="65bf8cf819db98a9fbc8b570e9306335fa8356d5.boutiques", - name="ClustExp_HistTable.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ClustExpHistTablePyOutputs(typing.NamedTuple): - """ - Output object returned when calling `clust_exp_hist_table_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - group_table: OutputPathType | None - """Table with information parsed from the statistics dataset history.""" - - -def clust_exp_hist_table_py( - stat_dset: InputPathType, - prefix: str | None = None, - session: str | None = None, - overwrite: bool = False, - runner: Runner | None = None, -) -> ClustExpHistTablePyOutputs: - """ - Script to extract the data table from history of datasets from 3dttest++, 3dMVM, - or 3dLME. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - stat_dset: Statistics dataset. - prefix: Name for output (no path). Default is GroupOut. - session: Output parent folder if you don't want the current working\ - directory. Default is ./. - overwrite: Remove previous folder with same PREFIX. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ClustExpHistTablePyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CLUST_EXP_HIST_TABLE_PY_METADATA) - cargs = [] - cargs.append("ClustExp_HistTable.py") - cargs.extend([ - "-StatDSET", - execution.input_file(stat_dset) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if session is not None: - cargs.extend([ - "-session", - session - ]) - if overwrite: - cargs.append("-overwrite") - ret = ClustExpHistTablePyOutputs( - root=execution.output_file("."), - group_table=execution.output_file(prefix + "_GroupTable.csv") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CLUST_EXP_HIST_TABLE_PY_METADATA", - "ClustExpHistTablePyOutputs", - "clust_exp_hist_table_py", -] diff --git a/python/src/niwrap/afni/clust_exp_stat_parse_py.py b/python/src/niwrap/afni/clust_exp_stat_parse_py.py deleted file mode 100644 index 8d8d18f71..000000000 --- a/python/src/niwrap/afni/clust_exp_stat_parse_py.py +++ /dev/null @@ -1,163 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CLUST_EXP_STAT_PARSE_PY_METADATA = Metadata( - id="ea140a29445ae8cf4f0dcd37868ab11f8f883921.boutiques", - name="ClustExp_StatParse.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ClustExpStatParsePyOutputs(typing.NamedTuple): - """ - Output object returned when calling `clust_exp_stat_parse_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - table_mean: OutputPathType | None - """Table with all data extracted from all subjects.""" - group_table: OutputPathType | None - """Table with information parsed from the statistics data set history.""" - v_3dclust_output: OutputPathType | None - """Output directly from 3dclust.""" - clusters_output: OutputPathType | None - """Cleaned up version of the whereami output.""" - statinfo_output: OutputPathType | None - """Summary info for the shiny app.""" - thresholded_dataset: OutputPathType | None - """A new data set from input statistics, thresholded at uncorrected p - value.""" - thresholded_mask_dataset: OutputPathType | None - """Integer labeled mask of the thresholded image with cluster sizes at least - as big as the -MinVox.""" - master_copy: OutputPathType | None - """A NIfTI copy of the master file provided that may have been resampled.""" - - -def clust_exp_stat_parse_py( - statdset: InputPathType, - meanbrik: float, - threshbrik: float, - subjdset: InputPathType, - subjtable: InputPathType, - master: InputPathType, - prefix: str | None = None, - pval: float | None = None, - minvox: float | None = None, - atlas: str | None = None, - session: str | None = None, - noshiny: bool = False, - overwrite: bool = False, - runner: Runner | None = None, -) -> ClustExpStatParsePyOutputs: - """ - Parser for statistical data sets and subject data sets, generating several - outputs for further analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - statdset: Statistics dataset. - meanbrik: Mean subbrik (integer >= 0). - threshbrik: Threshold subbrik. Might be the same as MeanBrik (integer\ - >= 0). - subjdset: Labeled dataset with all subjects (from @ClustExp_CatLab). - subjtable: Table with subject labels and input datasets. - master: Master data set for underlay. - prefix: Name for output (no path). - pval: Uncorrected p value for thresholding. - minvox: Minimum voxels in cluster. - atlas: Atlas name for lookup (list at: whereami -help). - session: Output parent folder if you don't want the current working\ - directory. - noshiny: Do not create shiny app. - overwrite: Remove previous folder with same PREFIX. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ClustExpStatParsePyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CLUST_EXP_STAT_PARSE_PY_METADATA) - cargs = [] - cargs.append("ClustExp_StatParse.py") - cargs.extend([ - "-StatDSET", - execution.input_file(statdset) - ]) - cargs.extend([ - "-MeanBrik", - str(meanbrik) - ]) - cargs.extend([ - "-ThreshBrik", - str(threshbrik) - ]) - cargs.extend([ - "-SubjDSET", - execution.input_file(subjdset) - ]) - cargs.extend([ - "-SubjTable", - execution.input_file(subjtable) - ]) - cargs.extend([ - "-master", - execution.input_file(master) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if pval is not None: - cargs.extend([ - "-p", - str(pval) - ]) - if minvox is not None: - cargs.extend([ - "-MinVox", - str(minvox) - ]) - if atlas is not None: - cargs.extend([ - "-atlas", - atlas - ]) - if session is not None: - cargs.extend([ - "-session", - session - ]) - if noshiny: - cargs.append("-NoShiny") - if overwrite: - cargs.append("-overwrite") - ret = ClustExpStatParsePyOutputs( - root=execution.output_file("."), - table_mean=execution.output_file(prefix + "_p_uncor_" + str(pval) + "_mean.csv") if (prefix is not None and pval is not None) else None, - group_table=execution.output_file(prefix + "_GroupTable.csv") if (prefix is not None) else None, - v_3dclust_output=execution.output_file(prefix + "_p_uncor_" + str(pval) + "_3dclust.1D") if (prefix is not None and pval is not None) else None, - clusters_output=execution.output_file(prefix + "_p_uncor_" + str(pval) + "_clusters.csv") if (prefix is not None and pval is not None) else None, - statinfo_output=execution.output_file(prefix + "_StatInfo.csv") if (prefix is not None) else None, - thresholded_dataset=execution.output_file(prefix + "_p_uncor_" + str(pval) + ".nii.gz") if (prefix is not None and pval is not None) else None, - thresholded_mask_dataset=execution.output_file(prefix + "_p_uncor_" + str(pval) + "_mask.nii.gz") if (prefix is not None and pval is not None) else None, - master_copy=execution.output_file(prefix + "_master.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CLUST_EXP_STAT_PARSE_PY_METADATA", - "ClustExpStatParsePyOutputs", - "clust_exp_stat_parse_py", -] diff --git a/python/src/niwrap/afni/column_cat.py b/python/src/niwrap/afni/column_cat.py deleted file mode 100644 index 9c9187bc1..000000000 --- a/python/src/niwrap/afni/column_cat.py +++ /dev/null @@ -1,78 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -COLUMN_CAT_METADATA = Metadata( - id="3a134043c87d0163c9100245c6b67189ec396c2d.boutiques", - name="column_cat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ColumnCatOutputs(typing.NamedTuple): - """ - Output object returned when calling `column_cat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Redirect output of concatenation to a file""" - - -def column_cat( - input_files: list[InputPathType], - line_number: float | None = None, - separator_string: str | None = None, - runner: Runner | None = None, -) -> ColumnCatOutputs: - """ - Catenate files horizontally. Each line of output is the concatenation of each - current line from the input files, all on the same line, separated by a space or - a user-defined separator. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input files to be concatenated. - line_number: Print only the specified line number (1-based). - separator_string: Use the specified string as a separator between\ - columns. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ColumnCatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(COLUMN_CAT_METADATA) - cargs = [] - cargs.append("column_cat") - if line_number is not None: - cargs.extend([ - "-line", - str(line_number) - ]) - if separator_string is not None: - cargs.extend([ - "-sep", - separator_string - ]) - cargs.extend([execution.input_file(f) for f in input_files]) - ret = ColumnCatOutputs( - root=execution.output_file("."), - output_file=execution.output_file("output_file.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "COLUMN_CAT_METADATA", - "ColumnCatOutputs", - "column_cat", -] diff --git a/python/src/niwrap/afni/compare_surfaces.py b/python/src/niwrap/afni/compare_surfaces.py deleted file mode 100644 index bb34522b5..000000000 --- a/python/src/niwrap/afni/compare_surfaces.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -COMPARE_SURFACES_METADATA = Metadata( - id="1e4adc71975e9cacfb4dd4b6b68d24185052774f.boutiques", - name="CompareSurfaces", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CompareSurfacesOutputs(typing.NamedTuple): - """ - Output object returned when calling `compare_surfaces(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - distance_output_file: OutputPathType | None - """Distance output file.""" - color_output_file: OutputPathType | None - """Node color output file.""" - - -def compare_surfaces( - spec_file: InputPathType, - hemisphere: typing.Literal["L", "R"], - volume_parent_1: InputPathType, - volume_parent_2: InputPathType, - file_prefix: str | None = None, - one_node: float | None = None, - node_range: list[float] | None = None, - no_consistency_check: bool = False, - no_volreg: bool = False, - no_transform: bool = False, - set_environment_variable: str | None = None, - trace_: bool = False, - extreme_trace: bool = False, - no_memory_trace: bool = False, - yes_memory_trace: bool = False, - runner: Runner | None = None, -) -> CompareSurfacesOutputs: - """ - Calculates distance at each node in Surface 1 (S1) to Surface 2 (S2) along the - local surface normal at each node in S1. Superseded by SurfToSurf. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: File containing surface specification. - hemisphere: Specify the hemisphere being processed (left or right). - volume_parent_1: Volume parent BRIK for first surface. - volume_parent_2: Volume parent BRIK for second surface. - file_prefix: Prefix for distance and node color output files. Existing\ - file will not be overwritten. - one_node: Output results for node index only. This option is for\ - debugging. - node_range: Output results from node istart to node istop only. This\ - option is for debugging. - no_consistency_check: Skip mesh orientation consistency check. This\ - speeds up the start time so it is useful for debugging runs. - no_volreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - no_transform: Same as -novolreg. - set_environment_variable: Set environment variable ENVname to be\ - ENVvalue. Quotes are necessary. - trace_: Turns on In/Out debug and Memory tracing. - extreme_trace: Turns on extreme tracing. - no_memory_trace: Turn off memory tracing. - yes_memory_trace: Turn on memory tracing (default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CompareSurfacesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(COMPARE_SURFACES_METADATA) - cargs = [] - cargs.append("CompareSurfaces") - cargs.extend([ - "-spec", - execution.input_file(spec_file) - ]) - cargs.extend([ - "-hemi", - hemisphere - ]) - cargs.extend([ - "-sv1", - execution.input_file(volume_parent_1) - ]) - cargs.extend([ - "-sv2", - execution.input_file(volume_parent_2) - ]) - if file_prefix is not None: - cargs.extend([ - "-prefix", - file_prefix - ]) - if one_node is not None: - cargs.extend([ - "-onenode", - str(one_node) - ]) - if node_range is not None: - cargs.extend([ - "-noderange", - *map(str, node_range) - ]) - if no_consistency_check: - cargs.append("-nocons") - if no_volreg: - cargs.append("-novolreg") - if no_transform: - cargs.append("-noxform") - if set_environment_variable is not None: - cargs.extend([ - "-setenv", - set_environment_variable - ]) - if trace_: - cargs.append("-trace") - if extreme_trace: - cargs.append("-TRACE") - if no_memory_trace: - cargs.append("-nomall") - if yes_memory_trace: - cargs.append("-yesmall") - ret = CompareSurfacesOutputs( - root=execution.output_file("."), - distance_output_file=execution.output_file(file_prefix + "_distance.txt") if (file_prefix is not None) else None, - color_output_file=execution.output_file(file_prefix + "_color.txt") if (file_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "COMPARE_SURFACES_METADATA", - "CompareSurfacesOutputs", - "compare_surfaces", -] diff --git a/python/src/niwrap/afni/convert_cdiflist_to_grads.py b/python/src/niwrap/afni/convert_cdiflist_to_grads.py deleted file mode 100644 index 301fd6567..000000000 --- a/python/src/niwrap/afni/convert_cdiflist_to_grads.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_CDIFLIST_TO_GRADS_METADATA = Metadata( - id="ea130b033404a9cbd6779270e1ab5a04fbc1255c.boutiques", - name="convert_cdiflist_to_grads", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ConvertCdiflistToGradsOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_cdiflist_to_grads(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_rvec: OutputPathType - """Row-format of gradients (unit magnitude).""" - output_bval: OutputPathType - """Row-format of bvals.""" - output_cvec: OutputPathType - """Col-format of gradients (scaled by b-values).""" - - -def convert_cdiflist_to_grads( - cdiflist: InputPathType, - bval_max: float, - prefix: str, - ver: bool = False, - date: bool = False, - help_: bool = False, - hview: bool = False, - runner: Runner | None = None, -) -> ConvertCdiflistToGradsOutputs: - """ - This program reads in a GE cdiflist and outputs gradient file and file of - bvalues for subsequent processing. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - cdiflist: Name(s) of cdiflist text file output by GE scanners when\ - acquiring DWIs. - bval_max: Max bvalue used, which provides a reference value for scaling\ - everything else. - prefix: Output basename for the subsequent grad and bvalue files\ - (suffix and extensions will be added). - ver: Display current version. - date: Display release/editing date of current version. - help_: Display help in terminal. - hview: Display help in terminal. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertCdiflistToGradsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_CDIFLIST_TO_GRADS_METADATA) - cargs = [] - cargs.append("convert_cdiflist_to_grads.py") - cargs.append("-cdiflist") - cargs.extend([ - "-cdiflist", - execution.input_file(cdiflist) - ]) - cargs.append("-bval_max") - cargs.extend([ - "-bval_max", - str(bval_max) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if ver: - cargs.append("-ver") - if date: - cargs.append("-date") - if help_: - cargs.append("-help") - if hview: - cargs.append("-h") - ret = ConvertCdiflistToGradsOutputs( - root=execution.output_file("."), - output_rvec=execution.output_file(prefix + "_rvec.dat"), - output_bval=execution.output_file(prefix + "_bval.dat"), - output_cvec=execution.output_file(prefix + "_cvec.dat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_CDIFLIST_TO_GRADS_METADATA", - "ConvertCdiflistToGradsOutputs", - "convert_cdiflist_to_grads", -] diff --git a/python/src/niwrap/afni/convert_dset.py b/python/src/niwrap/afni/convert_dset.py deleted file mode 100644 index f62e96b53..000000000 --- a/python/src/niwrap/afni/convert_dset.py +++ /dev/null @@ -1,188 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_DSET_METADATA = Metadata( - id="844cbaec7e78b76addf8794c6d75de087e117e30.boutiques", - name="ConvertDset", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ConvertDsetOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_dset(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - converted_dataset: OutputPathType | None - """Converted dataset output""" - - -def convert_dset( - output_type: list[typing.Literal["niml_asc", "niml_bi", "1D", "1Dp", "1Dpt", "gii", "gii_asc", "gii_b64", "gii_b64gz", "1D_stderr", "1D_stdout", "niml_stderr", "niml_stdout", "1Dp_stdout", "1Dp_stderr", "1Dpt_stdout", "1Dpt_stderr"]], - input_dataset: InputPathType, - input_type: typing.Literal["niml", "1D", "dx"] | None = None, - output_prefix: str | None = None, - dset_labels: str | None = None, - add_node_index: bool = False, - node_index_file: InputPathType | None = None, - node_select_file: InputPathType | None = None, - prepend_node_index: bool = False, - pad_to_node: str | None = None, - labelize: InputPathType | None = None, - graphize: bool = False, - graph_nodelist: str | None = None, - graph_full_nodelist: InputPathType | None = None, - graph_named_nodelist: str | None = None, - graph_xyz_lpi: bool = False, - graph_edgelist: InputPathType | None = None, - onegraph: bool = False, - multigraph: bool = False, - split: int | None = None, - no_history: bool = False, - runner: Runner | None = None, -) -> ConvertDsetOutputs: - """ - Converts a surface dataset from one format to another. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_type: Type of output datasets. - input_dataset: Input dataset to be converted. - input_type: Type of input datasets. - output_prefix: Output prefix for dataset. - dset_labels: Label the columns (sub-bricks) of the output dataset. - add_node_index: Add a node index element if one does not exist in the\ - input dataset. - node_index_file: File containing node indices. - node_select_file: File specifying the nodes to keep in the output. - prepend_node_index: Add a node index column to the data. - pad_to_node: Output a full dataset from node 0 to MAX_INDEX. - labelize: Turn the dataset into a labeled set per the colormap in CMAP. - graphize: Turn the dataset into a SUMA graph dataset. - graph_nodelist: Two files specifying the indices and the coordinates of\ - the graph's nodes. - graph_full_nodelist: Similar to -graph_nodelist_1D but without need for\ - NODEINDLIST.1D. - graph_named_nodelist: Two files specifying graph node indices, string\ - labels, and their coordinates. - graph_xyz_lpi: Coordinates in NodeList.1D are in LPI instead of RAI. - graph_edgelist: Indices of graph nodes defining edge. - onegraph: Expect input dataset to be one square matrix defining the\ - graph (default). - multigraph: Expect each column in input dataset to define an entire\ - graph. - split: Split a multi-column dataset into about N output datasets. - no_history: Do not include a history element in the output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertDsetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_DSET_METADATA) - cargs = [] - cargs.append("ConvertDset") - cargs.extend([ - "-o_", - *output_type - ]) - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if input_type is not None: - cargs.extend([ - "-i_", - input_type - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if dset_labels is not None: - cargs.extend([ - "-dset_labels", - dset_labels - ]) - if add_node_index: - cargs.append("-add_node_index") - if node_index_file is not None: - cargs.extend([ - "-node_index_1D", - execution.input_file(node_index_file) - ]) - if node_select_file is not None: - cargs.extend([ - "-node_select_1D", - execution.input_file(node_select_file) - ]) - if prepend_node_index: - cargs.append("-prepend_node_index_1D") - if pad_to_node is not None: - cargs.extend([ - "-pad_to_node", - pad_to_node - ]) - if labelize is not None: - cargs.extend([ - "-labelize", - execution.input_file(labelize) - ]) - if graphize: - cargs.append("-graphize") - if graph_nodelist is not None: - cargs.extend([ - "-graph_nodelist_1D", - graph_nodelist - ]) - if graph_full_nodelist is not None: - cargs.extend([ - "-graph_full_nodelist_1D", - execution.input_file(graph_full_nodelist) - ]) - if graph_named_nodelist is not None: - cargs.extend([ - "-graph_named_nodelist_txt", - graph_named_nodelist - ]) - if graph_xyz_lpi: - cargs.append("-graph_XYZ_LPI") - if graph_edgelist is not None: - cargs.extend([ - "-graph_edgelist_1D", - execution.input_file(graph_edgelist) - ]) - if onegraph: - cargs.append("-onegraph") - if multigraph: - cargs.append("-multigraph") - if split is not None: - cargs.extend([ - "-split", - str(split) - ]) - if no_history: - cargs.append("-no_history") - ret = ConvertDsetOutputs( - root=execution.output_file("."), - converted_dataset=execution.output_file(output_prefix) if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_DSET_METADATA", - "ConvertDsetOutputs", - "convert_dset", -] diff --git a/python/src/niwrap/afni/convert_surface.py b/python/src/niwrap/afni/convert_surface.py deleted file mode 100644 index 53a14244a..000000000 --- a/python/src/niwrap/afni/convert_surface.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_SURFACE_METADATA = Metadata( - id="0c666db0cc394b6bd84fde9a52f4bed0c71ffdd6.boutiques", - name="ConvertSurface", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ConvertSurfaceOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_surface(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_surface_file: OutputPathType - """The converted output surface file.""" - - -def convert_surface( - input_surface: str, - output_surface: str, - surface_volume: str | None = None, - transform_tlrc: bool = False, - mni_lpi: bool = False, - ixmat_1_d: str | None = None, - native: bool = False, - runner: Runner | None = None, -) -> ConvertSurfaceOutputs: - """ - Reads in a surface and writes it out in another format. Only fields pertinent to - SUMA are preserved. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_surface: Specifies the input surface. - output_surface: Specifies the output surface. - surface_volume: Specifies a surface volume. - transform_tlrc: Apply Talairach transform. - mni_lpi: Turn AFNI tlrc coordinates (RAI) into MNI coord space in LPI. - ixmat_1_d: Apply inverse transformation specified in 1D file. - native: Write the output surface in the coordinate system native to its\ - format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertSurfaceOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_SURFACE_METADATA) - cargs = [] - cargs.append("ConvertSurface") - cargs.extend([ - "-i", - input_surface - ]) - cargs.extend([ - "-o", - output_surface - ]) - if surface_volume is not None: - cargs.extend([ - "-sv", - surface_volume - ]) - if transform_tlrc: - cargs.append("-tlrc") - if mni_lpi: - cargs.append("-MNI_lpi") - if ixmat_1_d is not None: - cargs.extend([ - "-ixmat_1D", - ixmat_1_d - ]) - if native: - cargs.append("-native") - ret = ConvertSurfaceOutputs( - root=execution.output_file("."), - output_surface_file=execution.output_file(output_surface), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_SURFACE_METADATA", - "ConvertSurfaceOutputs", - "convert_surface", -] diff --git a/python/src/niwrap/afni/convex_hull.py b/python/src/niwrap/afni/convex_hull.py deleted file mode 100644 index 767608318..000000000 --- a/python/src/niwrap/afni/convex_hull.py +++ /dev/null @@ -1,172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVEX_HULL_METADATA = Metadata( - id="945c8df244e1356a8e523e12b46e0aa912eddb4c.boutiques", - name="ConvexHull", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ConvexHullOutputs(typing.NamedTuple): - """ - Output object returned when calling `convex_hull(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_surf: OutputPathType | None - """Output surface file""" - - -def convex_hull( - vol: InputPathType | None = None, - isoval: float | None = None, - isorange: list[float] | None = None, - isocmask: str | None = None, - xform: str | None = None, - surface_input: InputPathType | None = None, - surf_vol: InputPathType | None = None, - input_1d: InputPathType | None = None, - q_opt: str | None = None, - proj_xy: bool = False, - orig_coord: bool = False, - these_coords: InputPathType | None = None, - output_prefix: str | None = None, - debug: str | None = None, - novolreg: bool = False, - setenv: str | None = None, - runner: Runner | None = None, -) -> ConvexHullOutputs: - """ - A program to find the convex hull, or perform a Delaunay triangulation of a set - of points. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - vol: Input AFNI (or AFNI readable) volume. - isoval: Create isosurface where volume = V. - isorange: Create isosurface where V0 <= volume < V1. - isocmask: Create isosurface where MASK_COM != 0. Example: -isocmask '-a\ - VOL+orig -expr (1-bool(a-V))' is equivalent to using -isoval V. NOTE:\ - Allowed only with -xform mask. - xform: Transform to apply to volume values before searching for sign\ - change boundary. Options: mask, shift, none. - surface_input: Input surface type. - surf_vol: Specify a surface volume which contains a transform to apply\ - to the surface node coordinates. - input_1d: Construct the triangulation of the points contained in 1D\ - file XYZ. Use AFNI's [] selectors to specify the XYZ columns. - q_opt: Meshing option OPT. Options: convex_hull, triangulate_xy. - proj_xy: Project points onto plane whose normal is the third principal\ - component. Then rotate projection so that plane is parallel to Z =\ - constant. - orig_coord: Use original coordinates when writing surface, not\ - transformed ones. - these_coords: Use coordinates in COORDS.1D when writing surface. - output_prefix: Prefix of output surface. Specifies the format and\ - prefix of the surface. - debug: Debugging level. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - setenv: Set environment variable ENVname to be ENVvalue. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvexHullOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVEX_HULL_METADATA) - cargs = [] - cargs.append("ConvexHull") - if vol is not None: - cargs.extend([ - "-input", - execution.input_file(vol) - ]) - if isoval is not None: - cargs.extend([ - "-isoval", - str(isoval) - ]) - if isorange is not None: - cargs.extend([ - "-isorange", - *map(str, isorange) - ]) - if isocmask is not None: - cargs.extend([ - "-isocmask", - isocmask - ]) - if xform is not None: - cargs.extend([ - "-xform", - xform - ]) - if surface_input is not None: - cargs.extend([ - "-i_TYPE", - execution.input_file(surface_input) - ]) - if surf_vol is not None: - cargs.extend([ - "-sv", - execution.input_file(surf_vol) - ]) - if input_1d is not None: - cargs.extend([ - "-input_1D", - execution.input_file(input_1d) - ]) - if q_opt is not None: - cargs.extend([ - "-q_opt", - q_opt - ]) - if proj_xy: - cargs.append("-proj_xy") - if orig_coord: - cargs.append("-orig_coord") - if these_coords is not None: - cargs.extend([ - "-these_coords", - execution.input_file(these_coords) - ]) - if output_prefix is not None: - cargs.extend([ - "-o_TYPE", - output_prefix - ]) - if debug is not None: - cargs.extend([ - "-debug", - debug - ]) - if novolreg: - cargs.append("-novolreg") - if setenv is not None: - cargs.extend([ - "-setenv", - setenv - ]) - ret = ConvexHullOutputs( - root=execution.output_file("."), - out_surf=execution.output_file(output_prefix) if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVEX_HULL_METADATA", - "ConvexHullOutputs", - "convex_hull", -] diff --git a/python/src/niwrap/afni/count.py b/python/src/niwrap/afni/count.py deleted file mode 100644 index 6296f526c..000000000 --- a/python/src/niwrap/afni/count.py +++ /dev/null @@ -1,137 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -COUNT_METADATA = Metadata( - id="d518eb3cafe76c3d60b5e88beee05f05e59c9422.boutiques", - name="count", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CountOutputs(typing.NamedTuple): - """ - Output object returned when calling `count(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def count( - bot: str, - top: str, - step: str | None = None, - seed: float | None = None, - sseed: str | None = None, - column: bool = False, - digits: float | None = None, - form: str | None = None, - root: str | None = None, - sep: str | None = None, - suffix: str | None = None, - scale: float | None = None, - comma: bool = False, - skipnmodm: str | None = None, - runner: Runner | None = None, -) -> CountOutputs: - """ - Numbered copies generator with custom format support and random sequence - options. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - bot: Starting number or character. - top: Ending number or character. - step: Stride step or mode (integer step size, R#, S# or S). - seed: Seed number for random number generator. - sseed: Seed string for random number generator. - column: Write output, one number per line. - digits: Number of digits to print. - form: Custom format string for printing the numbers. - root: String to print before the number. - sep: Separator character between the numbers. - suffix: String to print after the number. - scale: Scale factor to multiply each number. - comma: Put commas between the outputs. - skipnmodm: Skip numbers with modulus. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CountOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(COUNT_METADATA) - cargs = [] - cargs.append("count") - cargs.append(bot) - cargs.append(top) - if step is not None: - cargs.append(step) - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - if sseed is not None: - cargs.extend([ - "-sseed", - sseed - ]) - if column: - cargs.append("-column") - if digits is not None: - cargs.extend([ - "-digits", - str(digits) - ]) - if form is not None: - cargs.extend([ - "-form", - form - ]) - if root is not None: - cargs.extend([ - "-root", - root - ]) - if sep is not None: - cargs.extend([ - "-sep", - sep - ]) - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if scale is not None: - cargs.extend([ - "-scale", - str(scale) - ]) - if comma: - cargs.append("-comma") - if skipnmodm is not None: - cargs.extend([ - "-skipnmodm", - skipnmodm - ]) - ret = CountOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "COUNT_METADATA", - "CountOutputs", - "count", -] diff --git a/python/src/niwrap/afni/create_icosahedron.py b/python/src/niwrap/afni/create_icosahedron.py deleted file mode 100644 index b943aca48..000000000 --- a/python/src/niwrap/afni/create_icosahedron.py +++ /dev/null @@ -1,115 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CREATE_ICOSAHEDRON_METADATA = Metadata( - id="1b17cec756a725d6453bb5c0f89f105427f4d2ca.boutiques", - name="CreateIcosahedron", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class CreateIcosahedronOutputs(typing.NamedTuple): - """ - Output object returned when calling `create_icosahedron(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def create_icosahedron( - rad: float | None = None, - rec_depth: float | None = None, - lin_depth: float | None = None, - min_nodes: float | None = None, - nums: bool = False, - nums_quiet: bool = False, - center_coordinates: list[float] | None = None, - to_sphere: bool = False, - output_prefix: str | None = None, - help_: bool = False, - runner: Runner | None = None, -) -> CreateIcosahedronOutputs: - """ - Tool to create an icosahedron with optional tessellation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - rad: Size of icosahedron. - rec_depth: Recursive tessellation depth for icosahedron. - lin_depth: Number of edge divides for linear icosahedron tessellation. - min_nodes: Automatically select the -ld value which produces an\ - icosahedron of at least MIN_NODES nodes. - nums: Output the number of nodes (vertices), triangles, edges, total\ - volume, and total area then quit. - nums_quiet: Output numbers in a less verbose manner. - center_coordinates: Coordinates of the center of the icosahedron. - to_sphere: Project nodes to sphere. - output_prefix: Prefix for output files. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CreateIcosahedronOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CREATE_ICOSAHEDRON_METADATA) - cargs = [] - cargs.append("CreateIcosahedron") - if rad is not None: - cargs.extend([ - "-rad", - str(rad) - ]) - if rec_depth is not None: - cargs.extend([ - "-rd", - str(rec_depth) - ]) - if lin_depth is not None: - cargs.extend([ - "-ld", - str(lin_depth) - ]) - if min_nodes is not None: - cargs.extend([ - "-min_nodes", - str(min_nodes) - ]) - if nums: - cargs.append("-nums") - if nums_quiet: - cargs.append("-nums_quiet") - if center_coordinates is not None: - cargs.extend([ - "-ctr", - *map(str, center_coordinates) - ]) - if to_sphere: - cargs.append("-tosphere") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if help_: - cargs.append("-help") - ret = CreateIcosahedronOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CREATE_ICOSAHEDRON_METADATA", - "CreateIcosahedronOutputs", - "create_icosahedron", -] diff --git a/python/src/niwrap/afni/dcm2niix_afni.py b/python/src/niwrap/afni/dcm2niix_afni.py deleted file mode 100644 index e6d2758ea..000000000 --- a/python/src/niwrap/afni/dcm2niix_afni.py +++ /dev/null @@ -1,259 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DCM2NIIX_AFNI_METADATA = Metadata( - id="2b048e6ed8405f5110cc5399162aab212faa5c72.boutiques", - name="dcm2niix_afni", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Dcm2niixAfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `dcm2niix_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - nifti_files: OutputPathType - """The main output NIfTI files""" - - -def dcm2niix_afni( - input_folder: str, - compression_level: int | None = None, - adjacent_dicoms: str | None = None, - bids_sidecar: str | None = None, - anonymize_bids: str | None = None, - comment: str | None = None, - directory_search_depth: int | None = None, - export_format: str | None = None, - filename_template: str | None = None, - generate_defaults: str | None = None, - ignore_images: str | None = None, - lossless_scale: str | None = None, - merge_slices: str | None = None, - series_crc_number: list[str] | None = None, - output_directory: str | None = None, - phillips_scaling: str | None = None, - rename_dicoms: str | None = None, - single_file_mode: str | None = None, - up_to_date: bool = False, - verbose: str | None = None, - write_behavior: int | None = None, - crop_3d: str | None = None, - gz_compress: str | None = None, - big_endian: str | None = None, - progress: str | None = None, - ignore_trigger_times: bool = False, - terse: bool = False, - version: bool = False, - xml_: bool = False, - runner: Runner | None = None, -) -> Dcm2niixAfniOutputs: - """ - DICOM to NIfTI converter optimized for AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_folder: Folder containing DICOM files. - compression_level: GZ compression level (1=fastest..9=smallest, default\ - 6). - adjacent_dicoms: Adjacent DICOMs (images from same series always in\ - same folder) for faster conversion (n/y, default n). - bids_sidecar: BIDS sidecar (y/n/o [o=only: no NIfTI], default y). - anonymize_bids: Anonymize BIDS (y/n, default y). - comment: Comment stored in NIfTI aux_file (provide up to 24 characters\ - e.g. '-c first_visit'). - directory_search_depth: Directory search depth. Convert DICOMs in\ - sub-folders of in_folder? (0..9, default 5). - export_format: Export as NRRD (y) or MGH (o) instead of NIfTI (y/n/o,\ - default n). - filename_template: Filename template for output (default '%f_%p_%t_%s'). - generate_defaults: Generate defaults file (y/n/o/i [o=only: reset and\ - write defaults; i=ignore: reset defaults], default n). - ignore_images: Ignore derived, localizer and 2D images (y/n, default n). - lossless_scale: Losslessly scale 16-bit integers to use dynamic range\ - (y/n/o, default o). - merge_slices: Merge 2D slices from same series regardless of echo,\ - exposure, etc. (n/y or 0/1/2, default 2). - series_crc_number: Only convert this series CRC number - can be used up\ - to 16 times (default convert all). - output_directory: Output directory (omit to save to input folder). - phillips_scaling: Philips precise float (not display) scaling (y/n,\ - default y). - rename_dicoms: Rename instead of convert DICOMs (y/n, default n). - single_file_mode: Single file mode, do not convert other images in\ - folder (y/n, default n). - up_to_date: Up-to-date check. - verbose: Verbose (n/y or 0/1/2, default 0). - write_behavior: Write behavior for name conflicts (0=skip duplicates,\ - 1=overwrite, 2=add suffix). - crop_3d: Crop 3D acquisitions (y/n/i, default n, use 'i'gnore to\ - neither crop nor rotate 3D acquisitions). - gz_compress: GZ compress images (y/o/i/n/3, default n) [y=pigz,\ - o=optimal pigz, i=internal:miniz, n=no, 3=no,3D]. - big_endian: Byte order (y/n/o, default o) [y=big-endian,\ - n=little-endian, o=optimal/native]. - progress: Slicer format progress information (y/n, default n). - ignore_trigger_times: Disregard values in 0018, 1060 and 0020, 9153. - terse: Omit filename post-fixes (can cause overwrites). - version: Report version. - xml_: Slicer format features. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Dcm2niixAfniOutputs`). - """ - if series_crc_number is not None and not (len(series_crc_number) <= 16): - raise ValueError(f"Length of 'series_crc_number' must be less than 16 but was {len(series_crc_number)}") - runner = runner or get_global_runner() - execution = runner.start_execution(DCM2NIIX_AFNI_METADATA) - cargs = [] - cargs.append("dcm2niix_afni") - cargs.append(input_folder) - if compression_level is not None: - cargs.extend([ - "-1..-9", - str(compression_level) - ]) - if adjacent_dicoms is not None: - cargs.extend([ - "-a", - adjacent_dicoms - ]) - if bids_sidecar is not None: - cargs.extend([ - "-b", - bids_sidecar - ]) - if anonymize_bids is not None: - cargs.extend([ - "-ba", - anonymize_bids - ]) - if comment is not None: - cargs.extend([ - "-c", - comment - ]) - if directory_search_depth is not None: - cargs.extend([ - "-d", - str(directory_search_depth) - ]) - if export_format is not None: - cargs.extend([ - "-e", - export_format - ]) - if filename_template is not None: - cargs.extend([ - "-f", - filename_template - ]) - if generate_defaults is not None: - cargs.extend([ - "-g", - generate_defaults - ]) - if ignore_images is not None: - cargs.extend([ - "-i", - ignore_images - ]) - if lossless_scale is not None: - cargs.extend([ - "-l", - lossless_scale - ]) - if merge_slices is not None: - cargs.extend([ - "-m", - merge_slices - ]) - if series_crc_number is not None: - cargs.extend([ - "-n", - *series_crc_number - ]) - if output_directory is not None: - cargs.extend([ - "-o", - output_directory - ]) - if phillips_scaling is not None: - cargs.extend([ - "-p", - phillips_scaling - ]) - if rename_dicoms is not None: - cargs.extend([ - "-r", - rename_dicoms - ]) - if single_file_mode is not None: - cargs.extend([ - "-s", - single_file_mode - ]) - if up_to_date: - cargs.append("-u") - if verbose is not None: - cargs.extend([ - "-v", - verbose - ]) - if write_behavior is not None: - cargs.extend([ - "-w", - str(write_behavior) - ]) - if crop_3d is not None: - cargs.extend([ - "-x", - crop_3d - ]) - if gz_compress is not None: - cargs.extend([ - "-z", - gz_compress - ]) - if big_endian is not None: - cargs.extend([ - "--big-endian", - big_endian - ]) - if progress is not None: - cargs.extend([ - "--progress", - progress - ]) - if ignore_trigger_times: - cargs.append("--ignore_trigger_times") - if terse: - cargs.append("--terse") - if version: - cargs.append("--version") - if xml_: - cargs.append("--xml") - ret = Dcm2niixAfniOutputs( - root=execution.output_file("."), - nifti_files=execution.output_file("/*.nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DCM2NIIX_AFNI_METADATA", - "Dcm2niixAfniOutputs", - "dcm2niix_afni", -] diff --git a/python/src/niwrap/afni/dicom_hdr.py b/python/src/niwrap/afni/dicom_hdr.py deleted file mode 100644 index 0f3e89e36..000000000 --- a/python/src/niwrap/afni/dicom_hdr.py +++ /dev/null @@ -1,100 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DICOM_HDR_METADATA = Metadata( - id="f1dd7c5e97c664a21c6f4e09518ffc5513e4e54f.boutiques", - name="dicom_hdr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DicomHdrOutputs(typing.NamedTuple): - """ - Output object returned when calling `dicom_hdr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def dicom_hdr( - files: list[InputPathType], - hex_: bool = False, - noname: bool = False, - sexinfo: bool = False, - mulfram: bool = False, - v_dump: float | None = None, - no_length: bool = False, - slice_times: bool = False, - slice_times_verb: bool = False, - siemens_csa_data: bool = False, - runner: Runner | None = None, -) -> DicomHdrOutputs: - """ - A tool to print DICOM file information to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: DICOM file(s) to read. - hex_: Include hexadecimal printout for integer values. - noname: Don't include element names in the printout. - sexinfo: Dump Siemens EXtra INFO text (0029 1020), if present (can be\ - VERY lengthy). - mulfram: Dump multi-frame information, if present (1 line per frame,\ - plus an XML-style header/footer). This option also implies -noname. - v_dump: Dump n words of binary data also. - no_length: Skip lengths and offsets (helps diffs). - slice_times: Show slice times from Siemens mosaic images. - slice_times_verb: Show slice times from Siemens mosaic images\ - verbosely. (multiple uses increase verbosity, can dump CSA data). - siemens_csa_data: Same as 3 -slice_times_verb opts. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DicomHdrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DICOM_HDR_METADATA) - cargs = [] - cargs.append("dicom_hdr") - cargs.extend([execution.input_file(f) for f in files]) - if hex_: - cargs.append("-hex") - if noname: - cargs.append("-noname") - if sexinfo: - cargs.append("-sexinfo") - if mulfram: - cargs.append("-mulfram") - if v_dump is not None: - cargs.extend([ - "-v", - str(v_dump) - ]) - if no_length: - cargs.append("-no_length") - if slice_times: - cargs.append("-slice_times") - if slice_times_verb: - cargs.append("-slice_times_verb") - if siemens_csa_data: - cargs.append("-siemens_csa_data") - ret = DicomHdrOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DICOM_HDR_METADATA", - "DicomHdrOutputs", - "dicom_hdr", -] diff --git a/python/src/niwrap/afni/dicom_hinfo.py b/python/src/niwrap/afni/dicom_hinfo.py deleted file mode 100644 index 5b3db91a2..000000000 --- a/python/src/niwrap/afni/dicom_hinfo.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DICOM_HINFO_METADATA = Metadata( - id="b4e332870ec766036b07e84e159257d3b9ab3eb2.boutiques", - name="dicom_hinfo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DicomHinfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `dicom_hinfo(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def dicom_hinfo( - tag: list[str], - sepstr: str | None = None, - full_entry: bool = False, - no_name: bool = False, - namelast: bool = False, - runner: Runner | None = None, -) -> DicomHinfoOutputs: - """ - Prints selected information from one or more DICOM files to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tag: Specify one or more DICOM tags to print, in the format aaaa,bbbb\ - where aaaa and bbbb are hexadecimal digits. - sepstr: Use the specified string to separate fields instead of space. - full_entry: Output the full entry if it is more than one word or\ - contains white space. - no_name: Omit the filename from the output. - namelast: Place the filename last in the output instead of first. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DicomHinfoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DICOM_HINFO_METADATA) - cargs = [] - cargs.append("dicom_hinfo") - cargs.extend([ - "-tag", - *tag - ]) - if sepstr is not None: - cargs.extend([ - "-sepstr", - sepstr - ]) - if full_entry: - cargs.append("-full_entry") - if no_name: - cargs.append("-no_name") - if namelast: - cargs.append("-namelast") - cargs.append("[FILES...]") - ret = DicomHinfoOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DICOM_HINFO_METADATA", - "DicomHinfoOutputs", - "dicom_hinfo", -] diff --git a/python/src/niwrap/afni/dicom_to_raw.py b/python/src/niwrap/afni/dicom_to_raw.py deleted file mode 100644 index a29d78ed2..000000000 --- a/python/src/niwrap/afni/dicom_to_raw.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DICOM_TO_RAW_METADATA = Metadata( - id="7eb027b7c5690d1e6ebc29a721254ed558470f1d.boutiques", - name="dicom_to_raw", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DicomToRawOutputs(typing.NamedTuple): - """ - Output object returned when calling `dicom_to_raw(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_raw_file: OutputPathType - """Output raw file(s)""" - - -def dicom_to_raw( - input_dicom: InputPathType, - runner: Runner | None = None, -) -> DicomToRawOutputs: - """ - Reads images from DICOM file and writes them to raw file(s). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dicom: Input DICOM file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DicomToRawOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DICOM_TO_RAW_METADATA) - cargs = [] - cargs.append("dicom_to_raw") - cargs.append(execution.input_file(input_dicom)) - ret = DicomToRawOutputs( - root=execution.output_file("."), - output_raw_file=execution.output_file(pathlib.Path(input_dicom).name + ".raw.0001"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DICOM_TO_RAW_METADATA", - "DicomToRawOutputs", - "dicom_to_raw", -] diff --git a/python/src/niwrap/afni/dimon.py b/python/src/niwrap/afni/dimon.py deleted file mode 100644 index 9d41ebcd2..000000000 --- a/python/src/niwrap/afni/dimon.py +++ /dev/null @@ -1,123 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DIMON_METADATA = Metadata( - id="47141d28c3f7ccd9b2aa834d602f55feeab89023.boutiques", - name="Dimon", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DimonOutputs(typing.NamedTuple): - """ - Output object returned when calling `dimon(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - sorted_files: OutputPathType - """Sorted input files with specified prefix""" - sorted_files_details: OutputPathType | None - """Details about sorted files""" - - -def dimon( - infile_prefix: str, - infile_pattern: str | None = None, - infile_list: InputPathType | None = None, - rt_cmd: str | None = None, - host: str | None = None, - drive_afni: str | None = None, - drive_wait: str | None = None, - te_list: str | None = None, - sort_method: str | None = None, - runner: Runner | None = None, -) -> DimonOutputs: - """ - Monitor real-time acquisition of DICOM image files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile_prefix: Prefix matching input files. - infile_pattern: Pattern for input files. - infile_list: List of filenames. - rt_cmd: Send COMMAND(s) to realtime plugin. - host: Specify the host for afni communication. - drive_afni: Send 'drive afni' command, CMND. - drive_wait: Send delayed 'drive afni' command, CMND. - te_list: Specify a list of echo times. - sort_method: Apply sorting method to image structures. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DimonOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DIMON_METADATA) - cargs = [] - cargs.append("Dimon") - cargs.extend([ - "-infile_prefix", - infile_prefix - ]) - if infile_pattern is not None: - cargs.extend([ - "-infile_pattern", - infile_pattern - ]) - if infile_list is not None: - cargs.extend([ - "-infile_list", - execution.input_file(infile_list) - ]) - if rt_cmd is not None: - cargs.extend([ - "-rt_cmd", - rt_cmd - ]) - if host is not None: - cargs.extend([ - "-host", - host - ]) - if drive_afni is not None: - cargs.extend([ - "-drive_afni", - drive_afni - ]) - if drive_wait is not None: - cargs.extend([ - "-drive_wait", - drive_wait - ]) - if te_list is not None: - cargs.extend([ - "-te_list", - te_list - ]) - if sort_method is not None: - cargs.extend([ - "-sort_method", - sort_method - ]) - ret = DimonOutputs( - root=execution.output_file("."), - sorted_files=execution.output_file(infile_prefix + "*"), - sorted_files_details=execution.output_file(pathlib.Path(infile_list).name + "_details") if (infile_list is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DIMON_METADATA", - "DimonOutputs", - "dimon", -] diff --git a/python/src/niwrap/afni/djpeg.py b/python/src/niwrap/afni/djpeg.py deleted file mode 100644 index c11503ac9..000000000 --- a/python/src/niwrap/afni/djpeg.py +++ /dev/null @@ -1,87 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DJPEG_METADATA = Metadata( - id="c95201e76f8579869e021a74a6d5d17f69dd1c84.boutiques", - name="djpeg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DjpegOutputs(typing.NamedTuple): - """ - Output object returned when calling `djpeg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """Output image file""" - - -def djpeg( - input_file: InputPathType, - output_file: str, - gray: bool = False, - fast_dct: bool = False, - one_pixel_height: bool = False, - pseudo_pixel_ratio: bool = False, - crop_region: str | None = None, - runner: Runner | None = None, -) -> DjpegOutputs: - """ - Decompress a JPEG file to an image file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input JPEG file (e.g. image.jpg). - output_file: Output image file (e.g. image.ppm). - gray: Force grayscale output. - fast_dct: Prevent dithering of output. - one_pixel_height: Force one-pixel modulation flag. - pseudo_pixel_ratio: Force pseudo-pixel ratio flag. - crop_region: Crop region (syntax: WxH+X+Y, e.g., 100x100+10+10). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DjpegOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DJPEG_METADATA) - cargs = [] - cargs.append("djpeg") - cargs.append(execution.input_file(input_file)) - cargs.append(output_file) - if gray: - cargs.append("-grayscale") - if fast_dct: - cargs.append("-fast") - if one_pixel_height: - cargs.append("-onepixel") - if pseudo_pixel_ratio: - cargs.append("-236") - if crop_region is not None: - cargs.extend([ - "-crop", - crop_region - ]) - ret = DjpegOutputs( - root=execution.output_file("."), - output_image=execution.output_file(output_file), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DJPEG_METADATA", - "DjpegOutputs", - "djpeg", -] diff --git a/python/src/niwrap/afni/drive_suma.py b/python/src/niwrap/afni/drive_suma.py deleted file mode 100644 index 888ab1242..000000000 --- a/python/src/niwrap/afni/drive_suma.py +++ /dev/null @@ -1,236 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DRIVE_SUMA_METADATA = Metadata( - id="926f692f4116a5424cd5bd01a3b09ea3e0539288.boutiques", - name="DriveSuma", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DriveSumaOutputs(typing.NamedTuple): - """ - Output object returned when calling `drive_suma(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def drive_suma( - command: str, - surf_label: str | None = None, - surface_file: InputPathType | None = None, - surf_state: str | None = None, - surf_winding: str | None = None, - coordinates: InputPathType | None = None, - autorecord: str | None = None, - background_color: str | None = None, - view_file: InputPathType | None = None, - do_file: InputPathType | None = None, - do_draw_mask: str | None = None, - fixed_do: str | None = None, - mobile_do: str | None = None, - key_press: str | None = None, - viewer: str | None = None, - anim_dup: float | None = None, - save_as: str | None = None, - save_index: float | None = None, - save_range: str | None = None, - save_last: bool = False, - save_last_n: float | None = None, - save_all: bool = False, - echo_edu: bool = False, - echo_nel_stdout: bool = False, - echo_nel_stderr: bool = False, - examples: bool = False, - help_: bool = False, - h: bool = False, - help_nido: bool = False, - c_demo: bool = False, - viewer_cont: bool = False, - runner: Runner | None = None, -) -> DriveSumaOutputs: - """ - A program to drive suma from the command line. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - command: Command to be sent to SUMA. - surf_label: A label (identifier) to assign to the surface. - surface_file: Name of surface file. - surf_state: Name the state of that surface. - surf_winding: Winding of triangles (ccw or cw). - coordinates: A 1D formatted file containing new coordinates for nodes. - autorecord: Set the autorecord prefix. - background_color: Set the background color (R G B). - view_file: Load a previously saved view file. - do_file: Load a displayable object file. - do_draw_mask: Restrict where DO node-based objects are displayed. - fixed_do: Load a fixed coordinate type NIML DO. - mobile_do: Mobile version of fixed_do. - key_press: Act as if a key press was applied in the viewer. - viewer: Specify which viewer should be acted upon. - anim_dup: Save DUP copies of each frame into movie. - save_as: Save image(s) in recorder in specified format. - save_index: Save one image indexed IND. - save_range: Save images from FROM to TO. - save_last: Save last image. - save_last_n: Save last N images. - save_all: Save all images. - echo_edu: Echoes the entire command line for edification purposes. - echo_nel_stdout: Spit out the NIML object being sent to SUMA to stdout. - echo_nel_stderr: Spit out the NIML object being sent to SUMA to stderr. - examples: Show all the sample commands and exit. - help_: Show the help in detail. - h: Show help with slightly less detail. - help_nido: Show the help for NIML Displayable Objects and exit. - c_demo: Execute a preset number of commands to illustrate how one can\ - communicate with SUMA from one's own C code. - viewer_cont: Apply settings to viewer or viewer controller. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DriveSumaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DRIVE_SUMA_METADATA) - cargs = [] - cargs.append("DriveSuma") - cargs.append(command) - if surf_label is not None: - cargs.extend([ - "-surf_label", - surf_label - ]) - if surface_file is not None: - cargs.extend([ - "-i_TYPE", - execution.input_file(surface_file) - ]) - if surf_state is not None: - cargs.extend([ - "-surf_state", - surf_state - ]) - if surf_winding is not None: - cargs.extend([ - "-surf_winding", - surf_winding - ]) - if coordinates is not None: - cargs.extend([ - "-xyz_1D", - execution.input_file(coordinates) - ]) - if autorecord is not None: - cargs.extend([ - "-autorecord", - autorecord - ]) - if background_color is not None: - cargs.extend([ - "-bkg_col", - background_color - ]) - if view_file is not None: - cargs.extend([ - "-load_view", - execution.input_file(view_file) - ]) - if do_file is not None: - cargs.extend([ - "-load_do", - execution.input_file(do_file) - ]) - if do_draw_mask is not None: - cargs.extend([ - "-do_draw_mask", - do_draw_mask - ]) - if fixed_do is not None: - cargs.extend([ - "-fixed_do", - fixed_do - ]) - if mobile_do is not None: - cargs.extend([ - "-mobile_do", - mobile_do - ]) - if key_press is not None: - cargs.extend([ - "-key", - key_press - ]) - if viewer is not None: - cargs.extend([ - "-viewer", - viewer - ]) - if anim_dup is not None: - cargs.extend([ - "-anim_dup", - str(anim_dup) - ]) - if save_as is not None: - cargs.extend([ - "-save_as", - save_as - ]) - if save_index is not None: - cargs.extend([ - "-save_index", - str(save_index) - ]) - if save_range is not None: - cargs.extend([ - "-save_range", - save_range - ]) - if save_last: - cargs.append("-save_last") - if save_last_n is not None: - cargs.extend([ - "-save_last_n", - str(save_last_n) - ]) - if save_all: - cargs.append("-save_all") - if echo_edu: - cargs.append("-echo_edu") - if echo_nel_stdout: - cargs.append("-echo_nel_stdout") - if echo_nel_stderr: - cargs.append("-echo_nel_stderr") - if examples: - cargs.append("-examples") - if help_: - cargs.append("-help") - if h: - cargs.append("-h") - if help_nido: - cargs.append("-help_nido") - if c_demo: - cargs.append("-C_demo") - if viewer_cont: - cargs.append("-com viewer_cont") - ret = DriveSumaOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DRIVE_SUMA_METADATA", - "DriveSumaOutputs", - "drive_suma", -] diff --git a/python/src/niwrap/afni/dsetstat2p.py b/python/src/niwrap/afni/dsetstat2p.py deleted file mode 100644 index 4147e00a4..000000000 --- a/python/src/niwrap/afni/dsetstat2p.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DSETSTAT2P_METADATA = Metadata( - id="c5c1a464fb7aea2f28d11cf8382423aa8937d801.boutiques", - name="dsetstat2p", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Dsetstat2pOutputs(typing.NamedTuple): - """ - Output object returned when calling `dsetstat2p(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output p-value or stat value""" - - -def dsetstat2p( - dataset: str, - statval: float, - one_sided: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> Dsetstat2pOutputs: - """ - Converts a statistic to a p-value with reference to a particular dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Specify a dataset DDD and, if it has multiple sub-bricks, the\ - [i]th subbrick with the statistic of interest MUST be selected\ - explicitly; note the use of quotation marks around the brick selector\ - (because of the square-brackets). Note that 'i' can be either a number\ - of a string label selector. - statval: Input stat-value S, which MUST be in the interval [0,\ - infinity). - one_sided: Choose one-sided or bi-sided/two-sided testing. - quiet: An optional flag so that output ONLY the final statistic value\ - output to standard output; this can be then be viewed, redirected to a\ - text file or saved as a shell variable. (Default: display supplementary\ - text.). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Dsetstat2pOutputs`). - """ - if not (0 <= statval): - raise ValueError(f"'statval' must be greater than 0 <= x but was {statval}") - runner = runner or get_global_runner() - execution = runner.start_execution(DSETSTAT2P_METADATA) - cargs = [] - cargs.append("dsetstat2p") - cargs.append(dataset) - cargs.append(str(statval)) - if one_sided: - cargs.append("-1sided") - if quiet: - cargs.append("-quiet") - ret = Dsetstat2pOutputs( - root=execution.output_file("."), - output_file=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DSETSTAT2P_METADATA", - "Dsetstat2pOutputs", - "dsetstat2p", -] diff --git a/python/src/niwrap/afni/dtistudio_fiberto_segments.py b/python/src/niwrap/afni/dtistudio_fiberto_segments.py deleted file mode 100644 index aa859993f..000000000 --- a/python/src/niwrap/afni/dtistudio_fiberto_segments.py +++ /dev/null @@ -1,72 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DTISTUDIO_FIBERTO_SEGMENTS_METADATA = Metadata( - id="3f18eb1cd61025f3b6f243c49c95ab75c9ad86a9.boutiques", - name="DTIStudioFibertoSegments", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class DtistudioFibertoSegmentsOutputs(typing.NamedTuple): - """ - Output object returned when calling `dtistudio_fiberto_segments(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_segment_file: OutputPathType | None - """Output SUMA segment file""" - - -def dtistudio_fiberto_segments( - dataset: InputPathType, - output_file: str | None = None, - swap_flag: bool = False, - runner: Runner | None = None, -) -> DtistudioFibertoSegmentsOutputs: - """ - Convert a DTIStudio Fiber file to a SUMA segment file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset file. - output_file: Name of the output file (default is rawxyzseg.dat). - swap_flag: Swap bytes in data. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DtistudioFibertoSegmentsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DTISTUDIO_FIBERTO_SEGMENTS_METADATA) - cargs = [] - cargs.append("DTIStudioFibertoSegments") - cargs.append(execution.input_file(dataset)) - if output_file is not None: - cargs.extend([ - "-output", - output_file - ]) - if swap_flag: - cargs.append("-swap") - ret = DtistudioFibertoSegmentsOutputs( - root=execution.output_file("."), - output_segment_file=execution.output_file(output_file) if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DTISTUDIO_FIBERTO_SEGMENTS_METADATA", - "DtistudioFibertoSegmentsOutputs", - "dtistudio_fiberto_segments", -] diff --git a/python/src/niwrap/afni/epi_b0_correct.py b/python/src/niwrap/afni/epi_b0_correct.py deleted file mode 100644 index 9297c2a05..000000000 --- a/python/src/niwrap/afni/epi_b0_correct.py +++ /dev/null @@ -1,227 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -EPI_B0_CORRECT_METADATA = Metadata( - id="690e7b1a6986e67ced0f065ca6d025cd2006e8eb.boutiques", - name="epi_b0_correct", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class EpiB0CorrectOutputs(typing.NamedTuple): - """ - Output object returned when calling `epi_b0_correct(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warp_dset: OutputPathType - """Warp dataset containing the warp along the phase encode axis.""" - cmds_script: OutputPathType - """Script of the commands used to generate the warp and process the EPI.""" - params_txt: OutputPathType - """Text file of parameters input or derived from datasets.""" - unwarped_epi: OutputPathType - """EPI dataset with estimated distortion correction applied.""" - qc_image_dir: OutputPathType - """Directory containing QC images.""" - - -def epi_b0_correct( - prefix: str, - input_freq: InputPathType, - input_epi: InputPathType, - epi_pe_dir: str, - input_mask: InputPathType | None = None, - input_magn: InputPathType | None = None, - input_anat: InputPathType | None = None, - input_json: InputPathType | None = None, - epi_pe_bwpp: float | None = None, - epi_pe_echo_sp: float | None = None, - epi_pe_vox_dim: float | None = None, - scale_freq: float | None = None, - out_cmds: str | None = None, - out_pars: str | None = None, - wdir_name: str | None = None, - blur_sigma: float | None = None, - do_recenter_freq: str | None = None, - mask_dilate: list[float] | None = None, - no_clean: bool = False, - qc_box_focus_ulay: bool = False, - no_qc_image: bool = False, - help_: bool = False, - ver: bool = False, - date: bool = False, - runner: Runner | None = None, -) -> EpiB0CorrectOutputs: - """ - B0 distortion correction tool using an acquired frequency (phase) image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix of output files; can include path. - input_freq: Phase dataset (frequency volume); should be at similar\ - resolution and FOV as the EPI dataset; must be scaled appropriately. - input_epi: EPI dataset to which B0 distortion correction will be\ - applied. - epi_pe_dir: Direction (axis) of phase encoding, e.g., AP, PA, RL, ... - input_mask: Mask of brain volume. - input_magn: Magnitude dataset from which to estimate brain mask; can be\ - used for QC imaging. - input_anat: Anatomical dataset to be used as underlay for QC images\ - (optional). - input_json: JSON file containing parameters about the EPI dataset. - epi_pe_bwpp: Bandwidth per pixel (in Hz) in the EPI dataset along the\ - phase encode direction. - epi_pe_echo_sp: Effective TE spacing of the phase encoded volume, in\ - seconds. - epi_pe_vox_dim: Voxel size along the EPI dataset's phase encode axis,\ - in mm. - scale_freq: Scale to apply to frequency volume to match units (def:\ - SF=1.0). - out_cmds: Name for output script recording commands (def:\ - PREFIX_cmds.tcsh). - out_pars: Name for output text file recording relevant parameters (def:\ - PREFIX_pars.txt). - wdir_name: Working directory name (def: automatic name). - blur_sigma: Amount of blurring to apply to masked phase encode dataset\ - (def: BS=9). - do_recenter_freq: Method to recenter the phase volume within the brain\ - mask (def: MC=mode). - mask_dilate: Erosion and dilation parameters for automask (when using\ - magnitude image). - no_clean: Don't remove the temporary directory of intermediate files. - qc_box_focus_ulay: Focus the QC images on an automask region of the\ - underlay dataset. - no_qc_image: Don't generate QC images. - help_: Display program help in terminal. - ver: Display program version number in terminal. - date: Display date of program's last update in terminal. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `EpiB0CorrectOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(EPI_B0_CORRECT_METADATA) - cargs = [] - cargs.append("epi_b0_correct.py") - cargs.append(prefix) - cargs.extend([ - "-in_freq", - execution.input_file(input_freq) - ]) - cargs.extend([ - "-in_epi", - execution.input_file(input_epi) - ]) - if input_mask is not None: - cargs.extend([ - "-in_mask", - execution.input_file(input_mask) - ]) - if input_magn is not None: - cargs.extend([ - "-in_magn", - execution.input_file(input_magn) - ]) - if input_anat is not None: - cargs.extend([ - "-in_anat", - execution.input_file(input_anat) - ]) - if input_json is not None: - cargs.extend([ - "-in_epi_json", - execution.input_file(input_json) - ]) - cargs.extend([ - "-epi_pe_dir", - epi_pe_dir - ]) - if epi_pe_bwpp is not None: - cargs.extend([ - "-epi_pe_bwpp", - str(epi_pe_bwpp) - ]) - if epi_pe_echo_sp is not None: - cargs.extend([ - "-epi_pe_echo_sp", - str(epi_pe_echo_sp) - ]) - if epi_pe_vox_dim is not None: - cargs.extend([ - "-epi_pe_voxdim", - str(epi_pe_vox_dim) - ]) - if scale_freq is not None: - cargs.extend([ - "-scale_freq", - str(scale_freq) - ]) - if out_cmds is not None: - cargs.extend([ - "-out_cmds", - out_cmds - ]) - if out_pars is not None: - cargs.extend([ - "-out_pars", - out_pars - ]) - if wdir_name is not None: - cargs.extend([ - "-wdir_name", - wdir_name - ]) - if blur_sigma is not None: - cargs.extend([ - "-blur_sigma", - str(blur_sigma) - ]) - if do_recenter_freq is not None: - cargs.extend([ - "-do_recenter_freq", - do_recenter_freq - ]) - if mask_dilate is not None: - cargs.extend([ - "-mask_dilate", - *map(str, mask_dilate) - ]) - if no_clean: - cargs.append("-no_clean") - if qc_box_focus_ulay: - cargs.append("-qc_box_focus_ulay") - if no_qc_image: - cargs.append("-no_qc_image") - if help_: - cargs.append("-help") - if ver: - cargs.append("-ver") - if date: - cargs.append("-date") - ret = EpiB0CorrectOutputs( - root=execution.output_file("."), - warp_dset=execution.output_file(prefix + "_WARP.nii.gz"), - cmds_script=execution.output_file(prefix + "_cmds.tcsh"), - params_txt=execution.output_file(prefix + "_pars.txt"), - unwarped_epi=execution.output_file(prefix + "_unwarped.nii.gz"), - qc_image_dir=execution.output_file(prefix + "_QC/"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "EPI_B0_CORRECT_METADATA", - "EpiB0CorrectOutputs", - "epi_b0_correct", -] diff --git a/python/src/niwrap/afni/examine_xmat.py b/python/src/niwrap/afni/examine_xmat.py deleted file mode 100644 index 55f1801bf..000000000 --- a/python/src/niwrap/afni/examine_xmat.py +++ /dev/null @@ -1,124 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -EXAMINE_XMAT_METADATA = Metadata( - id="c3ca745374e5b2ec795b4eaa035b59e875ce2c61.boutiques", - name="ExamineXmat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ExamineXmatOutputs(typing.NamedTuple): - """ - Output object returned when calling `examine_xmat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - plot_image: OutputPathType | None - """Output plot image""" - plot_image_png: OutputPathType | None - """Output plot image""" - plot_image_pdf: OutputPathType | None - """Output plot image""" - cor_image: OutputPathType | None - """Output cor image""" - plot_image_prefix: OutputPathType | None - """Output plot image""" - - -def examine_xmat( - input_file: InputPathType | None = None, - interactive: bool = False, - prefix: str | None = None, - cprefix: str | None = None, - pprefix: str | None = None, - select_: str | None = None, - msg_trace: bool = False, - verbosity: float | None = None, - runner: Runner | None = None, -) -> ExamineXmatOutputs: - """ - A program for examining the design matrix generated by 3dDeconvolve. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: xmat file to plot. - interactive: Run ExamineXmat in interactive mode. This is the default\ - if -prefix is not given. If -interactive is used with -prefix, the last\ - plot you see is the plot saved to file. - prefix: Prefix of plot image and cor image. - cprefix: Prefix of cor image only. - pprefix: Prefix of plot image only. - select_: What to plot. Selection strings to specify regressors. - msg_trace: Output trace information along with errors and notices. - verbosity: Verbosity level. 0 for quiet, 1 or more for talkative. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ExamineXmatOutputs`). - """ - if verbosity is not None and not (0 <= verbosity): - raise ValueError(f"'verbosity' must be greater than 0 <= x but was {verbosity}") - runner = runner or get_global_runner() - execution = runner.start_execution(EXAMINE_XMAT_METADATA) - cargs = [] - cargs.append("ExamineXmat") - if input_file is not None: - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if interactive: - cargs.append("-interactive") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if cprefix is not None: - cargs.extend([ - "-cprefix", - cprefix - ]) - if pprefix is not None: - cargs.extend([ - "-pprefix", - pprefix - ]) - if select_ is not None: - cargs.extend([ - "-select", - select_ - ]) - if msg_trace: - cargs.append("-msg.trace") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = ExamineXmatOutputs( - root=execution.output_file("."), - plot_image=execution.output_file(prefix + ".jpg") if (prefix is not None) else None, - plot_image_png=execution.output_file(prefix + ".png") if (prefix is not None) else None, - plot_image_pdf=execution.output_file(prefix + ".pdf") if (prefix is not None) else None, - cor_image=execution.output_file(cprefix + ".jpg") if (cprefix is not None) else None, - plot_image_prefix=execution.output_file(pprefix + ".jpg") if (pprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "EXAMINE_XMAT_METADATA", - "ExamineXmatOutputs", - "examine_xmat", -] diff --git a/python/src/niwrap/afni/fat_mat2d_plot_py.py b/python/src/niwrap/afni/fat_mat2d_plot_py.py deleted file mode 100644 index ebe0f23d5..000000000 --- a/python/src/niwrap/afni/fat_mat2d_plot_py.py +++ /dev/null @@ -1,168 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MAT2D_PLOT_PY_METADATA = Metadata( - id="4a1c04bfb1114a4c4dfde20fda4aea87cabad529.boutiques", - name="fat_mat2d_plot.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMat2dPlotPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mat2d_plot_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType | None - """Individual image files of matrices; these can contain colorbars, as - well.""" - - -def fat_mat2d_plot_py( - input_file: InputPathType, - matrices: list[str] | None = None, - prefix: str | None = None, - file_type: str | None = None, - dpi: float | None = None, - min_colorbar: float | None = None, - max_colorbar: float | None = None, - fs_xticks: float | None = None, - fs_yticks: float | None = None, - fs_title: float | None = None, - fs_cbar: float | None = None, - cbar_n_intervals: float | None = None, - cbar: str | None = None, - cbar_width_perc: float | None = None, - no_colorbar: bool = False, - figsize_x: float | None = None, - figsize_y: float | None = None, - hold_image: bool = False, - tight_layout: bool = False, - xticks_off: bool = False, - yticks_off: bool = False, - version: bool = False, - date: bool = False, - help_: bool = False, - help_view: bool = False, - runner: Runner | None = None, -) -> FatMat2dPlotPyOutputs: - """ - Plots simple matrices output from 3dNetCorr (*.netcc) and 3dTrackID (*.grid). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Name of *.netcc or *.grid file with matrices to be plotted. - matrices: List of matrices to be plotted, identified by their parameter\ - name. If no list is provided, then all matrices in the input file will\ - be plotted. - prefix: Output basename for image(s). Note that this can include path\ - information, but the name of each matrix and the file extension will be\ - appended to it. - file_type: Filetype, given as extension (e.g., png, jpg). Available\ - filetypes depend slightly on your OS and setup. - dpi: Spatial resolution (dots per inch) of output images. - min_colorbar: Minimum value of the colorbar. - max_colorbar: Maximum value of the colorbar. - fs_xticks: Font size of ticks along the x-axis. - fs_yticks: Font size of ticks along the y-axis. - fs_title: Font size of the title. - fs_cbar: Font size of the colorbar. - cbar_n_intervals: Number of intervals on colorbars for enumeration\ - purposes. This controls how many numbers appear along the colorbar\ - (which would be NI +1). - cbar: Name of the colorbar to use. The available colormaps can be found\ - online. - cbar_width_perc: Width of the colorbar as a percentage of the image. - no_colorbar: Disable the colorbar in the image. - figsize_x: Width of the created image in inches. - figsize_y: Height of the created image in inches. - hold_image: In addition to saving an image file, open the image and\ - keep displaying it until a key is pressed in the terminal. - tight_layout: Use matplotlib's tight layout functionality in arranging\ - the plot. - xticks_off: Don't display labels along the x-axis. - yticks_off: Don't display labels along the y-axis. - version: Display the version number of the program. - date: Display the release/editing date of the current version. - help_: Display help in the terminal. - help_view: Display help in a separate text editor. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMat2dPlotPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MAT2D_PLOT_PY_METADATA) - cargs = [] - cargs.append("fat_mat2d_plot.py") - cargs.append(execution.input_file(input_file)) - if matrices is not None: - cargs.extend(matrices) - if prefix is not None: - cargs.append(prefix) - if file_type is not None: - cargs.append(file_type) - if dpi is not None: - cargs.append(str(dpi)) - if min_colorbar is not None: - cargs.append(str(min_colorbar)) - if max_colorbar is not None: - cargs.append(str(max_colorbar)) - if fs_xticks is not None: - cargs.append(str(fs_xticks)) - if fs_yticks is not None: - cargs.append(str(fs_yticks)) - if fs_title is not None: - cargs.append(str(fs_title)) - if fs_cbar is not None: - cargs.append(str(fs_cbar)) - if cbar_n_intervals is not None: - cargs.append(str(cbar_n_intervals)) - if cbar is not None: - cargs.append(cbar) - if cbar_width_perc is not None: - cargs.append(str(cbar_width_perc)) - if no_colorbar: - cargs.append("-cbar_off") - if figsize_x is not None: - cargs.append(str(figsize_x)) - if figsize_y is not None: - cargs.append(str(figsize_y)) - if hold_image: - cargs.append("-hold_image") - if tight_layout: - cargs.append("-tight_layout") - if xticks_off: - cargs.append("-xticks_off") - if yticks_off: - cargs.append("-yticks_off") - if version: - cargs.append("-ver") - if date: - cargs.append("-date") - if help_: - cargs.append("-help") - if help_view: - cargs.append("-hview") - ret = FatMat2dPlotPyOutputs( - root=execution.output_file("."), - output_files=execution.output_file(prefix + "_[MATRIX_NAME]." + file_type) if (prefix is not None and file_type is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MAT2D_PLOT_PY_METADATA", - "FatMat2dPlotPyOutputs", - "fat_mat2d_plot_py", -] diff --git a/python/src/niwrap/afni/fat_mat_sel_py.py b/python/src/niwrap/afni/fat_mat_sel_py.py deleted file mode 100644 index 838738491..000000000 --- a/python/src/niwrap/afni/fat_mat_sel_py.py +++ /dev/null @@ -1,215 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MAT_SEL_PY_METADATA = Metadata( - id="2dbd312d736f7cb02342c5c6ae41fc2d1aac7035.boutiques", - name="fat_mat_sel.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMatSelPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mat_sel_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - individual_images: OutputPathType - """Individual images of matrix plots.""" - matrix_grids: OutputPathType - """Output matrix grid files.""" - v_1_d_dsets: OutputPathType - """Output 1D dataset files.""" - - -def fat_mat_sel_py( - parameters: str, - matr_in: str | None = None, - list_match: InputPathType | None = None, - out_ind_matr: bool = False, - out_ind_1ddset: bool = False, - hold_image: bool = False, - extern_labs_no: bool = False, - type_file: str | None = None, - dpi_file: float | None = None, - xlen_file: float | None = None, - ylen_file: float | None = None, - tight_layout_on: bool = False, - fig_off: bool = False, - size_font: float | None = None, - lab_size_font: float | None = None, - a_plotmin: float | None = None, - b_plotmax: float | None = None, - cbar_off: bool = False, - map_of_colors: str | None = None, - cbar_int_num: float | None = None, - width_cbar_perc: float | None = None, - specifier: str | None = None, - xtick_lab_off: bool = False, - runner: Runner | None = None, -) -> FatMatSelPyOutputs: - """ - Perform simple matrix plotting operations from outputs of FATCAT programs - 3dNetCorr and 3dTrackID. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - parameters: Supply names of parameters, separated by whitespace, for\ - selecting from a matrix file. - matr_in: Provide the set of matrix (*.grid or *.netcc) files by\ - searchable path. This can be a globbable entry in quotes containing\ - wildcard characters. - list_match: Provide the matrix (*.grid or *.netcc) files by explicit\ - path, matched per file with a CSV subject ID. - out_ind_matr: Output individual matrix files of properties. - out_ind_1ddset: Output as a 1D dset, more easily readable by other\ - programs. - hold_image: Switch to hold the Python-produced image on the output\ - screen until a key has been hit. - extern_labs_no: Switch to turn off the usage of user-defined labels in\ - the *.grid/*.netcc files. - type_file: Select image format type (e.g., jpg, png, pdf). - dpi_file: Set resolution (dots per inch) of output image. - xlen_file: Horizontal dimension of output saved image, in units of\ - inches. - ylen_file: Vertical dimension of output saved image, in units of\ - inches. - tight_layout_on: Use matplotlib's tight_layout() option to ensure no\ - overlap of features in the image. - fig_off: Switch if you don't want matrix figure output. - size_font: Set font size for colorbar and title. - lab_size_font: Set font size for x- and y-axis labels. - a_plotmin: Minimum colorbar value. - b_plotmax: Maximum colorbar value. - cbar_off: Switch to not include a colorbar at the right side of the\ - plot. - map_of_colors: Change the colormap style used in the plot. - cbar_int_num: Set the number of intervals on the colorbar. - width_cbar_perc: Width of colorbar as percentage of width of the\ - correlation matrix. - specifier: Specify number formatting for the colorbar numbers (e.g.,\ - '%.4f' for four decimal places). - xtick_lab_off: Switch to turn off labels along the x- (horizontal) axis\ - but leave those along the y- (vertical) axis. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMatSelPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MAT_SEL_PY_METADATA) - cargs = [] - cargs.append("fat_mat_sel.py") - cargs.extend([ - "--Pars", - parameters - ]) - if matr_in is not None: - cargs.extend([ - "--matr_in", - matr_in - ]) - if list_match is not None: - cargs.extend([ - "--list_match", - execution.input_file(list_match) - ]) - if out_ind_matr: - cargs.append("--out_ind_matr") - if out_ind_1ddset: - cargs.append("--Out_ind_1ddset") - if hold_image: - cargs.append("--Hold_image") - if extern_labs_no: - cargs.append("--ExternLabsNo") - if type_file is not None: - cargs.extend([ - "--type_file", - type_file - ]) - if dpi_file is not None: - cargs.extend([ - "--dpi_file", - str(dpi_file) - ]) - if xlen_file is not None: - cargs.extend([ - "--xlen_file", - str(xlen_file) - ]) - if ylen_file is not None: - cargs.extend([ - "--ylen_file", - str(ylen_file) - ]) - if tight_layout_on: - cargs.append("--Tight_layout_on") - if fig_off: - cargs.append("--Fig_off") - if size_font is not None: - cargs.extend([ - "--Size_font", - str(size_font) - ]) - if lab_size_font is not None: - cargs.extend([ - "--Lab_size_font", - str(lab_size_font) - ]) - if a_plotmin is not None: - cargs.extend([ - "--A_plotmin", - str(a_plotmin) - ]) - if b_plotmax is not None: - cargs.extend([ - "--B_plotmax", - str(b_plotmax) - ]) - if cbar_off: - cargs.append("--Cbar_off") - if map_of_colors is not None: - cargs.extend([ - "--Map_of_colors", - map_of_colors - ]) - if cbar_int_num is not None: - cargs.extend([ - "--cbar_int_num", - str(cbar_int_num) - ]) - if width_cbar_perc is not None: - cargs.extend([ - "--width_cbar_perc", - str(width_cbar_perc) - ]) - if specifier is not None: - cargs.extend([ - "--specifier", - specifier - ]) - if xtick_lab_off: - cargs.append("--Xtick_lab_off") - ret = FatMatSelPyOutputs( - root=execution.output_file("."), - individual_images=execution.output_file("individual_images/*"), - matrix_grids=execution.output_file("matrix_grids/*"), - v_1_d_dsets=execution.output_file("1D_dsets/*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MAT_SEL_PY_METADATA", - "FatMatSelPyOutputs", - "fat_mat_sel_py", -] diff --git a/python/src/niwrap/afni/fat_mat_tableize.py b/python/src/niwrap/afni/fat_mat_tableize.py deleted file mode 100644 index f88768af7..000000000 --- a/python/src/niwrap/afni/fat_mat_tableize.py +++ /dev/null @@ -1,122 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MAT_TABLEIZE_METADATA = Metadata( - id="174365e6a9d9950711c3103b78320ab05da8673e.boutiques", - name="fat_mat_tableize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMatTableizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mat_tableize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_table: OutputPathType - """Table file usable in AFNI group analysis programs.""" - output_log: OutputPathType - """Log file reporting inputs, matching, and aspects of creating the table - file.""" - - -def fat_mat_tableize( - input_matrices: list[str], - output_prefix: str, - input_csv: InputPathType | None = None, - input_list: InputPathType | None = None, - parameters: list[str] | None = None, - version: bool = False, - date: bool = False, - help_: bool = False, - help_short: bool = False, - help_view: bool = False, - runner: Runner | None = None, -) -> FatMatTableizeOutputs: - """ - Make tables for AFNI group analysis programs from 3dNetCorr (*.netcc) and - 3dTrackID (*.grid) outputs, with optional additional subject information from - CSV files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_matrices: Names of *.netcc or *.grid files with matrices to be\ - used to make table; can be provided using wildcard chars. - output_prefix: Output basename for the table and log files. Suffix and\ - file extensions will be added for the outputs. - input_csv: Name of a CSV file to include in the table. The first column\ - must have subject ID labels that match with the input matrix files. - input_list: File containing paths to subject matrices and optionally\ - CSV IDs for matching. - parameters: List of matrices to be included in the table, identified by\ - their parameter name. - version: Display current version. - date: Display release/editing date of current version. - help_: Display help in terminal. - help_short: Display help in terminal (short flag). - help_view: Display help in a separate text editor. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMatTableizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MAT_TABLEIZE_METADATA) - cargs = [] - cargs.append("fat_mat_tableize.py") - cargs.extend([ - "-in_mat", - *input_matrices - ]) - if input_csv is not None: - cargs.extend([ - "-in_csv", - execution.input_file(input_csv) - ]) - if input_list is not None: - cargs.extend([ - "-in_listfile", - execution.input_file(input_list) - ]) - cargs.extend([ - "-prefix", - output_prefix - ]) - if parameters is not None: - cargs.extend([ - "-pars", - *parameters - ]) - if version: - cargs.append("-ver") - if date: - cargs.append("-date") - if help_: - cargs.append("-help") - if help_short: - cargs.append("-h") - if help_view: - cargs.append("-hview") - ret = FatMatTableizeOutputs( - root=execution.output_file("."), - output_table=execution.output_file(output_prefix + "_tbl.txt"), - output_log=execution.output_file(output_prefix + "_prep.log"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MAT_TABLEIZE_METADATA", - "FatMatTableizeOutputs", - "fat_mat_tableize", -] diff --git a/python/src/niwrap/afni/fat_mvm_gridconv_py.py b/python/src/niwrap/afni/fat_mvm_gridconv_py.py deleted file mode 100644 index 6d28c7b71..000000000 --- a/python/src/niwrap/afni/fat_mvm_gridconv_py.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MVM_GRIDCONV_PY_METADATA = Metadata( - id="92d9fdaa8fac36c122e4e79e18057d88e1e6a26f.boutiques", - name="fat_mvm_gridconv.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMvmGridconvPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mvm_gridconv_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - converted_grid_files: OutputPathType - """Output converted grid files, with '_MOD.grid' postfix or custom output - name provided in the list file.""" - - -def fat_mvm_gridconv_py( - matrix_files: str | None = None, - list_file: InputPathType | None = None, - runner: Runner | None = None, -) -> FatMvmGridconvPyOutputs: - """ - Preprocess 'old school' *.grid files for statistical modeling using 3dMVM. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - matrix_files: Provide the set of matrix (*.grid) files as a searchable\ - path. This can be a globbable entry in quotes containing wildcard\ - characters. - list_file: Provide the matrix (*.grid) files by explicit path in a text\ - file. The LIST text file must contain at least one column (path to\ - subject matrix file) with an optional second column (output file\ - names). If no second column is given, the default '_MOD.grid' postfix\ - is applied. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMvmGridconvPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MVM_GRIDCONV_PY_METADATA) - cargs = [] - cargs.append("fat_mvm_gridconv.py") - if matrix_files is not None: - cargs.extend([ - "-m", - matrix_files - ]) - if list_file is not None: - cargs.extend([ - "-l", - execution.input_file(list_file) - ]) - ret = FatMvmGridconvPyOutputs( - root=execution.output_file("."), - converted_grid_files=execution.output_file("*_MOD.grid"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MVM_GRIDCONV_PY_METADATA", - "FatMvmGridconvPyOutputs", - "fat_mvm_gridconv_py", -] diff --git a/python/src/niwrap/afni/fat_mvm_prep.py b/python/src/niwrap/afni/fat_mvm_prep.py deleted file mode 100644 index ae46c559c..000000000 --- a/python/src/niwrap/afni/fat_mvm_prep.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MVM_PREP_METADATA = Metadata( - id="90f6bc657de16af423e425320b0789c1d1f1d2eb.boutiques", - name="fat_mvm_prep", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMvmPrepOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mvm_prep(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - mvmtbl: OutputPathType - """Output tabular text file for 3dMVM.""" - mvmprep_log: OutputPathType - """Log file detailing subject matching and ROI list.""" - - -def fat_mvm_prep( - prefix: str, - csv_file: InputPathType, - matrix_files: str | None = None, - list_match: InputPathType | None = None, - unionize_rois: bool = False, - na_warn_off: bool = False, - extern_labels_no: bool = False, - runner: Runner | None = None, -) -> FatMvmPrepOutputs: - """ - Combine FATCAT output with CSV data for statistical modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output files. - csv_file: Comma-separated variable (CSV) file for input. - matrix_files: Set of matrix (*.grid or *.netcc) files by searchable\ - path. - list_match: Text file containing two columns: path to subject matrix\ - file and CSV IDs. - unionize_rois: Make the ROI list as the union of elements across the\ - group. - na_warn_off: Turn off the automatic warnings as the data table is\ - created. - extern_labels_no: Turn off the writing/usage of user-defined labels in\ - the *.grid/*.netcc files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMvmPrepOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MVM_PREP_METADATA) - cargs = [] - cargs.append("fat_mvm_prep.py") - cargs.extend([ - "-p", - prefix - ]) - cargs.extend([ - "-c", - execution.input_file(csv_file) - ]) - if matrix_files is not None: - cargs.extend([ - "-m", - matrix_files - ]) - if list_match is not None: - cargs.extend([ - "-l", - execution.input_file(list_match) - ]) - if unionize_rois: - cargs.append("-u") - if na_warn_off: - cargs.append("-N") - if extern_labels_no: - cargs.append("-E") - ret = FatMvmPrepOutputs( - root=execution.output_file("."), - mvmtbl=execution.output_file(prefix + "_MVMtbl.txt"), - mvmprep_log=execution.output_file(prefix + "_MVMprep.log"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MVM_PREP_METADATA", - "FatMvmPrepOutputs", - "fat_mvm_prep", -] diff --git a/python/src/niwrap/afni/fat_mvm_scripter_py.py b/python/src/niwrap/afni/fat_mvm_scripter_py.py deleted file mode 100644 index 4e87ad4ae..000000000 --- a/python/src/niwrap/afni/fat_mvm_scripter_py.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_MVM_SCRIPTER_PY_METADATA = Metadata( - id="82b72a127567ec2077a59b2fc40c92cb4cb7aea9.boutiques", - name="fat_mvm_scripter.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatMvmScripterPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_mvm_scripter_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - generated_script: OutputPathType - """Script for running 3dMVM, using the prescribed variables along with each - individual parameter.""" - results_file: OutputPathType - """Text file of the test results.""" - - -def fat_mvm_scripter_py( - prefix: str, - table: InputPathType, - log: InputPathType, - vars_: str | None = None, - file_vars: InputPathType | None = None, - pars: str | None = None, - file_pars: InputPathType | None = None, - rois: str | None = None, - file_rois: InputPathType | None = None, - no_posthoc: bool = False, - na_warn_off: bool = False, - subnet_pref: str | None = None, - cat_pair_off: bool = False, - runner: Runner | None = None, -) -> FatMvmScripterPyOutputs: - """ - Automated tool to create command scripts for 3dMVM statistical modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output prefix for the script file, which will ultimately create\ - a PREFIX_MVM.txt file of statistical results from 3dMVM. - table: Text file containing columns of subject data, one subject per\ - row, formatted as a *_MVMtbl.txt output by fat_mvm_prep.py. - log: File formatted according to fat_mvm_prep.py containing commented\ - headings and lists of cross-group ROIs and parameters. - vars_: List of variables for the 3dMVM model. Names must be separated\ - with whitespace. Categorical variables will be detected automatically\ - by the presence of nonnumeric characters in their columns. - file_vars: Second method for supplying a list of variables for 3dMVM.\ - VAR_FILE is a text file with a single column of variable names. - pars: List of parameters (names of matrices) to run in distinct 3dMVM\ - models. Names must be separated with whitespace. - file_pars: Second method for supplying a list of parameters for 3dMVM\ - runs. PAR_FILE is a text file with a single column of parameter names. - rois: Optional command to select a subset of available network ROIs.\ - Names must be separated with whitespace. - file_rois: Second method for supplying a subset of ROIs for 3dMVM runs.\ - ROI_FILE is a text file with a single column of variable names. - no_posthoc: Switch to turn off the automatic generation of per-ROI post\ - hoc tests. - na_warn_off: Switch to turn off the automatic warnings as the data\ - table is created. 3dMVM will excise subjects with NA values, so there\ - shouldn't be NA values in columns you want to model. - subnet_pref: Name SUBPR for the new table file that is created when a\ - subnetwork list of ROIs is used. - cat_pair_off: Switch to turn off the test for categorical variables\ - undergoing posthoc testing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatMvmScripterPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_MVM_SCRIPTER_PY_METADATA) - cargs = [] - cargs.append("fat_mvm_scripter.py") - cargs.extend([ - "--prefix", - prefix - ]) - cargs.extend([ - "--table", - execution.input_file(table) - ]) - cargs.extend([ - "--log", - execution.input_file(log) - ]) - if vars_ is not None: - cargs.extend([ - "--vars", - vars_ - ]) - if file_vars is not None: - cargs.extend([ - "--file_vars", - execution.input_file(file_vars) - ]) - if pars is not None: - cargs.extend([ - "--Pars", - pars - ]) - if file_pars is not None: - cargs.extend([ - "--File_Pars", - execution.input_file(file_pars) - ]) - if rois is not None: - cargs.extend([ - "--rois", - rois - ]) - if file_rois is not None: - cargs.extend([ - "--file_rois", - execution.input_file(file_rois) - ]) - if no_posthoc: - cargs.append("--no_posthoc") - if na_warn_off: - cargs.append("--NA_warn_off") - if subnet_pref is not None: - cargs.extend([ - "--subnet_pref", - subnet_pref - ]) - if cat_pair_off: - cargs.append("--cat_pair_off") - ret = FatMvmScripterPyOutputs( - root=execution.output_file("."), - generated_script=execution.output_file(prefix + "_scri.tcsh"), - results_file=execution.output_file(prefix + "_MVM.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_MVM_SCRIPTER_PY_METADATA", - "FatMvmScripterPyOutputs", - "fat_mvm_scripter_py", -] diff --git a/python/src/niwrap/afni/fat_proc_align_anat_pair.py b/python/src/niwrap/afni/fat_proc_align_anat_pair.py deleted file mode 100644 index 4c358a0aa..000000000 --- a/python/src/niwrap/afni/fat_proc_align_anat_pair.py +++ /dev/null @@ -1,127 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_ALIGN_ANAT_PAIR_METADATA = Metadata( - id="b8144a4b5ca2e9d93de3ee16481095c9a8a388b0.boutiques", - name="fat_proc_align_anat_pair", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcAlignAnatPairOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_align_anat_pair(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - aligned_t1w: OutputPathType - """Aligned T1w volume""" - qc_snapshot_t1w_on_t2w: OutputPathType - """QC snapshot of the T1w volume overlaying the T2w volume""" - qc_snapshot_t1w_edges_on_t2w: OutputPathType - """QC snapshot of the T1w edges overlaying the T2w volume""" - - -def fat_proc_align_anat_pair( - input_t1w: InputPathType, - input_t2w: InputPathType, - output_prefix: str, - output_grid: float | None = None, - input_t2w_mask: InputPathType | None = None, - do_ss_tmp_t1w: bool = False, - warp: str | None = None, - matrix: InputPathType | None = None, - workdir: str | None = None, - no_cmd_out: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> FatProcAlignAnatPairOutputs: - """ - A tool for aligning a T1w anatomical image to a T2w anatomical image using - solid-body parameters (translation and rotation). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_t1w: T1-weighted volume. - input_t2w: T2-weighted volume. - output_prefix: Output prefix for files and snapshots. - output_grid: Specify output T1w volume's final resolution (isotropic). - input_t2w_mask: Input a mask to apply to the T2w volume for alignment. - do_ss_tmp_t1w: Apply skullstripping to the T1w volume during an\ - intermediate step. - warp: Specify the degrees of freedom for warping using options from\ - 3dAllineate. - matrix: Apply a pre-made matrix from 3dAllineate. - workdir: Specify a working directory. - no_cmd_out: Do not save the command line call and the location where it\ - was run. - no_clean: Do not delete the temporary working directory. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcAlignAnatPairOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_ALIGN_ANAT_PAIR_METADATA) - cargs = [] - cargs.append("fat_proc_align_anat_pair") - cargs.append("-in_t1w") - cargs.append(execution.input_file(input_t1w)) - cargs.append("-in_t2w") - cargs.append(execution.input_file(input_t2w)) - cargs.append("-prefix") - cargs.append(output_prefix) - if output_grid is not None: - cargs.extend([ - "-newgrid", - str(output_grid) - ]) - if input_t2w_mask is not None: - cargs.extend([ - "-in_t2w_mask", - execution.input_file(input_t2w_mask) - ]) - if do_ss_tmp_t1w: - cargs.append("-do_ss_tmp_t1w") - if warp is not None: - cargs.extend([ - "-warp", - warp - ]) - if matrix is not None: - cargs.extend([ - "-matrix", - execution.input_file(matrix) - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if no_cmd_out: - cargs.append("-no_cmd_out") - if no_clean: - cargs.append("-no_clean") - ret = FatProcAlignAnatPairOutputs( - root=execution.output_file("."), - aligned_t1w=execution.output_file(output_prefix + "_t1w_aligned.nii.gz"), - qc_snapshot_t1w_on_t2w=execution.output_file(output_prefix + "_QC_T1w_over_T2w.png"), - qc_snapshot_t1w_edges_on_t2w=execution.output_file(output_prefix + "_QC_T1w_edges_over_T2w.png"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_ALIGN_ANAT_PAIR_METADATA", - "FatProcAlignAnatPairOutputs", - "fat_proc_align_anat_pair", -] diff --git a/python/src/niwrap/afni/fat_proc_axialize_anat.py b/python/src/niwrap/afni/fat_proc_axialize_anat.py deleted file mode 100644 index 7d1e5154b..000000000 --- a/python/src/niwrap/afni/fat_proc_axialize_anat.py +++ /dev/null @@ -1,179 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_AXIALIZE_ANAT_METADATA = Metadata( - id="e138eb56e5029d03d449b78987c687adf3579333.boutiques", - name="fat_proc_axialize_anat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcAxializeAnatOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_axialize_anat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """An anatomical data set that is regularly situated within its FOV - volume""" - working_directory: OutputPathType | None - """The working directory with intermediate files""" - - -def fat_proc_axialize_anat( - in_file: InputPathType, - ref_file: InputPathType, - prefix: str, - mode_t2w: bool = False, - mode_t1w: bool = False, - workdir: str | None = None, - out_match_ref: bool = False, - do_ceil_out: bool = False, - extra_al_wtmask: InputPathType | None = None, - extra_al_cost: str | None = None, - extra_al_opts: str | None = None, - focus_mask: InputPathType | None = None, - focus_by_ss: bool = False, - remove_inf_sli: float | None = None, - pre_align_center_mass: bool = False, - pre_center_mass: bool = False, - post_lr_symm: bool = False, - no_pre_lr_symm: bool = False, - no_clean: bool = False, - qc_ulay_range: list[float] | None = None, - no_qc_view: bool = False, - qc_prefix: str | None = None, - runner: Runner | None = None, -) -> FatProcAxializeAnatOutputs: - """ - Helps align the major axes of an anatomical volume to those of the volumetric - field of view. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input anatomical volume full name. - ref_file: Reference volume full name, such as TT or MNI. - prefix: Output prefix for files and snapshots. - mode_t2w: Switch for T2-weighted image processing. - mode_t1w: Switch for T1-weighted image processing. - workdir: Name of the working subdirectory in the output directory. - out_match_ref: Match the final output volume space FOV and spatial\ - resolution to the reference file. - do_ceil_out: Apply a ceiling based on the 98%ile value within an\ - automasked volume. - extra_al_wtmask: Extra weight mask to emphasize specific parts for\ - alignment. - extra_al_cost: Specify a cost function for 3dAllineate to use (default\ - 'lpa'). - extra_al_opts: Extra options for 3dAllineate when applying the warp. - focus_mask: Input mask to focus processing and alignment. - focus_by_ss: Make a mask by simply skullstripping input data set. - remove_inf_sli: Remove a number of slices from the inferior part of the\ - FOV. - pre_align_center_mass: Pre-align the centers of mass of the volumes. - pre_center_mass: Pre-recenter input center of mass to (0, 0, 0). - post_lr_symm: Apply post-alignment left-right symmetrization. - no_pre_lr_symm: Turn off pre-alignment left-right symmetrization. - no_clean: Do not remove working directory '__WORKING_axialize_anat'. - qc_ulay_range: Provide a min (UMIN) and max (UMAX) range for underlay\ - grayscale bar. - no_qc_view: Turn off default QC image saving/viewing. - qc_prefix: Provide a prefix for QC outputs separate from the main\ - prefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcAxializeAnatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_AXIALIZE_ANAT_METADATA) - cargs = [] - cargs.append("fat_proc_axialize_anat") - cargs.append(execution.input_file(in_file)) - cargs.append(execution.input_file(ref_file)) - cargs.append(prefix) - if mode_t2w: - cargs.append("-mode_t2w") - if mode_t1w: - cargs.append("-mode_t1w") - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if out_match_ref: - cargs.append("-out_match_ref") - if do_ceil_out: - cargs.append("-do_ceil_out") - if extra_al_wtmask is not None: - cargs.extend([ - "-extra_al_wtmask", - execution.input_file(extra_al_wtmask) - ]) - if extra_al_cost is not None: - cargs.extend([ - "-extra_al_cost", - extra_al_cost - ]) - if extra_al_opts is not None: - cargs.extend([ - "-extra_al_opts", - extra_al_opts - ]) - if focus_mask is not None: - cargs.extend([ - "-focus_mask", - execution.input_file(focus_mask) - ]) - if focus_by_ss: - cargs.append("-focus_by_ss") - if remove_inf_sli is not None: - cargs.extend([ - "-remove_inf_sli", - str(remove_inf_sli) - ]) - if pre_align_center_mass: - cargs.append("-pre_align_center_mass") - if pre_center_mass: - cargs.append("-pre_center_mass") - if post_lr_symm: - cargs.append("-post_lr_symm") - if no_pre_lr_symm: - cargs.append("-no_pre_lr_symm") - if no_clean: - cargs.append("-no_clean") - if qc_ulay_range is not None: - cargs.extend([ - "-qc1_ulay_range", - *map(str, qc_ulay_range) - ]) - if no_qc_view: - cargs.append("-no_qc_view") - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - ret = FatProcAxializeAnatOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz"), - working_directory=execution.output_file(workdir) if (workdir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_AXIALIZE_ANAT_METADATA", - "FatProcAxializeAnatOutputs", - "fat_proc_axialize_anat", -] diff --git a/python/src/niwrap/afni/fat_proc_connec_vis.py b/python/src/niwrap/afni/fat_proc_connec_vis.py deleted file mode 100644 index 375e1dab7..000000000 --- a/python/src/niwrap/afni/fat_proc_connec_vis.py +++ /dev/null @@ -1,149 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_CONNEC_VIS_METADATA = Metadata( - id="3c0e03aae455fbd21d6ab5bd41865b6565e23556.boutiques", - name="fat_proc_connec_vis", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcConnecVisOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_connec_vis(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - cmd_txt: OutputPathType - """Command text file output""" - tcat_file: OutputPathType - """Concatenated ROI masks multibrick file from the -output_tcat flag""" - tstat_file: OutputPathType - """Single brick file from 3dTstat operation on the tcat dataset, produced by - the -output_tstat flag""" - - -def fat_proc_connec_vis( - in_rois: str, - prefix: str, - prefix_file: str | None = None, - tsmoo_kpb: float | None = None, - tsmoo_niter: float | None = None, - iso_opt: str | None = None, - trackid_no_or: bool = False, - output_tcat: bool = False, - output_tstat: bool = False, - wdir: str | None = None, - no_clean: bool = False, - runner: Runner | None = None, -) -> FatProcConnecVisOutputs: - """ - This program is for visualizing the volumetric output of tracking, mainly for - the '-dump_rois ...' from 3dTrackID. It creates surface-ized views of the - separate white matter connection maps (WMCs) which can be viewed simultaneously - in 3D with SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_rois: List of separate files, each with a single ROI volume mask;\ - can include wildcards, etc. to specify the list. - prefix: Directory to contain the output files: *cmd.txt and surface\ - files such as *.gii and *.niml.dset; the namebase of files within this\ - directory will be the default for the program, 'wmc'. The value PPP can\ - contain parts of a path in it. - prefix_file: Prefix for the output files: *cmd.txt and surface files\ - such as *.gii and *.niml.dset; can include path steps; and can make one\ - level of a new directory. For example, if FFF were 'A/B', then the\ - program could make a new directory called 'A' if it didn't exist\ - already and populate it with individual files having the same prefix\ - 'B'. - tsmoo_kpb: 'KPB' parameter in IsoSurface program; default value is\ - 0.01. - tsmoo_niter: 'NITER' parameter in IsoSurface program; default value is\ - 6. - iso_opt: Input one of the 'iso* options' from IsoSurface program, such\ - as 'isorois+dsets', 'mergerois', etc. Quotations around the entry may\ - be needed, especially if something like the '-mergerois [LAB_OUT]'\ - route is being followed. Default: isorois+dsets. - trackid_no_or: Use this option to have the program recognize the naming\ - convention of 3dTrackID output and to ignore the OR-logic ROIs,\ - including only the AND-logic (AKA pairwise) connections. - output_tcat: Flag to output the multibrick file of concatenated ROI\ - masks; note that the [0]th brick will be all zeros (it is just a\ - placeholder). So, if there are N ROI maps concatenated, there will be\ - N+1 bricks in the output dataset, which has the name PPP_tcat.nii.gz. - output_tstat: Flag to output the single brick file from the 3dTstat\ - operation on the tcat dataset. If there were N ROI maps concatenated,\ - then the largest value should be N. The output file's name will be\ - PPP_tstat.nii.gz. - wdir: Working directory prefix. The format is '__WDIR_connec_vis_PPP',\ - where PPP is the input prefix. - no_clean: Optional switch to NOT remove the working directory (default\ - is to remove the working directory). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcConnecVisOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_CONNEC_VIS_METADATA) - cargs = [] - cargs.append("fat_proc_connec_vis") - cargs.append(in_rois) - cargs.append(prefix) - if prefix_file is not None: - cargs.extend([ - "-prefix_file", - prefix_file - ]) - if tsmoo_kpb is not None: - cargs.extend([ - "-tsmoo_kpb", - str(tsmoo_kpb) - ]) - if tsmoo_niter is not None: - cargs.extend([ - "-tsmoo_niter", - str(tsmoo_niter) - ]) - if iso_opt is not None: - cargs.extend([ - "-iso_opt", - iso_opt - ]) - if trackid_no_or: - cargs.append("-trackid_no_or") - if output_tcat: - cargs.append("-output_tcat") - if output_tstat: - cargs.append("-output_tstat") - if wdir is not None: - cargs.extend([ - "-wdir", - wdir - ]) - if no_clean: - cargs.append("-no_clean") - ret = FatProcConnecVisOutputs( - root=execution.output_file("."), - cmd_txt=execution.output_file(prefix + "_cmd.txt"), - tcat_file=execution.output_file(prefix + "_tcat.nii.gz"), - tstat_file=execution.output_file(prefix + "_tstat.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_CONNEC_VIS_METADATA", - "FatProcConnecVisOutputs", - "fat_proc_connec_vis", -] diff --git a/python/src/niwrap/afni/fat_proc_convert_dcm_anat.py b/python/src/niwrap/afni/fat_proc_convert_dcm_anat.py deleted file mode 100644 index 0019c6857..000000000 --- a/python/src/niwrap/afni/fat_proc_convert_dcm_anat.py +++ /dev/null @@ -1,117 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_CONVERT_DCM_ANAT_METADATA = Metadata( - id="0177f4c891bb01f1d16cc7a255fd2d69587e47e9.boutiques", - name="fat_proc_convert_dcm_anat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcConvertDcmAnatOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_convert_dcm_anat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_volume: OutputPathType - """Converted anatomical volume output.""" - - -def fat_proc_convert_dcm_anat( - prefix: str, - nifti_input: InputPathType | None = None, - workdir: str | None = None, - orient: str | None = None, - no_clean: bool = False, - reorig_reorient_off: bool = False, - qc_prefix: str | None = None, - no_cmd_out: bool = False, - no_qc_view: bool = False, - runner: Runner | None = None, -) -> FatProcConvertDcmAnatOutputs: - """ - Converts an anatomical dataset from DICOM files into a volume, specifically - designed to fit in line with other processing such as DTI analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Set prefix (and path) for output data. - nifti_input: Input as NIFTI file (zipped or unzipped fine). Alternative\ - to '-indir ..'. - workdir: Specify a working directory, which can be removed (default\ - name = '__WORKING_convert_dcm_anat'). - orient: Optional chance to reset orientation of the volume files\ - (default is currently 'RAI'). - no_clean: Prevents removal of working directory. - reorig_reorient_off: Turns off the nicety of putting (0, 0, 0) at\ - brain's center of mass (-> 'reorigin' calc) and reorienting data (->\ - 'reorient' calc). - qc_prefix: Set the prefix of the QC image files separately (default is\ - ''). - no_cmd_out: Don't save the command line call and the location where it\ - was run. - no_qc_view: Turn off generating QC image files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcConvertDcmAnatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_CONVERT_DCM_ANAT_METADATA) - cargs = [] - cargs.append("fat_proc_convert_dcm_anat") - if nifti_input is not None: - cargs.extend([ - "-innii", - execution.input_file(nifti_input) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if orient is not None: - cargs.extend([ - "-orient", - orient - ]) - if no_clean: - cargs.append("-no_clean") - if reorig_reorient_off: - cargs.append("-reorig_reorient_off") - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - if no_cmd_out: - cargs.append("-no_cmd_out") - if no_qc_view: - cargs.append("-no_qc_view") - ret = FatProcConvertDcmAnatOutputs( - root=execution.output_file("."), - output_volume=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_CONVERT_DCM_ANAT_METADATA", - "FatProcConvertDcmAnatOutputs", - "fat_proc_convert_dcm_anat", -] diff --git a/python/src/niwrap/afni/fat_proc_convert_dcm_dwis.py b/python/src/niwrap/afni/fat_proc_convert_dcm_dwis.py deleted file mode 100644 index a13f20d2f..000000000 --- a/python/src/niwrap/afni/fat_proc_convert_dcm_dwis.py +++ /dev/null @@ -1,158 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_CONVERT_DCM_DWIS_METADATA = Metadata( - id="9b9610517874019289f1b6f2dec8529be62fcd51.boutiques", - name="fat_proc_convert_dcm_dwis", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcConvertDcmDwisOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_convert_dcm_dwis(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_nifti: OutputPathType - """A NIFTI file with N volumes.""" - output_rvec: OutputPathType - """A row-wise (3xN) bvec file of the (unit-magnitude) gradient - orientations.""" - output_bval: OutputPathType - """A row-wise (1xN) bval file of the gradient magnitudes.""" - output_mat_a: OutputPathType - """A column-wise (Nx6) AFNI-style matrix file of the (scaled) b-matrix - values.""" - output_mat_t: OutputPathType - """A column-wise (Nx6) TORTOISE-style matrix file of the (scaled) b-matrix - values.""" - output_cvec: OutputPathType - """A column-wise (Nx3) bvec file of the (b-magn scaled) gradient - orientations.""" - - -def fat_proc_convert_dcm_dwis( - dicom_dir: str, - output_prefix: str, - nifti_files: list[InputPathType] | None = None, - bvec_files: list[InputPathType] | None = None, - bval_files: list[InputPathType] | None = None, - work_dir: str | None = None, - orientation: str | None = None, - origin_xyz: list[float] | None = None, - flip_x: bool = False, - flip_y: bool = False, - flip_z: bool = False, - no_flip: bool = False, - qc_prefix: str | None = None, - reorient_off: bool = False, - no_clean: bool = False, - no_cmd_out: bool = False, - no_qc_view: bool = False, - do_movie: str | None = None, - runner: Runner | None = None, -) -> FatProcConvertDcmDwisOutputs: - """ - Convert sets of DWIs in DICOM format into 'nicer' volume+grad format, reorient - volumetric data, and glue together multiple sessions/directories of data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dicom_dir: Directory of DICOM files of the DWI data with 'AP' phase\ - encoding. Can contain a wildcard expression for several directories. - output_prefix: Prefix (and path) for output data (e.g., *.nii.gz,\ - *.bvec, *.bval files). Required. - nifti_files: One or more NIFTI files of DWIs. - bvec_files: One or more row-wise, gradient (unit-magnitude) files\ - (e.g., *.bvec). - bval_files: One or more bvalue files (e.g., *.bval). - work_dir: Optional working directory for intermediate files. - orientation: Optional chance to reset orientation of the volume files\ - (default is currently 'RAI'). - origin_xyz: Explicit origin coordinates (X, Y, Z). - flip_x: Flip gradients along the X-axis. - flip_y: Flip gradients along the Y-axis. - flip_z: Flip gradients along the Z-axis. - no_flip: Prevent flipping of gradients (default). - qc_prefix: Set the prefix for QC image files separately (default is\ - ''). - reorient_off: Turn off reorigin calculation and reorientation. - no_clean: Do not remove the working directory of intermediate files\ - (default is to delete it). - no_cmd_out: Do not save the command line call and location where it was\ - run. - no_qc_view: Do not generate QC image files. - do_movie: Generate a movie of the newly created dataset (AGIF or MPEG). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcConvertDcmDwisOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_CONVERT_DCM_DWIS_METADATA) - cargs = [] - cargs.append("fat_proc_convert_dcm_dwis") - cargs.append(dicom_dir) - cargs.append(output_prefix) - if nifti_files is not None: - cargs.extend([execution.input_file(f) for f in nifti_files]) - if bvec_files is not None: - cargs.extend([execution.input_file(f) for f in bvec_files]) - if bval_files is not None: - cargs.extend([execution.input_file(f) for f in bval_files]) - if work_dir is not None: - cargs.append(work_dir) - if orientation is not None: - cargs.append(orientation) - if origin_xyz is not None: - cargs.extend(map(str, origin_xyz)) - if flip_x: - cargs.append("-flip_x") - if flip_y: - cargs.append("-flip_y") - if flip_z: - cargs.append("-flip_z") - if no_flip: - cargs.append("-no_flip") - if qc_prefix is not None: - cargs.append(qc_prefix) - if reorient_off: - cargs.append("-reorig_reorient_off") - if no_clean: - cargs.append("-no_clean") - if no_cmd_out: - cargs.append("-no_cmd_out") - if no_qc_view: - cargs.append("-no_qc_view") - if do_movie is not None: - cargs.extend([ - "-do_movie", - do_movie - ]) - ret = FatProcConvertDcmDwisOutputs( - root=execution.output_file("."), - output_nifti=execution.output_file(output_prefix + ".nii.gz"), - output_rvec=execution.output_file(output_prefix + ".rvec"), - output_bval=execution.output_file(output_prefix + ".bval"), - output_mat_a=execution.output_file(output_prefix + "_matA.dat"), - output_mat_t=execution.output_file(output_prefix + "_matT.dat"), - output_cvec=execution.output_file(output_prefix + "_cvec.dat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_CONVERT_DCM_DWIS_METADATA", - "FatProcConvertDcmDwisOutputs", - "fat_proc_convert_dcm_dwis", -] diff --git a/python/src/niwrap/afni/fat_proc_decmap.py b/python/src/niwrap/afni/fat_proc_decmap.py deleted file mode 100644 index b8381aeec..000000000 --- a/python/src/niwrap/afni/fat_proc_decmap.py +++ /dev/null @@ -1,143 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_DECMAP_METADATA = Metadata( - id="5d4b32a54bdd18b7bea855a52f4b838de1b32088.boutiques", - name="fat_proc_decmap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcDecmapOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_decmap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_dec_rgb: OutputPathType - """Single file of type 'rgb' for RGB coloration display.""" - outfile_dec_unwt_thr: OutputPathType - """Single file of type 'rgb' without FA weighting but using FA to threshold - where DEC values are calculated.""" - outfile_dec_sca: OutputPathType - """DEC file additionally scaled by a value (such as 0.7).""" - qc_dec_images: OutputPathType - """Set of cor, axi, and sag images (each a 5x3 montage) of the DEC data.""" - qc_dec_unwt_thrx_images: OutputPathType - """Set of cor, axi, and sag images (each a 5x3 montage) of the DEC - unweighted thresholded data.""" - qc_dec_sca_images: OutputPathType - """Set of cor, axi, and sag images (each a 5x3 montage) of the DEC scaled - data.""" - - -def fat_proc_decmap( - in_fa: InputPathType, - in_v1: InputPathType, - prefix: str, - mask: InputPathType | None = None, - fa_thr: float | None = None, - fa_sca: float | None = None, - workdir: str | None = None, - no_clean: bool = False, - qc_prefix: str | None = None, - no_cmd_out: bool = False, - no_qc_view: bool = False, - runner: Runner | None = None, -) -> FatProcDecmapOutputs: - """ - This program makes a directionally encoded color (DEC) map for DTI results. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_fa: Input FA (scalar) map. - in_v1: Input first eigenvector (3-vector) map. - prefix: Set prefix (and path) for output DWI data. - mask: Optional mask for picking out a region. Otherwise, only places\ - with FA>0 are given coloration. - fa_thr: For QC1 type of DEC images, use FFF to threshold where DEC\ - values are calculated (default: 0.2). - fa_sca: For QC2 type of DEC images, use SSS to scale the FA weighting\ - of what would otherwise be a 'classical' DEC map (default: 0.7). - workdir: Specify a working directory, which can be removed (default:\ - '__WORKING_decmap'). - no_clean: Do not delete temporary files when finishing. - qc_prefix: Set the prefix of the QC image files (default: 'PREFIX'). - no_cmd_out: Do not save the command line call of this program and\ - location where it was run. - no_qc_view: Turn off generating QC image files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcDecmapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_DECMAP_METADATA) - cargs = [] - cargs.append("fat_proc_decmap") - cargs.append("-in_fa") - cargs.append(execution.input_file(in_fa)) - cargs.append("-in_v1") - cargs.append(execution.input_file(in_v1)) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if fa_thr is not None: - cargs.extend([ - "-fa_thr", - str(fa_thr) - ]) - if fa_sca is not None: - cargs.extend([ - "-fa_sca", - str(fa_sca) - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if no_clean: - cargs.append("-no_clean") - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - if no_cmd_out: - cargs.append("-no_cmd_out") - if no_qc_view: - cargs.append("-no_qc_view") - ret = FatProcDecmapOutputs( - root=execution.output_file("."), - outfile_dec_rgb=execution.output_file(prefix + "_dec.nii.gz"), - outfile_dec_unwt_thr=execution.output_file(prefix + "_dec_unwt_thr.nii.gz"), - outfile_dec_sca=execution.output_file(prefix + "_dec_sca*.nii.gz"), - qc_dec_images=execution.output_file(prefix + "_qc_dec*.png"), - qc_dec_unwt_thrx_images=execution.output_file(prefix + "_qc_dec_unwt_thrx*.png"), - qc_dec_sca_images=execution.output_file(prefix + "_qc_dec_sca*.png"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_DECMAP_METADATA", - "FatProcDecmapOutputs", - "fat_proc_decmap", -] diff --git a/python/src/niwrap/afni/fat_proc_dwi_to_dt.py b/python/src/niwrap/afni/fat_proc_dwi_to_dt.py deleted file mode 100644 index 28bbd39c8..000000000 --- a/python/src/niwrap/afni/fat_proc_dwi_to_dt.py +++ /dev/null @@ -1,236 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_DWI_TO_DT_METADATA = Metadata( - id="c5a2942f4ac3b0a68c89864b914dd62d776684d1.boutiques", - name="fat_proc_dwi_to_dt", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcDwiToDtOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_dwi_to_dt(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Output files generated with the specified prefix.""" - - -def fat_proc_dwi_to_dt( - in_dwi: InputPathType, - in_gradmat: InputPathType, - prefix: str, - in_bvals: InputPathType | None = None, - mask: InputPathType | None = None, - mask_from_struc: bool = False, - in_struc_res: InputPathType | None = None, - in_ref_orig: InputPathType | None = None, - prefix_dti: str | None = None, - flip_x: bool = False, - flip_y: bool = False, - flip_z: bool = False, - no_flip: bool = False, - no_scale_out_1000: bool = False, - no_reweight: bool = False, - no_cumulative_wts: bool = False, - qc_fa_thr: float | None = None, - qc_fa_max: float | None = None, - qc_fa_unc_max: float | None = None, - qc_v12_unc_max: float | None = None, - qc_prefix: str | None = None, - no_qc_view: bool = False, - no_cmd_out: bool = False, - workdir: str | None = None, - no_clean: bool = False, - uncert_off: bool = False, - uncert_iters: float | None = None, - uncert_extra_cmds: str | None = None, - check_abs_min: float | None = None, - runner: Runner | None = None, -) -> FatProcDwiToDtOutputs: - """ - This program fits tensors and DT parameters, as well as the uncertainty of DT - parameters needed for tractography. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_dwi: 4D volume of N DWIs. Required. - in_gradmat: Input text file of N gradient vectors or bmatrices. - prefix: Set prefix for output DWI data. - in_bvals: Optional, if bvalue information is in a separate file from\ - the b-vectors or matrices. - mask: Optional whole brain mask can be input; otherwise, automasking is\ - performed. - mask_from_struc: Flag to make a mask using 3dSkullStrip+3dmask_tool\ - from the structural file. - in_struc_res: Alignment of the output DWI to the REF data set via\ - anatomical reference; a version of the anatomical that has been\ - resampled to match the DWI set. - in_ref_orig: Use another data set to adjust the DWI and subsequent\ - parameter dsets' orientation and origin. - prefix_dti: Set prefix for output DTI data; default is 'dt'. Do not\ - include path information here. - flip_x: Flip the DW gradients in the x-direction. - flip_y: Flip the DW gradients in the y-direction. - flip_z: Flip the DW gradients in the z-direction. - no_flip: Do not flip the DW gradients. - no_scale_out_1000: Turn off scaling of physical length units by 1000\ - for tensor fitting. - no_reweight: Turn off reweighting and refitting of tensors during\ - estimation. - no_cumulative_wts: Turn off displaying overall weight factors for each\ - gradient. - qc_fa_thr: Set threshold for overlay FA volume in QC image. - qc_fa_max: Set cbar max for overlay FA volume in QC image. - qc_fa_unc_max: Set cbar max for overlay uncertainty (stdev) of FA in QC\ - image. - qc_v12_unc_max: Set cbar max for overlay uncertainty (stdev) of V1\ - towards V2 direction for DTs in QC image. - qc_prefix: Set the prefix of the QC image files separately. - no_qc_view: Turn off generating QC image files. - no_cmd_out: Don't save the command line call of this program and the\ - location where it was run. - workdir: Specify a working directory, which can be removed. - no_clean: Do not remove the working directory. - uncert_off: Don't perform uncertainty calculation. - uncert_iters: Set the number of Monte Carlo iterations for the\ - uncertainty calculation (default: 300). - uncert_extra_cmds: Extra commands for the uncertainty calculations. - check_abs_min: Help the program push through finding tiny negative\ - values in columns that should contain numbers >=0. Provide a tolerance\ - value VVV. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcDwiToDtOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_DWI_TO_DT_METADATA) - cargs = [] - cargs.append("fat_proc_dwi_to_dt") - cargs.append(execution.input_file(in_dwi)) - cargs.extend([ - "-in_col_matA | -in_col_matT | -in_col_vec | -in_row_vec", - execution.input_file(in_gradmat) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if in_bvals is not None: - cargs.extend([ - "-in_bvals", - execution.input_file(in_bvals) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mask_from_struc: - cargs.append("-mask_from_struc") - if in_struc_res is not None: - cargs.extend([ - "-in_struc_res", - execution.input_file(in_struc_res) - ]) - if in_ref_orig is not None: - cargs.extend([ - "-in_ref_orig", - execution.input_file(in_ref_orig) - ]) - if prefix_dti is not None: - cargs.extend([ - "-prefix_dti", - prefix_dti - ]) - if flip_x: - cargs.append("-flip_x") - if flip_y: - cargs.append("-flip_y") - if flip_z: - cargs.append("-flip_z") - if no_flip: - cargs.append("-no_flip") - if no_scale_out_1000: - cargs.append("-no_scale_out_1000") - if no_reweight: - cargs.append("-no_reweight") - if no_cumulative_wts: - cargs.append("-no_cumulative_wts") - if qc_fa_thr is not None: - cargs.extend([ - "-qc_fa_thr", - str(qc_fa_thr) - ]) - if qc_fa_max is not None: - cargs.extend([ - "-qc_fa_max", - str(qc_fa_max) - ]) - if qc_fa_unc_max is not None: - cargs.extend([ - "-qc_fa_unc_max", - str(qc_fa_unc_max) - ]) - if qc_v12_unc_max is not None: - cargs.extend([ - "-qc_v12_unc_max", - str(qc_v12_unc_max) - ]) - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - if no_qc_view: - cargs.append("-no_qc_view") - if no_cmd_out: - cargs.append("-no_cmd_out") - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if no_clean: - cargs.append("-no_clean") - if uncert_off: - cargs.append("-uncert_off") - if uncert_iters is not None: - cargs.extend([ - "-uncert_iters", - str(uncert_iters) - ]) - if uncert_extra_cmds is not None: - cargs.extend([ - "-uncert_extra_cmds", - uncert_extra_cmds - ]) - if check_abs_min is not None: - cargs.extend([ - "-check_abs_min", - str(check_abs_min) - ]) - ret = FatProcDwiToDtOutputs( - root=execution.output_file("."), - output_files=execution.output_file(prefix + "*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_DWI_TO_DT_METADATA", - "FatProcDwiToDtOutputs", - "fat_proc_dwi_to_dt", -] diff --git a/python/src/niwrap/afni/fat_proc_filter_dwis.py b/python/src/niwrap/afni/fat_proc_filter_dwis.py deleted file mode 100644 index c8d70c920..000000000 --- a/python/src/niwrap/afni/fat_proc_filter_dwis.py +++ /dev/null @@ -1,140 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_FILTER_DWIS_METADATA = Metadata( - id="f1ab079defa2b7a6a0437c119ce099f8d81cc812.boutiques", - name="fat_proc_filter_dwis", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcFilterDwisOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_filter_dwis(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - filtered_dwi: OutputPathType - """Filtered 4D DWI dataset.""" - filtered_bvecs: OutputPathType - """Filtered gradient file matching input format.""" - filtered_bvals: OutputPathType - """Filtered b-values file, if provided.""" - - -def fat_proc_filter_dwis( - input_dwi: InputPathType, - input_gradient: InputPathType, - select_string: str, - output_prefix: str, - select_file: InputPathType | None = None, - input_bvals: InputPathType | None = None, - unit_mag_out: bool = False, - qc_prefix: str | None = None, - no_qc_view: bool = False, - no_cmd_out: bool = False, - do_movie: typing.Literal["AGIF", "MPEG"] | None = None, - runner: Runner | None = None, -) -> FatProcFilterDwisOutputs: - """ - Filter out user-found and user-defined bad volumes from DWI data sets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dwi: Name of a 4D file of DWIs (required). - input_gradient: Bvec/bmat file from the gradients. Required. One of\ - these options must be used: -in_col_matA, -in_col_matT, -in_col_vec,\ - -in_row_vec. - select_string: A string of indices and index ranges for selecting which\ - volumes/grads/bvals to keep. This string gets applied to the volume,\ - bval|bvec|bmat files for an input set. Either this or -select_file is\ - required. - output_prefix: Output prefix for all the volumes and text files.\ - Required. - select_file: A file containing a string of indices and index ranges for\ - selecting which volumes/grads/bvals to keep. This string gets applied\ - to the volume, bval|bvec|bmat files for an input set. Either this or\ - -select is required. - input_bvals: If the bvec/bmat is a file of unit-magnitude values, then\ - the bvalues can be input. - unit_mag_out: Ensure that the output grad information is unit\ - magnitude. - qc_prefix: Set the prefix of the QC image files separately. - no_qc_view: Turn off generating QC image files. - no_cmd_out: Don't save the command line call of this program and the\ - location where it was run. - do_movie: Output a movie of the newly created dataset (AGIF or MPEG). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcFilterDwisOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_FILTER_DWIS_METADATA) - cargs = [] - cargs.append("fat_proc_filter_dwis") - cargs.extend([ - "-in_dwi", - execution.input_file(input_dwi) - ]) - cargs.extend([ - "-in_col_matA|-in_col_matT|-in_col_vec|-in_row_vec", - execution.input_file(input_gradient) - ]) - cargs.extend([ - "-select", - select_string - ]) - if select_file is not None: - cargs.extend([ - "-select_file", - execution.input_file(select_file) - ]) - cargs.extend([ - "-prefix", - output_prefix - ]) - if input_bvals is not None: - cargs.extend([ - "-in_bvals", - execution.input_file(input_bvals) - ]) - if unit_mag_out: - cargs.append("-unit_mag_out") - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - if no_qc_view: - cargs.append("-no_qc_view") - if no_cmd_out: - cargs.append("-no_cmd_out") - if do_movie is not None: - cargs.extend([ - "-do_movie", - do_movie - ]) - ret = FatProcFilterDwisOutputs( - root=execution.output_file("."), - filtered_dwi=execution.output_file(output_prefix + "_filtered.nii.gz"), - filtered_bvecs=execution.output_file(output_prefix + "_filtered.bvecs"), - filtered_bvals=execution.output_file(output_prefix + "_filtered.bvals"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_FILTER_DWIS_METADATA", - "FatProcFilterDwisOutputs", - "fat_proc_filter_dwis", -] diff --git a/python/src/niwrap/afni/fat_proc_imit2w_from_t1w.py b/python/src/niwrap/afni/fat_proc_imit2w_from_t1w.py deleted file mode 100644 index 5dde3d621..000000000 --- a/python/src/niwrap/afni/fat_proc_imit2w_from_t1w.py +++ /dev/null @@ -1,123 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_IMIT2W_FROM_T1W_METADATA = Metadata( - id="6e7211eeaf18937b51ec873d5287062ff3f44746.boutiques", - name="fat_proc_imit2w_from_t1w", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcImit2wFromT1wOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_imit2w_from_t1w(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - t2w_contrast_volume: OutputPathType - """Volume with T2w-like tissue contrast from T1w""" - cleaned_t1w_volume: OutputPathType - """Cleaned/processed version of the input T1w volume with scaled skull and - noise outside the brain""" - skull_stripped_t1w: OutputPathType - """Skull-stripped version of the T1w volume""" - qc_images: OutputPathType - """QC images of the skull-stripped T1w volume and the final imitation-T2w - volume""" - - -def fat_proc_imit2w_from_t1w( - t1_file: InputPathType, - prefix: str, - workdir: str | None = None, - mask: InputPathType | None = None, - ss_blur_fwhm: float | None = None, - no_clean: bool = False, - no_qc_view: bool = False, - qc_prefix: str | None = None, - runner: Runner | None = None, -) -> FatProcImit2wFromT1wOutputs: - """ - Process T1w anatomical images to generate an imitation T2w-contrast image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - t1_file: Full name of the input T1w volume. - prefix: Output prefix for files and snapshots. - workdir: Specify a working directory, which can be removed (default:\ - __WORKING_imit2w_from_t1w). - mask: Optional input of a pre-skullstripped T1_FILE (either mask or\ - skull-stripped volume). - ss_blur_fwhm: Optional, add in blurring during the 3dSkullStrip part\ - (in mm, default: 2 FWHM). - no_clean: Optional switch to NOT remove working directory\ - '__WORKING_imit2w_from_t1w' (default: remove working dir). - no_qc_view: Turn off the automatic creation of QC montages (default:\ - on). - qc_prefix: Change the prefix of the QC images (default: use prefix of\ - volumes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcImit2wFromT1wOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_IMIT2W_FROM_T1W_METADATA) - cargs = [] - cargs.append("fat_proc_imit2w_from_t1w") - cargs.extend([ - "-inset", - execution.input_file(t1_file) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if ss_blur_fwhm is not None: - cargs.extend([ - "-ss_blur_fwhm", - str(ss_blur_fwhm) - ]) - if no_clean: - cargs.append("-no_clean") - if no_qc_view: - cargs.append("-no_qc_view") - if qc_prefix is not None: - cargs.extend([ - "-qc_prefix", - qc_prefix - ]) - ret = FatProcImit2wFromT1wOutputs( - root=execution.output_file("."), - t2w_contrast_volume=execution.output_file(prefix + ".nii.gz"), - cleaned_t1w_volume=execution.output_file(prefix + "_orig.nii.gz"), - skull_stripped_t1w=execution.output_file(prefix + "_orig_ss.nii.gz"), - qc_images=execution.output_file(prefix + "_qc*.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_IMIT2W_FROM_T1W_METADATA", - "FatProcImit2wFromT1wOutputs", - "fat_proc_imit2w_from_t1w", -] diff --git a/python/src/niwrap/afni/fat_proc_map_to_dti.py b/python/src/niwrap/afni/fat_proc_map_to_dti.py deleted file mode 100644 index 2a0667658..000000000 --- a/python/src/niwrap/afni/fat_proc_map_to_dti.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_MAP_TO_DTI_METADATA = Metadata( - id="474924386097dcd7df273db530cc8e0549474d04.boutiques", - name="fat_proc_map_to_dti", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcMapToDtiOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_map_to_dti(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def fat_proc_map_to_dti( - source: InputPathType, - base: InputPathType, - prefix: str, - followers_nn: list[InputPathType] | None = None, - followers_wsinc5: list[InputPathType] | None = None, - followers_surf: list[InputPathType] | None = None, - followers_ndset: list[InputPathType] | None = None, - followers_spec: list[InputPathType] | None = None, - matrix: InputPathType | None = None, - workdir: str | None = None, - no_cmd_out: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> FatProcMapToDtiOutputs: - """ - A program for mapping data sets into DWI space, suitable for aligning anatomical - ROI maps or EPI data to a DWI reference volume. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - source: T1w volume file (source volume). - base: DWI reference volume file. - prefix: Output prefix for files and snapshots. - followers_nn: Follower data sets with NN interpolation. - followers_wsinc5: Follower data sets with wsinc5 interpolation. - followers_surf: Surface follower data sets. - followers_ndset: NIML follower data sets. - followers_spec: Spec follower data sets. - matrix: Pre-made matrix file for transformation. - workdir: Specify a working directory. - no_cmd_out: Don't save the command line call of this program. - no_clean: Do not delete temporary working directory. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcMapToDtiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_MAP_TO_DTI_METADATA) - cargs = [] - cargs.append("fat_proc_map_to_dti") - cargs.extend([ - "-source", - execution.input_file(source) - ]) - cargs.extend([ - "-base", - execution.input_file(base) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if followers_nn is not None: - cargs.extend([ - "-followers_NN", - *[execution.input_file(f) for f in followers_nn] - ]) - if followers_wsinc5 is not None: - cargs.extend([ - "-followers_wsinc5", - *[execution.input_file(f) for f in followers_wsinc5] - ]) - if followers_surf is not None: - cargs.extend([ - "-followers_surf", - *[execution.input_file(f) for f in followers_surf] - ]) - if followers_ndset is not None: - cargs.extend([ - "-followers_ndset", - *[execution.input_file(f) for f in followers_ndset] - ]) - if followers_spec is not None: - cargs.extend([ - "-followers_spec", - *[execution.input_file(f) for f in followers_spec] - ]) - if matrix is not None: - cargs.extend([ - "-matrix", - execution.input_file(matrix) - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if no_cmd_out: - cargs.append("-no_cmd_out") - if no_clean: - cargs.append("-no_clean") - ret = FatProcMapToDtiOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_MAP_TO_DTI_METADATA", - "FatProcMapToDtiOutputs", - "fat_proc_map_to_dti", -] diff --git a/python/src/niwrap/afni/fat_proc_select_vols.py b/python/src/niwrap/afni/fat_proc_select_vols.py deleted file mode 100644 index 87db3fafa..000000000 --- a/python/src/niwrap/afni/fat_proc_select_vols.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_PROC_SELECT_VOLS_METADATA = Metadata( - id="423b3bdef1ce58c3541799a5887c14712d5adc04.boutiques", - name="fat_proc_select_vols", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatProcSelectVolsOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_proc_select_vols(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_selector_string: OutputPathType - """Text file with AFNI-usable selector string""" - - -def fat_proc_select_vols( - dwi_input: InputPathType, - img_input: InputPathType, - prefix: str, - in_bads: InputPathType | None = None, - apply_to_vols: bool = False, - do_movie: str | None = None, - workdir: str | None = None, - no_cmd_out: bool = False, - runner: Runner | None = None, -) -> FatProcSelectVolsOutputs: - """ - Tool for building a selector string for AFNI subbricks and/or 1D text files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dwi_input: Input DWI dataset. - img_input: 2D image of the DWI dataset. - prefix: Output prefix for files. - in_bads: A single column file of integers representing bad volumes\ - indices (optional). - apply_to_vols: Apply the created selection of good volumes to the DWI\ - dataset. - do_movie: Output a movie of the newly created dataset. Only 'AGIF' or\ - 'MPEG' arguments can be used. - workdir: Specify a working directory. - no_cmd_out: Don't save the command line call of this program and the\ - location where it was run. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatProcSelectVolsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_PROC_SELECT_VOLS_METADATA) - cargs = [] - cargs.append("fat_proc_select_vols") - cargs.append("-in_dwi") - cargs.append(execution.input_file(dwi_input)) - cargs.append("-in_img") - cargs.append(execution.input_file(img_input)) - cargs.append("-prefix") - cargs.append(prefix) - if in_bads is not None: - cargs.extend([ - "-in_bads", - execution.input_file(in_bads) - ]) - if apply_to_vols: - cargs.append("-apply_to_vols") - if do_movie is not None: - cargs.extend([ - "-do_movie", - do_movie - ]) - if workdir is not None: - cargs.extend([ - "-workdir", - workdir - ]) - if no_cmd_out: - cargs.append("-no_cmd_out") - ret = FatProcSelectVolsOutputs( - root=execution.output_file("."), - output_selector_string=execution.output_file(prefix + "_bads.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_PROC_SELECT_VOLS_METADATA", - "FatProcSelectVolsOutputs", - "fat_proc_select_vols", -] diff --git a/python/src/niwrap/afni/fat_roi_row.py b/python/src/niwrap/afni/fat_roi_row.py deleted file mode 100644 index bfcc18efd..000000000 --- a/python/src/niwrap/afni/fat_roi_row.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FAT_ROI_ROW_METADATA = Metadata( - id="f5083921ef214a1b40041c4bf19809f2f02371e8.boutiques", - name="fat_roi_row", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatRoiRowOutputs(typing.NamedTuple): - """ - Output object returned when calling `fat_roi_row(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Selected ROI row output file in .row format.""" - - -def fat_roi_row( - roi: str, - matrix_files: str | None = None, - list_file: InputPathType | None = None, - extern_labs_no: bool = False, - runner: Runner | None = None, -) -> FatRoiRowOutputs: - """ - Select a single ROI's row out of a connectivity matrix file (*.grid or *.netcc) - for viewing and/or further analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - roi: Specify which ROI's row of connectivity you want to select out. If\ - labeltables were used, you may select the ROI by either the string\ - label or the ROI mask number. - matrix_files: Provide the set of matrix (*.grid or *.netcc) files by\ - searchable path. This can be a globbable entry in quotes containing\ - wildcard characters. - list_file: Provide the set of matrix (*.grid or *.netcc) files by\ - explicit path in a text file. The LIST text file must contain at least\ - one column with the path to subject matrix file. - extern_labs_no: Switch to turn off the writing/usage of user-defined\ - labels in the *.grid/*.netcc files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatRoiRowOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FAT_ROI_ROW_METADATA) - cargs = [] - cargs.append("fat_roi_row.py") - cargs.append("-r") - cargs.extend([ - "-r", - roi - ]) - cargs.append("{") - cargs.append("-m") - if matrix_files is not None: - cargs.extend([ - "-m", - matrix_files - ]) - cargs.append("|") - cargs.append("-l") - if list_file is not None: - cargs.extend([ - "-l", - execution.input_file(list_file) - ]) - cargs.append("}") - cargs.append("-E") - if extern_labs_no: - cargs.append("-E") - ret = FatRoiRowOutputs( - root=execution.output_file("."), - output_file=execution.output_file(roi + "_selected.row"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FAT_ROI_ROW_METADATA", - "FatRoiRowOutputs", - "fat_roi_row", -] diff --git a/python/src/niwrap/afni/fatcat_matplot.py b/python/src/niwrap/afni/fatcat_matplot.py deleted file mode 100644 index fd7e19b4e..000000000 --- a/python/src/niwrap/afni/fatcat_matplot.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FATCAT_MATPLOT_METADATA = Metadata( - id="085b4167b85a1cc4f21c43adeefb80758ae946b1.boutiques", - name="FATCAT_matplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FatcatMatplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `fatcat_matplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def fatcat_matplot( - directory: str, - shiny_folder: bool = False, - runner: Runner | None = None, -) -> FatcatMatplotOutputs: - """ - Launch a shiny app to visualize .netcc and/or .grid files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - directory: Path to a folder containing .netcc and/or .grid files. - shiny_folder: Use a custom shiny folder (for testing purposes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FatcatMatplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FATCAT_MATPLOT_METADATA) - cargs = [] - cargs.append("FATCAT_matplot") - cargs.append(directory) - if shiny_folder: - cargs.append("-ShinyFolder") - ret = FatcatMatplotOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FATCAT_MATPLOT_METADATA", - "FatcatMatplotOutputs", - "fatcat_matplot", -] diff --git a/python/src/niwrap/afni/fdrval.py b/python/src/niwrap/afni/fdrval.py deleted file mode 100644 index 0f00412fa..000000000 --- a/python/src/niwrap/afni/fdrval.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FDRVAL_METADATA = Metadata( - id="f92df9dc9c7bd351f5f06439c97a5434e22b31b8.boutiques", - name="fdrval", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FdrvalOutputs(typing.NamedTuple): - """ - Output object returned when calling `fdrval(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """Computed q-values or p-values for the given thresholds""" - - -def fdrval( - dset: InputPathType, - sub: float, - val_list: list[float], - pval: bool = False, - ponly: bool = False, - qonly: bool = False, - qinput: bool = False, - inverse: bool = False, - runner: Runner | None = None, -) -> FdrvalOutputs: - """ - Computes q-values from FDR curve data stored in dataset headers. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Input dataset. - sub: Sub-brick number. - val_list: List of threshold values. - pval: Output the p-value (on the same line, after q). - ponly: Don't output q-values, just p-values. - qonly: Don't output p-values, just q-values. - qinput: The 'val' inputs are taken to be q-values and then the outputs\ - are the corresponding statistical thresholds. - inverse: Inverse of the usual operation. 'Val' inputs must be between 0\ - and 1 (exclusive). Cannot be used with '-ponly' or '-pval'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FdrvalOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FDRVAL_METADATA) - cargs = [] - cargs.append("fdrval") - cargs.append(execution.input_file(dset)) - cargs.append(str(sub)) - cargs.extend(map(str, val_list)) - if pval: - cargs.append("-pval") - if ponly: - cargs.append("-ponly") - if qonly: - cargs.append("-qonly") - if qinput: - cargs.append("-qinput") - if inverse: - cargs.append("-inverse") - ret = FdrvalOutputs( - root=execution.output_file("."), - output=execution.output_file("stdout.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FDRVAL_METADATA", - "FdrvalOutputs", - "fdrval", -] diff --git a/python/src/niwrap/afni/fftest.py b/python/src/niwrap/afni/fftest.py deleted file mode 100644 index 47d579427..000000000 --- a/python/src/niwrap/afni/fftest.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FFTEST_METADATA = Metadata( - id="d36ef0d937165dece9dda123ca931abfcf2bf0b0.boutiques", - name="fftest", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FftestOutputs(typing.NamedTuple): - """ - Output object returned when calling `fftest(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def fftest( - length: float, - num_tests: float, - vector_size: float, - quiet_mode: bool = False, - runner: Runner | None = None, -) -> FftestOutputs: - """ - A command line tool for testing purposes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - length: Length of the test. - num_tests: Number of tests to run. - vector_size: Vector size for the test. - quiet_mode: Quiet mode. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FftestOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FFTEST_METADATA) - cargs = [] - cargs.append("fftest") - cargs.append(str(length)) - cargs.append(str(num_tests)) - cargs.append(str(vector_size)) - if quiet_mode: - cargs.append("-q") - ret = FftestOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FFTEST_METADATA", - "FftestOutputs", - "fftest", -] diff --git a/python/src/niwrap/afni/file_tool.py b/python/src/niwrap/afni/file_tool.py deleted file mode 100644 index 89b65ae6a..000000000 --- a/python/src/niwrap/afni/file_tool.py +++ /dev/null @@ -1,252 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FILE_TOOL_METADATA = Metadata( - id="a338b51bc00f0441446c6ca843266cef70008a68.boutiques", - name="file_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FileToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `file_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - modified_file: OutputPathType | None - """The modified output file""" - - -def file_tool( - infiles: list[InputPathType], - help_: bool = False, - version: bool = False, - hist: bool = False, - debug: float | None = None, - ge_all: bool = False, - ge_header: bool = False, - ge_extras: bool = False, - ge_uv17: bool = False, - ge_run: bool = False, - ge_off: bool = False, - ge4_all: bool = False, - ge4_image: bool = False, - ge4_series: bool = False, - ge4_study: bool = False, - def_ana_hdr: bool = False, - diff_ana_hdrs: bool = False, - disp_ana_hdr: bool = False, - hex_: bool = False, - mod_ana_hdr: bool = False, - mod_field: str | None = None, - prefix: str | None = None, - overwrite: bool = False, - show_bad_all: bool = False, - show_bad_backslash: bool = False, - show_bad_char: bool = False, - show_file_type: bool = False, - fix_rich_quotes: str | None = None, - test: bool = False, - length: float | None = None, - mod_data: str | None = None, - mod_type: str | None = None, - offset: float | None = None, - quiet: bool = False, - disp_hex: bool = False, - disp_hex1: bool = False, - disp_hex2: bool = False, - disp_hex4: bool = False, - disp_int2: bool = False, - disp_int4: bool = False, - disp_real4: bool = False, - swap_bytes: bool = False, - runner: Runner | None = None, -) -> FileToolOutputs: - """ - Program to display or modify sections of a file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infiles: Specify input files to display or modify. - help_: Show help information. - version: Show version information. - hist: Show the program's modification history. - debug: Print extra info along the way, default is 0, max is 2. - ge_all: Display GE header and extras info. - ge_header: Display GE header info. - ge_extras: Display extra GE image info. - ge_uv17: Display the value of uv17 (the run #). - ge_run: Display the value of uv17 (the run #). - ge_off: Display file offsets for various fields. - ge4_all: Display GEMS 4.x series and image headers. - ge4_image: Display GEMS 4.x image header. - ge4_series: Display GEMS 4.x series header. - ge4_study: Display GEMS 4.x study header. - def_ana_hdr: Display the definition of an ANALYZE header. - diff_ana_hdrs: Display field differences between 2 headers. - disp_ana_hdr: Display ANALYZE headers. - hex_: Display field values in hexadecimal. - mod_ana_hdr: Modify ANALYZE headers. - mod_field: Specify a field and value(s) to modify. - prefix: Specify an output filename. - overwrite: Specify to overwrite the input file(s). - show_bad_all: Show lines with whitespace after '\\'. - show_bad_backslash: Show lines with whitespace after '\\'. - show_bad_char: Show any non-printable characters. - show_file_type: Print file type of UNIX, Mac or DOS. - fix_rich_quotes: Replace rich-text quotes with ASCII. - test: Short for -show_bad_all. Check script files for known issues. - length: Specify the number of bytes to print/modify. - mod_data: Specify a string to modify the data to. - mod_type: Specify the data type to write to the file. - offset: Specify the offset into each file. - quiet: Do not output header information. - disp_hex: Display bytes in hex. - disp_hex1: Display bytes in hex. - disp_hex2: Display 2-byte integers in hex. - disp_hex4: Display 4-byte integers in hex. - disp_int2: Display 2-byte integers. - disp_int4: Display 4-byte integers. - disp_real4: Display 4-byte real numbers. - swap_bytes: Use byte-swapping on numbers. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FileToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FILE_TOOL_METADATA) - cargs = [] - cargs.append("file_tool") - if help_: - cargs.append("-help") - if version: - cargs.append("-version") - if hist: - cargs.append("-hist") - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - cargs.extend([ - "-infiles", - *[execution.input_file(f) for f in infiles] - ]) - if ge_all: - cargs.append("-ge_all") - if ge_header: - cargs.append("-ge_header") - if ge_extras: - cargs.append("-ge_extras") - if ge_uv17: - cargs.append("-ge_uv17") - if ge_run: - cargs.append("-ge_run") - if ge_off: - cargs.append("-ge_off") - if ge4_all: - cargs.append("-ge4_all") - if ge4_image: - cargs.append("-ge4_image") - if ge4_series: - cargs.append("-ge4_series") - if ge4_study: - cargs.append("-ge4_study") - if def_ana_hdr: - cargs.append("-def_ana_hdr") - if diff_ana_hdrs: - cargs.append("-diff_ana_hdrs") - if disp_ana_hdr: - cargs.append("-disp_ana_hdr") - if hex_: - cargs.append("-hex") - if mod_ana_hdr: - cargs.append("-mod_ana_hdr") - if mod_field is not None: - cargs.extend([ - "-mod_field", - mod_field - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if overwrite: - cargs.append("-overwrite") - if show_bad_all: - cargs.append("-show_bad_all") - if show_bad_backslash: - cargs.append("-show_bad_backslash") - if show_bad_char: - cargs.append("-show_bad_char") - if show_file_type: - cargs.append("-show_file_type") - if fix_rich_quotes is not None: - cargs.extend([ - "-fix_rich_quotes", - fix_rich_quotes - ]) - if test: - cargs.append("-test") - if length is not None: - cargs.extend([ - "-length", - str(length) - ]) - if mod_data is not None: - cargs.extend([ - "-mod_data", - mod_data - ]) - if mod_type is not None: - cargs.extend([ - "-mod_type", - mod_type - ]) - if offset is not None: - cargs.extend([ - "-offset", - str(offset) - ]) - if quiet: - cargs.append("-quiet") - if disp_hex: - cargs.append("-disp_hex") - if disp_hex1: - cargs.append("-disp_hex1") - if disp_hex2: - cargs.append("-disp_hex2") - if disp_hex4: - cargs.append("-disp_hex4") - if disp_int2: - cargs.append("-disp_int2") - if disp_int4: - cargs.append("-disp_int4") - if disp_real4: - cargs.append("-disp_real4") - if swap_bytes: - cargs.append("-swap_bytes") - ret = FileToolOutputs( - root=execution.output_file("."), - modified_file=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FILE_TOOL_METADATA", - "FileToolOutputs", - "file_tool", -] diff --git a/python/src/niwrap/afni/fim2.py b/python/src/niwrap/afni/fim2.py deleted file mode 100644 index 3e5a39e2c..000000000 --- a/python/src/niwrap/afni/fim2.py +++ /dev/null @@ -1,217 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FIM2_METADATA = Metadata( - id="dc4766ddbc19de164de7f967033e9406b2958bcf.boutiques", - name="fim2", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Fim2Outputs(typing.NamedTuple): - """ - Output object returned when calling `fim2(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - activation_magnitudes: OutputPathType | None - """Activation magnitudes output file""" - correlation_image: OutputPathType | None - """Correlation image output file""" - contrast_to_noise_image: OutputPathType | None - """Contrast-to-noise image output file""" - std_deviation_image: OutputPathType | None - """Standard deviation image output file""" - ls_fit_coefficients: OutputPathType | None - """Least squares fit coefficients image files""" - subtracted_references: OutputPathType | None - """Subtracted ortho reference time series images""" - - -def fim2( - image_files: list[InputPathType], - pcnt: float | None = None, - pcthresh: float | None = None, - im1: int | None = None, - num: int | None = None, - non: bool = False, - coef: float | None = None, - ort: list[InputPathType] | None = None, - ideal: list[InputPathType] | None = None, - polref: int | None = None, - fimfile: str | None = None, - corr: bool = False, - corfile: str | None = None, - cnrfile: str | None = None, - sigfile: str | None = None, - fitfile: str | None = None, - subort: str | None = None, - flim: bool = False, - clean: bool = False, - clip: bool = False, - q: bool = False, - dfspace: bool = False, - regbase: str | None = None, - runner: Runner | None = None, -) -> Fim2Outputs: - """ - Functional Imaging Mapping Tool. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - image_files: Input MRI image files. - pcnt: Correlation coefficient threshold will be 1 - 0.01 * #. - pcthresh: Correlation coefficient threshold will be #. - im1: Index of image file to use as first in time series; default is 1. - num: Number of images to actually use; default is to use all images. - non: Turn off default normalization of the output activation image. - coef: Scaling factor to convert the activation output from floats to\ - short ints. - ort: Filename of a time series to which the image data will be\ - orthogonalized before correlations are computed. - ideal: Filename of a time series to which the image data is to be\ - correlated. - polref: Use polynomials of order 0..# as extra 'orts'; default is 0. - fimfile: Filename to save activation magnitudes in. - corr: Indicates to write correlation output to image file\ - 'fimfile.CORR'. - corfile: Filename to save correlation image in. - cnrfile: Filename to save contrast-to-noise image in. - sigfile: Filename to save standard deviation image in. - fitfile: Image files of the least squares fit coefficients of all the\ - -ort and -polref time series. - subort: Filename of the new timeseries of images with the orts and\ - polrefs subtracted out. - flim: Write outputs in mrilib 'float' format. - clean: Output images won't have the +/- 10000 values forced into their\ - corners for scaling purposes. - clip: Set to zero regions of low intensity in output correlations, etc. - q: Quiet operation mode. - dfspace: Use the 'dfspace' filter to register the images spatially\ - before filtering. - regbase: Read image in file 'fname' as the base image for registration. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Fim2Outputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FIM2_METADATA) - cargs = [] - cargs.append("fim2") - cargs.extend([execution.input_file(f) for f in image_files]) - if pcnt is not None: - cargs.extend([ - "-pcnt", - str(pcnt) - ]) - if pcthresh is not None: - cargs.extend([ - "-pcthresh", - str(pcthresh) - ]) - if im1 is not None: - cargs.extend([ - "-im1", - str(im1) - ]) - if num is not None: - cargs.extend([ - "-num", - str(num) - ]) - if non: - cargs.append("-non") - if coef is not None: - cargs.extend([ - "-coef", - str(coef) - ]) - if ort is not None: - cargs.extend([ - "-ort", - *[execution.input_file(f) for f in ort] - ]) - if ideal is not None: - cargs.extend([ - "-ideal", - *[execution.input_file(f) for f in ideal] - ]) - if polref is not None: - cargs.extend([ - "-polref", - str(polref) - ]) - if fimfile is not None: - cargs.extend([ - "-fimfile", - fimfile - ]) - if corr: - cargs.append("-corr") - if corfile is not None: - cargs.extend([ - "-corfile", - corfile - ]) - if cnrfile is not None: - cargs.extend([ - "-cnrfile", - cnrfile - ]) - if sigfile is not None: - cargs.extend([ - "-sigfile", - sigfile - ]) - if fitfile is not None: - cargs.extend([ - "-fitfile", - fitfile - ]) - if subort is not None: - cargs.extend([ - "-subort", - subort - ]) - if flim: - cargs.append("-flim") - if clean: - cargs.append("-clean") - if clip: - cargs.append("-clip") - if q: - cargs.append("-q") - if dfspace: - cargs.append("-dfspace") - if regbase is not None: - cargs.extend([ - "-regbase", - regbase - ]) - ret = Fim2Outputs( - root=execution.output_file("."), - activation_magnitudes=execution.output_file(fimfile) if (fimfile is not None) else None, - correlation_image=execution.output_file(corfile) if (corfile is not None) else None, - contrast_to_noise_image=execution.output_file(cnrfile) if (cnrfile is not None) else None, - std_deviation_image=execution.output_file(sigfile) if (sigfile is not None) else None, - ls_fit_coefficients=execution.output_file(fitfile) if (fitfile is not None) else None, - subtracted_references=execution.output_file(subort) if (subort is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FIM2_METADATA", - "Fim2Outputs", - "fim2", -] diff --git a/python/src/niwrap/afni/find_variance_lines.py b/python/src/niwrap/afni/find_variance_lines.py deleted file mode 100644 index 820aee5c0..000000000 --- a/python/src/niwrap/afni/find_variance_lines.py +++ /dev/null @@ -1,163 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FIND_VARIANCE_LINES_METADATA = Metadata( - id="400a7e1ff61116676091a1736a0b5ffb08f0a496.boutiques", - name="find_variance_lines", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FindVarianceLinesOutputs(typing.NamedTuple): - """ - Output object returned when calling `find_variance_lines(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - variance_maps: OutputPathType | None - """Variance maps per run""" - scaled_variance_maps: OutputPathType | None - """Scaled variance maps per run""" - cluster_reports: OutputPathType | None - """Cluster reports""" - jpeg_images: OutputPathType | None - """JPEG images showing locations of high variance""" - - -def find_variance_lines( - input_files: list[InputPathType], - mask: str | None = None, - min_cvox: int | None = None, - min_nt: int | None = None, - nerode: int | None = None, - nfirst: int | None = None, - percentile: int | None = None, - polort: str | None = None, - output_dir: str | None = None, - do_clean: int | None = None, - do_img: int | None = None, - echo: bool = False, - help_: bool = False, - hist: bool = False, - ver: bool = False, - runner: Runner | None = None, -) -> FindVarianceLinesOutputs: - """ - Look for bars of high variance that might suggest scanner interference in EPI - datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input EPI datasets. - mask: Mask for computations (default=AUTO). - min_cvox: Minimum voxels for valid mask column (default=5). - min_nt: Minimum number of time points required (default=10). - nerode: How much to erode input or auto-mask (default=0). - nfirst: Discard the first VAL time points (default=0). - percentile: Percentile of variance values to scale to (default=90). - polort: Polynomial detrending degree (default=A). - output_dir: Name of the output directory (default=vlines.result). - do_clean: Do we clean up a little? (default=1). - do_img: Make vline images? (default=1). - echo: Run script with shell 'echo' set (default=no). - help_: Show this help. - hist: Show the version history. - ver: Show the current version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FindVarianceLinesOutputs`). - """ - if percentile is not None and not (0 <= percentile <= 99): - raise ValueError(f"'percentile' must be between 0 <= x <= 99 but was {percentile}") - if do_clean is not None and not (0 <= do_clean <= 1): - raise ValueError(f"'do_clean' must be between 0 <= x <= 1 but was {do_clean}") - if do_img is not None and not (0 <= do_img <= 1): - raise ValueError(f"'do_img' must be between 0 <= x <= 1 but was {do_img}") - runner = runner or get_global_runner() - execution = runner.start_execution(FIND_VARIANCE_LINES_METADATA) - cargs = [] - cargs.append("find_variance_lines.tcsh") - cargs.extend([execution.input_file(f) for f in input_files]) - if mask is not None: - cargs.extend([ - "-mask", - mask - ]) - if min_cvox is not None: - cargs.extend([ - "-min_cvox", - str(min_cvox) - ]) - if min_nt is not None: - cargs.extend([ - "-min_nt", - str(min_nt) - ]) - if nerode is not None: - cargs.extend([ - "-nerode", - str(nerode) - ]) - if nfirst is not None: - cargs.extend([ - "-nfirst", - str(nfirst) - ]) - if percentile is not None: - cargs.extend([ - "-perc", - str(percentile) - ]) - if polort is not None: - cargs.extend([ - "-polort", - polort - ]) - if output_dir is not None: - cargs.extend([ - "-rdir", - output_dir - ]) - if do_clean is not None: - cargs.extend([ - "-do_clean", - str(do_clean) - ]) - if do_img is not None: - cargs.extend([ - "-do_img", - str(do_img) - ]) - if echo: - cargs.append("-echo") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if ver: - cargs.append("-ver") - ret = FindVarianceLinesOutputs( - root=execution.output_file("."), - variance_maps=execution.output_file(output_dir + "/variance_map_run*.nii.gz") if (output_dir is not None) else None, - scaled_variance_maps=execution.output_file(output_dir + "/scaled_variance_map_run*.nii.gz") if (output_dir is not None) else None, - cluster_reports=execution.output_file(output_dir + "/cluster_report_run*.txt") if (output_dir is not None) else None, - jpeg_images=execution.output_file(output_dir + "/*.jpg") if (output_dir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FIND_VARIANCE_LINES_METADATA", - "FindVarianceLinesOutputs", - "find_variance_lines", -] diff --git a/python/src/niwrap/afni/firdesign.py b/python/src/niwrap/afni/firdesign.py deleted file mode 100644 index f13572676..000000000 --- a/python/src/niwrap/afni/firdesign.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FIRDESIGN_METADATA = Metadata( - id="a74504adf0b49ec5a0615bc609bf67d8b73823f0.boutiques", - name="FIRdesign", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FirdesignOutputs(typing.NamedTuple): - """ - Output object returned when calling `firdesign(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def firdesign( - fbot: float, - ftop: float, - ntap: float, - tr: float | None = None, - alternative_band: list[float] | None = None, - alternative_ntap: float | None = None, - runner: Runner | None = None, -) -> FirdesignOutputs: - """ - Uses the Remez algorithm to calculate the FIR filter weights for a bandpass - filter; results are written to stdout in an unadorned (no header) column of - numbers. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fbot: Lowest frequency in the pass band. - ftop: Highest frequency in the pass band, must be higher than fbot and\ - <= 0.5/TR. - ntap: Number of filter weights (AKA 'taps') to use, must be in the\ - range 8..2000 (inclusive). - tr: Set time grid spacing to 'dd' [default is 1.0]. - alternative_band: Alternative way to specify the passband. - alternative_ntap: Alternative way to specify the number of taps. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FirdesignOutputs`). - """ - if not (0 <= fbot): - raise ValueError(f"'fbot' must be greater than 0 <= x but was {fbot}") - if not (0 <= ftop): - raise ValueError(f"'ftop' must be greater than 0 <= x but was {ftop}") - if not (8 <= ntap <= 2000): - raise ValueError(f"'ntap' must be between 8 <= x <= 2000 but was {ntap}") - if alternative_ntap is not None and not (8 <= alternative_ntap <= 2000): - raise ValueError(f"'alternative_ntap' must be between 8 <= x <= 2000 but was {alternative_ntap}") - runner = runner or get_global_runner() - execution = runner.start_execution(FIRDESIGN_METADATA) - cargs = [] - cargs.append("FIRdesign") - cargs.append(str(fbot)) - cargs.append(str(ftop)) - cargs.append(str(ntap)) - if tr is not None: - cargs.extend([ - "-TR", - str(tr) - ]) - if alternative_band is not None: - cargs.extend([ - "-band", - *map(str, alternative_band) - ]) - if alternative_ntap is not None: - cargs.extend([ - "-ntap", - str(alternative_ntap) - ]) - ret = FirdesignOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FIRDESIGN_METADATA", - "FirdesignOutputs", - "firdesign", -] diff --git a/python/src/niwrap/afni/float_scan.py b/python/src/niwrap/afni/float_scan.py deleted file mode 100644 index 26c437560..000000000 --- a/python/src/niwrap/afni/float_scan.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FLOAT_SCAN_METADATA = Metadata( - id="7f0b4871d3f11c7378179da06f7acc8b8434976f.boutiques", - name="float_scan", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FloatScanOutputs(typing.NamedTuple): - """ - Output object returned when calling `float_scan(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout_file: OutputPathType - """Output file with illegal values replaced by 0 when -fix flag is used""" - - -def float_scan( - input_file: InputPathType, - fix_illegal_values: bool = False, - verbose_mode: bool = False, - skip_count: int | None = None, - runner: Runner | None = None, -) -> FloatScanOutputs: - """ - Scans the input file of IEEE floating point numbers for illegal values: - infinities and not-a-number (NaN) values. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input file containing IEEE floating point numbers. - fix_illegal_values: Writes a copy of the input file to stdout,\ - replacing illegal values with 0. - verbose_mode: Verbose mode: print out index of each illegal value. - skip_count: Skip the first n floating point locations (i.e., the first\ - 4*n bytes) in the file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FloatScanOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FLOAT_SCAN_METADATA) - cargs = [] - cargs.append("float_scan") - if fix_illegal_values: - cargs.append("-fix") - if verbose_mode: - cargs.append("-v") - if skip_count is not None: - cargs.extend([ - "-skip", - str(skip_count) - ]) - cargs.append(execution.input_file(input_file)) - ret = FloatScanOutputs( - root=execution.output_file("."), - stdout_file=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FLOAT_SCAN_METADATA", - "FloatScanOutputs", - "float_scan", -] diff --git a/python/src/niwrap/afni/from3d.py b/python/src/niwrap/afni/from3d.py deleted file mode 100644 index eec144016..000000000 --- a/python/src/niwrap/afni/from3d.py +++ /dev/null @@ -1,123 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FROM3D_METADATA = Metadata( - id="f1fd9173af972349aa65df96d4aeba216307ee59.boutiques", - name="from3d", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class From3dOutputs(typing.NamedTuple): - """ - Output object returned when calling `from3d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - extracted_images: OutputPathType - """Extracted 2D images from the 3D dataset""" - - -def from3d( - input_: InputPathType, - prefix: str, - verbose: bool = False, - nsize: bool = False, - raw: bool = False, - float_: bool = False, - zfirst: float | None = None, - zlast: float | None = None, - tfirst: float | None = None, - tlast: float | None = None, - runner: Runner | None = None, -) -> From3dOutputs: - """ - Extract 2D image files from a 3D AFNI dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Read 3D dataset from file 'fname'. - prefix: Write 2D images using prefix 'rname'. - verbose: Print out verbose information during the run. - nsize: Adjust size of 2D data file to be NxN, by padding with zeros,\ - where N is a power of 2. - raw: Write images in 'raw' format (just the data bytes). There will be\ - no header information saying what the image dimensions are. - float_: Write images as floats, no matter what they are in the dataset\ - itself. - zfirst: Set 'num' = number of first z slice to be extracted (default =\ - 1). - zlast: Set 'num' = number of last z slice to be extracted (default =\ - largest). - tfirst: Set 'num' = number of first time slice to be extracted (default\ - = 1). - tlast: Set 'num' = number of last time slice to be extracted (default =\ - largest). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `From3dOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FROM3D_METADATA) - cargs = [] - cargs.append("from3d") - if verbose: - cargs.append("-v") - if nsize: - cargs.append("-nsize") - if raw: - cargs.append("-raw") - if float_: - cargs.append("-float") - if zfirst is not None: - cargs.extend([ - "-zfirst", - str(zfirst) - ]) - if zlast is not None: - cargs.extend([ - "-zlast", - str(zlast) - ]) - if tfirst is not None: - cargs.extend([ - "-tfirst", - str(tfirst) - ]) - if tlast is not None: - cargs.extend([ - "-tlast", - str(tlast) - ]) - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - ret = From3dOutputs( - root=execution.output_file("."), - extracted_images=execution.output_file(prefix + "*.img"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FROM3D_METADATA", - "From3dOutputs", - "from3d", -] diff --git a/python/src/niwrap/afni/fsread_annot.py b/python/src/niwrap/afni/fsread_annot.py deleted file mode 100644 index 8708a7246..000000000 --- a/python/src/niwrap/afni/fsread_annot.py +++ /dev/null @@ -1,141 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -FSREAD_ANNOT_METADATA = Metadata( - id="d6cd0f7bce55789b13d629787f5523d58b155de7.boutiques", - name="FSread_annot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class FsreadAnnotOutputs(typing.NamedTuple): - """ - Output object returned when calling `fsread_annot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_col_1d: OutputPathType - """Output 4-column 1D color file.""" - out_roi_1d: OutputPathType - """Output 5-column 1D ROI file.""" - out_niml_dset: OutputPathType - """Output niml formatted label dataset.""" - out_cmap_1d: OutputPathType - """Output 4-column 1D color map file.""" - - -def fsread_annot( - infile: InputPathType, - hemi: str | None = None, - fscmap: InputPathType | None = None, - fscmap_range: list[float] | None = None, - fsversion: str | None = None, - col_1d: str | None = None, - roi_1d: str | None = None, - cmap_1d: str | None = None, - show_fscmap: bool = False, - dset: str | None = None, - help_: bool = False, - runner: Runner | None = None, -) -> FsreadAnnotOutputs: - """ - Reads a FreeSurfer annotation file and outputs an equivalent ROI file and/or a - colormap file for use with SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Binary formatted FreeSurfer annotation file. - hemi: Specify hemisphere. HEMI is one of lh or rh. Program guesses by\ - default. - fscmap: Get the colormap from the Freesurfer colormap file CMAPFILE.\ - Colormaps inside the ANNOTFILE would be ignored. - fscmap_range: CMAPFILE contains multiple types of labels. The\ - annotation values in ANNOTFILE can map to multiple labels if you do not\ - restrict the range with iMin and iMax. - fsversion: VER is the annotation file vintage. Choose from 2009 or\ - 2005. - col_1d: Write a 4-column 1D color file. - roi_1d: Write a 5-column 1D roi file. - cmap_1d: Write a 4-column 1D color map file. - show_fscmap: Show the info of the colormap in the ANNOT file. - dset: Write the annotation and colormap as a niml formatted Label Dset. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `FsreadAnnotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(FSREAD_ANNOT_METADATA) - cargs = [] - cargs.append("FSread_annot") - cargs.append("--input") - cargs.append(execution.input_file(infile)) - if hemi is not None: - cargs.extend([ - "-hemi", - hemi - ]) - if fscmap is not None: - cargs.extend([ - "-FScmap", - execution.input_file(fscmap) - ]) - if fscmap_range is not None: - cargs.extend([ - "-FScmaprange", - *map(str, fscmap_range) - ]) - if fsversion is not None: - cargs.extend([ - "-FSversion", - fsversion - ]) - if col_1d is not None: - cargs.extend([ - "-col_1D", - col_1d - ]) - if roi_1d is not None: - cargs.extend([ - "-roi_1D", - roi_1d - ]) - if cmap_1d is not None: - cargs.extend([ - "-cmap_1D", - cmap_1d - ]) - if show_fscmap: - cargs.append("-show_FScmap") - if dset is not None: - cargs.extend([ - "-dset", - dset - ]) - if help_: - cargs.append("-help") - ret = FsreadAnnotOutputs( - root=execution.output_file("."), - out_col_1d=execution.output_file("annot.1D.col"), - out_roi_1d=execution.output_file("annot.1D.roi"), - out_niml_dset=execution.output_file("annot.niml.dset"), - out_cmap_1d=execution.output_file("annot.1D.cmap"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "FSREAD_ANNOT_METADATA", - "FsreadAnnotOutputs", - "fsread_annot", -] diff --git a/python/src/niwrap/afni/gen_epi_review_py.py b/python/src/niwrap/afni/gen_epi_review_py.py deleted file mode 100644 index 13cb6ba8d..000000000 --- a/python/src/niwrap/afni/gen_epi_review_py.py +++ /dev/null @@ -1,124 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GEN_EPI_REVIEW_PY_METADATA = Metadata( - id="4fec13541e12c24be0f1212f2da80b15e3aa36b4.boutiques", - name="gen_epi_review.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GenEpiReviewPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `gen_epi_review_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def gen_epi_review_py( - datasets: list[str], - script_name: str | None = None, - windows: list[str] | None = None, - verbosity: float | None = None, - image_size: list[float] | None = None, - image_xoffset: float | None = None, - image_yoffset: float | None = None, - graph_size: list[float] | None = None, - graph_xoffset: float | None = None, - graph_yoffset: float | None = None, - runner: Runner | None = None, -) -> GenEpiReviewPyOutputs: - """ - Generate an AFNI processing script to review EPI data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Specify input datasets for processing. - script_name: Specify the name of the generated script. - windows: Specify the image windows to open. - verbosity: Specify a verbosity level. - image_size: Set image dimensions, in pixels. - image_xoffset: Set the X-offset for the image, in pixels. - image_yoffset: Set the Y-offset for the image, in pixels. - graph_size: Set graph dimensions, in pixels. - graph_xoffset: Set the X-offset for the graph, in pixels. - graph_yoffset: Set the Y-offset for the graph, in pixels. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GenEpiReviewPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GEN_EPI_REVIEW_PY_METADATA) - cargs = [] - cargs.append("gen_epi_review.py") - cargs.extend([ - "-dsets", - *datasets - ]) - if script_name is not None: - cargs.extend([ - "-script", - script_name - ]) - if windows is not None: - cargs.extend([ - "-windows", - *windows - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - if image_size is not None: - cargs.extend([ - "-im_size", - *map(str, image_size) - ]) - if image_xoffset is not None: - cargs.extend([ - "-im_xoff", - str(image_xoffset) - ]) - if image_yoffset is not None: - cargs.extend([ - "-im_yoff", - str(image_yoffset) - ]) - if graph_size is not None: - cargs.extend([ - "-gr_size", - *map(str, graph_size) - ]) - if graph_xoffset is not None: - cargs.extend([ - "-gr_xoff", - str(graph_xoffset) - ]) - if graph_yoffset is not None: - cargs.extend([ - "-gr_yoff", - str(graph_yoffset) - ]) - ret = GenEpiReviewPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GEN_EPI_REVIEW_PY_METADATA", - "GenEpiReviewPyOutputs", - "gen_epi_review_py", -] diff --git a/python/src/niwrap/afni/gen_group_command.py b/python/src/niwrap/afni/gen_group_command.py deleted file mode 100644 index e0f857c76..000000000 --- a/python/src/niwrap/afni/gen_group_command.py +++ /dev/null @@ -1,142 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GEN_GROUP_COMMAND_METADATA = Metadata( - id="4fe3201bf131205f747bb9a5634cc52a3ce35255.boutiques", - name="gen_group_command", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GenGroupCommandOutputs(typing.NamedTuple): - """ - Output object returned when calling `gen_group_command(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_script: OutputPathType | None - """The generated command script file""" - - -def gen_group_command( - command_name: str, - datasets: list[str], - prefix: str | None = None, - set_labels: list[str] | None = None, - subj_prefix: str | None = None, - subj_suffix: str | None = None, - subs_betas: list[str] | None = None, - subs_tstats: list[str] | None = None, - type_: str | None = None, - verb: str | None = None, - write_script: str | None = None, - other_options: list[str] | None = None, - runner: Runner | None = None, -) -> GenGroupCommandOutputs: - """ - Generate group analysis command scripts by parsing wildcard-based lists of input - datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - command_name: Resulting command, such as 3dttest++. - datasets: List of datasets, can be used multiple times for different\ - groups. - prefix: Prefix for the output file names. - set_labels: Labels corresponding to datasets entries. - subj_prefix: Prefix for subject names. - subj_suffix: Suffix for subject names. - subs_betas: Sub-bricks for beta weights. - subs_tstats: Sub-bricks for t-stats (3dMEMA). - type_: Specify the type of test to perform. - verb: Set the verbosity level. - write_script: Write command script to specified file name. - other_options: List of options to pass along to result. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GenGroupCommandOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GEN_GROUP_COMMAND_METADATA) - cargs = [] - cargs.append("gen_group_command.py") - cargs.extend([ - "-command", - command_name - ]) - cargs.extend([ - "-dsets", - *datasets - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if set_labels is not None: - cargs.extend([ - "-set_labels", - *set_labels - ]) - if subj_prefix is not None: - cargs.extend([ - "-subj_prefix", - subj_prefix - ]) - if subj_suffix is not None: - cargs.extend([ - "-subj_suffix", - subj_suffix - ]) - if subs_betas is not None: - cargs.extend([ - "-subs_betas", - *subs_betas - ]) - if subs_tstats is not None: - cargs.extend([ - "-subs_tstats", - *subs_tstats - ]) - if type_ is not None: - cargs.extend([ - "-type", - type_ - ]) - if verb is not None: - cargs.extend([ - "-verb", - verb - ]) - if write_script is not None: - cargs.extend([ - "-write_script", - write_script - ]) - if other_options is not None: - cargs.extend([ - "-options", - *other_options - ]) - ret = GenGroupCommandOutputs( - root=execution.output_file("."), - output_script=execution.output_file(write_script) if (write_script is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GEN_GROUP_COMMAND_METADATA", - "GenGroupCommandOutputs", - "gen_group_command", -] diff --git a/python/src/niwrap/afni/gen_ss_review_scripts.py b/python/src/niwrap/afni/gen_ss_review_scripts.py deleted file mode 100644 index 619214c9f..000000000 --- a/python/src/niwrap/afni/gen_ss_review_scripts.py +++ /dev/null @@ -1,197 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GEN_SS_REVIEW_SCRIPTS_METADATA = Metadata( - id="0b2bced52ccd788df5199b4d3c54d3385072af7d.boutiques", - name="gen_ss_review_scripts", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GenSsReviewScriptsOutputs(typing.NamedTuple): - """ - Output object returned when calling `gen_ss_review_scripts(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - basic_review: OutputPathType - """Basic review script output""" - driver_review: OutputPathType - """Driver review script output""" - driver_commands: OutputPathType - """Driver commands script output""" - - -def gen_ss_review_scripts( - subject_id: str | None = None, - rm_trs: float | None = None, - num_stim: float | None = None, - mb_level: float | None = None, - slice_pattern: str | None = None, - motion_dset: InputPathType | None = None, - outlier_dset: InputPathType | None = None, - enorm_dset: InputPathType | None = None, - mot_limit: float | None = None, - out_limit: float | None = None, - xmat_regress: InputPathType | None = None, - xmat_uncensored: InputPathType | None = None, - stats_dset: InputPathType | None = None, - final_anat: InputPathType | None = None, - final_view: str | None = None, - prefix: str | None = None, - verbosity: float | None = None, - uvars_json: InputPathType | None = None, - init_uvars_json: InputPathType | None = None, - runner: Runner | None = None, -) -> GenSsReviewScriptsOutputs: - """ - Generate single subject analysis review scripts. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subject_id: Subject ID. - rm_trs: Number of TRs removed per run. - num_stim: Number of main stimulus classes. - mb_level: Multiband slice acquisition level (>= 1). - slice_pattern: Slice timing pattern. - motion_dset: Motion parameters dataset. - outlier_dset: Outlier fraction time series dataset. - enorm_dset: Euclidean norm of motion parameters dataset. - mot_limit: Motion limit. - out_limit: Outlier fraction limit. - xmat_regress: X-matrix file used in regression. - xmat_uncensored: Un-censored X-matrix file. - stats_dset: Output from 3dDeconvolve. - final_anat: Final anatomical dataset. - final_view: Final view of data (e.g. 'orig' or 'tlrc'). - prefix: Set the prefix for script names. - verbosity: Set the verbosity level. - uvars_json: Write JSON file of user variables dict. - init_uvars_json: Initialize user variables from the given JSON file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GenSsReviewScriptsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GEN_SS_REVIEW_SCRIPTS_METADATA) - cargs = [] - cargs.append("gen_ss_review_scripts.py") - if subject_id is not None: - cargs.extend([ - "-subj", - subject_id - ]) - if rm_trs is not None: - cargs.extend([ - "-rm_trs", - str(rm_trs) - ]) - if num_stim is not None: - cargs.extend([ - "-num_stim", - str(num_stim) - ]) - if mb_level is not None: - cargs.extend([ - "-mb_level", - str(mb_level) - ]) - if slice_pattern is not None: - cargs.extend([ - "-slice_pattern", - slice_pattern - ]) - if motion_dset is not None: - cargs.extend([ - "-motion_dset", - execution.input_file(motion_dset) - ]) - if outlier_dset is not None: - cargs.extend([ - "-outlier_dset", - execution.input_file(outlier_dset) - ]) - if enorm_dset is not None: - cargs.extend([ - "-enorm_dset", - execution.input_file(enorm_dset) - ]) - if mot_limit is not None: - cargs.extend([ - "-mot_limit", - str(mot_limit) - ]) - if out_limit is not None: - cargs.extend([ - "-out_limit", - str(out_limit) - ]) - if xmat_regress is not None: - cargs.extend([ - "-xmat_regress", - execution.input_file(xmat_regress) - ]) - if xmat_uncensored is not None: - cargs.extend([ - "-xmat_uncensored", - execution.input_file(xmat_uncensored) - ]) - if stats_dset is not None: - cargs.extend([ - "-stats_dset", - execution.input_file(stats_dset) - ]) - if final_anat is not None: - cargs.extend([ - "-final_anat", - execution.input_file(final_anat) - ]) - if final_view is not None: - cargs.extend([ - "-final_view", - final_view - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - if uvars_json is not None: - cargs.extend([ - "-write_uvars_json", - execution.input_file(uvars_json) - ]) - if init_uvars_json is not None: - cargs.extend([ - "-init_uvars_json", - execution.input_file(init_uvars_json) - ]) - ret = GenSsReviewScriptsOutputs( - root=execution.output_file("."), - basic_review=execution.output_file("./@ss_review_basic"), - driver_review=execution.output_file("./@ss_review_driver"), - driver_commands=execution.output_file("./@ss_review_driver_commands"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GEN_SS_REVIEW_SCRIPTS_METADATA", - "GenSsReviewScriptsOutputs", - "gen_ss_review_scripts", -] diff --git a/python/src/niwrap/afni/gen_ss_review_table_py.py b/python/src/niwrap/afni/gen_ss_review_table_py.py deleted file mode 100644 index aab4fd4e8..000000000 --- a/python/src/niwrap/afni/gen_ss_review_table_py.py +++ /dev/null @@ -1,137 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GEN_SS_REVIEW_TABLE_PY_METADATA = Metadata( - id="3ce921bee704f32f3fa43ac197d4d35b07490bf8.boutiques", - name="gen_ss_review_table.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GenSsReviewTablePyOutputs(typing.NamedTuple): - """ - Output object returned when calling `gen_ss_review_table_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_table: OutputPathType | None - """Final table output file""" - output_outliers: OutputPathType | None - """Outliers table output file""" - - -def gen_ss_review_table_py( - infiles: list[InputPathType], - write_table: InputPathType | None = None, - write_outliers: InputPathType | None = None, - overwrite: bool = False, - empty_is_outlier: bool = False, - outlier_sep: str | None = None, - separator: str | None = None, - showlabs: bool = False, - show_infiles: bool = False, - show_keepers: bool = False, - report_outliers: list[str] | None = None, - report_outliers_fill_style: str | None = None, - show_missing: bool = False, - verbosity: int | None = None, - runner: Runner | None = None, -) -> GenSsReviewTablePyOutputs: - """ - Generate a table from ss_review_basic output files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infiles: Input ss_review_basic output text files to process. - write_table: Write final table to the given file. - write_outliers: Write outlier table to the given file. - overwrite: Overwrite the output -write_table, if it exists. - empty_is_outlier: Treat empty tests as outliers. - outlier_sep: Use SEP for the outlier table separator. - separator: Use SEP for the label/vals separator (default = ':'). - showlabs: Display counts of all labels found, with parents. - show_infiles: Include input files in reviewtable result. - show_keepers: Show a table of subjects kept rather than dropped. - report_outliers: Report outliers where the comparison holds. - report_outliers_fill_style: How to fill non-outliers in the table. - show_missing: Display all missing keys. - verbosity: Verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GenSsReviewTablePyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GEN_SS_REVIEW_TABLE_PY_METADATA) - cargs = [] - cargs.append("gen_ss_review_table.py") - cargs.extend([execution.input_file(f) for f in infiles]) - if write_table is not None: - cargs.extend([ - "-write_table", - execution.input_file(write_table) - ]) - if write_outliers is not None: - cargs.extend([ - "-write_outliers", - execution.input_file(write_outliers) - ]) - if overwrite: - cargs.append("-overwrite") - if empty_is_outlier: - cargs.append("-empty_is_outlier") - if outlier_sep is not None: - cargs.extend([ - "-outlier_sep", - outlier_sep - ]) - if separator is not None: - cargs.extend([ - "-separator", - separator - ]) - if showlabs: - cargs.append("-showlabs") - if show_infiles: - cargs.append("-show_infiles") - if show_keepers: - cargs.append("-show_keepers") - if report_outliers is not None: - cargs.extend([ - "-report_outliers", - *report_outliers - ]) - if report_outliers_fill_style is not None: - cargs.extend([ - "-report_outliers_fill_style", - report_outliers_fill_style - ]) - if show_missing: - cargs.append("-show_missing") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = GenSsReviewTablePyOutputs( - root=execution.output_file("."), - output_table=execution.output_file(pathlib.Path(write_table).name) if (write_table is not None) else None, - output_outliers=execution.output_file(pathlib.Path(write_outliers).name) if (write_outliers is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GEN_SS_REVIEW_TABLE_PY_METADATA", - "GenSsReviewTablePyOutputs", - "gen_ss_review_table_py", -] diff --git a/python/src/niwrap/afni/get_afni_model_prf.py b/python/src/niwrap/afni/get_afni_model_prf.py deleted file mode 100644 index d9701cd5e..000000000 --- a/python/src/niwrap/afni/get_afni_model_prf.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GET_AFNI_MODEL_PRF_METADATA = Metadata( - id="7a7ca6195cf6a819e836aae382d360e001286f3d.boutiques", - name="get_afni_model_PRF", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GetAfniModelPrfOutputs(typing.NamedTuple): - """ - Output object returned when calling `get_afni_model_prf(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def get_afni_model_prf( - amplitude: float, - x_coord: float, - y_coord: float, - sigma: float, - runner: Runner | None = None, -) -> GetAfniModelPrfOutputs: - """ - A tool to get AFNI model parameters assuming a PRF framework. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - amplitude: Amplitude for the AFNI model. - x_coord: X-coordinate for the AFNI model. - y_coord: Y-coordinate for the AFNI model. - sigma: Sigma value for the AFNI model. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GetAfniModelPrfOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GET_AFNI_MODEL_PRF_METADATA) - cargs = [] - cargs.append("get_afni_model_PRF") - cargs.append(str(amplitude)) - cargs.append(str(x_coord)) - cargs.append(str(y_coord)) - cargs.append(str(sigma)) - ret = GetAfniModelPrfOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GET_AFNI_MODEL_PRF_METADATA", - "GetAfniModelPrfOutputs", - "get_afni_model_prf", -] diff --git a/python/src/niwrap/afni/get_afni_model_prf_6.py b/python/src/niwrap/afni/get_afni_model_prf_6.py deleted file mode 100644 index 5c995ba9e..000000000 --- a/python/src/niwrap/afni/get_afni_model_prf_6.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GET_AFNI_MODEL_PRF_6_METADATA = Metadata( - id="a1644a25504c74d6961d86251212dfc9c7f6fb99.boutiques", - name="get_afni_model_PRF_6", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GetAfniModelPrf6Outputs(typing.NamedTuple): - """ - Output object returned when calling `get_afni_model_prf_6(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def get_afni_model_prf_6( - nt_: float, - amp: float, - x: float, - y: float, - sigma: float, - sigrat: float, - theta: float, - runner: Runner | None = None, -) -> GetAfniModelPrf6Outputs: - """ - A command to invoke AFNI's population receptive field (pRF) model. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - nt_: Number of time points of the stimulus dataset. - amp: Amplitude of the pRF model. - x: X coordinate of the pRF center. - y: Y coordinate of the pRF center. - sigma: Standard deviation of the Gaussian pRF. - sigrat: Ratio of standard deviations (sigma_x/sigma_y) of the Gaussian\ - pRF. - theta: Rotation angle theta of the Gaussian pRF. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GetAfniModelPrf6Outputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GET_AFNI_MODEL_PRF_6_METADATA) - cargs = [] - cargs.append("get_afni_model_PRF_6") - cargs.append(str(nt_)) - cargs.append(str(amp)) - cargs.append(str(x)) - cargs.append(str(y)) - cargs.append(str(sigma)) - cargs.append(str(sigrat)) - cargs.append(str(theta)) - ret = GetAfniModelPrf6Outputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GET_AFNI_MODEL_PRF_6_METADATA", - "GetAfniModelPrf6Outputs", - "get_afni_model_prf_6", -] diff --git a/python/src/niwrap/afni/get_afni_model_prf_6_bad.py b/python/src/niwrap/afni/get_afni_model_prf_6_bad.py deleted file mode 100644 index bf226970c..000000000 --- a/python/src/niwrap/afni/get_afni_model_prf_6_bad.py +++ /dev/null @@ -1,73 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GET_AFNI_MODEL_PRF_6_BAD_METADATA = Metadata( - id="f7614b8ced72773ab9bfd46ff569ff9a092b84e3.boutiques", - name="get_afni_model_PRF_6_BAD", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GetAfniModelPrf6BadOutputs(typing.NamedTuple): - """ - Output object returned when calling `get_afni_model_prf_6_bad(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def get_afni_model_prf_6_bad( - amplitude: float, - x_coord: float, - y_coord: float, - sigma: float, - sigrat: float, - theta: float, - runner: Runner | None = None, -) -> GetAfniModelPrf6BadOutputs: - """ - Command line tool for obtaining AFNI pRF model. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - amplitude: Amplitude parameter A. - x_coord: X coordinate parameter x. - y_coord: Y coordinate parameter y. - sigma: Sigma parameter sigma. - sigrat: Sigma ratio parameter sigrat. - theta: Theta parameter theta (in radians). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GetAfniModelPrf6BadOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GET_AFNI_MODEL_PRF_6_BAD_METADATA) - cargs = [] - cargs.append("get_afni_model_PRF_6_BAD") - cargs.append(str(amplitude)) - cargs.append(str(x_coord)) - cargs.append(str(y_coord)) - cargs.append(str(sigma)) - cargs.append(str(sigrat)) - cargs.append(str(theta)) - ret = GetAfniModelPrf6BadOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GET_AFNI_MODEL_PRF_6_BAD_METADATA", - "GetAfniModelPrf6BadOutputs", - "get_afni_model_prf_6_bad", -] diff --git a/python/src/niwrap/afni/gifti_tool.py b/python/src/niwrap/afni/gifti_tool.py deleted file mode 100644 index 2c6fa4814..000000000 --- a/python/src/niwrap/afni/gifti_tool.py +++ /dev/null @@ -1,192 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GIFTI_TOOL_METADATA = Metadata( - id="4946ede9cc84ec22d01a494ff249ccac8104538c.boutiques", - name="gifti_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GiftiToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `gifti_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_gifti: OutputPathType - """Output GIFTI file""" - - -def gifti_tool( - infile: InputPathType, - write_gifti: str, - new_numda: float | None = None, - new_dtype: str | None = None, - new_intent: str | None = None, - new_ndim: float | None = None, - new_dims: list[float] | None = None, - set_extern_filelist: list[str] | None = None, - mod_add_data: bool = False, - verb: float | None = None, - show_gifti: bool = False, - read_das: list[float] | None = None, - mod_gim_atr: list[str] | None = None, - mod_gim_meta: list[str] | None = None, - mod_da_atr: list[str] | None = None, - mod_da_meta: list[str] | None = None, - mod_das: list[float] | None = None, - new_dset: bool = False, - compare_gifti: bool = False, - compare_data: bool = False, - compare_verb: float | None = None, - approx_gifti: bool = False, - runner: Runner | None = None, -) -> GiftiToolOutputs: - """ - Tool for creating, displaying, modifying, or comparing GIFTI datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Specify one or more GIFTI datasets as input. - write_gifti: Write out dataset as gifti image. - new_numda: New dataset will have NUMDA DataArray elements. - new_dtype: Set data type to TYPE. - new_intent: DA elements will have intent INTENT. - new_ndim: Set Dimensionality to NUMDIMS. - new_dims: Set dims[] to these 6 values. - set_extern_filelist: Store data in external files. - mod_add_data: Add data to empty DataArray elements. - verb: Set verbose level. - show_gifti: Show final gifti image. - read_das: Read DataArray list indices. - mod_gim_atr: Set the GIFTI NAME=VALUE attribute pair at GIFTI level. - mod_gim_meta: Add this pair to the GIFTI MetaData. - mod_da_atr: Set the DataArray NAME=VALUE attribute pair. - mod_da_meta: Set the DataArray NAME=VALUE pair in DA's MetaData. - mod_das: Specify the set of DataArrays to modify. - new_dset: Create a new GIFTI dataset. - compare_gifti: Compare two GIFTI datasets. - compare_data: Flag to request comparison of the data. - compare_verb: Set the verbose level of comparisons. - approx_gifti: Approximate comparison of GIFTI datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GiftiToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GIFTI_TOOL_METADATA) - cargs = [] - cargs.append("gifti_tool") - cargs.extend([ - "-infile", - execution.input_file(infile) - ]) - if new_numda is not None: - cargs.extend([ - "-new_numDA", - str(new_numda) - ]) - if new_dtype is not None: - cargs.extend([ - "-new_dtype", - new_dtype - ]) - if new_intent is not None: - cargs.extend([ - "-new_intent", - new_intent - ]) - if new_ndim is not None: - cargs.extend([ - "-new_ndim", - str(new_ndim) - ]) - if new_dims is not None: - cargs.extend([ - "-new_dims", - *map(str, new_dims) - ]) - cargs.extend([ - "-write_gifti", - write_gifti - ]) - if set_extern_filelist is not None: - cargs.extend([ - "-set_extern_filelist", - *set_extern_filelist - ]) - if mod_add_data: - cargs.append("-mod_add_data") - if verb is not None: - cargs.extend([ - "-verb", - str(verb) - ]) - if show_gifti: - cargs.append("-show_gifti") - if read_das is not None: - cargs.extend([ - "-read_DAs", - *map(str, read_das) - ]) - if mod_gim_atr is not None: - cargs.extend([ - "-mod_gim_atr", - *mod_gim_atr - ]) - if mod_gim_meta is not None: - cargs.extend([ - "-mod_gim_meta", - *mod_gim_meta - ]) - if mod_da_atr is not None: - cargs.extend([ - "-mod_DA_atr", - *mod_da_atr - ]) - if mod_da_meta is not None: - cargs.extend([ - "-mod_DA_meta", - *mod_da_meta - ]) - if mod_das is not None: - cargs.extend([ - "-mod_DAs", - *map(str, mod_das) - ]) - if new_dset: - cargs.append("-new_dset") - if compare_gifti: - cargs.append("-compare_gifti") - if compare_data: - cargs.append("-compare_data") - if compare_verb is not None: - cargs.extend([ - "-compare_verb", - str(compare_verb) - ]) - if approx_gifti: - cargs.append("-approx_gifti") - ret = GiftiToolOutputs( - root=execution.output_file("."), - output_gifti=execution.output_file(write_gifti), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GIFTI_TOOL_METADATA", - "GiftiToolOutputs", - "gifti_tool", -] diff --git a/python/src/niwrap/afni/gltsymtest.py b/python/src/niwrap/afni/gltsymtest.py deleted file mode 100644 index ee4822c62..000000000 --- a/python/src/niwrap/afni/gltsymtest.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -GLTSYMTEST_METADATA = Metadata( - id="8b69853d0f4540d3f47435c31725118e2911c6f2.boutiques", - name="GLTsymtest", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class GltsymtestOutputs(typing.NamedTuple): - """ - Output object returned when calling `gltsymtest(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def gltsymtest( - varlist: str, - expr: list[str], - badonly: bool = False, - runner: Runner | None = None, -) -> GltsymtestOutputs: - """ - A tool to test the validity of '-gltsym' strings for use with 3dDeconvolve or - 3dREMLfit. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - varlist: A list of allowed variable names in the expression, separated\ - by commas, semicolons, and/or spaces. - expr: GLT symbolic expression(s), enclosed in quotes. - badonly: A flag to only output BAD messages rather than all messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `GltsymtestOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(GLTSYMTEST_METADATA) - cargs = [] - cargs.append("GLTsymtest") - if badonly: - cargs.append("-badonly") - cargs.append(varlist) - cargs.extend(expr) - ret = GltsymtestOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "GLTSYMTEST_METADATA", - "GltsymtestOutputs", - "gltsymtest", -] diff --git a/python/src/niwrap/afni/help_format.py b/python/src/niwrap/afni/help_format.py deleted file mode 100644 index f4feb97a0..000000000 --- a/python/src/niwrap/afni/help_format.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -HELP_FORMAT_METADATA = Metadata( - id="2c2e44d1845d44d18c53666d3810111107853205.boutiques", - name="help_format", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class HelpFormatOutputs(typing.NamedTuple): - """ - Output object returned when calling `help_format(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - formatted_output: OutputPathType - """The formatted text with hyperlinks""" - - -def help_format( - stdin: str, - runner: Runner | None = None, -) -> HelpFormatOutputs: - """ - Formats text by converting URLs into HTML hyperlinks. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - stdin: Standard input text to be formatted. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `HelpFormatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(HELP_FORMAT_METADATA) - cargs = [] - cargs.append("help_format") - cargs.append(stdin) - ret = HelpFormatOutputs( - root=execution.output_file("."), - formatted_output=execution.output_file("formatted_output.html"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "HELP_FORMAT_METADATA", - "HelpFormatOutputs", - "help_format", -] diff --git a/python/src/niwrap/afni/im2niml.py b/python/src/niwrap/afni/im2niml.py deleted file mode 100644 index 4429184c1..000000000 --- a/python/src/niwrap/afni/im2niml.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IM2NIML_METADATA = Metadata( - id="3c92592db9d506b4424ac028f92405630d2fda18.boutiques", - name="im2niml", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Im2nimlOutputs(typing.NamedTuple): - """ - Output object returned when calling `im2niml(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - niml_output: OutputPathType - """NIML element""" - - -def im2niml( - input_files: list[InputPathType], - runner: Runner | None = None, -) -> Im2nimlOutputs: - """ - Converts the input image(s) to a text-based NIML element and writes the result - to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input image file(s) (e.g. image.jpg). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Im2nimlOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IM2NIML_METADATA) - cargs = [] - cargs.append("im2niml") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = Im2nimlOutputs( - root=execution.output_file("."), - niml_output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IM2NIML_METADATA", - "Im2nimlOutputs", - "im2niml", -] diff --git a/python/src/niwrap/afni/images_equal.py b/python/src/niwrap/afni/images_equal.py deleted file mode 100644 index 94287fcda..000000000 --- a/python/src/niwrap/afni/images_equal.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAGES_EQUAL_METADATA = Metadata( - id="830357495ce35a09c03740c89847cea1c8976199.boutiques", - name="images_equal", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImagesEqualOutputs(typing.NamedTuple): - """ - Output object returned when calling `images_equal(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - comparison_result: OutputPathType - """Result of the image comparison: 1 if equal, 0 if not.""" - - -def images_equal( - file_a: InputPathType, - file_b: InputPathType, - all_flag: bool = False, - runner: Runner | None = None, -) -> ImagesEqualOutputs: - """ - A simple program to test if two 2D images are identical. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - file_a: First image file to compare. - file_b: Second image file to compare. - all_flag: Compare all images in the files; all must be equal for exit\ - status to be 1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImagesEqualOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAGES_EQUAL_METADATA) - cargs = [] - cargs.append("images_equal") - cargs.append(execution.input_file(file_a)) - cargs.append(execution.input_file(file_b)) - if all_flag: - cargs.append("-all") - ret = ImagesEqualOutputs( - root=execution.output_file("."), - comparison_result=execution.output_file("comparison_result.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAGES_EQUAL_METADATA", - "ImagesEqualOutputs", - "images_equal", -] diff --git a/python/src/niwrap/afni/imand.py b/python/src/niwrap/afni/imand.py deleted file mode 100644 index e8b431af2..000000000 --- a/python/src/niwrap/afni/imand.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAND_METADATA = Metadata( - id="c48ca42cf72c91b13a658c727dcfb9f75ba40bf0.boutiques", - name="imand", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImandOutputs(typing.NamedTuple): - """ - Output object returned when calling `imand(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """The resulting output image file.""" - - -def imand( - input_images: list[InputPathType], - output_image: InputPathType, - threshold: float | None = None, - runner: Runner | None = None, -) -> ImandOutputs: - """ - Image AND operation tool. Only pixels nonzero in all input images (and above the - threshold, if given) will be output. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_images: Input images to be processed. Multiple input images can\ - be specified. - output_image: Output image file. - threshold: Threshold value; only pixels above this value will be\ - output. Optional. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImandOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAND_METADATA) - cargs = [] - cargs.append("imand") - if threshold is not None: - cargs.extend([ - "--thresh", - str(threshold) - ]) - cargs.extend([execution.input_file(f) for f in input_images]) - cargs.append(execution.input_file(output_image)) - ret = ImandOutputs( - root=execution.output_file("."), - outfile=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAND_METADATA", - "ImandOutputs", - "imand", -] diff --git a/python/src/niwrap/afni/imaver.py b/python/src/niwrap/afni/imaver.py deleted file mode 100644 index 3b9513528..000000000 --- a/python/src/niwrap/afni/imaver.py +++ /dev/null @@ -1,73 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAVER_METADATA = Metadata( - id="d40eed47338fed1128a04d1c60c1e336c6bcfad8.boutiques", - name="imaver", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImaverOutputs(typing.NamedTuple): - """ - Output object returned when calling `imaver(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_ave_output: OutputPathType | None - """Output image file for averages (optional)""" - out_sig_output: OutputPathType | None - """Output image file for standard deviations (optional)""" - - -def imaver( - input_images: list[InputPathType], - out_ave: str | None = None, - out_sig: str | None = None, - runner: Runner | None = None, -) -> ImaverOutputs: - """ - Computes the mean and standard deviation, pixel-by-pixel, of a whole bunch of - images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_images: Input image files for processing. - out_ave: Output average image file. Use '-' to skip output. - out_sig: Output standard deviation image file. Use '-' to skip output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImaverOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAVER_METADATA) - cargs = [] - cargs.append("imaver") - if out_ave is not None: - cargs.append(out_ave) - if out_sig is not None: - cargs.append(out_sig) - cargs.extend([execution.input_file(f) for f in input_images]) - ret = ImaverOutputs( - root=execution.output_file("."), - out_ave_output=execution.output_file(out_ave) if (out_ave is not None) else None, - out_sig_output=execution.output_file(out_sig) if (out_sig is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAVER_METADATA", - "ImaverOutputs", - "imaver", -] diff --git a/python/src/niwrap/afni/imcalc.py b/python/src/niwrap/afni/imcalc.py deleted file mode 100644 index b9daf8edc..000000000 --- a/python/src/niwrap/afni/imcalc.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMCALC_METADATA = Metadata( - id="619429e3eb3a18d69af5e0d47edb5f5289323a19.boutiques", - name="imcalc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImcalcOutputs(typing.NamedTuple): - """ - Output object returned when calling `imcalc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType | None - """Output image file produced after applying the expression to input - images""" - - -def imcalc( - expression: str, - datum_type: str | None = None, - image_inputs: list[InputPathType] | None = None, - output_name: str | None = None, - runner: Runner | None = None, -) -> ImcalcOutputs: - """ - Tool for arithmetic operations on 2D images, pixel-by-pixel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expression: Apply the expression within quotes to the input images, one\ - voxel at a time, to produce the output image. (e.g., "sqrt(a*b)" to\ - compute the geometric mean). - datum_type: Coerce the output data to be stored as the given type:\ - byte, short, or float. Default is the datum of the first input image on\ - the command line. - image_inputs: Read image 'dname' and call the voxel values 'a' in the\ - expression. 'a' may be any letter from 'a' to 'z'. If some letter name\ - is used in the expression but not present in one of the image options\ - here, then that variable is set to 0. - output_name: Use 'name' for the output image filename. Default is\ - 'imcalc.out'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImcalcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMCALC_METADATA) - cargs = [] - cargs.append("imcalc") - if datum_type is not None: - cargs.extend([ - "-datum type", - datum_type - ]) - if image_inputs is not None: - cargs.extend([ - "-a", - *[execution.input_file(f) for f in image_inputs] - ]) - cargs.extend([ - "-expr", - expression - ]) - if output_name is not None: - cargs.extend([ - "-output", - output_name - ]) - ret = ImcalcOutputs( - root=execution.output_file("."), - output_image=execution.output_file(output_name) if (output_name is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMCALC_METADATA", - "ImcalcOutputs", - "imcalc", -] diff --git a/python/src/niwrap/afni/imcat.py b/python/src/niwrap/afni/imcat.py deleted file mode 100644 index f9d7626fb..000000000 --- a/python/src/niwrap/afni/imcat.py +++ /dev/null @@ -1,230 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMCAT_METADATA = Metadata( - id="aaf3852ed2e5487ca6e742c661a53a14976a9a76.boutiques", - name="imcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `imcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType | None - """Output image file""" - - -def imcat( - input_files: list[InputPathType], - scale_image: InputPathType | None = None, - scale_pixels: InputPathType | None = None, - scale_intensity: bool = False, - gscale: float | None = None, - rgb_out: bool = False, - res_in: list[float] | None = None, - respad_in: list[float] | None = None, - pad_val: float | None = None, - crop: list[float] | None = None, - autocrop_ctol: float | None = None, - autocrop_atol: float | None = None, - autocrop: bool = False, - zero_wrap: bool = False, - white_wrap: bool = False, - gray_wrap: float | None = None, - image_wrap: bool = False, - rand_wrap: bool = False, - prefix: str | None = None, - matrix: list[float] | None = None, - nx: float | None = None, - ny: float | None = None, - matrix_from_scale: bool = False, - gap: float | None = None, - gap_col: list[float] | None = None, - runner: Runner | None = None, -) -> ImcatOutputs: - """ - Assembles a set of images into an image matrix (IM) montage of NX by NY images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input image files. - scale_image: Multiply each image IM(i,j) in output image matrix IM by\ - the color or intensity of the pixel (i,j) in SCALE_IMG. - scale_pixels: Multiply each pixel (i,j) in output image by the color or\ - intensity of the pixel (i,j) in SCALE_IMG. SCALE_IMG is automatically\ - resized to the resolution of the output image. - scale_intensity: Instead of multiplying by the color of pixel (i,j),\ - use its intensity (average color). - gscale: Apply FAC in addition to scaling of -scale_* options. - rgb_out: Force output to be in RGB, even if input is bytes. This option\ - is turned on automatically in certain cases. - res_in: Set resolution of all input images to RX by RY pixels. Default\ - is to make all input have the same resolution as the first image. - respad_in: Like -res_in, but resample to the max while respecting the\ - aspect ratio, and then pad to achieve desired pixel count. - pad_val: Set the padding value, should it be needed by -respad_in to\ - VAL. VAL is typecast to byte, default is 0, max is 255. - crop: Crop images by L (Left), R (Right), T (Top), B (Bottom) pixels.\ - Cutting is performed after any resolution change, if any, is to be\ - done. - autocrop_ctol: A line is eliminated if none of its R G B values differ\ - by more than CTOL% from those of the corner pixel. - autocrop_atol: A line is eliminated if none of its R G B values differ\ - by more than ATOL% from those of line average. - autocrop: This option is the same as using both of -autocrop_atol 20\ - and -autocrop_ctol 20. - zero_wrap: If number of images is not enough to fill matrix solid black\ - images are used. - white_wrap: If number of images is not enough to fill matrix solid\ - white images are used. - gray_wrap: If number of images is not enough to fill matrix, solid gray\ - images are used. GRAY must be between 0 and 1.0. - image_wrap: If number of images is not enough to fill matrix, images on\ - command line are reused (default). - rand_wrap: When reusing images to fill matrix, randomize the order in\ - refill section only. - prefix: Prefix the output files with string 'ppp'. - matrix: Specify number of images in each row and column of IM at the\ - same time. - nx: Number of images in each row. - ny: Number of images in each column. - matrix_from_scale: Set NX and NY to be the same as the SCALE_IMG's\ - dimensions. (needs -scale_image). - gap: Put a line G pixels wide between images. - gap_col: Set color of line to R G B values. Values range between 0 and\ - 255. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImcatOutputs`). - """ - if pad_val is not None and not (0 <= pad_val <= 255): - raise ValueError(f"'pad_val' must be between 0 <= x <= 255 but was {pad_val}") - if gray_wrap is not None and not (0.0 <= gray_wrap <= 1.0): - raise ValueError(f"'gray_wrap' must be between 0.0 <= x <= 1.0 but was {gray_wrap}") - runner = runner or get_global_runner() - execution = runner.start_execution(IMCAT_METADATA) - cargs = [] - cargs.append("imcat") - cargs.extend([execution.input_file(f) for f in input_files]) - if scale_image is not None: - cargs.extend([ - "-scale_image", - execution.input_file(scale_image) - ]) - if scale_pixels is not None: - cargs.extend([ - "-scale_pixels", - execution.input_file(scale_pixels) - ]) - if scale_intensity: - cargs.append("-scale_intensity") - if gscale is not None: - cargs.extend([ - "-gscale", - str(gscale) - ]) - if rgb_out: - cargs.append("-rgb_out") - if res_in is not None: - cargs.extend([ - "-res_in", - *map(str, res_in) - ]) - if respad_in is not None: - cargs.extend([ - "-respad_in", - *map(str, respad_in) - ]) - if pad_val is not None: - cargs.extend([ - "-pad_val", - str(pad_val) - ]) - if crop is not None: - cargs.extend([ - "-crop", - *map(str, crop) - ]) - if autocrop_ctol is not None: - cargs.extend([ - "-autocrop_ctol", - str(autocrop_ctol) - ]) - if autocrop_atol is not None: - cargs.extend([ - "-autocrop_atol", - str(autocrop_atol) - ]) - if autocrop: - cargs.append("-autocrop") - if zero_wrap: - cargs.append("-zero_wrap") - if white_wrap: - cargs.append("-white_wrap") - if gray_wrap is not None: - cargs.extend([ - "-gray_wrap", - str(gray_wrap) - ]) - if image_wrap: - cargs.append("-image_wrap") - if rand_wrap: - cargs.append("-rand_wrap") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if matrix is not None: - cargs.extend([ - "-matrix", - *map(str, matrix) - ]) - if nx is not None: - cargs.extend([ - "-nx", - str(nx) - ]) - if ny is not None: - cargs.extend([ - "-ny", - str(ny) - ]) - if matrix_from_scale: - cargs.append("-matrix_from_scale") - if gap is not None: - cargs.extend([ - "-gap", - str(gap) - ]) - if gap_col is not None: - cargs.extend([ - "-gap_col", - *map(str, gap_col) - ]) - ret = ImcatOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(prefix + "output_image.[EXT]") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMCAT_METADATA", - "ImcatOutputs", - "imcat", -] diff --git a/python/src/niwrap/afni/imcutup.py b/python/src/niwrap/afni/imcutup.py deleted file mode 100644 index 616d1e91e..000000000 --- a/python/src/niwrap/afni/imcutup.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMCUTUP_METADATA = Metadata( - id="763cc3153f2643aeee624c066590a03d172b8915.boutiques", - name="imcutup", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImcutupOutputs(typing.NamedTuple): - """ - Output object returned when calling `imcutup(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType | None - """Output smaller images with the specified prefix numbering format.""" - - -def imcutup( - nx: int, - ny: int, - input_file: InputPathType, - prefix: str | None = None, - xynum: bool = False, - yxnum: bool = False, - xynum_format: bool = False, - yxnum_format: bool = False, - runner: Runner | None = None, -) -> ImcutupOutputs: - """ - Breaks up larger images into smaller image files of user-defined size. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - nx: Number of pixels along the x-dimension for the smaller images. - ny: Number of pixels along the y-dimension for the smaller images. - input_file: Input image filename. Must be a single 2D image. - prefix: Prefix the output files with the provided string. - xynum: Number the output images in x-first, then y (default behavior). - yxnum: Number the output images in y-first, then x. - xynum_format: 2D numbering in x.y format. - yxnum_format: 2D numbering in y.x format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImcutupOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMCUTUP_METADATA) - cargs = [] - cargs.append("imcutup") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if xynum: - cargs.append("-xynum") - if yxnum: - cargs.append("-yxnum") - if xynum_format: - cargs.append("-x.ynum") - if yxnum_format: - cargs.append("-y.xnum") - cargs.append(str(nx)) - cargs.append(str(ny)) - cargs.append(execution.input_file(input_file)) - ret = ImcutupOutputs( - root=execution.output_file("."), - output_files=execution.output_file(prefix + "*") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMCUTUP_METADATA", - "ImcutupOutputs", - "imcutup", -] diff --git a/python/src/niwrap/afni/imdump.py b/python/src/niwrap/afni/imdump.py deleted file mode 100644 index 26476bc75..000000000 --- a/python/src/niwrap/afni/imdump.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMDUMP_METADATA = Metadata( - id="7f8451c2da7ec8cbf2c32a069270cdd298deaee7.boutiques", - name="imdump", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImdumpOutputs(typing.NamedTuple): - """ - Output object returned when calling `imdump(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout: OutputPathType - """Nonzero pixels in the format: x-index y-index value, one pixel per - line.""" - - -def imdump( - input_image: InputPathType, - runner: Runner | None = None, -) -> ImdumpOutputs: - """ - Prints out nonzero pixels in an image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_image: Input image file to be processed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImdumpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMDUMP_METADATA) - cargs = [] - cargs.append("imdump") - cargs.append(execution.input_file(input_image)) - ret = ImdumpOutputs( - root=execution.output_file("."), - stdout=execution.output_file("stdout.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMDUMP_METADATA", - "ImdumpOutputs", - "imdump", -] diff --git a/python/src/niwrap/afni/immask.py b/python/src/niwrap/afni/immask.py deleted file mode 100644 index 977b7bcf1..000000000 --- a/python/src/niwrap/afni/immask.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMMASK_METADATA = Metadata( - id="7d98077e608ff5474eccfea876c99ed053c8f0cb.boutiques", - name="immask", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImmaskOutputs(typing.NamedTuple): - """ - Output object returned when calling `immask(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Masked output image""" - - -def immask( - input_image: InputPathType, - output_image: str, - threshold: float | None = None, - mask_image: InputPathType | None = None, - positive_only: bool = False, - runner: Runner | None = None, -) -> ImmaskOutputs: - """ - Masks the input image based on specified criteria and produces the output image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_image: Input image to be masked. - output_image: Output image after masking. - threshold: Threshold value; all pixels with absolute value below this\ - will be set to zero in the output image. - mask_image: Mask image; only locations that are nonzero in the mask\ - image will be nonzero in the output image. - positive_only: Use only positive pixels from input image. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImmaskOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMMASK_METADATA) - cargs = [] - cargs.append("immask") - if threshold is not None: - cargs.extend([ - "-thresh", - str(threshold) - ]) - if mask_image is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_image) - ]) - if positive_only: - cargs.append("-pos") - cargs.append(execution.input_file(input_image)) - cargs.append(output_image) - ret = ImmaskOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMMASK_METADATA", - "ImmaskOutputs", - "immask", -] diff --git a/python/src/niwrap/afni/imreg.py b/python/src/niwrap/afni/imreg.py deleted file mode 100644 index c00c6ec0d..000000000 --- a/python/src/niwrap/afni/imreg.py +++ /dev/null @@ -1,170 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMREG_METADATA = Metadata( - id="4ed217ec6db0c1ed0ca85263b118a5554ebb437a.boutiques", - name="imreg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImregOutputs(typing.NamedTuple): - """ - Output object returned when calling `imreg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - registered_images: OutputPathType | None - """Registered images""" - dx_file: OutputPathType | None - """Time series dx file""" - dy_file: OutputPathType | None - """Time series dy file""" - phi_file: OutputPathType | None - """Time series phi file""" - - -def imreg( - base_image: str, - image_sequence: list[InputPathType], - nowrite: bool = False, - prefix: str | None = None, - suffix: str | None = None, - start: float | None = None, - step: float | None = None, - flim: bool = False, - keepsize: bool = False, - quiet: bool = False, - debug: bool = False, - dprefix: str | None = None, - bilinear: bool = False, - modes: str | None = None, - mlcf: bool = False, - wtim: InputPathType | None = None, - dfspace: bool = False, - cmass: bool = False, - fine: list[float] | None = None, - nofine: bool = False, - runner: Runner | None = None, -) -> ImregOutputs: - """ - Registers each 2D image in 'image_sequence' to 'base_image'. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base_image: Base image or method to determine base image ('+AVER' or\ - '+count'). - image_sequence: Sequence of images to be registered. - nowrite: Don't write outputs, just print progress reports. - prefix: Prefix for output file names. - suffix: Suffix for output file names. - start: Start index for output file names. - step: Step size for output file indices. - flim: Write output in mrilib floating point format. - keepsize: Preserve the original image size on output. - quiet: Don't write progress report messages. - debug: Write lots of debugging output. - dprefix: Prefix for dx, dy, and phi files. - bilinear: Use bilinear interpolation. - modes: Interpolation modes during coarse, fine, and registration phases. - mlcf: Equivalent to '-modes bilinear bicubic Fourier'. - wtim: Weighting image file. - dfspace: Use difiterated differential spatial method. - cmass: Align centers of mass of the images. - fine: Fine fit parameters: blur, dxy, dphi. - nofine: Turn off the 'fine' fit algorithm. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImregOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMREG_METADATA) - cargs = [] - cargs.append("imreg") - cargs.append(base_image) - cargs.extend([execution.input_file(f) for f in image_sequence]) - if nowrite: - cargs.append("-nowrite") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if start is not None: - cargs.extend([ - "-start", - str(start) - ]) - if step is not None: - cargs.extend([ - "-step", - str(step) - ]) - if flim: - cargs.append("-flim") - if keepsize: - cargs.append("-keepsize") - if quiet: - cargs.append("-quiet") - if debug: - cargs.append("-debug") - if dprefix is not None: - cargs.extend([ - "-dprefix", - dprefix - ]) - if bilinear: - cargs.append("-bilinear") - if modes is not None: - cargs.extend([ - "-modes", - modes - ]) - if mlcf: - cargs.append("-mlcF") - if wtim is not None: - cargs.extend([ - "-wtim", - execution.input_file(wtim) - ]) - if dfspace: - cargs.append("-dfspace") - if cmass: - cargs.append("-cmass") - if fine is not None: - cargs.extend([ - "-fine", - *map(str, fine) - ]) - if nofine: - cargs.append("-nofine") - ret = ImregOutputs( - root=execution.output_file("."), - registered_images=execution.output_file(prefix + ".[INDEX]." + suffix) if (prefix is not None and suffix is not None) else None, - dx_file=execution.output_file(dprefix + ".dx") if (dprefix is not None) else None, - dy_file=execution.output_file(dprefix + ".dy") if (dprefix is not None) else None, - phi_file=execution.output_file(dprefix + ".phi") if (dprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMREG_METADATA", - "ImregOutputs", - "imreg", -] diff --git a/python/src/niwrap/afni/imrotate.py b/python/src/niwrap/afni/imrotate.py deleted file mode 100644 index a39ec1e5d..000000000 --- a/python/src/niwrap/afni/imrotate.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMROTATE_METADATA = Metadata( - id="b624ef735952148868b7e81bfcbe37097f08c38e.boutiques", - name="imrotate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImrotateOutputs(typing.NamedTuple): - """ - Output object returned when calling `imrotate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType - """Path to the output image file""" - - -def imrotate( - dx: float, - dy: float, - phi: float, - input_image: InputPathType, - output_image: InputPathType, - fourier_interpolation: bool = False, - runner: Runner | None = None, -) -> ImrotateOutputs: - """ - Shifts and rotates an image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dx: Pixels to shift rightwards (can be non-integer). - dy: Pixels to shift downwards (can be non-integer). - phi: Degrees to rotate clockwise. - input_image: Input image file. - output_image: Output image file. - fourier_interpolation: Use Fourier interpolation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImrotateOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMROTATE_METADATA) - cargs = [] - cargs.append("imrotate") - if fourier_interpolation: - cargs.append("-Fourier") - cargs.append(str(dx)) - cargs.append(str(dy)) - cargs.append(str(phi)) - cargs.append(execution.input_file(input_image)) - cargs.append(execution.input_file(output_image)) - ret = ImrotateOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMROTATE_METADATA", - "ImrotateOutputs", - "imrotate", -] diff --git a/python/src/niwrap/afni/imstack.py b/python/src/niwrap/afni/imstack.py deleted file mode 100644 index d2d2b9b24..000000000 --- a/python/src/niwrap/afni/imstack.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMSTACK_METADATA = Metadata( - id="4d6200fa2e1b9b6bfc0d03b2731f1be8201a7a22.boutiques", - name="imstack", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImstackOutputs(typing.NamedTuple): - """ - Output object returned when calling `imstack(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_data_file: OutputPathType | None - """Output data file""" - output_header_file: OutputPathType | None - """Output header file""" - - -def imstack( - image_files: list[InputPathType], - data_type: typing.Literal["short", "float"] | None = None, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> ImstackOutputs: - """ - Stacks up a set of 2D images into one big file (a la MGH). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - image_files: Input image filenames. - data_type: Converts the output data file to be 'type', which is either\ - 'short' or 'float'. The default type is the type of the first image. - output_prefix: Names the output files to be 'name'.b'type' and\ - 'name'.hdr. The default name is 'obi-wan-kenobi'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImstackOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMSTACK_METADATA) - cargs = [] - cargs.append("imstack") - cargs.extend([execution.input_file(f) for f in image_files]) - if data_type is not None: - cargs.extend([ - "-datum", - data_type - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - ret = ImstackOutputs( - root=execution.output_file("."), - output_data_file=execution.output_file(output_prefix + ".b" + data_type) if (output_prefix is not None and data_type is not None) else None, - output_header_file=execution.output_file(output_prefix + ".hdr") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMSTACK_METADATA", - "ImstackOutputs", - "imstack", -] diff --git a/python/src/niwrap/afni/imstat.py b/python/src/niwrap/afni/imstat.py deleted file mode 100644 index ab62c9633..000000000 --- a/python/src/niwrap/afni/imstat.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMSTAT_METADATA = Metadata( - id="3e706f8dd2b4c3dcc2445da624da2cd01f51f304.boutiques", - name="imstat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImstatOutputs(typing.NamedTuple): - """ - Output object returned when calling `imstat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - mean_output: OutputPathType | None - """Mean of pixel-wise statistics for the collection of 2D images""" - sdev_output: OutputPathType | None - """Standard deviation of pixel-wise statistics for the collection of 2D - images""" - - -def imstat( - image_files: list[InputPathType], - no_label: bool = False, - quiet: bool = False, - pixstat_prefix: str | None = None, - runner: Runner | None = None, -) -> ImstatOutputs: - """ - Calculation of statistics of one or more images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - image_files: Input image file(s). - no_label: Don't write labels on each file's summary line. - quiet: Don't print statistics for each file. - pixstat_prefix: If more than one image file is given, then\ - 'prefix.mean' and 'prefix.sdev' will be written as the pixel-wise\ - statistics images of the whole collection. These images will be in the\ - 'flim' floating point format. [This option only works on 2D images!]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImstatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMSTAT_METADATA) - cargs = [] - cargs.append("imstat") - if no_label: - cargs.append("-nolabel") - if quiet: - cargs.append("-quiet") - if pixstat_prefix is not None: - cargs.extend([ - "-pixstat", - pixstat_prefix - ]) - cargs.extend([execution.input_file(f) for f in image_files]) - ret = ImstatOutputs( - root=execution.output_file("."), - mean_output=execution.output_file(pixstat_prefix + ".mean") if (pixstat_prefix is not None) else None, - sdev_output=execution.output_file(pixstat_prefix + ".sdev") if (pixstat_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMSTAT_METADATA", - "ImstatOutputs", - "imstat", -] diff --git a/python/src/niwrap/afni/imupsam.py b/python/src/niwrap/afni/imupsam.py deleted file mode 100644 index 75974c93c..000000000 --- a/python/src/niwrap/afni/imupsam.py +++ /dev/null @@ -1,75 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMUPSAM_METADATA = Metadata( - id="156965091ca5242419f26a19463380332f6a9731.boutiques", - name="imupsam", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ImupsamOutputs(typing.NamedTuple): - """ - Output object returned when calling `imupsam(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType - """Upsampled image output file""" - - -def imupsam( - factor: int, - input_image: InputPathType, - output_image: str, - ascii_flag: bool = False, - runner: Runner | None = None, -) -> ImupsamOutputs: - """ - Upsamples a 2D image by a specified factor. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - factor: Upsampling factor; must be an integer in the range 2 to 30. - input_image: Path of the input 2D image file. - output_image: Path of the output upsampled image file. Use '-' to write\ - to stdout. - ascii_flag: Write the result in ASCII format: all numbers for the file\ - are output, with no header info. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImupsamOutputs`). - """ - if not (2 <= factor <= 30): - raise ValueError(f"'factor' must be between 2 <= x <= 30 but was {factor}") - runner = runner or get_global_runner() - execution = runner.start_execution(IMUPSAM_METADATA) - cargs = [] - cargs.append("imupsam") - if ascii_flag: - cargs.append("-A") - cargs.append(str(factor)) - cargs.append(execution.input_file(input_image)) - cargs.append(output_image) - ret = ImupsamOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMUPSAM_METADATA", - "ImupsamOutputs", - "imupsam", -] diff --git a/python/src/niwrap/afni/init_user_dotfiles_py.py b/python/src/niwrap/afni/init_user_dotfiles_py.py deleted file mode 100644 index 3af4ffd65..000000000 --- a/python/src/niwrap/afni/init_user_dotfiles_py.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -INIT_USER_DOTFILES_PY_METADATA = Metadata( - id="5fba872c5a2b8244bb6731f68100cd2208946051.boutiques", - name="init_user_dotfiles.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class InitUserDotfilesPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `init_user_dotfiles_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def init_user_dotfiles_py( - help_: bool = False, - help_dotfiles_all: bool = False, - help_dotfiles_mod: bool = False, - help_shells: bool = False, - hist: bool = False, - show_valid_opts: bool = False, - ver: bool = False, - dot_files_list: list[str] | None = None, - dir_bin: str | None = None, - dir_dot: str | None = None, - do_updates: list[str] | None = None, - dry_run: bool = False, - force: bool = False, - make_backup: str | None = None, - shell_list: list[str] | None = None, - test: bool = False, - verbosity_level: int | None = None, - runner: Runner | None = None, -) -> InitUserDotfilesPyOutputs: - """ - Initialize or evaluate user dot files (.cshrc, .bashrc, ...) for system - settings. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - help_: Show this help. - help_dotfiles_all: Display dot files known by the program. - help_dotfiles_mod: Display modifiable dot files. - help_shells: Display shells known by the program. - hist: Show module history. - show_valid_opts: List valid options. - ver: Show current version. - dot_files_list: Specify dot files to focus on (default from\ - -help_dotfiles_mod). - dir_bin: Specify bin directory to add to PATH (default comes from\ - `which afni_proc.py`). - dir_dot: Specify directory containing dot files. - do_updates: Specify which updates to make (default is nothing). - dry_run: Do not modify files, but see what would happen. - force: Force edits, whether they seem needed or not. - make_backup: Specify whether to make backups of originals (default is\ - yes). - shell_list: Specify shells instead of using -dflist. - test: Just test the files for potential changes. - verbosity_level: Set the verbosity level (default 1). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `InitUserDotfilesPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(INIT_USER_DOTFILES_PY_METADATA) - cargs = [] - cargs.append("init_user_dotfiles.py") - if help_: - cargs.append("-help") - if help_dotfiles_all: - cargs.append("-help_dotfiles_all") - if help_dotfiles_mod: - cargs.append("-help_dotfiles_mod") - if help_shells: - cargs.append("-help_shells") - if hist: - cargs.append("-hist") - if show_valid_opts: - cargs.append("-show_valid_opts") - if ver: - cargs.append("-ver") - if dot_files_list is not None: - cargs.extend([ - "-dflist", - *dot_files_list - ]) - if dir_bin is not None: - cargs.extend([ - "-dir_bin", - dir_bin - ]) - if dir_dot is not None: - cargs.extend([ - "-dir_dot", - dir_dot - ]) - if do_updates is not None: - cargs.extend([ - "-do_updates", - *do_updates - ]) - if dry_run: - cargs.append("-dry_run") - if force: - cargs.append("-force") - if make_backup is not None: - cargs.extend([ - "-make_backup", - make_backup - ]) - if shell_list is not None: - cargs.extend([ - "-shell_list", - *shell_list - ]) - if test: - cargs.append("-test") - if verbosity_level is not None: - cargs.extend([ - "-verb", - str(verbosity_level) - ]) - ret = InitUserDotfilesPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "INIT_USER_DOTFILES_PY_METADATA", - "InitUserDotfilesPyOutputs", - "init_user_dotfiles_py", -] diff --git a/python/src/niwrap/afni/inspec.py b/python/src/niwrap/afni/inspec.py deleted file mode 100644 index 8111dab50..000000000 --- a/python/src/niwrap/afni/inspec.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -INSPEC_METADATA = Metadata( - id="ac68ea5451eb1e5a829cefef7c709de41948f32a.boutiques", - name="inspec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class InspecOutputs(typing.NamedTuple): - """ - Output object returned when calling `inspec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def inspec( - specfile: InputPathType, - newspecname: str | None = None, - detail: float | None = None, - leftspec: InputPathType | None = None, - rightspec: InputPathType | None = None, - state_rm: str | None = None, - help_: bool = False, - runner: Runner | None = None, -) -> InspecOutputs: - """ - Outputs information found from specfile. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - specfile: Spec file to be read. - newspecname: Rewrite spec file. - detail: Level of output detail. Default is 1 in general, 0 with\ - -LRmerge. Available levels are 0, 1, 2, and 3. - leftspec: Merge two spec files in a way that makes sense for viewing in\ - SUMA. - rightspec: Merge two spec files in a way that makes sense for viewing\ - in SUMA. - state_rm: Get rid of state STATE_RM from the specfile. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `InspecOutputs`). - """ - if detail is not None and not (0 <= detail <= 3): - raise ValueError(f"'detail' must be between 0 <= x <= 3 but was {detail}") - runner = runner or get_global_runner() - execution = runner.start_execution(INSPEC_METADATA) - cargs = [] - cargs.append("inspec") - cargs.extend([ - "-spec", - execution.input_file(specfile) - ]) - if newspecname is not None: - cargs.extend([ - "-prefix", - newspecname - ]) - if detail is not None: - cargs.extend([ - "-detail", - str(detail) - ]) - if leftspec is not None: - cargs.extend([ - "-LRmerge", - execution.input_file(leftspec) - ]) - if rightspec is not None: - cargs.extend([ - "-LRmerge", - execution.input_file(rightspec) - ]) - if state_rm is not None: - cargs.extend([ - "-remove_state", - state_rm - ]) - if help_: - cargs.append("-help") - ret = InspecOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "INSPEC_METADATA", - "InspecOutputs", - "inspec", -] diff --git a/python/src/niwrap/afni/iso_surface.py b/python/src/niwrap/afni/iso_surface.py deleted file mode 100644 index 80deb5767..000000000 --- a/python/src/niwrap/afni/iso_surface.py +++ /dev/null @@ -1,152 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ISO_SURFACE_METADATA = Metadata( - id="ae4f55d6aa3df9abb44d283d9623f609eefee601.boutiques", - name="IsoSurface", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class IsoSurfaceOutputs(typing.NamedTuple): - """ - Output object returned when calling `iso_surface(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_surface_ply: OutputPathType - """Output isosurface in PLY format.""" - output_surface_gii: OutputPathType - """Output isosurface in GIFTI format.""" - output_surface_stl: OutputPathType - """Output isosurface in STL format.""" - - -def iso_surface( - input_vol: InputPathType | None = None, - shape_spec: list[str] | None = None, - isorois: bool = False, - isoval: str | None = None, - isorange: list[str] | None = None, - isocmask: str | None = None, - output_prefix: str | None = None, - tsmooth: list[str] | None = None, - debug: str | None = None, - autocrop: bool = False, - remesh: str | None = None, - xform: str | None = None, - novolreg: bool = False, - noxform: bool = False, - runner: Runner | None = None, -) -> IsoSurfaceOutputs: - """ - A program to perform isosurface extraction from a volume. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_vol: Input volume file. - shape_spec: Built-in shape specification. - isorois: Create isosurface for each unique value in the input volume. - isoval: Create isosurface where volume = V. - isorange: Create isosurface where V0 <= volume < V1. - isocmask: Create isosurface where MASK_COM != 0. - output_prefix: Prefix of output surface file. - tsmooth: Smooth resultant surface using Taubin smoothing with\ - parameters KPB and NITER. - debug: Debug levels of 0 (default), 1, 2, 3. - autocrop: Crop input volume before extraction. - remesh: Remesh the surface(s). - xform: Transform to apply to volume values before extracting. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations. - noxform: Same as -novolreg. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `IsoSurfaceOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ISO_SURFACE_METADATA) - cargs = [] - cargs.append("IsoSurface") - if input_vol is not None: - cargs.extend([ - "-input", - execution.input_file(input_vol) - ]) - if shape_spec is not None: - cargs.extend([ - "-shape", - *shape_spec - ]) - if isorois: - cargs.append("-isorois") - if isoval is not None: - cargs.extend([ - "-isoval", - isoval - ]) - if isorange is not None: - cargs.extend([ - "-isorange", - *isorange - ]) - if isocmask is not None: - cargs.extend([ - "-isocmask", - isocmask - ]) - if output_prefix is not None: - cargs.extend([ - "-o_TYPE", - output_prefix - ]) - if tsmooth is not None: - cargs.extend([ - "-Tsmooth", - *tsmooth - ]) - if debug is not None: - cargs.extend([ - "-debug", - debug - ]) - if autocrop: - cargs.append("-autocrop") - if remesh is not None: - cargs.extend([ - "-remesh", - remesh - ]) - if xform is not None: - cargs.extend([ - "-xform", - xform - ]) - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - ret = IsoSurfaceOutputs( - root=execution.output_file("."), - output_surface_ply=execution.output_file("[MASK]_surf.ply"), - output_surface_gii=execution.output_file("[MASK]_surf.gii"), - output_surface_stl=execution.output_file("[MASK]_surf.stl"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ISO_SURFACE_METADATA", - "IsoSurfaceOutputs", - "iso_surface", -] diff --git a/python/src/niwrap/afni/make_color_map.py b/python/src/niwrap/afni/make_color_map.py deleted file mode 100644 index 43ab44c0a..000000000 --- a/python/src/niwrap/afni/make_color_map.py +++ /dev/null @@ -1,188 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAKE_COLOR_MAP_METADATA = Metadata( - id="20feab346cace5f8666142aaf08be813c7020806.boutiques", - name="MakeColorMap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MakeColorMapOutputs(typing.NamedTuple): - """ - Output object returned when calling `make_color_map(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - afni_hex_output_prefix: OutputPathType | None - """Prefix for individual color values in AFNI Hex format.""" - palette_file_output: OutputPathType - """Example palette file output.""" - - -def make_color_map( - fiducials_ncol: InputPathType | None = None, - fiducials: InputPathType | None = None, - num_colors: float | None = None, - std_mapname: str | None = None, - palette_file: InputPathType | None = None, - cmap_name: str | None = None, - fscolut_labels: list[float] | None = None, - fscolut_file: InputPathType | None = None, - afni_hex: str | None = None, - afni_hex_complete: str | None = None, - suma_colormap: str | None = None, - user_colut_file: InputPathType | None = None, - sdset: InputPathType | None = None, - sdset_prefix: str | None = None, - flipupdown: bool = False, - skip_last: bool = False, - show_fscolut: bool = False, - help_flag: bool = False, - help_full_flag: bool = False, - flip_map_updside_down: bool = False, - runner: Runner | None = None, -) -> MakeColorMapOutputs: - """ - Utility for creating and modifying colormaps with various formats and fiducial - points. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fiducials_ncol: Fiducial colors and their indices in the color map are\ - listed in file Fiducials_Ncol. - fiducials: Fiducial colors are listed in an ascii file Fiducials. - num_colors: Total number of colors in the color map. - std_mapname: Returns one of SUMA's standard colormaps. - palette_file: Specify the palette file for colormap. - cmap_name: Specify the colormap name. - fscolut_labels: Get AFNI/SUMA colormaps of FreeSurfer colors indexed\ - between lbl0 and lbl1. - fscolut_file: Use color LUT file FS_COL_LUT. - afni_hex: Afni Hex format. Use this option if you want a color map\ - formatted to fit in AFNI's .afnirc file. - afni_hex_complete: Afni Hex format, ready to go into pbardefs.h. - suma_colormap: Write colormap in SUMA's format. - user_colut_file: Provide a user's own color lookup file. - sdset: Add colormap to surface-based dataset DSET, making it a labeled\ - dataset. - sdset_prefix: Prefix of dset for writing labeled version of DSET. - flipupdown: Flip the map upside down. - skip_last: If used, the last color in the Fiducial list is omitted. - show_fscolut: Show all of the FreeSurfer LUT. - help_flag: Displays the help message. - help_full_flag: Displays the help message. - flip_map_updside_down: Flip the map upside down. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MakeColorMapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MAKE_COLOR_MAP_METADATA) - cargs = [] - cargs.append("MakeColorMap") - if fiducials_ncol is not None: - cargs.extend([ - "-fn", - execution.input_file(fiducials_ncol) - ]) - if fiducials is not None: - cargs.extend([ - "-f", - execution.input_file(fiducials) - ]) - if num_colors is not None: - cargs.extend([ - "-nc", - str(num_colors) - ]) - if std_mapname is not None: - cargs.extend([ - "-std", - std_mapname - ]) - if palette_file is not None: - cargs.extend([ - "-cmapdb", - execution.input_file(palette_file) - ]) - if cmap_name is not None: - cargs.extend([ - "-cmap", - cmap_name - ]) - if fscolut_labels is not None: - cargs.extend([ - "-fscolut", - *map(str, fscolut_labels) - ]) - if fscolut_file is not None: - cargs.extend([ - "-fscolutfile", - execution.input_file(fscolut_file) - ]) - if afni_hex is not None: - cargs.extend([ - "-ah", - afni_hex - ]) - if afni_hex_complete is not None: - cargs.extend([ - "-ahc", - afni_hex_complete - ]) - if suma_colormap is not None: - cargs.extend([ - "-suma_cmap", - suma_colormap - ]) - if user_colut_file is not None: - cargs.extend([ - "-usercolutfile", - execution.input_file(user_colut_file) - ]) - if sdset is not None: - cargs.extend([ - "-sdset", - execution.input_file(sdset) - ]) - if sdset_prefix is not None: - cargs.extend([ - "-sdset_prefix", - sdset_prefix - ]) - if flipupdown: - cargs.append("-flipud") - if skip_last: - cargs.append("-sl") - if show_fscolut: - cargs.append("-show_fscolut") - if help_flag: - cargs.append("-h") - if help_full_flag: - cargs.append("-help") - if flip_map_updside_down: - cargs.append("-flipud") - ret = MakeColorMapOutputs( - root=execution.output_file("."), - afni_hex_output_prefix=execution.output_file(afni_hex + "_01") if (afni_hex is not None) else None, - palette_file_output=execution.output_file("TestPalette.pal"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAKE_COLOR_MAP_METADATA", - "MakeColorMapOutputs", - "make_color_map", -] diff --git a/python/src/niwrap/afni/make_pq_script_py.py b/python/src/niwrap/afni/make_pq_script_py.py deleted file mode 100644 index ff51a750d..000000000 --- a/python/src/niwrap/afni/make_pq_script_py.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAKE_PQ_SCRIPT_PY_METADATA = Metadata( - id="a615a94a90a33ebcd0b428159142b2d1a4947946.boutiques", - name="make_pq_script.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MakePqScriptPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `make_pq_script_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - script: OutputPathType - """Generated output script""" - - -def make_pq_script_py( - dataset: InputPathType, - brick_index: float, - mask: InputPathType, - out_script: str, - runner: Runner | None = None, -) -> MakePqScriptPyOutputs: - """ - Creates a script to compute p-value and q-value curves. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset (no sub-brick selectors). - brick_index: Volume sub-brick for specific t-stat. - mask: Mask volume dataset. - out_script: Name for output script to write. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MakePqScriptPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MAKE_PQ_SCRIPT_PY_METADATA) - cargs = [] - cargs.append("make_pq_script.py") - cargs.append(execution.input_file(dataset)) - cargs.append(str(brick_index)) - cargs.append(execution.input_file(mask)) - cargs.append(out_script) - ret = MakePqScriptPyOutputs( - root=execution.output_file("."), - script=execution.output_file(out_script), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAKE_PQ_SCRIPT_PY_METADATA", - "MakePqScriptPyOutputs", - "make_pq_script_py", -] diff --git a/python/src/niwrap/afni/make_random_timing_py.py b/python/src/niwrap/afni/make_random_timing_py.py deleted file mode 100644 index aabd5e33a..000000000 --- a/python/src/niwrap/afni/make_random_timing_py.py +++ /dev/null @@ -1,231 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAKE_RANDOM_TIMING_PY_METADATA = Metadata( - id="015b2b1c66a3f929dc8b7bc80bb3691f68a641ef.boutiques", - name="make_random_timing.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MakeRandomTimingPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `make_random_timing_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stim_output: OutputPathType - """Stimulus timing output file""" - - -def make_random_timing_py( - num_runs: float, - run_time: list[float], - num_stim: float, - num_reps: list[float], - prefix: str, - stim_dur: list[float] | None = None, - across_runs: bool = False, - max_consec: list[float] | None = None, - max_rest: float | None = None, - min_rest: float | None = None, - not_first: list[str] | None = None, - not_last: list[str] | None = None, - offset: float | None = None, - ordered_stimuli: list[str] | None = None, - pre_stim_rest: float | None = None, - post_stim_rest: float | None = None, - save_3dd_cmd: str | None = None, - seed: float | None = None, - stim_labels: list[str] | None = None, - t_digits: float | None = None, - t_gran: float | None = None, - tr: float | None = None, - tr_locked: bool = False, - verb: float | None = None, - show_timing_stats: bool = False, - runner: Runner | None = None, -) -> MakeRandomTimingPyOutputs: - """ - Create random stimulus timing files for use with AFNI 3dDeconvolve. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - num_runs: Set the number of runs. - run_time: Set the total time per run (in seconds). - num_stim: Set the number of stimulus classes. - num_reps: Set the number of repetitions per class (or across runs). - prefix: Set the prefix for output filenames. - stim_dur: Set the duration for a single stimulus (in seconds). - across_runs: Distribute stimuli across all runs at once. - max_consec: Specify maximum consecutive stimuli per class. - max_rest: Specify maximum rest between stimuli. - min_rest: Specify extra rest after each stimulus. - not_first: Specify classes that should not start a run. - not_last: Specify classes that should not end a run. - offset: Specify an offset to add to every stim time. - ordered_stimuli: Specify a partial ordering of stimuli. - pre_stim_rest: Specify minimum rest period to start each run. - post_stim_rest: Specify minimum rest period to end each run. - save_3dd_cmd: Save a 3dDeconvolve -nodata example. - seed: Specify a seed for random number generation. - stim_labels: Specify labels for the stimulus classes. - t_digits: Set the number of decimal places for times. - t_gran: Set the time granularity. - tr: Set the scanner TR. - tr_locked: Make stimuli timing locked to the accompanying TR. - verb: Set the verbose level. - show_timing_stats: Show statistics from the timing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MakeRandomTimingPyOutputs`). - """ - if not (1 <= num_runs): - raise ValueError(f"'num_runs' must be greater than 1 <= x but was {num_runs}") - if not (1 <= num_stim): - raise ValueError(f"'num_stim' must be greater than 1 <= x but was {num_stim}") - if not_first is not None and not (1 <= len(not_first)): - raise ValueError(f"Length of 'not_first' must be greater than 1 but was {len(not_first)}") - if not_last is not None and not (1 <= len(not_last)): - raise ValueError(f"Length of 'not_last' must be greater than 1 but was {len(not_last)}") - if ordered_stimuli is not None and not (1 <= len(ordered_stimuli)): - raise ValueError(f"Length of 'ordered_stimuli' must be greater than 1 but was {len(ordered_stimuli)}") - if stim_labels is not None and not (1 <= len(stim_labels)): - raise ValueError(f"Length of 'stim_labels' must be greater than 1 but was {len(stim_labels)}") - runner = runner or get_global_runner() - execution = runner.start_execution(MAKE_RANDOM_TIMING_PY_METADATA) - cargs = [] - cargs.append("make_random_timing.py") - cargs.extend([ - "-num_runs", - str(num_runs) - ]) - cargs.extend([ - "-run_time", - *map(str, run_time) - ]) - cargs.extend([ - "-num_stim", - str(num_stim) - ]) - cargs.extend([ - "-num_reps", - *map(str, num_reps) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if stim_dur is not None: - cargs.extend([ - "-stim_dur", - *map(str, stim_dur) - ]) - if across_runs: - cargs.append("-across_runs") - if max_consec is not None: - cargs.extend([ - "-max_consec", - *map(str, max_consec) - ]) - if max_rest is not None: - cargs.extend([ - "-max_rest", - str(max_rest) - ]) - if min_rest is not None: - cargs.extend([ - "-min_rest", - str(min_rest) - ]) - if not_first is not None: - cargs.extend([ - "-not_first", - *not_first - ]) - if not_last is not None: - cargs.extend([ - "-not_last", - *not_last - ]) - if offset is not None: - cargs.extend([ - "-offset", - str(offset) - ]) - if ordered_stimuli is not None: - cargs.extend([ - "-ordered_stimuli", - *ordered_stimuli - ]) - if pre_stim_rest is not None: - cargs.extend([ - "-pre_stim_rest", - str(pre_stim_rest) - ]) - if post_stim_rest is not None: - cargs.extend([ - "-post_stim_rest", - str(post_stim_rest) - ]) - if save_3dd_cmd is not None: - cargs.extend([ - "-save_3dd_cmd", - save_3dd_cmd - ]) - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - if stim_labels is not None: - cargs.extend([ - "-stim_labels", - *stim_labels - ]) - if t_digits is not None: - cargs.extend([ - "-t_digits", - str(t_digits) - ]) - if t_gran is not None: - cargs.extend([ - "-t_gran", - str(t_gran) - ]) - if tr is not None: - cargs.extend([ - "-tr", - str(tr) - ]) - if tr_locked: - cargs.append("-tr_locked") - if verb is not None: - cargs.extend([ - "-verb", - str(verb) - ]) - if show_timing_stats: - cargs.append("-show_timing_stats") - ret = MakeRandomTimingPyOutputs( - root=execution.output_file("."), - stim_output=execution.output_file(prefix + "_*.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAKE_RANDOM_TIMING_PY_METADATA", - "MakeRandomTimingPyOutputs", - "make_random_timing_py", -] diff --git a/python/src/niwrap/afni/make_stim_times_py.py b/python/src/niwrap/afni/make_stim_times_py.py deleted file mode 100644 index cd1151536..000000000 --- a/python/src/niwrap/afni/make_stim_times_py.py +++ /dev/null @@ -1,129 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAKE_STIM_TIMES_PY_METADATA = Metadata( - id="f75208d0c600ab0dda24250c27a9d53502ab9290.boutiques", - name="make_stim_times.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MakeStimTimesPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `make_stim_times_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_stim_times_01: OutputPathType - """Output stim_times file for first stimulus class""" - out_stim_times_02: OutputPathType - """Output stim_times file for second stimulus class""" - out_stim_times_03: OutputPathType - """Output stim_times file for third stimulus class""" - - -def make_stim_times_py( - files: list[InputPathType], - prefix: str, - tr: float, - nruns: float, - nt_: float, - run_trs: list[float] | None = None, - offset: float | None = None, - labels: list[str] | None = None, - no_consec_events: bool = False, - amplitudes: bool = False, - show_valid_opts: bool = False, - verbose: float | None = None, - runner: Runner | None = None, -) -> MakeStimTimesPyOutputs: - """ - Convert a set of 0/1 stim files into a set of stim_times files, or convert - real-valued files into those for use with -stim_times_AM2. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: Specify stim files. - prefix: Output prefix for files. - tr: TR time, in seconds. - nruns: Number of runs. - nt_: Number of TRs per run. - run_trs: Specify TRs per run, if they differ. - offset: Add OFFSET to all output times. - labels: Provide labels for filenames. - no_consec_events: Do not allow consecutive events. - amplitudes: Marry times with amplitudes. - show_valid_opts: Output all options. - verbose: Provide verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MakeStimTimesPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MAKE_STIM_TIMES_PY_METADATA) - cargs = [] - cargs.append("make_stim_times.py") - cargs.extend([execution.input_file(f) for f in files]) - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-tr", - str(tr) - ]) - cargs.extend([ - "-nruns", - str(nruns) - ]) - cargs.extend([ - "-nt", - str(nt_) - ]) - if run_trs is not None: - cargs.extend(map(str, run_trs)) - if offset is not None: - cargs.extend([ - "-offset", - str(offset) - ]) - if labels is not None: - cargs.extend([ - "-labels", - *labels - ]) - if no_consec_events: - cargs.append("-no_consec") - if amplitudes: - cargs.append("-amplitudes") - if show_valid_opts: - cargs.append("-show_valid_opts") - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - ret = MakeStimTimesPyOutputs( - root=execution.output_file("."), - out_stim_times_01=execution.output_file(prefix + ".01.1D"), - out_stim_times_02=execution.output_file(prefix + ".02.1D"), - out_stim_times_03=execution.output_file(prefix + ".03.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAKE_STIM_TIMES_PY_METADATA", - "MakeStimTimesPyOutputs", - "make_stim_times_py", -] diff --git a/python/src/niwrap/afni/map_icosahedron.py b/python/src/niwrap/afni/map_icosahedron.py deleted file mode 100644 index 7dabac2f6..000000000 --- a/python/src/niwrap/afni/map_icosahedron.py +++ /dev/null @@ -1,122 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAP_ICOSAHEDRON_METADATA = Metadata( - id="1d9e7bc123810e1827523a4f31aefece32f411e6.boutiques", - name="MapIcosahedron", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MapIcosahedronOutputs(typing.NamedTuple): - """ - Output object returned when calling `map_icosahedron(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def map_icosahedron( - spec_file: InputPathType, - rec_depth: float | None = None, - lin_depth: float | None = None, - morph_surf: str | None = None, - num_it: float | None = None, - prefix: str | None = None, - nn_dset: str | None = None, - dset: str | None = None, - fix_cut_surfaces: bool = False, - verbosity: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> MapIcosahedronOutputs: - """ - Creates new versions of original-mesh surfaces using the mesh of an icosahedron. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: Spec file containing original-mesh surfaces. - rec_depth: Recursive (binary) tessellation depth for icosahedron\ - (default: 3). - lin_depth: Number of edge divides for linear icosahedron tessellation. - morph_surf: Specifies the morphSurf surface. - num_it: Number of smoothing iterations. - prefix: Prefix for output files (default: 'std.'). - nn_dset: Map DSET onto the new mesh using Nearest Neighbor\ - interpolation. - dset: Map DSET onto the new mesh using barycentric interpolation. - fix_cut_surfaces: Check and fix standard-mesh surfaces with cuts for\ - cross-cut connections. - verbosity: Enable verbose output. - help_: Display the help text. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MapIcosahedronOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MAP_ICOSAHEDRON_METADATA) - cargs = [] - cargs.append("MapIcosahedron") - cargs.append(execution.input_file(spec_file)) - if rec_depth is not None: - cargs.extend([ - "-rd", - str(rec_depth) - ]) - if lin_depth is not None: - cargs.extend([ - "-ld", - str(lin_depth) - ]) - if morph_surf is not None: - cargs.extend([ - "-morph", - morph_surf - ]) - if num_it is not None: - cargs.extend([ - "-it", - str(num_it) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if nn_dset is not None: - cargs.extend([ - "-NN_dset_map", - nn_dset - ]) - if dset is not None: - cargs.extend([ - "-dset_map", - dset - ]) - if fix_cut_surfaces: - cargs.append("-fix_cut_surfaces") - if verbosity: - cargs.append("-verb") - if help_: - cargs.append("-help") - ret = MapIcosahedronOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAP_ICOSAHEDRON_METADATA", - "MapIcosahedronOutputs", - "map_icosahedron", -] diff --git a/python/src/niwrap/afni/map_track_id.py b/python/src/niwrap/afni/map_track_id.py deleted file mode 100644 index 7790abd67..000000000 --- a/python/src/niwrap/afni/map_track_id.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MAP_TRACK_ID_METADATA = Metadata( - id="b7b386b4448e9a7ba850519cb7c0ac387a865bbf.boutiques", - name="map_TrackID", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MapTrackIdOutputs(typing.NamedTuple): - """ - Output object returned when calling `map_track_id(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_trk_file: OutputPathType - """Mapped track file to new space""" - - -def map_track_id( - prefix: str, - in_trk: InputPathType, - in_map: InputPathType, - reference: InputPathType, - verbose: bool = False, - orig_zero: bool = False, - line_only_num: bool = False, - already_inv: bool = False, - runner: Runner | None = None, -) -> MapTrackIdOutputs: - """ - Maps the track file (*.trk) output of 3dTrackID to another space using the - 1Dmatrix_save info of 3dAllineate. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for the output track file. - in_trk: The name of the *.trk file to be mapped. - in_map: Single line of matrix values for the transformation. - reference: 3D data set in the space to which the TRK file is being\ - mapped. - verbose: Verbose output. - orig_zero: Put (0,0,0) as the origin in the output *.trk file. - line_only_num: If your 1D_MATR file is just 12 numbers in a row. - already_inv: If you have inverted the mapping or use another program\ - than 3dAllineate. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MapTrackIdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MAP_TRACK_ID_METADATA) - cargs = [] - cargs.append("map_TrackID") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-in_trk") - cargs.append(execution.input_file(in_trk)) - cargs.append("-in_map") - cargs.append(execution.input_file(in_map)) - cargs.append("-ref") - cargs.append(execution.input_file(reference)) - if verbose: - cargs.append("-verb") - if orig_zero: - cargs.append("-orig_zero") - if line_only_num: - cargs.append("-line_only_num") - if already_inv: - cargs.append("-already_inv") - ret = MapTrackIdOutputs( - root=execution.output_file("."), - output_trk_file=execution.output_file(prefix + ".trk"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MAP_TRACK_ID_METADATA", - "MapTrackIdOutputs", - "map_track_id", -] diff --git a/python/src/niwrap/afni/mba.py b/python/src/niwrap/afni/mba.py deleted file mode 100644 index c87423a29..000000000 --- a/python/src/niwrap/afni/mba.py +++ /dev/null @@ -1,162 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MBA_METADATA = Metadata( - id="cee08b6858733246df01cc8fbb1acb20fffe47a7.boutiques", - name="MBA", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MbaOutputs(typing.NamedTuple): - """ - Output object returned when calling `mba(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_txt: OutputPathType - """Main output text file storing inference information""" - output_rdata: OutputPathType - """R data file for post hoc processing and plotting""" - matrix_plot: OutputPathType - """Matrix plot visualization of analysis""" - - -def mba( - prefix: str, - data_table: InputPathType, - chains: int | None = None, - iterations: int | None = None, - model: str | None = None, - eoi: str | None = None, - cvars: str | None = None, - qvars: str | None = None, - qcvar: str | None = None, - stdz: str | None = None, - wcp: int | None = None, - disty: str | None = None, - se: str | None = None, - dbg_args: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> MbaOutputs: - """ - Matrix-Based Analysis Program through Bayesian Multilevel Modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output file names. - data_table: Specify the data structure in a table of long format. - chains: Specify the number of Markov chains. - iterations: Specify the number of iterations per Markov chain. - model: Specify the effects associated with explanatory variables. - eoi: Identify effects of interest in the output. - cvars: Identify categorical (qualitative) variables. - qvars: Identify quantitative variables (or covariates). - qcvar: Identify comparisons of interest between quantitative variables. - stdz: Identify quantitative variables (or covariates) to be\ - standardized. - wcp: Invoke within-chain parallelization to speed up runtime. - disty: Specify the distribution for the response variable. - se: Specify the column name that designates the standard error for the\ - response variable. - dbg_args: Enable R to save the parameters in a file called\ - .MBA.dbg.AFNI.args for debugging purposes. - help_: Show help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MbaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MBA_METADATA) - cargs = [] - cargs.append("MBA") - cargs.append(prefix) - if chains is not None: - cargs.extend([ - "-chains", - str(chains) - ]) - if iterations is not None: - cargs.extend([ - "-iterations", - str(iterations) - ]) - if model is not None: - cargs.extend([ - "-model", - model - ]) - if eoi is not None: - cargs.extend([ - "-EOI", - eoi - ]) - cargs.extend([ - "-dataTable", - execution.input_file(data_table) - ]) - if cvars is not None: - cargs.extend([ - "-cVars", - cvars - ]) - if qvars is not None: - cargs.extend([ - "-qVars", - qvars - ]) - if qcvar is not None: - cargs.extend([ - "-qContr", - qcvar - ]) - if stdz is not None: - cargs.extend([ - "-stdz", - stdz - ]) - if wcp is not None: - cargs.extend([ - "-WCP", - str(wcp) - ]) - if disty is not None: - cargs.extend([ - "-distY", - disty - ]) - if se is not None: - cargs.extend([ - "-se", - se - ]) - cargs.append("[RPREFIX]") - if dbg_args: - cargs.append("-dbgArgs") - if help_: - cargs.append("-help") - ret = MbaOutputs( - root=execution.output_file("."), - output_txt=execution.output_file(prefix + ".txt"), - output_rdata=execution.output_file(prefix + ".RData"), - matrix_plot=execution.output_file(prefix + "_matrixplot.png"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MBA_METADATA", - "MbaOutputs", - "mba", -] diff --git a/python/src/niwrap/afni/meica_py.py b/python/src/niwrap/afni/meica_py.py deleted file mode 100644 index 23c8a308c..000000000 --- a/python/src/niwrap/afni/meica_py.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MEICA_PY_METADATA = Metadata( - id="5ae02d926937c9c63f30c373b905edbe3696ed5f.boutiques", - name="meica.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MeicaPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `meica_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - cleaned_bold: OutputPathType - """Cleaned BOLD image after ME-ICA processing""" - components_output: OutputPathType - """Independent components result of ICA""" - - -def meica_py( - infile: InputPathType, - echo_times: str, - affine: str, - output_directory: str, - components: float | None = None, - talairach: bool = False, - threshold: float | None = None, - debug: bool = False, - runner: Runner | None = None, -) -> MeicaPyOutputs: - """ - Multi-Echo Independent Component Analysis for fMRI denoising. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input image dataset (e.g. dataset.nii.gz). - echo_times: Echo times (e.g. 15.0,30.0,45.0). - affine: Affine registration matrix. - output_directory: Output directory. - components: Number of components for ICA. - talairach: Apply standard Talairach transformation. - threshold: Threshold value for masking. - debug: Enable debug mode. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MeicaPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MEICA_PY_METADATA) - cargs = [] - cargs.append("meica.py") - cargs.append("-d") - cargs.append(execution.input_file(infile)) - cargs.append("-e") - cargs.append(echo_times) - cargs.append("-a") - cargs.append(affine) - cargs.append("-o") - cargs.append(output_directory) - if components is not None: - cargs.extend([ - "-c", - str(components) - ]) - if talairach: - cargs.append("-t") - if threshold is not None: - cargs.extend([ - "--thresh", - str(threshold) - ]) - if debug: - cargs.append("--debug") - ret = MeicaPyOutputs( - root=execution.output_file("."), - cleaned_bold=execution.output_file(output_directory + "/cleaned_bold.nii.gz"), - components_output=execution.output_file(output_directory + "/components.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MEICA_PY_METADATA", - "MeicaPyOutputs", - "meica_py", -] diff --git a/python/src/niwrap/afni/myget.py b/python/src/niwrap/afni/myget.py deleted file mode 100644 index 930485cf8..000000000 --- a/python/src/niwrap/afni/myget.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MYGET_METADATA = Metadata( - id="c9b4fcca61f5094a804dc14dd52979b5c3e3888c.boutiques", - name="myget", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class MygetOutputs(typing.NamedTuple): - """ - Output object returned when calling `myget(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """The filename to save the downloaded file""" - - -def myget( - url: str, - protocol_version: typing.Literal["-1", "-1.1"] | None = None, - runner: Runner | None = None, -) -> MygetOutputs: - """ - A simple file downloader from a URL. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - url: The URL to download the file from. - protocol_version: Specify protocol version. You can choose between -1\ - or -1.1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MygetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MYGET_METADATA) - cargs = [] - cargs.append("myget") - if protocol_version is not None: - cargs.append(protocol_version) - cargs.append(url) - ret = MygetOutputs( - root=execution.output_file("."), - output_file=execution.output_file("[OUTPUT_FILE]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MYGET_METADATA", - "MygetOutputs", - "myget", -] diff --git a/python/src/niwrap/afni/neuro_deconvolve_py.py b/python/src/niwrap/afni/neuro_deconvolve_py.py deleted file mode 100644 index 296f1a8e7..000000000 --- a/python/src/niwrap/afni/neuro_deconvolve_py.py +++ /dev/null @@ -1,122 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NEURO_DECONVOLVE_PY_METADATA = Metadata( - id="7deab2368a36fa0ebe35904371306494cb49280c.boutiques", - name="neuro_deconvolve.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NeuroDeconvolvePyOutputs(typing.NamedTuple): - """ - Output object returned when calling `neuro_deconvolve_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType - """Main default output head file""" - output_brik: OutputPathType - """Main default output BRIK file""" - kernel_file_out: OutputPathType | None - """File storing the response kernel""" - - -def neuro_deconvolve_py( - input_file: InputPathType, - prefix: str, - script: str, - kernel: str | None = None, - kernel_file: str | None = None, - mask_dset: InputPathType | None = None, - old_style: bool = False, - tr: float | None = None, - tr_nup: float | None = None, - verbosity: float | None = None, - runner: Runner | None = None, -) -> NeuroDeconvolvePyOutputs: - """ - Generate a script to apply 3dTfitter to deconvolve an MRI signal (BOLD response - curve) into a neuro response curve. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Set the data to deconvolve. - prefix: Set the prefix for output filenames. - script: Specify the name of the output script. - kernel: Set the response kernel. - kernel_file: Set the filename to store the kernel in; should be at the\ - upsampled TR. - mask_dset: Set a mask dataset for 3dTfitter to use. - old_style: Make old-style script (pre-2015.02.24) for 1D case. - tr: Set the scanner TR; needed for 1D formatted input files. - tr_nup: Upsample factor for TR; number of pieces each original TR is\ - divided into. - verbosity: Set the verbose level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NeuroDeconvolvePyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NEURO_DECONVOLVE_PY_METADATA) - cargs = [] - cargs.append("neuro_deconvolve.py") - cargs.append(execution.input_file(input_file)) - cargs.append(prefix) - cargs.append(script) - if kernel is not None: - cargs.extend([ - "-kernel", - kernel - ]) - if kernel_file is not None: - cargs.extend([ - "-kernel_file", - kernel_file - ]) - if mask_dset is not None: - cargs.extend([ - "-mask_dset", - execution.input_file(mask_dset) - ]) - if old_style: - cargs.append("-old") - if tr is not None: - cargs.extend([ - "-tr", - str(tr) - ]) - if tr_nup is not None: - cargs.extend([ - "-tr_nup", - str(tr_nup) - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = NeuroDeconvolvePyOutputs( - root=execution.output_file("."), - output_head=execution.output_file(prefix + "+orig.HEAD"), - output_brik=execution.output_file(prefix + "+orig.BRIK"), - kernel_file_out=execution.output_file(kernel_file) if (kernel_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NEURO_DECONVOLVE_PY_METADATA", - "NeuroDeconvolvePyOutputs", - "neuro_deconvolve_py", -] diff --git a/python/src/niwrap/afni/nicat.py b/python/src/niwrap/afni/nicat.py deleted file mode 100644 index 167c89a71..000000000 --- a/python/src/niwrap/afni/nicat.py +++ /dev/null @@ -1,75 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NICAT_METADATA = Metadata( - id="73c164cef1e5f1ef78d5ba447429f7192095a87b.boutiques", - name="nicat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NicatOutputs(typing.NamedTuple): - """ - Output object returned when calling `nicat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def nicat( - stream_spec: str, - reopen: str | None = None, - copy_stream: bool = False, - read_only: bool = False, - runner: Runner | None = None, -) -> NicatOutputs: - """ - Copies stdin to the NIML stream, which will be opened for writing. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - stream_spec: Stream specification (e.g., tcp:localhost:4444). - reopen: Reopen the stream after connection to the stream specified by\ - the given value. - copy_stream: Copy the stream to stdout instead; the 'streamspec' will\ - be opened for reading. - read_only: Read the stream but don't copy to stdout. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NicatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NICAT_METADATA) - cargs = [] - cargs.append("nicat") - cargs.append(stream_spec) - if reopen is not None: - cargs.extend([ - "-reopen", - reopen - ]) - if copy_stream: - cargs.append("-r") - if read_only: - cargs.append("-R") - ret = NicatOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NICAT_METADATA", - "NicatOutputs", - "nicat", -] diff --git a/python/src/niwrap/afni/niccc.py b/python/src/niwrap/afni/niccc.py deleted file mode 100644 index 9c9d0b866..000000000 --- a/python/src/niwrap/afni/niccc.py +++ /dev/null @@ -1,129 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NICCC_METADATA = Metadata( - id="ecc865fc2143792b2c5c1c0adc6ffbd967c02c7f.boutiques", - name="niccc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NicccOutputs(typing.NamedTuple): - """ - Output object returned when calling `niccc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stderr_output: OutputPathType - """Results output to stderr""" - - -def niccc( - streamspec: str, - duplicate: bool = False, - nodata: bool = False, - attribute: str | None = None, - match: str | None = None, - file: bool = False, - string_: bool = False, - stdout: bool = False, - hash_: bool = False, - quiet: bool = False, - find_attr: list[str] | None = None, - skip_attr: list[str] | None = None, - runner: Runner | None = None, -) -> NicccOutputs: - """ - A program for conducting certain NIML tests on input from streamspec and write - the results to stderr. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - streamspec: A string defining a NIML stream. - duplicate: Duplicate the element before showing it. This is to test\ - NI_duplicate function. - nodata: Show header parts only in output. - attribute: Dump the value of attribute ATTR. - match: Match attribute: If MATCH is exact, then attribute name is\ - matched exactly. If MATCH is partial, then a match of all the\ - characters in ATTR is enough. - file: Streamspec is a filename. - string_: Streamspec is an element string like: ''. - stdout: Write elements to stdout, instead of stderr. - hash_: Put the # at the beginning of lines with no data. - quiet: Quiet stderr messages, and don't echo attribute name with\ - -attribute option. - find_attr: Only output elements that have an attribute ATTR of value\ - ATTRVAL. - skip_attr: Do not output elements that have an attribute ATTR of value\ - ATTRVAL. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NicccOutputs`). - """ - if find_attr is not None and (len(find_attr) != 2): - raise ValueError(f"Length of 'find_attr' must be 2 but was {len(find_attr)}") - if skip_attr is not None and (len(skip_attr) != 2): - raise ValueError(f"Length of 'skip_attr' must be 2 but was {len(skip_attr)}") - runner = runner or get_global_runner() - execution = runner.start_execution(NICCC_METADATA) - cargs = [] - cargs.append("niccc") - cargs.append(streamspec) - if duplicate: - cargs.append("-dup") - if nodata: - cargs.append("-nodata") - if attribute is not None: - cargs.extend([ - "-attribute", - attribute - ]) - if match is not None: - cargs.extend([ - "-match", - match - ]) - if file: - cargs.append("-f") - if string_: - cargs.append("-s") - if stdout: - cargs.append("-stdout") - if hash_: - cargs.append("-#") - if quiet: - cargs.append("-quiet") - if find_attr is not None: - cargs.extend([ - "-find_nel_with_attr", - *find_attr - ]) - if skip_attr is not None: - cargs.extend([ - "-skip_nel_with_attr", - *skip_attr - ]) - ret = NicccOutputs( - root=execution.output_file("."), - stderr_output=execution.output_file("stderr"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NICCC_METADATA", - "NicccOutputs", - "niccc", -] diff --git a/python/src/niwrap/afni/nifti_tool.py b/python/src/niwrap/afni/nifti_tool.py deleted file mode 100644 index c80ef529a..000000000 --- a/python/src/niwrap/afni/nifti_tool.py +++ /dev/null @@ -1,132 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NIFTI_TOOL_METADATA = Metadata( - id="38a2d9449adee7d6233168e977d87d95385ebe37.boutiques", - name="nifti_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NiftiToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `nifti_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """The nifti file generated as output.""" - - -def nifti_tool( - action: str, - input_files: list[InputPathType] | None = None, - field: str | None = None, - mod_field: str | None = None, - prefix: str | None = None, - debug: float | None = None, - overwrite: bool = False, - convert2dtype: str | None = None, - convert_fail_choice: str | None = None, - convert_verify: bool = False, - add_comment_ext: str | None = None, - rm_ext: str | None = None, - runner: Runner | None = None, -) -> NiftiToolOutputs: - """ - Display, modify, or compare nifti headers. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - action: Action type that defines what nifti_tool will do. - input_files: One or more input nifti files. - field: Field name to display, modify, or compare. - mod_field: Field name and new value to modify. - prefix: Prefix for the output file. - debug: Debugging level (0-3). - overwrite: Overwrite input files with modifications. - convert2dtype: Convert data to a new datatype. - convert_fail_choice: Action on conversion failure (ignore, warn, fail). - convert_verify: Verify datatype conversion exactness. - add_comment_ext: Add COMMENT-type extension to dataset. - rm_ext: Remove extension by index or ALL. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NiftiToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NIFTI_TOOL_METADATA) - cargs = [] - cargs.append("nifti_tool") - cargs.append(action) - if input_files is not None: - cargs.extend([ - "-infiles", - *[execution.input_file(f) for f in input_files] - ]) - if field is not None: - cargs.extend([ - "-field", - field - ]) - if mod_field is not None: - cargs.extend([ - "-mod_field", - mod_field - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if overwrite: - cargs.append("-overwrite") - if convert2dtype is not None: - cargs.extend([ - "-convert2dtype", - convert2dtype - ]) - if convert_fail_choice is not None: - cargs.extend([ - "-convert_fail_choice", - convert_fail_choice - ]) - if convert_verify: - cargs.append("-convert_verify") - if add_comment_ext is not None: - cargs.extend([ - "-add_comment_ext", - add_comment_ext - ]) - if rm_ext is not None: - cargs.extend([ - "-rm_ext", - rm_ext - ]) - ret = NiftiToolOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NIFTI_TOOL_METADATA", - "NiftiToolOutputs", - "nifti_tool", -] diff --git a/python/src/niwrap/afni/niml_feedme.py b/python/src/niwrap/afni/niml_feedme.py deleted file mode 100644 index fe40367bb..000000000 --- a/python/src/niwrap/afni/niml_feedme.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NIML_FEEDME_METADATA = Metadata( - id="fb1cdc6646a98c2a55bf5ec641a55cf82a23e490.boutiques", - name="niml_feedme", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NimlFeedmeOutputs(typing.NamedTuple): - """ - Output object returned when calling `niml_feedme(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def niml_feedme( - dataset: InputPathType, - host: str | None = None, - interval: float | None = None, - verbose: bool = False, - accum: bool = False, - target_dataset: str | None = None, - drive_cmds: list[str] | None = None, - runner: Runner | None = None, -) -> NimlFeedmeOutputs: - """ - Sends volumes from the dataset to AFNI via the NIML socket interface. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset to be sent to AFNI. - host: Send data, via TCP/IP, to AFNI running on the computer system\ - 'sname'. By default, uses the current system (localhost), if you don't\ - use this option. - interval: Tries to maintain an inter-transmit interval of 'ms'\ - milliseconds. The default is 1000 msec per volume. - verbose: Be (very) talkative about actions. - accum: Send sub-bricks so that they accumulate in AFNI. The default is\ - to create only a 1 volume dataset inside AFNI, and each sub-brick just\ - replaces that one volume when it is received. - target_dataset: Change the dataset name transmitted to AFNI from\ - 'niml_feedme' to 'nam'. - drive_cmds: Send 'cmd' as a DRIVE_AFNI command. If cmd contains blanks,\ - it must be in 'quotes'. Multiple -drive options may be used. These\ - commands will be sent to AFNI just after the first volume is\ - transmitted. See file README.driver for a list of commands. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NimlFeedmeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NIML_FEEDME_METADATA) - cargs = [] - cargs.append("niml_feedme") - if host is not None: - cargs.extend([ - "-host", - host - ]) - if interval is not None: - cargs.extend([ - "-dt", - str(interval) - ]) - if verbose: - cargs.append("-verb") - if accum: - cargs.append("-accum") - if target_dataset is not None: - cargs.extend([ - "-target", - target_dataset - ]) - if drive_cmds is not None: - cargs.extend([ - "-drive", - *drive_cmds - ]) - cargs.append(execution.input_file(dataset)) - ret = NimlFeedmeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NIML_FEEDME_METADATA", - "NimlFeedmeOutputs", - "niml_feedme", -] diff --git a/python/src/niwrap/afni/nsize.py b/python/src/niwrap/afni/nsize.py deleted file mode 100644 index 5e2e2d4fa..000000000 --- a/python/src/niwrap/afni/nsize.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NSIZE_METADATA = Metadata( - id="d61eb0714ab51aec00c025a2f54aab55318f6b55.boutiques", - name="nsize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class NsizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `nsize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - image_out_file: OutputPathType - """Zero padded output image file""" - - -def nsize( - image_in: InputPathType, - image_out: str, - runner: Runner | None = None, -) -> NsizeOutputs: - """ - Zero pads an input image to the nearest larger NxN dimensions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - image_in: Input image file. - image_out: Output padded image file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NsizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NSIZE_METADATA) - cargs = [] - cargs.append("nsize") - cargs.append(execution.input_file(image_in)) - cargs.append(image_out) - ret = NsizeOutputs( - root=execution.output_file("."), - image_out_file=execution.output_file(image_out), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NSIZE_METADATA", - "NsizeOutputs", - "nsize", -] diff --git a/python/src/niwrap/afni/p2dsetstat.py b/python/src/niwrap/afni/p2dsetstat.py deleted file mode 100644 index 1e193df49..000000000 --- a/python/src/niwrap/afni/p2dsetstat.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -P2DSETSTAT_METADATA = Metadata( - id="eb69978f59a4e2eaa05a7732b02e79f2ba3725b2.boutiques", - name="p2dsetstat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class P2dsetstatOutputs(typing.NamedTuple): - """ - Output object returned when calling `p2dsetstat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stat_value: OutputPathType - """The converted statistic value.""" - - -def p2dsetstat( - dataset: str, - pvalue: float, - onesided: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> P2dsetstatOutputs: - """ - Convert a p-value to a statistic of choice with reference to a specific dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Specify a dataset DDD and, if it has multiple sub-bricks, the\ - [i]th subbrick with the statistic of interest MUST be selected\ - explicitly; note the use of quotation marks around the brick selector\ - (because of the square-brackets). 'i' can be either a number or a\ - string label selector. - pvalue: Input p-value P, which MUST be in the interval [0,1]. - onesided: One-sided test. - quiet: Output only the final statistic value. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `P2dsetstatOutputs`). - """ - if not (0 <= pvalue <= 1): - raise ValueError(f"'pvalue' must be between 0 <= x <= 1 but was {pvalue}") - runner = runner or get_global_runner() - execution = runner.start_execution(P2DSETSTAT_METADATA) - cargs = [] - cargs.append("p2dsetstat") - cargs.append("-inset") - cargs.extend([ - "-inset", - dataset - ]) - cargs.append("-pval") - cargs.extend([ - "-pval", - str(pvalue) - ]) - if onesided: - cargs.append("-1sided") - if quiet: - cargs.append("-quiet") - ret = P2dsetstatOutputs( - root=execution.output_file("."), - stat_value=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "P2DSETSTAT_METADATA", - "P2dsetstatOutputs", - "p2dsetstat", -] diff --git a/python/src/niwrap/afni/parse_fs_lt_log_py.py b/python/src/niwrap/afni/parse_fs_lt_log_py.py deleted file mode 100644 index f85014a5b..000000000 --- a/python/src/niwrap/afni/parse_fs_lt_log_py.py +++ /dev/null @@ -1,81 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PARSE_FS_LT_LOG_PY_METADATA = Metadata( - id="268d4ee0e1a275627c35202711852c46337de68c.boutiques", - name="parse_fs_lt_log.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ParseFsLtLogPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `parse_fs_lt_log_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def parse_fs_lt_log_py( - logfile: InputPathType, - labels: list[str], - show_orig: bool = False, - show_all_orig: bool = False, - verbosity: float | None = None, - runner: Runner | None = None, -) -> ParseFsLtLogPyOutputs: - """ - Parses FreeSurfer labeltable log file and retrieves labeltable indices. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - logfile: Specify rank log file. - labels: Specify a list of labels to search for. - show_orig: Show original label indices. - show_all_orig: Show all original label indices. - verbosity: Specify verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ParseFsLtLogPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PARSE_FS_LT_LOG_PY_METADATA) - cargs = [] - cargs.append("parse_fs_lt_log.py") - cargs.append("-logfile") - cargs.append(execution.input_file(logfile)) - cargs.append("-labels") - cargs.extend([ - "-labels", - *labels - ]) - if show_orig: - cargs.append("-show_orig") - if show_all_orig: - cargs.append("-show_all_orig") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = ParseFsLtLogPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PARSE_FS_LT_LOG_PY_METADATA", - "ParseFsLtLogPyOutputs", - "parse_fs_lt_log_py", -] diff --git a/python/src/niwrap/afni/plugout_drive.py b/python/src/niwrap/afni/plugout_drive.py deleted file mode 100644 index 09417492d..000000000 --- a/python/src/niwrap/afni/plugout_drive.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PLUGOUT_DRIVE_METADATA = Metadata( - id="e1cb039cf6cd9c8eda885b4de1361558d90e3b37.boutiques", - name="plugout_drive", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PlugoutDriveOutputs(typing.NamedTuple): - """ - Output object returned when calling `plugout_drive(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def plugout_drive( - host: str | None = None, - verbose: bool = False, - port: float | None = None, - maxwait: float | None = None, - name: str | None = None, - command: list[str] | None = None, - quit_: bool = False, - runner: Runner | None = None, -) -> PlugoutDriveOutputs: - """ - This program connects to AFNI and sends commands that the user specifies - interactively or on command line over to AFNI to be executed. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - host: Connect to AFNI running on the specified host using TCP/IP.\ - Default is 'localhost'. - verbose: Verbose mode. - port: Use TCP/IP port number. Default is 8099. - maxwait: Maximum wait time in seconds for AFNI to connect. Default is 9\ - seconds. - name: Name that AFNI assigns to this plugout. Default is a pre-defined\ - name. - command: Command to be executed on AFNI. Example: '-com "SET_FUNCTION\ - SomeFunction"'. - quit_: Quit after executing all -com commands. Default is to wait for\ - more commands. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PlugoutDriveOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PLUGOUT_DRIVE_METADATA) - cargs = [] - cargs.append("plugout_drive") - if host is not None: - cargs.extend([ - "-host", - host - ]) - if verbose: - cargs.append("-v") - if port is not None: - cargs.extend([ - "-port", - str(port) - ]) - if maxwait is not None: - cargs.extend([ - "-maxwait", - str(maxwait) - ]) - if name is not None: - cargs.extend([ - "-name", - name - ]) - if command is not None: - cargs.extend([ - "-com", - *command - ]) - if quit_: - cargs.append("-quit") - ret = PlugoutDriveOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PLUGOUT_DRIVE_METADATA", - "PlugoutDriveOutputs", - "plugout_drive", -] diff --git a/python/src/niwrap/afni/plugout_ijk.py b/python/src/niwrap/afni/plugout_ijk.py deleted file mode 100644 index b0f1e77ac..000000000 --- a/python/src/niwrap/afni/plugout_ijk.py +++ /dev/null @@ -1,126 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PLUGOUT_IJK_METADATA = Metadata( - id="546af73f34fcb7f296f73da1cc63ae4ec231fec2.boutiques", - name="plugout_ijk", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PlugoutIjkOutputs(typing.NamedTuple): - """ - Output object returned when calling `plugout_ijk(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def plugout_ijk( - host: str | None = None, - verbose: bool = False, - port: float | None = None, - name: str | None = None, - port_offset: float | None = None, - port_quiet: float | None = None, - port_bloc_offset: float | None = None, - max_bloc: bool = False, - max_bloc_quiet: bool = False, - num_assigned_ports: bool = False, - num_assigned_ports_quiet: bool = False, - runner: Runner | None = None, -) -> PlugoutIjkOutputs: - """ - Connects to AFNI and sends (i,j,k) dataset indices to control the viewpoint. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - host: Connect to AFNI running on the specified computer using TCP/IP. - verbose: Verbose mode. - port: Use TCP/IP port number 'pp'. - name: Use the string 'sss' for the name that AFNI assigns to this\ - plugout. - port_offset: Provide a port offset to allow multiple instances of\ - communicating programs to operate on the same machine. - port_quiet: Provide a port offset like -np, but more quiet in the face\ - of adversity. - port_bloc_offset: Provide a port offset block for easier port\ - management. - max_bloc: Print the current value of MAX_BLOC and exit. - max_bloc_quiet: Print MAX_BLOC value only and exit. - num_assigned_ports: Print the number of assigned ports used by AFNI\ - then quit. - num_assigned_ports_quiet: Prints the number of assigned ports quietly. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PlugoutIjkOutputs`). - """ - if port_offset is not None and not (1025 <= port_offset <= 65500): - raise ValueError(f"'port_offset' must be between 1025 <= x <= 65500 but was {port_offset}") - if port_bloc_offset is not None and not (port_bloc_offset <= 4000): - raise ValueError(f"'port_bloc_offset' must be less than x <= 4000 but was {port_bloc_offset}") - runner = runner or get_global_runner() - execution = runner.start_execution(PLUGOUT_IJK_METADATA) - cargs = [] - cargs.append("plugout_ijk") - if host is not None: - cargs.extend([ - "-host", - host - ]) - if verbose: - cargs.append("-v") - if port is not None: - cargs.extend([ - "-port", - str(port) - ]) - if name is not None: - cargs.extend([ - "-name", - name - ]) - if port_offset is not None: - cargs.extend([ - "-np", - str(port_offset) - ]) - if port_quiet is not None: - cargs.extend([ - "-npq", - str(port_quiet) - ]) - if port_bloc_offset is not None: - cargs.extend([ - "-npb", - str(port_bloc_offset) - ]) - if max_bloc: - cargs.append("-max_port_bloc") - if max_bloc_quiet: - cargs.append("-max_port_bloc_quiet") - if num_assigned_ports: - cargs.append("-num_assigned_ports") - if num_assigned_ports_quiet: - cargs.append("-num_assigned_ports_quiet") - ret = PlugoutIjkOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PLUGOUT_IJK_METADATA", - "PlugoutIjkOutputs", - "plugout_ijk", -] diff --git a/python/src/niwrap/afni/plugout_tt.py b/python/src/niwrap/afni/plugout_tt.py deleted file mode 100644 index 76ef21783..000000000 --- a/python/src/niwrap/afni/plugout_tt.py +++ /dev/null @@ -1,136 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PLUGOUT_TT_METADATA = Metadata( - id="d510b7ebed31b891771c37d3c963ffa43b94825e.boutiques", - name="plugout_tt", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PlugoutTtOutputs(typing.NamedTuple): - """ - Output object returned when calling `plugout_tt(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def plugout_tt( - host: str | None = None, - ijk_option: bool = False, - verbose: bool = False, - port: float | None = None, - name: str | None = None, - port_offset: float | None = None, - port_offset_quiet: float | None = None, - port_bloc: float | None = None, - max_port_bloc: bool = False, - max_port_bloc_quiet: bool = False, - num_assigned_ports: bool = False, - num_assigned_ports_quiet: bool = False, - runner: Runner | None = None, -) -> PlugoutTtOutputs: - """ - This program connects to AFNI and receives notification whenever the user - changes Talairach coordinates. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - host: Name of the host computer to connect to AFNI on. The default is\ - to connect on the current host using shared memory. - ijk_option: Get voxel indices from AFNI instead of Talairach\ - coordinates. - verbose: Enable verbose mode (prints lots of diagnostic messages). - port: TCP/IP port number to use. The default is 8001. - name: String to use as the name that AFNI assigns to this plugout. The\ - default is something silly. - port_offset: Provide a port offset to allow multiple instances of\ - communicating programs to operate on the same computer. Use an integer\ - in the inclusive range [1025 to 65500]. - port_offset_quiet: Provide a port offset to allow multiple instances of\ - communicating programs to operate on the same computer with quiet\ - output in case of issues. Use an integer in the inclusive range [1025\ - to 65500]. - port_bloc: Provide a port offset bloc for easier configuration of\ - multiple instances. PORT_OFFSET_BLOC is an integer between 0 and\ - MAX_BLOC (around 4000). - max_port_bloc: Print the current value of MAX_BLOC and exit. Stay under\ - 2000 for safety. - max_port_bloc_quiet: Print the current value of MAX_BLOC quietly and\ - exit. - num_assigned_ports: Print the number of assigned ports used by AFNI,\ - then quit. - num_assigned_ports_quiet: Print the number of assigned ports used by\ - AFNI quietly, then quit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PlugoutTtOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PLUGOUT_TT_METADATA) - cargs = [] - cargs.append("plugout_tt") - if host is not None: - cargs.extend([ - "-host", - host - ]) - if ijk_option: - cargs.append("-ijk") - if verbose: - cargs.append("-v") - if port is not None: - cargs.extend([ - "-port", - str(port) - ]) - if name is not None: - cargs.extend([ - "-name", - name - ]) - if port_offset is not None: - cargs.extend([ - "-np", - str(port_offset) - ]) - if port_offset_quiet is not None: - cargs.extend([ - "-npq", - str(port_offset_quiet) - ]) - if port_bloc is not None: - cargs.extend([ - "-npb", - str(port_bloc) - ]) - if max_port_bloc: - cargs.append("-max_port_bloc") - if max_port_bloc_quiet: - cargs.append("-max_port_bloc_quiet") - if num_assigned_ports: - cargs.append("-num_assigned_ports") - if num_assigned_ports_quiet: - cargs.append("-num_assigned_ports_quiet") - ret = PlugoutTtOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PLUGOUT_TT_METADATA", - "PlugoutTtOutputs", - "plugout_tt", -] diff --git a/python/src/niwrap/afni/plugout_tta.py b/python/src/niwrap/afni/plugout_tta.py deleted file mode 100644 index 004c7ff72..000000000 --- a/python/src/niwrap/afni/plugout_tta.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PLUGOUT_TTA_METADATA = Metadata( - id="b80e1c976f7ff785517ce071f360a3f1c30742db.boutiques", - name="plugout_tta", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PlugoutTtaOutputs(typing.NamedTuple): - """ - Output object returned when calling `plugout_tta(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def plugout_tta( - host: str | None = None, - port: int | None = None, - verbose: bool = False, - port_offset: int | None = None, - port_offset_quiet: int | None = None, - port_offset_bloc: int | None = None, - max_port_bloc: bool = False, - max_port_bloc_quiet: bool = False, - num_assigned_ports: bool = False, - num_assigned_ports_quiet: bool = False, - runner: Runner | None = None, -) -> PlugoutTtaOutputs: - """ - Connects to AFNI and receives notification whenever the user changes Talairach - coordinates, then drives Netscape to display the closest figures from the - Talairach-Tournoux atlas. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - host: Connect to AFNI running on the specified computer using TCP/IP.\ - Use '-host localhost' to connect on current host with TCP/IP. - port: Use TCP/IP port number 'pp'. Default is 8005. - verbose: Verbose mode: prints out progress reports. - port_offset: Provide a port offset to allow multiple instances of\ - programs to communicate on the same machine. All ports are assigned\ - numbers relative to PORT_OFFSET. Range: [1025, 65500]. - port_offset_quiet: Like -np, but more quiet in the face of adversity. - port_offset_bloc: Provide a port offset block. Easier to use than -np.\ - Range: [0, MAX_BLOC]. Using this reduces chances of port conflicts. - max_port_bloc: Print the current value of MAX_BLOC and exit. - max_port_bloc_quiet: Print MAX_BLOC value and exit quietly. - num_assigned_ports: Print the number of assigned ports used by AFNI\ - then quit. - num_assigned_ports_quiet: Print the number of assigned ports used by\ - AFNI then quit quietly. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PlugoutTtaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PLUGOUT_TTA_METADATA) - cargs = [] - cargs.append("plugout_tta") - if host is not None: - cargs.extend([ - "-host", - host - ]) - if port is not None: - cargs.extend([ - "-port", - str(port) - ]) - if verbose: - cargs.append("-v") - if port_offset is not None: - cargs.extend([ - "-np", - str(port_offset) - ]) - if port_offset_quiet is not None: - cargs.extend([ - "-npq", - str(port_offset_quiet) - ]) - if port_offset_bloc is not None: - cargs.extend([ - "-npb", - str(port_offset_bloc) - ]) - if max_port_bloc: - cargs.append("-max_port_bloc") - if max_port_bloc_quiet: - cargs.append("-max_port_bloc_quiet") - if num_assigned_ports: - cargs.append("-num_assigned_ports") - if num_assigned_ports_quiet: - cargs.append("-num_assigned_ports_quiet") - ret = PlugoutTtaOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PLUGOUT_TTA_METADATA", - "PlugoutTtaOutputs", - "plugout_tta", -] diff --git a/python/src/niwrap/afni/prompt_popup.py b/python/src/niwrap/afni/prompt_popup.py deleted file mode 100644 index 0a31cc416..000000000 --- a/python/src/niwrap/afni/prompt_popup.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PROMPT_POPUP_METADATA = Metadata( - id="86851443966e9bfb5766658bc6ca87fa7bd600d7.boutiques", - name="prompt_popup", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PromptPopupOutputs(typing.NamedTuple): - """ - Output object returned when calling `prompt_popup(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def prompt_popup( - message_pause: str | None = None, - buttons_b: list[str] | None = None, - timeout_to: float | None = None, - runner: Runner | None = None, -) -> PromptPopupOutputs: - """ - A command-line tool that pops up a window prompting user interaction with a - message and buttons. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - message_pause: Same as -message to match the old prompt_user. - buttons_b: Same as -button. - timeout_to: Same as -timeout TT. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PromptPopupOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PROMPT_POPUP_METADATA) - cargs = [] - cargs.append("prompt_popup") - cargs.append("-message") - if message_pause is not None: - cargs.extend([ - "-pause", - message_pause - ]) - cargs.append("-button") - if buttons_b is not None: - cargs.extend([ - "-b", - *buttons_b - ]) - cargs.append("-timeout") - if timeout_to is not None: - cargs.extend([ - "-to", - str(timeout_to) - ]) - ret = PromptPopupOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PROMPT_POPUP_METADATA", - "PromptPopupOutputs", - "prompt_popup", -] diff --git a/python/src/niwrap/afni/prompt_user.py b/python/src/niwrap/afni/prompt_user.py deleted file mode 100644 index 3ce38d97c..000000000 --- a/python/src/niwrap/afni/prompt_user.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PROMPT_USER_METADATA = Metadata( - id="782279d082f08241e6d04420d5c1a420777073d0.boutiques", - name="prompt_user", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PromptUserOutputs(typing.NamedTuple): - """ - Output object returned when calling `prompt_user(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def prompt_user( - pause_message: str, - timeout_alias: float | None = None, - runner: Runner | None = None, -) -> PromptUserOutputs: - """ - Tool that prompts a window requesting user input with a custom message. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - pause_message: Pops a window prompting the user with MESSAGE. If\ - MESSAGE is '-', it is read from stdin. - timeout_alias: Alias for -timeout. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PromptUserOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PROMPT_USER_METADATA) - cargs = [] - cargs.append("prompt_user") - cargs.extend([ - "<-pause>", - pause_message - ]) - if timeout_alias is not None: - cargs.extend([ - "-to", - str(timeout_alias) - ]) - ret = PromptUserOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PROMPT_USER_METADATA", - "PromptUserOutputs", - "prompt_user", -] diff --git a/python/src/niwrap/afni/pta.py b/python/src/niwrap/afni/pta.py deleted file mode 100644 index 2bcc1fcef..000000000 --- a/python/src/niwrap/afni/pta.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PTA_METADATA = Metadata( - id="4e961b6423dd3c4934a447dbf22ed74e7465c3df.boutiques", - name="PTA", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class PtaOutputs(typing.NamedTuple): - """ - Output object returned when calling `pta(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stat_output: OutputPathType - """Statistical evidence output of PTA""" - prediction_output: OutputPathType - """Predicted values and their standard errors""" - - -def pta( - prefix: str, - input_file: InputPathType, - model_formula: str, - vt_formulation: str | None = None, - prediction_table: InputPathType | None = None, - verbosity_level: float | None = None, - response_var: str | None = None, - dbg_args: bool = False, - runner: Runner | None = None, -) -> PtaOutputs: - """ - Program for Profile Tracking Analysis - estimates nonlinear trajectories through - smoothing splines. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output files. - input_file: Input data file in table format (data frame structure of\ - long format in R). - model_formula: Model formulation through multilevel smoothing splines. - vt_formulation: Specify varying smoothing terms. Two components are\ - required: the first one 'var' indicates the variable (e.g., subject)\ - around which the smoothing will vary while the second component\ - specifies the smoothing formulation (e.g., s(age,subject)). - prediction_table: Data table to generate predicted values for graphical\ - illustration. - verbosity_level: Verbosity level (0 for quiet, 1 or more for talkative). - response_var: Column name designated as the response/outcome variable\ - (default is 'Y'). - dbg_args: Enable R to save parameters for debugging. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PtaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PTA_METADATA) - cargs = [] - cargs.append("PTA") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - cargs.extend([ - "-model", - model_formula - ]) - if vt_formulation is not None: - cargs.extend([ - "-vt", - vt_formulation - ]) - if prediction_table is not None: - cargs.extend([ - "-prediction", - execution.input_file(prediction_table) - ]) - if verbosity_level is not None: - cargs.extend([ - "-verb", - str(verbosity_level) - ]) - if response_var is not None: - cargs.extend([ - "-Y", - response_var - ]) - if dbg_args: - cargs.append("-dbgArgs") - ret = PtaOutputs( - root=execution.output_file("."), - stat_output=execution.output_file(prefix + "-stat.txt"), - prediction_output=execution.output_file(prefix + "-prediction.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PTA_METADATA", - "PtaOutputs", - "pta", -] diff --git a/python/src/niwrap/afni/qdelaunay.py b/python/src/niwrap/afni/qdelaunay.py deleted file mode 100644 index 39571c215..000000000 --- a/python/src/niwrap/afni/qdelaunay.py +++ /dev/null @@ -1,239 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QDELAUNAY_METADATA = Metadata( - id="6ffd24be5e49d65ad58c48581dbc1c38e779c71c.boutiques", - name="qdelaunay", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QdelaunayOutputs(typing.NamedTuple): - """ - Output object returned when calling `qdelaunay(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def qdelaunay( - input_file: InputPathType, - furthest_site: bool = False, - triangulated_output: bool = False, - joggled_input: bool = False, - joggle_range: float | None = None, - search_simplex: bool = False, - point_infinity: bool = False, - delaunay_visible: str | None = None, - delaunay_regions: str | None = None, - trace_level: float | None = None, - check: bool = False, - statistics_: bool = False, - verify: bool = False, - output_stdout: bool = False, - facets_summary: float | None = None, - input_file_option: InputPathType | None = None, - output_file_option: InputPathType | None = None, - trace_point: float | None = None, - trace_merge: float | None = None, - trace_merge_width: float | None = None, - stop_point: float | None = None, - stop_cone_point: float | None = None, - centrum_radius: float | None = None, - max_angle_cosine: float | None = None, - perturb_factor: float | None = None, - min_facet_width: float | None = None, - facet_dump: bool = False, - geomview: bool = False, - vertices_incident: bool = False, - mathematica: bool = False, - off_format: bool = False, - point_coordinates: bool = False, - summary: bool = False, - runner: Runner | None = None, -) -> QdelaunayOutputs: - """ - Compute the Delaunay triangulation using Qhull. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input file containing point coordinates. - furthest_site: Compute furthest-site Delaunay triangulation. - triangulated_output: Triangulated output. - joggled_input: Joggled input instead of merged facets. - joggle_range: Randomly joggle input in range [-n,n]. - search_simplex: Search all points for the initial simplex. - point_infinity: Add point-at-infinity to Delaunay triangulation. - delaunay_visible: Print Delaunay region if visible from point n, -n if\ - not. - delaunay_regions: Print Delaunay regions that include point n, -n if\ - not. - trace_level: Trace at level n, 4=all, 5=mem/gauss, -1= events. - check: Check frequently during execution. - statistics_: Print statistics. - verify: Verify result: structure, convexity, and in-circle test. - output_stdout: Send all output to stdout. - facets_summary: Report summary when n or more facets created. - input_file_option: Input data from file, no spaces or single quotes. - output_file_option: Output results to file, may be enclosed in single\ - quotes. - trace_point: Turn on tracing when point n added to hull. - trace_merge: Turn on tracing at merge n. - trace_merge_width: Trace merge facets when width > n. - stop_point: Stop Qhull after adding point n, -n for before. - stop_cone_point: Stop Qhull after building cone for point n. - centrum_radius: Radius of centrum (roundoff added). Merge facets if\ - non-convex. - max_angle_cosine: Cosine of maximum angle. Merge facets if cosine > n\ - or non-convex. - perturb_factor: Randomly perturb computations by a factor of [1-n,1+n]. - min_facet_width: Min facet width for outside point (before roundoff). - facet_dump: Facet dump. - geomview: Geomview output. - vertices_incident: Vertices incident to each Delaunay region. - mathematica: Mathematica output (2-d only, lifted to a paraboloid). - off_format: OFF format (dim, points, and facets as a paraboloid). - point_coordinates: Point coordinates (lifted to a paraboloid). - summary: Summary (stderr). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QdelaunayOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QDELAUNAY_METADATA) - cargs = [] - cargs.append("qdelaunay") - cargs.append(execution.input_file(input_file)) - if furthest_site: - cargs.append("Qu") - if triangulated_output: - cargs.append("Qt") - if joggled_input: - cargs.append("QJ") - if joggle_range is not None: - cargs.extend([ - "QJn", - str(joggle_range) - ]) - if search_simplex: - cargs.append("Qs") - if point_infinity: - cargs.append("Qz") - if delaunay_visible is not None: - cargs.extend([ - "QGn", - delaunay_visible - ]) - if delaunay_regions is not None: - cargs.extend([ - "QVn", - delaunay_regions - ]) - if trace_level is not None: - cargs.extend([ - "T4", - str(trace_level) - ]) - if check: - cargs.append("Tc") - if statistics_: - cargs.append("Ts") - if verify: - cargs.append("Tv") - if output_stdout: - cargs.append("Tz") - if facets_summary is not None: - cargs.extend([ - "TFn", - str(facets_summary) - ]) - if input_file_option is not None: - cargs.extend([ - "TI", - execution.input_file(input_file_option) - ]) - if output_file_option is not None: - cargs.extend([ - "TO", - execution.input_file(output_file_option) - ]) - if trace_point is not None: - cargs.extend([ - "TPn", - str(trace_point) - ]) - if trace_merge is not None: - cargs.extend([ - "TMn", - str(trace_merge) - ]) - if trace_merge_width is not None: - cargs.extend([ - "TWn", - str(trace_merge_width) - ]) - if stop_point is not None: - cargs.extend([ - "TVn", - str(stop_point) - ]) - if stop_cone_point is not None: - cargs.extend([ - "TCn", - str(stop_cone_point) - ]) - if centrum_radius is not None: - cargs.extend([ - "Cn", - str(centrum_radius) - ]) - if max_angle_cosine is not None: - cargs.extend([ - "An", - str(max_angle_cosine) - ]) - if perturb_factor is not None: - cargs.extend([ - "Rn", - str(perturb_factor) - ]) - if min_facet_width is not None: - cargs.extend([ - "Wn", - str(min_facet_width) - ]) - if facet_dump: - cargs.append("f") - if geomview: - cargs.append("G") - if vertices_incident: - cargs.append("i") - if mathematica: - cargs.append("m") - if off_format: - cargs.append("o") - if point_coordinates: - cargs.append("p") - if summary: - cargs.append("s") - ret = QdelaunayOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QDELAUNAY_METADATA", - "QdelaunayOutputs", - "qdelaunay", -] diff --git a/python/src/niwrap/afni/qhull.py b/python/src/niwrap/afni/qhull.py deleted file mode 100644 index 8c908268e..000000000 --- a/python/src/niwrap/afni/qhull.py +++ /dev/null @@ -1,153 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QHULL_METADATA = Metadata( - id="c66bd98623328e49e50c28ca6d4ac9a47c26c314.boutiques", - name="qhull", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QhullOutputs(typing.NamedTuple): - """ - Output object returned when calling `qhull(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_results: OutputPathType | None - """Output file with the specified results.""" - - -def qhull( - input_coords: str, - delaunay: bool = False, - furthest_delaunay: bool = False, - voronoi: bool = False, - furthest_voronoi: bool = False, - halfspace_intersection: bool = False, - triangulated_output: bool = False, - joggled_input: bool = False, - verify: bool = False, - summary: bool = False, - vertices_incident: bool = False, - normals: bool = False, - vertex_coordinates: bool = False, - halfspace_intersections: bool = False, - extreme_points: bool = False, - total_area_volume: bool = False, - off_format: bool = False, - geomview_output: bool = False, - mathematica_output: bool = False, - print_facets: str | None = None, - output_file: InputPathType | None = None, - runner: Runner | None = None, -) -> QhullOutputs: - """ - Tool to compute convex hulls and related structures. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_coords: Dimension, number of points, and point coordinates\ - provided via stdin. - delaunay: Compute Delaunay triangulation by lifting points to a\ - paraboloid. - furthest_delaunay: Compute furthest-site Delaunay triangulation (upper\ - convex hull). - voronoi: Compute Voronoi diagram as the dual of the Delaunay\ - triangulation. - furthest_voronoi: Compute furthest-site Voronoi diagram. - halfspace_intersection: Compute halfspace intersection about\ - [1,1,0,...] via polar duality. - triangulated_output: Triangulated output. - joggled_input: Joggled input instead of merged facets. - verify: Verify result: structure, convexity, and point inclusion. - summary: Summary of results. - vertices_incident: Vertices incident to each facet. - normals: Normals with offsets. - vertex_coordinates: Vertex coordinates (if 'Qc', includes coplanar\ - points). If 'v', Voronoi vertices. - halfspace_intersections: Halfspace intersections. - extreme_points: Extreme points (convex hull vertices). - total_area_volume: Compute total area and volume. - off_format: OFF format (if 'v', outputs Voronoi regions). - geomview_output: Geomview output (2-d, 3-d and 4-d). - mathematica_output: Mathematica output (2-d and 3-d). - print_facets: Print facets that include point n, -n if not. - output_file: Output results to file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QhullOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QHULL_METADATA) - cargs = [] - cargs.append("qhull") - cargs.append(input_coords) - if delaunay: - cargs.append("d") - if furthest_delaunay: - cargs.append("d Qu") - if voronoi: - cargs.append("v") - if furthest_voronoi: - cargs.append("v Qu") - if halfspace_intersection: - cargs.append("H1,1") - if triangulated_output: - cargs.append("Qt") - if joggled_input: - cargs.append("QJ") - if verify: - cargs.append("Tv") - if summary: - cargs.append("s") - if vertices_incident: - cargs.append("i") - if normals: - cargs.append("n") - if vertex_coordinates: - cargs.append("p") - if halfspace_intersections: - cargs.append("Fp") - if extreme_points: - cargs.append("Fx") - if total_area_volume: - cargs.append("FA") - if off_format: - cargs.append("o") - if geomview_output: - cargs.append("G") - if mathematica_output: - cargs.append("m") - if print_facets is not None: - cargs.extend([ - "QVn", - print_facets - ]) - if output_file is not None: - cargs.extend([ - "TO", - execution.input_file(output_file) - ]) - ret = QhullOutputs( - root=execution.output_file("."), - output_results=execution.output_file(pathlib.Path(output_file).name + ".txt") if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QHULL_METADATA", - "QhullOutputs", - "qhull", -] diff --git a/python/src/niwrap/afni/quick_alpha_vals_py.py b/python/src/niwrap/afni/quick_alpha_vals_py.py deleted file mode 100644 index 5993f1266..000000000 --- a/python/src/niwrap/afni/quick_alpha_vals_py.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QUICK_ALPHA_VALS_PY_METADATA = Metadata( - id="467c10597885378ee65e5261792a6d6f5203efb5.boutiques", - name="quick.alpha.vals.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QuickAlphaValsPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `quick_alpha_vals_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - alpha_table: OutputPathType - """Generated alpha table file""" - - -def quick_alpha_vals_py( - max_file: InputPathType, - niter: int | None = None, - runner: Runner | None = None, -) -> QuickAlphaValsPyOutputs: - """ - Generate an alpha table from slow_surf_clustsim.py results. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - max_file: File containing maximum z values. - niter: Number of iterations that should be in the z file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QuickAlphaValsPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QUICK_ALPHA_VALS_PY_METADATA) - cargs = [] - cargs.append("quick.alpha.vals.py") - if niter is not None: - cargs.extend([ - "-niter", - str(niter) - ]) - cargs.append(execution.input_file(max_file)) - ret = QuickAlphaValsPyOutputs( - root=execution.output_file("."), - alpha_table=execution.output_file("alpha_table.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QUICK_ALPHA_VALS_PY_METADATA", - "QuickAlphaValsPyOutputs", - "quick_alpha_vals_py", -] diff --git a/python/src/niwrap/afni/quickspec.py b/python/src/niwrap/afni/quickspec.py deleted file mode 100644 index 2695d33b3..000000000 --- a/python/src/niwrap/afni/quickspec.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QUICKSPEC_METADATA = Metadata( - id="0a985ab38a04ef53341c98e04d446660dcd3c0c6.boutiques", - name="quickspec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QuickspecOutputs(typing.NamedTuple): - """ - Output object returned when calling `quickspec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_specfile: OutputPathType | None - """The spec file output.""" - - -def quickspec( - tn: list[str], - tsn: list[str], - tsnad: list[str] | None = None, - tsnadm: list[str] | None = None, - tsnadl: list[str] | None = None, - spec: str | None = None, - help_: bool = False, - runner: Runner | None = None, -) -> QuickspecOutputs: - """ - A quick and dirty way of loading a surface into SUMA or command line programs - using a spec file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tn: Specify surface type and name. - tsn: Specify surface type, state, and name. - tsnad: Specify surface type, state, name, anatomical correctness, and\ - Local Domain Parent. - tsnadm: Specify surface type, state, name, anatomical correctness,\ - Local Domain Parent, and node marker file. - tsnadl: Specify surface type, state, name, anatomical correctness,\ - Local Domain Parent, and label dataset file. - spec: Name of spec file output. Default is quick.spec. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QuickspecOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QUICKSPEC_METADATA) - cargs = [] - cargs.append("quickspec") - cargs.extend([ - "-tn", - *tn - ]) - cargs.extend([ - "-tsn", - *tsn - ]) - if tsnad is not None: - cargs.extend([ - "-tsnad", - *tsnad - ]) - if tsnadm is not None: - cargs.extend([ - "-tsnadm", - *tsnadm - ]) - if tsnadl is not None: - cargs.extend([ - "-tsnadl", - *tsnadl - ]) - if spec is not None: - cargs.extend([ - "-spec", - spec - ]) - if help_: - cargs.append("-h") - ret = QuickspecOutputs( - root=execution.output_file("."), - out_specfile=execution.output_file(spec) if (spec is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QUICKSPEC_METADATA", - "QuickspecOutputs", - "quickspec", -] diff --git a/python/src/niwrap/afni/quickspec_sl.py b/python/src/niwrap/afni/quickspec_sl.py deleted file mode 100644 index 00c24940d..000000000 --- a/python/src/niwrap/afni/quickspec_sl.py +++ /dev/null @@ -1,120 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QUICKSPEC_SL_METADATA = Metadata( - id="889040e44332ca29004fb5b3b94e878babda4bd4.boutiques", - name="quickspecSL", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QuickspecSlOutputs(typing.NamedTuple): - """ - Output object returned when calling `quickspec_sl(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_spec_file: OutputPathType | None - """Output spec file""" - - -def quickspec_sl( - surf_a: InputPathType, - surf_b: InputPathType, - surf_intermed_pref: str | None = None, - infl_surf_a: InputPathType | None = None, - infl_surf_b: InputPathType | None = None, - infl_surf_intermed_pref: str | None = None, - both_lr_flag: bool = False, - out_spec: str | None = None, - runner: Runner | None = None, -) -> QuickspecSlOutputs: - """ - This program makes a *.spec file after a set of intermediate surfaces have been - generated with SurfLayers. It can also make a *.spec file that relates inflated - surfaces to anatomically-correct surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surf_a: Inner (anatomically-correct) boundary surface dataset (e.g.\ - smoothwm.gii). - surf_b: Outer (anatomically-correct) boundary surface dataset (e.g.\ - pial.gii). - surf_intermed_pref: Prefix for (anatomically-correct) intermediate\ - surfaces, typically output by SurfLayers (default: isurf). - infl_surf_a: Inner (inflated) boundary surface dataset (e.g.\ - infl.smoothwm.gii). - infl_surf_b: Outer (inflated) boundary surface dataset (e.g.\ - infl.pial.gii). - infl_surf_intermed_pref: Prefix for (inflated) intermediate surfaces,\ - typically output by SurfLayers (default: infl.isurf). - both_lr_flag: Specify an output spec for both hemispheres if surfaces\ - for both exist. - out_spec: Name for output *.spec file (default: newspec.spec). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QuickspecSlOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QUICKSPEC_SL_METADATA) - cargs = [] - cargs.append("quickspecSL") - cargs.append("-surf_A") - cargs.append(execution.input_file(surf_a)) - cargs.append("-surf_B") - cargs.append(execution.input_file(surf_b)) - cargs.append("-surf_intermed_pref") - if surf_intermed_pref is not None: - cargs.extend([ - "-surf_intermed_pref", - surf_intermed_pref - ]) - cargs.append("-infl_surf_A") - if infl_surf_a is not None: - cargs.extend([ - "-infl_surf_A", - execution.input_file(infl_surf_a) - ]) - cargs.append("-infl_surf_B") - if infl_surf_b is not None: - cargs.extend([ - "-infl_surf_B", - execution.input_file(infl_surf_b) - ]) - cargs.append("-infl_surf_intermed_pref") - if infl_surf_intermed_pref is not None: - cargs.extend([ - "-infl_surf_intermed_pref", - infl_surf_intermed_pref - ]) - cargs.append("-both_lr") - if both_lr_flag: - cargs.append("-both_lr") - cargs.append("-out_spec") - if out_spec is not None: - cargs.extend([ - "-out_spec", - out_spec - ]) - ret = QuickspecSlOutputs( - root=execution.output_file("."), - output_spec_file=execution.output_file(out_spec) if (out_spec is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QUICKSPEC_SL_METADATA", - "QuickspecSlOutputs", - "quickspec_sl", -] diff --git a/python/src/niwrap/afni/quotize.py b/python/src/niwrap/afni/quotize.py deleted file mode 100644 index 79750706f..000000000 --- a/python/src/niwrap/afni/quotize.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -QUOTIZE_METADATA = Metadata( - id="ad50821aafd97f95bcd0363a536ab23ce971bcff.boutiques", - name="quotize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class QuotizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `quotize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - array_output: OutputPathType - """Generated C array of strings file""" - - -def quotize( - name: str, - input_file: InputPathType, - output_file: InputPathType, - runner: Runner | None = None, -) -> QuotizeOutputs: - """ - Turns a text file into a C array of strings initialized into an array 'char - *name[]'. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - name: The name to be used for the array of strings. - input_file: Input text file to be converted. - output_file: Output file which will contain the C array of strings. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `QuotizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(QUOTIZE_METADATA) - cargs = [] - cargs.append("quotize") - cargs.append(name) - cargs.append("<") - cargs.append(execution.input_file(input_file)) - cargs.append(">") - cargs.append(execution.input_file(output_file)) - ret = QuotizeOutputs( - root=execution.output_file("."), - array_output=execution.output_file(pathlib.Path(output_file).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "QUOTIZE_METADATA", - "QuotizeOutputs", - "quotize", -] diff --git a/python/src/niwrap/afni/r_pkgs_install.py b/python/src/niwrap/afni/r_pkgs_install.py deleted file mode 100644 index db522aabb..000000000 --- a/python/src/niwrap/afni/r_pkgs_install.py +++ /dev/null @@ -1,87 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -R_PKGS_INSTALL_METADATA = Metadata( - id="2bb05babb0a5ddfa993973f35b1e4cabcb308e30.boutiques", - name="rPkgsInstall", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RPkgsInstallOutputs(typing.NamedTuple): - """ - Output object returned when calling `r_pkgs_install(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_packages: OutputPathType - """Output R packages after installation, update, or removal""" - - -def r_pkgs_install( - packages: str, - download_site: str | None = None, - check: bool = False, - update_: bool = False, - remove: bool = False, - runner: Runner | None = None, -) -> RPkgsInstallOutputs: - """ - A tool for installing, checking, updating, or removing R packages for AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - packages: List of R packages to install, update, or remove. Use 'ALL'\ - to refer to all AFNI-required packages. - download_site: Specify the package repository website. Default is\ - 'http://cloud.r-project.org'. - check: Verify whether the specified R packages are installed on the\ - computer without installing/updating/removing them. - update_: Update the specified R packages. If packages are not\ - installed, they will be installed. - remove: Remove the specified R packages from the system. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RPkgsInstallOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(R_PKGS_INSTALL_METADATA) - cargs = [] - cargs.append("rPkgsInstall") - cargs.extend([ - "-pkgs", - packages - ]) - if download_site is not None: - cargs.extend([ - "-site", - download_site - ]) - if check: - cargs.append("-check") - if update_: - cargs.append("-update") - if remove: - cargs.append("-remove") - ret = RPkgsInstallOutputs( - root=execution.output_file("."), - output_packages=execution.output_file(packages), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RPkgsInstallOutputs", - "R_PKGS_INSTALL_METADATA", - "r_pkgs_install", -] diff --git a/python/src/niwrap/afni/rba.py b/python/src/niwrap/afni/rba.py deleted file mode 100644 index 36cd30884..000000000 --- a/python/src/niwrap/afni/rba.py +++ /dev/null @@ -1,240 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RBA_METADATA = Metadata( - id="e398b3a57e7258897bfc2032d62fb4854a2e607c.boutiques", - name="RBA", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RbaOutputs(typing.NamedTuple): - """ - Output object returned when calling `rba(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_txt: OutputPathType - """Main output text file with inference information for effects of - interest.""" - output_rdata: OutputPathType - """Saved R data in binary format for post hoc processing.""" - - -def rba( - prefix: str, - data_table: InputPathType, - chains: float | None = None, - iterations: float | None = None, - model: str | None = None, - eoi: str | None = None, - wcp: float | None = None, - tstat: str | None = None, - stdz: str | None = None, - c_vars: str | None = None, - q_vars: str | None = None, - dist_roi: str | None = None, - dist_subj: str | None = None, - dist_y: str | None = None, - ridge_plot: str | None = None, - roi: str | None = None, - subj: str | None = None, - scale: float | None = None, - se: str | None = None, - pdp: str | None = None, - mean: str | None = None, - sigma: str | None = None, - debug: bool = False, - verbose: float | None = None, - md: bool = False, - r2z: bool = False, - runner: Runner | None = None, -) -> RbaOutputs: - """ - Region-Based Analysis Program through Bayesian Multilevel Modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output file names. - data_table: Data table in pure text format. - chains: Specify the number of Markov chains. - iterations: Specify the number of iterations per Markov chain. - model: Specify the model formula. - eoi: Identify effects of interest in the output. - wcp: Invoke within-chain parallelization. - tstat: Specify the column name that lists the t-statistic values. - stdz: Identify quantitative variables (or covariates) to be\ - standardized. - c_vars: Identify categorical (qualitative) variables (or factors). - q_vars: Identify quantitative variables (or covariates). - dist_roi: Specify the distribution for the ROIs. - dist_subj: Specify the distribution for the subjects. - dist_y: Specify the distribution for the response variable. - ridge_plot: Plot the posterior distributions stacked together. - roi: Specify the column name that is designated as the region variable. - subj: Specify the column name that is designated as the measuring unit\ - variable (usually subject). - scale: Specify a multiplier for the Y values. - se: This option indicates that standard error for the response variable\ - is available as input. - pdp: Specify the layout of posterior distribution plot. - mean: Specify the formulation for the mean of the likelihood (sampling\ - distribution). - sigma: Specify the formulation for the standard deviation (sigma) of\ - the likelihood (sampling distribution). - debug: This option will enable R to save the parameters in a file for\ - debugging. - verbose: Specify verbose level. - md: This option indicates that there are missing data in the input. - r2z: Perform Fisher transformation on the response variable if it is a\ - correlation coefficient. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RbaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RBA_METADATA) - cargs = [] - cargs.append("RBA") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-dataTable", - execution.input_file(data_table) - ]) - if chains is not None: - cargs.extend([ - "-chains", - str(chains) - ]) - if iterations is not None: - cargs.extend([ - "-iterations", - str(iterations) - ]) - if model is not None: - cargs.extend([ - "-model", - model - ]) - if eoi is not None: - cargs.extend([ - "-EOI", - eoi - ]) - if wcp is not None: - cargs.extend([ - "-WCP", - str(wcp) - ]) - if tstat is not None: - cargs.extend([ - "-tstat", - tstat - ]) - if stdz is not None: - cargs.extend([ - "-stdz", - stdz - ]) - if c_vars is not None: - cargs.extend([ - "-cVars", - c_vars - ]) - if q_vars is not None: - cargs.extend([ - "-qVars", - q_vars - ]) - if dist_roi is not None: - cargs.extend([ - "-distROI", - dist_roi - ]) - if dist_subj is not None: - cargs.extend([ - "-distSubj", - dist_subj - ]) - if dist_y is not None: - cargs.extend([ - "-distY", - dist_y - ]) - if ridge_plot is not None: - cargs.extend([ - "-ridgePlot", - ridge_plot - ]) - if roi is not None: - cargs.extend([ - "-ROI", - roi - ]) - if subj is not None: - cargs.extend([ - "-Subj", - subj - ]) - if scale is not None: - cargs.extend([ - "-scale", - str(scale) - ]) - if se is not None: - cargs.extend([ - "-se", - se - ]) - if pdp is not None: - cargs.extend([ - "-PDP", - pdp - ]) - if mean is not None: - cargs.extend([ - "-mean", - mean - ]) - if sigma is not None: - cargs.extend([ - "-sigma", - sigma - ]) - if debug: - cargs.append("-dbgArgs") - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - if md: - cargs.append("-MD") - if r2z: - cargs.append("-r2z") - ret = RbaOutputs( - root=execution.output_file("."), - output_txt=execution.output_file(prefix + ".txt"), - output_rdata=execution.output_file(prefix + ".RData"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RBA_METADATA", - "RbaOutputs", - "rba", -] diff --git a/python/src/niwrap/afni/rbox.py b/python/src/niwrap/afni/rbox.py deleted file mode 100644 index 344836f2e..000000000 --- a/python/src/niwrap/afni/rbox.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RBOX_METADATA = Metadata( - id="80319d4648d635c07c7e3bce7e954e3b8fe64128.boutiques", - name="rbox", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RboxOutputs(typing.NamedTuple): - """ - Output object returned when calling `rbox(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def rbox( - number_points: str, - dimension: str | None = None, - integer_coordinates: bool = False, - bounding_box: float | None = None, - offset: float | None = None, - user_seed: float | None = None, - mesh_lattice: list[str] | None = None, - runner: Runner | None = None, -) -> RboxOutputs: - """ - Generate various point distributions. Default is random in cube. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - number_points: Number of random points in cube, lens, spiral, sphere or\ - grid. - dimension: Dimension (e.g., D3 for 3-d). - integer_coordinates: Print integer coordinates, default 'Bn' is 1e+06. - bounding_box: Bounding box coordinates, default 0.5. - offset: Offset coordinates by n. - user_seed: Use n as the random number seed. - mesh_lattice: Lattice (Mesh) rotated by [n,-m,0], [m,n,0], [0,0,r], ... - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RboxOutputs`). - """ - if mesh_lattice is not None and not (3 <= len(mesh_lattice)): - raise ValueError(f"Length of 'mesh_lattice' must be greater than 3 but was {len(mesh_lattice)}") - runner = runner or get_global_runner() - execution = runner.start_execution(RBOX_METADATA) - cargs = [] - cargs.append("rbox") - cargs.append(number_points) - if dimension is not None: - cargs.append(dimension) - if integer_coordinates: - cargs.append("z") - if bounding_box is not None: - cargs.extend([ - "B", - str(bounding_box) - ]) - if offset is not None: - cargs.extend([ - "O", - str(offset) - ]) - if user_seed is not None: - cargs.extend([ - "t", - str(user_seed) - ]) - if mesh_lattice is not None: - cargs.extend([ - "M", - *mesh_lattice - ]) - ret = RboxOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RBOX_METADATA", - "RboxOutputs", - "rbox", -] diff --git a/python/src/niwrap/afni/read_matlab_files_py.py b/python/src/niwrap/afni/read_matlab_files_py.py deleted file mode 100644 index 4cb709c1f..000000000 --- a/python/src/niwrap/afni/read_matlab_files_py.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -READ_MATLAB_FILES_PY_METADATA = Metadata( - id="228461aad9e4f1abdf8c4f6cdf4dda42da06fc96.boutiques", - name="read_matlab_files.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ReadMatlabFilesPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `read_matlab_files_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - converted_1d_file: OutputPathType | None - """Converted 1D format file""" - - -def read_matlab_files_py( - infiles: list[str], - prefix: str | None = None, - overwrite: bool = False, - help_: bool = False, - history: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> ReadMatlabFilesPyOutputs: - """ - Describe or convert MATLAB files (.mat) to 1D format. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infiles: Input MATLAB files to be processed. - prefix: Prefix for output file names. - overwrite: Overwrite any existing output files. - help_: Show help message. - history: Show revision history. - version: Show version number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ReadMatlabFilesPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(READ_MATLAB_FILES_PY_METADATA) - cargs = [] - cargs.append("read_matlab_files.py") - cargs.extend(infiles) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if overwrite: - cargs.append("-overwrite") - if help_: - cargs.append("-help") - if history: - cargs.append("-hist") - if version: - cargs.append("-ver") - ret = ReadMatlabFilesPyOutputs( - root=execution.output_file("."), - converted_1d_file=execution.output_file(prefix + ".[INDEX].[KEY].1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "READ_MATLAB_FILES_PY_METADATA", - "ReadMatlabFilesPyOutputs", - "read_matlab_files_py", -] diff --git a/python/src/niwrap/afni/realtime_receiver.py b/python/src/niwrap/afni/realtime_receiver.py deleted file mode 100644 index 28f2885ce..000000000 --- a/python/src/niwrap/afni/realtime_receiver.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -REALTIME_RECEIVER_METADATA = Metadata( - id="2c28c3cc99310e4f83462fd252818743c9fb534c.boutiques", - name="realtime_receiver", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RealtimeReceiverOutputs(typing.NamedTuple): - """ - Output object returned when calling `realtime_receiver(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def realtime_receiver( - show_data: typing.Literal["yes", "no"] | None = None, - write_text_data: str | None = None, - data_choice: typing.Literal["motion", "motion_norm", "all_extras", "diff_ratio"] | None = None, - serial_port: str | None = None, - show_demo_gui: typing.Literal["yes", "no"] | None = None, - dc_params: list[float] | None = None, - extras_on_one_line: typing.Literal["yes", "no"] | None = None, - show_comm_times: bool = False, - show_demo_data: bool = False, - swap: bool = False, - tcp_port: float | None = None, - verbosity: float | None = None, - runner: Runner | None = None, -) -> RealtimeReceiverOutputs: - """ - Program to receive and display real-time plugin data from AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - show_data: Display incoming data in terminal window. - write_text_data: Write data to text file. - data_choice: Pick which data to send as feedback. - serial_port: Specify serial port file for feedback data. - show_demo_gui: Demonstrate a feedback GUI. - dc_params: Set data_choice parameters, e.g. for diff_ratio, params P1\ - P2. - extras_on_one_line: Show 'extras' on one line only. - show_comm_times: Display communication times. - show_demo_data: Display feedback data in terminal window. - swap: Swap bytes of incoming data. - tcp_port: Specify TCP port for incoming connections. - verbosity: Set the verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RealtimeReceiverOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(REALTIME_RECEIVER_METADATA) - cargs = [] - cargs.append("realtime_receiver.py") - if show_data is not None: - cargs.extend([ - "-show_data", - show_data - ]) - if write_text_data is not None: - cargs.extend([ - "-write_text_data", - write_text_data - ]) - if data_choice is not None: - cargs.extend([ - "-data_choice", - data_choice - ]) - if serial_port is not None: - cargs.extend([ - "-serial_port", - serial_port - ]) - if show_demo_gui is not None: - cargs.extend([ - "-show_demo_gui", - show_demo_gui - ]) - if dc_params is not None: - cargs.extend([ - "-dc_params", - *map(str, dc_params) - ]) - if extras_on_one_line is not None: - cargs.extend([ - "-extras_on_one_line", - extras_on_one_line - ]) - if show_comm_times: - cargs.append("-show_comm_times") - if show_demo_data: - cargs.append("-show_demo_data") - if swap: - cargs.append("-swap") - if tcp_port is not None: - cargs.extend([ - "-tcp_port", - str(tcp_port) - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = RealtimeReceiverOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "REALTIME_RECEIVER_METADATA", - "RealtimeReceiverOutputs", - "realtime_receiver", -] diff --git a/python/src/niwrap/afni/retro_ts_py.py b/python/src/niwrap/afni/retro_ts_py.py deleted file mode 100644 index d529e8eec..000000000 --- a/python/src/niwrap/afni/retro_ts_py.py +++ /dev/null @@ -1,217 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RETRO_TS_PY_METADATA = Metadata( - id="82462d0527ae23d487ce3dd58f42754940326375.boutiques", - name="RetroTS.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RetroTsPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `retro_ts_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output file containing respiratory and cardiac regressors""" - - -def retro_ts_py( - num_slices: float, - volume_tr: float, - resp_file: InputPathType | None = None, - card_file: InputPathType | None = None, - phys_fs: float | None = None, - phys_file: InputPathType | None = None, - phys_json: InputPathType | None = None, - prefix: str | None = None, - rvt_shifts: str | None = None, - rvt_out: bool = False, - resp_cutoff_freq: float | None = None, - cardiac_cutoff_freq: float | None = None, - cardiac_out: bool = False, - respiration_out: bool = False, - interp_style: str | None = None, - fir_order: float | None = None, - quiet: bool = False, - demo: bool = False, - show_graphs: bool = False, - debug: bool = False, - slice_offset: str | None = None, - slice_major: float | None = None, - slice_order: str | None = None, - zero_phase_offset: bool = False, - legacy_transform: float | None = None, - runner: Runner | None = None, -) -> RetroTsPyOutputs: - """ - Creates slice-based regressors for regressing out components of heart rate, - respiration, and respiration volume per time using independent data files or - BIDS formatted files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - num_slices: Number of slices. - volume_tr: Volume TR in seconds. - resp_file: Respiration data file. - card_file: Cardiac data file. - phys_fs: Physiological signal sampling frequency in Hz. - phys_file: BIDS formatted physio file in tab-separated format, can be\ - gzipped. - phys_json: BIDS formatted physio metadata json file. If not specified,\ - the json corresponding to the phys_file will be loaded. - prefix: Prefix of output file. - rvt_shifts: Vector of shifts in seconds of RVT signal. (default is\ - [0:5:20]). - rvt_out: Flag for writing RVT regressors (default is 1). - resp_cutoff_freq: Cut-off frequency in Hz for respiratory lowpass\ - filter (default 3 Hz). - cardiac_cutoff_freq: Cut-off frequency in Hz for cardiac lowpass filter\ - (default 3 Hz). - cardiac_out: Flag for writing Cardiac regressors (default is 1). - respiration_out: Flag for writing Respiratory regressors (default is 1). - interp_style: Resampling kernel (default is 'linear'). - fir_order: Order of FIR filter (default is 40). - quiet: Show talkative progress as the program runs (default is 1). - demo: Run demonstration of RetroTS (default is 0). - show_graphs: Show graphs (default is unset; set with any parameter to\ - view). - debug: Drop into pdb upon an exception (default is False). - slice_offset: Vector of slice acquisition time offsets in seconds\ - (default is equivalent of alt+z). - slice_major: Unknown parameter (default is 1). - slice_order: Slice timing information in seconds. (default is alt+z). - zero_phase_offset: Zero phase offset flag. - legacy_transform: Specify the version of the original Matlab code's\ - transformation (default is 0). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RetroTsPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RETRO_TS_PY_METADATA) - cargs = [] - cargs.append("RetroTS.py") - if resp_file is not None: - cargs.extend([ - "-r", - execution.input_file(resp_file) - ]) - if card_file is not None: - cargs.extend([ - "-c", - execution.input_file(card_file) - ]) - if phys_fs is not None: - cargs.extend([ - "-p", - str(phys_fs) - ]) - cargs.extend([ - "-n", - str(num_slices) - ]) - cargs.extend([ - "-v", - str(volume_tr) - ]) - if phys_file is not None: - cargs.extend([ - "-phys_file", - execution.input_file(phys_file) - ]) - if phys_json is not None: - cargs.extend([ - "-phys_json", - execution.input_file(phys_json) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if rvt_shifts is not None: - cargs.extend([ - "-rvt_shifts", - rvt_shifts - ]) - if rvt_out: - cargs.append("-rvt_out") - if resp_cutoff_freq is not None: - cargs.extend([ - "-respiration_cutoff_frequency", - str(resp_cutoff_freq) - ]) - if cardiac_cutoff_freq is not None: - cargs.extend([ - "-cardiac_cutoff_frequency", - str(cardiac_cutoff_freq) - ]) - if cardiac_out: - cargs.append("-cardiac_out") - if respiration_out: - cargs.append("-respiration_out") - if interp_style is not None: - cargs.extend([ - "-interpolation_style", - interp_style - ]) - if fir_order is not None: - cargs.extend([ - "-fir_order", - str(fir_order) - ]) - if quiet: - cargs.append("-quiet") - if demo: - cargs.append("-demo") - if show_graphs: - cargs.append("-show_graphs") - if debug: - cargs.append("-debug") - if slice_offset is not None: - cargs.extend([ - "-slice_offset", - slice_offset - ]) - if slice_major is not None: - cargs.extend([ - "-slice_major", - str(slice_major) - ]) - if slice_order is not None: - cargs.extend([ - "-slice_order", - slice_order - ]) - if zero_phase_offset: - cargs.append("-zero_phase_offset") - if legacy_transform is not None: - cargs.extend([ - "-legacy_transform", - str(legacy_transform) - ]) - ret = RetroTsPyOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".slibase.1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RETRO_TS_PY_METADATA", - "RetroTsPyOutputs", - "retro_ts_py", -] diff --git a/python/src/niwrap/afni/rmz.py b/python/src/niwrap/afni/rmz.py deleted file mode 100644 index f6340b894..000000000 --- a/python/src/niwrap/afni/rmz.py +++ /dev/null @@ -1,73 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RMZ_METADATA = Metadata( - id="aa236a73a237e5aa1c1315e0d74d586b582f45f0.boutiques", - name="rmz", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RmzOutputs(typing.NamedTuple): - """ - Output object returned when calling `rmz(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def rmz( - filenames: list[InputPathType], - quiet: bool = False, - hash_flag: float | None = None, - keep_flag: bool = False, - runner: Runner | None = None, -) -> RmzOutputs: - """ - Zeros out files before removing them. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - filenames: Files to zero out and remove. - quiet: Quiet mode. - hash_flag: Number of times to zero out the files. - keep_flag: Keep the files instead of removing them. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RmzOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RMZ_METADATA) - cargs = [] - cargs.append("rmz") - if quiet: - cargs.append("-q") - if hash_flag is not None: - cargs.extend([ - "-#", - str(hash_flag) - ]) - if keep_flag: - cargs.append("-k") - cargs.extend([execution.input_file(f) for f in filenames]) - ret = RmzOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RMZ_METADATA", - "RmzOutputs", - "rmz", -] diff --git a/python/src/niwrap/afni/roi2dataset.py b/python/src/niwrap/afni/roi2dataset.py deleted file mode 100644 index 520f9e6cf..000000000 --- a/python/src/niwrap/afni/roi2dataset.py +++ /dev/null @@ -1,128 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ROI2DATASET_METADATA = Metadata( - id="c994458c150bdc96a6edfd6a62cc84bbf9e38f61.boutiques", - name="ROI2dataset", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Roi2datasetOutputs(typing.NamedTuple): - """ - Output object returned when calling `roi2dataset(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def roi2dataset( - prefix: str, - input_rois: list[InputPathType], - keep_separate: bool = False, - nodelist: str | None = None, - nodelist_nodups: str | None = None, - nodelist_with_roival: bool = False, - label_dset: str | None = None, - output_format: str | None = None, - domain_parent_id: str | None = None, - pad_to_node: float | None = None, - pad_label: float | None = None, - runner: Runner | None = None, -) -> Roi2datasetOutputs: - """ - Transforms a series of ROI files to a node dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix of output dataset. - input_rois: ROI files to turn into a data set (space-separated list).\ - This parameter MUST be the last one on command line. - keep_separate: Output one column (sub-brick) for each ROI value. - nodelist: Prefix for a set of .1D files that contain a list of node\ - indices in the order they appear in an ROI. - nodelist_nodups: Prefix for a set of .1D files that contain a list of\ - node indices in the order they appear in an ROI, with duplicate nodes\ - removed. - nodelist_with_roival: Also add the ROI value as a second column in .1D\ - files output by -nodelist. - label_dset: Write a label dataset instead of a simple dataset. Sets\ - output format to NIML. - output_format: Output format of dataset. One of: ni_bi, ni_as, 1D. - domain_parent_id: Idcode of domain parent. Only ROIs with the same\ - domain parent are included in the output. - pad_to_node: Output a full dataset from node 0 to node max_index (total\ - of max_index + 1 nodes). - pad_label: Use padding_label (an integer) to label nodes not part of\ - any ROI. Default is 0. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Roi2datasetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ROI2DATASET_METADATA) - cargs = [] - cargs.append("ROI2dataset") - cargs.append("-prefix") - cargs.append(prefix) - cargs.extend([execution.input_file(f) for f in input_rois]) - if keep_separate: - cargs.append("-keep_separate") - if nodelist is not None: - cargs.extend([ - "-nodelist", - nodelist - ]) - if nodelist_nodups is not None: - cargs.extend([ - "-nodelist.nodups", - nodelist_nodups - ]) - if nodelist_with_roival: - cargs.append("-nodelist_with_ROIval") - if label_dset is not None: - cargs.extend([ - "-label_dset", - label_dset - ]) - if output_format is not None: - cargs.extend([ - "-of", - output_format - ]) - if domain_parent_id is not None: - cargs.extend([ - "-dom_par_id", - domain_parent_id - ]) - if pad_to_node is not None: - cargs.extend([ - "-pad_to_node", - str(pad_to_node) - ]) - if pad_label is not None: - cargs.extend([ - "-pad_label", - str(pad_label) - ]) - ret = Roi2datasetOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ROI2DATASET_METADATA", - "Roi2datasetOutputs", - "roi2dataset", -] diff --git a/python/src/niwrap/afni/roigrow.py b/python/src/niwrap/afni/roigrow.py deleted file mode 100644 index 3a84b793f..000000000 --- a/python/src/niwrap/afni/roigrow.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ROIGROW_METADATA = Metadata( - id="e86b42392e60416adb9d12f0b2877f5c053d5768.boutiques", - name="ROIgrow", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RoigrowOutputs(typing.NamedTuple): - """ - Output object returned when calling `roigrow(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """1D output dataset.""" - - -def roigrow( - input_surface: str, - roi_labels: str, - lim_distance: float, - output_prefix: str | None = None, - full_list: bool = False, - grow_from_edge: bool = False, - insphere_diameter: float | None = None, - inbox_edges: list[float] | None = None, - runner: Runner | None = None, -) -> RoigrowOutputs: - """ - A program to expand an ROI on the surface. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_surface: Specify input surface. You can also use -t* and -spec\ - and -surf methods to input surfaces. - roi_labels: Data column containing integer labels of ROIs. Each integer\ - label gets grown separately. - lim_distance: Distance to cover from each node. The units of LIM are\ - those of the surface's node coordinates. Distances are calculated along\ - the surface's mesh. - output_prefix: Prefix of 1D output dataset. Default is ROIgrow. - full_list: Output a row for each node on the surface. Nodes not in the\ - grown ROI, receive a 0 for a label. This option is ONLY for use with\ - -roi_labels. - grow_from_edge: Grow ROIs from their edges rather than the brute force\ - default. This might make the program faster on large ROIs and large\ - surfaces. - insphere_diameter: Diameter of the sphere inside which nodes are added\ - instead of growing along the surface. - inbox_edges: Use a box of edge widths E1, E2, E3 instead of DIA. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RoigrowOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ROIGROW_METADATA) - cargs = [] - cargs.append("ROIgrow") - cargs.extend([ - "-i_TYPE", - input_surface - ]) - cargs.extend([ - "-roi_labels", - roi_labels - ]) - cargs.extend([ - "-lim", - str(lim_distance) - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if full_list: - cargs.append("-full_list") - if grow_from_edge: - cargs.append("-grow_from_edge") - if insphere_diameter is not None: - cargs.extend([ - "-insphere", - str(insphere_diameter) - ]) - if inbox_edges is not None: - cargs.extend([ - "-inbox", - *map(str, inbox_edges) - ]) - ret = RoigrowOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + ".1D") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ROIGROW_METADATA", - "RoigrowOutputs", - "roigrow", -] diff --git a/python/src/niwrap/afni/rotcom.py b/python/src/niwrap/afni/rotcom.py deleted file mode 100644 index d9a285b70..000000000 --- a/python/src/niwrap/afni/rotcom.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ROTCOM_METADATA = Metadata( - id="65366e1283781ddcf84d07b0c61d20c1cdbf07ba.boutiques", - name="rotcom", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RotcomOutputs(typing.NamedTuple): - """ - Output object returned when calling `rotcom(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout: OutputPathType - """The 4x3 transformation matrix+vector output""" - - -def rotcom( - rotate_ashift: str, - dataset: InputPathType | None = None, - runner: Runner | None = None, -) -> RotcomOutputs: - """ - Prints to stdout the 4x3 transformation matrix+vector that would be applied by - 3drotate to the given dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - rotate_ashift: Combination of rotate and ashift options in a single\ - quoted string (e.g., '-rotate 10I 0R 0A -ashift 5S 0 0'). - dataset: Input dataset for determining coordinate order. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RotcomOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ROTCOM_METADATA) - cargs = [] - cargs.append("rotcom") - cargs.append(rotate_ashift) - if dataset is not None: - cargs.append(execution.input_file(dataset)) - ret = RotcomOutputs( - root=execution.output_file("."), - stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ROTCOM_METADATA", - "RotcomOutputs", - "rotcom", -] diff --git a/python/src/niwrap/afni/rsfgen.py b/python/src/niwrap/afni/rsfgen.py deleted file mode 100644 index ecaa5c754..000000000 --- a/python/src/niwrap/afni/rsfgen.py +++ /dev/null @@ -1,143 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RSFGEN_METADATA = Metadata( - id="42de4c95300ddfa6a27f2ddbc5b6d9dc63cdd292.boutiques", - name="RSFgen", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RsfgenOutputs(typing.NamedTuple): - """ - Output object returned when calling `rsfgen(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType | None - """Output .1D stimulus function files prefixed with the provided output - prefix.""" - - -def rsfgen( - length: int, - num_experimental_conditions: int, - block_length: str | None = None, - random_seed: float | None = None, - suppress_output_flag: bool = False, - single_file_flag: bool = False, - single_column_flag: bool = False, - output_prefix: str | None = None, - num_reps: str | None = None, - permutation_seed: float | None = None, - markov_file: InputPathType | None = None, - prob_zero: float | None = None, - input_table: InputPathType | None = None, - runner: Runner | None = None, -) -> RsfgenOutputs: - """ - Program to generate random stimulus functions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - length: Length of time series. - num_experimental_conditions: Number of input stimuli (experimental\ - conditions). - block_length: Block length for stimulus. Must specify stimulus index\ - and length. Example: -nblock 1 5. - random_seed: Random number seed. - suppress_output_flag: Flag to suppress screen output. - single_file_flag: Place stimulus functions into a single .1D file. - single_column_flag: Write stimulus functions as a single column of\ - decimal integers. - output_prefix: Prefix for output .1D stimulus functions. - num_reps: Number of repetitions for stimulus. - permutation_seed: Stim label permutation random number seed. - markov_file: File containing the transition probability matrix. - prob_zero: Probability of a zero (i.e., null) state (default: 0). - input_table: Filename of column or table of numbers. All other input\ - options (except -seed and -prefix) are ignored with this option. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RsfgenOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RSFGEN_METADATA) - cargs = [] - cargs.append("RSFgen") - cargs.extend([ - "-nt", - str(length) - ]) - cargs.extend([ - "-num_stimts", - str(num_experimental_conditions) - ]) - if block_length is not None: - cargs.extend([ - "-nblock", - block_length - ]) - if random_seed is not None: - cargs.extend([ - "-seed", - str(random_seed) - ]) - if suppress_output_flag: - cargs.append("-quiet") - if single_file_flag: - cargs.append("-one_file") - if single_column_flag: - cargs.append("-one_col") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if num_reps is not None: - cargs.extend([ - "-nreps", - num_reps - ]) - if permutation_seed is not None: - cargs.extend([ - "-pseed", - str(permutation_seed) - ]) - if markov_file is not None: - cargs.extend([ - "-markov", - execution.input_file(markov_file) - ]) - if prob_zero is not None: - cargs.extend([ - "-pzero", - str(prob_zero) - ]) - if input_table is not None: - cargs.extend([ - "-table", - execution.input_file(input_table) - ]) - ret = RsfgenOutputs( - root=execution.output_file("."), - output_files=execution.output_file(output_prefix + "1.1D") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RSFGEN_METADATA", - "RsfgenOutputs", - "rsfgen", -] diff --git a/python/src/niwrap/afni/rtfeedme.py b/python/src/niwrap/afni/rtfeedme.py deleted file mode 100644 index 93c893f21..000000000 --- a/python/src/niwrap/afni/rtfeedme.py +++ /dev/null @@ -1,128 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RTFEEDME_METADATA = Metadata( - id="32964e0c08bfc25e6c4f6eca5347bfc95b91dd98.boutiques", - name="rtfeedme", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class RtfeedmeOutputs(typing.NamedTuple): - """ - Output object returned when calling `rtfeedme(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def rtfeedme( - datasets: list[InputPathType], - host: str | None = None, - interval_ms: float | None = None, - send_3d: bool = False, - buffer_mb: float | None = None, - verbose: bool = False, - swap_bytes: bool = False, - nz_fake: float | None = None, - drive_cmd: list[str] | None = None, - note: list[str] | None = None, - yrange: float | None = None, - runner: Runner | None = None, -) -> RtfeedmeOutputs: - """ - Test the real-time plugin by sending all the bricks in 'dataset' to AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: List of datasets to send to AFNI, specified as paths to\ - dataset files. Multiple datasets can be specified. - host: Send data via TCP/IP to AFNI running on the specified computer\ - system 'sname'. Default is the current system using shared memory. Use\ - 'localhost' to send on the current system using TCP/IP. - interval_ms: Inter-transmit interval in milliseconds. Default is to\ - send data as fast as possible. - send_3d: Send data in 3D bricks. Default is 2D slices. - buffer_mb: Set the interprocess communications buffer size in megabytes\ - when using shared memory. Has no effect if using TCP/IP. Default is 1\ - MB; if set to 0, a 50 KB buffer is used. - verbose: Be talkative about actions. - swap_bytes: Swap byte pairs before sending data. - nz_fake: Send 'nz' as the value of nzz for debugging purposes. - drive_cmd: Send 'cmd' as a DRIVE_AFNI command. If 'cmd' contains\ - spaces, it must be quoted. Multiple -drive options can be used. - note: Send 'sss' as a NOTE to the realtime plugin. Multiple -note\ - options can be used. - yrange: Send value 'v' as the y-range for realtime motion estimation\ - graphing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RtfeedmeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RTFEEDME_METADATA) - cargs = [] - cargs.append("rtfeedme") - cargs.extend([execution.input_file(f) for f in datasets]) - if host is not None: - cargs.extend([ - "-host", - host - ]) - if interval_ms is not None: - cargs.extend([ - "-dt", - str(interval_ms) - ]) - if send_3d: - cargs.append("-3D") - if buffer_mb is not None: - cargs.extend([ - "-buf", - str(buffer_mb) - ]) - if verbose: - cargs.append("-verbose") - if swap_bytes: - cargs.append("-swap2") - if nz_fake is not None: - cargs.extend([ - "-nzfake", - str(nz_fake) - ]) - if drive_cmd is not None: - cargs.extend([ - "-drive", - *drive_cmd - ]) - if note is not None: - cargs.extend([ - "-note", - *note - ]) - if yrange is not None: - cargs.extend([ - "-gyr", - str(yrange) - ]) - ret = RtfeedmeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RTFEEDME_METADATA", - "RtfeedmeOutputs", - "rtfeedme", -] diff --git a/python/src/niwrap/afni/samp_bias.py b/python/src/niwrap/afni/samp_bias.py deleted file mode 100644 index 21a6c92ab..000000000 --- a/python/src/niwrap/afni/samp_bias.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SAMP_BIAS_METADATA = Metadata( - id="1bc09ad1dce154d1fd68f57703b503d806026a9f.boutiques", - name="SampBias", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SampBiasOutputs(typing.NamedTuple): - """ - Output object returned when calling `samp_bias(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_1_d: OutputPathType - """Output results in .1D format""" - out_prefix: OutputPathType | None - """Output results in a proper surface-based dataset.""" - - -def samp_bias( - specfile: InputPathType, - surfname: str, - outfile: str, - plimit: float | None = None, - dlimit: float | None = None, - prefix: str | None = None, - runner: Runner | None = None, -) -> SampBiasOutputs: - """ - SampBias is a tool for sampling bias resultant segments between paired nodes on - anatomical surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - specfile: Spec file containing input surfaces. - surfname: Name of input surface. - outfile: Output results in .1D format. - plimit: Maximum length of path along surface in mm. Default is 50 mm. - dlimit: Maximum length of euclidean distance in mm. Default is 1000 mm. - prefix: Output results into a proper surface-based dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SampBiasOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SAMP_BIAS_METADATA) - cargs = [] - cargs.append("SampBias") - cargs.extend([ - "-spec", - execution.input_file(specfile) - ]) - cargs.extend([ - "-surf", - surfname - ]) - if plimit is not None: - cargs.extend([ - "-plimit", - str(plimit) - ]) - if dlimit is not None: - cargs.extend([ - "-dlimit", - str(dlimit) - ]) - cargs.extend([ - "-out", - outfile - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = SampBiasOutputs( - root=execution.output_file("."), - out_1_d=execution.output_file(outfile + ".1D"), - out_prefix=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SAMP_BIAS_METADATA", - "SampBiasOutputs", - "samp_bias", -] diff --git a/python/src/niwrap/afni/scale_to_map.py b/python/src/niwrap/afni/scale_to_map.py deleted file mode 100644 index 956190365..000000000 --- a/python/src/niwrap/afni/scale_to_map.py +++ /dev/null @@ -1,208 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SCALE_TO_MAP_METADATA = Metadata( - id="7269958c24dcc82fa2e2dff154a02b583fd43e93.boutiques", - name="ScaleToMap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class ScaleToMapOutputs(typing.NamedTuple): - """ - Output object returned when calling `scale_to_map(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def scale_to_map( - input_file: InputPathType, - icol: float, - vcol: float, - cmap: str | None = None, - cmapfile: InputPathType | None = None, - cmapdb: InputPathType | None = None, - frf: bool = False, - clp: list[float] | None = None, - perc_clp: list[float] | None = None, - apr: float | None = None, - anr: float | None = None, - interp: bool = False, - nointerp: bool = False, - direct: bool = False, - msk_zero: bool = False, - msk: list[float] | None = None, - msk_col: list[float] | None = None, - nomsk_col: bool = False, - br: float | None = None, - help_: bool = False, - verbose: bool = False, - showmap: bool = False, - showdb: bool = False, - novolreg: bool = False, - noxform: bool = False, - setenv: str | None = None, - trace_: bool = False, - trace_2: bool = False, - nomall: bool = False, - yesmall: bool = False, - runner: Runner | None = None, -) -> ScaleToMapOutputs: - """ - Tool to scale values to a color map. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input file in 1D formatted ascii containing node values. - icol: Index of node index column (-1 if node index is implicit). - vcol: Index of node value column. - cmap: Choose one of the standard colormaps available with SUMA. - cmapfile: Read color map from a Mapfile. - cmapdb: Read color maps from an AFNI .pal file. - frf: Indicate that the first row in the file is the first color. - clp: Clip values in IntVect to specified range. - perc_clp: Percentile clip values in IntVect to specified range. - apr: Clip values in IntVect to [0 range]. - anr: Clip values in IntVect to [-range range]. - interp: Use color interpolation between colors in colormap (default). - nointerp: Turn off color interpolation within the colormap. - direct: Directly map values to index of color in colormap. - msk_zero: Mask values that are 0. - msk: Mask values in vcol between specified range. - msk_col: Set color of masked voxels. - nomsk_col: Do not output nodes that got masked. - br: Apply a brightness factor to colormap and mask color. - help_: Display help message. - verbose: Verbose mode. - showmap: Print colormap to screen and quit. - showdb: Print colors and colormaps of AFNI along with any loaded from\ - Palfile. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - noxform: Same as -novolreg. - setenv: Set environment variable ENVname to ENVvalue. Quotes are\ - necessary. - trace_: Turn on extreme tracing. - trace_2: Turn on extreme tracing. - nomall: Turn off memory tracing. - yesmall: Turn on memory tracing (default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ScaleToMapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SCALE_TO_MAP_METADATA) - cargs = [] - cargs.append("ScaleToMap") - cargs.append(execution.input_file(input_file)) - cargs.append(str(icol)) - cargs.append(str(vcol)) - if cmap is not None: - cargs.extend([ - "-cmap", - cmap - ]) - if cmapfile is not None: - cargs.extend([ - "-cmapfile", - execution.input_file(cmapfile) - ]) - if cmapdb is not None: - cargs.extend([ - "-cmapdb", - execution.input_file(cmapdb) - ]) - if frf: - cargs.append("-frf") - if clp is not None: - cargs.extend([ - "-clp", - *map(str, clp) - ]) - if perc_clp is not None: - cargs.extend([ - "-perc_clp", - *map(str, perc_clp) - ]) - if apr is not None: - cargs.extend([ - "-apr", - str(apr) - ]) - if anr is not None: - cargs.extend([ - "-anr", - str(anr) - ]) - if interp: - cargs.append("-interp") - if nointerp: - cargs.append("-nointerp") - if direct: - cargs.append("-direct") - if msk_zero: - cargs.append("-msk_zero") - if msk is not None: - cargs.extend([ - "-msk", - *map(str, msk) - ]) - if msk_col is not None: - cargs.extend([ - "-msk_col", - *map(str, msk_col) - ]) - if nomsk_col: - cargs.append("-nomsk_col") - if br is not None: - cargs.extend([ - "-br", - str(br) - ]) - if help_: - cargs.append("-h") - if verbose: - cargs.append("-verb") - if showmap: - cargs.append("-showmap") - if showdb: - cargs.append("-showdb") - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if setenv is not None: - cargs.extend([ - "-setenv", - setenv - ]) - if trace_: - cargs.append("-TRACE") - if trace_2: - cargs.append("-TRACE") - if nomall: - cargs.append("-nomall") - if yesmall: - cargs.append("-yesmall") - ret = ScaleToMapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SCALE_TO_MAP_METADATA", - "ScaleToMapOutputs", - "scale_to_map", -] diff --git a/python/src/niwrap/afni/serial_helper.py b/python/src/niwrap/afni/serial_helper.py deleted file mode 100644 index 3bbfa5d62..000000000 --- a/python/src/niwrap/afni/serial_helper.py +++ /dev/null @@ -1,123 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SERIAL_HELPER_METADATA = Metadata( - id="4df7ea7f38a6767c1aba72a89599b9e5c022108c.boutiques", - name="serial_helper", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SerialHelperOutputs(typing.NamedTuple): - """ - Output object returned when calling `serial_helper(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def serial_helper( - serial_port: str, - sock_num: float | None = None, - mp_max: float | None = None, - mp_min: float | None = None, - num_extra: float | None = None, - disp_all: float | None = None, - debug: float | None = None, - show_times: bool = False, - help_: bool = False, - hist: bool = False, - no_serial: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> SerialHelperOutputs: - """ - Passes motion parameters from socket to serial port. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - serial_port: Output serial port filename. - sock_num: Specify socket number to serve. - mp_max: Limit the maximum value of the MP data. - mp_min: Limit the minimum value of the MP data. - num_extra: Receive additional floats per TR. - disp_all: Receive NVOX*8 extra floats per TR. - debug: Set the debugging level (0-3). - show_times: Show communication times. - help_: Display this help information. - hist: Show the module history. - no_serial: Turn off serial port output. - version: Show the current version number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SerialHelperOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SERIAL_HELPER_METADATA) - cargs = [] - cargs.append("serial_helper") - cargs.extend([ - "-serial_port", - serial_port - ]) - if sock_num is not None: - cargs.extend([ - "-sock_num", - str(sock_num) - ]) - if mp_max is not None: - cargs.extend([ - "-mp_max", - str(mp_max) - ]) - if mp_min is not None: - cargs.extend([ - "-mp_min", - str(mp_min) - ]) - if num_extra is not None: - cargs.extend([ - "-num_extra", - str(num_extra) - ]) - if disp_all is not None: - cargs.extend([ - "-disp_all", - str(disp_all) - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if show_times: - cargs.append("-show_times") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if no_serial: - cargs.append("-no_serial") - if version: - cargs.append("-version") - ret = SerialHelperOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SERIAL_HELPER_METADATA", - "SerialHelperOutputs", - "serial_helper", -] diff --git a/python/src/niwrap/afni/sfim.py b/python/src/niwrap/afni/sfim.py deleted file mode 100644 index 5b1b3787e..000000000 --- a/python/src/niwrap/afni/sfim.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SFIM_METADATA = Metadata( - id="860745fb4f5f8d4a5b2deb3bf7f0e0fff5352b56.boutiques", - name="sfim", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SfimOutputs(typing.NamedTuple): - """ - Output object returned when calling `sfim(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType | None - """Output image file for interval 'i' with task state name.""" - - -def sfim( - sfint_file: str | None = None, - baseline_state: str | None = None, - local_base_option: bool = False, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> SfimOutputs: - """ - Stepwise Functional IMages. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - sfint_file: Filename which contains the interval definitions. Default\ - is 'sfint'. Example: '3*# 5*rest 4*A 5*rest 4*B 5*rest 4*A 5*rest'. - baseline_state: Task state name to use as the baseline. Default is\ - 'rest'. - local_base_option: Flag to indicate if each non-base task state\ - interval should have the mean of the two nearest base intervals\ - subtracted instead of the grand mean of all the base task intervals. - output_prefix: Prefix for output image filenames for all states. The\ - i'th interval with task state name 'fred' will be written to file\ - 'pname.fred.i'. Default is 'sfim'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SfimOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SFIM_METADATA) - cargs = [] - cargs.append("sfim") - if sfint_file is not None: - cargs.extend([ - "-sfint", - sfint_file - ]) - if baseline_state is not None: - cargs.extend([ - "-base", - baseline_state - ]) - if local_base_option: - cargs.append("-localbase") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - cargs.append("[INPUT_FILES...]") - ret = SfimOutputs( - root=execution.output_file("."), - output_files=execution.output_file(output_prefix + ".*.i") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SFIM_METADATA", - "SfimOutputs", - "sfim", -] diff --git a/python/src/niwrap/afni/slow_surf_clustsim_py.py b/python/src/niwrap/afni/slow_surf_clustsim_py.py deleted file mode 100644 index 7e2776d1a..000000000 --- a/python/src/niwrap/afni/slow_surf_clustsim_py.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SLOW_SURF_CLUSTSIM_PY_METADATA = Metadata( - id="d0f65569329873ee3b5d627e2e983fb33e8b87f3.boutiques", - name="slow_surf_clustsim.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SlowSurfClustsimPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `slow_surf_clustsim_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def slow_surf_clustsim_py( - on_surface: str | None = None, - save_script: str | None = None, - print_script: bool = False, - uvar: list[str] | None = None, - verbosity: float | None = None, - help_: bool = False, - hist: bool = False, - show_default_cvars: bool = False, - show_default_uvars: bool = False, - show_valid_opts: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> SlowSurfClustsimPyOutputs: - """ - Generate a tcsh script to run clustsim on surface. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - on_surface: Start from noise on the surface (so no volume data is\ - involved). - save_script: Save script to given file. - print_script: Print script to terminal. - uvar: Set the user variable (use -show_default_uvars to see user vars).\ - Example usage: -uvar spec_file sb23_lh_141_std.spec -uvar surf_vol\ - sb23_SurfVol_aligned+orig. - verbosity: Set the verbosity level. - help_: Show this help. - hist: Show module history. - show_default_cvars: List default control variables. - show_default_uvars: List default user variables. - show_valid_opts: List valid options. - version: Show current version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SlowSurfClustsimPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SLOW_SURF_CLUSTSIM_PY_METADATA) - cargs = [] - cargs.append("slow_surf_clustsim.py") - if on_surface is not None: - cargs.extend([ - "-on_surface", - on_surface - ]) - if save_script is not None: - cargs.extend([ - "-save_script", - save_script - ]) - if print_script: - cargs.append("-print_script") - if uvar is not None: - cargs.extend([ - "-uvar", - *uvar - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if show_default_cvars: - cargs.append("-show_default_cvars") - if show_default_uvars: - cargs.append("-show_default_uvars") - if show_valid_opts: - cargs.append("-show_valid_opts") - if version: - cargs.append("-ver") - ret = SlowSurfClustsimPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SLOW_SURF_CLUSTSIM_PY_METADATA", - "SlowSurfClustsimPyOutputs", - "slow_surf_clustsim_py", -] diff --git a/python/src/niwrap/afni/spharm_deco.py b/python/src/niwrap/afni/spharm_deco.py deleted file mode 100644 index 247efe994..000000000 --- a/python/src/niwrap/afni/spharm_deco.py +++ /dev/null @@ -1,95 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SPHARM_DECO_METADATA = Metadata( - id="6d15519a5c1313333c559fb924ae8964f9b076e5.boutiques", - name="SpharmDeco", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SpharmDecoOutputs(typing.NamedTuple): - """ - Output object returned when calling `spharm_deco(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - harmonics_file: OutputPathType - """File for harmonics of each order l.""" - beta_coefficients: OutputPathType - """Beta coefficients for each data column.""" - reconstructed_data: OutputPathType - """Reconstructed data or surface files named based on PREFIX.""" - - -def spharm_deco( - debug: float | None = None, - sigma: float | None = None, - runner: Runner | None = None, -) -> SpharmDecoOutputs: - """ - Spherical Harmonics Decomposition of a surface's coordinates or data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - debug: Debug levels (1-3). - sigma: Smoothing parameter (0 .. 0.001) which weighs down the\ - contribution of higher order harmonics. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SpharmDecoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SPHARM_DECO_METADATA) - cargs = [] - cargs.append("SpharmDeco") - cargs.append("[<-i_TYPE") - cargs.append("S>]") - cargs.append("[<-unit_sph") - cargs.append("UNIT_SPH_LABEL>]") - cargs.append("[<-l") - cargs.append("L>]") - cargs.append("[<-i_TYPE") - cargs.append("SD>]") - cargs.append("[<-data") - cargs.append("D>]") - cargs.append("[-bases_prefix") - cargs.append("BASES]") - cargs.append("[-prefix") - cargs.append("PREFIX]") - cargs.append("[-o_TYPE") - cargs.append("SDR]") - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if sigma is not None: - cargs.extend([ - "-sigma", - str(sigma) - ]) - ret = SpharmDecoOutputs( - root=execution.output_file("."), - harmonics_file=execution.output_file("BASES_PREFIX.sph*.1D"), - beta_coefficients=execution.output_file("PREFIX.beta.col*.1D.dset"), - reconstructed_data=execution.output_file("_reconstructed"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SPHARM_DECO_METADATA", - "SpharmDecoOutputs", - "spharm_deco", -] diff --git a/python/src/niwrap/afni/spharm_reco.py b/python/src/niwrap/afni/spharm_reco.py deleted file mode 100644 index 78aff58f6..000000000 --- a/python/src/niwrap/afni/spharm_reco.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SPHARM_RECO_METADATA = Metadata( - id="e4694e60cf190079bd5bcd5ea95b7f710798b83c.boutiques", - name="SpharmReco", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SpharmRecoOutputs(typing.NamedTuple): - """ - Output object returned when calling `spharm_reco(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def spharm_reco( - input_surface: str, - decomposition_order: float, - bases_prefix: str, - coefficients: list[InputPathType], - output_prefix: str | None = None, - output_surface: list[str] | None = None, - debug: float | None = None, - smoothing: float | None = None, - runner: Runner | None = None, -) -> SpharmRecoOutputs: - """ - Spherical Harmonics Reconstruction from a set of harmonics and their - corresponding coefficients. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_surface: Surface that provides the topology of the mesh (nodes'\ - connections). TYPE specifies the input surface type. - decomposition_order: Decomposition order. - bases_prefix: Prefix of files containing the bases functions (spherical\ - harmonics). These files are generated with SpharmDeco. - coefficients: Coefficients files used to recompose data columns.\ - Multiple coefficient files can be specified by repeating the option. - output_prefix: Write out the reconstructed data into dataset PREFIX.\ - The output contains N columns; one for each COEF file. - output_surface: Write out a new surface with reconstructed coordinates.\ - Requires N to be a multiple of 3. - debug: Debug levels (1-3). - smoothing: Smoothing parameter (0 .. 0.001) weighing the contribution\ - of higher order harmonics. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SpharmRecoOutputs`). - """ - if not (1 <= len(coefficients)): - raise ValueError(f"Length of 'coefficients' must be greater than 1 but was {len(coefficients)}") - if smoothing is not None and not (0 <= smoothing <= 0.001): - raise ValueError(f"'smoothing' must be between 0 <= x <= 0.001 but was {smoothing}") - runner = runner or get_global_runner() - execution = runner.start_execution(SPHARM_RECO_METADATA) - cargs = [] - cargs.append("SpharmReco") - cargs.extend([ - "-i_TYPE", - input_surface - ]) - cargs.extend([ - "-l", - str(decomposition_order) - ]) - cargs.extend([ - "-bases_prefix", - bases_prefix - ]) - cargs.extend([ - "-coef", - *[execution.input_file(f) for f in coefficients] - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if output_surface is not None: - cargs.extend([ - "-o_TYPE", - *output_surface - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if smoothing is not None: - cargs.extend([ - "-sigma", - str(smoothing) - ]) - ret = SpharmRecoOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SPHARM_RECO_METADATA", - "SpharmRecoOutputs", - "spharm_reco", -] diff --git a/python/src/niwrap/afni/stimband.py b/python/src/niwrap/afni/stimband.py deleted file mode 100644 index e9c697f23..000000000 --- a/python/src/niwrap/afni/stimband.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -STIMBAND_METADATA = Metadata( - id="464e80031a1b4a970344b72621a7160776336ad8.boutiques", - name="stimband", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class StimbandOutputs(typing.NamedTuple): - """ - Output object returned when calling `stimband(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_band: OutputPathType - """The frequency band covering at least 90% of the power of the stimulus - columns.""" - - -def stimband( - verbose_flag: bool = False, - min_freq: float | None = None, - min_bwidth: float | None = None, - min_pow: float | None = None, - runner: Runner | None = None, -) -> StimbandOutputs: - """ - Determines frequency band covering at least 90% of the 'power' (|FFT|^2) of - stimulus columns from X.nocensor.xmat.1D files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - verbose_flag: Print the power band for each individual stimulus column\ - from each matrix. - min_freq: Set the minimum frequency output for the band. Default value\ - is 0.01. - min_bwidth: Set the minimum bandwidth output (top frequency minus\ - bottom frequency). Default is 0.03. - min_pow: Set the minimum power fraction (percentage) to 'ff' instead of\ - the default 90%. Value must be in the range 50..99. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `StimbandOutputs`). - """ - if min_pow is not None and not (50 <= min_pow <= 99): - raise ValueError(f"'min_pow' must be between 50 <= x <= 99 but was {min_pow}") - runner = runner or get_global_runner() - execution = runner.start_execution(STIMBAND_METADATA) - cargs = [] - cargs.append("stimband") - if verbose_flag: - cargs.append("-verb") - cargs.append("[MATRIXFILES...]") - cargs.append("[ADDITIONAL_MATRIXFILES...]") - if min_freq is not None: - cargs.extend([ - "-min_freq", - str(min_freq) - ]) - if min_bwidth is not None: - cargs.extend([ - "-min_bwidth", - str(min_bwidth) - ]) - if min_pow is not None: - cargs.extend([ - "-min_pow", - str(min_pow) - ]) - ret = StimbandOutputs( - root=execution.output_file("."), - output_band=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "STIMBAND_METADATA", - "StimbandOutputs", - "stimband", -] diff --git a/python/src/niwrap/afni/strblast.py b/python/src/niwrap/afni/strblast.py deleted file mode 100644 index 60357ee57..000000000 --- a/python/src/niwrap/afni/strblast.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -STRBLAST_METADATA = Metadata( - id="a2cee2c629b430408b17d4c3a5b48c6d60070e17.boutiques", - name="strblast", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class StrblastOutputs(typing.NamedTuple): - """ - Output object returned when calling `strblast(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def strblast( - targetstring: str, - input_files: list[InputPathType], - new_char: str | None = None, - new_string: str | None = None, - unescape: bool = False, - quiet: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> StrblastOutputs: - """ - Finds exact copies of the target string in each of the input files, and replaces - all characters with some junk string. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - targetstring: Target string to search for in the input files. - input_files: Input files to search for the target string. - new_char: Replace TARGETSTRING with CHAR (repeated). - new_string: Replace TARGETSTRING with STRING. - unescape: Parse TARGETSTRING for escaped characters (includes '\\t',\ - '\\n', '\\r'). - quiet: Do not report files with no strings found. Use -quiet -quiet to\ - avoid any reporting. - help_: Show help message and exit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `StrblastOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(STRBLAST_METADATA) - cargs = [] - cargs.append("strblast") - cargs.append(targetstring) - cargs.extend([execution.input_file(f) for f in input_files]) - if new_char is not None: - cargs.extend([ - "-new_char", - new_char - ]) - if new_string is not None: - cargs.extend([ - "-new_string", - new_string - ]) - if unescape: - cargs.append("-unescape") - if quiet: - cargs.append("-quiet") - if help_: - cargs.append("-help") - ret = StrblastOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "STRBLAST_METADATA", - "StrblastOutputs", - "strblast", -] diff --git a/python/src/niwrap/afni/suma_change_spec.py b/python/src/niwrap/afni/suma_change_spec.py deleted file mode 100644 index 1daaf4c89..000000000 --- a/python/src/niwrap/afni/suma_change_spec.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SUMA_CHANGE_SPEC_METADATA = Metadata( - id="4bf222ffae950010f81275acc0be3c92fdd2d01c.boutiques", - name="suma_change_spec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SumaChangeSpecOutputs(typing.NamedTuple): - """ - Output object returned when calling `suma_change_spec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_spec: OutputPathType | None - """New Spec file""" - backup_spec: OutputPathType - """Backup of the original Spec file""" - - -def suma_change_spec( - input_: InputPathType, - state: str, - domainparent: str | None = None, - output: str | None = None, - remove: bool = False, - anatomical: bool = False, - runner: Runner | None = None, -) -> SumaChangeSpecOutputs: - """ - This program changes SUMA's surface specification (Spec) files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: SUMA Spec file to change. - state: State within the Spec file to change. - domainparent: New Domain Parent for the state within the Spec file. - output: Name to which the new Spec file will be temporarily written. - remove: Remove the automatically created backup. - anatomical: Add 'Anatomical = Y' to the selected SurfaceState. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SumaChangeSpecOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SUMA_CHANGE_SPEC_METADATA) - cargs = [] - cargs.append("suma_change_spec") - cargs.append(execution.input_file(input_)) - cargs.append(state) - if domainparent is not None: - cargs.append(domainparent) - if output is not None: - cargs.append(output) - if remove: - cargs.append("-remove") - if anatomical: - cargs.append("-anatomical") - ret = SumaChangeSpecOutputs( - root=execution.output_file("."), - output_spec=execution.output_file(output) if (output is not None) else None, - backup_spec=execution.output_file(pathlib.Path(input_).name + ".bkp"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SUMA_CHANGE_SPEC_METADATA", - "SumaChangeSpecOutputs", - "suma_change_spec", -] diff --git a/python/src/niwrap/afni/suma_glxdino.py b/python/src/niwrap/afni/suma_glxdino.py deleted file mode 100644 index b108567c8..000000000 --- a/python/src/niwrap/afni/suma_glxdino.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SUMA_GLXDINO_METADATA = Metadata( - id="ecd47b551f3a043c06c9cdcc9b01baa6d371a1b0.boutiques", - name="SUMA_glxdino", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SumaGlxdinoOutputs(typing.NamedTuple): - """ - Output object returned when calling `suma_glxdino(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def suma_glxdino( - verbose: bool = False, - runner: Runner | None = None, -) -> SumaGlxdinoOutputs: - """ - A simple openGL test program using GLX. If it does not run, then SUMA certainly - won't. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - verbose: Switch on diagnostic messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SumaGlxdinoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SUMA_GLXDINO_METADATA) - cargs = [] - cargs.append("SUMA_glxdino") - if verbose: - cargs.append("-v") - ret = SumaGlxdinoOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SUMA_GLXDINO_METADATA", - "SumaGlxdinoOutputs", - "suma_glxdino", -] diff --git a/python/src/niwrap/afni/surf2_vol_coord.py b/python/src/niwrap/afni/surf2_vol_coord.py deleted file mode 100644 index b44bbea4e..000000000 --- a/python/src/niwrap/afni/surf2_vol_coord.py +++ /dev/null @@ -1,132 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF2_VOL_COORD_METADATA = Metadata( - id="10021b8805c4eb1593a3c873a3dc81eb8ed6a6d1.boutiques", - name="Surf2VolCoord", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class Surf2VolCoordOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf2_vol_coord(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - results_file: OutputPathType - """Output results file.""" - - -def surf2_vol_coord( - surface: str, - grid_vol: InputPathType, - closest_nodes: InputPathType, - prefix: str, - grid_subbrick: float | None = None, - sv: InputPathType | None = None, - one_node: str | None = None, - qual: str | None = None, - lpi: bool = False, - rai: bool = False, - verb_level: float | None = None, - runner: Runner | None = None, -) -> Surf2VolCoordOutputs: - """ - Relates node indices to coordinates given x y z coordinates and returns the - nodes closest to them. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Specify input surface. - grid_vol: Specifies the grid for the output volume. - closest_nodes: A coordinate file specifying coordinates for which the\ - closest nodes will be found. - prefix: Output results to file PREFIX (will overwrite). Default is\ - stdout. - grid_subbrick: Sub-brick from which data are taken. - sv: Surface Volume file aligning with the surface. - one_node: Specify a single node's coordinates. - qual: A string of characters that qualify the surface in which the\ - closest node was found. - lpi: Coordinate axis direction for values in XYZ.1D are in LPI. - rai: Coordinate axis direction for values in XYZ.1D are in RAI\ - (default). - verb_level: Verbosity level, default is 0. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `Surf2VolCoordOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF2_VOL_COORD_METADATA) - cargs = [] - cargs.append("Surf2VolCoord") - cargs.append("-i_TYPE") - cargs.extend([ - "-i_TYPE", - surface - ]) - cargs.append("-grid_parent") - cargs.extend([ - "-grid_parent", - execution.input_file(grid_vol) - ]) - if grid_subbrick is not None: - cargs.extend([ - "-grid_subbrick", - str(grid_subbrick) - ]) - if sv is not None: - cargs.extend([ - "-sv", - execution.input_file(sv) - ]) - if one_node is not None: - cargs.extend([ - "-one_node", - one_node - ]) - cargs.extend([ - "-closest_nodes", - execution.input_file(closest_nodes) - ]) - if qual is not None: - cargs.extend([ - "-qual", - qual - ]) - if lpi: - cargs.append("-LPI") - if rai: - cargs.append("-RAI") - if verb_level is not None: - cargs.extend([ - "-verb", - str(verb_level) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - ret = Surf2VolCoordOutputs( - root=execution.output_file("."), - results_file=execution.output_file(prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF2_VOL_COORD_METADATA", - "Surf2VolCoordOutputs", - "surf2_vol_coord", -] diff --git a/python/src/niwrap/afni/surf_clust.py b/python/src/niwrap/afni/surf_clust.py deleted file mode 100644 index 9d345c557..000000000 --- a/python/src/niwrap/afni/surf_clust.py +++ /dev/null @@ -1,281 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_CLUST_METADATA = Metadata( - id="2346425eb197f04f33322dea847636dd74a3b8a3.boutiques", - name="SurfClust", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfClustOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_clust(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - cluster_table: OutputPathType | None - """Cluster table output""" - clustered_dataset: OutputPathType | None - """Clustered version of input dataset""" - roi_dataset: OutputPathType | None - """ROI dataset with rank of clusters""" - - -def surf_clust( - input_dataset: list[InputPathType], - rmm: float, - specfile: InputPathType | None = None, - input_surface: str | None = None, - input_surf_name: InputPathType | None = None, - amm2: float | None = None, - min_nodes: float | None = None, - prefix: str | None = None, - out_clusterdset: bool = False, - out_roidset: bool = False, - out_fulllist: bool = False, - sort_none: bool = False, - sort_n_nodes: bool = False, - sort_area: bool = False, - thresh_col: float | None = None, - thresh: float | None = None, - athresh: float | None = None, - ir_range: list[float] | None = None, - ex_range: list[float] | None = None, - prepend_node_index: bool = False, - update_: float | None = None, - no_cent: bool = False, - cent: bool = False, - novolreg: bool = False, - noxform: bool = False, - set_env: str | None = None, - trace_: bool = False, - trace_extreme: bool = False, - no_memory_trace: bool = False, - yes_memory_trace: bool = False, - mini_help: bool = False, - help_: bool = False, - extreme_help: bool = False, - view_help: bool = False, - web_help: bool = False, - find_help: str | None = None, - raw_help: bool = False, - spx_help: bool = False, - aspx_help: bool = False, - runner: Runner | None = None, -) -> SurfClustOutputs: - """ - A program to perform clustering analysis surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: The input dataset and the index of the datacolumn to use\ - (index 0 for 1st column). Values of 0 indicate inactive nodes. - rmm: Maximum distance between an activated node and the cluster to\ - which it belongs. - specfile: The surface spec file. - input_surface: The input surface name. - input_surf_name: Full name of the input surface. - amm2: Minimum area for clusters. - min_nodes: Minimum nodes for clusters. - prefix: Prefix for output. Default is the prefix of the input dataset. - out_clusterdset: Output a clustered version of input dataset. - out_roidset: Output an ROI dataset with the rank of its cluster. - out_fulllist: Output a value for all nodes of input surface. - sort_none: No sorting of ROI clusters. - sort_n_nodes: Sorting based on number of nodes in cluster. - sort_area: Sorting based on area of clusters (default). - thresh_col: Index of thresholding column. Default is column 0. - thresh: Apply thresholding prior to clustering. - athresh: Apply absolute thresholding prior to clustering. - ir_range: Apply thresholding in range. A node n is considered if\ - thresh_col[n] >= R0 && thresh_col[n] <= R1. - ex_range: Apply thresholding outside of range. A node n is considered\ - if thresh_col[n] < R0 || thresh_col[n] > R1. - prepend_node_index: Force the output dataset to have node indices in\ - column 0 of output. - update_: Pacify me when perc of the data have been processed. perc is\ - between 1% and 50%. Default is no update. - no_cent: Do not find the central nodes. - cent: Do find the central nodes (default). - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - noxform: Same as -novolreg. - set_env: Set environment variable ENVname to be ENVvalue. Quotes are\ - necessary. - trace_: Turns on In/Out debug and Memory tracing. - trace_extreme: Turns on extreme tracing. - no_memory_trace: Turn off memory tracing. - yes_memory_trace: Turn on memory tracing (default). - mini_help: Mini help, same as -help in many cases. - help_: The entire help output. - extreme_help: Extreme help, same as -help in majority of cases. - view_help: Open help in text editor. AFNI will try to find a GUI editor\ - on your machine. You can control which it should use by setting\ - environment variable AFNI_GUI_EDITOR. - web_help: Open help in web browser. AFNI will try to find a browser.\ - You can control which it should use by setting environment variable\ - AFNI_GUI_EDITOR. - find_help: Look for lines in this program's -help output that match\ - (approximately) the given word. - raw_help: Help string unedited. - spx_help: Help string in sphinx format, but do not try to autoformat. - aspx_help: Help string in sphinx format with autoformatting of options. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfClustOutputs`). - """ - if (len(input_dataset) != 2): - raise ValueError(f"Length of 'input_dataset' must be 2 but was {len(input_dataset)}") - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_CLUST_METADATA) - cargs = [] - cargs.append("SurfClust") - if specfile is not None: - cargs.extend([ - "-spec", - execution.input_file(specfile) - ]) - if input_surface is not None: - cargs.extend([ - "-surf_A", - input_surface - ]) - if input_surf_name is not None: - cargs.extend([ - "-i", - execution.input_file(input_surf_name) - ]) - cargs.extend([ - "-input", - *[execution.input_file(f) for f in input_dataset] - ]) - cargs.extend([ - "-rmm", - str(rmm) - ]) - if amm2 is not None: - cargs.extend([ - "-amm2", - str(amm2) - ]) - if min_nodes is not None: - cargs.extend([ - "-n", - str(min_nodes) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if out_clusterdset: - cargs.append("-out_clusterdset") - if out_roidset: - cargs.append("-out_roidset") - if out_fulllist: - cargs.append("-out_fulllist") - if sort_none: - cargs.append("-sort_none") - if sort_n_nodes: - cargs.append("-sort_n_nodes") - if sort_area: - cargs.append("-sort_area") - if thresh_col is not None: - cargs.extend([ - "-thresh_col", - str(thresh_col) - ]) - if thresh is not None: - cargs.extend([ - "-thresh", - str(thresh) - ]) - if athresh is not None: - cargs.extend([ - "-athresh", - str(athresh) - ]) - if ir_range is not None: - cargs.extend([ - "-ir_range", - *map(str, ir_range) - ]) - if ex_range is not None: - cargs.extend([ - "-ex_range", - *map(str, ex_range) - ]) - if prepend_node_index: - cargs.append("-prepend_node_index") - if update_ is not None: - cargs.extend([ - "-update", - str(update_) - ]) - if no_cent: - cargs.append("-no_cent") - if cent: - cargs.append("-cent") - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if set_env is not None: - cargs.extend([ - "-setenv", - set_env - ]) - if trace_: - cargs.append("-trace") - if trace_extreme: - cargs.append("-TRACE") - if no_memory_trace: - cargs.append("-nomall") - if yes_memory_trace: - cargs.append("-yesmall") - if mini_help: - cargs.append("-h") - if help_: - cargs.append("-help") - if extreme_help: - cargs.append("-HELP") - if view_help: - cargs.append("-h_view") - if web_help: - cargs.append("-h_web") - if find_help is not None: - cargs.extend([ - "-h_find", - find_help - ]) - if raw_help: - cargs.append("-h_raw") - if spx_help: - cargs.append("-h_spx") - if aspx_help: - cargs.append("-h_aspx") - ret = SurfClustOutputs( - root=execution.output_file("."), - cluster_table=execution.output_file(prefix + "_ClstTable_rXX_aXX.1D") if (prefix is not None) else None, - clustered_dataset=execution.output_file(prefix + "_Clustered_rXX_aXX.dset") if (prefix is not None) else None, - roi_dataset=execution.output_file(prefix + "_ClstMsk_rXX_aXX.dset") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_CLUST_METADATA", - "SurfClustOutputs", - "surf_clust", -] diff --git a/python/src/niwrap/afni/surf_dist.py b/python/src/niwrap/afni/surf_dist.py deleted file mode 100644 index 577bf8d94..000000000 --- a/python/src/niwrap/afni/surf_dist.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_DIST_METADATA = Metadata( - id="72e073419f09d40df9016fa6050521df038dab85.boutiques", - name="SurfDist", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfDistOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_dist(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - distances: OutputPathType - """File containing the distances between nodes""" - - -def surf_dist( - surface: InputPathType, - nodepairs: InputPathType, - node_path_do: str | None = None, - graph: bool = False, - runner: Runner | None = None, -) -> SurfDistOutputs: - """ - Calculate shortest distance between node pairs on a surface mesh. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Surface on which distances are computed. - nodepairs: Specify node pairs for distance computation. - node_path_do: Output the shortest path between each node pair as a SUMA\ - Displayable object. - graph: Calculate distance along the mesh (default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfDistOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_DIST_METADATA) - cargs = [] - cargs.append("SurfDist") - cargs.append(execution.input_file(surface)) - cargs.append(execution.input_file(nodepairs)) - if node_path_do is not None: - cargs.extend([ - "-node_path_do", - node_path_do - ]) - if graph: - cargs.append("-graph") - ret = SurfDistOutputs( - root=execution.output_file("."), - distances=execution.output_file("example.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_DIST_METADATA", - "SurfDistOutputs", - "surf_dist", -] diff --git a/python/src/niwrap/afni/surf_dset_info.py b/python/src/niwrap/afni/surf_dset_info.py deleted file mode 100644 index f860e0833..000000000 --- a/python/src/niwrap/afni/surf_dset_info.py +++ /dev/null @@ -1,147 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_DSET_INFO_METADATA = Metadata( - id="0eea0d47be8d446fa32a71638d9796998abd8047.boutiques", - name="SurfDsetInfo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfDsetInfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_dset_info(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def surf_dset_info( - input_dsets: list[InputPathType], - debug_level: int | None = None, - novolreg: bool = False, - noxform: bool = False, - setenv: str | None = None, - trace_: bool = False, - extreme_trace: bool = False, - nomall: bool = False, - yesmall: bool = False, - mini_help: bool = False, - help_: bool = False, - extreme_help: bool = False, - help_view: bool = False, - help_web: bool = False, - help_find: str | None = None, - help_raw: bool = False, - help_spx: bool = False, - help_aspx: bool = False, - all_opts: bool = False, - runner: Runner | None = None, -) -> SurfDsetInfoOutputs: - """ - Provides information about surface datasets (DSET). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dsets: Input dataset. - debug_level: Debug level. If DBG = 2, show full dataset information in\ - NIML form. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations. - noxform: Same as -novolreg. - setenv: Set environment variable. - trace_: Turns on In/Out debug and Memory tracing. - extreme_trace: Turns on extreme tracing. - nomall: Turn off memory tracing. - yesmall: Turn on memory tracing (default). - mini_help: Mini help. - help_: Show entire help output. - extreme_help: Show extreme help. - help_view: Open help in text editor. - help_web: Open help in web browser. - help_find: Look for lines in help output that match the specified word. - help_raw: Show unedited help string. - help_spx: Show help string in sphinx format, but do not autoformat. - help_aspx: Show help string in sphinx with autoformatting. - all_opts: Attempt to identify all options for the program from the help\ - output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfDsetInfoOutputs`). - """ - if debug_level is not None and not (0 <= debug_level): - raise ValueError(f"'debug_level' must be greater than 0 <= x but was {debug_level}") - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_DSET_INFO_METADATA) - cargs = [] - cargs.append("SurfDsetInfo") - cargs.extend([ - "-input", - *[execution.input_file(f) for f in input_dsets] - ]) - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if setenv is not None: - cargs.extend([ - "-setenv", - setenv - ]) - if trace_: - cargs.append("-trace") - if extreme_trace: - cargs.append("-TRACE") - if nomall: - cargs.append("-nomall") - if yesmall: - cargs.append("-yesmall") - if mini_help: - cargs.append("-h") - if help_: - cargs.append("-help") - if extreme_help: - cargs.append("-HELP") - if help_view: - cargs.append("-h_view") - if help_web: - cargs.append("-h_web") - if help_find is not None: - cargs.extend([ - "-h_find", - help_find - ]) - if help_raw: - cargs.append("-h_raw") - if help_spx: - cargs.append("-h_spx") - if help_aspx: - cargs.append("-h_aspx") - if all_opts: - cargs.append("-all_opts") - ret = SurfDsetInfoOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_DSET_INFO_METADATA", - "SurfDsetInfoOutputs", - "surf_dset_info", -] diff --git a/python/src/niwrap/afni/surf_extrema.py b/python/src/niwrap/afni/surf_extrema.py deleted file mode 100644 index 2050d4201..000000000 --- a/python/src/niwrap/afni/surf_extrema.py +++ /dev/null @@ -1,119 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_EXTREMA_METADATA = Metadata( - id="878c450ead99de06c9173d0159c8e69a49c74d62.boutiques", - name="SurfExtrema", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfExtremaOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_extrema(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_grd: OutputPathType - """Output file containing the scaled average gradient values.""" - output_ext: OutputPathType - """Output file containing the nodes with maximum values.""" - - -def surf_extrema( - prefix: str, - input_: InputPathType | None = None, - hood: float | None = None, - thresh: float | None = None, - gthresh: float | None = None, - gscale: typing.Literal["NONE", "LMEAN", "GMEAN"] | None = None, - extype: typing.Literal["MAX", "MIN", "ABS"] | None = None, - table: str | None = None, - runner: Runner | None = None, -) -> SurfExtremaOutputs: - """ - A program finding the local extrema in a dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for the output datasets. - input_: Input dataset in which Extrema are to be identified. - hood: Neighborhood radius (R) in mm. Default is 8 mm. - thresh: Do not consider nodes with value less than this threshold.\ - Default is 0. - gthresh: Do not consider nodes with gradient less than this threshold.\ - Default is 0.01. - gscale: Scaling to apply to gradient computation. - extype: Find maxima, minima, or extrema. Options are MAX (default),\ - MIN, ABS. - table: Name of file in which to store a record of the extrema found. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfExtremaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_EXTREMA_METADATA) - cargs = [] - cargs.append("SurfExtrema") - if input_ is not None: - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if hood is not None: - cargs.extend([ - "-nbhd_rad", - str(hood) - ]) - if thresh is not None: - cargs.extend([ - "-thresh", - str(thresh) - ]) - if gthresh is not None: - cargs.extend([ - "-gthresh", - str(gthresh) - ]) - if gscale is not None: - cargs.extend([ - "-gscale", - gscale - ]) - if extype is not None: - cargs.extend([ - "-extype", - extype - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if table is not None: - cargs.extend([ - "-table", - table - ]) - ret = SurfExtremaOutputs( - root=execution.output_file("."), - output_grd=execution.output_file(prefix + ".grd"), - output_ext=execution.output_file(prefix + ".ext"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_EXTREMA_METADATA", - "SurfExtremaOutputs", - "surf_extrema", -] diff --git a/python/src/niwrap/afni/surf_fwhm.py b/python/src/niwrap/afni/surf_fwhm.py deleted file mode 100644 index b2a55155e..000000000 --- a/python/src/niwrap/afni/surf_fwhm.py +++ /dev/null @@ -1,157 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_FWHM_METADATA = Metadata( - id="820e2cdba66aaf5cb57d0db2242d410c19f6020f.boutiques", - name="SurfFWHM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfFwhmOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_fwhm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - detrended_output: OutputPathType | None - """Detrended dataset.""" - main_output: OutputPathType | None - """Main output dataset.""" - histogram_output: OutputPathType | None - """Histogram showing the distribution of local FWHM.""" - mask_output: OutputPathType | None - """Mask output dataset.""" - - -def surf_fwhm( - input_file: InputPathType, - mask: InputPathType | None = None, - surf_1: str | None = None, - surf_sphere: str | None = None, - clean: bool = False, - detrend: float | None = None, - detpoly: float | None = None, - detprefix: str | None = None, - prefix: str | None = None, - vox_size: float | None = None, - neighborhood: float | None = None, - ok_warn: bool = False, - examples: bool = False, - slice_: bool = False, - runner: Runner | None = None, -) -> SurfFwhmOutputs: - """ - A program for calculating local and global FWHM. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Dataset for which the FWHM is to be calculated. - mask: Node mask so that only nodes in the mask are used to obtain\ - estimates. - surf_1: Option for specifying the surface over which the input dataset\ - is defined. - surf_sphere: Spherical version of -SURF_1 for Local FWHM estimates. - clean: Strip text from output to simplify parsing. - detrend: Detrend to order 'q'. If q is not given, the program picks\ - q=NT/30. - detpoly: Detrend with polynomials of order p. - detprefix: Save the detrended file into a dataset with prefix 'd'. - prefix: Prefix of output data set. - vox_size: Specify the nominal voxel size in mm. - neighborhood: Neighborhood radius R for local FWHM estimates. - ok_warn: Flag to set the mode to ok_warn. - examples: Show command line examples and quit. - slice_: Use the contours from planar intersections to estimate\ - gradients. For testing and development purposes only. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfFwhmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_FWHM_METADATA) - cargs = [] - cargs.append("SurfFWHM") - cargs.append(execution.input_file(input_file)) - if mask is not None: - cargs.extend([ - "-MASK", - execution.input_file(mask) - ]) - if surf_1 is not None: - cargs.extend([ - "-SURF_1", - surf_1 - ]) - if surf_sphere is not None: - cargs.extend([ - "-SURF_SPHERE", - surf_sphere - ]) - if clean: - cargs.append("-clean") - if detrend is not None: - cargs.extend([ - "-detrend", - str(detrend) - ]) - if detpoly is not None: - cargs.extend([ - "-detpoly", - str(detpoly) - ]) - if detprefix is not None: - cargs.extend([ - "-detprefix", - detprefix - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if vox_size is not None: - cargs.extend([ - "-vox_size", - str(vox_size) - ]) - if neighborhood is not None: - cargs.extend([ - "-hood", - str(neighborhood) - ]) - if ok_warn: - cargs.append("-ok_warn") - if examples: - cargs.append("-examples") - if slice_: - cargs.append("-slice") - cargs.append("[TALK_SUMA_OPTIONS]") - cargs.append("[NIML_OPTIONS]") - cargs.append("[DEBUG_OPTIONS]") - cargs.append("[HELP_OPTIONS]") - ret = SurfFwhmOutputs( - root=execution.output_file("."), - detrended_output=execution.output_file(prefix + ".1D.dset") if (prefix is not None) else None, - main_output=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - histogram_output=execution.output_file(prefix + "_histog.1D") if (prefix is not None) else None, - mask_output=execution.output_file(prefix + "_mask.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_FWHM_METADATA", - "SurfFwhmOutputs", - "surf_fwhm", -] diff --git a/python/src/niwrap/afni/surf_info.py b/python/src/niwrap/afni/surf_info.py deleted file mode 100644 index 7859484df..000000000 --- a/python/src/niwrap/afni/surf_info.py +++ /dev/null @@ -1,120 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_INFO_METADATA = Metadata( - id="d2662d0789ce0ce3e69fb658348261cec5de9136.boutiques", - name="SurfInfo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfInfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_info(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - metrics_output: OutputPathType - """Output file containing calculated surface metrics.""" - - -def surf_info( - surface: InputPathType, - com: bool = False, - debug_level: float | None = None, - detail_level: float | None = None, - quiet: bool = False, - separator: str | None = None, - input_surface: str | None = None, - surface_state: str | None = None, - surface_volume: InputPathType | None = None, - spec_file: InputPathType | None = None, - runner: Runner | None = None, -) -> SurfInfoOutputs: - """ - Tool to gather information about surface files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Input surface file. - com: Output the center of mass. - debug_level: Debugging level (2 turns LocalHead ON). - detail_level: Calculate surface metrics. 1=yes, 0=no. - quiet: Do not include the name of the parameter in output. - separator: Use string SEP to separate parameter values. Default is ' ;\ - '. - input_surface: Specify the input surface type and file. - surface_state: Specify surface type, state, and name. - surface_volume: Specify a surface volume file. - spec_file: Specify a surface specification (spec) file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfInfoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_INFO_METADATA) - cargs = [] - cargs.append("SurfInfo") - cargs.append("[options]") - cargs.append(execution.input_file(surface)) - if com: - cargs.append("-COM") - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if detail_level is not None: - cargs.extend([ - "-detail", - str(detail_level) - ]) - if quiet: - cargs.append("-quiet") - if separator is not None: - cargs.extend([ - "-sep", - separator - ]) - if input_surface is not None: - cargs.extend([ - "-i_TYPE", - input_surface - ]) - if surface_state is not None: - cargs.extend([ - "-tsn", - surface_state - ]) - if surface_volume is not None: - cargs.extend([ - "-sv", - execution.input_file(surface_volume) - ]) - if spec_file is not None: - cargs.extend([ - "-spec", - execution.input_file(spec_file) - ]) - ret = SurfInfoOutputs( - root=execution.output_file("."), - metrics_output=execution.output_file(pathlib.Path(surface).name + "_metrics.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_INFO_METADATA", - "SurfInfoOutputs", - "surf_info", -] diff --git a/python/src/niwrap/afni/surf_layers.py b/python/src/niwrap/afni/surf_layers.py deleted file mode 100644 index 1cb7ed885..000000000 --- a/python/src/niwrap/afni/surf_layers.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_LAYERS_METADATA = Metadata( - id="3f46cd6dc74745711c02167e428a901a79f7affc.boutiques", - name="SurfLayers", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfLayersOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_layers(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - interpolated_surfaces: OutputPathType | None - """Interpolated surfaces files""" - additional_spec_files: OutputPathType | None - """Additional files if -spec option was used""" - run_view_script: OutputPathType | None - """Run script to view output directly""" - - -def surf_layers( - spec_dset: InputPathType | None = None, - outdir: str | None = None, - states: str | None = None, - hemi: str | None = None, - n_intermed_surfs: float | None = None, - surf_a: InputPathType | None = None, - surf_b: InputPathType | None = None, - surf_intermed_pref: str | None = None, - echo: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> SurfLayersOutputs: - """ - Compute intermediate equi-distant surfaces between two boundary surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_dset: Dataset that is the SUMA specification file describing input\ - surfaces. - outdir: New directory for output (default: surflayers). - states: Typically smoothwm, pial states to describe inner and outer\ - surfaces (default: 'smoothwm pial'). - hemi: Choose hemisphere: 'lh', 'rh', or 'lh rh' (for both). - n_intermed_surfs: Total number of intermediate surfaces to create. - surf_a: Inner boundary surface by filename (e.g., smoothwm.gii). - surf_b: Outer boundary surface by filename (e.g., pial.gii). - surf_intermed_pref: Name for interpolated surfaces (default: isurf). - echo: Run script with 'set echo' (i.e., verbosely). - no_clean: Do not remove temp files (probably just for testing). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfLayersOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_LAYERS_METADATA) - cargs = [] - cargs.append("SurfLayers") - if spec_dset is not None: - cargs.extend([ - "-spec", - execution.input_file(spec_dset) - ]) - if outdir is not None: - cargs.extend([ - "-outdir", - outdir - ]) - if states is not None: - cargs.extend([ - "-states", - states - ]) - if hemi is not None: - cargs.extend([ - "-hemi", - hemi - ]) - if n_intermed_surfs is not None: - cargs.extend([ - "-n_intermed_surfs", - str(n_intermed_surfs) - ]) - if surf_a is not None: - cargs.extend([ - "-surf_A", - execution.input_file(surf_a) - ]) - if surf_b is not None: - cargs.extend([ - "-surf_B", - execution.input_file(surf_b) - ]) - if surf_intermed_pref is not None: - cargs.extend([ - "-surf_intermed_pref", - surf_intermed_pref - ]) - if echo: - cargs.append("-echo") - if no_clean: - cargs.append("-no_clean") - ret = SurfLayersOutputs( - root=execution.output_file("."), - interpolated_surfaces=execution.output_file(outdir + "/isurf." + hemi + ".*.gii") if (outdir is not None and hemi is not None) else None, - additional_spec_files=execution.output_file(outdir + "/*") if (outdir is not None) else None, - run_view_script=execution.output_file(outdir + "/run*tcsh") if (outdir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_LAYERS_METADATA", - "SurfLayersOutputs", - "surf_layers", -] diff --git a/python/src/niwrap/afni/surf_localstat.py b/python/src/niwrap/afni/surf_localstat.py deleted file mode 100644 index 75887daf4..000000000 --- a/python/src/niwrap/afni/surf_localstat.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_LOCALSTAT_METADATA = Metadata( - id="9e3561e89dfa2eba26d8a89cd6cd2dd67777d004.boutiques", - name="SurfLocalstat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfLocalstatOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_localstat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Computed local statistics dataset""" - - -def surf_localstat( - prefix: str, - stat_: typing.Literal["mean", "mode", "num", "FWHM", "ALL"], - input_dataset: InputPathType, - surface: InputPathType, - hood: float | None = None, - nbhd_rad: float | None = None, - runner: Runner | None = None, -) -> SurfLocalstatOutputs: - """ - Compute local statistics on a surface mesh. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix of output data set. - stat_: Compute the specified statistic on the values extracted from the\ - region around each voxel. Options: mean, mode, num, FWHM, ALL. - input_dataset: Input dataset. - surface: Input GIFTI surface file. - hood: Neighborhood of nodes within the specified radius R. - nbhd_rad: Distance from node n as measured by the shortest distance\ - along the mesh. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfLocalstatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_LOCALSTAT_METADATA) - cargs = [] - cargs.append("SurfLocalstat") - if hood is not None: - cargs.extend([ - "-hood", - str(hood) - ]) - if nbhd_rad is not None: - cargs.extend([ - "-nbhd_rad", - str(nbhd_rad) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-stat", - stat_ - ]) - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - cargs.extend([ - "-i_gii", - execution.input_file(surface) - ]) - ret = SurfLocalstatOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".niml.dset"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_LOCALSTAT_METADATA", - "SurfLocalstatOutputs", - "surf_localstat", -] diff --git a/python/src/niwrap/afni/surf_measures.py b/python/src/niwrap/afni/surf_measures.py deleted file mode 100644 index 53bf353f1..000000000 --- a/python/src/niwrap/afni/surf_measures.py +++ /dev/null @@ -1,166 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_MEASURES_METADATA = Metadata( - id="21378ea7d8b0e920275d5e4fab477aa23c434ab4.boutiques", - name="SurfMeasures", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfMeasuresOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_measures(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_1_d: OutputPathType | None - """Output in 1D format""" - output_dset: OutputPathType - """Output in specified dataset format""" - - -def surf_measures( - spec_file: InputPathType, - surf_a: str, - out_dset: str, - surf_b: str | None = None, - out_1_d: str | None = None, - func: list[str] | None = None, - surf_volume: InputPathType | None = None, - cmask: str | None = None, - debug: int | None = None, - dnode: float | None = None, - nodes_1_d: InputPathType | None = None, - info_all: bool = False, - info_area: bool = False, - info_norms: bool = False, - info_thick: bool = False, - info_vol: bool = False, - info_volg: bool = False, - ver: bool = False, - runner: Runner | None = None, -) -> SurfMeasuresOutputs: - """ - Compute measures from surface dataset(s). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: SUMA spec file containing a list of related surfaces. - surf_a: Surface name (in spec file) for the first surface. - out_dset: Output filename with dataset format. - surf_b: Surface name (in spec file) for the second surface. - out_1_d: Output filename in 1D format. - func: Measure function to be applied. - surf_volume: AFNI volume dataset associated with the surface. - cmask: Restrict nodes with a mask. - debug: Display extra run-time information with specified debug level\ - (0-5). - dnode: Display extra information for specified node. - nodes_1_d: Restrict output to specific nodes listed in a file. - info_all: Display all final info. - info_area: Display total area of each triangulated surface. - info_norms: Display info about the normals. - info_thick: Display minimum and maximum thickness between surfaces. - info_vol: Display total computed volume between surfaces. - info_volg: Display total computed volume estimated via Gauss' theorem. - ver: Show program version and compile date. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfMeasuresOutputs`). - """ - if debug is not None and not (0 <= debug <= 5): - raise ValueError(f"'debug' must be between 0 <= x <= 5 but was {debug}") - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_MEASURES_METADATA) - cargs = [] - cargs.append("SurfMeasures") - cargs.extend([ - "-spec", - execution.input_file(spec_file) - ]) - cargs.extend([ - "-surf_A", - surf_a - ]) - if surf_b is not None: - cargs.extend([ - "-surf_B", - surf_b - ]) - if out_1_d is not None: - cargs.extend([ - "-out_1D", - out_1_d - ]) - cargs.extend([ - "-out", - out_dset - ]) - if func is not None: - cargs.extend([ - "-func", - *func - ]) - if surf_volume is not None: - cargs.extend([ - "-sv", - execution.input_file(surf_volume) - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if dnode is not None: - cargs.extend([ - "-dnode", - str(dnode) - ]) - if nodes_1_d is not None: - cargs.extend([ - "-nodes_1D", - execution.input_file(nodes_1_d) - ]) - if info_all: - cargs.append("-info_all") - if info_area: - cargs.append("-info_area") - if info_norms: - cargs.append("-info_norms") - if info_thick: - cargs.append("-info_thick") - if info_vol: - cargs.append("-info_vol") - if info_volg: - cargs.append("-info_volg") - if ver: - cargs.append("-ver") - ret = SurfMeasuresOutputs( - root=execution.output_file("."), - output_1_d=execution.output_file(out_1_d + ".1D") if (out_1_d is not None) else None, - output_dset=execution.output_file(out_dset), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_MEASURES_METADATA", - "SurfMeasuresOutputs", - "surf_measures", -] diff --git a/python/src/niwrap/afni/surf_mesh.py b/python/src/niwrap/afni/surf_mesh.py deleted file mode 100644 index ccde37133..000000000 --- a/python/src/niwrap/afni/surf_mesh.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_MESH_METADATA = Metadata( - id="aba9dc7cdd5795dd83c2c7deb8fe8088d1965d12.boutiques", - name="SurfMesh", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfMeshOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_mesh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_surface_file: OutputPathType - """Output surface file""" - - -def surf_mesh( - input_surface: str, - output_surface: str, - edge_fraction: float, - surface_volume: InputPathType | None = None, - one_state: bool = False, - anatomical_label: bool = False, - no_volume_registration: bool = False, - set_env: str | None = None, - runner: Runner | None = None, -) -> SurfMeshOutputs: - """ - Surface mesh manipulation tool. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_surface: Input surface file with specified type. - output_surface: Output surface file with specified type. - edge_fraction: Fraction of edges to simplify the surface. - surface_volume: Surface volume file. - one_state: Make all input surfaces have the same state. - anatomical_label: Label all input surfaces as anatomically correct. - no_volume_registration: Ignore any Rotate, Volreg, Tagalign, or\ - WarpDrive transformations present in the Surface Volume. - set_env: Set environment variable. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfMeshOutputs`). - """ - if not (0 <= edge_fraction <= 1): - raise ValueError(f"'edge_fraction' must be between 0 <= x <= 1 but was {edge_fraction}") - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_MESH_METADATA) - cargs = [] - cargs.append("SurfMesh") - cargs.extend([ - "-i_TYPE", - input_surface - ]) - cargs.extend([ - "-o_TYPE", - output_surface - ]) - cargs.extend([ - "-edges", - str(edge_fraction) - ]) - if surface_volume is not None: - cargs.extend([ - "-sv", - execution.input_file(surface_volume) - ]) - if one_state: - cargs.append("-onestate") - if anatomical_label: - cargs.append("-anatomical") - if no_volume_registration: - cargs.append("-novolreg") - if set_env is not None: - cargs.extend([ - "-setenv", - set_env - ]) - ret = SurfMeshOutputs( - root=execution.output_file("."), - output_surface_file=execution.output_file(output_surface + ".surface"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_MESH_METADATA", - "SurfMeshOutputs", - "surf_mesh", -] diff --git a/python/src/niwrap/afni/surf_patch.py b/python/src/niwrap/afni/surf_patch.py deleted file mode 100644 index f7d2fa1fd..000000000 --- a/python/src/niwrap/afni/surf_patch.py +++ /dev/null @@ -1,180 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_PATCH_METADATA = Metadata( - id="1b9f54ccf622083c532013b3e22205e01ab00c46.boutiques", - name="SurfPatch", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfPatchOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_patch(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outpatch_a: OutputPathType - """Output patch for surface A""" - outpatch_b: OutputPathType - """Output patch for surface B""" - out_stitched_surface: OutputPathType - """Stitched surface file""" - - -def surf_patch( - spec_file: InputPathType, - surf_a: InputPathType, - surf_b: InputPathType, - nodefile: InputPathType, - inode: float, - ilabel: float, - prefix: str, - hits: float | None = None, - masklabel: str | None = None, - vol: bool = False, - vol_only: bool = False, - patch2surf: bool = False, - coord_gain: float | None = None, - check_bowtie: bool = False, - fix_bowtie: bool = False, - ok_bowtie: bool = False, - adjust_contour: bool = False, - do_not_adjust_contour: bool = False, - stitched_surface: InputPathType | None = None, - flip_orientation: bool = False, - verbosity: float | None = None, - runner: Runner | None = None, -) -> SurfPatchOutputs: - """ - Creates a patch of surface formed by nodes in a nodefile and optionally - calculates the volume between the same patch on two isotopic surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: Spec file containing input surfaces. - surf_a: Input surface A. - surf_b: Input surface B. - nodefile: File containing nodes defining the patch. - inode: Index of the column containing the nodes. - ilabel: Index of the column containing labels of the nodes in column\ - inode. - prefix: Prefix of output patch. - hits: Minimum number of nodes specified for a triangle to be made a\ - part of the patch (1 <= min_hits <= 3); default is 2. - masklabel: Only nodes that are labeled with this label are considered\ - for the patch. - vol: Calculate the volume formed by the patch on surf_A and surf_B.\ - Requires only two surfaces specified with surf_A and surf_B. - vol_only: Only calculate the volume, don't write out patches. - patch2surf: Turn surface patch into a surface where only nodes used in\ - forming the mesh are preserved. - coord_gain: Multiply node coordinates by a gain. Useful for enlarging\ - tiny patches for easier viewing in SUMA. - check_bowtie: Check if the patch has a section hanging by one node to\ - the rest of the mesh. Default when -vol or -vol_only are used. - fix_bowtie: Modify patch to eliminate bowties. - ok_bowtie: Do not check for, or fix bowties. Default when -vol* are not\ - used. - adjust_contour: Shrink patch contours at nodes that were not in\ - nodefile. - do_not_adjust_contour: Do not adjust contours. This is the default. - stitched_surface: Write out the stitched surface used to calculate the\ - volume. - flip_orientation: Change orientation of triangles before writing\ - surfaces. - verbosity: Set verbosity level, 1 is the default. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfPatchOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_PATCH_METADATA) - cargs = [] - cargs.append("SurfPatch") - cargs.append(execution.input_file(spec_file)) - cargs.extend([ - "-surf_A", - execution.input_file(surf_a) - ]) - cargs.extend([ - "-surf_B", - execution.input_file(surf_b) - ]) - cargs.extend([ - "-input", - execution.input_file(nodefile) - ]) - cargs.append(str(inode)) - cargs.append(str(ilabel)) - cargs.extend([ - "-prefix", - prefix - ]) - if hits is not None: - cargs.extend([ - "-hits", - str(hits) - ]) - if masklabel is not None: - cargs.extend([ - "-masklabel", - masklabel - ]) - if vol: - cargs.append("-vol") - if vol_only: - cargs.append("-vol_only") - if patch2surf: - cargs.append("-patch2surf") - if coord_gain is not None: - cargs.extend([ - "-coord_gain", - str(coord_gain) - ]) - if check_bowtie: - cargs.append("-check_bowtie") - if fix_bowtie: - cargs.append("-fix_bowtie") - if ok_bowtie: - cargs.append("-ok_bowtie") - if adjust_contour: - cargs.append("-adjust_contour") - if do_not_adjust_contour: - cargs.append("-do-not-adjust_contour") - if stitched_surface is not None: - cargs.extend([ - "-stitched_surface", - execution.input_file(stitched_surface) - ]) - if flip_orientation: - cargs.append("-flip_orientation") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = SurfPatchOutputs( - root=execution.output_file("."), - outpatch_a=execution.output_file(prefix + "_A"), - outpatch_b=execution.output_file(prefix + "_B"), - out_stitched_surface=execution.output_file(prefix + "_stitched"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_PATCH_METADATA", - "SurfPatchOutputs", - "surf_patch", -] diff --git a/python/src/niwrap/afni/surf_qual.py b/python/src/niwrap/afni/surf_qual.py deleted file mode 100644 index e8ce5d31f..000000000 --- a/python/src/niwrap/afni/surf_qual.py +++ /dev/null @@ -1,109 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_QUAL_METADATA = Metadata( - id="26998942504c3f8916ff5647525cc6689776bf8d.boutiques", - name="SurfQual", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfQualOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_qual(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - dist_output: OutputPathType | None - """File containing distances of nodes from the surface's center.""" - dist_color_output: OutputPathType | None - """Colorized file containing distances of nodes from the surface's - center.""" - bad_nodes_output: OutputPathType | None - """File containing nodes with bad dot product values.""" - bad_nodes_color_output: OutputPathType | None - """Colorized file containing nodes with bad dot product values.""" - dotprod_output: OutputPathType | None - """File containing dot product values for all nodes.""" - dotprod_color_output: OutputPathType | None - """Colorized file containing dot product values for all nodes.""" - intersect_nodes_output: OutputPathType | None - """File containing indices of nodes forming segments that intersect the - surface.""" - - -def surf_qual( - spec_file: InputPathType, - surface_a: list[InputPathType], - sphere_flag: bool = False, - summary_flag: bool = False, - self_intersect_flag: bool = False, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> SurfQualOutputs: - """ - A program to check the quality of surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: Spec file containing input surfaces. - surface_a: Name of input surface A. - sphere_flag: Indicates that surfaces read are spherical. - summary_flag: Provide summary of results to stdout. - self_intersect_flag: Check if surface is self intersecting. - output_prefix: Prefix of output files. Default is the surface's label. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfQualOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_QUAL_METADATA) - cargs = [] - cargs.append("SurfQual") - cargs.extend([ - "-spec", - execution.input_file(spec_file) - ]) - cargs.extend([ - "-surf_A", - *[execution.input_file(f) for f in surface_a] - ]) - if sphere_flag: - cargs.append("-sphere") - if summary_flag: - cargs.append("-summary") - if self_intersect_flag: - cargs.append("-self_intersect") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - ret = SurfQualOutputs( - root=execution.output_file("."), - dist_output=execution.output_file(output_prefix + "_Dist.1D.dset") if (output_prefix is not None) else None, - dist_color_output=execution.output_file(output_prefix + "_Dist.1D.col") if (output_prefix is not None) else None, - bad_nodes_output=execution.output_file(output_prefix + "_BadNodes.1D.dset") if (output_prefix is not None) else None, - bad_nodes_color_output=execution.output_file(output_prefix + "_BadNodes.1D.col") if (output_prefix is not None) else None, - dotprod_output=execution.output_file(output_prefix + "_dotprod.1D.dset") if (output_prefix is not None) else None, - dotprod_color_output=execution.output_file(output_prefix + "_dotprod.1D.col") if (output_prefix is not None) else None, - intersect_nodes_output=execution.output_file(output_prefix + "_IntersNodes.1D.dset") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_QUAL_METADATA", - "SurfQualOutputs", - "surf_qual", -] diff --git a/python/src/niwrap/afni/surf_retino_map.py b/python/src/niwrap/afni/surf_retino_map.py deleted file mode 100644 index e3890ca1a..000000000 --- a/python/src/niwrap/afni/surf_retino_map.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_RETINO_MAP_METADATA = Metadata( - id="f282168d578a8fb61be6e59e5e58d7129fbfa5b1.boutiques", - name="SurfRetinoMap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfRetinoMapOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_retino_map(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - vfr_output: OutputPathType | None - """Output Visual Field Ratio (VFR) dataset.""" - threshold_max_output: OutputPathType | None - """Maximum threshold at each node in the input datasets.""" - - -def surf_retino_map( - surface: str, - polar: str, - eccentricity: str, - prefix: str | None = None, - node_debug: float | None = None, - runner: Runner | None = None, -) -> SurfRetinoMapOutputs: - """ - Tool for retinotopic mapping on cortical surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Surface on which distances are computed. See 'Specifying input\ - surfaces' section for syntax. - polar: Retinotopic dataset: polar angle dataset. - eccentricity: Retinotopic dataset: eccentricity angle dataset. - prefix: Prefix for output datasets. - node_debug: Index of node number for which debugging information is\ - output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfRetinoMapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_RETINO_MAP_METADATA) - cargs = [] - cargs.append("SurfRetinoMap") - cargs.append(surface) - cargs.append(polar) - cargs.append(eccentricity) - if prefix is not None: - cargs.extend([ - "--prefix", - prefix - ]) - if node_debug is not None: - cargs.extend([ - "--node_dbg", - str(node_debug) - ]) - ret = SurfRetinoMapOutputs( - root=execution.output_file("."), - vfr_output=execution.output_file(prefix + "_VFR.nii.gz") if (prefix is not None) else None, - threshold_max_output=execution.output_file(prefix + "_threshold_max.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_RETINO_MAP_METADATA", - "SurfRetinoMapOutputs", - "surf_retino_map", -] diff --git a/python/src/niwrap/afni/surf_smooth.py b/python/src/niwrap/afni/surf_smooth.py deleted file mode 100644 index 88c69a4d2..000000000 --- a/python/src/niwrap/afni/surf_smooth.py +++ /dev/null @@ -1,174 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_SMOOTH_METADATA = Metadata( - id="9567232249acc1b0e69c280f3ce45f44bb256c86.boutiques", - name="SurfSmooth", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfSmoothOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_smooth(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType | None - """Name of the output file.""" - - -def surf_smooth( - surface: str, - method: str, - input_data: InputPathType | None = None, - target_fwhm: float | None = None, - fwhm: float | None = None, - number_iterations: float | None = None, - output_file: InputPathType | None = None, - band_pass_frequency: float | None = None, - lambda_mu: str | None = None, - interp_weights: str | None = None, - node_mask: InputPathType | None = None, - surface_output: InputPathType | None = None, - dbg_node: float | None = None, - use_neighbors_outside_mask: bool = False, - talk_suma: bool = False, - refresh_rate: float | None = None, - runner: Runner | None = None, -) -> SurfSmoothOutputs: - """ - Tool for smoothing data on surfaces using various methods. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface: Option for specifying the surface to smooth or the domain over\ - which DSET is defined. - method: Name of smoothing method to use. Choose from: HEAT_07, HEAT_05,\ - LM, NN_geom. - input_data: File containing data (in 1D or NIML format). Required for\ - HEAT_05 and HEAT_07 methods. - target_fwhm: Blur so that the final FWHM of the data is TF mm. Only for\ - HEAT_07 method. - fwhm: Effective Full Width at Half Maximum for smoothing. Required for\ - HEAT_05 and optional for HEAT_07 methods. - number_iterations: Number of smoothing iterations (default is 100 for\ - LM and NN_geom, -1 for HEAT methods). - output_file: Name of output file. Default based on method being used. - band_pass_frequency: Bandpass frequency for LM method (0 < k < 10). - lambda_mu: Lambda and Mu parameters for LM method. Sample values are:\ - 0.6307 and -0.6732. - interp_weights: Set interpolation weights for LM method. Options:\ - Equal, Fujiwara, Desbrun. - node_mask: Apply operations only to nodes listed in the given mask. - surface_output: Writes the surface with smoothed coordinates to disk.\ - For LM and NN_geom methods. - dbg_node: Output debug information for node 'node'. - use_neighbors_outside_mask: Allow value from a node neighboring node n\ - to contribute to the value at n even if the neighbor is not in the\ - mask. - talk_suma: Send progress with each iteration to SUMA for real-time\ - visualization. - refresh_rate: Maximum number of updates to SUMA per second. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfSmoothOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_SMOOTH_METADATA) - cargs = [] - cargs.append("SurfSmooth") - cargs.extend([ - "-SURF_1", - surface - ]) - cargs.extend([ - "-met", - method - ]) - if input_data is not None: - cargs.extend([ - "-input", - execution.input_file(input_data) - ]) - if target_fwhm is not None: - cargs.extend([ - "-target_fwhm", - str(target_fwhm) - ]) - if fwhm is not None: - cargs.extend([ - "-fwhm", - str(fwhm) - ]) - if number_iterations is not None: - cargs.extend([ - "-Niter", - str(number_iterations) - ]) - if output_file is not None: - cargs.extend([ - "-output", - execution.input_file(output_file) - ]) - if band_pass_frequency is not None: - cargs.extend([ - "-kpb", - str(band_pass_frequency) - ]) - if lambda_mu is not None: - cargs.extend([ - "-lm", - lambda_mu - ]) - if interp_weights is not None: - cargs.extend([ - "-iw", - interp_weights - ]) - if node_mask is not None: - cargs.extend([ - "-MASK", - execution.input_file(node_mask) - ]) - if surface_output is not None: - cargs.extend([ - "-surf_out", - execution.input_file(surface_output) - ]) - if dbg_node is not None: - cargs.extend([ - "-dbg_n", - str(dbg_node) - ]) - if use_neighbors_outside_mask: - cargs.append("-use_neighbors_outside_mask") - if talk_suma: - cargs.append("-talk_suma") - if refresh_rate is not None: - cargs.extend([ - "-refresh_rate", - str(refresh_rate) - ]) - ret = SurfSmoothOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(output_file).name) if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_SMOOTH_METADATA", - "SurfSmoothOutputs", - "surf_smooth", -] diff --git a/python/src/niwrap/afni/surf_to_surf.py b/python/src/niwrap/afni/surf_to_surf.py deleted file mode 100644 index 8a58848fe..000000000 --- a/python/src/niwrap/afni/surf_to_surf.py +++ /dev/null @@ -1,140 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURF_TO_SURF_METADATA = Metadata( - id="a2c971cd7bb0ee914e8be7cd7e5159482c16cc13.boutiques", - name="SurfToSurf", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfToSurfOutputs(typing.NamedTuple): - """ - Output object returned when calling `surf_to_surf(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output file in 1D format""" - - -def surf_to_surf( - input_surface_1: InputPathType, - input_surface_2: InputPathType, - surface_volume: InputPathType | None = None, - prefix: str | None = None, - output_params: str | None = None, - node_indices: InputPathType | None = None, - proj_dir: InputPathType | None = None, - data: InputPathType | None = None, - node_debug: float | None = None, - debug_level: float | None = None, - make_consistent: bool = False, - dset: InputPathType | None = None, - mapfile: InputPathType | None = None, - runner: Runner | None = None, -) -> SurfToSurfOutputs: - """ - Interpolate data from one surface to another. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_surface_1: First input surface file (S1). - input_surface_2: Second input surface file (S2). - surface_volume: Specify the surface volume (SV1). - prefix: Specify prefix for the output file. - output_params: List of mapping parameters to include in output. - node_indices: 1D file containing node indices of S1 to consider. - proj_dir: 1D file containing projection directions. - data: 1D file containing data to be interpolated. - node_debug: Node index for debugging purposes. - debug_level: Debugging level. - make_consistent: Force a consistency check and correct triangle\ - orientation. - dset: Dataset file for data interpolation; mutually exclusive with\ - -data. - mapfile: File containing mapping parameters between surfaces S2 and S1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfToSurfOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURF_TO_SURF_METADATA) - cargs = [] - cargs.append("SurfToSurf") - cargs.append(execution.input_file(input_surface_1)) - cargs.append(execution.input_file(input_surface_2)) - if surface_volume is not None: - cargs.extend([ - "-sv", - execution.input_file(surface_volume) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if output_params is not None: - cargs.extend([ - "-output_params", - output_params - ]) - if node_indices is not None: - cargs.extend([ - "-node_indices", - execution.input_file(node_indices) - ]) - if proj_dir is not None: - cargs.extend([ - "-proj_dir", - execution.input_file(proj_dir) - ]) - if data is not None: - cargs.extend([ - "-data", - execution.input_file(data) - ]) - if node_debug is not None: - cargs.extend([ - "-node_debug", - str(node_debug) - ]) - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if make_consistent: - cargs.append("-make_consistent") - if dset is not None: - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if mapfile is not None: - cargs.extend([ - "-mapfile", - execution.input_file(mapfile) - ]) - ret = SurfToSurfOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURF_TO_SURF_METADATA", - "SurfToSurfOutputs", - "surf_to_surf", -] diff --git a/python/src/niwrap/afni/surface_metrics.py b/python/src/niwrap/afni/surface_metrics.py deleted file mode 100644 index cf6173bb0..000000000 --- a/python/src/niwrap/afni/surface_metrics.py +++ /dev/null @@ -1,152 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURFACE_METRICS_METADATA = Metadata( - id="334f413c508897323e181314a6d4e06fdc8dc4a4.boutiques", - name="SurfaceMetrics", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class SurfaceMetricsOutputs(typing.NamedTuple): - """ - Output object returned when calling `surface_metrics(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def surface_metrics( - surf1: str, - internal_nodes: bool = False, - internal_nodes_: bool = False, - internal_nodes_2: bool = False, - internal_nodes_3: bool = False, - internal_nodes_4: bool = False, - internal_nodes_5: bool = False, - internal_nodes_6: bool = False, - internal_nodes_7: bool = False, - internal_nodes_8: bool = False, - internal_nodes_9: bool = False, - internal_nodes_10: bool = False, - internal_nodes_11: bool = False, - internal_nodes_12: bool = False, - internal_nodes_13: bool = False, - internal_nodes_14: bool = False, - internal_nodes_15: bool = False, - internal_nodes_16: bool = False, - internal_nodes_17: bool = False, - internal_nodes_18: bool = False, - internal_nodes_19: bool = False, - tlrc: bool = False, - prefix: str | None = None, - runner: Runner | None = None, -) -> SurfaceMetricsOutputs: - """ - Outputs information about a surface's mesh. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surf1: Specifies the input surface. - internal_nodes: Output nodes that are not a boundary. - internal_nodes_: Output nodes that are not a boundary. - internal_nodes_2: Output nodes that are not a boundary. - internal_nodes_3: Output nodes that are not a boundary. - internal_nodes_4: Output nodes that are not a boundary. - internal_nodes_5: Output nodes that are not a boundary. - internal_nodes_6: Output nodes that are not a boundary. - internal_nodes_7: Output nodes that are not a boundary. - internal_nodes_8: Output nodes that are not a boundary. - internal_nodes_9: Output nodes that are not a boundary. - internal_nodes_10: Output nodes that are not a boundary. - internal_nodes_11: Output nodes that are not a boundary. - internal_nodes_12: Output nodes that are not a boundary. - internal_nodes_13: Output nodes that are not a boundary. - internal_nodes_14: Output nodes that are not a boundary. - internal_nodes_15: Output nodes that are not a boundary. - internal_nodes_16: Output nodes that are not a boundary. - internal_nodes_17: Output nodes that are not a boundary. - internal_nodes_18: Output nodes that are not a boundary. - internal_nodes_19: Output nodes that are not a boundary. - tlrc: Apply Talairach transform to surface. - prefix: Use prefix for output files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfaceMetricsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURFACE_METRICS_METADATA) - cargs = [] - cargs.append("SurfaceMetrics") - if internal_nodes: - cargs.append("-internal_nodes") - if internal_nodes_: - cargs.append("-internal_nodes") - if internal_nodes_2: - cargs.append("-internal_nodes") - if internal_nodes_3: - cargs.append("-internal_nodes") - if internal_nodes_4: - cargs.append("-internal_nodes") - if internal_nodes_5: - cargs.append("-internal_nodes") - if internal_nodes_6: - cargs.append("-internal_nodes") - if internal_nodes_7: - cargs.append("-internal_nodes") - if internal_nodes_8: - cargs.append("-internal_nodes") - if internal_nodes_9: - cargs.append("-internal_nodes") - if internal_nodes_10: - cargs.append("-internal_nodes") - if internal_nodes_11: - cargs.append("-internal_nodes") - if internal_nodes_12: - cargs.append("-internal_nodes") - if internal_nodes_13: - cargs.append("-internal_nodes") - if internal_nodes_14: - cargs.append("-internal_nodes") - if internal_nodes_15: - cargs.append("-internal_nodes") - if internal_nodes_16: - cargs.append("-internal_nodes") - if internal_nodes_17: - cargs.append("-internal_nodes") - if internal_nodes_18: - cargs.append("-internal_nodes") - if internal_nodes_19: - cargs.append("-internal_nodes") - cargs.extend([ - "-SURF_1", - surf1 - ]) - if tlrc: - cargs.append("-tlrc") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = SurfaceMetricsOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURFACE_METRICS_METADATA", - "SurfaceMetricsOutputs", - "surface_metrics", -] diff --git a/python/src/niwrap/afni/tedana_wrapper_py.py b/python/src/niwrap/afni/tedana_wrapper_py.py deleted file mode 100644 index c5f2f7ad3..000000000 --- a/python/src/niwrap/afni/tedana_wrapper_py.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TEDANA_WRAPPER_PY_METADATA = Metadata( - id="e2c7a15939ce625753fa86861a1e32ee93aeb877.boutiques", - name="tedana_wrapper.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class TedanaWrapperPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `tedana_wrapper_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - tedana_output: OutputPathType | None - """Output directory for tedana results.""" - tedana_report: OutputPathType | None - """Tedana report file.""" - - -def tedana_wrapper_py( - input_files: list[InputPathType], - echo_times: list[float], - mask: InputPathType, - results_dir: str | None = None, - prefix: str | None = None, - save_all: bool = False, - prep_only: bool = False, - tedana_prog: str | None = None, - tedana_is_exec: bool = False, - ted_label: str | None = None, - tedana_opts: str | None = None, - runner: Runner | None = None, -) -> TedanaWrapperPyOutputs: - """ - Internal wrapper to run tedana.py, typically used within afni_proc.py. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: 4D dataset for each echo. - echo_times: Echo time (ms) for each echo. - mask: Mask in same space/grid as the input datasets. - results_dir: Folder to be created for all outputs. Default\ - [./Bunnymen]. - prefix: Prefix for dataset names. Default [Bunnymen]. - save_all: Save intermediate datasets. Default is to save only the\ - 3dZcat stacked dataset (and tedana stuff). - prep_only: Do not run tedana.py, stop at 3dZcat. - tedana_prog: Path and name of the version of tedana.py that will be\ - run. Default is meica.libs/tedana.py in the afni binaries directory. - tedana_is_exec: Run 'tedana.py' rather than 'python tedana.py'. - ted_label: Suffix for output folder. Adds suffix like TED.LABEL (NOT A\ - PATH). - tedana_opts: Additional options to pass to tedana.py. (In quotes)\ - Example: '--initcost=tanh --conv=2.5e-5'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TedanaWrapperPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TEDANA_WRAPPER_PY_METADATA) - cargs = [] - cargs.append("tedana_wrapper.py") - cargs.extend([ - "-input", - *[execution.input_file(f) for f in input_files] - ]) - cargs.extend([ - "-TE", - *map(str, echo_times) - ]) - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if results_dir is not None: - cargs.extend([ - "-results_dir", - results_dir - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if save_all: - cargs.append("-save_all") - if prep_only: - cargs.append("-prep_only") - if tedana_prog is not None: - cargs.extend([ - "-tedana_prog", - tedana_prog - ]) - if tedana_is_exec: - cargs.append("-tedana_is_exec") - if ted_label is not None: - cargs.extend([ - "-ted_label", - ted_label - ]) - if tedana_opts is not None: - cargs.extend([ - "-tedana_opts", - tedana_opts - ]) - ret = TedanaWrapperPyOutputs( - root=execution.output_file("."), - tedana_output=execution.output_file(results_dir + "/" + prefix + "_ted_output") if (results_dir is not None and prefix is not None) else None, - tedana_report=execution.output_file(results_dir + "/" + prefix + "_tedana_report.txt") if (results_dir is not None and prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TEDANA_WRAPPER_PY_METADATA", - "TedanaWrapperPyOutputs", - "tedana_wrapper_py", -] diff --git a/python/src/niwrap/afni/tfim.py b/python/src/niwrap/afni/tfim.py deleted file mode 100644 index 9898254a0..000000000 --- a/python/src/niwrap/afni/tfim.py +++ /dev/null @@ -1,115 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TFIM_METADATA = Metadata( - id="e112b845a4c25dd82a06881f7a7a51dae6274c19.boutiques", - name="tfim", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class TfimOutputs(typing.NamedTuple): - """ - Output object returned when calling `tfim(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - diff_output: OutputPathType | None - """Difference image output. Default prefix is 'tfim'.""" - tspm_output: OutputPathType | None - """T-statistic of difference. Default prefix is 'tfim'.""" - corr_output: OutputPathType | None - """Equivalent correlation statistic output. Written if -eqcorr is used.""" - - -def tfim( - set1_images: list[InputPathType], - set2_images: list[InputPathType], - prefix: str | None = None, - pthresh: float | None = None, - eqcorr: float | None = None, - paired: bool = False, - base1_value: float | None = None, - runner: Runner | None = None, -) -> TfimOutputs: - """ - MCW TFIM: t-tests on sets of functional images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - set1_images: First set of image files. - set2_images: Second set of image files. - prefix: Prefix for output filenames. Default is 'tfim'. - pthresh: Significance level (per voxel) to threshold the output with.\ - Voxels with t-statistic less significant than this will have their diff\ - output zeroed. Default is no threshold. - eqcorr: Write out the equivalent correlation statistic. The number\ - 'dval' is the value to use for 'dof'. Default is not to write this\ - file. - paired: Compare -set1 and -set2 using a paired sample t-test. Illegal\ - with the -base1 option. - base1_value: Base value for the first set of images. Used for Usage 2. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TfimOutputs`). - """ - if pthresh is not None and not (0 <= pthresh <= 1): - raise ValueError(f"'pthresh' must be between 0 <= x <= 1 but was {pthresh}") - runner = runner or get_global_runner() - execution = runner.start_execution(TFIM_METADATA) - cargs = [] - cargs.append("tfim") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if pthresh is not None: - cargs.extend([ - "-pthresh", - str(pthresh) - ]) - if eqcorr is not None: - cargs.extend([ - "-eqcorr", - str(eqcorr) - ]) - if paired: - cargs.append("-paired") - cargs.extend([ - "-set1", - *[execution.input_file(f) for f in set1_images] - ]) - cargs.extend([ - "-set2", - *[execution.input_file(f) for f in set2_images] - ]) - if base1_value is not None: - cargs.extend([ - "-base1", - str(base1_value) - ]) - ret = TfimOutputs( - root=execution.output_file("."), - diff_output=execution.output_file(prefix + ".diff") if (prefix is not None) else None, - tspm_output=execution.output_file(prefix + ".tspm") if (prefix is not None) else None, - corr_output=execution.output_file(prefix + ".corr") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TFIM_METADATA", - "TfimOutputs", - "tfim", -] diff --git a/python/src/niwrap/afni/timing_tool_py.py b/python/src/niwrap/afni/timing_tool_py.py deleted file mode 100644 index f9925f63a..000000000 --- a/python/src/niwrap/afni/timing_tool_py.py +++ /dev/null @@ -1,183 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TIMING_TOOL_PY_METADATA = Metadata( - id="e72448a163610156059a44280593b8076536b24a.boutiques", - name="timing_tool.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class TimingToolPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `timing_tool_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_timing_file: OutputPathType | None - """Output timing file as specified""" - timing_to_1_d_output: OutputPathType | None - """Output 1D formatted stimulus data""" - - -def timing_tool_py( - timing_file: InputPathType | None = None, - output_file: str | None = None, - run_length: list[float] | None = None, - tr: float | None = None, - offset: float | None = None, - extend_file: InputPathType | None = None, - sort: bool = False, - scale_data: float | None = None, - shift_to_run_offset: float | None = None, - timing_to_1_d_file: str | None = None, - stim_duration: float | None = None, - multi_timing_files: list[InputPathType] | None = None, - multi_show_isi_stats: bool = False, - multi_show_timing: bool = False, - show_timing: bool = False, - multi_stim_duration: list[float] | None = None, - round_times_frac: float | None = None, - truncate_times: bool = False, - multi_timing_event_list: str | None = None, - runner: Runner | None = None, -) -> TimingToolPyOutputs: - """ - Tool for manipulating and evaluating stimulus timing files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - timing_file: Specify a stimulus timing file to load. - output_file: Specify the output timing file. - run_length: Specify the run duration(s), in seconds. - tr: Specify the time resolution in 1D output (in seconds). - offset: Add OFFSET to every time in the main element. - extend_file: Extend timing rows with those in NEW_FILE. - sort: Sort the times, per row (run). - scale_data: Multiply every stim time by SCALAR. - shift_to_run_offset: Shift times so first event is at start of run. - timing_to_1_d_file: Convert stim_times format to stim_file. - stim_duration: Specify the stimulus duration, in seconds. - multi_timing_files: Specify multiple timing files to load. - multi_show_isi_stats: Display timing and ISI statistics for the\ - multiple timing files. - multi_show_timing: Display info on multiple timing elements. - show_timing: Display info on the main timing element. - multi_stim_duration: Specify stimulus duration(s), in seconds, for\ - multiple timing elements. - round_times_frac: Round times to multiples of the TR (0.0 <= FRAC <=\ - 1.0). - truncate_times: Truncate times to multiples of the TR. - multi_timing_event_list: Create an event list file from multiple timing\ - files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TimingToolPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TIMING_TOOL_PY_METADATA) - cargs = [] - cargs.append("timing_tool.py") - if timing_file is not None: - cargs.extend([ - "-timing", - execution.input_file(timing_file) - ]) - if output_file is not None: - cargs.extend([ - "-write_timing", - output_file - ]) - if run_length is not None: - cargs.extend([ - "-run_len", - *map(str, run_length) - ]) - if tr is not None: - cargs.extend([ - "-tr", - str(tr) - ]) - if offset is not None: - cargs.extend([ - "-add_offset", - str(offset) - ]) - if extend_file is not None: - cargs.extend([ - "-extend", - execution.input_file(extend_file) - ]) - if sort: - cargs.append("-sort") - if scale_data is not None: - cargs.extend([ - "-scale_data", - str(scale_data) - ]) - if shift_to_run_offset is not None: - cargs.extend([ - "-shift_to_run_offset", - str(shift_to_run_offset) - ]) - if timing_to_1_d_file is not None: - cargs.extend([ - "-timing_to_1D", - timing_to_1_d_file - ]) - if stim_duration is not None: - cargs.extend([ - "-stim_dur", - str(stim_duration) - ]) - if multi_timing_files is not None: - cargs.extend([ - "-multi_timing", - *[execution.input_file(f) for f in multi_timing_files] - ]) - if multi_show_isi_stats: - cargs.append("-multi_show_isi_stats") - if multi_show_timing: - cargs.append("-multi_show_timing_ele") - if show_timing: - cargs.append("-show_timing_ele") - if multi_stim_duration is not None: - cargs.extend([ - "-multi_stim_dur", - *map(str, multi_stim_duration) - ]) - if round_times_frac is not None: - cargs.extend([ - "-round_times", - str(round_times_frac) - ]) - if truncate_times: - cargs.append("-truncate_times") - if multi_timing_event_list is not None: - cargs.extend([ - "-multi_timing_to_event_list", - multi_timing_event_list - ]) - ret = TimingToolPyOutputs( - root=execution.output_file("."), - output_timing_file=execution.output_file(output_file) if (output_file is not None) else None, - timing_to_1_d_output=execution.output_file(timing_to_1_d_file) if (timing_to_1_d_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TIMING_TOOL_PY_METADATA", - "TimingToolPyOutputs", - "timing_tool_py", -] diff --git a/python/src/niwrap/afni/to3d.py b/python/src/niwrap/afni/to3d.py deleted file mode 100644 index 68a55cb16..000000000 --- a/python/src/niwrap/afni/to3d.py +++ /dev/null @@ -1,302 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TO3D_METADATA = Metadata( - id="fe584b79ebf34b39a3967101b0ec0845d5dc5f6d.boutiques", - name="to3d", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class To3dOutputs(typing.NamedTuple): - """ - Output object returned when calling `to3d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - headfile: OutputPathType | None - """Output AFNI HEAD file""" - brikfile: OutputPathType | None - """Output AFNI BRIK file""" - outfile_outliers: OutputPathType | None - """Outlier count file""" - - -def to3d( - input_files: list[InputPathType], - type_: typing.Literal["spgr", "fse", "epan", "anat", "ct", "spct", "pet", "mra", "bmap", "diff", "omri", "abuc", "fim", "fith", "fico", "fitt", "fift", "fizt", "fict", "fibt", "fibn", "figt", "fipt", "fbuc"] | None = None, - statpar: list[float] | None = None, - prefix: str | None = None, - session: str | None = None, - geomparent: InputPathType | None = None, - anatparent: InputPathType | None = None, - nosave_flag: bool = False, - nowritebrik_flag: bool = False, - view: typing.Literal["orig", "acpc", "tlrc"] | None = None, - time_zt: list[str] | None = None, - time_tz: list[str] | None = None, - tr_units: typing.Literal["ms", "msec", "s", "sec", "Hz", "Hertz"] | None = None, - torg: float | None = None, - x_fov: str | None = None, - y_fov: str | None = None, - z_fov: str | None = None, - x_slab: str | None = None, - y_slab: str | None = None, - z_slab: str | None = None, - zorigin: float | None = None, - data_type: typing.Literal["short", "float", "byte", "complex"] | None = None, - global_scaling_factor: float | None = None, - nofloatscan_flag: bool = False, - in1_flag: bool = False, - orient: str | None = None, - skip_outliers_flag: bool = False, - text_outliers_flag: bool = False, - save_outliers: str | None = None, - assume_dicom_mosaic_flag: bool = False, - oblique_origin_flag: bool = False, - reverse_list_flag: bool = False, - use_last_elem_flag: bool = False, - use_old_mosaic_code_flag: bool = False, - ushort2float_flag: bool = False, - verbose_flag: bool = False, - gamma: float | None = None, - ncolors: float | None = None, - xtwarns_flag: bool = False, - quit_on_err_flag: bool = False, - runner: Runner | None = None, -) -> To3dOutputs: - """ - Creates 3D datasets for use with AFNI from 2D image files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 2D image files. - type_: Declare images to contain data of a given type. - statpar: Supply auxiliary statistical parameters. - prefix: Prefix of the output 3D dataset. - session: Session directory for output 3D dataset. - geomparent: Read geometry data from dataset file. - anatparent: Take anatomy parent from dataset file. - nosave_flag: Suppress autosave of 3D dataset. - nowritebrik_flag: Suppress saving of the BRIK file. - view: Set the dataset's viewing coordinates. - time_zt: Specify time dependent dataset (z-axis first, then t-axis). - time_tz: Specify time dependent dataset (t-axis first, then z-axis). - tr_units: Specify TR units. - torg: Set time origin of dataset. - x_fov: Specify size and orientation of the x-axis extent. - y_fov: Specify size and orientation of the y-axis extent. - z_fov: Specify size and orientation of the z-axis extent. - x_slab: Specify x-axis slab. - y_slab: Specify y-axis slab. - z_slab: Specify z-axis slab. - zorigin: Set the center of the first slice offset in z-axis. - data_type: Set voxel data to be stored as given data type. - global_scaling_factor: Global scaling factor. - nofloatscan_flag: Do not scan for illegal floating point values. - in1_flag: Read and process images one slice at a time. - orient: Set the orientation of the 3D volumes. - skip_outliers_flag: Skip the outlier check for 3D+time datasets. - text_outliers_flag: Only print out the outlier check results in text\ - form. - save_outliers: Save the outliers count into a 1D file. - assume_dicom_mosaic_flag: Assume any Siemens DICOM file is a potential\ - MOSAIC image. - oblique_origin_flag: Assume origin and orientation from oblique\ - transformation matrix. - reverse_list_flag: Reverse the input file list. - use_last_elem_flag: Search DICOM images for the last occurrence of each\ - element. - use_old_mosaic_code_flag: Do not use the Dec 2010 updates to Siemens\ - mosaic code. - ushort2float_flag: Convert input shorts to float and add 2^16 to any\ - negatives. - verbose_flag: Show debugging information for reading DICOM files. - gamma: Gamma correction factor for the monitor. - ncolors: Number of gray levels for the image displays. - xtwarns_flag: Turn on display of Xt warning messages. - quit_on_err_flag: Do not launch interactive to3d mode if input has\ - error. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `To3dOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TO3D_METADATA) - cargs = [] - cargs.append("to3d") - cargs.extend([execution.input_file(f) for f in input_files]) - if type_ is not None: - cargs.extend([ - "-type", - type_ - ]) - if statpar is not None: - cargs.extend([ - "-statpar", - *map(str, statpar) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if session is not None: - cargs.extend([ - "-session", - session - ]) - if geomparent is not None: - cargs.extend([ - "-geomparent", - execution.input_file(geomparent) - ]) - if anatparent is not None: - cargs.extend([ - "-anatparent", - execution.input_file(anatparent) - ]) - if nosave_flag: - cargs.append("-nosave") - if nowritebrik_flag: - cargs.append("-nowritebrik") - if view is not None: - cargs.extend([ - "-view", - view - ]) - if time_zt is not None: - cargs.extend([ - "-time:zt", - *time_zt - ]) - if time_tz is not None: - cargs.extend([ - "-time:tz", - *time_tz - ]) - if tr_units is not None: - cargs.extend([ - "-t", - tr_units - ]) - if torg is not None: - cargs.extend([ - "-Torg", - str(torg) - ]) - if x_fov is not None: - cargs.extend([ - "-xFOV", - x_fov - ]) - if y_fov is not None: - cargs.extend([ - "-yFOV", - y_fov - ]) - if z_fov is not None: - cargs.extend([ - "-zFOV", - z_fov - ]) - if x_slab is not None: - cargs.extend([ - "-xSLAB", - x_slab - ]) - if y_slab is not None: - cargs.extend([ - "-ySLAB", - y_slab - ]) - if z_slab is not None: - cargs.extend([ - "-zSLAB", - z_slab - ]) - if zorigin is not None: - cargs.extend([ - "-zorigin", - str(zorigin) - ]) - if data_type is not None: - cargs.extend([ - "-datum", - data_type - ]) - if global_scaling_factor is not None: - cargs.extend([ - "-gsfac", - str(global_scaling_factor) - ]) - if nofloatscan_flag: - cargs.append("-nofloatscan") - if in1_flag: - cargs.append("-in:1") - if orient is not None: - cargs.extend([ - "-orient", - orient - ]) - if skip_outliers_flag: - cargs.append("-skip_outliers") - if text_outliers_flag: - cargs.append("-text_outliers") - if save_outliers is not None: - cargs.extend([ - "-save_outliers", - save_outliers - ]) - if assume_dicom_mosaic_flag: - cargs.append("-assume_dicom_mosaic") - if oblique_origin_flag: - cargs.append("-oblique_origin") - if reverse_list_flag: - cargs.append("-reverse_list") - if use_last_elem_flag: - cargs.append("-use_last_elem") - if use_old_mosaic_code_flag: - cargs.append("-use_old_mosaic_code") - if ushort2float_flag: - cargs.append("-ushort2float") - if verbose_flag: - cargs.append("-verb") - if gamma is not None: - cargs.extend([ - "-gamma", - str(gamma) - ]) - if ncolors is not None: - cargs.extend([ - "-ncolors", - str(ncolors) - ]) - if xtwarns_flag: - cargs.append("-xtwarns") - if quit_on_err_flag: - cargs.append("-quit_on_err") - ret = To3dOutputs( - root=execution.output_file("."), - headfile=execution.output_file(prefix + ".HEAD") if (prefix is not None) else None, - brikfile=execution.output_file(prefix + ".BRIK") if (prefix is not None) else None, - outfile_outliers=execution.output_file(save_outliers) if (save_outliers is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TO3D_METADATA", - "To3dOutputs", - "to3d", -] diff --git a/python/src/niwrap/afni/tokens.py b/python/src/niwrap/afni/tokens.py deleted file mode 100644 index dc1d82a86..000000000 --- a/python/src/niwrap/afni/tokens.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TOKENS_METADATA = Metadata( - id="3ea97bfd7ad70145baf8725309d723e73b54f8c9.boutiques", - name="tokens", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class TokensOutputs(typing.NamedTuple): - """ - Output object returned when calling `tokens(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def tokens( - infile: InputPathType | None = None, - extra_char: list[str] | None = None, - runner: Runner | None = None, -) -> TokensOutputs: - """ - Token counting tool. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Specify input file (stdin if none). - extra_char: Specify extra character to count as valid. Can be used more\ - than once. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TokensOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TOKENS_METADATA) - cargs = [] - cargs.append("tokens") - if infile is not None: - cargs.extend([ - "-infile", - execution.input_file(infile) - ]) - if extra_char is not None: - cargs.extend([ - "-extra", - *extra_char - ]) - ret = TokensOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TOKENS_METADATA", - "TokensOutputs", - "tokens", -] diff --git a/python/src/niwrap/afni/trr.py b/python/src/niwrap/afni/trr.py deleted file mode 100644 index 7e19ab473..000000000 --- a/python/src/niwrap/afni/trr.py +++ /dev/null @@ -1,188 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TRR_METADATA = Metadata( - id="1b3c1e99291c33c3c4ba5b8a06a1cdc93b98a900.boutiques", - name="TRR", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class TrrOutputs(typing.NamedTuple): - """ - Output object returned when calling `trr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file_txt: OutputPathType - """Main output file containing inference information for effects of - interest""" - output_file_pdf: OutputPathType - """Density plot of the TRR distribution""" - output_file_rdata: OutputPathType - """Saved R data in binary format for post hoc processing""" - - -def trr( - prefix: str, - response_var: str, - subject_var: str, - data_table: InputPathType, - chains: float | None = None, - iterations: float | None = None, - repetition_var: str | None = None, - condition_var: str | None = None, - categorical_vars: str | None = None, - quantitative_vars: str | None = None, - response_dist: str | None = None, - model: str | None = None, - plot_size: list[float] | None = None, - standard_error: str | None = None, - t_stat: str | None = None, - within_chain_parallelization: float | None = None, - debug: bool = False, - verbose: float | None = None, - runner: Runner | None = None, -) -> TrrOutputs: - """ - Test-Retest Reliability Program through Bayesian Multilevel Modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output file names. - response_var: Specify the column name for the response variable. - subject_var: Specify the column name for the subject variable. - data_table: Specify the path to the data table in pure text format. - chains: Specify the number of Markov chains. - iterations: Specify the number of iterations per Markov chain. - repetition_var: Specify the column name for the repetition variable. - condition_var: Specify the column name for the condition variable. - categorical_vars: Identify categorical (qualitative) variables. - quantitative_vars: Identify quantitative (covariate) variables. - response_dist: Specify the distribution for the response variable\ - (e.g., 'gaussian', 'student', 'exgaussian'). - model: Specify the effects associated with explanatory variables. - plot_size: Specify the layout of posterior distribution plot (PDP) with\ - width and height in inches. - standard_error: Include standard error for the response variable as\ - input. - t_stat: Specify the column name for the t-statistic values. - within_chain_parallelization: Invoke within-chain parallelization;\ - specify number of threads per chain. - debug: Enable R to save the parameters for debugging. - verbose: Specify verbose level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TrrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TRR_METADATA) - cargs = [] - cargs.append("TRR") - cargs.extend([ - "-prefix", - prefix - ]) - if chains is not None: - cargs.extend([ - "-chains", - str(chains) - ]) - if iterations is not None: - cargs.extend([ - "-iterations", - str(iterations) - ]) - cargs.extend([ - "-Y", - response_var - ]) - cargs.extend([ - "-subject", - subject_var - ]) - if repetition_var is not None: - cargs.extend([ - "-repetition", - repetition_var - ]) - if condition_var is not None: - cargs.extend([ - "-condition", - condition_var - ]) - cargs.extend([ - "-dataTable", - execution.input_file(data_table) - ]) - if categorical_vars is not None: - cargs.extend([ - "-cVars", - categorical_vars - ]) - if quantitative_vars is not None: - cargs.extend([ - "-qVars", - quantitative_vars - ]) - if response_dist is not None: - cargs.extend([ - "-distY", - response_dist - ]) - if model is not None: - cargs.extend([ - "-model", - model - ]) - if plot_size is not None: - cargs.extend([ - "-PDP", - *map(str, plot_size) - ]) - if standard_error is not None: - cargs.extend([ - "-se", - standard_error - ]) - if t_stat is not None: - cargs.extend([ - "-tstat", - t_stat - ]) - if within_chain_parallelization is not None: - cargs.extend([ - "-WCP", - str(within_chain_parallelization) - ]) - if debug: - cargs.append("-dbgArgs") - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - ret = TrrOutputs( - root=execution.output_file("."), - output_file_txt=execution.output_file(prefix + ".txt"), - output_file_pdf=execution.output_file(prefix + ".pdf"), - output_file_rdata=execution.output_file(prefix + ".RData"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TRR_METADATA", - "TrrOutputs", - "trr", -] diff --git a/python/src/niwrap/afni/uber_align_test_py.py b/python/src/niwrap/afni/uber_align_test_py.py deleted file mode 100644 index b88416a5a..000000000 --- a/python/src/niwrap/afni/uber_align_test_py.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UBER_ALIGN_TEST_PY_METADATA = Metadata( - id="1cdb35a694ecfd6f154d70ecf75d0b5138262e0f.boutiques", - name="uber_align_test.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UberAlignTestPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `uber_align_test_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def uber_align_test_py( - no_gui: bool = False, - print_script: bool = False, - save_script: str | None = None, - user_variable: list[str] | None = None, - qt_opts: str | None = None, - help_: bool = False, - help_gui: bool = False, - history: bool = False, - show_valid_opts: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> UberAlignTestPyOutputs: - """ - Generate script to test anatomical/EPI alignment. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - no_gui: Run without the graphical user interface (GUI). - print_script: Print the generated script to standard output. - save_script: Save the generated script to the specified file. - user_variable: Specify user variables for alignment. - qt_opts: Pass PyQt4 options directly to the GUI. - help_: Show help information. - help_gui: Show help information for the GUI. - history: Show command history. - show_valid_opts: Show valid options. - version: Show version information. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UberAlignTestPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UBER_ALIGN_TEST_PY_METADATA) - cargs = [] - cargs.append("uber_align_test.py") - if no_gui: - cargs.append("-no_gui") - if print_script: - cargs.append("-print_script") - if save_script is not None: - cargs.extend([ - "-save_script", - save_script - ]) - if user_variable is not None: - cargs.extend([ - "-uvar", - *user_variable - ]) - if qt_opts is not None: - cargs.extend([ - "-qt_opts", - qt_opts - ]) - if help_: - cargs.append("-help") - if help_gui: - cargs.append("-help_gui") - if history: - cargs.append("-hist") - if show_valid_opts: - cargs.append("-show_valid_opts") - if version: - cargs.append("-ver") - ret = UberAlignTestPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UBER_ALIGN_TEST_PY_METADATA", - "UberAlignTestPyOutputs", - "uber_align_test_py", -] diff --git a/python/src/niwrap/afni/uber_proc_py.py b/python/src/niwrap/afni/uber_proc_py.py deleted file mode 100644 index a4189dda6..000000000 --- a/python/src/niwrap/afni/uber_proc_py.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UBER_PROC_PY_METADATA = Metadata( - id="810164b90b5470d8a01aa9ff880068dc2dfc8cc0.boutiques", - name="uber_proc.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UberProcPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `uber_proc_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def uber_proc_py( - results_dir: str | None = None, - runner: Runner | None = None, -) -> UberProcPyOutputs: - """ - Uber processing tool - work in progress. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - results_dir: Directory where results will be placed. Default is a new\ - 'uber_results' directory in the current working directory. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UberProcPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UBER_PROC_PY_METADATA) - cargs = [] - cargs.append("uber_proc.py") - if results_dir is not None: - cargs.append(results_dir) - ret = UberProcPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UBER_PROC_PY_METADATA", - "UberProcPyOutputs", - "uber_proc_py", -] diff --git a/python/src/niwrap/afni/uber_skel.py b/python/src/niwrap/afni/uber_skel.py deleted file mode 100644 index 722cefd4a..000000000 --- a/python/src/niwrap/afni/uber_skel.py +++ /dev/null @@ -1,109 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UBER_SKEL_METADATA = Metadata( - id="d77a80fc9ecd09ed285b440328c53e4f45eb7735.boutiques", - name="uber_skel", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UberSkelOutputs(typing.NamedTuple): - """ - Output object returned when calling `uber_skel(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def uber_skel( - qt_options: str | None = None, - no_gui_flag: bool = False, - print_script: bool = False, - save_script: str | None = None, - user_var: list[str] | None = None, - help_howto_program: bool = False, - help_: bool = False, - help_gui: bool = False, - history: bool = False, - show_valid_opts: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> UberSkelOutputs: - """ - Sample uber processing program for initializing user and control variables, with - options for both GUI and non-GUI modes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - qt_options: Pass PyQt4 options directly to the GUI. - no_gui_flag: Run without the GUI. - print_script: Print the script. - save_script: Save the script. - user_var: Initialize user variables. Usage: -uvar . - help_howto_program: Show programming comments. - help_: Show help. - help_gui: Show help for the GUI. - history: Show history. - show_valid_opts: Show valid options. - version: Show version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UberSkelOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UBER_SKEL_METADATA) - cargs = [] - cargs.append("uber_skel.py") - if qt_options is not None: - cargs.extend([ - "-qt_opts", - qt_options - ]) - if no_gui_flag: - cargs.append("-no_gui") - if print_script: - cargs.append("-print_script") - if save_script is not None: - cargs.extend([ - "-save_script", - save_script - ]) - if user_var is not None: - cargs.extend([ - "-uvar", - *user_var - ]) - if help_howto_program: - cargs.append("-help_howto_program") - if help_: - cargs.append("-help") - if help_gui: - cargs.append("-help_gui") - if history: - cargs.append("-hist") - if show_valid_opts: - cargs.append("-show_valid_opts") - if version: - cargs.append("-ver") - ret = UberSkelOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UBER_SKEL_METADATA", - "UberSkelOutputs", - "uber_skel", -] diff --git a/python/src/niwrap/afni/uber_subject_py.py b/python/src/niwrap/afni/uber_subject_py.py deleted file mode 100644 index 0c90dc4bd..000000000 --- a/python/src/niwrap/afni/uber_subject_py.py +++ /dev/null @@ -1,344 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UBER_SUBJECT_PY_METADATA = Metadata( - id="d4f27b8c1311827036baefee6a5e5f22311c1cf3.boutiques", - name="uber_subject.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UberSubjectPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `uber_subject_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def uber_subject_py( - qt_opts: str | None = None, - svar: str | None = None, - cvar: str | None = None, - no_gui: bool = False, - print_ap_command: bool = False, - save_ap_command: str | None = None, - exec_ap_command: bool = False, - exec_proc_script: bool = False, - align_cost: str | None = None, - align_giant_move: str | None = None, - align_opts_aea: str | None = None, - anal_domain: str | None = None, - anal_type: str | None = None, - anat: InputPathType | None = None, - anat_has_skull: str | None = None, - blocks: str | None = None, - blur_size: float | None = None, - epi: str | None = None, - epi_wildcard: str | None = None, - gid: str | None = None, - gltsym: str | None = None, - gltsym_label: str | None = None, - motion_limit: float | None = None, - outlier_limit: float | None = None, - regress_goforit: float | None = None, - regress_bandpass: str | None = None, - regress_jobs: float | None = None, - regress_mot_deriv: str | None = None, - regress_opts_3d_d: str | None = None, - reml_exec: str | None = None, - run_clustsim: str | None = None, - sid: str | None = None, - stim: InputPathType | None = None, - stim_basis: str | None = None, - stim_label: str | None = None, - stim_type: str | None = None, - stim_wildcard: str | None = None, - tcat_nfirst: float | None = None, - tlrc_base: str | None = None, - tlrc_ok_maxite: str | None = None, - tlrc_opts_at: str | None = None, - volreg_base: str | None = None, - verb: str | None = None, - runner: Runner | None = None, -) -> UberSubjectPyOutputs: - """ - Graphical interface to afni_proc.py. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - qt_opts: Pass options to PyQt4. - svar: Set subject variable to value. - cvar: Set control variable to value. - no_gui: Do not open graphical interface. - print_ap_command: Show afni_proc.py script. - save_ap_command: Save afni_proc.py script. - exec_ap_command: Run afni_proc.py command. - exec_proc_script: Run proc script. - align_cost: Specify cost function for anat/EPI alignment. - align_giant_move: Use -giant_move in AEA.py. - align_opts_aea: Specify extra options for align_epi_anat.py. - anal_domain: Set data domain (volume/rest). - anal_type: Set analysis type (task/rest). - anat: Set anatomical dataset name. - anat_has_skull: Whether anat has skull (yes/no). - blocks: Set list of processing blocks to apply. - blur_size: Set blur size in mm. - epi: Set list of EPI datasets. - epi_wildcard: Use wildcard for EPI datasets (yes/no). - gid: Set group ID. - gltsym: Specify list of symbolic GLTs. - gltsym_label: Set corresponding GLT labels. - motion_limit: Set per-TR motion limit in mm. - outlier_limit: Specify outlier limit for censoring. - regress_goforit: Set GOFORIT level in 3dDeconvolve. - regress_bandpass: Specify bandpass limits to remain after regress. - regress_jobs: Number of jobs to use in 3dDeconvolve. - regress_mot_deriv: Regress motion derivatives (yes/no). - regress_opts_3d_d: Specify extra options for 3dDeconvolve. - reml_exec: Run 3dREMLfit (yes/no). - run_clustsim: Run 3dClustSim (yes/no). - sid: Set subject ID. - stim: Set list of stim timing files. - stim_basis: Set basis functions for stim classes. - stim_label: Set stim file labels. - stim_type: Set stim types for stim classes. - stim_wildcard: Use wildcard for stim files (yes/no). - tcat_nfirst: Set number of TRs to remove per run. - tlrc_base: Specify anat for standard space alignment. - tlrc_ok_maxite: Pass -OK_maxite to @auto_tlrc (yes/no). - tlrc_opts_at: Specify extra options for @auto_tlrc. - volreg_base: Set volreg base string (first/third/last). - verb: Set verbose level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UberSubjectPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UBER_SUBJECT_PY_METADATA) - cargs = [] - cargs.append("uber_subject.py") - if qt_opts is not None: - cargs.extend([ - "-qt_opts", - qt_opts - ]) - if svar is not None: - cargs.extend([ - "-svar", - svar - ]) - if cvar is not None: - cargs.extend([ - "-cvar", - cvar - ]) - if no_gui: - cargs.append("-no_gui") - if print_ap_command: - cargs.append("-print_ap_command") - if save_ap_command is not None: - cargs.extend([ - "-save_ap_command", - save_ap_command - ]) - if exec_ap_command: - cargs.append("-exec_ap_command") - if exec_proc_script: - cargs.append("-exec_proc_script") - if align_cost is not None: - cargs.extend([ - "-align_cost", - align_cost - ]) - if align_giant_move is not None: - cargs.extend([ - "-align_giant_move", - align_giant_move - ]) - if align_opts_aea is not None: - cargs.extend([ - "-align_opts_aea", - align_opts_aea - ]) - if anal_domain is not None: - cargs.extend([ - "-anal_domain", - anal_domain - ]) - if anal_type is not None: - cargs.extend([ - "-anal_type", - anal_type - ]) - if anat is not None: - cargs.extend([ - "-anat", - execution.input_file(anat) - ]) - if anat_has_skull is not None: - cargs.extend([ - "-anat_has_skull", - anat_has_skull - ]) - if blocks is not None: - cargs.extend([ - "-blocks", - blocks - ]) - if blur_size is not None: - cargs.extend([ - "-blur_size", - str(blur_size) - ]) - if epi is not None: - cargs.extend([ - "-epi", - epi - ]) - if epi_wildcard is not None: - cargs.extend([ - "-epi_wildcard", - epi_wildcard - ]) - if gid is not None: - cargs.extend([ - "-gid", - gid - ]) - if gltsym is not None: - cargs.extend([ - "-gltsym", - gltsym - ]) - if gltsym_label is not None: - cargs.extend([ - "-gltsym_label", - gltsym_label - ]) - if motion_limit is not None: - cargs.extend([ - "-motion_limit", - str(motion_limit) - ]) - if outlier_limit is not None: - cargs.extend([ - "-outlier_limit", - str(outlier_limit) - ]) - if regress_goforit is not None: - cargs.extend([ - "-regress_GOFORIT", - str(regress_goforit) - ]) - if regress_bandpass is not None: - cargs.extend([ - "-regress_bandpass", - regress_bandpass - ]) - if regress_jobs is not None: - cargs.extend([ - "-regress_jobs", - str(regress_jobs) - ]) - if regress_mot_deriv is not None: - cargs.extend([ - "-regress_mot_deriv", - regress_mot_deriv - ]) - if regress_opts_3d_d is not None: - cargs.extend([ - "-regress_opts_3dD", - regress_opts_3d_d - ]) - if reml_exec is not None: - cargs.extend([ - "-reml_exec", - reml_exec - ]) - if run_clustsim is not None: - cargs.extend([ - "-run_clustsim", - run_clustsim - ]) - if sid is not None: - cargs.extend([ - "-sid", - sid - ]) - if stim is not None: - cargs.extend([ - "-stim", - execution.input_file(stim) - ]) - if stim_basis is not None: - cargs.extend([ - "-stim_basis", - stim_basis - ]) - if stim_label is not None: - cargs.extend([ - "-stim_label", - stim_label - ]) - if stim_type is not None: - cargs.extend([ - "-stim_type", - stim_type - ]) - if stim_wildcard is not None: - cargs.extend([ - "-stim_wildcard", - stim_wildcard - ]) - if tcat_nfirst is not None: - cargs.extend([ - "-tcat_nfirst", - str(tcat_nfirst) - ]) - if tlrc_base is not None: - cargs.extend([ - "-tlrc_base", - tlrc_base - ]) - if tlrc_ok_maxite is not None: - cargs.extend([ - "-tlrc_ok_maxite", - tlrc_ok_maxite - ]) - if tlrc_opts_at is not None: - cargs.extend([ - "-tlrc_opts_at", - tlrc_opts_at - ]) - if volreg_base is not None: - cargs.extend([ - "-volreg_base", - volreg_base - ]) - if verb is not None: - cargs.extend([ - "-verb", - verb - ]) - ret = UberSubjectPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UBER_SUBJECT_PY_METADATA", - "UberSubjectPyOutputs", - "uber_subject_py", -] diff --git a/python/src/niwrap/afni/un_warp_epi_py.py b/python/src/niwrap/afni/un_warp_epi_py.py deleted file mode 100644 index 6427ed697..000000000 --- a/python/src/niwrap/afni/un_warp_epi_py.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UN_WARP_EPI_PY_METADATA = Metadata( - id="64490c716682191e7b0bb31a5b8428c65b5c5a38.boutiques", - name="unWarpEPI.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UnWarpEpiPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `un_warp_epi_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def un_warp_epi_py( - forward: InputPathType, - reverse: InputPathType, - anat4warp: InputPathType, - data: str, - subj_id: str, - giant_move: bool = False, - runner: Runner | None = None, -) -> UnWarpEpiPyOutputs: - """ - Routine to unwarp EPI data set using another data set with opposite polarity. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - forward: Calibration matching data to be corrected. - reverse: Calibration with opposing polarity to data to be corrected. - anat4warp: Reference anatomical dataset. - data: Data to be corrected (same polarity as forward calibration data).\ - Separate with commas if specifying multiple datasets. - subj_id: ID of subject to be corrected. - giant_move: Set giant_move option for align_epi_anat if final align of\ - anatomy to corrected EPI fails if datasets are far apart in space. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UnWarpEpiPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UN_WARP_EPI_PY_METADATA) - cargs = [] - cargs.append("unWarpEPI.py") - cargs.append("-f") - cargs.extend([ - "-f", - execution.input_file(forward) - ]) - cargs.append("-r") - cargs.extend([ - "-r", - execution.input_file(reverse) - ]) - cargs.append("-a") - cargs.extend([ - "-a", - execution.input_file(anat4warp) - ]) - cargs.append("-d") - cargs.extend([ - "-d", - data - ]) - cargs.append("-s") - cargs.extend([ - "-s", - subj_id - ]) - if giant_move: - cargs.append("-g") - ret = UnWarpEpiPyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UN_WARP_EPI_PY_METADATA", - "UnWarpEpiPyOutputs", - "un_warp_epi_py", -] diff --git a/python/src/niwrap/afni/uniq_images.py b/python/src/niwrap/afni/uniq_images.py deleted file mode 100644 index 40b44717f..000000000 --- a/python/src/niwrap/afni/uniq_images.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -UNIQ_IMAGES_METADATA = Metadata( - id="78da67a816d6d0b1ae55b072a61c7cc76bbe87da.boutiques", - name="uniq_images", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class UniqImagesOutputs(typing.NamedTuple): - """ - Output object returned when calling `uniq_images(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - unique_files_list: OutputPathType - """Generated list of filenames with unique images""" - - -def uniq_images( - input_files: list[InputPathType], - runner: Runner | None = None, -) -> UniqImagesOutputs: - """ - Simple program to read in a list of image filenames, determine which files have - unique images inside, and echo out only a list of the filenames with unique - images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: List of image filenames to be processed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `UniqImagesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(UNIQ_IMAGES_METADATA) - cargs = [] - cargs.append("uniq_images") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = UniqImagesOutputs( - root=execution.output_file("."), - unique_files_list=execution.output_file("unique_images_list.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "UNIQ_IMAGES_METADATA", - "UniqImagesOutputs", - "uniq_images", -] diff --git a/python/src/niwrap/afni/v_1d_apar2mat.py b/python/src/niwrap/afni/v_1d_apar2mat.py deleted file mode 100644 index d3fc675ca..000000000 --- a/python/src/niwrap/afni/v_1d_apar2mat.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_APAR2MAT_METADATA = Metadata( - id="ca46e845c2aeb2bfc0d1ca66f53ca7adef2d7e64.boutiques", - name="1dApar2mat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dApar2matOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_apar2mat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1d_apar2mat( - x_shift: float, - y_shift: float, - z_shift: float, - z_angle: float, - x_angle: float, - y_angle: float, - x_scale: float, - y_scale: float, - z_scale: float, - y_x_shear: float, - z_x_shear: float, - z_y_shear: float, - runner: Runner | None = None, -) -> V1dApar2matOutputs: - """ - Computes the affine transformation matrix from the set of 3dAllineate - parameters. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - x_shift: x-shift in mm. - y_shift: y-shift in mm. - z_shift: z-shift in mm. - z_angle: z-angle (roll) in degrees. - x_angle: x-angle (pitch) in degrees. - y_angle: y-angle (yaw) in degrees. - x_scale: x-scale factor in [0.10,10.0]. - y_scale: y-scale factor in [0.10,10.0]. - z_scale: z-scale factor in [0.10,10.0]. - y_x_shear: y/x-shear factor in [-0.3333,0.3333]. - z_x_shear: z/x-shear factor in [-0.3333,0.3333]. - z_y_shear: z/y-shear factor in [-0.3333,0.3333]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dApar2matOutputs`). - """ - if not (0.1 <= x_scale <= 10.0): - raise ValueError(f"'x_scale' must be between 0.1 <= x <= 10.0 but was {x_scale}") - if not (0.1 <= y_scale <= 10.0): - raise ValueError(f"'y_scale' must be between 0.1 <= x <= 10.0 but was {y_scale}") - if not (0.1 <= z_scale <= 10.0): - raise ValueError(f"'z_scale' must be between 0.1 <= x <= 10.0 but was {z_scale}") - if not (-0.3333 <= y_x_shear <= 0.3333): - raise ValueError(f"'y_x_shear' must be between -0.3333 <= x <= 0.3333 but was {y_x_shear}") - if not (-0.3333 <= z_x_shear <= 0.3333): - raise ValueError(f"'z_x_shear' must be between -0.3333 <= x <= 0.3333 but was {z_x_shear}") - if not (-0.3333 <= z_y_shear <= 0.3333): - raise ValueError(f"'z_y_shear' must be between -0.3333 <= x <= 0.3333 but was {z_y_shear}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_APAR2MAT_METADATA) - cargs = [] - cargs.append("1dApar2mat") - cargs.append(str(x_shift)) - cargs.append(str(y_shift)) - cargs.append(str(z_shift)) - cargs.append(str(z_angle)) - cargs.append(str(x_angle)) - cargs.append(str(y_angle)) - cargs.append(str(x_scale)) - cargs.append(str(y_scale)) - cargs.append(str(z_scale)) - cargs.append(str(y_x_shear)) - cargs.append(str(z_x_shear)) - cargs.append(str(z_y_shear)) - ret = V1dApar2matOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dApar2matOutputs", - "V_1D_APAR2MAT_METADATA", - "v_1d_apar2mat", -] diff --git a/python/src/niwrap/afni/v_1d_astrip.py b/python/src/niwrap/afni/v_1d_astrip.py deleted file mode 100644 index fd34a1e78..000000000 --- a/python/src/niwrap/afni/v_1d_astrip.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_ASTRIP_METADATA = Metadata( - id="ea5f26ed07e83433aaff1882a3ae80d4c15231c8.boutiques", - name="1dAstrip", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dAstripOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_astrip(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file with only numeric characters.""" - - -def v_1d_astrip( - infile: InputPathType, - runner: Runner | None = None, -) -> V1dAstripOutputs: - """ - Strips non-numeric characters from a file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file from which non-numeric characters will be stripped. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dAstripOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_ASTRIP_METADATA) - cargs = [] - cargs.append("1dAstrip") - cargs.append("< " + execution.input_file(infile)) - ret = V1dAstripOutputs( - root=execution.output_file("."), - outfile=execution.output_file("[OUTPUT_FILE]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dAstripOutputs", - "V_1D_ASTRIP_METADATA", - "v_1d_astrip", -] diff --git a/python/src/niwrap/afni/v_1d_bandpass.py b/python/src/niwrap/afni/v_1d_bandpass.py deleted file mode 100644 index 5d864d169..000000000 --- a/python/src/niwrap/afni/v_1d_bandpass.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_BANDPASS_METADATA = Metadata( - id="69b4e08ff33a85a01f56df929195839c7c7f9208.boutiques", - name="1dBandpass", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dBandpassOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_bandpass(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1d_bandpass( - fbot: float, - ftop: float, - infile: InputPathType, - timestep: float | None = None, - ortfile: InputPathType | None = None, - nodetrend: bool = False, - norm: bool = False, - runner: Runner | None = None, -) -> V1dBandpassOutputs: - """ - Bandpass filtering of time series data in AFNI *.1D files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fbot: Lowest frequency in the passband, in Hz (must be greater than or\ - equal to 0). - ftop: Highest frequency in the passband, in Hz (must be greater than\ - FBOT). - infile: Input AFNI *.1D file; each column is processed. - timestep: Set time step to 'dd' sec (default is 1.0). - ortfile: Also orthogonalize input to columns in specified *.1D file\ - (only one '-ort' option is allowed). - nodetrend: Skip the quadratic detrending of the input. - norm: Make output time series have L2 norm = 1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dBandpassOutputs`). - """ - if not (0 <= fbot): - raise ValueError(f"'fbot' must be greater than 0 <= x but was {fbot}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_BANDPASS_METADATA) - cargs = [] - cargs.append("1dBandpass") - cargs.append(str(fbot)) - cargs.append(str(ftop)) - cargs.append(execution.input_file(infile)) - if timestep is not None: - cargs.extend([ - "-dt", - str(timestep) - ]) - if ortfile is not None: - cargs.extend([ - "-ort", - execution.input_file(ortfile) - ]) - if nodetrend: - cargs.append("-nodetrend") - if norm: - cargs.append("-norm") - ret = V1dBandpassOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dBandpassOutputs", - "V_1D_BANDPASS_METADATA", - "v_1d_bandpass", -] diff --git a/python/src/niwrap/afni/v_1d_bport.py b/python/src/niwrap/afni/v_1d_bport.py deleted file mode 100644 index 4ab833b48..000000000 --- a/python/src/niwrap/afni/v_1d_bport.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_BPORT_METADATA = Metadata( - id="79bac243ab40da21c48aba385d1738323fa2e271.boutiques", - name="1dBport", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dBportOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_bport(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout: OutputPathType - """Standard output file written by the tool""" - - -def v_1d_bport( - band: list[float], - invert: bool = False, - noconst: bool = False, - quad: bool = False, - input_dataset: InputPathType | None = None, - input_1d_file: InputPathType | None = None, - nodata: list[float] | None = None, - tr: float | None = None, - concat: InputPathType | None = None, - runner: Runner | None = None, -) -> V1dBportOutputs: - """ - Creates a set of columns of sines and cosines for bandpassing via regression. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - band: Specify lowest and highest frequencies in the passband. - invert: Invert the selection after computing which frequency indexes\ - correspond to the input band(s). - noconst: Same as -nozero. Do NOT generate the 0 frequency (constant)\ - component when fbot = 0. - quad: Add regressors for linear and quadratic trends. - input_dataset: Specify the dataset input. - input_1d_file: Specify the 1D input file. - nodata: Specify the number of time points and optionally TR value for\ - the simulation. - tr: Set the time step duration. - concat: Specify the list of start indexes for concatenated runs. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dBportOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_BPORT_METADATA) - cargs = [] - cargs.append("1dBport") - cargs.extend([ - "-band", - *map(str, band) - ]) - if invert: - cargs.append("-invert") - if noconst: - cargs.append("-noconst") - if quad: - cargs.append("-quad") - if input_dataset is not None: - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if input_1d_file is not None: - cargs.extend([ - "-input1D", - execution.input_file(input_1d_file) - ]) - if nodata is not None: - cargs.extend([ - "-nodata", - *map(str, nodata) - ]) - if tr is not None: - cargs.extend([ - "-TR", - str(tr) - ]) - if concat is not None: - cargs.extend([ - "-concat", - execution.input_file(concat) - ]) - ret = V1dBportOutputs( - root=execution.output_file("."), - stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dBportOutputs", - "V_1D_BPORT_METADATA", - "v_1d_bport", -] diff --git a/python/src/niwrap/afni/v_1d_correlate.py b/python/src/niwrap/afni/v_1d_correlate.py deleted file mode 100644 index cf84b5dd8..000000000 --- a/python/src/niwrap/afni/v_1d_correlate.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_CORRELATE_METADATA = Metadata( - id="98a6695a8bc372660a7916494450722774fd95c4.boutiques", - name="1dCorrelate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dCorrelateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_correlate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1d_correlate( - input_files: list[InputPathType], - ktaub: bool = False, - nboot: float | None = None, - alpha: float | None = None, - blk: bool = False, - runner: Runner | None = None, -) -> V1dCorrelateOutputs: - """ - 1dCorrelate calculates the correlation coefficients between columns of input 1D - files along with confidence intervals via a bootstrap procedure. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 1D files. - ktaub: Kendall's tau_b correlation (popular somewhere, maybe). - nboot: Set the number of bootstrap replicates. - alpha: Set the 2-sided confidence interval width to '100-A' percent. - blk: Alternate flag for variable-length block resampling. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dCorrelateOutputs`). - """ - if alpha is not None and not (1 <= alpha <= 20): - raise ValueError(f"'alpha' must be between 1 <= x <= 20 but was {alpha}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_CORRELATE_METADATA) - cargs = [] - cargs.append("1dCorrelate") - if ktaub: - cargs.append("-Ktaub") - if nboot is not None: - cargs.extend([ - "-nboot", - str(nboot) - ]) - if alpha is not None: - cargs.extend([ - "-alpha", - str(alpha) - ]) - if blk: - cargs.append("-blk") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V1dCorrelateOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dCorrelateOutputs", - "V_1D_CORRELATE_METADATA", - "v_1d_correlate", -] diff --git a/python/src/niwrap/afni/v_1d_dw_grad_o_mat__.py b/python/src/niwrap/afni/v_1d_dw_grad_o_mat__.py deleted file mode 100644 index 0dab9b8c0..000000000 --- a/python/src/niwrap/afni/v_1d_dw_grad_o_mat__.py +++ /dev/null @@ -1,194 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_DW_GRAD_O_MAT___METADATA = Metadata( - id="46eee009ed5251cf0654dc7e2305bcbaecf3782b.boutiques", - name="1dDW_Grad_o_Mat++", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dDwGradOMatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_dw_grad_o_mat__(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file of gradients or matrices""" - out_row_bval_file: OutputPathType | None - """Output b-values file in a single row""" - out_col_bval_file: OutputPathType | None - """Output b-values file in a single column""" - - -def v_1d_dw_grad_o_mat__( - in_row_vec: InputPathType, - in_col_vec: InputPathType, - in_col_mat_a: InputPathType, - in_col_mat_t: InputPathType, - out_row_vec: str, - out_col_vec: str, - out_col_mat_a: str, - out_col_mat_t: str, - flip_x: bool = False, - flip_y: bool = False, - flip_z: bool = False, - no_flip: bool = False, - in_bvals: InputPathType | None = None, - out_col_bval: bool = False, - out_row_bval_sep: str | None = None, - out_col_bval_sep: str | None = None, - unit_mag_out: bool = False, - check_abs_min: float | None = None, - bref_mean_top: bool = False, - put_zeros_top: bool = False, - bmax_ref: float | None = None, - runner: Runner | None = None, -) -> V1dDwGradOMatOutputs: - """ - Manipulation of diffusion-weighted (DW) gradient vector files, b-value files, - and b- or g-matrices with various input and output configurations. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_row_vec: Input file of 3 rows of gradients (e.g., dcm2nii-format\ - output). - in_col_vec: Input file of 3 columns of gradients. - in_col_mat_a: Input file of 6 columns of b- or g-matrix in 'A(FNI)'\ - diagonal first format. - in_col_mat_t: Input file of 6 columns of b- or g-matrix in 'T(ORTOISE)'\ - row first format. - out_row_vec: Output file of 3 rows of gradients. - out_col_vec: Output file of 3 columns of gradients. - out_col_mat_a: Output file of 6 columns of b- or g-matrix in 'A(FNI)'\ - diagonal first format. - out_col_mat_t: Output file of 6 columns of b- or g-matrix in\ - 'T(ORTOISE)' row first format. - flip_x: Change sign of first column of gradients (or of the x-component\ - parts of the matrix). - flip_y: Change sign of second column of gradients (or of the\ - y-component parts of the matrix). - flip_z: Change sign of third column of gradients (or of the z-component\ - parts of the matrix). - no_flip: Don't change any gradient/matrix signs (default behavior). - in_bvals: BVAL_FILE is a file of b-values either in a single row or a\ - single column. - out_col_bval: Switch to put a column of the bvalues as the first column\ - in the output data. - out_row_bval_sep: Output a file of bvalues in a single row. - out_col_bval_sep: Output a file of bvalues in a single column. - unit_mag_out: Switch to scale each vector/matrix from the INFILE to\ - either unit or zero magnitude. - check_abs_min: Specify the threshold to replace small negative diagonal\ - elements with zero in the input matrix. - bref_mean_top: When averaging the reference 'b0' values, represent the\ - mean of X values in the top row. - put_zeros_top: Add a row at the top with all zeros in the output format. - bmax_ref: THRESH is a scalar number below which b-values are considered\ - zero or reference. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dDwGradOMatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_DW_GRAD_O_MAT___METADATA) - cargs = [] - cargs.append("1dDW_Grad_o_Mat++") - cargs.extend([ - "-in_row_vec", - execution.input_file(in_row_vec) - ]) - cargs.extend([ - "-in_col_vec", - execution.input_file(in_col_vec) - ]) - cargs.extend([ - "-in_col_matA", - execution.input_file(in_col_mat_a) - ]) - cargs.extend([ - "-in_col_matT", - execution.input_file(in_col_mat_t) - ]) - if flip_x: - cargs.append("-flip_x") - if flip_y: - cargs.append("-flip_y") - if flip_z: - cargs.append("-flip_z") - if no_flip: - cargs.append("-no_flip") - cargs.extend([ - "-out_row_vec", - out_row_vec - ]) - cargs.extend([ - "-out_col_vec", - out_col_vec - ]) - cargs.extend([ - "-out_col_matA", - out_col_mat_a - ]) - cargs.extend([ - "-out_col_matT", - out_col_mat_t - ]) - if in_bvals is not None: - cargs.extend([ - "-in_bvals", - execution.input_file(in_bvals) - ]) - if out_col_bval: - cargs.append("-out_col_bval") - if out_row_bval_sep is not None: - cargs.extend([ - "-out_row_bval_sep", - out_row_bval_sep - ]) - if out_col_bval_sep is not None: - cargs.extend([ - "-out_col_bval_sep", - out_col_bval_sep - ]) - if unit_mag_out: - cargs.append("-unit_mag_out") - if check_abs_min is not None: - cargs.extend([ - "-check_abs_min", - str(check_abs_min) - ]) - if bref_mean_top: - cargs.append("-bref_mean_top") - if put_zeros_top: - cargs.append("-put_zeros_top") - if bmax_ref is not None: - cargs.extend([ - "-bmax_ref", - str(bmax_ref) - ]) - ret = V1dDwGradOMatOutputs( - root=execution.output_file("."), - outfile=execution.output_file(out_row_vec), - out_row_bval_file=execution.output_file(out_row_bval_sep) if (out_row_bval_sep is not None) else None, - out_col_bval_file=execution.output_file(out_row_bval_sep) if (out_row_bval_sep is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dDwGradOMatOutputs", - "V_1D_DW_GRAD_O_MAT___METADATA", - "v_1d_dw_grad_o_mat__", -] diff --git a/python/src/niwrap/afni/v_1d_flag_motion.py b/python/src/niwrap/afni/v_1d_flag_motion.py deleted file mode 100644 index f73fecba3..000000000 --- a/python/src/niwrap/afni/v_1d_flag_motion.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_FLAG_MOTION_METADATA = Metadata( - id="efc64bd39dbf6f50e88a48eb1a0be3834e4162f6.boutiques", - name="1dFlagMotion", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dFlagMotionOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_flag_motion(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_points: OutputPathType - """List of points exceeding the motion bounds in 1D format""" - - -def v_1d_flag_motion( - input_motion_file: InputPathType, - max_translation: float | None = None, - max_rotation: float | None = None, - runner: Runner | None = None, -) -> V1dFlagMotionOutputs: - """ - Produces a list of time points with excessive motion relative to the previous - time point. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_motion_file: Input file with EXACTLY 6 columns: roll pitch yaw\ - delta-SI delta-LR delta-AP (angles in degrees followed by translations\ - in mm). - max_translation: Maximum translation allowed in any direction (defaults\ - to 1.5mm). - max_rotation: Maximum rotation allowed in any direction (defaults to\ - 1.25 degrees). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dFlagMotionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_FLAG_MOTION_METADATA) - cargs = [] - cargs.append("1dFlagMotion") - cargs.append(execution.input_file(input_motion_file)) - if max_translation is not None: - cargs.extend([ - "-MaxTrans", - str(max_translation) - ]) - if max_rotation is not None: - cargs.extend([ - "-MaxRot", - str(max_rotation) - ]) - ret = V1dFlagMotionOutputs( - root=execution.output_file("."), - output_points=execution.output_file("output_motion_points.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dFlagMotionOutputs", - "V_1D_FLAG_MOTION_METADATA", - "v_1d_flag_motion", -] diff --git a/python/src/niwrap/afni/v_1d_marry.py b/python/src/niwrap/afni/v_1d_marry.py deleted file mode 100644 index 96f983645..000000000 --- a/python/src/niwrap/afni/v_1d_marry.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_MARRY_METADATA = Metadata( - id="f9f4039bb8ba124f894ee17e087388280263a504.boutiques", - name="1dMarry", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dMarryOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_marry(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file when marrying files. This file should be captured using a - redirection such as '>'.""" - divorcee_a: OutputPathType - """First output file when divorcing.""" - divorcee_b: OutputPathType - """Second output file when divorcing.""" - - -def v_1d_marry( - files: list[InputPathType], - sep: str | None = None, - divorce: bool = False, - runner: Runner | None = None, -) -> V1dMarryOutputs: - """ - Joins together 2 (or more) ragged-right .1D files, for use with 3dDeconvolve - -stim_times_AM2, or breaks up 1 married file into 2 (or more) single-valued - files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: Input file(s) to be married or divorced. - sep: Separator(s) for marrying files. The first character is used as\ - the separator between values 1 and 2, the second character between\ - values 2 and 3, etc. - divorce: Divorce mode: splits married file into separate files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dMarryOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_MARRY_METADATA) - cargs = [] - cargs.append("1dMarry") - if sep is not None: - cargs.extend([ - "-sep", - sep - ]) - if divorce: - cargs.append("-divorce") - cargs.extend([execution.input_file(f) for f in files]) - cargs.append("[FILE2]") - ret = V1dMarryOutputs( - root=execution.output_file("."), - outfile=execution.output_file("stdout"), - divorcee_a=execution.output_file("[FILE2]_A.1D"), - divorcee_b=execution.output_file("[FILE2]_B.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dMarryOutputs", - "V_1D_MARRY_METADATA", - "v_1d_marry", -] diff --git a/python/src/niwrap/afni/v_1d_nlfit.py b/python/src/niwrap/afni/v_1d_nlfit.py deleted file mode 100644 index ee8f47173..000000000 --- a/python/src/niwrap/afni/v_1d_nlfit.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_NLFIT_METADATA = Metadata( - id="c1d5cfe0184660d0c6c860cf8aab83a105f64fe9.boutiques", - name="1dNLfit", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dNlfitOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_nlfit(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - fit_results: OutputPathType - """Results (fitted time series models) are written to stdout. Should be - saved by '>' redirection.""" - - -def v_1d_nlfit( - expression: str, - independent_variable: str, - parameters: list[str], - dependent_data: InputPathType, - method: int | None = None, - runner: Runner | None = None, -) -> V1dNlfitOutputs: - """ - Program to fit a model to a vector of data. The model is given by a symbolic - expression, with parameters to be estimated. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expression: The expression for the fit. It must contain one symbol from\ - 'a' to 'z' which is marked as the independent variable by option\ - '-indvar', and at least one more symbol which is a parameter to be\ - estimated. - independent_variable: Indicates which variable in '-expr' is the\ - independent variable. All other symbols are parameters, which are\ - either fixed (constants) or variables to be estimated. Read the values\ - of the independent variable from 1D file. - parameters: Set fixed value or estimating range for a particular\ - symbol. For a fixed value, it takes the form 'a=3.14'. For an estimated\ - parameter, it takes the form 'q=-sqrt(2):sqrt(2)'. All symbols in\ - '-expr' must have a corresponding '-param' option, EXCEPT for the\ - '-indvar' symbol. - dependent_data: Read the values of the dependent variable (to be fitted\ - to '-expr') from 1D file. The file must have the same number of rows as\ - the '-indvar' file. - method: Set the method for fitting: '1' for L1, '2' for L2 (default is\ - L2). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dNlfitOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_NLFIT_METADATA) - cargs = [] - cargs.append("1dNLfit") - cargs.extend([ - "-expr", - expression - ]) - cargs.extend([ - "-indvar", - independent_variable - ]) - cargs.extend([ - "-param", - *parameters - ]) - cargs.extend([ - "-depdata", - execution.input_file(dependent_data) - ]) - if method is not None: - cargs.extend([ - "-meth", - str(method) - ]) - ret = V1dNlfitOutputs( - root=execution.output_file("."), - fit_results=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dNlfitOutputs", - "V_1D_NLFIT_METADATA", - "v_1d_nlfit", -] diff --git a/python/src/niwrap/afni/v_1d_rplot.py b/python/src/niwrap/afni/v_1d_rplot.py deleted file mode 100644 index 07269aa73..000000000 --- a/python/src/niwrap/afni/v_1d_rplot.py +++ /dev/null @@ -1,65 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_RPLOT_METADATA = Metadata( - id="c9aa3010cca9653f0537f0f1895ec50024c5afb8.boutiques", - name="1dRplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dRplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_rplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_plot: OutputPathType - """Output plot file""" - - -def v_1d_rplot( - input_file: InputPathType, - runner: Runner | None = None, -) -> V1dRplotOutputs: - """ - Program for plotting a 1D file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input 1D file to plot. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dRplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_RPLOT_METADATA) - cargs = [] - cargs.append("1dRplot") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - cargs.append("[OPTIONS]") - ret = V1dRplotOutputs( - root=execution.output_file("."), - output_plot=execution.output_file("[PREFIX]*.jpg"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dRplotOutputs", - "V_1D_RPLOT_METADATA", - "v_1d_rplot", -] diff --git a/python/src/niwrap/afni/v_1d_sem.py b/python/src/niwrap/afni/v_1d_sem.py deleted file mode 100644 index aff54e83d..000000000 --- a/python/src/niwrap/afni/v_1d_sem.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_SEM_METADATA = Metadata( - id="8936d4c2b543a7a7fe17bbe75468cd8d13f99b52.boutiques", - name="1dSEM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dSemOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_sem(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output printed to the terminal. This file may be redirected.""" - - -def v_1d_sem( - theta: InputPathType, - correlation_matrix: InputPathType, - residual_variance: InputPathType, - degrees_of_freedom: float, - runner: Runner | None = None, -) -> V1dSemOutputs: - """ - Computes path coefficients for connection matrix in Structural Equation Modeling - (SEM). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - theta: Connection matrix 1D file with initial representation. - correlation_matrix: Correlation matrix 1D file. - residual_variance: Residual variance vector 1D file. - degrees_of_freedom: Degrees of freedom. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dSemOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_SEM_METADATA) - cargs = [] - cargs.append("1dSEM") - cargs.append("-theta") - cargs.append(execution.input_file(theta)) - cargs.append("-C") - cargs.append(execution.input_file(correlation_matrix)) - cargs.append("-psi") - cargs.append(execution.input_file(residual_variance)) - cargs.append("-DF") - cargs.append(str(degrees_of_freedom)) - cargs.append("[OPTIONS]") - ret = V1dSemOutputs( - root=execution.output_file("."), - output_file=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dSemOutputs", - "V_1D_SEM_METADATA", - "v_1d_sem", -] diff --git a/python/src/niwrap/afni/v_1d_tool_py.py b/python/src/niwrap/afni/v_1d_tool_py.py deleted file mode 100644 index 7f0d88b22..000000000 --- a/python/src/niwrap/afni/v_1d_tool_py.py +++ /dev/null @@ -1,136 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_TOOL_PY_METADATA = Metadata( - id="14f0b3bf351835bacda04353b7e54c019220ebc2.boutiques", - name="1d_tool.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dToolPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_tool_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Resulting 1D file""" - - -def v_1d_tool_py( - infile: InputPathType, - write: str | None = None, - select_cols: str | None = None, - select_rows: str | None = None, - select_groups: str | None = None, - censor_motion: float | None = None, - pad_into_many_runs: str | None = None, - set_nruns: float | None = None, - set_run_lengths: str | None = None, - show_rows_cols: bool = False, - transpose: bool = False, - reverse: bool = False, - show_max_displace: bool = False, - runner: Runner | None = None, -) -> V1dToolPyOutputs: - """ - A tool for manipulating and evaluating 1D files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input 1D file. - write: Output file to write results. - select_cols: Select specific columns. - select_rows: Select specific rows. - select_groups: Select columns by group numbers. - censor_motion: Generate a boolean censor file. - pad_into_many_runs: Pad a 1D file into many runs. - set_nruns: Set number of runs. - set_run_lengths: Set run lengths. - show_rows_cols: Show the number of rows and columns. - transpose: Transpose the input matrix. - reverse: Reverse the data over time. - show_max_displace: Show the maximum pairwise displacement. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dToolPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_TOOL_PY_METADATA) - cargs = [] - cargs.append("1d_tool.py") - cargs.extend([ - "-infile", - execution.input_file(infile) - ]) - if write is not None: - cargs.extend([ - "-write", - write - ]) - if select_cols is not None: - cargs.extend([ - "-select_cols", - select_cols - ]) - if select_rows is not None: - cargs.extend([ - "-select_rows", - select_rows - ]) - if select_groups is not None: - cargs.extend([ - "-select_groups", - select_groups - ]) - if censor_motion is not None: - cargs.extend([ - "-censor_motion", - str(censor_motion) - ]) - if pad_into_many_runs is not None: - cargs.extend([ - "-pad_into_many_runs", - pad_into_many_runs - ]) - if set_nruns is not None: - cargs.extend([ - "-set_nruns", - str(set_nruns) - ]) - if set_run_lengths is not None: - cargs.extend([ - "-set_run_lengths", - set_run_lengths - ]) - if show_rows_cols: - cargs.append("-show_rows_cols") - if transpose: - cargs.append("-transpose") - if reverse: - cargs.append("-reverse") - if show_max_displace: - cargs.append("-show_max_displace") - ret = V1dToolPyOutputs( - root=execution.output_file("."), - outfile=execution.output_file(write) if (write is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dToolPyOutputs", - "V_1D_TOOL_PY_METADATA", - "v_1d_tool_py", -] diff --git a/python/src/niwrap/afni/v_1d_tsort.py b/python/src/niwrap/afni/v_1d_tsort.py deleted file mode 100644 index d431a7b30..000000000 --- a/python/src/niwrap/afni/v_1d_tsort.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_TSORT_METADATA = Metadata( - id="ab14a7e62a8b710af2d1fe9b369ef04e44e6defe.boutiques", - name="1dTsort", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dTsortOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_tsort(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1d_tsort( - infile: InputPathType, - dec_order: bool = False, - transpose: bool = False, - column: float | None = None, - imode: bool = False, - runner: Runner | None = None, -) -> V1dTsortOutputs: - """ - Sorts each column of the input 1D file and writes result to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input 1D file to be sorted. - dec_order: Sort into decreasing order. - transpose: Transpose the file before output. - column: Sort only on column #j (counting starts at 0), and carry the\ - rest of the columns with it. - imode: Typecast all values to integers, return the mode in the input\ - then exit. No sorting results are returned. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dTsortOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_TSORT_METADATA) - cargs = [] - cargs.append("1dTsort") - if dec_order: - cargs.append("-dec") - if transpose: - cargs.append("-flip") - if column is not None: - cargs.extend([ - "-col", - str(column) - ]) - if imode: - cargs.append("-imode") - cargs.append(execution.input_file(infile)) - ret = V1dTsortOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dTsortOutputs", - "V_1D_TSORT_METADATA", - "v_1d_tsort", -] diff --git a/python/src/niwrap/afni/v_1d_upsample.py b/python/src/niwrap/afni/v_1d_upsample.py deleted file mode 100644 index f70bc4ee4..000000000 --- a/python/src/niwrap/afni/v_1d_upsample.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1D_UPSAMPLE_METADATA = Metadata( - id="785c941f30822b63c7729e1d98eaabc08cf4608f.boutiques", - name="1dUpsample", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dUpsampleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1d_upsample(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Upsampled 1D time series output""" - - -def v_1d_upsample( - upsample_factor: float, - input_file: InputPathType, - linear_interpolation: bool = False, - runner: Runner | None = None, -) -> V1dUpsampleOutputs: - """ - Upsamples a 1D time series to a finer time grid. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - upsample_factor: Upsample factor (integer from 2..32). - input_file: Input 1D time series file. - linear_interpolation: Use 1st order polynomials (i.e., linear\ - interpolation) instead of 7th order polynomials. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dUpsampleOutputs`). - """ - if not (2 <= upsample_factor <= 32): - raise ValueError(f"'upsample_factor' must be between 2 <= x <= 32 but was {upsample_factor}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1D_UPSAMPLE_METADATA) - cargs = [] - cargs.append("1dUpsample") - cargs.append(str(upsample_factor)) - cargs.append(execution.input_file(input_file)) - if linear_interpolation: - cargs.append("-one") - ret = V1dUpsampleOutputs( - root=execution.output_file("."), - output_file=execution.output_file("ethel.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dUpsampleOutputs", - "V_1D_UPSAMPLE_METADATA", - "v_1d_upsample", -] diff --git a/python/src/niwrap/afni/v_1dcat.py b/python/src/niwrap/afni/v_1dcat.py deleted file mode 100644 index b4645570a..000000000 --- a/python/src/niwrap/afni/v_1dcat.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DCAT_METADATA = Metadata( - id="6497fba75068a5e9c7d3930e26c7a5f42390e7b0.boutiques", - name="1dcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - concatenated_output: OutputPathType - """Concatenated output in specified format""" - - -def v_1dcat( - input_files: list[InputPathType], - tsv_output: bool = False, - csv_output: bool = False, - nonconst_output: bool = False, - nonfixed_output: bool = False, - number_format: str | None = None, - stack_output: bool = False, - column_row_selection: str | None = None, - ok_empty: bool = False, - runner: Runner | None = None, -) -> V1dcatOutputs: - """ - Concatenates columns of multiple 1D or TSV/CSV files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 1D or TSV/CSV files to concatenate. - tsv_output: Output in TSV format with tabs as separators and a header\ - line. - csv_output: Output in CSV format with commas as separators and a header\ - line. - nonconst_output: Omit columns that are identically constant from the\ - output. - nonfixed_output: Keep only columns marked as 'free' in the 3dAllineate\ - header. - number_format: Specify the format of the numbers to be output. - stack_output: Stack the columns of the resulting matrix in the output. - column_row_selection: Apply the same column/row selection string to all\ - filenames on the command line. - ok_empty: Exit quietly when encountering an empty file on disk. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dcatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DCAT_METADATA) - cargs = [] - cargs.append("1dcat") - cargs.extend([execution.input_file(f) for f in input_files]) - if tsv_output: - cargs.append("-tsvout") - if csv_output: - cargs.append("-csvout") - if nonconst_output: - cargs.append("-nonconst") - if nonfixed_output: - cargs.append("-nonfixed") - if number_format is not None: - cargs.extend([ - "-form", - number_format - ]) - if stack_output: - cargs.append("-stack") - if column_row_selection is not None: - cargs.extend([ - "-sel", - column_row_selection - ]) - if ok_empty: - cargs.append("-OKempty") - ret = V1dcatOutputs( - root=execution.output_file("."), - concatenated_output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dcatOutputs", - "V_1DCAT_METADATA", - "v_1dcat", -] diff --git a/python/src/niwrap/afni/v_1ddot.py b/python/src/niwrap/afni/v_1ddot.py deleted file mode 100644 index b7d9fc3cb..000000000 --- a/python/src/niwrap/afni/v_1ddot.py +++ /dev/null @@ -1,95 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DDOT_METADATA = Metadata( - id="05f41fc608bd0bdd44c1329f183132f4def01256.boutiques", - name="1ddot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1ddotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1ddot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout_output: OutputPathType - """Output correlation or covariance matrix printed to stdout.""" - - -def v_1ddot( - input_files: list[InputPathType], - one_flag: bool = False, - dem_flag: bool = False, - cov_flag: bool = False, - inn_flag: bool = False, - rank_flag: bool = False, - terse_flag: bool = False, - okzero_flag: bool = False, - runner: Runner | None = None, -) -> V1ddotOutputs: - """ - Computes the correlation matrix of the input 1D files and their inverse - correlation matrix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 1D files. - one_flag: Make 1st vector be all 1's. - dem_flag: Remove mean from all vectors (conflicts with '-one'). - cov_flag: Compute with covariance matrix instead of correlation. - inn_flag: Compute with inner product matrix instead. - rank_flag: Compute Spearman rank correlation instead (also implies\ - '-terse'). - terse_flag: Output only the correlation or covariance matrix without\ - any garnish. - okzero_flag: Do not quit if a vector is all zeros. The correlation\ - matrix will have 0 where NaNs ought to go. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1ddotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DDOT_METADATA) - cargs = [] - cargs.append("1ddot") - if one_flag: - cargs.append("-one") - if dem_flag: - cargs.append("-dem") - if cov_flag: - cargs.append("-cov") - if inn_flag: - cargs.append("-inn") - if rank_flag: - cargs.append("-rank") - if terse_flag: - cargs.append("-terse") - if okzero_flag: - cargs.append("-okzero") - cargs.extend([execution.input_file(f) for f in input_files]) - cargs.append(">") - cargs.append("stdout.txt") - ret = V1ddotOutputs( - root=execution.output_file("."), - stdout_output=execution.output_file("stdout.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1ddotOutputs", - "V_1DDOT_METADATA", - "v_1ddot", -] diff --git a/python/src/niwrap/afni/v_1deval.py b/python/src/niwrap/afni/v_1deval.py deleted file mode 100644 index e14af6b16..000000000 --- a/python/src/niwrap/afni/v_1deval.py +++ /dev/null @@ -1,110 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DEVAL_METADATA = Metadata( - id="b5dd462ea1c62542686cd5c2108f06b5f28820b2.boutiques", - name="1deval", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1devalOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1deval(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_1_d: OutputPathType - """Output of evaluated expression.""" - - -def v_1deval( - expression: str, - del_: float | None = None, - start: float | None = None, - num: float | None = None, - index: InputPathType | None = None, - v_1_d: bool = False, - symbols: list[InputPathType] | None = None, - runner: Runner | None = None, -) -> V1devalOutputs: - """ - Evaluates an expression that may include columns of data from one or more text - files and writes the result to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expression: Expression to evaluate. - del_: Use 'd' as the step for a single undetermined variable in the\ - expression. - start: Start at value 's' for a single undetermined variable in the\ - expression. - num: Evaluate the expression 'n' times. - index: Read index column from file i.1D and write it out as 1st column\ - of output. - v_1_d: Write output in the form of a single '1D:' string suitable for\ - input on the command line of another program. - symbols: Read time series file and assign it to the symbol 'a'. Letters\ - 'a' to 'z' may be used as symbols. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1devalOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DEVAL_METADATA) - cargs = [] - cargs.append("1deval") - if del_ is not None: - cargs.extend([ - "-del", - str(del_) - ]) - if start is not None: - cargs.extend([ - "-start", - str(start) - ]) - if num is not None: - cargs.extend([ - "-num", - str(num) - ]) - if index is not None: - cargs.extend([ - "-index", - execution.input_file(index) - ]) - if v_1_d: - cargs.append("-1D:") - if symbols is not None: - cargs.extend([ - "-a", - *[execution.input_file(f) for f in symbols] - ]) - cargs.append("-expr") - cargs.extend([ - "-expr", - expression - ]) - ret = V1devalOutputs( - root=execution.output_file("."), - output_1_d=execution.output_file("output.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1devalOutputs", - "V_1DEVAL_METADATA", - "v_1deval", -] diff --git a/python/src/niwrap/afni/v_1dfft.py b/python/src/niwrap/afni/v_1dfft.py deleted file mode 100644 index 674c28129..000000000 --- a/python/src/niwrap/afni/v_1dfft.py +++ /dev/null @@ -1,112 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DFFT_METADATA = Metadata( - id="1b882371fd5c103972dacb7d40e09d3d66d4ad04.boutiques", - name="1dfft", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dfftOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dfft(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_fft: OutputPathType - """Output file with the absolute value of the FFT of the input columns.""" - - -def v_1dfft( - infile: InputPathType, - outfile: str, - ignore: float | None = None, - use: float | None = None, - nfft: float | None = None, - tocx: bool = False, - fromcx: bool = False, - hilbert: bool = False, - nodetrend: bool = False, - runner: Runner | None = None, -) -> V1dfftOutputs: - """ - Compute the absolute value of the FFT of input columns from an AFNI 1D file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input .1D file containing an ASCII list of numbers arranged in\ - columns. - outfile: Output file to store the FFT results. - ignore: Skip the first 'sss' lines in the input file. [default = no\ - skipping]. - use: Use only 'uuu' lines of the input file. [default = use them all]. - nfft: Set FFT length to 'nnn'. [default = length of data (# of lines\ - used)]. - tocx: Save Re and Im parts of transform in 2 columns. - fromcx: Convert 2 column complex input into 1 column real output. Note:\ - This will not work if the original data FFT length was an odd number. - hilbert: When -fromcx is used, the inverse FFT will do the Hilbert\ - transform instead. - nodetrend: Skip the detrending of the input. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dfftOutputs`). - """ - if ignore is not None and not (0 <= ignore): - raise ValueError(f"'ignore' must be greater than 0 <= x but was {ignore}") - if use is not None and not (0 <= use): - raise ValueError(f"'use' must be greater than 0 <= x but was {use}") - if nfft is not None and not (1 <= nfft): - raise ValueError(f"'nfft' must be greater than 1 <= x but was {nfft}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DFFT_METADATA) - cargs = [] - cargs.append("1dfft") - cargs.append(execution.input_file(infile)) - cargs.append(outfile) - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - if use is not None: - cargs.extend([ - "-use", - str(use) - ]) - if nfft is not None: - cargs.extend([ - "-nfft", - str(nfft) - ]) - if tocx: - cargs.append("-tocx") - if fromcx: - cargs.append("-fromcx") - if hilbert: - cargs.append("-hilbert") - if nodetrend: - cargs.append("-nodetrend") - ret = V1dfftOutputs( - root=execution.output_file("."), - out_fft=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dfftOutputs", - "V_1DFFT_METADATA", - "v_1dfft", -] diff --git a/python/src/niwrap/afni/v_1dgen_arma11.py b/python/src/niwrap/afni/v_1dgen_arma11.py deleted file mode 100644 index 5b1a2c101..000000000 --- a/python/src/niwrap/afni/v_1dgen_arma11.py +++ /dev/null @@ -1,138 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DGEN_ARMA11_METADATA = Metadata( - id="eec5da6e665ce89463e9d156358a3805c810fa76.boutiques", - name="1dgenARMA11", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dgenArma11Outputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dgen_arma11(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """Generated ARMA(1,1) time series""" - - -def v_1dgen_arma11( - length_alt: float | None = None, - num_series: float | None = None, - param_a: float | None = None, - param_b: float | None = None, - param_lam: float | None = None, - std_dev: float | None = None, - normalize: bool = False, - seed: float | None = None, - corcut: float | None = None, - arma31: str | None = None, - arma51: str | None = None, - runner: Runner | None = None, -) -> V1dgenArma11Outputs: - """ - Program to generate an ARMA(1,1) time series, for simulation studies. Results - are written to stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - length_alt: Specify the length of the time series vector to generate\ - (equivalent to -num option). - num_series: The number of time series vectors to generate; defaults to\ - 1 if not given. - param_a: Specify ARMA(1,1) parameters 'a'. - param_b: Specify ARMA(1,1) parameter 'b' directly. - param_lam: Specify ARMA(1,1) parameter 'b' indirectly. - std_dev: Set standard deviation of results [default=1]. - normalize: Normalize time series so sum of squares is 1. - seed: Set random number seed. - corcut: Specify a cutoff for the correlation coefficient r(k) of noise\ - samples at k units apart. Default is 0.00010. - arma31: Specify parameters for a restricted ARMA(3,1) model: -arma31 a\ - r theta vrat. - arma51: Specify parameters for a restricted ARMA(5,1) model: -arma51 a\ - r1 theta1 r2 theta2 vrat. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dgenArma11Outputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DGEN_ARMA11_METADATA) - cargs = [] - cargs.append("1dgenARMA11") - if length_alt is not None: - cargs.extend([ - "-len", - str(length_alt) - ]) - if num_series is not None: - cargs.extend([ - "-nvec", - str(num_series) - ]) - if param_a is not None: - cargs.extend([ - "-a", - str(param_a) - ]) - if param_b is not None: - cargs.extend([ - "-b", - str(param_b) - ]) - if param_lam is not None: - cargs.extend([ - "-lam", - str(param_lam) - ]) - if std_dev is not None: - cargs.extend([ - "-sig", - str(std_dev) - ]) - if normalize: - cargs.append("-norm") - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - if corcut is not None: - cargs.extend([ - "-CORcut", - str(corcut) - ]) - if arma31 is not None: - cargs.extend([ - "-arma31", - arma31 - ]) - if arma51 is not None: - cargs.extend([ - "-arma51", - arma51 - ]) - ret = V1dgenArma11Outputs( - root=execution.output_file("."), - output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dgenArma11Outputs", - "V_1DGEN_ARMA11_METADATA", - "v_1dgen_arma11", -] diff --git a/python/src/niwrap/afni/v_1dgrayplot.py b/python/src/niwrap/afni/v_1dgrayplot.py deleted file mode 100644 index 2ada90c5c..000000000 --- a/python/src/niwrap/afni/v_1dgrayplot.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DGRAYPLOT_METADATA = Metadata( - id="9f1dfb91ea2888caae64e3a7a65f59bb59e4f314.boutiques", - name="1dgrayplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dgrayplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dgrayplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1dgrayplot( - tsfile: InputPathType, - install: bool = False, - ignore: float | None = None, - flip: bool = False, - sep: bool = False, - use: float | None = None, - ps: bool = False, - runner: Runner | None = None, -) -> V1dgrayplotOutputs: - """ - Graphs the columns of a *.1D type time series file to the screen in grayscale. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tsfile: Input time series file (*.1D format). - install: Install a new X11 colormap (for X11 PseudoColor). - ignore: Skip first 'nn' rows in the input file [default = 0]. - flip: Plot x and y axes interchanged [default: data columns plotted\ - DOWN the screen]. - sep: Separate scales for each column. - use: Plot 'mm' points [default: all of them]. - ps: Don't draw plot in a window; write it to stdout in PostScript\ - format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dgrayplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DGRAYPLOT_METADATA) - cargs = [] - cargs.append("1dgrayplot") - cargs.append(execution.input_file(tsfile)) - if install: - cargs.append("-install") - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - if flip: - cargs.append("-flip") - if sep: - cargs.append("-sep") - if use is not None: - cargs.extend([ - "-use", - str(use) - ]) - if ps: - cargs.append("-ps") - ret = V1dgrayplotOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dgrayplotOutputs", - "V_1DGRAYPLOT_METADATA", - "v_1dgrayplot", -] diff --git a/python/src/niwrap/afni/v_1dmatcalc.py b/python/src/niwrap/afni/v_1dmatcalc.py deleted file mode 100644 index 460e5c64e..000000000 --- a/python/src/niwrap/afni/v_1dmatcalc.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DMATCALC_METADATA = Metadata( - id="363bd7932d82bc77c3f5fe6e0307d7efddad15de.boutiques", - name="1dmatcalc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dmatcalcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dmatcalc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output file resulting from the evaluated expression""" - - -def v_1dmatcalc( - expression: str | None = None, - runner: Runner | None = None, -) -> V1dmatcalcOutputs: - """ - A tool to evaluate space-delimited RPN (Reverse Polish Notation) matrix-valued - expressions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expression: Expression to evaluate the RPN matrix-valued operations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dmatcalcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DMATCALC_METADATA) - cargs = [] - cargs.append("1dmatcalc") - if expression is not None: - cargs.append(expression) - ret = V1dmatcalcOutputs( - root=execution.output_file("."), - output_file=execution.output_file("[OUTPUT_FILE]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dmatcalcOutputs", - "V_1DMATCALC_METADATA", - "v_1dmatcalc", -] diff --git a/python/src/niwrap/afni/v_1dnorm.py b/python/src/niwrap/afni/v_1dnorm.py deleted file mode 100644 index e57562494..000000000 --- a/python/src/niwrap/afni/v_1dnorm.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DNORM_METADATA = Metadata( - id="ea6e83597c9dc8fb3895db8c36d06ddc6f559447.boutiques", - name="1dnorm", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dnormOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dnorm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - normalized_output: OutputPathType - """Normalized output AFNI *.1D file""" - - -def v_1dnorm( - infile: InputPathType, - outfile: str, - norm1: bool = False, - normx: bool = False, - demean: bool = False, - demed: bool = False, - runner: Runner | None = None, -) -> V1dnormOutputs: - """ - Normalize columns of a 1D file (AFNI ASCII list of numbers). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input AFNI *.1D file (ASCII list of numbers arranged in\ - columns); if '-' input will be read from stdin. - outfile: Output AFNI *.1D file (normalized); if '-' output will be\ - written to stdout. - norm1: Normalize so sum of absolute values is 1 (L_1 norm). - normx: Normalize so that max absolute value is 1 (L_infinity norm). - demean: Subtract each column's mean before normalizing. - demed: Subtract each column's median before normalizing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dnormOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DNORM_METADATA) - cargs = [] - cargs.append("1dnorm") - cargs.append(execution.input_file(infile)) - cargs.append(outfile) - if norm1: - cargs.append("-norm1") - if normx: - cargs.append("-normx") - if demean: - cargs.append("-demean") - if demed: - cargs.append("-demed") - ret = V1dnormOutputs( - root=execution.output_file("."), - normalized_output=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dnormOutputs", - "V_1DNORM_METADATA", - "v_1dnorm", -] diff --git a/python/src/niwrap/afni/v_1dplot.py b/python/src/niwrap/afni/v_1dplot.py deleted file mode 100644 index a97d38285..000000000 --- a/python/src/niwrap/afni/v_1dplot.py +++ /dev/null @@ -1,395 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DPLOT_METADATA = Metadata( - id="8a73ee3a42ebaf653aef47adb6f3fa781e513997.boutiques", - name="1dplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_1dplot( - tsfiles: list[InputPathType], - install: bool = False, - sep: bool = False, - one: bool = False, - sepscl: bool = False, - noline: bool = False, - noline_: bool = False, - box: bool = False, - hist: bool = False, - norm2: bool = False, - normx: bool = False, - norm1: bool = False, - demean: bool = False, - x: InputPathType | None = None, - xl10: InputPathType | None = None, - dx: float | None = None, - xzero: float | None = None, - nopush: bool = False, - ignore: float | None = None, - use: float | None = None, - xlabel: str | None = None, - ylabel: str | None = None, - plabel: str | None = None, - title: str | None = None, - wintitle: str | None = None, - naked: bool = False, - aspect: float | None = None, - stdin: bool = False, - ps: bool = False, - jpg: str | None = None, - jpeg: str | None = None, - png: str | None = None, - pnm: str | None = None, - pngs: str | None = None, - jpgs: str | None = None, - jpegs: str | None = None, - pnms: str | None = None, - ytran: str | None = None, - xtran: str | None = None, - xaxis: str | None = None, - yaxis: str | None = None, - ynames: list[str] | None = None, - volreg: bool = False, - thick: bool = False, - thick_: bool = False, - dashed: str | None = None, - setenv: str | None = None, - censor_rgb: str | None = None, - censor: InputPathType | None = None, - censortr: list[str] | None = None, - concat: InputPathType | None = None, - rbox: str | None = None, - rbox_: str | None = None, - line: str | None = None, - runner: Runner | None = None, -) -> V1dplotOutputs: - """ - Graphs the columns of a *.1D time series file to the X11 screen, or to an image - file (.jpg or .png). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tsfiles: Input time series files (*.1D) to be plotted. - install: Install a new X11 colormap. - sep: Plot each column in a separate sub-graph. - one: Plot all columns together in one big graph. - sepscl: Plot each column in a separate sub-graph and allow each\ - sub-graph to have a different y-scale. This option is meaningless with\ - -one!. - noline: Same as -noline, but will not try to plot values outside the\ - rectangular box that contains the graph axes. - noline_: Same as -noline, but will not try to plot values outside the\ - rectangular box that contains the graph axes. - box: Plot a small 'box' at each data point. - hist: Plot graphs in histogram style (i.e., vertical boxes). - norm2: Independently scale each time series plotted to have L_2 norm =\ - 1 (sum of squares). - normx: Independently scale each time series plotted to have max\ - absolute value = 1 (L_infinity norm). - norm1: Independently scale each time series plotted to have max sum of\ - absolute values = 1 (L_1 norm). - demean: Remove the mean from each time series before normalizing. - x: Use for X axis the data in a specified .1D file. - xl10: Use log10 of the specified .1D file as the X axis. - dx: Spacing between points on the x-axis. - xzero: Initial x coordinate. - nopush: Don't 'push' axes ranges outwards. - ignore: Skip first 'nn' rows in the input file. - use: Plot 'mm' points. - xlabel: Put string 'aa' below the x-axis. - ylabel: Put string 'aa' to the left of the y-axis. - plabel: Put string 'pp' atop the plot. - title: Same as -plabel, but only works with -ps/-png/-jpg/-pnm options. - wintitle: Set string 'pp' as the title of the frame containing the\ - plot. - naked: Do NOT plot axes or labels, just the graph(s). - aspect: Set the width-to-height ratio of the plot region to 'A'. - stdin: Don't read from tsfile; instead, read from stdin and plot it. - ps: Don't draw plot in a window; instead, write it to stdout in\ - PostScript format. - jpg: Render plot to JPEG image and save to a file named 'fname'. - jpeg: Render plot to JPEG image and save to a file named 'fname'. - png: Render plot to PNG image and save to a file named 'fname'. - pnm: Render plot to PNM image and save to a file named 'fname'. - pngs: Render plot to PNG image of specified size and save to a file\ - named 'fname'. - jpgs: Render plot to JPEG image of specified size and save to a file\ - named 'fname'. - jpegs: Render plot to JPEG image of specified size and save to a file\ - named 'fname'. - pnms: Render plot to PNM image of specified size and save to a file\ - named 'fname'. - ytran: Transform the data along the y-axis by applying the expression\ - to each input value. - xtran: Transform the data along the x-axis by applying the expression\ - to each input value. - xaxis: Set the x-axis to run from value 'b' to value 't', with 'n'\ - major divisions and 'm' minor tic marks per major division. - yaxis: Set the y-axis to run from value 'b' to value 't', with 'n'\ - major divisions and 'm' minor tic marks per major division. - ynames: Use the strings as labels to the right of the graphs,\ - corresponding to each input column. - volreg: Makes the 'ynames' be the same as the 6 labels used in\ - plug_volreg for Roll, Pitch, Yaw, I-S, R-L, and A-P movements. - thick: Twice the power of '-thick' at no extra cost!. - thick_: Twice the power of '-thick' at no extra cost!. - dashed: Plot dashed lines between data points using specified\ - colon-separated list of dash values (1: solid, 2: longer dashes, 3:\ - shorter dashes). - setenv: Set environment variable 'name' to 'val' for this run of the\ - program only. - censor_rgb: Set the color used for marking to a specified color. - censor: Specify the filename of the censor .1D time series. - censortr: Specify time indexes to be marked in the graph(s). - concat: Specify the filename for the list of concatenated runs. - rbox: Draw a rectangular box with one extra horizontal line. - rbox_: Draw a rectangular box with one extra horizontal line. - line: Draw one line segment. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DPLOT_METADATA) - cargs = [] - cargs.append("1dplot") - cargs.extend([execution.input_file(f) for f in tsfiles]) - if install: - cargs.append("-install") - if sep: - cargs.append("-sep") - if one: - cargs.append("-one") - if sepscl: - cargs.append("-sepscl") - if noline: - cargs.append("-NOLINE") - if noline_: - cargs.append("-NOLINE") - if box: - cargs.append("-box") - if hist: - cargs.append("-hist") - if norm2: - cargs.append("-norm2") - if normx: - cargs.append("-normx") - if norm1: - cargs.append("-norm1") - if demean: - cargs.append("-demean") - if x is not None: - cargs.extend([ - "-x", - execution.input_file(x) - ]) - if xl10 is not None: - cargs.extend([ - "-xl10", - execution.input_file(xl10) - ]) - if dx is not None: - cargs.extend([ - "-dx", - str(dx) - ]) - if xzero is not None: - cargs.extend([ - "-xzero", - str(xzero) - ]) - if nopush: - cargs.append("-nopush") - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - if use is not None: - cargs.extend([ - "-use", - str(use) - ]) - if xlabel is not None: - cargs.extend([ - "-xlabel", - xlabel - ]) - if ylabel is not None: - cargs.extend([ - "-ylabel", - ylabel - ]) - if plabel is not None: - cargs.extend([ - "-plabel", - plabel - ]) - if title is not None: - cargs.extend([ - "-title", - title - ]) - if wintitle is not None: - cargs.extend([ - "-wintitle", - wintitle - ]) - if naked: - cargs.append("-naked") - if aspect is not None: - cargs.extend([ - "-aspect", - str(aspect) - ]) - if stdin: - cargs.append("-stdin") - if ps: - cargs.append("-ps") - if jpg is not None: - cargs.extend([ - "-jpg", - jpg - ]) - if jpeg is not None: - cargs.extend([ - "-jpeg", - jpeg - ]) - if png is not None: - cargs.extend([ - "-png", - png - ]) - if pnm is not None: - cargs.extend([ - "-pnm", - pnm - ]) - if pngs is not None: - cargs.extend([ - "-pngs", - pngs - ]) - if jpgs is not None: - cargs.extend([ - "-jpgs", - jpgs - ]) - if jpegs is not None: - cargs.extend([ - "-jpegs", - jpegs - ]) - if pnms is not None: - cargs.extend([ - "-pnms", - pnms - ]) - if ytran is not None: - cargs.extend([ - "-ytran", - ytran - ]) - if xtran is not None: - cargs.extend([ - "-xtran", - xtran - ]) - if xaxis is not None: - cargs.extend([ - "-xaxis", - xaxis - ]) - if yaxis is not None: - cargs.extend([ - "-yaxis", - yaxis - ]) - if ynames is not None: - cargs.extend([ - "-ynames", - *ynames - ]) - if volreg: - cargs.append("-volreg") - if thick: - cargs.append("-THICK") - if thick_: - cargs.append("-THICK") - if dashed is not None: - cargs.extend([ - "-dashed", - dashed - ]) - if setenv is not None: - cargs.extend([ - "-D", - setenv - ]) - if censor_rgb is not None: - cargs.extend([ - "-censor_RGB", - censor_rgb - ]) - if censor is not None: - cargs.extend([ - "-censor", - execution.input_file(censor) - ]) - if censortr is not None: - cargs.extend([ - "-CENSORTR", - *censortr - ]) - if concat is not None: - cargs.extend([ - "-concat", - execution.input_file(concat) - ]) - if rbox is not None: - cargs.extend([ - "-Rbox", - rbox - ]) - if rbox_ is not None: - cargs.extend([ - "-Rbox", - rbox_ - ]) - if line is not None: - cargs.extend([ - "-line", - line - ]) - ret = V1dplotOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dplotOutputs", - "V_1DPLOT_METADATA", - "v_1dplot", -] diff --git a/python/src/niwrap/afni/v_1dplot_py.py b/python/src/niwrap/afni/v_1dplot_py.py deleted file mode 100644 index 1d45b389f..000000000 --- a/python/src/niwrap/afni/v_1dplot_py.py +++ /dev/null @@ -1,272 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DPLOT_PY_METADATA = Metadata( - id="9a09a3b646afa4ae694c267932f8acdb6bcb6eec.boutiques", - name="1dplot.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dplotPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dplot_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """Output image file, default to .jpg""" - - -def v_1dplot_py( - infiles: list[InputPathType], - prefix: str, - help_: bool = False, - boxplot_on: bool = False, - bplot_view: str | None = None, - margin_off: bool = False, - scale: list[str] | None = None, - xfile: InputPathType | None = None, - xvals: list[float] | None = None, - yaxis: list[str] | None = None, - ylabels: list[str] | None = None, - ylabels_maxlen: float | None = None, - legend_on: bool = False, - legend_labels: list[str] | None = None, - legend_locs: list[str] | None = None, - xlabel: str | None = None, - title: str | None = None, - reverse_order: bool = False, - sepscl: bool = False, - one_graph: bool = False, - dpi: float | None = None, - figsize: list[float] | None = None, - fontsize: float | None = None, - fontfamily: str | None = None, - fontstyles: str | None = None, - colors: list[str] | None = None, - patches: list[str] | None = None, - censor_trs: list[str] | None = None, - censor_files: list[InputPathType] | None = None, - censor_hline: list[str] | None = None, - censor_rgb: str | None = None, - bkgd_color: str | None = None, - runner: Runner | None = None, -) -> V1dplotPyOutputs: - """ - This program is for making images to visualize columns of numbers from 1D text - files. It uses Python, particularly matplotlib, to create plots. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infiles: One or more file names of text files. Each column in this file\ - will be treated as a separate time series for plotting. - prefix: Output filename or prefix. Default output image type is .jpg. - help_: See helpfile. - boxplot_on: A fun feature to show an additional boxplot adjacent to\ - each time series. - bplot_view: Adjust view for boxplots when using censoring. - margin_off: Fill the plot frame completely, thus no labels, frame, or\ - titles will be visible. - scale: Provide a list of scales to apply to the y-values. - xfile: One way to input x-values explicitly: as a "1D" file containing\ - a single file of numbers. - xvals: Provide exactly 3 numbers for x-values: start, stop, and\ - stepsize. - yaxis: Optional range for each 'infile' y-axis. - ylabels: Optional text labels for each 'infile' column. - ylabels_maxlen: allows y-axis labels to wrap into multiple rows, each\ - of length <= which the user can decide. - legend_on: Turn on the plotting of a legend in the plot(s). - legend_labels: Optional legend labels, if using '-legend_on'. - legend_locs: Optional legend locations, if using '-legend_on'. - xlabel: Optional text labels for the abscissa/x-axis. - title: Optional title for the set of plots. - reverse_order: Reverses the order of plotted time series. - sepscl: Make each graph have its own y-range. - one_graph: Plot multiple infiles in a single subplot. - dpi: Choose the output image's DPI. Default value is 150. - figsize: Choose the output image's dimensions (units are inches). - fontsize: Change image fontsize; default is 10. - fontfamily: Change font-family used; default is monospace. - fontstyles: Add a specific font name; should match with chosen\ - font-family. - colors: Decide what color(s) to cycle through in plots (one or more). - patches: Specify run lengths for background patches to distinguish runs. - censor_trs: Specify time points where censoring has occurred using AFNI\ - index notation. - censor_files: Specify time points where censoring has occurred using\ - one or more 1D files. - censor_hline: Add a dotted horizontal line to the plot, representing\ - the censor threshold. - censor_rgb: Choose the color of the censoring background; default is:\ - [1, 0.7, 0.7]. - bkgd_color: Change the background color outside of the plot windows.\ - Default is 0.9. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dplotPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DPLOT_PY_METADATA) - cargs = [] - cargs.append("1dplot.py") - cargs.extend([ - "-infiles", - *[execution.input_file(f) for f in infiles] - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if help_: - cargs.append("-h") - if boxplot_on: - cargs.append("-boxplot_on") - if bplot_view is not None: - cargs.extend([ - "-bplot_view", - bplot_view - ]) - if margin_off: - cargs.append("-margin_off") - if scale is not None: - cargs.extend([ - "-scale", - *scale - ]) - if xfile is not None: - cargs.extend([ - "-xfile", - execution.input_file(xfile) - ]) - if xvals is not None: - cargs.extend([ - "-xvals", - *map(str, xvals) - ]) - if yaxis is not None: - cargs.extend([ - "-yaxis", - *yaxis - ]) - if ylabels is not None: - cargs.extend([ - "-ylabels", - *ylabels - ]) - if ylabels_maxlen is not None: - cargs.extend([ - "-ylabels_maxlen", - str(ylabels_maxlen) - ]) - if legend_on: - cargs.append("-legend_on") - if legend_labels is not None: - cargs.extend([ - "-legend_labels", - *legend_labels - ]) - if legend_locs is not None: - cargs.extend([ - "-legend_locs", - *legend_locs - ]) - if xlabel is not None: - cargs.extend([ - "-xlabel", - xlabel - ]) - if title is not None: - cargs.extend([ - "-title", - title - ]) - if reverse_order: - cargs.append("-reverse_order") - if sepscl: - cargs.append("-sepscl") - if one_graph: - cargs.append("-one_graph") - if dpi is not None: - cargs.extend([ - "-dpi", - str(dpi) - ]) - if figsize is not None: - cargs.extend([ - "-figsize", - *map(str, figsize) - ]) - if fontsize is not None: - cargs.extend([ - "-fontsize", - str(fontsize) - ]) - if fontfamily is not None: - cargs.extend([ - "-fontfamily", - fontfamily - ]) - if fontstyles is not None: - cargs.extend([ - "-fontstyles", - fontstyles - ]) - if colors is not None: - cargs.extend([ - "-colors", - *colors - ]) - if patches is not None: - cargs.extend([ - "-patches", - *patches - ]) - if censor_trs is not None: - cargs.extend([ - "-censor_trs", - *censor_trs - ]) - if censor_files is not None: - cargs.extend([ - "-censor_files", - *[execution.input_file(f) for f in censor_files] - ]) - if censor_hline is not None: - cargs.extend([ - "-censor_hline", - *censor_hline - ]) - if censor_rgb is not None: - cargs.extend([ - "-censor_RGB", - censor_rgb - ]) - if bkgd_color is not None: - cargs.extend([ - "-bkgd_color", - bkgd_color - ]) - ret = V1dplotPyOutputs( - root=execution.output_file("."), - output_image=execution.output_file(prefix + ".jpg"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dplotPyOutputs", - "V_1DPLOT_PY_METADATA", - "v_1dplot_py", -] diff --git a/python/src/niwrap/afni/v_1dsound.py b/python/src/niwrap/afni/v_1dsound.py deleted file mode 100644 index 5a017b1c3..000000000 --- a/python/src/niwrap/afni/v_1dsound.py +++ /dev/null @@ -1,119 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DSOUND_METADATA = Metadata( - id="27afe9539a9fa717bc8a3162d9645362879cc57c.boutiques", - name="1dsound", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dsoundOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dsound(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """The output audio file.""" - - -def v_1dsound( - tsfile: InputPathType, - prefix: str | None = None, - encoding_16_pcm: bool = False, - encoding_8_pcm: bool = False, - encoding_8ulaw: bool = False, - tper_option: float | None = None, - fm_option: bool = False, - notes_option: bool = False, - notewave_option: str | None = None, - despike_option: bool = False, - play_option: bool = False, - runner: Runner | None = None, -) -> V1dsoundOutputs: - """ - Program to create a sound file from a 1D file (column of numbers). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tsfile: The input 1D time series file containing the data to transform\ - into sound. - prefix: Prefix for the output filename, which will have '.au'\ - extension. - encoding_16_pcm: Output in 16-bit linear PCM encoding (uncompressed). - encoding_8_pcm: Output in 8-bit linear PCM encoding. - encoding_8ulaw: Output in 8-bit mu-law encoding. - tper_option: Time in seconds per time point in 'tsfile'. Allowed range\ - is 0.01 to 1.0 (inclusive). [default is 0.2s]. - fm_option: Output sound is frequency modulated between 110 and 1760 Hz\ - from min to max in the input 1D file. - notes_option: Output sound is a sequence of notes, low to high pitch\ - based on min to max in the input 1D file. Uses pentatonic scale. - notewave_option: Shape of the notes used. Select from [sine, sqsine,\ - square, triangle]. - despike_option: Apply a simple despiking algorithm to avoid artifacts\ - from large/small values in the input. - play_option: Plays the sound file after it is written. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dsoundOutputs`). - """ - if tper_option is not None and not (0.01 <= tper_option <= 1.0): - raise ValueError(f"'tper_option' must be between 0.01 <= x <= 1.0 but was {tper_option}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DSOUND_METADATA) - cargs = [] - cargs.append("1dsound") - cargs.append(execution.input_file(tsfile)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if encoding_16_pcm: - cargs.append("-16PCM") - if encoding_8_pcm: - cargs.append("-8PCM") - if encoding_8ulaw: - cargs.append("-8ulaw") - if tper_option is not None: - cargs.extend([ - "-tper", - str(tper_option) - ]) - if fm_option: - cargs.append("-FM") - if notes_option: - cargs.append("-notes") - if notewave_option is not None: - cargs.extend([ - "-notewave", - notewave_option - ]) - if despike_option: - cargs.append("-despike") - if play_option: - cargs.append("-play") - ret = V1dsoundOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".au") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dsoundOutputs", - "V_1DSOUND_METADATA", - "v_1dsound", -] diff --git a/python/src/niwrap/afni/v_1dsum.py b/python/src/niwrap/afni/v_1dsum.py deleted file mode 100644 index 3476ca475..000000000 --- a/python/src/niwrap/afni/v_1dsum.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DSUM_METADATA = Metadata( - id="bc19d515e82be4f6b3c9c9f81c1a201e83b798ea.boutiques", - name="1dsum", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dsumOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dsum(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Sum or average of columns in the input files""" - - -def v_1dsum( - input_files: list[InputPathType], - ignore_rows: float | None = None, - use_rows: float | None = None, - mean_flag: bool = False, - nocomment_flag: bool = False, - okempty_flag: bool = False, - runner: Runner | None = None, -) -> V1dsumOutputs: - """ - Sum or average columns of ASCII files with numbers arranged in rows and columns. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input ASCII files with numbers arranged in rows and\ - columns. - ignore_rows: Skip the first nn rows of each file. - use_rows: Use only mm rows from each file. - mean_flag: Compute the average instead of the sum. - nocomment_flag: Do not reproduce comments from the header of the first\ - input file to the output. - okempty_flag: If encountering an empty 1D file, print 0 and exit\ - quietly instead of exiting with an error message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dsumOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DSUM_METADATA) - cargs = [] - cargs.append("1dsum") - cargs.extend([execution.input_file(f) for f in input_files]) - if ignore_rows is not None: - cargs.extend([ - "-ignore", - str(ignore_rows) - ]) - if use_rows is not None: - cargs.extend([ - "-use", - str(use_rows) - ]) - if mean_flag: - cargs.append("-mean") - if nocomment_flag: - cargs.append("-nocomment") - if okempty_flag: - cargs.append("-OKempty") - ret = V1dsumOutputs( - root=execution.output_file("."), - output_file=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dsumOutputs", - "V_1DSUM_METADATA", - "v_1dsum", -] diff --git a/python/src/niwrap/afni/v_1dsvd.py b/python/src/niwrap/afni/v_1dsvd.py deleted file mode 100644 index 3ec789b31..000000000 --- a/python/src/niwrap/afni/v_1dsvd.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DSVD_METADATA = Metadata( - id="a1518e76606dbfed112adeb737310758011efc67.boutiques", - name="1dsvd", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dsvdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dsvd(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout: OutputPathType - """Output of the SVD computation""" - - -def v_1dsvd( - input_files: list[InputPathType], - one: bool = False, - vmean: bool = False, - vnorm: bool = False, - cond: bool = False, - sing: bool = False, - sort: bool = False, - nosort: bool = False, - asort: bool = False, - left_eigenvectors: bool = False, - num_eigenvectors: str | None = None, - runner: Runner | None = None, -) -> V1dsvdOutputs: - """ - Computes SVD of the matrix formed by the 1D file(s) and outputs the result on - stdout. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 1D file(s) for SVD computation. - one: Make 1st vector be all 1's. - vmean: Remove mean from each vector (cannot be used with -one). - vnorm: Make L2-norm of each vector = 1 before SVD. - cond: Only print condition number (ratio of extremes). - sing: Only print singular values. - sort: Sort singular values in descending order (default). - nosort: Don't sort singular values. - asort: Sort singular values in ascending order. - left_eigenvectors: Only output left eigenvectors in .1D format. - num_eigenvectors: Specify number of left eigenvectors to output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dsvdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DSVD_METADATA) - cargs = [] - cargs.append("1dsvd") - if one: - cargs.append("-one") - if vmean: - cargs.append("-vmean") - if vnorm: - cargs.append("-vnorm") - if cond: - cargs.append("-cond") - if sing: - cargs.append("-sing") - if sort: - cargs.append("-sort") - if nosort: - cargs.append("-nosort") - if asort: - cargs.append("-asort") - if left_eigenvectors: - cargs.append("-1Dleft") - if num_eigenvectors is not None: - cargs.extend([ - "-nev", - num_eigenvectors - ]) - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V1dsvdOutputs( - root=execution.output_file("."), - stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dsvdOutputs", - "V_1DSVD_METADATA", - "v_1dsvd", -] diff --git a/python/src/niwrap/afni/v_1dtranspose.py b/python/src/niwrap/afni/v_1dtranspose.py deleted file mode 100644 index b619bb09f..000000000 --- a/python/src/niwrap/afni/v_1dtranspose.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_1DTRANSPOSE_METADATA = Metadata( - id="9f114085767119818f875df6af7d69bffca16b30.boutiques", - name="1dtranspose", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dtransposeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_1dtranspose(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Transposed output file""" - - -def v_1dtranspose( - infile: InputPathType, - outfile: str | None = None, - runner: Runner | None = None, -) -> V1dtransposeOutputs: - """ - Transpose an AFNI *.1D file (ASCII list of numbers arranged in columns). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file (e.g. data.1D). - outfile: Output file (e.g. transposed_data.1D), or '-' to write to\ - stdout. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dtransposeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_1DTRANSPOSE_METADATA) - cargs = [] - cargs.append("1dtranspose") - cargs.append(execution.input_file(infile)) - if outfile is not None: - cargs.append(outfile) - ret = V1dtransposeOutputs( - root=execution.output_file("."), - outfile=execution.output_file(outfile) if (outfile is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dtransposeOutputs", - "V_1DTRANSPOSE_METADATA", - "v_1dtranspose", -] diff --git a/python/src/niwrap/afni/v_24swap.py b/python/src/niwrap/afni/v_24swap.py deleted file mode 100644 index ecf932e72..000000000 --- a/python/src/niwrap/afni/v_24swap.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_24SWAP_METADATA = Metadata( - id="6078cfba70268f01f74a8921a77d80e46d21cf23.boutiques", - name="24swap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V24swapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_24swap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_24swap( - input_files: list[InputPathType], - quiet: bool = False, - pattern: str | None = None, - runner: Runner | None = None, -) -> V24swapOutputs: - """ - Swaps bytes pairs and/or quadruples on the files listed. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input file(s) to swap bytes. - quiet: Operate quietly. - pattern: Pattern that determines the pattern of 2 and 4 byte swaps. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V24swapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_24SWAP_METADATA) - cargs = [] - cargs.append("24swap") - if quiet: - cargs.append("-q") - if pattern is not None: - cargs.extend([ - "-pattern", - pattern - ]) - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V24swapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V24swapOutputs", - "V_24SWAP_METADATA", - "v_24swap", -] diff --git a/python/src/niwrap/afni/v_2d_im_reg.py b/python/src/niwrap/afni/v_2d_im_reg.py deleted file mode 100644 index 2cbcb48fc..000000000 --- a/python/src/niwrap/afni/v_2d_im_reg.py +++ /dev/null @@ -1,127 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_2D_IM_REG_METADATA = Metadata( - id="e128fa199e792a2b55b540ec32be59c11d9b8749.boutiques", - name="2dImReg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2dImRegOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_2d_im_reg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output 3d+time dataset""" - dx_file: OutputPathType | None - """File containing dx registration parameters in pixels/mm""" - dy_file: OutputPathType | None - """File containing dy registration parameters in pixels/mm""" - psi_file: OutputPathType | None - """File containing psi registration parameters in degrees""" - oldrms_file: OutputPathType | None - """File containing the volume RMS error for the original dataset""" - newrms_file: OutputPathType | None - """File containing the volume RMS error for the registered dataset""" - - -def v_2d_im_reg( - input_file: InputPathType, - prefix: str, - base_file: InputPathType | None = None, - base: float | None = None, - nofine: bool = False, - fine_blur: float | None = None, - fine_dxy: float | None = None, - fine_dphi: float | None = None, - dprefix: str | None = None, - dmm: bool = False, - rprefix: str | None = None, - debug: bool = False, - runner: Runner | None = None, -) -> V2dImRegOutputs: - """ - 2D image registration tool for 3D+time datasets, aligning images on a - slice-by-slice basis to a specified base image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Filename of input 3d+time dataset to process. - prefix: Prefix name for output 3d+time dataset. - base_file: Filename of 3d+time dataset for base image (default =\ - current input dataset). - base: Time index for base image (0 <= num) (default: num = 3). - nofine: Deactivate fine fit phase of image registration (default: fine\ - fit is active). - fine_blur: FWHM of blurring prior to registration (in pixels) (default:\ - blur = 1.0). - fine_dxy: Convergence tolerance for translations (in pixels) (default:\ - dxy = 0.07). - fine_dphi: Convergence tolerance for rotations (in degrees) (default:\ - dphi = 0.21). - dprefix: Write files containing the registration parameters for each\ - slice in chronological order. - dmm: Change dx and dy output format from pixels to mm. - rprefix: Write files containing the volume RMS error for the original\ - and the registered datasets. - debug: Lots of additional output to screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2dImRegOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_2D_IM_REG_METADATA) - cargs = [] - cargs.append("2dImReg") - cargs.append(execution.input_file(input_file)) - if base_file is not None: - cargs.append(execution.input_file(base_file)) - if base is not None: - cargs.append(str(base)) - if nofine: - cargs.append("-nofine") - if fine_blur is not None: - cargs.append(str(fine_blur)) - if fine_dxy is not None: - cargs.append(str(fine_dxy)) - if fine_dphi is not None: - cargs.append(str(fine_dphi)) - cargs.append(prefix) - if dprefix is not None: - cargs.append(dprefix) - if dmm: - cargs.append("-dmm") - if rprefix is not None: - cargs.append(rprefix) - if debug: - cargs.append("-debug") - ret = V2dImRegOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii"), - dx_file=execution.output_file(dprefix + ".dx") if (dprefix is not None) else None, - dy_file=execution.output_file(dprefix + ".dy") if (dprefix is not None) else None, - psi_file=execution.output_file(dprefix + ".psi") if (dprefix is not None) else None, - oldrms_file=execution.output_file(rprefix + ".oldrms") if (rprefix is not None) else None, - newrms_file=execution.output_file(rprefix + ".newrms") if (rprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2dImRegOutputs", - "V_2D_IM_REG_METADATA", - "v_2d_im_reg", -] diff --git a/python/src/niwrap/afni/v_2dcat.py b/python/src/niwrap/afni/v_2dcat.py deleted file mode 100644 index 90308db88..000000000 --- a/python/src/niwrap/afni/v_2dcat.py +++ /dev/null @@ -1,231 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_2DCAT_METADATA = Metadata( - id="86c841e523ad32a9e63fcb9b28fa7555580ced48.boutiques", - name="2dcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2dcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_2dcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType | None - """The main output image matrix file.""" - output_1_d: OutputPathType | None - """A 1D file containing the average of RGB values, if the prefix ends with - .1D.""" - - -def v_2dcat( - filenames: list[InputPathType], - scale_image: InputPathType | None = None, - scale_pixels: InputPathType | None = None, - scale_intensity: bool = False, - gscale: float | None = None, - rgb_out: bool = False, - res_in: list[float] | None = None, - respad_in: list[float] | None = None, - pad_val: float | None = None, - crop: list[float] | None = None, - autocrop_ctol: float | None = None, - autocrop_atol: float | None = None, - autocrop: bool = False, - zero_wrap: bool = False, - white_wrap: bool = False, - gray_wrap: float | None = None, - image_wrap: bool = False, - rand_wrap: bool = False, - prefix: str | None = None, - matrix: list[float] | None = None, - nx: float | None = None, - ny: float | None = None, - matrix_from_scale: bool = False, - gap: float | None = None, - gap_col: list[float] | None = None, - runner: Runner | None = None, -) -> V2dcatOutputs: - """ - Puts a set of images into an image matrix montage of NX by NY images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - filenames: List of input image files. - scale_image: Multiply each image in the output image matrix by the\ - color or intensity of the pixel in the scale image. - scale_pixels: Multiply each pixel in the output image by the color or\ - intensity of the pixel in the scale image. The scale image is resized\ - to the output image's resolution. - scale_intensity: Use the intensity (average color) of the pixel instead\ - of its color. - gscale: Apply additional scaling factor. - rgb_out: Force output to be in RGB, even if input is bytes. - res_in: Set resolution of all input images. - respad_in: Resample to max while respecting the aspect ratio, then pad\ - to desired pixel count. - pad_val: Set the padding value when using -respad_in. Should be in the\ - range [0, 255], default is 0. - crop: Crop images by specified number of pixels from the left, right,\ - top, and bottom. - autocrop_ctol: Automatically crop lines where RGB values differ by less\ - than the specified percentage from the corner pixel values. - autocrop_atol: Automatically crop lines where RGB values differ by less\ - than the specified percentage from the line average. - autocrop: Automatically crop lines with default tolerances using both\ - autocrop_atol and autocrop_ctol set to 20. - zero_wrap: Use solid black images if not enough images are provided to\ - fill the matrix. - white_wrap: Use solid white images if not enough images are provided to\ - fill the matrix. - gray_wrap: Use solid gray images if not enough images are provided to\ - fill the matrix. The gray value must be between 0 and 1.0. - image_wrap: Reuse images to fill the matrix. This is the default\ - behavior. - rand_wrap: Randomize the order of images when reusing to fill the\ - matrix. - prefix: Prefix the output file names with the specified string. - matrix: Specify the number of images in each row (NX) and column (NY)\ - of the image matrix. - nx: Specify the number of images in each row. - ny: Specify the number of images in each column. - matrix_from_scale: Set matrix dimensions NX and NY to be the same as\ - the SCALE_IMG's dimensions. Requires the -scale_image option. - gap: Put a gap of specified pixels between images. - gap_col: Set color of the gap line to specified R, G, B values. Values\ - range from 0 to 255. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2dcatOutputs`). - """ - if pad_val is not None and not (0 <= pad_val <= 255): - raise ValueError(f"'pad_val' must be between 0 <= x <= 255 but was {pad_val}") - if gray_wrap is not None and not (0 <= gray_wrap <= 1): - raise ValueError(f"'gray_wrap' must be between 0 <= x <= 1 but was {gray_wrap}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_2DCAT_METADATA) - cargs = [] - cargs.append("2dcat") - cargs.extend([execution.input_file(f) for f in filenames]) - if scale_image is not None: - cargs.extend([ - "-scale_image", - execution.input_file(scale_image) - ]) - if scale_pixels is not None: - cargs.extend([ - "-scale_pixels", - execution.input_file(scale_pixels) - ]) - if scale_intensity: - cargs.append("-scale_intensity") - if gscale is not None: - cargs.extend([ - "-gscale", - str(gscale) - ]) - if rgb_out: - cargs.append("-rgb_out") - if res_in is not None: - cargs.extend([ - "-res_in", - *map(str, res_in) - ]) - if respad_in is not None: - cargs.extend([ - "-respad_in", - *map(str, respad_in) - ]) - if pad_val is not None: - cargs.extend([ - "-pad_val", - str(pad_val) - ]) - if crop is not None: - cargs.extend([ - "-crop", - *map(str, crop) - ]) - if autocrop_ctol is not None: - cargs.extend([ - "-autocrop_ctol", - str(autocrop_ctol) - ]) - if autocrop_atol is not None: - cargs.extend([ - "-autocrop_atol", - str(autocrop_atol) - ]) - if autocrop: - cargs.append("-autocrop") - if zero_wrap: - cargs.append("-zero_wrap") - if white_wrap: - cargs.append("-white_wrap") - if gray_wrap is not None: - cargs.extend([ - "-gray_wrap", - str(gray_wrap) - ]) - if image_wrap: - cargs.append("-image_wrap") - if rand_wrap: - cargs.append("-rand_wrap") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if matrix is not None: - cargs.extend([ - "-matrix", - *map(str, matrix) - ]) - if nx is not None: - cargs.extend([ - "-nx", - str(nx) - ]) - if ny is not None: - cargs.extend([ - "-ny", - str(ny) - ]) - if matrix_from_scale: - cargs.append("-matrix_from_scale") - if gap is not None: - cargs.extend([ - "-gap", - str(gap) - ]) - if gap_col is not None: - cargs.extend([ - "-gap_col", - *map(str, gap_col) - ]) - ret = V2dcatOutputs( - root=execution.output_file("."), - output_image=execution.output_file(prefix + ".ppm") if (prefix is not None) else None, - output_1_d=execution.output_file(prefix + ".1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2dcatOutputs", - "V_2DCAT_METADATA", - "v_2dcat", -] diff --git a/python/src/niwrap/afni/v_2perm.py b/python/src/niwrap/afni/v_2perm.py deleted file mode 100644 index b42b92af6..000000000 --- a/python/src/niwrap/afni/v_2perm.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_2PERM_METADATA = Metadata( - id="59e66117db737fe0417f8f2ec096b420131bb96a.boutiques", - name="2perm", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2permOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_2perm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - file_a: OutputPathType | None - """First subset output file""" - file_b: OutputPathType | None - """Second subset output file""" - - -def v_2perm( - bottom_int: float, - top_int: float, - prefix: str | None = None, - comma: bool = False, - subset1_size: float | None = None, - subset2_size: float | None = None, - runner: Runner | None = None, -) -> V2permOutputs: - """ - Generates two random non-overlapping subsets of a given set of integers. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - bottom_int: Bottom integer of the range. - top_int: Top integer of the range. - prefix: Prefix for output files (default 'AFNIroolz'). - comma: Write each file as a single row of comma-separated numbers. - subset1_size: Size of the first subset (optional, default is half the\ - range). - subset2_size: Size of the second subset (optional, default is half the\ - range). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2permOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_2PERM_METADATA) - cargs = [] - cargs.append("2perm") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if comma: - cargs.append("-comma") - cargs.append(str(bottom_int)) - cargs.append(str(top_int)) - if subset1_size is not None: - cargs.append(str(subset1_size)) - if subset2_size is not None: - cargs.append(str(subset2_size)) - ret = V2permOutputs( - root=execution.output_file("."), - file_a=execution.output_file(prefix + "_A") if (prefix is not None) else None, - file_b=execution.output_file(prefix + "_B") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2permOutputs", - "V_2PERM_METADATA", - "v_2perm", -] diff --git a/python/src/niwrap/afni/v_2swap.py b/python/src/niwrap/afni/v_2swap.py deleted file mode 100644 index bcebb791b..000000000 --- a/python/src/niwrap/afni/v_2swap.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_2SWAP_METADATA = Metadata( - id="728c4876a96d25e9c23842571e532226995c4d5f.boutiques", - name="2swap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2swapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_2swap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_2swap( - input_files: list[InputPathType], - quiet: bool = False, - runner: Runner | None = None, -) -> V2swapOutputs: - """ - Swaps byte pairs on the files listed. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input files. - quiet: Work quietly. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2swapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_2SWAP_METADATA) - cargs = [] - cargs.append("2swap") - if quiet: - cargs.append("-q") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V2swapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2swapOutputs", - "V_2SWAP_METADATA", - "v_2swap", -] diff --git a/python/src/niwrap/afni/v_3_droimaker.py b/python/src/niwrap/afni/v_3_droimaker.py deleted file mode 100644 index 94db32f2d..000000000 --- a/python/src/niwrap/afni/v_3_droimaker.py +++ /dev/null @@ -1,188 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3_DROIMAKER_METADATA = Metadata( - id="dfdbf8bd123cafe427a36b018dc4ddc9b71a1066.boutiques", - name="3DROIMaker", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3DroimakerOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3_droimaker(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - gm_map: OutputPathType - """GM map of ROIs based on value- and volume-thresholding, corresponding to - gray matter regions of activation.""" - gmi_map: OutputPathType - """Map of inflated GM ROIs based on GM map, with ROIs inflated either by - user-design or WM skeleton.""" - - -def v_3_droimaker( - inset: InputPathType, - thresh: float, - prefix: str, - refset: InputPathType | None = None, - volthr: float | None = None, - only_conn_top: float | None = None, - inflate: float | None = None, - trim_off_wm: bool = False, - wm_skel: InputPathType | None = None, - skel_thr: float | None = None, - skel_stop: bool = False, - skel_stop_strict: bool = False, - csf_skel: InputPathType | None = None, - mask: InputPathType | None = None, - neigh_upto_vert: bool = False, - nifti: bool = False, - preinfl_inset: InputPathType | None = None, - preinfl_inflate: float | None = None, - dump_no_labtab: bool = False, - runner: Runner | None = None, -) -> V3DroimakerOutputs: - """ - Create a labelled set of ROIs from input data, useful in combining functional - and tractographic/structural data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: 3D volume(s) of values, especially functionally-derived\ - quantities like correlation values or ICA Z-scores. - thresh: Threshold for values in INSET, used to create ROI islands from\ - the 3D volume's sea of values. - prefix: Prefix of output name, with output files being: PREFIX_GM* and\ - PREFIX_GMI*. - refset: 3D (or multi-subbrick) volume containing integer values with\ - which to label specific GM ROIs after thresholding. - volthr: Minimum size a cluster of voxels must have in order to remain a\ - GM ROI after thresholding. Can reduce 'noisy' clusters. - only_conn_top: Select N max contiguous voxels in a region starting from\ - peak voxel and expanding. - inflate: Number of voxels to pad each found ROI in order to turn GM\ - ROIs into inflated (GMI) ROIs. - trim_off_wm: Trim the INSET to exclude voxels in WM by excluding those\ - which overlap an input WM skeleton. - wm_skel: 3D volume containing info of WM, as might be defined from an\ - FA map or anatomical segmentation. - skel_thr: Threshold value for WM skeleton if it is not a mask. - skel_stop: Stop inflation at locations which are already on WM\ - skeleton. - skel_stop_strict: Do not allow any inflation into the skel-region. - csf_skel: 3D volume containing info of CSF. Info must be a binary mask\ - already. - mask: Mask within which to apply threshold. Useful if the MINTHR is a\ - negative value. - neigh_upto_vert: Define neighbors loosely so that voxels can be grouped\ - into the same ROI if they share at least one vertex. - nifti: Switch to output *.nii.gz GM and GMI files. - preinfl_inset: Start with a WM ROI, inflate it to find the nearest GM,\ - then expand that GM and subtract away the WM+CSF parts. - preinfl_inflate: Number of voxels for initial inflation of PSET. - dump_no_labtab: Switch for turning off labeltable attachment to the\ - output GM and GMI files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3DroimakerOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3_DROIMAKER_METADATA) - cargs = [] - cargs.append("3dROIMaker") - cargs.append(execution.input_file(inset)) - cargs.extend([ - "-thresh", - str(thresh) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if refset is not None: - cargs.extend([ - "-refset", - execution.input_file(refset) - ]) - if volthr is not None: - cargs.extend([ - "-volthr", - str(volthr) - ]) - if only_conn_top is not None: - cargs.extend([ - "-only_conn_top", - str(only_conn_top) - ]) - if inflate is not None: - cargs.extend([ - "-inflate", - str(inflate) - ]) - if trim_off_wm: - cargs.append("-trim_off_wm") - if wm_skel is not None: - cargs.extend([ - "-wm_skel", - execution.input_file(wm_skel) - ]) - if skel_thr is not None: - cargs.extend([ - "-skel_thr", - str(skel_thr) - ]) - if skel_stop: - cargs.append("-skel_stop") - if skel_stop_strict: - cargs.append("-skel_stop_strict") - if csf_skel is not None: - cargs.extend([ - "-csf_skel", - execution.input_file(csf_skel) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if neigh_upto_vert: - cargs.append("-neigh_upto_vert") - if nifti: - cargs.append("-nifti") - if preinfl_inset is not None: - cargs.extend([ - "-preinfl_inset", - execution.input_file(preinfl_inset) - ]) - if preinfl_inflate is not None: - cargs.extend([ - "-preinfl_inflate", - str(preinfl_inflate) - ]) - if dump_no_labtab: - cargs.append("-dump_no_labtab") - ret = V3DroimakerOutputs( - root=execution.output_file("."), - gm_map=execution.output_file(prefix + "_GM+orig.*.HEAD"), - gmi_map=execution.output_file(prefix + "_GMI+orig.*.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3DroimakerOutputs", - "V_3_DROIMAKER_METADATA", - "v_3_droimaker", -] diff --git a/python/src/niwrap/afni/v_3d_aboverlap.py b/python/src/niwrap/afni/v_3d_aboverlap.py deleted file mode 100644 index 7b4299dfb..000000000 --- a/python/src/niwrap/afni/v_3d_aboverlap.py +++ /dev/null @@ -1,75 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ABOVERLAP_METADATA = Metadata( - id="ce33e10c4b1ac12e30e9f2905df1b25512061469.boutiques", - name="3dABoverlap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAboverlapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_aboverlap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_aboverlap( - dataset_a: InputPathType, - dataset_b: InputPathType, - no_automask: bool = False, - quiet: bool = False, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dAboverlapOutputs: - """ - Counts various metrics about how the automasks of datasets A and B overlap or - don't overlap. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset_a: First input dataset. - dataset_b: Second input dataset. - no_automask: Consider input datasets as masks (automask does not work\ - on mask datasets). - quiet: Be as quiet as possible (without being entirely mute). - verbose: Print out some progress reports (to stderr). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAboverlapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ABOVERLAP_METADATA) - cargs = [] - cargs.append("3dABoverlap") - cargs.append(execution.input_file(dataset_a)) - cargs.append(execution.input_file(dataset_b)) - if no_automask: - cargs.append("-no_automask") - if quiet: - cargs.append("-quiet") - if verbose: - cargs.append("-verb") - ret = V3dAboverlapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAboverlapOutputs", - "V_3D_ABOVERLAP_METADATA", - "v_3d_aboverlap", -] diff --git a/python/src/niwrap/afni/v_3d_acost.py b/python/src/niwrap/afni/v_3d_acost.py deleted file mode 100644 index 35b74238f..000000000 --- a/python/src/niwrap/afni/v_3d_acost.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ACOST_METADATA = Metadata( - id="0ff6573e114cd6d142c6db98eac6125eecf4d8dc.boutiques", - name="3dAcost", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAcostOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_acost(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType - """Output aligned dataset (HEAD file)""" - output_brik: OutputPathType - """Output aligned dataset (BRIK file)""" - - -def v_3d_acost( - infile: InputPathType, - basefile: InputPathType, - outfile: str, - all_cost: bool = False, - runner: Runner | None = None, -) -> V3dAcostOutputs: - """ - Allineate dataset to a base dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input dataset for allineation. - basefile: Base dataset for allineation. - outfile: Prefix for the output dataset. - all_cost: Prints all alignment cost metrics. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAcostOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ACOST_METADATA) - cargs = [] - cargs.append("3dAcost") - cargs.append(execution.input_file(infile)) - cargs.extend([ - "-base", - execution.input_file(basefile) - ]) - cargs.extend([ - "-prefix", - outfile - ]) - if all_cost: - cargs.append("-allcostX") - ret = V3dAcostOutputs( - root=execution.output_file("."), - output_head=execution.output_file(outfile + "+orig.HEAD"), - output_brik=execution.output_file(outfile + "+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAcostOutputs", - "V_3D_ACOST_METADATA", - "v_3d_acost", -] diff --git a/python/src/niwrap/afni/v_3d_afnito3_d.py b/python/src/niwrap/afni/v_3d_afnito3_d.py deleted file mode 100644 index 1abfd5b72..000000000 --- a/python/src/niwrap/afni/v_3d_afnito3_d.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AFNITO3_D_METADATA = Metadata( - id="e3f942482667d6f8a24043e5c140a337ebce0366.boutiques", - name="3dAFNIto3D", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAfnito3DOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_afnito3_d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output 3D file, either in binary or text format""" - - -def v_3d_afnito3_d( - dataset: InputPathType, - runner: Runner | None = None, -) -> V3dAfnito3DOutputs: - """ - Reads in an AFNI dataset, and writes it out as a 3D file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: AFNI dataset to be converted. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAfnito3DOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AFNITO3_D_METADATA) - cargs = [] - cargs.append("3dAFNIto3D") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(dataset)) - ret = V3dAfnito3DOutputs( - root=execution.output_file("."), - outfile=execution.output_file("[PREFIX].3D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAfnito3DOutputs", - "V_3D_AFNITO3_D_METADATA", - "v_3d_afnito3_d", -] diff --git a/python/src/niwrap/afni/v_3d_afnito_analyze.py b/python/src/niwrap/afni/v_3d_afnito_analyze.py deleted file mode 100644 index 35697fdc3..000000000 --- a/python/src/niwrap/afni/v_3d_afnito_analyze.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AFNITO_ANALYZE_METADATA = Metadata( - id="148bd389172590c5159d3af3816f81ff4b847248.boutiques", - name="3dAFNItoANALYZE", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAfnitoAnalyzeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_afnito_analyze(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_hdr_file: OutputPathType - """ANALYZE header file for each sub-brick""" - output_img_file: OutputPathType - """ANALYZE image file for each sub-brick""" - output_4d_hdr_file: OutputPathType - """Single ANALYZE header file if using -4D option""" - output_4d_img_file: OutputPathType - """Single ANALYZE image file if using -4D option""" - - -def v_3d_afnito_analyze( - output_name: str, - afni_dataset: InputPathType, - v_4d_option: bool = False, - orient_option: str | None = None, - runner: Runner | None = None, -) -> V3dAfnitoAnalyzeOutputs: - """ - Writes AFNI dataset to ANALYZE 7.5 format .hdr/.img file pairs. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_name: Output ANALYZE file base name (e.g., aname). - afni_dataset: Input AFNI dataset. - v_4d_option: Write all data to one big ANALYZE file pair named\ - aname.hdr/aname.img. - orient_option: Flip the dataset to a different orientation when writing\ - to ANALYZE files (e.g., LPI). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAfnitoAnalyzeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AFNITO_ANALYZE_METADATA) - cargs = [] - cargs.append("3dAFNItoANALYZE") - if v_4d_option: - cargs.append("-4D") - if orient_option is not None: - cargs.extend([ - "-orient", - orient_option - ]) - cargs.append(output_name) - cargs.append(execution.input_file(afni_dataset)) - ret = V3dAfnitoAnalyzeOutputs( - root=execution.output_file("."), - output_hdr_file=execution.output_file(output_name + "_[INDEX].hdr"), - output_img_file=execution.output_file(output_name + "_[INDEX].img"), - output_4d_hdr_file=execution.output_file(output_name + ".hdr"), - output_4d_img_file=execution.output_file(output_name + ".img"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAfnitoAnalyzeOutputs", - "V_3D_AFNITO_ANALYZE_METADATA", - "v_3d_afnito_analyze", -] diff --git a/python/src/niwrap/afni/v_3d_afnito_nifti.py b/python/src/niwrap/afni/v_3d_afnito_nifti.py deleted file mode 100644 index c95b51b7f..000000000 --- a/python/src/niwrap/afni/v_3d_afnito_nifti.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AFNITO_NIFTI_METADATA = Metadata( - id="c2219650fbe1d83f01eda91dff81cc7a82f46430.boutiques", - name="3dAFNItoNIFTI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAfnitoNiftiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_afnito_nifti(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_nifti: OutputPathType | None - """Output NIfTI file.""" - - -def v_3d_afnito_nifti( - input_dataset: InputPathType, - prefix: str | None = None, - verbose: bool = False, - force_float: bool = False, - pure: bool = False, - denote: bool = False, - oldid: bool = False, - newid: bool = False, - runner: Runner | None = None, -) -> V3dAfnitoNiftiOutputs: - """ - Converts an AFNI dataset to a NIfTI-1.1 file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input AFNI dataset. - prefix: Output NIfTI file prefix. - verbose: Print progress messages (increases verbosity if repeated). - force_float: Force the output dataset to be 32-bit floats. - pure: Do not write an AFNI extension field into the output file. - denote: Remove text notes from AFNI extension field that might contain\ - identifying information. - oldid: Retain the input dataset's AFNI ID code. - newid: Assign a new AFNI ID code to the dataset (default action). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAfnitoNiftiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AFNITO_NIFTI_METADATA) - cargs = [] - cargs.append("3dAFNItoNIFTI") - cargs.append(execution.input_file(input_dataset)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose: - cargs.append("-verb") - if force_float: - cargs.append("-float") - if pure: - cargs.append("-pure") - if denote: - cargs.append("-denote") - if oldid: - cargs.append("-oldid") - if newid: - cargs.append("-newid") - ret = V3dAfnitoNiftiOutputs( - root=execution.output_file("."), - output_nifti=execution.output_file(prefix + ".nii") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAfnitoNiftiOutputs", - "V_3D_AFNITO_NIFTI_METADATA", - "v_3d_afnito_nifti", -] diff --git a/python/src/niwrap/afni/v_3d_afnito_niml.py b/python/src/niwrap/afni/v_3d_afnito_niml.py deleted file mode 100644 index 81722779d..000000000 --- a/python/src/niwrap/afni/v_3d_afnito_niml.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AFNITO_NIML_METADATA = Metadata( - id="fa55e6421659dfc0a2252aa9f27a9bf2e6c19dfc.boutiques", - name="3dAFNItoNIML", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAfnitoNimlOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_afnito_niml(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_afnito_niml( - dset: InputPathType, - runner: Runner | None = None, -) -> V3dAfnitoNimlOutputs: - """ - Dumps AFNI dataset header information to stdout in NIML format. Mostly for - debugging and testing purposes!. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: AFNI dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAfnitoNimlOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AFNITO_NIML_METADATA) - cargs = [] - cargs.append("3dAFNItoNIML") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(dset)) - ret = V3dAfnitoNimlOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAfnitoNimlOutputs", - "V_3D_AFNITO_NIML_METADATA", - "v_3d_afnito_niml", -] diff --git a/python/src/niwrap/afni/v_3d_afnito_raw.py b/python/src/niwrap/afni/v_3d_afnito_raw.py deleted file mode 100644 index e3a47a220..000000000 --- a/python/src/niwrap/afni/v_3d_afnito_raw.py +++ /dev/null @@ -1,73 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AFNITO_RAW_METADATA = Metadata( - id="67bff5ed68a691d8da5e7aa97ecf946e7772101e.boutiques", - name="3dAFNItoRaw", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAfnitoRawOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_afnito_raw(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_afnito_raw( - dataset: str, - output_file: str | None = None, - force_float: bool = False, - runner: Runner | None = None, -) -> V3dAfnitoRawOutputs: - """ - Convert an AFNI brik file with multiple sub-briks to a raw file with each - sub-brik voxel concatenated voxel-wise. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input AFNI dataset with possible modifiers for sub-brick and\ - sub-range selection. - output_file: Name of the output file (not an AFNI dataset prefix).\ - Default is rawxyz.dat. - force_float: Force floating point output. Floating point forced if any\ - sub-brik scale factors not equal to 1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAfnitoRawOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AFNITO_RAW_METADATA) - cargs = [] - cargs.append("3dAFNItoRaw") - if output_file is not None: - cargs.extend([ - "-output", - output_file - ]) - if force_float: - cargs.append("-datum float") - cargs.append(dataset) - ret = V3dAfnitoRawOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAfnitoRawOutputs", - "V_3D_AFNITO_RAW_METADATA", - "v_3d_afnito_raw", -] diff --git a/python/src/niwrap/afni/v_3d_allineate.py b/python/src/niwrap/afni/v_3d_allineate.py deleted file mode 100644 index 48a354aa5..000000000 --- a/python/src/niwrap/afni/v_3d_allineate.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ALLINEATE_METADATA = Metadata( - id="9e9b34eca4cf79e9ab56b274a89a3cd8dc932bed.boutiques", - name="3dAllineate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAllineateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_allineate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_brik: OutputPathType - """Output dataset brick file""" - out_head: OutputPathType - """Output dataset head file""" - out_param_save: OutputPathType | None - """File holding saved warp parameters""" - out_matrix_save: OutputPathType | None - """File holding saved matrix transformations""" - - -def v_3d_allineate( - source: InputPathType, - prefix: str, - base: InputPathType | None = None, - param_save: str | None = None, - param_apply: str | None = None, - matrix_save: str | None = None, - matrix_apply: str | None = None, - cost: str | None = None, - interp: str | None = None, - final: str | None = None, - nmatch: float | None = None, - nopad: bool = False, - verbose: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dAllineateOutputs: - """ - Program to align one dataset (the 'source') to a 'base' dataset using an affine - (matrix) transformation of space. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - source: Source dataset file. - prefix: Output prefix. - base: Base dataset file. - param_save: Save the warp parameters in ASCII (.1D) format into file. - param_apply: Read warp parameters from file and apply them to the\ - source dataset. - matrix_save: Save the transformation matrix for each sub-brick into\ - file. - matrix_apply: Use the matrices in file to define the spatial\ - transformations to be applied. - cost: Defines the 'cost' function that defines the matching between the\ - source and the base. - interp: Defines interpolation method to use during matching process. - final: Defines the interpolation mode used to create the output dataset. - nmatch: Use at most 'nnn' scattered points to match the datasets. - nopad: Do not use zero-padding on the base image. - verbose: Print out verbose progress reports. - quiet: Don't print out verbose stuff. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAllineateOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ALLINEATE_METADATA) - cargs = [] - cargs.append("3dAllineate") - cargs.append(execution.input_file(source)) - if base is not None: - cargs.extend([ - "-base", - execution.input_file(base) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if param_save is not None: - cargs.extend([ - "-1Dparam_save", - param_save - ]) - if param_apply is not None: - cargs.extend([ - "-1Dparam_apply", - param_apply - ]) - if matrix_save is not None: - cargs.extend([ - "-1Dmatrix_save", - matrix_save - ]) - if matrix_apply is not None: - cargs.extend([ - "-1Dmatrix_apply", - matrix_apply - ]) - if cost is not None: - cargs.extend([ - "-cost", - cost - ]) - if interp is not None: - cargs.extend([ - "-interp", - interp - ]) - if final is not None: - cargs.extend([ - "-final", - final - ]) - if nmatch is not None: - cargs.extend([ - "-nmatch", - str(nmatch) - ]) - if nopad: - cargs.append("-nopad") - if verbose: - cargs.append("-verb") - if quiet: - cargs.append("-quiet") - ret = V3dAllineateOutputs( - root=execution.output_file("."), - out_brik=execution.output_file(prefix + "+orig.BRIK"), - out_head=execution.output_file(prefix + "+orig.HEAD"), - out_param_save=execution.output_file(param_save) if (param_save is not None) else None, - out_matrix_save=execution.output_file(matrix_save) if (matrix_save is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAllineateOutputs", - "V_3D_ALLINEATE_METADATA", - "v_3d_allineate", -] diff --git a/python/src/niwrap/afni/v_3d_amp_to_rsfc.py b/python/src/niwrap/afni/v_3d_amp_to_rsfc.py deleted file mode 100644 index b776cfe26..000000000 --- a/python/src/niwrap/afni/v_3d_amp_to_rsfc.py +++ /dev/null @@ -1,120 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AMP_TO_RSFC_METADATA = Metadata( - id="8f1035f559364c8aba66040e805e441ea060e9fe.boutiques", - name="3dAmpToRSFC", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAmpToRsfcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_amp_to_rsfc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_alff: OutputPathType - """Amplitude of low frequency fluctuations (L1 sum).""" - output_malff: OutputPathType - """ALFF divided by the mean value within the input/estimated whole brain - mask (mean-scaled ALFF).""" - output_falff: OutputPathType - """ALFF divided by sum of full amplitude spectrum (fractional ALFF).""" - output_rsfa: OutputPathType - """Square-root of summed square of low frequency fluctuations (L2 sum).""" - output_mrsfa: OutputPathType - """RSFA divided by the mean value within the input/estimated whole brain - mask (mean-scaled RSFA).""" - output_frsfa: OutputPathType - """ALFF divided by sum of full amplitude spectrum (fractional RSFA).""" - - -def v_3d_amp_to_rsfc( - prefix: str, - in_amp: InputPathType | None = None, - in_pow: InputPathType | None = None, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dAmpToRsfcOutputs: - """ - Convert spectral amplitudes into standard RSFC parameters. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file prefix; file names will be: PREFIX_ALFF,\ - PREFIX_FALFF, etc. - in_amp: Input file of one-sided spectral amplitudes, such as output by\ - 3dLombScargle. - in_pow: Input file of a one-sided power spectrum, such as output by\ - 3dLombScargle. - mask: Volume mask of voxels to include for calculations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAmpToRsfcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AMP_TO_RSFC_METADATA) - cargs = [] - cargs.append("3dAmpToRSFC") - cargs.append("{") - cargs.append("-in_amp") - if in_amp is not None: - cargs.extend([ - "-in_amp", - execution.input_file(in_amp) - ]) - cargs.append("|") - cargs.append("-in_pow") - if in_pow is not None: - cargs.extend([ - "-in_pow", - execution.input_file(in_pow) - ]) - cargs.append("}") - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-band") - cargs.append("[FBOT]") - cargs.append("[FTOP]") - cargs.append("{") - cargs.append("-mask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("}") - cargs.append("{") - cargs.append("-nifti") - cargs.append("}") - ret = V3dAmpToRsfcOutputs( - root=execution.output_file("."), - output_alff=execution.output_file(prefix + "_ALFF*"), - output_malff=execution.output_file(prefix + "_MALFF*"), - output_falff=execution.output_file(prefix + "_FALFF*"), - output_rsfa=execution.output_file(prefix + "_RSFA*"), - output_mrsfa=execution.output_file(prefix + "_MRSFA*"), - output_frsfa=execution.output_file(prefix + "_FRSFA*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAmpToRsfcOutputs", - "V_3D_AMP_TO_RSFC_METADATA", - "v_3d_amp_to_rsfc", -] diff --git a/python/src/niwrap/afni/v_3d_anhist.py b/python/src/niwrap/afni/v_3d_anhist.py deleted file mode 100644 index f629796e5..000000000 --- a/python/src/niwrap/afni/v_3d_anhist.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ANHIST_METADATA = Metadata( - id="a861594cf05d4476be6b171236514f1bcdbb8be4.boutiques", - name="3dAnhist", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAnhistOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_anhist(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_1_d: OutputPathType - """Dumped histogram data""" - output_ps: OutputPathType - """Plot of histogram data""" - - -def v_3d_anhist( - dataset: InputPathType, - quiet: bool = False, - dump_histogram: bool = False, - no_scurve: bool = False, - winsorize: str | None = None, - top_2peaks: bool = False, - label: str | None = None, - filename: str | None = None, - runner: Runner | None = None, -) -> V3dAnhistOutputs: - """ - Tool to analyze histogram peaks in a T1-weighted high-res brain image dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset, should be T1-weighted high-res brain image\ - (shorts only). - quiet: Suppress progress reports. - dump_histogram: Dump histogram data to Anhist.1D and plot to Anhist.ps. - no_scurve: Do not fit histogram with curves. - winsorize: Apply Winsorizing filter prior to histogram scan. Can\ - specify number of times (e.g., -w7). - top_2peaks: Analyze top 2 peaks only, for overlap, etc. - label: Use specified label for Anhist.ps plot file instead of the input\ - dataset filename. - filename: Use specified filename instead of 'Anhist'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAnhistOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ANHIST_METADATA) - cargs = [] - cargs.append("3dAnhist") - cargs.append(execution.input_file(dataset)) - if quiet: - cargs.append("-q") - if dump_histogram: - cargs.append("-h") - if no_scurve: - cargs.append("-F") - if winsorize is not None: - cargs.extend([ - "-w", - winsorize - ]) - if top_2peaks: - cargs.append("-2") - if label is not None: - cargs.extend([ - "-label", - label - ]) - if filename is not None: - cargs.extend([ - "-fname", - filename - ]) - ret = V3dAnhistOutputs( - root=execution.output_file("."), - output_1_d=execution.output_file("Anhist.1D"), - output_ps=execution.output_file("Anhist.ps"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAnhistOutputs", - "V_3D_ANHIST_METADATA", - "v_3d_anhist", -] diff --git a/python/src/niwrap/afni/v_3d_anova.py b/python/src/niwrap/afni/v_3d_anova.py deleted file mode 100644 index ee14f9873..000000000 --- a/python/src/niwrap/afni/v_3d_anova.py +++ /dev/null @@ -1,168 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ANOVA_METADATA = Metadata( - id="5e344a331305443b719b1dede3ddeb0a8eab25b7.boutiques", - name="3dANOVA", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAnovaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_anova(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - ftr_output: OutputPathType | None - """Output F-statistic dataset file""" - ftr_brick_output: OutputPathType | None - """Output F-statistic BRIK file""" - mean_output: OutputPathType | None - """Output mean dataset file""" - mean_brick_output: OutputPathType | None - """Output mean BRIK file""" - diff_output: OutputPathType | None - """Output difference dataset file""" - diff_brick_output: OutputPathType | None - """Output difference BRIK file""" - contr_output: OutputPathType | None - """Output contrast dataset file""" - contr_brick_output: OutputPathType | None - """Output contrast BRIK file""" - bucket_output: OutputPathType | None - """Output bucket dataset file""" - bucket_brick_output: OutputPathType | None - """Output bucket BRIK file""" - - -def v_3d_anova( - levels: int, - datasets: list[str], - voxel: int | None = None, - diskspace: bool = False, - mask: InputPathType | None = None, - debug: int | None = None, - ftr: str | None = None, - mean: str | None = None, - diff: str | None = None, - contr: str | None = None, - old_method: bool = False, - ok: bool = False, - assume_sph: bool = False, - bucket: str | None = None, - runner: Runner | None = None, -) -> V3dAnovaOutputs: - """ - Performs single-factor Analysis of Variance (ANOVA) on 3D datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - levels: Number of factor levels. - datasets: Datasets for each factor level. - voxel: Screen output for the specified voxel number. - diskspace: Print out the required disk space for program execution. - mask: Use sub-brick #0 of dataset to define which voxels to process. - debug: Request extra output verbosity. - ftr: F-statistic for treatment effect. - mean: Estimate of factor level mean. - diff: Difference between factor levels. - contr: Contrast in factor levels. - old_method: Perform ANOVA using the previous functionality. - ok: Confirm understanding of t-stats and sphericity assumptions with\ - old method. - assume_sph: Assume sphericity (zero-sum contrasts only). - bucket: Create one AFNI 'bucket' dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAnovaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ANOVA_METADATA) - cargs = [] - cargs.append("3dANOVA") - cargs.append("-levels") - cargs.append(str(levels)) - cargs.extend([ - "-dset", - *datasets - ]) - if voxel is not None: - cargs.extend([ - "-voxel", - str(voxel) - ]) - if diskspace: - cargs.append("-diskspace") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if ftr is not None: - cargs.extend([ - "-ftr", - ftr - ]) - if mean is not None: - cargs.extend([ - "-mean", - mean - ]) - if diff is not None: - cargs.extend([ - "-diff", - diff - ]) - if contr is not None: - cargs.extend([ - "-contr", - contr - ]) - if old_method: - cargs.append("-old_method") - if ok: - cargs.append("-OK") - if assume_sph: - cargs.append("-assume_sph") - if bucket is not None: - cargs.extend([ - "-bucket", - bucket - ]) - ret = V3dAnovaOutputs( - root=execution.output_file("."), - ftr_output=execution.output_file(ftr + ".HEAD") if (ftr is not None) else None, - ftr_brick_output=execution.output_file(ftr + ".BRIK") if (ftr is not None) else None, - mean_output=execution.output_file(mean + "_mean.HEAD") if (mean is not None) else None, - mean_brick_output=execution.output_file(mean + "_mean.BRIK") if (mean is not None) else None, - diff_output=execution.output_file(diff + "_diff.HEAD") if (diff is not None) else None, - diff_brick_output=execution.output_file(diff + "_diff.BRIK") if (diff is not None) else None, - contr_output=execution.output_file(contr + "_contr.HEAD") if (contr is not None) else None, - contr_brick_output=execution.output_file(contr + "_contr.BRIK") if (contr is not None) else None, - bucket_output=execution.output_file(bucket + ".HEAD") if (bucket is not None) else None, - bucket_brick_output=execution.output_file(bucket + ".BRIK") if (bucket is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAnovaOutputs", - "V_3D_ANOVA_METADATA", - "v_3d_anova", -] diff --git a/python/src/niwrap/afni/v_3d_anova2.py b/python/src/niwrap/afni/v_3d_anova2.py deleted file mode 100644 index 807e5e70f..000000000 --- a/python/src/niwrap/afni/v_3d_anova2.py +++ /dev/null @@ -1,264 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ANOVA2_METADATA = Metadata( - id="6aabc2d723b550f25dba0bfb60752185a653b6b0.boutiques", - name="3dANOVA2", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAnova2Outputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_anova2(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_ftr: OutputPathType | None - """F-statistic for treatment effect output file""" - output_fa: OutputPathType | None - """F-statistic for factor A effect output file""" - output_fb: OutputPathType | None - """F-statistic for factor B effect output file""" - output_fab: OutputPathType | None - """F-statistic for interaction output file""" - output_amean: OutputPathType | None - """Estimate mean of factor A level output file""" - output_bmean: OutputPathType | None - """Estimate mean of factor B level output file""" - output_xmean: OutputPathType | None - """Estimate mean of cell at level i of factor A and level j of factor B - output file""" - output_adiff: OutputPathType | None - """Difference between levels i and j of factor A output file""" - output_bdiff: OutputPathType | None - """Difference between levels i and j of factor B output file""" - output_xdiff: OutputPathType | None - """Difference between cell mean at A=i, B=j and cell mean at A=k, B=l output - file""" - output_acontr: OutputPathType | None - """Contrast in factor A levels output file""" - output_bcontr: OutputPathType | None - """Contrast in factor B levels output file""" - output_xcontr: OutputPathType | None - """Contrast in cell means output file""" - output_bucket: OutputPathType | None - """Create one AFNI 'bucket' dataset file""" - - -def v_3d_anova2( - type_: int, - alevels: int, - blevels: int, - dataset: list[str] | None = None, - voxel: int | None = None, - diskspace: bool = False, - mask: InputPathType | None = None, - ftr: str | None = None, - fa: str | None = None, - fb: str | None = None, - fab: str | None = None, - amean: str | None = None, - bmean: str | None = None, - xmean: str | None = None, - adiff: str | None = None, - bdiff: str | None = None, - xdiff: str | None = None, - acontr: str | None = None, - bcontr: str | None = None, - xcontr: str | None = None, - bucket: str | None = None, - old_method: bool = False, - ok: bool = False, - assume_sph: bool = False, - runner: Runner | None = None, -) -> V3dAnova2Outputs: - """ - This program performs a two-factor Analysis of Variance (ANOVA) on 3D datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - type_: Type of ANOVA model to be used: 1=fixed, 2=random, 3=mixed. - alevels: Number of levels of factor A. - blevels: Number of levels of factor B. - dataset: Data set for levels of factor A and factor B. - voxel: Screen output for voxel number. - diskspace: Print out disk space required for program execution. - mask: Use sub-brick #0 of dataset 'mset' to define which voxels to\ - process. - ftr: F-statistic for treatment effect. - fa: F-statistic for factor A effect. - fb: F-statistic for factor B effect. - fab: F-statistic for interaction. - amean: Estimate mean of factor A level. - bmean: Estimate mean of factor B level. - xmean: Estimate mean of cell at level i of factor A and level j of\ - factor B. - adiff: Difference between levels i and j of factor A. - bdiff: Difference between levels i and j of factor B. - xdiff: Difference between cell mean at A=i, B=j and cell mean at A=k,\ - B=l. - acontr: Contrast in factor A levels. - bcontr: Contrast in factor B levels. - xcontr: Contrast in cell means. - bucket: Create one AFNI 'bucket' dataset whose sub-bricks are obtained\ - by concatenating the above output files. - old_method: Request to perform ANOVA using the previous functionality\ - (requires -OK, also). - ok: Confirm understanding that contrasts that do not sum to zero have\ - inflated t-stats, and contrasts that do sum to zero assume sphericity\ - (to be used with -old_method). - assume_sph: Assume sphericity (zero-sum contrasts, only). This allows\ - use of the old_method for computing contrasts which sum to zero. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAnova2Outputs`). - """ - if not (1 <= type_ <= 3): - raise ValueError(f"'type_' must be between 1 <= x <= 3 but was {type_}") - if dataset is not None and not (1 <= len(dataset)): - raise ValueError(f"Length of 'dataset' must be greater than 1 but was {len(dataset)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ANOVA2_METADATA) - cargs = [] - cargs.append("3dANOVA2") - cargs.extend([ - "-type", - str(type_) - ]) - cargs.extend([ - "-alevels", - str(alevels) - ]) - cargs.extend([ - "-blevels", - str(blevels) - ]) - if dataset is not None: - cargs.extend([ - "-dset", - *dataset - ]) - if voxel is not None: - cargs.extend([ - "-voxel", - str(voxel) - ]) - if diskspace: - cargs.append("-diskspace") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if ftr is not None: - cargs.extend([ - "-ftr", - ftr - ]) - if fa is not None: - cargs.extend([ - "-fa", - fa - ]) - if fb is not None: - cargs.extend([ - "-fb", - fb - ]) - if fab is not None: - cargs.extend([ - "-fab", - fab - ]) - if amean is not None: - cargs.extend([ - "-amean", - amean - ]) - if bmean is not None: - cargs.extend([ - "-bmean", - bmean - ]) - if xmean is not None: - cargs.extend([ - "-xmean", - xmean - ]) - if adiff is not None: - cargs.extend([ - "-adiff", - adiff - ]) - if bdiff is not None: - cargs.extend([ - "-bdiff", - bdiff - ]) - if xdiff is not None: - cargs.extend([ - "-xdiff", - xdiff - ]) - if acontr is not None: - cargs.extend([ - "-acontr", - acontr - ]) - if bcontr is not None: - cargs.extend([ - "-bcontr", - bcontr - ]) - if xcontr is not None: - cargs.extend([ - "-xcontr", - xcontr - ]) - if bucket is not None: - cargs.extend([ - "-bucket", - bucket - ]) - if old_method: - cargs.append("-old_method") - if ok: - cargs.append("-OK") - if assume_sph: - cargs.append("-assume_sph") - ret = V3dAnova2Outputs( - root=execution.output_file("."), - output_ftr=execution.output_file(ftr + ".+tlrc") if (ftr is not None) else None, - output_fa=execution.output_file(fa + ".+tlrc") if (fa is not None) else None, - output_fb=execution.output_file(fb + ".+tlrc") if (fb is not None) else None, - output_fab=execution.output_file(fab + ".+tlrc") if (fab is not None) else None, - output_amean=execution.output_file(amean + ".+tlrc") if (amean is not None) else None, - output_bmean=execution.output_file(bmean + ".+tlrc") if (bmean is not None) else None, - output_xmean=execution.output_file(xmean + ".+tlrc") if (xmean is not None) else None, - output_adiff=execution.output_file(adiff + ".+tlrc") if (adiff is not None) else None, - output_bdiff=execution.output_file(bdiff + ".+tlrc") if (bdiff is not None) else None, - output_xdiff=execution.output_file(xdiff + ".+tlrc") if (xdiff is not None) else None, - output_acontr=execution.output_file(acontr + ".+tlrc") if (acontr is not None) else None, - output_bcontr=execution.output_file(bcontr + ".+tlrc") if (bcontr is not None) else None, - output_xcontr=execution.output_file(xcontr + ".+tlrc") if (xcontr is not None) else None, - output_bucket=execution.output_file(bucket + ".+tlrc") if (bucket is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAnova2Outputs", - "V_3D_ANOVA2_METADATA", - "v_3d_anova2", -] diff --git a/python/src/niwrap/afni/v_3d_anova3.py b/python/src/niwrap/afni/v_3d_anova3.py deleted file mode 100644 index f55192613..000000000 --- a/python/src/niwrap/afni/v_3d_anova3.py +++ /dev/null @@ -1,147 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ANOVA3_METADATA = Metadata( - id="6d54bc36377a2a039a659783b44df3ecbd6b1534.boutiques", - name="3dANOVA3", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAnova3Outputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_anova3(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_fa: OutputPathType - """Output file for the main ANOVA result.""" - outfile_fb: OutputPathType - """Output file for the main B ANOVA result.""" - outfile_fc: OutputPathType - """Output file for the main C ANOVA result.""" - outfile_fab: OutputPathType - """Output file for the interaction between A and B.""" - outfile_fac: OutputPathType - """Output file for the interaction between A and C.""" - outfile_fbc: OutputPathType - """Output file for the interaction between B and C.""" - outfile_fabc: OutputPathType - """Output file for the interaction between A, B, and C.""" - outfile_amean: OutputPathType - """Output file for the A mean results.""" - outfile_bmean: OutputPathType - """Output file for the B mean results.""" - - -def v_3d_anova3( - type_: int, - alevels: int, - blevels: int, - clevels: int, - dsets: list[str], - voxel_num: int | None = None, - diskspace: bool = False, - mask: InputPathType | None = None, - anova_options: list[str] | None = None, - runner: Runner | None = None, -) -> V3dAnova3Outputs: - """ - Performs three-factor ANOVA on 3D data sets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - type_: Type of ANOVA model to be used. k = 1: A,B,C fixed; AxBxC, k =\ - 2: A,B,C random; AxBxC, k = 3: A fixed; B,C random; AxBxC, k = 4: A,B\ - fixed; C random; AxBxC, k = 5: A,B fixed; C random; AxB,BxC,C(A). - alevels: Number of levels for factor A. - blevels: Number of levels for factor B. - clevels: Number of levels for factor C. - dsets: Input data sets for specific levels of factors A, B, and C. - voxel_num: Screen output for specified voxel number. - diskspace: Print out disk space required for program execution. - mask: Use sub-brick #0 of dataset to define which voxels to process. - anova_options: Modified ANOVA computation options. See:\ - https://afni.nimh.nih.gov/sscc/gangc/ANOVA_Mod.html. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAnova3Outputs`). - """ - if not (1 <= type_ <= 5): - raise ValueError(f"'type_' must be between 1 <= x <= 5 but was {type_}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ANOVA3_METADATA) - cargs = [] - cargs.append("3dANOVA3") - cargs.append("-type") - cargs.extend([ - "-type", - str(type_) - ]) - cargs.append("-alevels") - cargs.extend([ - "-alevels", - str(alevels) - ]) - cargs.append("-blevels") - cargs.extend([ - "-blevels", - str(blevels) - ]) - cargs.append("-clevels") - cargs.extend([ - "-clevels", - str(clevels) - ]) - cargs.extend([ - "-dset", - *dsets - ]) - if voxel_num is not None: - cargs.extend([ - "-voxel", - str(voxel_num) - ]) - if diskspace: - cargs.append("-diskspace") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("[OUTFILES]") - if anova_options is not None: - cargs.extend([ - "-old_method -OK -assume_sph", - *anova_options - ]) - ret = V3dAnova3Outputs( - root=execution.output_file("."), - outfile_fa=execution.output_file("[OUTFILE_FA]"), - outfile_fb=execution.output_file("[OUTFILE_FB]"), - outfile_fc=execution.output_file("[OUTFILE_FC]"), - outfile_fab=execution.output_file("[OUTFILE_FAB]"), - outfile_fac=execution.output_file("[OUTFILE_FAC]"), - outfile_fbc=execution.output_file("[OUTFILE_FBC]"), - outfile_fabc=execution.output_file("[OUTFILE_FABC]"), - outfile_amean=execution.output_file("[OUTFILE_AMEAN]"), - outfile_bmean=execution.output_file("[OUTFILE_BMEAN]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAnova3Outputs", - "V_3D_ANOVA3_METADATA", - "v_3d_anova3", -] diff --git a/python/src/niwrap/afni/v_3d_attribute.py b/python/src/niwrap/afni/v_3d_attribute.py deleted file mode 100644 index 6c1e935b7..000000000 --- a/python/src/niwrap/afni/v_3d_attribute.py +++ /dev/null @@ -1,95 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ATTRIBUTE_METADATA = Metadata( - id="07185f589357b6d2c84b335e833e86a619976b6b.boutiques", - name="3dAttribute", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAttributeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_attribute(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout: OutputPathType - """Output of the attribute value""" - - -def v_3d_attribute( - aname: str, - dset: InputPathType, - all_: bool = False, - name: bool = False, - center: bool = False, - ssep: str | None = None, - sprep: str | None = None, - quote: bool = False, - runner: Runner | None = None, -) -> V3dAttributeOutputs: - """ - Prints the value of the attribute 'aname' from the header of the dataset 'dset'. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - aname: Attribute name to be printed from the dataset. - dset: Dataset from which the attribute value will be printed. - all_: Print all attributes from the dataset. - name: Include attribute name in the output. - center: Print the center of volume in RAI coordinates. - ssep: Use string SSEP as a separator between strings for multiple\ - sub-bricks. - sprep: Use string SPREP to replace blank space in string attributes. - quote: Use single quote around each string. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAttributeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ATTRIBUTE_METADATA) - cargs = [] - cargs.append("3dAttribute") - if all_: - cargs.append("-all") - if name: - cargs.append("-name") - if center: - cargs.append("-center") - if ssep is not None: - cargs.extend([ - "-ssep", - ssep - ]) - if sprep is not None: - cargs.extend([ - "-sprep", - sprep - ]) - if quote: - cargs.append("-quote") - cargs.append(aname) - cargs.append(execution.input_file(dset)) - ret = V3dAttributeOutputs( - root=execution.output_file("."), - stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAttributeOutputs", - "V_3D_ATTRIBUTE_METADATA", - "v_3d_attribute", -] diff --git a/python/src/niwrap/afni/v_3d_auto_tcorrelate.py b/python/src/niwrap/afni/v_3d_auto_tcorrelate.py deleted file mode 100644 index 314d13928..000000000 --- a/python/src/niwrap/afni/v_3d_auto_tcorrelate.py +++ /dev/null @@ -1,132 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AUTO_TCORRELATE_METADATA = Metadata( - id="54f323538871e62136cb28afd7fdc9c55ace001b.boutiques", - name="3dAutoTcorrelate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAutoTcorrelateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_auto_tcorrelate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brick: OutputPathType | None - """Main output dataset""" - output_head: OutputPathType | None - """Header information for main output dataset""" - out1d_file: OutputPathType | None - """Output in 1D text format""" - - -def v_3d_auto_tcorrelate( - input_dataset: InputPathType, - pearson: bool = False, - eta2: bool = False, - polort: int | None = None, - autoclip: bool = False, - automask: bool = False, - mask: InputPathType | None = None, - mask_only_targets: bool = False, - mask_source: InputPathType | None = None, - prefix: str | None = None, - out1d: str | None = None, - time_: bool = False, - mmap_: bool = False, - runner: Runner | None = None, -) -> V3dAutoTcorrelateOutputs: - """ - Computes the correlation coefficient between the time series of each pair of - voxels in the input dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset. - pearson: Correlation is the normal Pearson (product moment) correlation\ - coefficient [default]. - eta2: Output is eta^2 measure from Cohen et al., NeuroImage, 2008. - polort: Remove polynomial trend of order 'm', for m=-1..3. - autoclip: Clip off low-intensity regions in the dataset. - automask: Apply automask to the dataset. - mask: Mask of both 'source' and 'target' voxels. - mask_only_targets: Provide output for all voxels. - mask_source: Provide output for voxels only in specified mask. - prefix: Save output into dataset with specified prefix. - out1d: Save output in a text file in 1D format. - time_: Mark output as a 3D+time dataset. - mmap_: Write .BRIK results to disk directly using Unix mmap(). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAutoTcorrelateOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AUTO_TCORRELATE_METADATA) - cargs = [] - cargs.append("3dAutoTcorrelate") - cargs.append(execution.input_file(input_dataset)) - if pearson: - cargs.append("-pearson") - if eta2: - cargs.append("-eta2") - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mask_only_targets: - cargs.append("-mask_only_targets") - if mask_source is not None: - cargs.extend([ - "-mask_source", - execution.input_file(mask_source) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if out1d is not None: - cargs.extend([ - "-out1D", - out1d - ]) - if time_: - cargs.append("-time") - if mmap_: - cargs.append("-mmap") - ret = V3dAutoTcorrelateOutputs( - root=execution.output_file("."), - output_brick=execution.output_file(prefix + ".BRIK") if (prefix is not None) else None, - output_head=execution.output_file(prefix + ".HEAD") if (prefix is not None) else None, - out1d_file=execution.output_file(out1d) if (out1d is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAutoTcorrelateOutputs", - "V_3D_AUTO_TCORRELATE_METADATA", - "v_3d_auto_tcorrelate", -] diff --git a/python/src/niwrap/afni/v_3d_autobox.py b/python/src/niwrap/afni/v_3d_autobox.py deleted file mode 100644 index aae89ab56..000000000 --- a/python/src/niwrap/afni/v_3d_autobox.py +++ /dev/null @@ -1,139 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AUTOBOX_METADATA = Metadata( - id="614b8e391ea136b04b4fe49d62f798c0eada766e.boutiques", - name="3dAutobox", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAutoboxOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_autobox(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_autobox( - input_: InputPathType, - prefix: str | None = None, - alt_input: InputPathType | None = None, - noclust: bool = False, - extent: bool = False, - extent_ijk: bool = False, - extent_ijk_to_file: str | None = None, - extent_ijk_midslice: bool = False, - extent_ijkord: bool = False, - extent_ijkord_to_file: str | None = None, - extent_xyz_to_file: str | None = None, - extent_xyz_midslice: bool = False, - npad: float | None = None, - npad_safety_on: bool = False, - runner: Runner | None = None, -) -> V3dAutoboxOutputs: - """ - Computes size of a box that fits around the volume. Can also be used to crop the - volume to that box. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - prefix: Crop the input dataset to the size of the box, and write an\ - output dataset with PREFIX for the name. If not used, no new volume is\ - written out. - alt_input: An alternate way to specify the input dataset. - noclust: Don't do any clustering to find the box. Any non-zero voxel\ - will be preserved in the cropped volume. - extent: Write to standard out the spatial extent of the box. - extent_ijk: Write out the 6 auto bbox ijk slice numbers to screen: imin\ - imax jmin jmax kmin kmax. - extent_ijk_to_file: Write out the 6 auto bbox ijk slice numbers to a\ - simple-formatted text file FF: imin imax jmin jmax kmin kmax. - extent_ijk_midslice: Write out the 3 ijk midslices of the autobox to\ - the screen: imid jmid kmid. - extent_ijkord: Write out the 6 auto bbox ijk slice numbers to screen in\ - a particular order and format. Useful for scripting. - extent_ijkord_to_file: Write out the 6 auto bbox ijk slice numbers to a\ - file in a particular order and format. Useful for 3dcalc expressions. - extent_xyz_to_file: Write out the 6 auto bbox xyz coordinates to a\ - simple-formatted text file GG: xmin xmax ymin ymax zmin zmax. - extent_xyz_midslice: Write out the 3 xyz midslices of the autobox to\ - the screen: xmid ymid zmid. - npad: Number of extra voxels to pad on each side of box. - npad_safety_on: Constrain npad-ded extents to be within dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAutoboxOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AUTOBOX_METADATA) - cargs = [] - cargs.append("3dAutobox") - cargs.append(execution.input_file(input_)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if alt_input is not None: - cargs.extend([ - "-input", - execution.input_file(alt_input) - ]) - if noclust: - cargs.append("-noclust") - if extent: - cargs.append("-extent") - if extent_ijk: - cargs.append("-extent_ijk") - if extent_ijk_to_file is not None: - cargs.extend([ - "-extent_ijk_to_file", - extent_ijk_to_file - ]) - if extent_ijk_midslice: - cargs.append("-extent_ijk_midslice") - if extent_ijkord: - cargs.append("-extent_ijkord") - if extent_ijkord_to_file is not None: - cargs.extend([ - "-extent_ijkord_to_file", - extent_ijkord_to_file - ]) - if extent_xyz_to_file is not None: - cargs.extend([ - "-extent_xyz_to_file", - extent_xyz_to_file - ]) - if extent_xyz_midslice: - cargs.append("-extent_xyz_midslice") - if npad is not None: - cargs.extend([ - "-npad", - str(npad) - ]) - if npad_safety_on: - cargs.append("-npad_safety_on") - ret = V3dAutoboxOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAutoboxOutputs", - "V_3D_AUTOBOX_METADATA", - "v_3d_autobox", -] diff --git a/python/src/niwrap/afni/v_3d_automask.py b/python/src/niwrap/afni/v_3d_automask.py deleted file mode 100644 index b65bff1ee..000000000 --- a/python/src/niwrap/afni/v_3d_automask.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_AUTOMASK_METADATA = Metadata( - id="ba13d99448c3e02722a06bb4c0bceafb30dbc0f2.boutiques", - name="3dAutomask", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dAutomaskOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_automask(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - brain_file: OutputPathType - """Output file from 3dautomask.""" - out_file: OutputPathType - """Output image file name.""" - brain_file_: OutputPathType - """Brain file (skull stripped).""" - out_file_: OutputPathType - """Mask file.""" - - -def v_3d_automask( - in_file: InputPathType, - clfrac: float | None = None, - dilate: int | None = None, - erode: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - runner: Runner | None = None, -) -> V3dAutomaskOutputs: - """ - Create a brain-only mask of the image using AFNI 3dAutomask command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dautomask. - clfrac: Sets the clip level fraction (must be 0.1-0.9). a small value\ - will tend to make the mask larger [default = 0.5]. - dilate: Dilate the mask outwards. - erode: Erode the mask inwards. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dAutomaskOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_AUTOMASK_METADATA) - cargs = [] - cargs.append("3dAutomask") - if clfrac is not None: - cargs.extend([ - "-clfrac", - str(clfrac) - ]) - if dilate is not None: - cargs.extend([ - "-dilate", - str(dilate) - ]) - if erode is not None: - cargs.extend([ - "-erode", - str(erode) - ]) - cargs.append(execution.input_file(in_file)) - if outputtype is not None: - cargs.append(outputtype) - ret = V3dAutomaskOutputs( - root=execution.output_file("."), - brain_file=execution.output_file(pathlib.Path(in_file).name + "_masked"), - out_file=execution.output_file(pathlib.Path(in_file).name + "_mask"), - brain_file_=execution.output_file("brain_file"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dAutomaskOutputs", - "V_3D_AUTOMASK_METADATA", - "v_3d_automask", -] diff --git a/python/src/niwrap/afni/v_3d_ball_match.py b/python/src/niwrap/afni/v_3d_ball_match.py deleted file mode 100644 index 2f1afd0c3..000000000 --- a/python/src/niwrap/afni/v_3d_ball_match.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BALL_MATCH_METADATA = Metadata( - id="fe3fd0a09e1cb0531678dcf999710e6d7163d194.boutiques", - name="3dBallMatch", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBallMatchOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_ball_match(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_stdout: OutputPathType - """Output containing matching coordinates and related data""" - - -def v_3d_ball_match( - input_dataset: InputPathType, - radius: float | None = None, - dataset_option: str | None = None, - ball_radius: float | None = None, - spheroid_axes: list[float] | None = None, - runner: Runner | None = None, -) -> V3dBallMatchOutputs: - """ - A tool to find a good match between a ball (filled sphere) of the given radius - and a dataset to determine a crude approximate center of the brain quickly. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g., Fred.nii). - radius: Radius of the 3D ball to match (in mm). - dataset_option: Specifies the input dataset. - ball_radius: Set the radius of the 3D ball to match (mm). - spheroid_axes: Match with a spheroid of revolution, with principal axis\ - radius 'a' and secondary axes radii 'b'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBallMatchOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BALL_MATCH_METADATA) - cargs = [] - cargs.append("3dBallMatch") - cargs.append(execution.input_file(input_dataset)) - if radius is not None: - cargs.append(str(radius)) - if dataset_option is not None: - cargs.extend([ - "-input", - dataset_option - ]) - if ball_radius is not None: - cargs.extend([ - "-ball", - str(ball_radius) - ]) - if spheroid_axes is not None: - cargs.extend([ - "-spheroid", - *map(str, spheroid_axes) - ]) - ret = V3dBallMatchOutputs( - root=execution.output_file("."), - output_stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBallMatchOutputs", - "V_3D_BALL_MATCH_METADATA", - "v_3d_ball_match", -] diff --git a/python/src/niwrap/afni/v_3d_bandpass.py b/python/src/niwrap/afni/v_3d_bandpass.py deleted file mode 100644 index fc7f8e56b..000000000 --- a/python/src/niwrap/afni/v_3d_bandpass.py +++ /dev/null @@ -1,158 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BANDPASS_METADATA = Metadata( - id="c411bed68642a28de02059c05daf1e8275470fca.boutiques", - name="3dBandpass", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBandpassOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_bandpass(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output file from 3dbandpass.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_bandpass( - highpass: float, - in_file: InputPathType, - lowpass: float, - automask: bool = False, - blur: float | None = None, - despike: bool = False, - local_pv: float | None = None, - mask: InputPathType | None = None, - nfft: int | None = None, - no_detrend: bool = False, - normalize: bool = False, - notrans: bool = False, - orthogonalize_dset: InputPathType | None = None, - orthogonalize_file: list[InputPathType] | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - tr: float | None = None, - runner: Runner | None = None, -) -> V3dBandpassOutputs: - """ - Program to lowpass and/or highpass each voxel time series in a dataset, offering - more/different options than Fourier. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - highpass: Highpass. - in_file: Input file to 3dbandpass. - lowpass: Lowpass. - automask: Create a mask from the input dataset. - blur: Blur (inside the mask only) with a filter width (fwhm) of 'fff'\ - millimeters. - despike: Despike each time series before other processing. hopefully,\ - you don't actually need to do this, which is why it is optional. - local_pv: Replace each vector by the local principal vector (aka first\ - singular vector) from a neighborhood of radius 'rrr' millimeters. note\ - that the pv time series is l2 normalized. this option is mostly for bob\ - cox to have fun with. - mask: Mask file. - nfft: Set the fft length [must be a legal value]. - no_detrend: Skip the quadratic detrending of the input that occurs\ - before the fft-based bandpassing. you would only want to do this if the\ - dataset had been detrended already in some other program. - normalize: Make all output time series have l2 norm = 1 (i.e., sum of\ - squares = 1). - notrans: Don't check for initial positive transients in the data. the\ - test is a little slow, so skipping it is ok, if you know the data time\ - series are transient-free. - orthogonalize_dset: Orthogonalize each voxel to the corresponding voxel\ - time series in dataset 'fset', which must have the same spatial and\ - temporal grid structure as the main input dataset. at present, only one\ - '-dsort' option is allowed. - orthogonalize_file: Also orthogonalize input to columns in f.1d.\ - multiple '-ort' options are allowed. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - tr: Set time step (tr) in sec [default=from dataset header]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBandpassOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BANDPASS_METADATA) - cargs = [] - cargs.append("3dBandpass") - if automask: - cargs.append("-automask") - if blur is not None: - cargs.extend([ - "-blur", - str(blur) - ]) - if despike: - cargs.append("-despike") - cargs.append(str(highpass)) - cargs.append(execution.input_file(in_file)) - if local_pv is not None: - cargs.extend([ - "-localPV", - str(local_pv) - ]) - cargs.append(str(lowpass)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if nfft is not None: - cargs.extend([ - "-nfft", - str(nfft) - ]) - if no_detrend: - cargs.append("-nodetrend") - if normalize: - cargs.append("-norm") - if notrans: - cargs.append("-notrans") - if orthogonalize_dset is not None: - cargs.extend([ - "-dsort", - execution.input_file(orthogonalize_dset) - ]) - if orthogonalize_file is not None: - cargs.extend([ - "-ort", - *[execution.input_file(f) for f in orthogonalize_file] - ]) - if outputtype is not None: - cargs.append(outputtype) - if tr is not None: - cargs.extend([ - "-dt", - str(tr) - ]) - ret = V3dBandpassOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_bp"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBandpassOutputs", - "V_3D_BANDPASS_METADATA", - "v_3d_bandpass", -] diff --git a/python/src/niwrap/afni/v_3d_blur_in_mask.py b/python/src/niwrap/afni/v_3d_blur_in_mask.py deleted file mode 100644 index 3a509dbdd..000000000 --- a/python/src/niwrap/afni/v_3d_blur_in_mask.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BLUR_IN_MASK_METADATA = Metadata( - id="54e83754ace4243a2e468e019f4934e172656ca3.boutiques", - name="3dBlurInMask", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBlurInMaskOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_blur_in_mask(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset""" - - -def v_3d_blur_in_mask( - input_file: InputPathType, - output_prefix: str, - fwhm: float, - fwhm_dataset: InputPathType | None = None, - mask: InputPathType | None = None, - multi_mask: InputPathType | None = None, - automask: bool = False, - preserve: bool = False, - quiet: bool = False, - float_: bool = False, - fwhm_xyz: list[float] | None = None, - runner: Runner | None = None, -) -> V3dBlurInMaskOutputs: - """ - Blurs a dataset spatially inside a mask. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Dataset to be smoothed and output. - output_prefix: Prefix for output dataset. - fwhm: Amount of smoothness to add to the dataset (in mm). - fwhm_dataset: Dataset containing the amount of smoothness for each\ - voxel. - mask: Mask dataset for blurring; voxels NOT in the mask will be zeroed\ - in the output. - multi_mask: Multi-mask dataset; each distinct nonzero value is treated\ - as a separate mask. - automask: Create an automask from the input dataset. - preserve: Preserve original values in the dataset outside the mask. - quiet: Don't be verbose with progress reports. - float_: Save dataset as floats. - fwhm_xyz: Add different amounts of smoothness in the 3 spatial\ - directions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBlurInMaskOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BLUR_IN_MASK_METADATA) - cargs = [] - cargs.append("3dBlurInMask") - cargs.append(execution.input_file(input_file)) - cargs.append(output_prefix) - cargs.extend([ - "-FWHM", - str(fwhm) - ]) - if fwhm_dataset is not None: - cargs.extend([ - "-FWHMdset", - execution.input_file(fwhm_dataset) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if multi_mask is not None: - cargs.extend([ - "-Mmask", - execution.input_file(multi_mask) - ]) - if automask: - cargs.append("-automask") - if preserve: - cargs.append("-preserve") - if quiet: - cargs.append("-quiet") - if float_: - cargs.append("-float") - if fwhm_xyz is not None: - cargs.extend([ - "-FWHMxyz", - *map(str, fwhm_xyz) - ]) - ret = V3dBlurInMaskOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBlurInMaskOutputs", - "V_3D_BLUR_IN_MASK_METADATA", - "v_3d_blur_in_mask", -] diff --git a/python/src/niwrap/afni/v_3d_blur_to_fwhm.py b/python/src/niwrap/afni/v_3d_blur_to_fwhm.py deleted file mode 100644 index b9f7d406d..000000000 --- a/python/src/niwrap/afni/v_3d_blur_to_fwhm.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BLUR_TO_FWHM_METADATA = Metadata( - id="48e6ee8deafc60e001f0e39b991e7d7b95a40948.boutiques", - name="3dBlurToFWHM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBlurToFwhmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_blur_to_fwhm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_blur_to_fwhm( - in_file: InputPathType, - automask: bool = False, - blurmaster: InputPathType | None = None, - fwhm: float | None = None, - fwhmxy: float | None = None, - mask: InputPathType | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - runner: Runner | None = None, -) -> V3dBlurToFwhmOutputs: - """ - Blurs a 'master' dataset until it reaches a specified FWHM smoothness - (approximately). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: The dataset that will be smoothed. - automask: Create an automask from the input dataset. - blurmaster: The dataset whose smoothness controls the process. - fwhm: Blur until the 3d fwhm reaches this value (in mm). - fwhmxy: Blur until the 2d (x,y)-plane fwhm reaches this value (in mm). - mask: Mask dataset, if desired. voxels not in mask will be set to zero\ - in output. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBlurToFwhmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BLUR_TO_FWHM_METADATA) - cargs = [] - cargs.append("3dBlurToFWHM") - if automask: - cargs.append("-automask") - if blurmaster is not None: - cargs.extend([ - "-blurmaster", - execution.input_file(blurmaster) - ]) - if fwhm is not None: - cargs.extend([ - "-FWHM", - str(fwhm) - ]) - if fwhmxy is not None: - cargs.extend([ - "-FWHMxy", - str(fwhmxy) - ]) - cargs.extend([ - "-input", - execution.input_file(in_file) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("[OUT_FILE]") - if outputtype is not None: - cargs.append(outputtype) - ret = V3dBlurToFwhmOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_afni"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBlurToFwhmOutputs", - "V_3D_BLUR_TO_FWHM_METADATA", - "v_3d_blur_to_fwhm", -] diff --git a/python/src/niwrap/afni/v_3d_brain_sync.py b/python/src/niwrap/afni/v_3d_brain_sync.py deleted file mode 100644 index 7102be5ca..000000000 --- a/python/src/niwrap/afni/v_3d_brain_sync.py +++ /dev/null @@ -1,115 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BRAIN_SYNC_METADATA = Metadata( - id="5b4873a7460d63bb6ab8b2f718571646d6b0ba3b.boutiques", - name="3dBrainSync", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBrainSyncOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_brain_sync(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - qprefix_output: OutputPathType | None - """Output dataset after orthogonal matrix transformation""" - pprefix_output: OutputPathType | None - """Output dataset after permutation transformation""" - qprefix_sval: OutputPathType | None - """Singular values from the BC' decomposition""" - qprefix_qmat: OutputPathType | None - """Q matrix""" - pprefix_perm: OutputPathType | None - """Permutation indexes p(i)""" - - -def v_3d_brain_sync( - inset1: InputPathType, - inset2: InputPathType, - qprefix: str | None = None, - pprefix: str | None = None, - normalize: bool = False, - mask: InputPathType | None = None, - verb: bool = False, - runner: Runner | None = None, -) -> V3dBrainSyncOutputs: - """ - 'Synchronizes' the -inset2 dataset to match the -inset1 dataset, using - orthogonal or permutation transformation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset1: Reference dataset. - inset2: Dataset to be matched to the reference dataset. - qprefix: Specifies the output dataset to be used for the orthogonal\ - matrix transformation. - pprefix: Specifies the output dataset to be used for the permutation\ - transformation. - normalize: Normalize the output dataset(s) so that each time series has\ - sum-of-squares = 1. - mask: Only operate on nonzero voxels in the mask dataset. - verb: Print some progress reports and auxiliary information. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBrainSyncOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BRAIN_SYNC_METADATA) - cargs = [] - cargs.append("3dBrainSync") - cargs.extend([ - "-inset1", - execution.input_file(inset1) - ]) - cargs.extend([ - "-inset2", - execution.input_file(inset2) - ]) - if qprefix is not None: - cargs.extend([ - "-Qprefix", - qprefix - ]) - if pprefix is not None: - cargs.extend([ - "-Pprefix", - pprefix - ]) - if normalize: - cargs.append("-normalize") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if verb: - cargs.append("-verb") - ret = V3dBrainSyncOutputs( - root=execution.output_file("."), - qprefix_output=execution.output_file(qprefix + ".nii") if (qprefix is not None) else None, - pprefix_output=execution.output_file(pprefix + ".nii") if (pprefix is not None) else None, - qprefix_sval=execution.output_file(qprefix + ".sval.1D") if (qprefix is not None) else None, - qprefix_qmat=execution.output_file(qprefix + ".qmat.1D") if (qprefix is not None) else None, - pprefix_perm=execution.output_file(pprefix + ".perm.1D") if (pprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBrainSyncOutputs", - "V_3D_BRAIN_SYNC_METADATA", - "v_3d_brain_sync", -] diff --git a/python/src/niwrap/afni/v_3d_brain_voyagerto_afni.py b/python/src/niwrap/afni/v_3d_brain_voyagerto_afni.py deleted file mode 100644 index ce678cbb5..000000000 --- a/python/src/niwrap/afni/v_3d_brain_voyagerto_afni.py +++ /dev/null @@ -1,128 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BRAIN_VOYAGERTO_AFNI_METADATA = Metadata( - id="6e57612e994ff9fb4392a1ea7a2df2f7bddd8e62.boutiques", - name="3dBRAIN_VOYAGERtoAFNI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBrainVoyagertoAfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_brain_voyagerto_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik_file: OutputPathType - """Output BRIK file""" - output_head_file: OutputPathType - """Output HEAD file""" - - -def v_3d_brain_voyagerto_afni( - input_file: InputPathType, - force_byte_swap: bool = False, - brainvoyager_qx: bool = False, - tlrc_space: bool = False, - acpc_space: bool = False, - orig_space: bool = False, - prefix: str | None = None, - novolreg: bool = False, - noxform: bool = False, - set_environment: str | None = None, - trace_debugging: bool = False, - trace_extreme_debugging: bool = False, - turn_off_memory_tracing: bool = False, - turn_on_memory_tracing: bool = False, - runner: Runner | None = None, -) -> V3dBrainVoyagertoAfniOutputs: - """ - Converts a BrainVoyager vmr dataset to AFNI's BRIK format based on information - from BrainVoyager's website. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input BrainVoyager VMR file. - force_byte_swap: Force byte swapping. - brainvoyager_qx: .vmr file is from BrainVoyager QX. - tlrc_space: Dset in tlrc space. - acpc_space: Dset in acpc-aligned space. - orig_space: Dset in orig space. - prefix: Prefix for output files. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - noxform: Same as -novolreg. - set_environment: Set environment variable ENVname to be ENVvalue.\ - Quotes are necessary. - trace_debugging: Turns on In/Out debug and Memory tracing. - trace_extreme_debugging: Turns on extreme tracing. - turn_off_memory_tracing: Turn off memory tracing. - turn_on_memory_tracing: Turn on memory tracing (default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBrainVoyagertoAfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BRAIN_VOYAGERTO_AFNI_METADATA) - cargs = [] - cargs.append("3dBRAIN_VOYAGERtoAFNI") - cargs.extend([ - "--input", - execution.input_file(input_file) - ]) - if force_byte_swap: - cargs.append("-bs") - if brainvoyager_qx: - cargs.append("-qx") - if tlrc_space: - cargs.append("-tlrc") - if acpc_space: - cargs.append("-acpc") - if orig_space: - cargs.append("-orig") - if prefix is not None: - cargs.extend([ - "--prefix", - prefix - ]) - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if set_environment is not None: - cargs.extend([ - "-setenv", - set_environment - ]) - if trace_debugging: - cargs.append("-trace") - if trace_extreme_debugging: - cargs.append("-TRACE") - if turn_off_memory_tracing: - cargs.append("-nomall") - if turn_on_memory_tracing: - cargs.append("-yesmall") - ret = V3dBrainVoyagertoAfniOutputs( - root=execution.output_file("."), - output_brik_file=execution.output_file("output.BRIK"), - output_head_file=execution.output_file("output.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBrainVoyagertoAfniOutputs", - "V_3D_BRAIN_VOYAGERTO_AFNI_METADATA", - "v_3d_brain_voyagerto_afni", -] diff --git a/python/src/niwrap/afni/v_3d_brick_stat.py b/python/src/niwrap/afni/v_3d_brick_stat.py deleted file mode 100644 index a84ccf739..000000000 --- a/python/src/niwrap/afni/v_3d_brick_stat.py +++ /dev/null @@ -1,195 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_BRICK_STAT_METADATA = Metadata( - id="2171879e0c09931b6800be575110e0354a0a8e86.boutiques", - name="3dBrickStat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dBrickStatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_brick_stat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - console_output: OutputPathType - """Console output of computed statistics""" - - -def v_3d_brick_stat( - dataset: str, - quick: bool = False, - slow: bool = False, - min_: bool = False, - max_: bool = False, - mean: bool = False, - sum_: bool = False, - var: bool = False, - stdev: bool = False, - count: bool = False, - volume: bool = False, - positive: bool = False, - negative: bool = False, - zero: bool = False, - non_positive: bool = False, - non_negative: bool = False, - non_zero: bool = False, - absolute: bool = False, - nan: bool = False, - nonan: bool = False, - mask: str | None = None, - mrange: list[float] | None = None, - mvalue: float | None = None, - automask: bool = False, - percentile: list[float] | None = None, - perclist: list[float] | None = None, - median: bool = False, - perc_quiet: bool = False, - ver: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> V3dBrickStatOutputs: - """ - Compute voxel statistics of an input dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - quick: Get the information from the header only (default). - slow: Read the whole dataset to find the min and max values. - min_: Print the minimum value in dataset. - max_: Print the maximum value in dataset (default). - mean: Print the mean value in dataset. - sum_: Print the sum of values in the dataset. - var: Print the variance in the dataset. - stdev: Print the standard deviation in the dataset. - count: Print the number of voxels included. - volume: Print the volume of voxels included in microliters. - positive: Include only positive voxel values. - negative: Include only negative voxel values. - zero: Include only zero voxel values. - non_positive: Include only voxel values 0 or negative. - non_negative: Include only voxel values 0 or greater. - non_zero: Include only voxel values not equal to 0. - absolute: Use absolute value of voxel values for all calculations. - nan: Include only voxel values that are NaN or inf. Forces -slow mode. - nonan: Exclude voxel values that are NaN or inf. - mask: Use the specified dataset as mask to include/exclude voxels. - mrange: Only accept values between MIN and MAX (inclusive) from the\ - mask. - mvalue: Only accept values equal to VAL from the mask. - automask: Automatically compute mask for dataset. Cannot be combined\ - with -mask. - percentile: Compute and print percentile values from p0% to p1% at a\ - step of ps%. Only one sub-brick is accepted as input with this option. - perclist: Like -percentile, but output the given percentiles. - median: Shortcut for -percentile 50 1 50 (or -perclist 1 50). - perc_quiet: Only print percentile results, not input percentile cutoffs. - ver: Print author and version info. - help_: Print help screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dBrickStatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_BRICK_STAT_METADATA) - cargs = [] - cargs.append("3dBrickStat") - cargs.append(dataset) - if quick: - cargs.append("-quick") - if slow: - cargs.append("-slow") - if min_: - cargs.append("-min") - if max_: - cargs.append("-max") - if mean: - cargs.append("-mean") - if sum_: - cargs.append("-sum") - if var: - cargs.append("-var") - if stdev: - cargs.append("-stdev") - if count: - cargs.append("-count") - if volume: - cargs.append("-volume") - if positive: - cargs.append("-positive") - if negative: - cargs.append("-negative") - if zero: - cargs.append("-zero") - if non_positive: - cargs.append("-non-positive") - if non_negative: - cargs.append("-non-negative") - if non_zero: - cargs.append("-non-zero") - if absolute: - cargs.append("-absolute") - if nan: - cargs.append("-nan") - if nonan: - cargs.append("-nonan") - if mask is not None: - cargs.extend([ - "-mask", - mask - ]) - if mrange is not None: - cargs.extend([ - "-mrange", - *map(str, mrange) - ]) - if mvalue is not None: - cargs.extend([ - "-mvalue", - str(mvalue) - ]) - if automask: - cargs.append("-automask") - if percentile is not None: - cargs.extend([ - "-percentile", - *map(str, percentile) - ]) - if perclist is not None: - cargs.extend([ - "-perclist", - *map(str, perclist) - ]) - if median: - cargs.append("-median") - if perc_quiet: - cargs.append("-perc_quiet") - if ver: - cargs.append("-ver") - if help_: - cargs.append("-help") - ret = V3dBrickStatOutputs( - root=execution.output_file("."), - console_output=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dBrickStatOutputs", - "V_3D_BRICK_STAT_METADATA", - "v_3d_brick_stat", -] diff --git a/python/src/niwrap/afni/v_3d_clip_level.py b/python/src/niwrap/afni/v_3d_clip_level.py deleted file mode 100644 index 45c9b0eee..000000000 --- a/python/src/niwrap/afni/v_3d_clip_level.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CLIP_LEVEL_METADATA = Metadata( - id="cbab385648affc3f2118e85fff0817d898233dad.boutiques", - name="3dClipLevel", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dClipLevelOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_clip_level(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_clip_level( - dataset: InputPathType, - runner: Runner | None = None, -) -> V3dClipLevelOutputs: - """ - Estimates the value at which to clip the anatomical dataset so that background - regions are set to zero. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset (e.g. dataset.nii.gz). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dClipLevelOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CLIP_LEVEL_METADATA) - cargs = [] - cargs.append("3dClipLevel") - cargs.append("[options]") - cargs.append(execution.input_file(dataset)) - ret = V3dClipLevelOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dClipLevelOutputs", - "V_3D_CLIP_LEVEL_METADATA", - "v_3d_clip_level", -] diff --git a/python/src/niwrap/afni/v_3d_clust_count.py b/python/src/niwrap/afni/v_3d_clust_count.py deleted file mode 100644 index 6caa93a99..000000000 --- a/python/src/niwrap/afni/v_3d_clust_count.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CLUST_COUNT_METADATA = Metadata( - id="98fcc8c7fba23c3985c9517555b10b2b9741fa23.boutiques", - name="3dClustCount", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dClustCountOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_clust_count(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - clustcount_niml: OutputPathType | None - """Summed results file in NIML format.""" - clustcount_1_d: OutputPathType | None - """Summed results file in 1D format (when '-final' is used).""" - final_clustcount_niml: OutputPathType | None - """Summed results file in NIML format (when '-final' is used).""" - - -def v_3d_clust_count( - datasets: list[InputPathType], - prefix: str | None = None, - final: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dClustCountOutputs: - """ - This program takes as input 1 or more datasets, thresholds them at various - levels, and counts up the number of clusters of various sizes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input datasets to be processed. - prefix: Prefix of the filename into which results will be summed.\ - Actual filename will be 'sss.clustcount.niml'. If this file already\ - exists, results from the current run will be summed into the existing\ - results and the file then re-written. - final: Output results in a format similar to 3dClustSim -- as 1D and\ - NIML formatted files with probabilities of various cluster sizes. This\ - option can be used without any input datasets to create final output\ - files from saved '.clustcount.niml' output file from earlier runs. - quiet: Suppresses progress reports and other informational messages.\ - Should be placed first in the command line to quiet most messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dClustCountOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CLUST_COUNT_METADATA) - cargs = [] - cargs.append("3dClustCount") - cargs.extend([execution.input_file(f) for f in datasets]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if final: - cargs.append("-final") - if quiet: - cargs.append("-quiet") - ret = V3dClustCountOutputs( - root=execution.output_file("."), - clustcount_niml=execution.output_file(prefix + ".clustcount.niml") if (prefix is not None) else None, - clustcount_1_d=execution.output_file(prefix + ".1D") if (prefix is not None) else None, - final_clustcount_niml=execution.output_file(prefix + ".niml") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dClustCountOutputs", - "V_3D_CLUST_COUNT_METADATA", - "v_3d_clust_count", -] diff --git a/python/src/niwrap/afni/v_3d_clust_sim.py b/python/src/niwrap/afni/v_3d_clust_sim.py deleted file mode 100644 index 4f1e3ee4f..000000000 --- a/python/src/niwrap/afni/v_3d_clust_sim.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CLUST_SIM_METADATA = Metadata( - id="83de2ab5d958ac816560b23c9f06a1204e67508e.boutiques", - name="3dClustSim", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dClustSimOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_clust_sim(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_nn1_1sided: OutputPathType - """Output file for NN1 with 1-sided thresholding""" - output_nn1_2sided: OutputPathType - """Output file for NN1 with 2-sided thresholding""" - output_nn1_bisided: OutputPathType - """Output file for NN1 with bi-sided thresholding""" - output_nn2_1sided: OutputPathType - """Output file for NN2 with 1-sided thresholding""" - output_nn2_2sided: OutputPathType - """Output file for NN2 with 2-sided thresholding""" - output_nn2_bisided: OutputPathType - """Output file for NN2 with bi-sided thresholding""" - output_nn3_1sided: OutputPathType - """Output file for NN3 with 1-sided thresholding""" - output_nn3_2sided: OutputPathType - """Output file for NN3 with 2-sided thresholding""" - output_nn3_bisided: OutputPathType - """Output file for NN3 with bi-sided thresholding""" - mask_compressed: OutputPathType - """Compressed ASCII encoding of the mask volume""" - - -def v_3d_clust_sim( - runner: Runner | None = None, -) -> V3dClustSimOutputs: - """ - Program to estimate the probability of false positive (noise-only) clusters. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dClustSimOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CLUST_SIM_METADATA) - cargs = [] - cargs.append("3dClustSim") - cargs.append("[OPTIONS]") - ret = V3dClustSimOutputs( - root=execution.output_file("."), - output_nn1_1sided=execution.output_file("[PREFIX].NN1_1sided.1D"), - output_nn1_2sided=execution.output_file("[PREFIX].NN1_2sided.1D"), - output_nn1_bisided=execution.output_file("[PREFIX].NN1_bisided.1D"), - output_nn2_1sided=execution.output_file("[PREFIX].NN2_1sided.1D"), - output_nn2_2sided=execution.output_file("[PREFIX].NN2_2sided.1D"), - output_nn2_bisided=execution.output_file("[PREFIX].NN2_bisided.1D"), - output_nn3_1sided=execution.output_file("[PREFIX].NN3_1sided.1D"), - output_nn3_2sided=execution.output_file("[PREFIX].NN3_2sided.1D"), - output_nn3_bisided=execution.output_file("[PREFIX].NN3_bisided.1D"), - mask_compressed=execution.output_file("[PREFIX].mask"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dClustSimOutputs", - "V_3D_CLUST_SIM_METADATA", - "v_3d_clust_sim", -] diff --git a/python/src/niwrap/afni/v_3d_clusterize.py b/python/src/niwrap/afni/v_3d_clusterize.py deleted file mode 100644 index 184c77d80..000000000 --- a/python/src/niwrap/afni/v_3d_clusterize.py +++ /dev/null @@ -1,204 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CLUSTERIZE_METADATA = Metadata( - id="e57f2a4921df42477e28df98e2a64dd9155599d0.boutiques", - name="3dClusterize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dClusterizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_clusterize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_map_file: OutputPathType | None - """Output map of cluster ROIs""" - out_data_file: OutputPathType | None - """Cluster-masked version of the data volume""" - out_mask_file: OutputPathType | None - """Utilized mask dataset""" - - -def v_3d_clusterize( - inset: InputPathType, - ithr: str, - nn: int, - mask: InputPathType | None = None, - mask_from_hdr: bool = False, - out_mask: str | None = None, - idat: str | None = None, - onesided: str | None = None, - twosided: str | None = None, - bisided: str | None = None, - within_range: str | None = None, - clust_nvox: int | None = None, - clust_vol: int | None = None, - pref_map: str | None = None, - pref_dat: str | None = None, - one_d_format: bool = False, - no_one_d_format: bool = False, - summarize: bool = False, - nosum: bool = False, - quiet: bool = False, - outvol_if_no_clust: bool = False, - orient: str | None = None, - abs_table_data: bool = False, - binary: bool = False, - runner: Runner | None = None, -) -> V3dClusterizeOutputs: - """ - A tool for voxelwise thresholding and clusterizing of datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: Load in a dataset for thresholding and clusterizing. - ithr: Specify the sub-brick to use as the threshold source. - nn: Specify the number of voxel neighbors (1: 6, 2: 18, 3: 26). - mask: Load in a dataset to use as a mask. - mask_from_hdr: Use internal mask from dataset header. - out_mask: Specify to dump the utilized mask as a dataset. - idat: Specify the sub-brick to use as the data source. - onesided: Perform one-sided testing. - twosided: Perform two-sided testing. - bisided: Perform bisided testing. - within_range: Keep values within the range [AA, BB]. - clust_nvox: Specify the minimum cluster size in terms of number of\ - voxels. - clust_vol: Specify the minimum cluster size by volume in microliters. - pref_map: Prefix/filename of the output map of cluster ROIs. - pref_dat: Output a cluster-masked version of the data volume. - one_d_format: Write output in 1D format. - no_one_d_format: Do not write output in 1D format. - summarize: Write out only the total nonzero voxel count and volume for\ - each dataset. - nosum: Suppress printout of the totals. - quiet: Suppress all non-essential output. - outvol_if_no_clust: Output an empty volume if no clusters are found. - orient: Coordinate order in the output report table (default: RAI). - abs_table_data: Use absolute values for mean and SEM in report table. - binary: Turn output map of cluster ROIs into a binary mask. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dClusterizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CLUSTERIZE_METADATA) - cargs = [] - cargs.append("3dClusterize") - cargs.extend([ - "-inset", - execution.input_file(inset) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mask_from_hdr: - cargs.append("-mask_from_hdr") - if out_mask is not None: - cargs.extend([ - "-out_mask", - out_mask - ]) - cargs.extend([ - "-ithr", - ithr - ]) - if idat is not None: - cargs.extend([ - "-idat", - idat - ]) - if onesided is not None: - cargs.extend([ - "-1sided", - onesided - ]) - if twosided is not None: - cargs.extend([ - "-2sided", - twosided - ]) - if bisided is not None: - cargs.extend([ - "-bisided", - bisided - ]) - if within_range is not None: - cargs.extend([ - "-within_range", - within_range - ]) - cargs.extend([ - "-NN", - str(nn) - ]) - if clust_nvox is not None: - cargs.extend([ - "-clust_nvox", - str(clust_nvox) - ]) - if clust_vol is not None: - cargs.extend([ - "-clust_vol", - str(clust_vol) - ]) - if pref_map is not None: - cargs.extend([ - "-pref_map", - pref_map - ]) - if pref_dat is not None: - cargs.extend([ - "-pref_dat", - pref_dat - ]) - if one_d_format: - cargs.append("-1Dformat") - if no_one_d_format: - cargs.append("-no_1Dformat") - if summarize: - cargs.append("-summarize") - if nosum: - cargs.append("-nosum") - if quiet: - cargs.append("-quiet") - if outvol_if_no_clust: - cargs.append("-outvol_if_no_clust") - if orient is not None: - cargs.extend([ - "-orient", - orient - ]) - if abs_table_data: - cargs.append("-abs_table_data") - if binary: - cargs.append("-binary") - ret = V3dClusterizeOutputs( - root=execution.output_file("."), - out_map_file=execution.output_file(pref_map + "+orig.HEAD") if (pref_map is not None) else None, - out_data_file=execution.output_file(pref_dat + "+orig.HEAD") if (pref_dat is not None) else None, - out_mask_file=execution.output_file(out_mask + "+orig.HEAD") if (out_mask is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dClusterizeOutputs", - "V_3D_CLUSTERIZE_METADATA", - "v_3d_clusterize", -] diff --git a/python/src/niwrap/afni/v_3d_cm.py b/python/src/niwrap/afni/v_3d_cm.py deleted file mode 100644 index 797757af7..000000000 --- a/python/src/niwrap/afni/v_3d_cm.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CM_METADATA = Metadata( - id="77803dd85b550ca349853a4b4282fd1640db43b6.boutiques", - name="3dCM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dCmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_cm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - center_of_mass: OutputPathType - """Center of mass of the dataset.""" - - -def v_3d_cm( - dset: InputPathType, - runner: Runner | None = None, -) -> V3dCmOutputs: - """ - Tool for computing the center of mass of a dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Input dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dCmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CM_METADATA) - cargs = [] - cargs.append("3dCM") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(dset)) - ret = V3dCmOutputs( - root=execution.output_file("."), - center_of_mass=execution.output_file(""), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dCmOutputs", - "V_3D_CM_METADATA", - "v_3d_cm", -] diff --git a/python/src/niwrap/afni/v_3d_compare_affine.py b/python/src/niwrap/afni/v_3d_compare_affine.py deleted file mode 100644 index 54890ad91..000000000 --- a/python/src/niwrap/afni/v_3d_compare_affine.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_COMPARE_AFFINE_METADATA = Metadata( - id="05a5d8e8f58b82dd3d94b8878f12307d386f682c.boutiques", - name="3dCompareAffine", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dCompareAffineOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_compare_affine(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file containing comparison results of affine transformations""" - - -def v_3d_compare_affine( - mask: str | None = None, - dset: InputPathType | None = None, - affine: list[str] | None = None, - runner: Runner | None = None, -) -> V3dCompareAffineOutputs: - """ - Compares two (or more) affine spatial transformations on a dataset and outputs - measurements of their differences in spatial displacements. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - mask: Dataset containing non-zero voxels used as the region over which\ - to compare the affine transformations. - dset: Dataset to compute an automask from it and use that mask as the\ - spatial region for comparison. - affine: Input an affine transformation (file or 'MATRIX'). Multiple\ - '-affine' options can be used to input multiple files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dCompareAffineOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_COMPARE_AFFINE_METADATA) - cargs = [] - cargs.append("3dCompareAffine") - if mask is not None: - cargs.extend([ - "-mask", - mask - ]) - if dset is not None: - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if affine is not None: - cargs.extend([ - "-affine", - *affine - ]) - ret = V3dCompareAffineOutputs( - root=execution.output_file("."), - outfile=execution.output_file("[OUTPUT_PREFIX]_comparison.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dCompareAffineOutputs", - "V_3D_COMPARE_AFFINE_METADATA", - "v_3d_compare_affine", -] diff --git a/python/src/niwrap/afni/v_3d_conformist.py b/python/src/niwrap/afni/v_3d_conformist.py deleted file mode 100644 index 9fa27007f..000000000 --- a/python/src/niwrap/afni/v_3d_conformist.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CONFORMIST_METADATA = Metadata( - id="f609f1b815cd20fa63c94e47456124184827cae8.boutiques", - name="3dConformist", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dConformistOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_conformist(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Zero padded output dataset files""" - - -def v_3d_conformist( - input_files: list[InputPathType], - runner: Runner | None = None, -) -> V3dConformistOutputs: - """ - Program to conform a collection of datasets to the same size by zero padding. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets to be zero padded to the same size. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dConformistOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CONFORMIST_METADATA) - cargs = [] - cargs.append("3dConformist") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V3dConformistOutputs( - root=execution.output_file("."), - output_files=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dConformistOutputs", - "V_3D_CONFORMIST_METADATA", - "v_3d_conformist", -] diff --git a/python/src/niwrap/afni/v_3d_convolve.py b/python/src/niwrap/afni/v_3d_convolve.py deleted file mode 100644 index b2ef81480..000000000 --- a/python/src/niwrap/afni/v_3d_convolve.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CONVOLVE_METADATA = Metadata( - id="7ff5260374d99f320496bbeba5fe202f34334415.boutiques", - name="3dConvolve", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dConvolveOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_convolve(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Main output file of 3dConvolve""" - - -def v_3d_convolve( - infile: InputPathType, - outfile: str, - options: str | None = None, - runner: Runner | None = None, -) -> V3dConvolveOutputs: - """ - 3dConvolve is no longer supported in AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file for 3dConvolve. - outfile: Output file for 3dConvolve. - options: Additional options for 3dConvolve. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dConvolveOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CONVOLVE_METADATA) - cargs = [] - cargs.append("3dConvolve") - cargs.append(execution.input_file(infile)) - cargs.append(outfile) - if options is not None: - cargs.extend([ - "-options", - options - ]) - ret = V3dConvolveOutputs( - root=execution.output_file("."), - outfile=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dConvolveOutputs", - "V_3D_CONVOLVE_METADATA", - "v_3d_convolve", -] diff --git a/python/src/niwrap/afni/v_3d_cruiseto_afni.py b/python/src/niwrap/afni/v_3d_cruiseto_afni.py deleted file mode 100644 index 3193a8b45..000000000 --- a/python/src/niwrap/afni/v_3d_cruiseto_afni.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_CRUISETO_AFNI_METADATA = Metadata( - id="4e08f5a3a9cbf98ac93af642e1c17b50a9c78a24.boutiques", - name="3dCRUISEtoAFNI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dCruisetoAfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_cruiseto_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_cruiseto_afni( - input_: InputPathType, - novolreg: bool = False, - noxform: bool = False, - setenv: str | None = None, - trace_: bool = False, - trace_2: bool = False, - nomall: bool = False, - yesmall: bool = False, - help_: bool = False, - h: bool = False, - runner: Runner | None = None, -) -> V3dCruisetoAfniOutputs: - """ - Converts a CRUISE dataset defined by a header in OpenDX format. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input CRUISE header file in OpenDX format. - novolreg: Ignore any Rotate, Volreg, Tagalign, or WarpDrive\ - transformations present in the Surface Volume. - noxform: Same as -novolreg. - setenv: Set environment variable ENVname to be ENVvalue. Quotes are\ - necessary. Example: suma -setenv "'SUMA_BackgroundColor = 1 0 1'". - trace_: Turns on In/Out debug and Memory tracing. It's recommended to\ - redirect stdout to a file when using this option. - trace_2: Turns on extreme tracing. - nomall: Turn off memory tracing. - yesmall: Turn on memory tracing (default). - help_: The entire help output. - h: Displays mini help; in many cases, it's the same as -help. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dCruisetoAfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_CRUISETO_AFNI_METADATA) - cargs = [] - cargs.append("3dCRUISEtoAFNI") - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if novolreg: - cargs.append("-novolreg") - if noxform: - cargs.append("-noxform") - if setenv is not None: - cargs.extend([ - "-setenv", - setenv - ]) - if trace_: - cargs.append("-trace") - if trace_2: - cargs.append("-TRACE") - if nomall: - cargs.append("-nomall") - if yesmall: - cargs.append("-yesmall") - if help_: - cargs.append("-help") - if h: - cargs.append("-h") - ret = V3dCruisetoAfniOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dCruisetoAfniOutputs", - "V_3D_CRUISETO_AFNI_METADATA", - "v_3d_cruiseto_afni", -] diff --git a/python/src/niwrap/afni/v_3d_deconvolve.py b/python/src/niwrap/afni/v_3d_deconvolve.py deleted file mode 100644 index c903dc53d..000000000 --- a/python/src/niwrap/afni/v_3d_deconvolve.py +++ /dev/null @@ -1,170 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DECONVOLVE_METADATA = Metadata( - id="3c5bd8bab8c9c3f4b4586c2e6fc553ef1b03f1e4.boutiques", - name="3dDeconvolve", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDeconvolveOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_deconvolve(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - bucket_output: OutputPathType | None - """Main output bucket dataset in AFNI format.""" - cbucket_output: OutputPathType | None - """Regression coefficients stored in a dataset.""" - iresp_output: OutputPathType | None - """Estimated Impulse Response dataset.""" - fitts_output: OutputPathType | None - """Fitted Time Series dataset in AFNI format.""" - x1d_file: OutputPathType | None - """X-matrix output file in .1D format.""" - - -def v_3d_deconvolve( - input_dataset: InputPathType, - mask_dataset: InputPathType | None = None, - num_stimts: int | None = None, - stim_file: str | None = None, - stim_label: str | None = None, - stim_base: bool = False, - stim_times: str | None = None, - iresp: str | None = None, - fitts: str | None = None, - fout: bool = False, - tout: bool = False, - bucket: str | None = None, - cbucket: str | None = None, - x1_d: str | None = None, - jobs: int | None = None, - runner: Runner | None = None, -) -> V3dDeconvolveOutputs: - """ - Program to calculate the deconvolution of a measurement 3D+time dataset with a - specified input stimulus time series. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Filename of 3D+time input dataset. - mask_dataset: Filename of 3D mask dataset. - num_stimts: Number of input stimulus time series. - stim_file: Filename of kth time series input stimulus. - stim_label: Label for kth input stimulus. - stim_base: Kth input stimulus is part of the baseline model. - stim_times: Deconvolution response model for kth stimulus. - iresp: Prefix for 3D+time output dataset which will contain the kth\ - estimated impulse response. - fitts: Prefix for 3D+time output dataset which will contain the (full\ - model) time series fit to the input data. - fout: Flag to output the F-statistics for each stimulus. - tout: Flag to output the t-statistics. - bucket: Create one AFNI 'bucket' dataset containing various parameters\ - of interest. - cbucket: Save the regression coefficients (no statistics) into a\ - dataset. - x1_d: Save X matrix to a .xmat.1D (ASCII) file. - jobs: Run the program with multiple jobs (sub-processes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDeconvolveOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DECONVOLVE_METADATA) - cargs = [] - cargs.append("3dDeconvolve") - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if num_stimts is not None: - cargs.extend([ - "-num_stimts", - str(num_stimts) - ]) - if stim_file is not None: - cargs.extend([ - "-stim_file", - stim_file - ]) - if stim_label is not None: - cargs.extend([ - "-stim_label", - stim_label - ]) - if stim_base: - cargs.append("-stim_base") - if stim_times is not None: - cargs.extend([ - "-stim_times", - stim_times - ]) - if iresp is not None: - cargs.extend([ - "-iresp", - iresp - ]) - if fitts is not None: - cargs.extend([ - "-fitts", - fitts - ]) - if fout: - cargs.append("-fout") - if tout: - cargs.append("-tout") - if bucket is not None: - cargs.extend([ - "-bucket", - bucket - ]) - if cbucket is not None: - cargs.extend([ - "-cbucket", - cbucket - ]) - if x1_d is not None: - cargs.extend([ - "-x1D", - x1_d - ]) - if jobs is not None: - cargs.extend([ - "-jobs", - str(jobs) - ]) - ret = V3dDeconvolveOutputs( - root=execution.output_file("."), - bucket_output=execution.output_file(bucket + ".HEAD") if (bucket is not None) else None, - cbucket_output=execution.output_file(cbucket + ".HEAD") if (cbucket is not None) else None, - iresp_output=execution.output_file(iresp + ".HEAD") if (iresp is not None) else None, - fitts_output=execution.output_file(fitts + ".HEAD") if (fitts is not None) else None, - x1d_file=execution.output_file(x1_d + ".1D") if (x1_d is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDeconvolveOutputs", - "V_3D_DECONVOLVE_METADATA", - "v_3d_deconvolve", -] diff --git a/python/src/niwrap/afni/v_3d_degree_centrality.py b/python/src/niwrap/afni/v_3d_degree_centrality.py deleted file mode 100644 index 741c3e219..000000000 --- a/python/src/niwrap/afni/v_3d_degree_centrality.py +++ /dev/null @@ -1,112 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DEGREE_CENTRALITY_METADATA = Metadata( - id="1a5722d6aac4349ec026c10e117c0cc27e3fcea9.boutiques", - name="3dDegreeCentrality", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDegreeCentralityOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_degree_centrality(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - oned_file_outfile: OutputPathType | None - """The text output of the similarity matrix computed after thresholding with - one-dimensional and ijk voxel indices, correlations, image extents, and - affine matrix.""" - - -def v_3d_degree_centrality( - in_file: InputPathType, - autoclip: bool = False, - automask: bool = False, - mask: InputPathType | None = None, - oned_file: str | None = None, - polort: int | None = None, - sparsity: float | None = None, - thresh: float | None = None, - runner: Runner | None = None, -) -> V3dDegreeCentralityOutputs: - """ - Computes voxelwise weighted and binary degree centrality and stores the result - in a new 3D bucket dataset as floats to preserve their values. Degree centrality - reflects the strength and extent of the correlation of a voxel with every other - voxel in the brain. . - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3ddegreecentrality. - autoclip: Clip off low-intensity regions in the dataset. - automask: Mask the dataset to target brain-only voxels. - mask: Mask file to mask input data. - oned_file: Output filepath to text dump of correlation matrix. - polort: No description provided. - sparsity: Only take the top percent of connections. - thresh: Threshold to exclude connections where corr <= thresh. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDegreeCentralityOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DEGREE_CENTRALITY_METADATA) - cargs = [] - cargs.append("3dDegreeCentrality") - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - cargs.append(execution.input_file(in_file)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if oned_file is not None: - cargs.extend([ - "-out1D", - oned_file - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if sparsity is not None: - cargs.extend([ - "-sparsity", - str(sparsity) - ]) - if thresh is not None: - cargs.extend([ - "-thresh", - str(thresh) - ]) - ret = V3dDegreeCentralityOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name), - oned_file_outfile=execution.output_file(oned_file) if (oned_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDegreeCentralityOutputs", - "V_3D_DEGREE_CENTRALITY_METADATA", - "v_3d_degree_centrality", -] diff --git a/python/src/niwrap/afni/v_3d_depth_map.py b/python/src/niwrap/afni/v_3d_depth_map.py deleted file mode 100644 index 5d16c061b..000000000 --- a/python/src/niwrap/afni/v_3d_depth_map.py +++ /dev/null @@ -1,132 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DEPTH_MAP_METADATA = Metadata( - id="4a6704d8156d9e0a414515196af7b7f69ca298eb.boutiques", - name="3dDepthMap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDepthMapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_depth_map(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Main output file""" - - -def v_3d_depth_map( - input_dataset: InputPathType, - output_prefix: str, - mask: InputPathType | None = None, - dist_squared: bool = False, - ignore_voxdims: bool = False, - rimify: float | None = None, - zeros_are_zero: bool = False, - zeros_are_neg: bool = False, - nz_are_neg: bool = False, - bounds_are_not_zero: bool = False, - only2_d: str | None = None, - binary_only: bool = False, - verbosity: float | None = None, - runner: Runner | None = None, -) -> V3dDepthMapOutputs: - """ - Calculates the Euclidean Distance Transform (EDT) for 3D volumes, allowing - computation of ROI depth maps and applying various adjustments like masking and - rimification. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset. - output_prefix: Output prefix name. - mask: Mask dataset, applied after the EDT has been calculated. - dist_squared: Output EDT values as distance squared. - ignore_voxdims: Ignore voxel dimensions, producing outputs as if each\ - voxel dimension was unity. - rimify: Output a map of each ROI's boundary layer up to thickness RIM. - zeros_are_zero: EDT values only reported within nonzero locations of\ - the input dataset. - zeros_are_neg: EDT values in the zero/background regions will be\ - negative. - nz_are_neg: EDT values in the nonzero ROI regions will be negative. - bounds_are_not_zero: Treat FOV boundaries for nonzero ROIs as open\ - (i.e., continue infinitely). - only2_d: Run EDT in 2D along the specified plane (axi|cor|sag). - binary_only: Treat the input as a binary mask for a faster calculation. - verbosity: Manage verbosity when running code (default: 1). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDepthMapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DEPTH_MAP_METADATA) - cargs = [] - cargs.append("3dDepthMap") - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - cargs.extend([ - "-prefix", - output_prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if dist_squared: - cargs.append("-dist_sq") - if ignore_voxdims: - cargs.append("-ignore_voxdims") - if rimify is not None: - cargs.extend([ - "-rimify", - str(rimify) - ]) - if zeros_are_zero: - cargs.append("-zeros_are_zero") - if zeros_are_neg: - cargs.append("-zeros_are_neg") - if nz_are_neg: - cargs.append("-nz_are_neg") - if bounds_are_not_zero: - cargs.append("-bounds_are_not_zero") - if only2_d is not None: - cargs.extend([ - "-only2D", - only2_d - ]) - if binary_only: - cargs.append("-binary_only") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = V3dDepthMapOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDepthMapOutputs", - "V_3D_DEPTH_MAP_METADATA", - "v_3d_depth_map", -] diff --git a/python/src/niwrap/afni/v_3d_despike.py b/python/src/niwrap/afni/v_3d_despike.py deleted file mode 100644 index 8729bbd8c..000000000 --- a/python/src/niwrap/afni/v_3d_despike.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DESPIKE_METADATA = Metadata( - id="baa2169d318e0fa4cf31680f73c753efdfa10d5e.boutiques", - name="3dDespike", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDespikeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_despike(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output file.""" - - -def v_3d_despike( - in_file: InputPathType, - runner: Runner | None = None, -) -> V3dDespikeOutputs: - """ - Removes 'spikes' from the 3D+time input dataset and writes a new dataset with - the spike values replaced by something more pleasing to the eye. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3ddespike. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDespikeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DESPIKE_METADATA) - cargs = [] - cargs.append("3dDespike") - cargs.append(execution.input_file(in_file)) - ret = V3dDespikeOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDespikeOutputs", - "V_3D_DESPIKE_METADATA", - "v_3d_despike", -] diff --git a/python/src/niwrap/afni/v_3d_detrend.py b/python/src/niwrap/afni/v_3d_detrend.py deleted file mode 100644 index 145bed32c..000000000 --- a/python/src/niwrap/afni/v_3d_detrend.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DETREND_METADATA = Metadata( - id="60647b5333bef9ee86bcc873fe7fe2fe2f22589e.boutiques", - name="3dDetrend", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDetrendOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_detrend(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_detrend( - in_file: InputPathType, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - runner: Runner | None = None, -) -> V3dDetrendOutputs: - """ - This program removes components from voxel time series using linear least - squares. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3ddetrend. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDetrendOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DETREND_METADATA) - cargs = [] - cargs.append("3dDetrend") - cargs.append(execution.input_file(in_file)) - if outputtype is not None: - cargs.append(outputtype) - ret = V3dDetrendOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_detrend"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDetrendOutputs", - "V_3D_DETREND_METADATA", - "v_3d_detrend", -] diff --git a/python/src/niwrap/afni/v_3d_dft.py b/python/src/niwrap/afni/v_3d_dft.py deleted file mode 100644 index df1f06a65..000000000 --- a/python/src/niwrap/afni/v_3d_dft.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DFT_METADATA = Metadata( - id="0f3070685dbac59868921707a751cb9ad68c75ea.boutiques", - name="3dDFT", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDftOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dft(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output dataset file""" - outheader: OutputPathType - """Output dataset header file""" - - -def v_3d_dft( - infile: InputPathType, - prefix: str, - abs_output: bool = False, - nfft: float | None = None, - detrend: bool = False, - taper: float | None = None, - inverse: bool = False, - runner: Runner | None = None, -) -> V3dDftOutputs: - """ - Performs Discrete Fourier Transform (DFT) along the time axis of a complex- or - float-valued dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input dataset (complex- or float-valued). - prefix: Prefix for the output file. - abs_output: Output float dataset = abs(DFT). - nfft: DFT length (must be >= number of time points). - detrend: Least-squares remove linear drift before DFT. - taper: Fraction (0 <= f <= 1) of data to taper at ends (Hamming taper). - inverse: Perform the inverse DFT. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDftOutputs`). - """ - if taper is not None and not (0.0 <= taper <= 1.0): - raise ValueError(f"'taper' must be between 0.0 <= x <= 1.0 but was {taper}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DFT_METADATA) - cargs = [] - cargs.append("3dDFT") - cargs.append(execution.input_file(infile)) - cargs.extend([ - "-prefix", - prefix - ]) - if abs_output: - cargs.append("-abs") - if nfft is not None: - cargs.extend([ - "-nfft", - str(nfft) - ]) - if detrend: - cargs.append("-detrend") - if taper is not None: - cargs.extend([ - "-taper", - str(taper) - ]) - if inverse: - cargs.append("-inverse") - ret = V3dDftOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + "+orig.BRIK"), - outheader=execution.output_file(prefix + "+orig.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDftOutputs", - "V_3D_DFT_METADATA", - "v_3d_dft", -] diff --git a/python/src/niwrap/afni/v_3d_diff.py b/python/src/niwrap/afni/v_3d_diff.py deleted file mode 100644 index 1b1bcbcab..000000000 --- a/python/src/niwrap/afni/v_3d_diff.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DIFF_METADATA = Metadata( - id="5b96180172979184a8e38d0680d5f070bb647cfa.boutiques", - name="3dDiff", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDiffOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_diff(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_log: OutputPathType - """Log file containing the element-wise differences.""" - - -def v_3d_diff( - dataset_a: InputPathType, - dataset_b: InputPathType, - tolerance: float | None = None, - mask: InputPathType | None = None, - quiet_mode: bool = False, - tabular_mode: bool = False, - brutalist_mode: bool = False, - long_report_mode: bool = False, - runner: Runner | None = None, -) -> V3dDiffOutputs: - """ - A program to examine element-wise differences between two images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset_a: First input dataset for comparison. - dataset_b: Second input dataset for comparison. - tolerance: Floating-point tolerance/epsilon for the comparison. - mask: Mask to use when comparing the datasets. - quiet_mode: Quiet mode: 0 for no differences, 1 for differences, -1 for\ - error. - tabular_mode: Display a table of differences, mainly for 4D data. - brutalist_mode: Display one-liner with summary of differences. - long_report_mode: Print a detailed report with more information. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDiffOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DIFF_METADATA) - cargs = [] - cargs.append("3dDiff") - cargs.extend([ - "-a", - execution.input_file(dataset_a) - ]) - cargs.extend([ - "-b", - execution.input_file(dataset_b) - ]) - if tolerance is not None: - cargs.extend([ - "-tol", - str(tolerance) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if quiet_mode: - cargs.append("-q") - if tabular_mode: - cargs.append("-tabular") - if brutalist_mode: - cargs.append("-brutalist") - if long_report_mode: - cargs.append("-long_report") - ret = V3dDiffOutputs( - root=execution.output_file("."), - output_log=execution.output_file(pathlib.Path(dataset_a).name + "_vs_" + pathlib.Path(dataset_b).name + ".log"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDiffOutputs", - "V_3D_DIFF_METADATA", - "v_3d_diff", -] diff --git a/python/src/niwrap/afni/v_3d_dteig.py b/python/src/niwrap/afni/v_3d_dteig.py deleted file mode 100644 index 6d71fefd8..000000000 --- a/python/src/niwrap/afni/v_3d_dteig.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DTEIG_METADATA = Metadata( - id="5c446bf21775547faf60f0fa1576969e859e8381.boutiques", - name="3dDTeig", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDteigOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dteig(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Output dataset with computed eigenvalues, eigenvectors, FA, and MD""" - output_lambda: OutputPathType | None - """Output dataset for eigenvalues""" - output_eigvec: OutputPathType | None - """Output dataset for eigenvectors""" - output_fa: OutputPathType | None - """Output dataset for fractional anisotropy""" - output_md: OutputPathType | None - """Output dataset for mean diffusivity""" - - -def v_3d_dteig( - input_dataset: str, - prefix: str | None = None, - datum: typing.Literal["byte", "short", "float"] | None = None, - sep_dsets: bool = False, - uddata: bool = False, - runner: Runner | None = None, -) -> V3dDteigOutputs: - """ - Computes eigenvalues and eigenvectors for an input dataset of tensors. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset of Dxx, Dxy, Dyy, Dxz, Dyz, Dzz sub-bricks. - prefix: Use the given prefix for the output dataset. - datum: Coerce the output data to be stored as the given type (byte,\ - short, or float). - sep_dsets: Save eigenvalues, vectors, FA, and MD in separate datasets. - uddata: Tensor data is stored as upper diagonal instead of lower\ - diagonal. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDteigOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DTEIG_METADATA) - cargs = [] - cargs.append("3dDTeig") - cargs.append(input_dataset) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if sep_dsets: - cargs.append("-sep_dsets") - if uddata: - cargs.append("-uddata") - ret = V3dDteigOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - output_lambda=execution.output_file(prefix + "_lambda.nii.gz") if (prefix is not None) else None, - output_eigvec=execution.output_file(prefix + "_eigvec.nii.gz") if (prefix is not None) else None, - output_fa=execution.output_file(prefix + "_FA.nii.gz") if (prefix is not None) else None, - output_md=execution.output_file(prefix + "_MD.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDteigOutputs", - "V_3D_DTEIG_METADATA", - "v_3d_dteig", -] diff --git a/python/src/niwrap/afni/v_3d_dtto_dwi.py b/python/src/niwrap/afni/v_3d_dtto_dwi.py deleted file mode 100644 index e9b50d047..000000000 --- a/python/src/niwrap/afni/v_3d_dtto_dwi.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DTTO_DWI_METADATA = Metadata( - id="7152649faabf944b7f991d88bc2a8df46f5b5bd7.boutiques", - name="3dDTtoDWI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDttoDwiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dtto_dwi(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dwi: OutputPathType - """Computed DWI images including sub-brick for each gradient vector.""" - - -def v_3d_dtto_dwi( - gradient_file: InputPathType, - i0_dataset: InputPathType, - dt_dataset: InputPathType, - runner: Runner | None = None, -) -> V3dDttoDwiOutputs: - """ - Tool to compute multiple gradient images from tensors and gradient vector - coordinates applied to the I0-dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - gradient_file: 1D file containing the gradient vectors (ASCII floats)\ - for non-zero gradients. - i0_dataset: Volume without any gradient applied. - dt_dataset: 6-sub-brick dataset containing the diffusion tensor data\ - (Dxx, Dxy, Dyy, Dxz, Dyz, Dzz). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDttoDwiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DTTO_DWI_METADATA) - cargs = [] - cargs.append("3dDTtoDWI") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(gradient_file)) - cargs.append(execution.input_file(i0_dataset)) - cargs.append(execution.input_file(dt_dataset)) - ret = V3dDttoDwiOutputs( - root=execution.output_file("."), - output_dwi=execution.output_file("[PREFIX_NAME]*.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDttoDwiOutputs", - "V_3D_DTTO_DWI_METADATA", - "v_3d_dtto_dwi", -] diff --git a/python/src/niwrap/afni/v_3d_dtto_noisy_dwi.py b/python/src/niwrap/afni/v_3d_dtto_noisy_dwi.py deleted file mode 100644 index e18b80f5a..000000000 --- a/python/src/niwrap/afni/v_3d_dtto_noisy_dwi.py +++ /dev/null @@ -1,113 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DTTO_NOISY_DWI_METADATA = Metadata( - id="0ef5fe03a8b952b27e737adb59a395ac94790601.boutiques", - name="3dDTtoNoisyDWI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDttoNoisyDwiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dtto_noisy_dwi(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dwi: OutputPathType - """Synthetic set of DWI measures with noise. Contains N+1 bricks mimicking - B0+DWI data.""" - - -def v_3d_dtto_noisy_dwi( - dt_file: InputPathType, - grad_file: InputPathType, - noise_dwi: float, - prefix: str, - noise_b0: float | None = None, - mask: InputPathType | None = None, - bval: float | None = None, - s0: float | None = None, - runner: Runner | None = None, -) -> V3dDttoNoisyDwiOutputs: - """ - Generate a synthetic set of DWI measures with a given SNR from an AFNI-style DT - file and a set of gradients. This can be useful for simulations and testing. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dt_file: Diffusion tensor file with six bricks of DT components ordered\ - in the AFNI manner: Dxx,Dxy,Dyy,Dxz,Dyz,Dzz. - grad_file: Text file of gradients arranged in three columns. There\ - should be no row of all zeros representing the b=0 line. - noise_dwi: Fractional value of noise in DWIs. FF = sigma/S0 = 1/SNR0.\ - For example, FF=0.05 corresponds to SNR0=20. - prefix: Output file name prefix. Will have N+1 bricks when GRADFILE has\ - N rows of gradients. - noise_b0: Optional fraction of Rician noise in the b=0 reference image.\ - If not provided, FF2=FF. - mask: Optional mask within which to calculate uncertainty. Data should\ - be masked already otherwise. - bval: Optional DW factor to use if DT values are scaled to something\ - physical. Default is BB=1. - s0: Optional reference b=0 signal strength. Default value is SS=1000. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDttoNoisyDwiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DTTO_NOISY_DWI_METADATA) - cargs = [] - cargs.append("3dDTtoNoisyDWI") - cargs.append(execution.input_file(dt_file)) - cargs.append(execution.input_file(grad_file)) - cargs.extend([ - "-noise_DWI", - str(noise_dwi) - ]) - if noise_b0 is not None: - cargs.extend([ - "-noise_B0", - str(noise_b0) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if bval is not None: - cargs.extend([ - "-bval", - str(bval) - ]) - if s0 is not None: - cargs.extend([ - "-S0", - str(s0) - ]) - ret = V3dDttoNoisyDwiOutputs( - root=execution.output_file("."), - output_dwi=execution.output_file(prefix + "+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDttoNoisyDwiOutputs", - "V_3D_DTTO_NOISY_DWI_METADATA", - "v_3d_dtto_noisy_dwi", -] diff --git a/python/src/niwrap/afni/v_3d_dwito_dt.py b/python/src/niwrap/afni/v_3d_dwito_dt.py deleted file mode 100644 index c14740974..000000000 --- a/python/src/niwrap/afni/v_3d_dwito_dt.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DWITO_DT_METADATA = Metadata( - id="8960cd4bae08bae6a1b6d48945e70aab4aa70b33.boutiques", - name="3dDWItoDT", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDwitoDtOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dwito_dt(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output dataset""" - - -def v_3d_dwito_dt( - gradient_file: InputPathType, - dataset: InputPathType, - runner: Runner | None = None, -) -> V3dDwitoDtOutputs: - """ - Computes 6 principal direction tensors from multiple gradient vectors and - corresponding DTI image volumes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - gradient_file: A 1D file of the gradient vectors with lines of ASCII\ - floats (Gxi, Gyi, Gzi) or a 1D file of b-matrix elements. - dataset: A 3D bucket dataset with Np+1 sub-briks where the first\ - sub-brik is the volume acquired with no diffusion weighting. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDwitoDtOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DWITO_DT_METADATA) - cargs = [] - cargs.append("3dDWItoDT") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(gradient_file)) - cargs.append(execution.input_file(dataset)) - ret = V3dDwitoDtOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(".*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDwitoDtOutputs", - "V_3D_DWITO_DT_METADATA", - "v_3d_dwito_dt", -] diff --git a/python/src/niwrap/afni/v_3d_dwuncert.py b/python/src/niwrap/afni/v_3d_dwuncert.py deleted file mode 100644 index 3e516f8cb..000000000 --- a/python/src/niwrap/afni/v_3d_dwuncert.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_DWUNCERT_METADATA = Metadata( - id="e5435aa32b153e592fc54fcb544b034d7d4ed2ac.boutiques", - name="3dDWUncert", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dDwuncertOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_dwuncert(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """AFNI-format file with 6 subbricks, containing uncertainty information.""" - - -def v_3d_dwuncert( - input_file: InputPathType, - input_prefix: str, - output_prefix: str, - grad_file: InputPathType | None = None, - bmatrix_file: InputPathType | None = None, - num_iters: float | None = None, - mask_file: InputPathType | None = None, - calc_thr_fa: float | None = None, - csf_fa: float | None = None, - runner: Runner | None = None, -) -> V3dDwuncertOutputs: - """ - Use jackknifing to estimate uncertainty of DTI parameters, important for - probabilistic tractography. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input file with b0 and DWI subbricks. - input_prefix: Basename of DTI volumes. - output_prefix: Output file name prefix. - grad_file: File with 3 columns for x-, y-, and z-comps of DW-gradients. - bmatrix_file: File with gradient info in b-matrix format. - num_iters: Number of jackknife resample iterations. - mask_file: Mask file within which to calculate uncertainty. - calc_thr_fa: Threshold for the minimum FA value above which to\ - calculate uncertainty. - csf_fa: Number marking FA value of 'bad' voxels. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dDwuncertOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_DWUNCERT_METADATA) - cargs = [] - cargs.append("3dDWUncert") - cargs.append("-inset") - cargs.append(execution.input_file(input_file)) - cargs.append("-input") - cargs.append(input_prefix) - cargs.append("-prefix") - cargs.append(output_prefix) - cargs.append("-grads") - if grad_file is not None: - cargs.append(execution.input_file(grad_file)) - cargs.append("-bmatrix_FULL") - if bmatrix_file is not None: - cargs.append(execution.input_file(bmatrix_file)) - cargs.append("-iters") - if num_iters is not None: - cargs.extend([ - "-iters", - str(num_iters) - ]) - cargs.append("-mask") - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - cargs.append("-calc_thr_FA") - if calc_thr_fa is not None: - cargs.extend([ - "-calc_thr_FA", - str(calc_thr_fa) - ]) - cargs.append("-csf_fa") - if csf_fa is not None: - cargs.extend([ - "-csf_fa", - str(csf_fa) - ]) - ret = V3dDwuncertOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + "+*.HEAD/" + output_prefix + "+*.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dDwuncertOutputs", - "V_3D_DWUNCERT_METADATA", - "v_3d_dwuncert", -] diff --git a/python/src/niwrap/afni/v_3d_ecm.py b/python/src/niwrap/afni/v_3d_ecm.py deleted file mode 100644 index 446d4f895..000000000 --- a/python/src/niwrap/afni/v_3d_ecm.py +++ /dev/null @@ -1,158 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ECM_METADATA = Metadata( - id="91d8d58fa4639faaf4600f4e74c107adf466aacc.boutiques", - name="3dECM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dEcmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_ecm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_ecm( - in_file: InputPathType, - autoclip: bool = False, - automask: bool = False, - eps: float | None = None, - fecm: bool = False, - full: bool = False, - mask: InputPathType | None = None, - max_iter: int | None = None, - memory: float | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - polort: int | None = None, - scale: float | None = None, - shift: float | None = None, - sparsity: float | None = None, - thresh: float | None = None, - runner: Runner | None = None, -) -> V3dEcmOutputs: - """ - Performs degree centrality on a dataset using a given maskfile via the 3dECM - command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3decm. - autoclip: Clip off low-intensity regions in the dataset. - automask: Mask the dataset to target brain-only voxels. - eps: Sets the stopping criterion for the power iteration;\ - :math:`l2\\|v_\\text{old} - v_\\text{new}\\| < eps\\|v_\\text{old}\\|`;\ - default = 0.001. - fecm: Fast centrality method; substantial speed increase but cannot\ - accommodate thresholding; automatically selected if -thresh or\ - -sparsity are not set. - full: Full power method; enables thresholding; automatically selected\ - if -thresh or -sparsity are set. - mask: Mask file to mask input data. - max_iter: Sets the maximum number of iterations to use in the power\ - iteration; default = 1000. - memory: Limit memory consumption on system by setting the amount of gb\ - to limit the algorithm to; default = 2gb. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - polort: No description provided. - scale: Scale correlation coefficients in similarity matrix to after\ - shifting, x >= 0.0; default = 1.0 for -full, 0.5 for -fecm. - shift: Shift correlation coefficients in similarity matrix to enforce\ - non-negativity, s >= 0.0; default = 0.0 for -full, 1.0 for -fecm. - sparsity: Only take the top percent of connections. - thresh: Threshold to exclude connections where corr <= thresh. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dEcmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ECM_METADATA) - cargs = [] - cargs.append("3dECM") - cargs.append(execution.input_file(in_file)) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if eps is not None: - cargs.extend([ - "-eps", - str(eps) - ]) - if fecm: - cargs.append("-fecm") - if full: - cargs.append("-full") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if max_iter is not None: - cargs.extend([ - "-max_iter", - str(max_iter) - ]) - if memory is not None: - cargs.extend([ - "-memory", - str(memory) - ]) - cargs.append("[OUT_FILE]") - if outputtype is not None: - cargs.append(outputtype) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if scale is not None: - cargs.extend([ - "-scale", - str(scale) - ]) - if shift is not None: - cargs.extend([ - "-shift", - str(shift) - ]) - if sparsity is not None: - cargs.extend([ - "-sparsity", - str(sparsity) - ]) - if thresh is not None: - cargs.extend([ - "-thresh", - str(thresh) - ]) - ret = V3dEcmOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_afni"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dEcmOutputs", - "V_3D_ECM_METADATA", - "v_3d_ecm", -] diff --git a/python/src/niwrap/afni/v_3d_edu_01_scale.py b/python/src/niwrap/afni/v_3d_edu_01_scale.py deleted file mode 100644 index 6e547fbe9..000000000 --- a/python/src/niwrap/afni/v_3d_edu_01_scale.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EDU_01_SCALE_METADATA = Metadata( - id="421ae3b97be6019b8194c6bf2db5b0b7024dbd25.boutiques", - name="3dEdu_01_scale", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dEdu01ScaleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_edu_01_scale(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output scaled and/or masked copy of the [0]th volume of the input - dataset""" - - -def v_3d_edu_01_scale( - input_: InputPathType, - mask: InputPathType | None = None, - mult_factors: list[float] | None = None, - option_flag: bool = False, - runner: Runner | None = None, -) -> V3dEdu01ScaleOutputs: - """ - Educational program to create a new AFNI program. Scales and masks dataset - volumes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - mask: Mask dataset on same grid/data structure as the input dataset. - mult_factors: Numerical factors for multiplying each voxel; each voxel\ - is multiplied by both A and B. - option_flag: Option flag to do something. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dEdu01ScaleOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EDU_01_SCALE_METADATA) - cargs = [] - cargs.append("3dEdu_01_scale") - cargs.append(execution.input_file(input_)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mult_factors is not None: - cargs.extend([ - "-mult_facs", - *map(str, mult_factors) - ]) - if option_flag: - cargs.append("-some_opt") - ret = V3dEdu01ScaleOutputs( - root=execution.output_file("."), - outfile=execution.output_file("OUT_edu_[1-9]*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dEdu01ScaleOutputs", - "V_3D_EDU_01_SCALE_METADATA", - "v_3d_edu_01_scale", -] diff --git a/python/src/niwrap/afni/v_3d_eigs_to_dt.py b/python/src/niwrap/afni/v_3d_eigs_to_dt.py deleted file mode 100644 index cc5265b1d..000000000 --- a/python/src/niwrap/afni/v_3d_eigs_to_dt.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EIGS_TO_DT_METADATA = Metadata( - id="277228059bce43b644e4c5cf8ab984d713a0f026.boutiques", - name="3dEigsToDT", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dEigsToDtOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_eigs_to_dt(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - dt_brik_output: OutputPathType - """Output diffusion tensor (DT) file in AFNI format (BRIK)""" - dt_head_output: OutputPathType - """Output diffusion tensor (DT) file in AFNI format (HEAD)""" - - -def v_3d_eigs_to_dt( - eig_vals: str, - eig_vecs: str, - prefix: str, - mask: InputPathType | None = None, - flip_x: bool = False, - flip_y: bool = False, - flip_z: bool = False, - scale_eigs: float | None = None, - runner: Runner | None = None, -) -> V3dEigsToDtOutputs: - """ - Convert set of DTI eigenvectors and eigenvalues to a diffusion tensor, with - optional value-scaling and vector-flipping. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - eig_vals: Searchable descriptor for finding all three required\ - eigenvalue files. It should list all three eigenvalue files in\ - descending order of magnitude. - eig_vecs: Searchable descriptor for finding all three required\ - eigenvector files. It should list all three eigenvector files in order\ - matching the eigenvalue files. - prefix: Prefix for the output file name. It is recommended to include a\ - 'DT' label in it. - mask: Optional mask within which to calculate uncertainty. If not\ - provided, the data should be masked already. - flip_x: Change sign of the first element of eigenvectors. - flip_y: Change sign of the second element of eigenvectors. - flip_z: Change sign of the third element of eigenvectors. - scale_eigs: Rescale the eigenvalues by dividing by a number X > 0. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dEigsToDtOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EIGS_TO_DT_METADATA) - cargs = [] - cargs.append("3dEigsToDT") - cargs.append("-eig_vals") - cargs.append(eig_vals) - cargs.append("-eig_vecs") - cargs.append(eig_vecs) - cargs.append("-prefix") - cargs.append(prefix) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if flip_x: - cargs.append("-flip_x") - if flip_y: - cargs.append("-flip_y") - if flip_z: - cargs.append("-flip_z") - if scale_eigs is not None: - cargs.extend([ - "-scale_eigs", - str(scale_eigs) - ]) - ret = V3dEigsToDtOutputs( - root=execution.output_file("."), - dt_brik_output=execution.output_file(prefix + "_DT+orig.BRIK"), - dt_head_output=execution.output_file(prefix + "_DT+orig.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dEigsToDtOutputs", - "V_3D_EIGS_TO_DT_METADATA", - "v_3d_eigs_to_dt", -] diff --git a/python/src/niwrap/afni/v_3d_empty.py b/python/src/niwrap/afni/v_3d_empty.py deleted file mode 100644 index 53536a4a5..000000000 --- a/python/src/niwrap/afni/v_3d_empty.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EMPTY_METADATA = Metadata( - id="730ad3720777756112dc40869e7f93318748f6b6.boutiques", - name="3dEmpty", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dEmptyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_empty(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Output empty dataset header file""" - - -def v_3d_empty( - prefix: str | None = None, - geometry: str | None = None, - nxyz: list[float] | None = None, - nt_: float | None = None, - runner: Runner | None = None, -) -> V3dEmptyOutputs: - """ - Tool to create an 'empty' dataset .HEAD file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix name for output file (default = 'Empty'). - geometry: Set the 3D geometry of the grid using a string of the form\ - 'MATRIX(a11,a12,a13,a14,a21,a22,a23,a24,a31,a32,a33,a34):nx,ny,nz'. - nxyz: Set number of voxels to 'x', 'y', and 'z' along the 3 axes\ - [defaults=64]. - nt_: Number of time points [default=1]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dEmptyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EMPTY_METADATA) - cargs = [] - cargs.append("3dEmpty") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if geometry is not None: - cargs.extend([ - "-geometry", - geometry - ]) - if nxyz is not None: - cargs.extend([ - "-nxyz", - *map(str, nxyz) - ]) - if nt_ is not None: - cargs.extend([ - "-nt", - str(nt_) - ]) - ret = V3dEmptyOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + ".HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dEmptyOutputs", - "V_3D_EMPTY_METADATA", - "v_3d_empty", -] diff --git a/python/src/niwrap/afni/v_3d_entropy.py b/python/src/niwrap/afni/v_3d_entropy.py deleted file mode 100644 index cbf0825ae..000000000 --- a/python/src/niwrap/afni/v_3d_entropy.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ENTROPY_METADATA = Metadata( - id="17b92837a5e015c4028579e4399a89934e214cb1.boutiques", - name="3dEntropy", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dEntropyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_entropy(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_entropy( - input_dataset: InputPathType, - zskip: bool = False, - runner: Runner | None = None, -) -> V3dEntropyOutputs: - """ - Computes entropy for a 3D dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (stored as 16 bit shorts). - zskip: Skip 0 values in the entropy computation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dEntropyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ENTROPY_METADATA) - cargs = [] - cargs.append("3dEntropy") - if zskip: - cargs.append("-zskip") - cargs.append(execution.input_file(input_dataset)) - ret = V3dEntropyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dEntropyOutputs", - "V_3D_ENTROPY_METADATA", - "v_3d_entropy", -] diff --git a/python/src/niwrap/afni/v_3d_errts_cormat.py b/python/src/niwrap/afni/v_3d_errts_cormat.py deleted file mode 100644 index 94fb44afc..000000000 --- a/python/src/niwrap/afni/v_3d_errts_cormat.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ERRTS_CORMAT_METADATA = Metadata( - id="2f4cd813e00c21c8ed95885addacf3502e722a23.boutiques", - name="3dErrtsCormat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dErrtsCormatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_errts_cormat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """1D file of the Toeplitz entries.""" - - -def v_3d_errts_cormat( - dset: InputPathType, - concat: str | None = None, - input_: InputPathType | None = None, - mask: InputPathType | None = None, - maxlag: float | None = None, - polort: float | None = None, - runner: Runner | None = None, -) -> V3dErrtsCormatOutputs: - """ - Computes the correlation matrix corresponding to the residual (or error) time - series in 'dset'. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Dataset to read, usually the '-errts' output from 3dDeconvolve. - concat: As used in 3dDeconvolve. - input_: Alternate way of specifying the dataset to read. - mask: Mask dataset to apply. - maxlag: Set maximum lag. - polort: Set polort level. Default is 0. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dErrtsCormatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ERRTS_CORMAT_METADATA) - cargs = [] - cargs.append("3dErrtsCormat") - cargs.append(execution.input_file(dset)) - if concat is not None: - cargs.extend([ - "-concat", - concat - ]) - if input_ is not None: - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if maxlag is not None: - cargs.extend([ - "-maxlag", - str(maxlag) - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - ret = V3dErrtsCormatOutputs( - root=execution.output_file("."), - output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dErrtsCormatOutputs", - "V_3D_ERRTS_CORMAT_METADATA", - "v_3d_errts_cormat", -] diff --git a/python/src/niwrap/afni/v_3d_exchange.py b/python/src/niwrap/afni/v_3d_exchange.py deleted file mode 100644 index f1b40a3a1..000000000 --- a/python/src/niwrap/afni/v_3d_exchange.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EXCHANGE_METADATA = Metadata( - id="93070f9755d67a6df7e13c005e486486c48dd1b7.boutiques", - name="3dExchange", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dExchangeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_exchange(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType - """Output HEAD file""" - output_brik: OutputPathType - """Output BRIK file""" - - -def v_3d_exchange( - prefix: str, - infile: InputPathType, - mapfile: InputPathType, - version: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> V3dExchangeOutputs: - """ - Replaces voxel values using a mapping file with specified columns. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output prefix. - infile: Input dataset. Acceptable data types are byte, short, and\ - floats. - mapfile: Mapping columns. Input values in the first column, output\ - values in the second column. - version: Print author and version info. - help_: Print this help screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dExchangeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EXCHANGE_METADATA) - cargs = [] - cargs.append("3dExchange") - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-input") - cargs.append(execution.input_file(infile)) - cargs.append("-map") - cargs.append(execution.input_file(mapfile)) - if version: - cargs.append("-ver") - if help_: - cargs.append("-help") - ret = V3dExchangeOutputs( - root=execution.output_file("."), - output_head=execution.output_file(prefix + "+orig.HEAD"), - output_brik=execution.output_file(prefix + "+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dExchangeOutputs", - "V_3D_EXCHANGE_METADATA", - "v_3d_exchange", -] diff --git a/python/src/niwrap/afni/v_3d_extract_group_in_corr.py b/python/src/niwrap/afni/v_3d_extract_group_in_corr.py deleted file mode 100644 index d2d5d8184..000000000 --- a/python/src/niwrap/afni/v_3d_extract_group_in_corr.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EXTRACT_GROUP_IN_CORR_METADATA = Metadata( - id="589ed658ff74e91ed944c55e458a7888b478c333.boutiques", - name="3dExtractGroupInCorr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dExtractGroupInCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_extract_group_in_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Output dataset reconstructed from GroupInCorr data""" - - -def v_3d_extract_group_in_corr( - group_in_corr_file: InputPathType, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dExtractGroupInCorrOutputs: - """ - This program breaks the collection of images from a GroupInCorr file back into - individual AFNI 3D+time datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - group_in_corr_file: GroupInCorr file to extract datasets from (e.g.\ - AAA.grpincorr.niml). - prefix: Prefix to prepend to dataset labels. Use 'NULL' to skip the use\ - of the prefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dExtractGroupInCorrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EXTRACT_GROUP_IN_CORR_METADATA) - cargs = [] - cargs.append("3dExtractGroupInCorr") - cargs.append(execution.input_file(group_in_corr_file)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = V3dExtractGroupInCorrOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "_[DATASET_LABEL].nii") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dExtractGroupInCorrOutputs", - "V_3D_EXTRACT_GROUP_IN_CORR_METADATA", - "v_3d_extract_group_in_corr", -] diff --git a/python/src/niwrap/afni/v_3d_extrema.py b/python/src/niwrap/afni/v_3d_extrema.py deleted file mode 100644 index 8bd0d3756..000000000 --- a/python/src/niwrap/afni/v_3d_extrema.py +++ /dev/null @@ -1,164 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_EXTREMA_METADATA = Metadata( - id="b1468c4ee8a8b4bb488d1ae8001ff3228a3171fd.boutiques", - name="3dExtrema", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dExtremaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_extrema(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head_file: OutputPathType | None - """Output HEAD file""" - output_brik_file: OutputPathType | None - """Output BRIK file""" - - -def v_3d_extrema( - input_dataset: InputPathType, - output_prefix: str | None = None, - output_session: str | None = None, - quiet: bool = False, - mask_file: InputPathType | None = None, - mask_threshold: float | None = None, - data_threshold: float | None = None, - n_best: float | None = None, - separation_distance: float | None = None, - minima: bool = False, - maxima: bool = False, - strict: bool = False, - partial: bool = False, - interior: bool = False, - closure: bool = False, - slice_: bool = False, - volume: bool = False, - remove: bool = False, - average: bool = False, - weight: bool = False, - runner: Runner | None = None, -) -> V3dExtremaOutputs: - """ - Find local extrema (minima or maxima) in 3D datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g. dataset+tlrc'[sub-brick]'). - output_prefix: Prefix for the output dataset name. - output_session: Directory for the output dataset session. - quiet: Suppress screen output. - mask_file: Mask statistic from file. - mask_threshold: Only voxels whose mask statistic is >= m in absolute\ - value will be considered. - data_threshold: Only voxels whose value (intensity) is greater than d\ - in absolute value will be considered. - n_best: Only print the first N extrema. - separation_distance: Minimum separation distance (in mm) for distinct\ - extrema. - minima: Find local minima. - maxima: Find local maxima (default). - strict: Use strict inequality for extrema (default). - partial: Use partial inequality for extrema. - interior: Extrema must be interior points (default). - closure: Extrema may be boundary points. - slice_: Consider each slice separately (default). - volume: Consider the volume as a whole. - remove: Remove all but strongest of neighboring extrema (default). - average: Replace neighboring extrema by average. - weight: Replace neighboring extrema by weighted average. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dExtremaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_EXTREMA_METADATA) - cargs = [] - cargs.append("3dExtrema") - cargs.append(execution.input_file(input_dataset)) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if output_session is not None: - cargs.extend([ - "-session", - output_session - ]) - if quiet: - cargs.append("-quiet") - if mask_file is not None: - cargs.extend([ - "-mask_file", - execution.input_file(mask_file) - ]) - if mask_threshold is not None: - cargs.extend([ - "-mask_thr", - str(mask_threshold) - ]) - if data_threshold is not None: - cargs.extend([ - "-data_thr", - str(data_threshold) - ]) - if n_best is not None: - cargs.extend([ - "-nbest", - str(n_best) - ]) - if separation_distance is not None: - cargs.extend([ - "-sep_dist", - str(separation_distance) - ]) - if minima: - cargs.append("-minima") - if maxima: - cargs.append("-maxima") - if strict: - cargs.append("-strict") - if partial: - cargs.append("-partial") - if interior: - cargs.append("-interior") - if closure: - cargs.append("-closure") - if slice_: - cargs.append("-slice") - if volume: - cargs.append("-volume") - if remove: - cargs.append("-remove") - if average: - cargs.append("-average") - if weight: - cargs.append("-weight") - ret = V3dExtremaOutputs( - root=execution.output_file("."), - output_head_file=execution.output_file(output_prefix + ".HEAD") if (output_prefix is not None) else None, - output_brik_file=execution.output_file(output_prefix + ".BRIK") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dExtremaOutputs", - "V_3D_EXTREMA_METADATA", - "v_3d_extrema", -] diff --git a/python/src/niwrap/afni/v_3d_fdr.py b/python/src/niwrap/afni/v_3d_fdr.py deleted file mode 100644 index 14438351f..000000000 --- a/python/src/niwrap/afni/v_3d_fdr.py +++ /dev/null @@ -1,139 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_FDR_METADATA = Metadata( - id="3ac9a33caf8649adfa21c37c4ff26a8483e8935a.boutiques", - name="3dFDR", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dFdrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_fdr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType - """Output dataset in BRIK format""" - output_head: OutputPathType - """Output dataset in HEAD format""" - output_1d: OutputPathType - """Output list of voxel q-values""" - - -def v_3d_fdr( - input_file: InputPathType, - prefix: str, - mask_file: InputPathType | None = None, - mask_threshold: float | None = None, - constant_type: typing.Literal["cind", "cdep"] | None = None, - quiet: bool = False, - list_: bool = False, - mode_option: typing.Literal["old", "new"] | None = None, - pmask: bool = False, - nopmask: bool = False, - force: bool = False, - float_: bool = False, - qval: bool = False, - runner: Runner | None = None, -) -> V3dFdrOutputs: - """ - A tool for applying False Discovery Rate (FDR) thresholding to voxelwise - statistics in 3D functional datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input 3D functional dataset filename. - prefix: Use 'pname' for the output dataset prefix name. - mask_file: Use mask values from file mname. If file mname contains more\ - than 1 sub-brick, the mask sub-brick must be specified. Generally\ - should be used to avoid counting non-brain voxels. - mask_threshold: Only voxels whose corresponding mask value is greater\ - than or equal to the specified value in absolute terms will be\ - considered. Default is 1. - constant_type: Set constant c(N): 1 for independent p-values (default)\ - or sum(1/i, i=1,...,N) for any joint distribution. - quiet: Suppress screen output. - list_: Write sorted list of voxel q-values to screen. - mode_option: Use the old or new mode of operation. 'new' is now the\ - default. - pmask: Ignore p=1 voxels (default in new mode). - nopmask: Count p=1 voxels (default in old mode). - force: Force conversion of all sub-bricks, treating them as p-values. - float_: Force the output of z-scores in floating point format. - qval: Force the output of q-values rather than z-scores. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dFdrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_FDR_METADATA) - cargs = [] - cargs.append("3dFDR") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if mask_file is not None: - cargs.extend([ - "-mask_file", - execution.input_file(mask_file) - ]) - if mask_threshold is not None: - cargs.extend([ - "-mask_thr", - str(mask_threshold) - ]) - if constant_type is not None: - cargs.extend([ - "-c", - constant_type - ]) - if quiet: - cargs.append("-quiet") - if list_: - cargs.append("-list") - cargs.extend([ - "-prefix", - prefix - ]) - if mode_option is not None: - cargs.extend([ - "-", - mode_option - ]) - if pmask: - cargs.append("-pmask") - if nopmask: - cargs.append("-nopmask") - if force: - cargs.append("-force") - if float_: - cargs.append("-float") - if qval: - cargs.append("-qval") - ret = V3dFdrOutputs( - root=execution.output_file("."), - output_brik=execution.output_file(prefix + "+orig.BRIK"), - output_head=execution.output_file(prefix + "+orig.HEAD"), - output_1d=execution.output_file(prefix + ".1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dFdrOutputs", - "V_3D_FDR_METADATA", - "v_3d_fdr", -] diff --git a/python/src/niwrap/afni/v_3d_fft.py b/python/src/niwrap/afni/v_3d_fft.py deleted file mode 100644 index 8d20d270b..000000000 --- a/python/src/niwrap/afni/v_3d_fft.py +++ /dev/null @@ -1,126 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_FFT_METADATA = Metadata( - id="129f53095c989415a22c05c680edc2acfb61ba7f.boutiques", - name="3dFFT", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dFftOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_fft(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Output dataset generated by 3dFFT.""" - - -def v_3d_fft( - dataset: InputPathType, - abs_: bool = False, - phase: bool = False, - complex_: bool = False, - inverse: bool = False, - lx: float | None = None, - ly: float | None = None, - lz: float | None = None, - alt_in: bool = False, - alt_out: bool = False, - input_: InputPathType | None = None, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dFftOutputs: - """ - Performs the FFT of the input dataset in 3 directions (x, y, z) and produces the - output dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset (e.g., dataset.nii). - abs_: Outputs the magnitude of the FFT (default). - phase: Outputs the phase of the FFT (-PI..PI). - complex_: Outputs the complex-valued FFT. - inverse: Does the inverse FFT instead of the forward FFT. - lx: Use FFT of length 'xx' in the x-direction. - ly: Use FFT of length 'yy' in the y-direction. - lz: Use FFT of length 'zz' in the z-direction. - alt_in: Alternate signs of input data before FFT to bring zero\ - frequency from edge of FFT-space to center of grid for cosmetic\ - purposes. - alt_out: Alternate signs of output data after FFT. Use '-altOUT' with\ - '-altIN' on the forward transform to get the signs of the recovered\ - image correct. - input_: Read the input dataset from specified file instead of from the\ - last argument on the command line. - prefix: Use specified prefix for the output dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dFftOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_FFT_METADATA) - cargs = [] - cargs.append("3dFFT") - cargs.append(execution.input_file(dataset)) - if abs_: - cargs.append("--abs") - if phase: - cargs.append("--phase") - if complex_: - cargs.append("--complex") - if inverse: - cargs.append("--inverse") - if lx is not None: - cargs.extend([ - "--Lx", - str(lx) - ]) - if ly is not None: - cargs.extend([ - "--Ly", - str(ly) - ]) - if lz is not None: - cargs.extend([ - "--Lz", - str(lz) - ]) - if alt_in: - cargs.append("--altIN") - if alt_out: - cargs.append("--altOUT") - if input_ is not None: - cargs.extend([ - "--input", - execution.input_file(input_) - ]) - if prefix is not None: - cargs.extend([ - "--prefix", - prefix - ]) - ret = V3dFftOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dFftOutputs", - "V_3D_FFT_METADATA", - "v_3d_fft", -] diff --git a/python/src/niwrap/afni/v_3d_friedman.py b/python/src/niwrap/afni/v_3d_friedman.py deleted file mode 100644 index b5d225b0e..000000000 --- a/python/src/niwrap/afni/v_3d_friedman.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_FRIEDMAN_METADATA = Metadata( - id="39739dbe60149a8c929fe468d57b937cc221945c.boutiques", - name="3dFriedman", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dFriedmanOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_friedman(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Friedman statistics output file""" - - -def v_3d_friedman( - levels: int, - datasets: list[InputPathType], - output_prefix: str, - workmem: int | None = None, - voxel_num: int | None = None, - runner: Runner | None = None, -) -> V3dFriedmanOutputs: - """ - Performs nonparametric Friedman test for randomized complete block design - experiments. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - levels: Number of treatments. - datasets: Data sets for each treatment. - output_prefix: Prefix for the output files. - workmem: Number of megabytes of RAM to use for statistical workspace. - voxel_num: Screen output for a specific voxel number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dFriedmanOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_FRIEDMAN_METADATA) - cargs = [] - cargs.append("3dFriedman") - cargs.append(str(levels)) - cargs.extend([ - "-dset", - *[execution.input_file(f) for f in datasets] - ]) - if workmem is not None: - cargs.extend([ - "-workmem", - str(workmem) - ]) - if voxel_num is not None: - cargs.extend([ - "-voxel", - str(voxel_num) - ]) - cargs.extend([ - "-out", - output_prefix - ]) - ret = V3dFriedmanOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + "*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dFriedmanOutputs", - "V_3D_FRIEDMAN_METADATA", - "v_3d_friedman", -] diff --git a/python/src/niwrap/afni/v_3d_fwhmx.py b/python/src/niwrap/afni/v_3d_fwhmx.py deleted file mode 100644 index 936a5793b..000000000 --- a/python/src/niwrap/afni/v_3d_fwhmx.py +++ /dev/null @@ -1,134 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_FWHMX_METADATA = Metadata( - id="27449a1dcd931f8aae9d15520a0f627e5b7d94bd.boutiques", - name="3dFWHMx", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dFwhmxOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_fwhmx(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType | None - """Output file containing FWHM/ACF estimates""" - detrended_dataset: OutputPathType | None - """Detrended dataset file""" - - -def v_3d_fwhmx( - infile: InputPathType, - mask: InputPathType | None = None, - automask: bool = False, - demed: bool = False, - unif: bool = False, - detrend: float | None = None, - detprefix: str | None = None, - geom: bool = False, - arith: bool = False, - combine: bool = False, - out: str | None = None, - compat: bool = False, - acf: str | None = None, - runner: Runner | None = None, -) -> V3dFwhmxOutputs: - """ - Compute Full Width at Half Maximum (FWHM) for FMRI datasets using - AutoCorrelation Function (ACF). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input dataset. - mask: Use only voxels that are nonzero in dataset 'mmm'. - automask: Compute a mask from THIS dataset. - demed: if the input dataset has more than one sub-brick then subtract\ - the median of each voxel's time series before processing FWHM. - unif: Normalize each voxel's time series to have the same MAD before\ - processing FWHM, implies -demed. - detrend: Detrend to order 'q'. If q is not given, the program picks\ - q=NT/30; -detrend disables -demed, and includes -unif. - detprefix: Save the detrended file into a dataset with prefix 'd'. - geom: Compute the final estimate as the geometric mean. - arith: Compute the final estimate as the arithmetic mean. - combine: Combine the final measurements along each axis into one result. - out: Write output to file 'ttt' (3 columns of numbers). If not given,\ - the sub-brick outputs are not written. Use '-out -' to write to stdout,\ - if desired. - compat: Be compatible with the older 3dFWHM. - acf: Compute the spatial autocorrelation of the data as a function of\ - radius, then fit that to a model and output the model parameters. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dFwhmxOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_FWHMX_METADATA) - cargs = [] - cargs.append("3dFWHMx") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - if demed: - cargs.append("-demed") - if unif: - cargs.append("-unif") - if detrend is not None: - cargs.extend([ - "-detrend", - str(detrend) - ]) - if detprefix is not None: - cargs.extend([ - "-detprefix", - detprefix - ]) - if geom: - cargs.append("-geom") - if arith: - cargs.append("-arith") - if combine: - cargs.append("-combine") - if out is not None: - cargs.extend([ - "-out", - out - ]) - if compat: - cargs.append("-compat") - if acf is not None: - cargs.extend([ - "-acf", - acf - ]) - cargs.append(execution.input_file(infile)) - ret = V3dFwhmxOutputs( - root=execution.output_file("."), - out_file=execution.output_file(out + ".1D") if (out is not None) else None, - detrended_dataset=execution.output_file(detprefix + ".nii.gz") if (detprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dFwhmxOutputs", - "V_3D_FWHMX_METADATA", - "v_3d_fwhmx", -] diff --git a/python/src/niwrap/afni/v_3d_gen_feature_dist.py b/python/src/niwrap/afni/v_3d_gen_feature_dist.py deleted file mode 100644 index 426a41a91..000000000 --- a/python/src/niwrap/afni/v_3d_gen_feature_dist.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_GEN_FEATURE_DIST_METADATA = Metadata( - id="da95cd4ad99ed473c7cd10c18b299096e78c2557.boutiques", - name="3dGenFeatureDist", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dGenFeatureDistOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_gen_feature_dist(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_hive: OutputPathType | None - """Histogram volume output""" - - -def v_3d_gen_feature_dist( - features_string: str, - class_string: str, - prefix: str | None = None, - overwrite: bool = False, - debug_level: float | None = None, - other: bool = False, - no_other: bool = False, - show_histograms: str | None = None, - runner: Runner | None = None, -) -> V3dGenFeatureDistOutputs: - """ - 3dGenFeatureDist produces histogram volume (hives) from input data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - features_string: FEATURES_STRING is a semicolon delimited string of\ - features. - class_string: CLASS_STRING is a semicolon delimited string of class\ - labels. - prefix: PREF is the prefix for all output volumes that are not\ - debugging related. - overwrite: Automatically overwrite existing output. - debug_level: Debugging level. - other: Add histograms for an 'OTHER' class that has a uniform pdf. - no_other: Opposite of -OTHER. - show_histograms: Show specified histograms and quit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dGenFeatureDistOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_GEN_FEATURE_DIST_METADATA) - cargs = [] - cargs.append("3dGenFeatureDist") - cargs.extend([ - "-features", - features_string - ]) - cargs.extend([ - "-classes", - class_string - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if overwrite: - cargs.append("-overwrite") - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if other: - cargs.append("-OTHER") - if no_other: - cargs.append("-no_OTHER") - if show_histograms is not None: - cargs.extend([ - "-ShowTheseHists", - show_histograms - ]) - ret = V3dGenFeatureDistOutputs( - root=execution.output_file("."), - output_hive=execution.output_file(prefix + "_hive.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dGenFeatureDistOutputs", - "V_3D_GEN_FEATURE_DIST_METADATA", - "v_3d_gen_feature_dist", -] diff --git a/python/src/niwrap/afni/v_3d_gen_priors.py b/python/src/niwrap/afni/v_3d_gen_priors.py deleted file mode 100644 index adb72a315..000000000 --- a/python/src/niwrap/afni/v_3d_gen_priors.py +++ /dev/null @@ -1,227 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_GEN_PRIORS_METADATA = Metadata( - id="6bcbee0f81b8c6ac92070bd494e66a14fcbbd130.boutiques", - name="3dGenPriors", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dGenPriorsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_gen_priors(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_cprefix: OutputPathType - """Main classification output""" - out_pprefix: OutputPathType - """Main probability output""" - - -def v_3d_gen_priors( - sigs: InputPathType, - tdist: InputPathType, - cprefix: str, - pprefix: str, - labeltable: InputPathType, - do: str, - prefix: str | None = None, - cmask: str | None = None, - mask: str | None = None, - mrange: list[float] | None = None, - debug: float | None = None, - vox_debug: str | None = None, - vox_debug_file: str | None = None, - uid: str | None = None, - use_tmp: bool = False, - no_tmp: bool = False, - pset: str | None = None, - cset: str | None = None, - regroup_classes: str | None = None, - classes: str | None = None, - features: str | None = None, - strict_feature_match: bool = False, - featgroups: str | None = None, - show_this_dist: str | None = None, - fast: bool = False, - slow: bool = False, - runner: Runner | None = None, -) -> V3dGenPriorsOutputs: - """ - Produces classification priors based on voxel signatures. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - sigs: Signatures dataset. A dataset with F features per voxel. - tdist: Training results. This file is generated by 3dSignatures. - cprefix: Prefix for class dataset. - pprefix: Prefix for probability dataset. - labeltable: Labeltable to attach to output dataset. - do: Specify the output that this program should create. - prefix: Specify root prefix for output volumes. - cmask: Provide cmask expression. Voxels where expression is 0 are\ - excluded from computations. - mask: Provide mask dataset. - mrange: Consider MASK only for values between M0 and M1, inclusive. - debug: Set debug level. - vox_debug: 1D index or 3D indices (I J K) of voxel to debug. - vox_debug_file: File in which debug information is output. - uid: User identifier string. Used to generate names for temporary\ - files. - use_tmp: Use temporary storage to speed up the program. - no_tmp: Do not use temporary storage. - pset: Reuse probability output from an earlier run. - cset: Reuse classification output from an earlier run. - regroup_classes: Regroup classes into parent classes. Requires naming\ - the original classes as C1.*, C2.*, etc. - classes: Classify into these classes only. - features: Use these features only. Otherwise, all features in the\ - signature file will be used. - strict_feature_match: Use strict feature name matching. - featgroups: Feature groups. - show_this_dist: Show information obtained from the training data about\ - the distribution of DIST. Set DIST to ALL to see all distributions. - fast: Use OpenMPized routines for faster performance. - slow: Do not use OpenMPized routines. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dGenPriorsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_GEN_PRIORS_METADATA) - cargs = [] - cargs.append("3dGenPriors") - cargs.append("-sig") - cargs.append(execution.input_file(sigs)) - cargs.append("-tdist") - cargs.append(execution.input_file(tdist)) - cargs.append("-cprefix") - cargs.extend([ - "-cprefix", - cprefix - ]) - cargs.append("-pprefix") - cargs.extend([ - "-pprefix", - pprefix - ]) - cargs.append("-labeltable") - cargs.extend([ - "-labeltable", - execution.input_file(labeltable) - ]) - cargs.append("-do") - cargs.extend([ - "-do", - do - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if mask is not None: - cargs.extend([ - "-mask", - mask - ]) - if mrange is not None: - cargs.extend([ - "-mrange", - *map(str, mrange) - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if vox_debug is not None: - cargs.extend([ - "-vox_debug", - vox_debug - ]) - if vox_debug_file is not None: - cargs.extend([ - "-vox_debug_file", - vox_debug_file - ]) - if uid is not None: - cargs.extend([ - "-uid", - uid - ]) - if use_tmp: - cargs.append("-use_tmp") - if no_tmp: - cargs.append("-no_tmp") - if pset is not None: - cargs.extend([ - "-pset", - pset - ]) - if cset is not None: - cargs.extend([ - "-cset", - cset - ]) - if regroup_classes is not None: - cargs.extend([ - "-regroup_classes", - regroup_classes - ]) - if classes is not None: - cargs.extend([ - "-classes", - classes - ]) - if features is not None: - cargs.extend([ - "-features", - features - ]) - if strict_feature_match: - cargs.append("-strict_feature_match") - if featgroups is not None: - cargs.extend([ - "-featgroups", - featgroups - ]) - if show_this_dist is not None: - cargs.extend([ - "-ShowThisDist", - show_this_dist - ]) - if fast: - cargs.append("-fast") - if slow: - cargs.append("-slow") - ret = V3dGenPriorsOutputs( - root=execution.output_file("."), - out_cprefix=execution.output_file(cprefix + ".nii.gz"), - out_pprefix=execution.output_file(pprefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dGenPriorsOutputs", - "V_3D_GEN_PRIORS_METADATA", - "v_3d_gen_priors", -] diff --git a/python/src/niwrap/afni/v_3d_getrow.py b/python/src/niwrap/afni/v_3d_getrow.py deleted file mode 100644 index 69e826f5c..000000000 --- a/python/src/niwrap/afni/v_3d_getrow.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_GETROW_METADATA = Metadata( - id="d22ec4eb4bbd666f8edad727a5f0b3e13111b433.boutiques", - name="3dGetrow", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dGetrowOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_getrow(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType | None - """Output .1D ASCII file""" - - -def v_3d_getrow( - xrow: list[int] | None = None, - yrow: list[int] | None = None, - zrow: list[int] | None = None, - input_file: InputPathType | None = None, - output_file: str | None = None, - runner: Runner | None = None, -) -> V3dGetrowOutputs: - """ - Program to extract 1 row from a dataset and write it as a .1D file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - xrow: Extract row along the x-direction at fixed y-index of j and fixed\ - z-index of k. - yrow: Extract row along the y-direction at fixed x-index of i and fixed\ - z-index of k. - zrow: Extract row along the z-direction at fixed x-index of i and fixed\ - y-index of j. - input_file: Read input from dataset 'ddd' (instead of putting dataset\ - name at end of command line). - output_file: Filename for output .1D ASCII file will be 'ff' (if 'ff'\ - is '-', then output is to stdout, the default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dGetrowOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_GETROW_METADATA) - cargs = [] - cargs.append("3dGetrow") - if xrow is not None: - cargs.extend([ - "-xrow", - *map(str, xrow) - ]) - if yrow is not None: - cargs.extend([ - "-yrow", - *map(str, yrow) - ]) - if zrow is not None: - cargs.extend([ - "-zrow", - *map(str, zrow) - ]) - if input_file is not None: - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if output_file is not None: - cargs.extend([ - "-output", - output_file - ]) - ret = V3dGetrowOutputs( - root=execution.output_file("."), - out_file=execution.output_file(output_file + ".1D") if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dGetrowOutputs", - "V_3D_GETROW_METADATA", - "v_3d_getrow", -] diff --git a/python/src/niwrap/afni/v_3d_grayplot.py b/python/src/niwrap/afni/v_3d_grayplot.py deleted file mode 100644 index f51eeb08a..000000000 --- a/python/src/niwrap/afni/v_3d_grayplot.py +++ /dev/null @@ -1,145 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_GRAYPLOT_METADATA = Metadata( - id="6d17ab08ae2c6bafb3bb5a4bc0dd707aa3956213.boutiques", - name="3dGrayplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dGrayplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_grayplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - grayplot_img: OutputPathType | None - """Grayplot image file""" - - -def v_3d_grayplot( - input_: InputPathType, - mask: InputPathType | None = None, - prefix: str | None = None, - dimensions: list[float] | None = None, - resample_old: bool = False, - polort: float | None = None, - fwhm: float | None = None, - pvorder: bool = False, - ljorder: bool = False, - peelorder: bool = False, - ijkorder: bool = False, - range_: float | None = None, - percent: bool = False, - raw_with_bounds: list[float] | None = None, - runner: Runner | None = None, -) -> V3dGrayplotOutputs: - """ - Make a grayplot from a 3D+time dataset, like a carpet plot. Result is saved to a - PNG image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - mask: Name of mask dataset. Voxels that are 0 in the mask will not be\ - processed. - prefix: Name for the output file. Default is Grayplot.png. - dimensions: Output size of image in pixels: [width height]. Defaults\ - are width=1024 and height=512. - resample_old: Original resampling method for processed dataset. - polort: Order of polynomials for detrending. Default is 2. Use '-1' if\ - data is already detrended and de-meaned. - fwhm: FWHM of blurring radius to use in the dataset before making the\ - image. Default is 0 mm. - pvorder: Order the voxels by how well they match the two leading\ - principal components of their partition. - ljorder: Order the voxels by their Ljung-Box statistics, a measure of\ - temporal correlation. - peelorder: Order the voxels by how many 'peel' steps are needed to get\ - from the partition boundary to the voxel. - ijkorder: Default intra-partition ordering by dataset 3D index ('ijk'). - range_: Set the range of the data to be plotted. Value of 0 is\ - middle-gray, +X is white, -X is black. - percent: Scale values to percent differences from the mean of each\ - voxel timeseries. Suitable for raw time series datasets. - raw_with_bounds: Map values <= A to black, values >= B to white, and\ - intermediate values to grays. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dGrayplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_GRAYPLOT_METADATA) - cargs = [] - cargs.append("3dGrayplot") - cargs.append(execution.input_file(input_)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if dimensions is not None: - cargs.extend([ - "-dimen", - *map(str, dimensions) - ]) - if resample_old: - cargs.append("-oldresam") - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if fwhm is not None: - cargs.extend([ - "-fwhm", - str(fwhm) - ]) - if pvorder: - cargs.append("-pvorder") - if ljorder: - cargs.append("-LJorder") - if peelorder: - cargs.append("-peelorder") - if ijkorder: - cargs.append("-ijkorder") - if range_ is not None: - cargs.extend([ - "-range", - str(range_) - ]) - if percent: - cargs.append("-percent") - if raw_with_bounds is not None: - cargs.extend([ - "-raw_with_bounds", - *map(str, raw_with_bounds) - ]) - ret = V3dGrayplotOutputs( - root=execution.output_file("."), - grayplot_img=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dGrayplotOutputs", - "V_3D_GRAYPLOT_METADATA", - "v_3d_grayplot", -] diff --git a/python/src/niwrap/afni/v_3d_group_in_corr.py b/python/src/niwrap/afni/v_3d_group_in_corr.py deleted file mode 100644 index 7006a9524..000000000 --- a/python/src/niwrap/afni/v_3d_group_in_corr.py +++ /dev/null @@ -1,215 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_GROUP_IN_CORR_METADATA = Metadata( - id="409c8785c271784a304ce25d717eab688051ad5e.boutiques", - name="3dGroupInCorr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dGroupInCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_group_in_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Results from analysis""" - - -def v_3d_group_in_corr( - set_a: InputPathType, - set_b: InputPathType | None = None, - apair: bool = False, - label_a: str | None = None, - label_b: str | None = None, - pooled: bool = False, - unpooled: bool = False, - paired: bool = False, - nosix: bool = False, - covariates_file: InputPathType | None = None, - center: str | None = None, - seed_radius: float | None = None, - sendall: bool = False, - donocov: bool = False, - dospcov: bool = False, - cluster: str | None = None, - read: bool = False, - ztest: bool = False, - ah: str | None = None, - port_offset: float | None = None, - port_offset_quiet: float | None = None, - port_bloc: float | None = None, - suma: bool = False, - quiet: bool = False, - verbose: bool = False, - very_verbose: bool = False, - debug: bool = False, - batch: str | None = None, - runner: Runner | None = None, -) -> V3dGroupInCorrOutputs: - """ - Functional connectivity analysis in group of subjects. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - set_a: Setup file describing the first dataset collection. - set_b: Setup file describing the second dataset collection for\ - two-sample t-test analysis. - apair: Use -setA collection again but with different seed locations;\ - produce paired t-test. - label_a: Label for sub-bricks corresponding to setA. - label_b: Label for sub-bricks corresponding to setB. - pooled: Use pooled variance estimator for two-sample un-paired t-test. - unpooled: Use unpooled variance estimator for two-sample un-paired\ - t-test. - paired: Use a two-sample paired t-test. - nosix: Suppress the individual 1-sample t-tests and only return the\ - difference 2-sample t-test. - covariates_file: File containing covariate values for each dataset. - center: Option for centering covariates. - seed_radius: Radius for seed voxel time series averaging (mm). - sendall: Send all individual subject results to AFNI along with group\ - statistics. - donocov: Compute results both with and without covariates. - dospcov: Compute Spearman (rank) correlation coefficient of subject\ - correlation results vs each covariate. - cluster: Input results from a 3dClustSim run to interface with AFNI. - read: Force program to read data into memory instead of memory mapping. - ztest: Debugging option to test if input data is all zero. - ah: Connect to AFNI/SUMA on a remote host. - port_offset: Provide a port offset. - port_offset_quiet: Provide a port offset, with less verbose output. - port_bloc: Provide a port offset bloc. - suma: Talk to SUMA instead of AFNI. - quiet: Suppress informational messages. - verbose: Print extra informational messages. - very_verbose: Print even more detailed informational messages. - debug: Enable internal testing. - batch: Run program in batch mode with specified METHOD and command\ - file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dGroupInCorrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_GROUP_IN_CORR_METADATA) - cargs = [] - cargs.append("3dGroupInCorr") - cargs.extend([ - "-setA", - execution.input_file(set_a) - ]) - if set_b is not None: - cargs.extend([ - "-setB", - execution.input_file(set_b) - ]) - if apair: - cargs.append("-Apair") - if label_a is not None: - cargs.extend([ - "-labelA", - label_a - ]) - if label_b is not None: - cargs.extend([ - "-labelB", - label_b - ]) - if pooled: - cargs.append("-pooled") - if unpooled: - cargs.append("-unpooled") - if paired: - cargs.append("-paired") - if nosix: - cargs.append("-nosix") - if covariates_file is not None: - cargs.extend([ - "-covariates", - execution.input_file(covariates_file) - ]) - if center is not None: - cargs.extend([ - "-center", - center - ]) - if seed_radius is not None: - cargs.extend([ - "-seedrad", - str(seed_radius) - ]) - if sendall: - cargs.append("-sendall") - if donocov: - cargs.append("-donocov") - if dospcov: - cargs.append("-dospcov") - if cluster is not None: - cargs.extend([ - "-clust", - cluster - ]) - if read: - cargs.append("-read") - if ztest: - cargs.append("-ztest") - if ah is not None: - cargs.extend([ - "-ah", - ah - ]) - if port_offset is not None: - cargs.extend([ - "-np", - str(port_offset) - ]) - if port_offset_quiet is not None: - cargs.extend([ - "-npq", - str(port_offset_quiet) - ]) - if port_bloc is not None: - cargs.extend([ - "-npb", - str(port_bloc) - ]) - if suma: - cargs.append("-suma") - if quiet: - cargs.append("-quiet") - if verbose: - cargs.append("-verb") - if very_verbose: - cargs.append("-VERB") - if debug: - cargs.append("-debug") - if batch is not None: - cargs.extend([ - "-batch", - batch - ]) - ret = V3dGroupInCorrOutputs( - root=execution.output_file("."), - output_file=execution.output_file(pathlib.Path(set_a).name + ".results.nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dGroupInCorrOutputs", - "V_3D_GROUP_IN_CORR_METADATA", - "v_3d_group_in_corr", -] diff --git a/python/src/niwrap/afni/v_3d_hist.py b/python/src/niwrap/afni/v_3d_hist.py deleted file mode 100644 index d538fed7a..000000000 --- a/python/src/niwrap/afni/v_3d_hist.py +++ /dev/null @@ -1,181 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_HIST_METADATA = Metadata( - id="5c60bca543a8218316ce5c5d5d1a704a09668ad0.boutiques", - name="3dHist", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dHistOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_hist(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_hist( - input_: InputPathType, - mask_dset: InputPathType | None = None, - mask_range: list[float] | None = None, - cmask: str | None = None, - hist_file: InputPathType | None = None, - prefix: str | None = None, - equalized: str | None = None, - nbin: float | None = None, - min_: float | None = None, - max_: float | None = None, - binwidth: float | None = None, - ignore_out: bool = False, - range_hist: InputPathType | None = None, - showhist: bool = False, - at_val: float | None = None, - get_params: str | None = None, - voxvol: float | None = None, - val_at: str | None = None, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dHistOutputs: - """ - Computes histograms using functions for generating priors. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Dataset providing values for histogram. - mask_dset: Provide mask dataset to select subset of input. - mask_range: Specify the range of values to consider from MSET. Default\ - is anything non-zero. - cmask: Provide cmask expression. Voxels where expression is 0 are\ - excluded from computations. - hist_file: Read this previously created histogram instead of forming\ - one from DSET. - prefix: Write histogram to niml file called PREF.niml.hist. - equalized: Write a histogram equalized version of the input dataset. - nbin: Use K bins. - min_: Minimum intensity. - max_: Maximum intensity. - binwidth: Bin width. - ignore_out: Do not count samples outside the user specified range. - range_hist: Use previously created histogram to set range and binwidth\ - parameters. - showhist: Display histogram to stdout. - at_val: Set the value at which you want histogram values. - get_params: Return the desired properties at a given value. You can\ - select multiple properties. - voxvol: Specify voxel volume in mm^3. To be used with upvol. - val_at: Return the value where histogram property PAR is equal to\ - PARVAL. PAR can be: cdf, rcdf, ncdf, nrcdf, upvol. - quiet: Return a concise output to simplify parsing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dHistOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_HIST_METADATA) - cargs = [] - cargs.append("3dHist") - cargs.append(execution.input_file(input_)) - if mask_dset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dset) - ]) - if mask_range is not None: - cargs.extend([ - "-mask_range", - *map(str, mask_range) - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if hist_file is not None: - cargs.extend([ - "-thishist", - execution.input_file(hist_file) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if equalized is not None: - cargs.extend([ - "-equalized", - equalized - ]) - if nbin is not None: - cargs.extend([ - "-nbin", - str(nbin) - ]) - if min_ is not None: - cargs.extend([ - "-min", - str(min_) - ]) - if max_ is not None: - cargs.extend([ - "-max", - str(max_) - ]) - if binwidth is not None: - cargs.extend([ - "-binwidth", - str(binwidth) - ]) - if ignore_out: - cargs.append("-ignore_out") - if range_hist is not None: - cargs.extend([ - "-rhist", - execution.input_file(range_hist) - ]) - if showhist: - cargs.append("-showhist") - if at_val is not None: - cargs.extend([ - "-at", - str(at_val) - ]) - if get_params is not None: - cargs.extend([ - "-get", - get_params - ]) - if voxvol is not None: - cargs.extend([ - "-voxvol", - str(voxvol) - ]) - if val_at is not None: - cargs.extend([ - "-val_at", - val_at - ]) - if quiet: - cargs.append("-quiet") - ret = V3dHistOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dHistOutputs", - "V_3D_HIST_METADATA", - "v_3d_hist", -] diff --git a/python/src/niwrap/afni/v_3d_icc.py b/python/src/niwrap/afni/v_3d_icc.py deleted file mode 100644 index 546ac60c6..000000000 --- a/python/src/niwrap/afni/v_3d_icc.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ICC_METADATA = Metadata( - id="c36b2e699621f93d8018a24c3d6ec49dbb41d10c.boutiques", - name="3dICC", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dIccOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_icc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Name of the output file""" - - -def v_3d_icc( - model: str, - prefix: str, - data_table: str, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dIccOutputs: - """ - AFNI Program for IntraClass Correlatin (ICC) Analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - model: Model structure for all the variables. The expression FORMULA\ - with more than one variable has to be surrounded within quotes.\ - Variable names should be consistent with the ones used in the header of\ - -dataTable. - prefix: Name of output file. For AFNI format, provide prefix only, with\ - no view+suffix needed. Filename for NIfTI format should have .nii\ - attached, while file name for surface data is expected to end with\ - .niml.dset. - data_table: List the data structure with a header as the first line.\ - The first column is reserved with label 'Subj', and the last is\ - reserved for 'InputFile'. - mask: Path to mask file. Only process voxels inside this mask. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dIccOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ICC_METADATA) - cargs = [] - cargs.append("3dICC") - cargs.append(model) - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-mask") - if mask is not None: - cargs.append(execution.input_file(mask)) - cargs.append("-dataTable") - cargs.append(data_table) - cargs.append("[OPTIONS]") - ret = V3dIccOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dIccOutputs", - "V_3D_ICC_METADATA", - "v_3d_icc", -] diff --git a/python/src/niwrap/afni/v_3d_intracranial.py b/python/src/niwrap/afni/v_3d_intracranial.py deleted file mode 100644 index 5adcf8b1a..000000000 --- a/python/src/niwrap/afni/v_3d_intracranial.py +++ /dev/null @@ -1,109 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_INTRACRANIAL_METADATA = Metadata( - id="23015e339767dba4b46f464166abf3f72e4cb644.boutiques", - name="3dIntracranial", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dIntracranialOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_intracranial(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - segmented_image: OutputPathType - """Output file containing segmented image""" - - -def v_3d_intracranial( - infile: InputPathType, - prefix: str, - min_val: float | None = None, - max_val: float | None = None, - min_conn: float | None = None, - max_conn: float | None = None, - no_smooth: bool = False, - mask: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dIntracranialOutputs: - """ - Performs automatic segmentation of intracranial region. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Filename of anat dataset to be segmented. - prefix: Prefix name for file to contain segmented image. - min_val: Minimum voxel intensity limit. Default is internal PDF\ - estimate for lower bound. - max_val: Maximum voxel intensity limit. Default is internal PDF\ - estimate for upper bound. - min_conn: Minimum voxel connectivity to enter. Default is 4. - max_conn: Maximum voxel connectivity to leave. Default is 2. - no_smooth: Suppress spatial smoothing of segmentation mask. - mask: Generate functional image mask (complement). Default is to\ - generate anatomical image. - quiet: Suppress output to screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dIntracranialOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_INTRACRANIAL_METADATA) - cargs = [] - cargs.append("3dIntracranial") - cargs.append("-anat") - cargs.append(execution.input_file(infile)) - cargs.append("-prefix") - cargs.append(prefix) - if min_val is not None: - cargs.extend([ - "-min_val", - str(min_val) - ]) - if max_val is not None: - cargs.extend([ - "-max_val", - str(max_val) - ]) - if min_conn is not None: - cargs.extend([ - "-min_conn", - str(min_conn) - ]) - if max_conn is not None: - cargs.extend([ - "-max_conn", - str(max_conn) - ]) - if no_smooth: - cargs.append("-nosmooth") - if mask: - cargs.append("-mask") - if quiet: - cargs.append("-quiet") - ret = V3dIntracranialOutputs( - root=execution.output_file("."), - segmented_image=execution.output_file(prefix + "+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dIntracranialOutputs", - "V_3D_INTRACRANIAL_METADATA", - "v_3d_intracranial", -] diff --git a/python/src/niwrap/afni/v_3d_inv_fmri.py b/python/src/niwrap/afni/v_3d_inv_fmri.py deleted file mode 100644 index 00e7ed6c6..000000000 --- a/python/src/niwrap/afni/v_3d_inv_fmri.py +++ /dev/null @@ -1,136 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_INV_FMRI_METADATA = Metadata( - id="61c795f9e8fbcd27d184c27174d9a665a918cd0f.boutiques", - name="3dInvFMRI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dInvFmriOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_inv_fmri(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """The output 1D file.""" - - -def v_3d_inv_fmri( - input_file: InputPathType, - activation_map: InputPathType, - map_weight: InputPathType | None = None, - mask: InputPathType | None = None, - baseline_file: list[InputPathType] | None = None, - polynom_order: float | None = None, - output_file: str | None = None, - method: str | None = None, - alpha: float | None = None, - smooth_fir: bool = False, - smooth_median: bool = False, - runner: Runner | None = None, -) -> V3dInvFmriOutputs: - """ - Program to compute stimulus time series, given a 3D+time dataset and an - activation map (the inverse of the usual FMRI analysis problem). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input 3D+time dataset. - activation_map: Defines activation map; should be a bucket dataset\ - where each sub-brick defines the beta weight map for an unknown\ - stimulus time series. - map_weight: Defines a weighting factor for the map. Dataset can have\ - either 1 sub-brick or the same number as in the -map dataset. - mask: Defines a mask dataset to restrict input voxels from -data and\ - -map. - baseline_file: Baseline time series file. Each column of the file\ - defines a baseline time series. - polynom_order: Adds polynomials of specified order to the baseline\ - collection. - output_file: Name of the 1D output file. - method: Determines the method to use: C for least squares fit to data\ - matrix (default) or K for least squares fit to activation matrix. - alpha: Set the alpha factor to penalize large values of the output\ - vectors. - smooth_fir: Smooth the results with a 5 point lowpass FIR filter. - smooth_median: Smooth the results with a 5 point median filter. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dInvFmriOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_INV_FMRI_METADATA) - cargs = [] - cargs.append("3dInvFMRI") - cargs.extend([ - "-data", - execution.input_file(input_file) - ]) - cargs.extend([ - "-map", - execution.input_file(activation_map) - ]) - if map_weight is not None: - cargs.extend([ - "-mapwt", - execution.input_file(map_weight) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if baseline_file is not None: - cargs.extend([ - "-base", - *[execution.input_file(f) for f in baseline_file] - ]) - if polynom_order is not None: - cargs.extend([ - "-polort", - str(polynom_order) - ]) - if output_file is not None: - cargs.extend([ - "-out", - output_file - ]) - if method is not None: - cargs.extend([ - "-method", - method - ]) - if alpha is not None: - cargs.extend([ - "-alpha", - str(alpha) - ]) - if smooth_fir: - cargs.append("-fir5") - if smooth_median: - cargs.append("-median5") - ret = V3dInvFmriOutputs( - root=execution.output_file("."), - outfile=execution.output_file(output_file) if (output_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dInvFmriOutputs", - "V_3D_INV_FMRI_METADATA", - "v_3d_inv_fmri", -] diff --git a/python/src/niwrap/afni/v_3d_isc.py b/python/src/niwrap/afni/v_3d_isc.py deleted file mode 100644 index c267386dc..000000000 --- a/python/src/niwrap/afni/v_3d_isc.py +++ /dev/null @@ -1,128 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ISC_METADATA = Metadata( - id="6c9916869e62ba9cb0b03f15916de7329295e2a7.boutiques", - name="3dISC", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dIscOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_isc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - isc_output: OutputPathType - """Main output ISC file""" - tstat_output: OutputPathType - """T-statistic of ISC""" - - -def v_3d_isc( - outfile_prefix: str, - model_structure: str, - data_table: str, - num_jobs: float | None = None, - mask_file: InputPathType | None = None, - qvar_centers: str | None = None, - quantitative_vars: str | None = None, - fisher_transform: bool = False, - io_functions: typing.Literal["AFNI", "R"] | None = None, - runner: Runner | None = None, -) -> V3dIscOutputs: - """ - Program for Voxelwise Inter-Subject Correlation (ISC) Analysis using linear - mixed-effects modeling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - outfile_prefix: Output file name. For AFNI format, provide prefix only,\ - with no view+suffix needed. - model_structure: Specify the model structure for all the variables. The\ - expression FORMULA with more than one variable has to be surrounded\ - within quotes. - data_table: List the data structure with a header as the first line.\ - Has to occur last in the script. - num_jobs: Specify the number of jobs to run concurrently. Choose 1 for\ - a single-processor computer. - mask_file: Process voxels inside this mask only. Default is no masking. - qvar_centers: Specify centering values for quantitative variables\ - identified under -qVars. Multiple centers are separated by commas\ - without spaces and should be within quotes. - quantitative_vars: Identify quantitative variables (or covariates). The\ - list should be comma-separated and within quotes. - fisher_transform: Perform Fisher transformation on the response\ - variable (input files) if it is a correlation value. - io_functions: Use AFNI's C io functions (default) or R's io functions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dIscOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ISC_METADATA) - cargs = [] - cargs.append("3dISC") - cargs.extend([ - "-prefix", - outfile_prefix - ]) - if num_jobs is not None: - cargs.extend([ - "-jobs", - str(num_jobs) - ]) - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - cargs.extend([ - "-model", - model_structure - ]) - if qvar_centers is not None: - cargs.extend([ - "-qVarCenters", - qvar_centers - ]) - if quantitative_vars is not None: - cargs.extend([ - "-qVars", - quantitative_vars - ]) - if fisher_transform: - cargs.append("-r2z") - if io_functions is not None: - cargs.extend([ - "-cio", - io_functions - ]) - cargs.extend([ - "-dataTable", - data_table - ]) - ret = V3dIscOutputs( - root=execution.output_file("."), - isc_output=execution.output_file(outfile_prefix + "_ISC.nii"), - tstat_output=execution.output_file(outfile_prefix + "_tstat.nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dIscOutputs", - "V_3D_ISC_METADATA", - "v_3d_isc", -] diff --git a/python/src/niwrap/afni/v_3d_kruskal_wallis.py b/python/src/niwrap/afni/v_3d_kruskal_wallis.py deleted file mode 100644 index 85551f651..000000000 --- a/python/src/niwrap/afni/v_3d_kruskal_wallis.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_KRUSKAL_WALLIS_METADATA = Metadata( - id="d8f52138ea0ac2f25d27a21c1fd03e57b216b428.boutiques", - name="3dKruskalWallis", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dKruskalWallisOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_kruskal_wallis(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_prefix: OutputPathType - """Output file containing Kruskal-Wallis statistics""" - - -def v_3d_kruskal_wallis( - levels: int, - datasets: list[str], - output: str, - workmem: int | None = None, - voxel: int | None = None, - runner: Runner | None = None, -) -> V3dKruskalWallisOutputs: - """ - This program performs nonparametric Kruskal-Wallis test for comparison of - multiple treatments. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - levels: Number of treatments. - datasets: Data set for treatment #1 through to treatment #s. Specify\ - sub-brick if more than one present. - output: Kruskal-Wallis statistics are written to file prefixname. - workmem: Number of megabytes of RAM to use for statistical workspace. - voxel: Screen output for voxel # num. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dKruskalWallisOutputs`). - """ - if not (2 <= levels): - raise ValueError(f"'levels' must be greater than 2 <= x but was {levels}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_KRUSKAL_WALLIS_METADATA) - cargs = [] - cargs.append("3dKruskalWallis") - cargs.extend([ - "-levels", - str(levels) - ]) - cargs.extend([ - "-dset", - *datasets - ]) - if workmem is not None: - cargs.extend([ - "-workmem", - str(workmem) - ]) - if voxel is not None: - cargs.extend([ - "-voxel", - str(voxel) - ]) - cargs.extend([ - "-out", - output - ]) - ret = V3dKruskalWallisOutputs( - root=execution.output_file("."), - outfile_prefix=execution.output_file(output + "+tlrc"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dKruskalWallisOutputs", - "V_3D_KRUSKAL_WALLIS_METADATA", - "v_3d_kruskal_wallis", -] diff --git a/python/src/niwrap/afni/v_3d_lfcd.py b/python/src/niwrap/afni/v_3d_lfcd.py deleted file mode 100644 index c67b33a79..000000000 --- a/python/src/niwrap/afni/v_3d_lfcd.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LFCD_METADATA = Metadata( - id="addfa17bcea1fe82f0ee83c5d035f7c71933d3ea.boutiques", - name="3dLFCD", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLfcdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lfcd(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_lfcd( - in_file: InputPathType, - autoclip: bool = False, - automask: bool = False, - mask: InputPathType | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - polort: int | None = None, - thresh: float | None = None, - runner: Runner | None = None, -) -> V3dLfcdOutputs: - """ - Performs degree centrality on a dataset using a given maskfile via the 3dLFCD - command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dlfcd. - autoclip: Clip off low-intensity regions in the dataset. - automask: Mask the dataset to target brain-only voxels. - mask: Mask file to mask input data. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - polort: No description provided. - thresh: Threshold to exclude connections where corr <= thresh. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLfcdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LFCD_METADATA) - cargs = [] - cargs.append("3dLFCD") - cargs.append(execution.input_file(in_file)) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("[OUT_FILE]") - if outputtype is not None: - cargs.append(outputtype) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if thresh is not None: - cargs.extend([ - "-thresh", - str(thresh) - ]) - ret = V3dLfcdOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_afni"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLfcdOutputs", - "V_3D_LFCD_METADATA", - "v_3d_lfcd", -] diff --git a/python/src/niwrap/afni/v_3d_lme.py b/python/src/niwrap/afni/v_3d_lme.py deleted file mode 100644 index c1735f9ad..000000000 --- a/python/src/niwrap/afni/v_3d_lme.py +++ /dev/null @@ -1,208 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LME_METADATA = Metadata( - id="55c6778eace87b7e1ae56e342faa35268707bee1.boutiques", - name="3dLME", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLmeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lme(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_nifti: OutputPathType - """Output file in NIfTI format""" - - -def v_3d_lme( - prefix: str, - model: str, - data_table: str, - bounds: list[float] | None = None, - cio_flag: bool = False, - cor_str: str | None = None, - cutoff: float | None = None, - dbg_args_flag: bool = False, - jobs: float | None = None, - glt_code: str | None = None, - glt_label: str | None = None, - glf_label: str | None = None, - glf_code: str | None = None, - icc_flag: bool = False, - iccb_flag: bool = False, - log_lik_flag: bool = False, - logit_flag: bool = False, - ml_flag: bool = False, - qvars_centers: str | None = None, - qvars: str | None = None, - raneff: str | None = None, - mask: InputPathType | None = None, - num_glf: float | None = None, - num_glt: float | None = None, - resid: str | None = None, - re_: str | None = None, - reprefix: str | None = None, - rio_flag: bool = False, - show_options_flag: bool = False, - ss_type: float | None = None, - runner: Runner | None = None, -) -> V3dLmeOutputs: - """ - AFNI Group Analysis Program with Linear Mixed-Effects Modeling Approach. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output files. - model: Model formula describing the fixed effects. - data_table: Data table description. - bounds: Lower and upper bounds for outlier removal. - cio_flag: Use AFNI's C io functions (default) or R's io functions with\ - -Rio. - cor_str: Specify the correlation structure of the residuals. - cutoff: Specify the cutoff value for accuracy in logistic regression\ - analysis. - dbg_args_flag: Enable saving parameters for debugging. - jobs: Number of jobs for parallel computing. - glt_code: General linear test coding. - glt_label: Label for general linear test. - glf_label: Label for general linear F-test. - glf_code: General linear F-test coding. - icc_flag: Compute voxel-wise intra-class correlation. - iccb_flag: Compute voxel-wise intra-class correlation with Bayesian\ - approach. - log_lik_flag: Include voxel-wise log likelihood in the output. - logit_flag: Perform voxel-wise logistic modeling. - ml_flag: Use Maximum Likelihood estimation instead of REML. - qvars_centers: Centering values for quantitative variables. - qvars: Identify quantitative variables (or covariates). - raneff: Specify the random effects. - mask: Mask file for voxel processing. - num_glf: Number of general linear F-tests. - num_glt: Number of general linear t-tests. - resid: Prefix for residuals output file. - re_: List of variables whose random effects are saved in the output. - reprefix: Prefix for random effects output file. - rio_flag: Use R's io functions instead of AFNI's C io functions. - show_options_flag: List of allowed options. - ss_type: Specify the type for sums of squares in the F-statistics. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLmeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LME_METADATA) - cargs = [] - cargs.append("3dLME") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-model") - cargs.append(model) - cargs.append("-dataTable") - cargs.append(data_table) - cargs.append("-bounds") - if bounds is not None: - cargs.extend(map(str, bounds)) - cargs.append("-cio") - if cio_flag: - cargs.append("-cio") - cargs.append("-corStr") - if cor_str is not None: - cargs.append(cor_str) - cargs.append("-cutoff") - if cutoff is not None: - cargs.append(str(cutoff)) - cargs.append("-dbgArgs") - if dbg_args_flag: - cargs.append("-dbgArgs") - cargs.append("-jobs") - if jobs is not None: - cargs.append(str(jobs)) - cargs.append("-gltCode") - if glt_code is not None: - cargs.append(glt_code) - cargs.append("-gltLabel") - if glt_label is not None: - cargs.append(glt_label) - cargs.append("-glfLabel") - if glf_label is not None: - cargs.append(glf_label) - cargs.append("-glfCode") - if glf_code is not None: - cargs.append(glf_code) - cargs.append("-ICC") - if icc_flag: - cargs.append("-ICC") - cargs.append("-ICCb") - if iccb_flag: - cargs.append("-ICCb") - cargs.append("-logLik") - if log_lik_flag: - cargs.append("-logLik") - cargs.append("-LOGIT") - if logit_flag: - cargs.append("-LOGIT") - cargs.append("-ml") - if ml_flag: - cargs.append("-ML") - cargs.append("-qVarsCenters") - if qvars_centers is not None: - cargs.append(qvars_centers) - cargs.append("-qVars") - if qvars is not None: - cargs.append(qvars) - cargs.append("-ranEff") - if raneff is not None: - cargs.append(raneff) - cargs.append("-mask") - if mask is not None: - cargs.append(execution.input_file(mask)) - cargs.append("-num_glf") - if num_glf is not None: - cargs.append(str(num_glf)) - cargs.append("-num_glt") - if num_glt is not None: - cargs.append(str(num_glt)) - cargs.append("-resid") - if resid is not None: - cargs.append(resid) - cargs.append("-RE") - if re_ is not None: - cargs.append(re_) - cargs.append("-REprefix") - if reprefix is not None: - cargs.append(reprefix) - cargs.append("-RIO") - if rio_flag: - cargs.append("-Rio") - cargs.append("-show_allowed_options") - if show_options_flag: - cargs.append("-show_allowed_options") - cargs.append("-SS_type") - if ss_type is not None: - cargs.append(str(ss_type)) - ret = V3dLmeOutputs( - root=execution.output_file("."), - output_nifti=execution.output_file(prefix + ".nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLmeOutputs", - "V_3D_LME_METADATA", - "v_3d_lme", -] diff --git a/python/src/niwrap/afni/v_3d_lmer.py b/python/src/niwrap/afni/v_3d_lmer.py deleted file mode 100644 index 98e4f6851..000000000 --- a/python/src/niwrap/afni/v_3d_lmer.py +++ /dev/null @@ -1,190 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LMER_METADATA = Metadata( - id="13444732534ac79fb85190ab7da824160851b3be.boutiques", - name="3dLMEr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLmerOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lmer(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output file""" - residuals_file: OutputPathType | None - """Output residuals file""" - - -def v_3d_lmer( - data_table: InputPathType, - model: str, - prefix: str, - bound_lower: float | None = None, - bound_upper: float | None = None, - cio: bool = False, - debug_args: bool = False, - glf_code: str | None = None, - glt_code: str | None = None, - help_: bool = False, - input_file_column: str | None = None, - jobs: float | None = None, - mask: InputPathType | None = None, - qvar_centers: str | None = None, - qvars: str | None = None, - resid: str | None = None, - rio: bool = False, - show_options: bool = False, - ss_type: float | None = None, - trr: bool = False, - vvar_centers: str | None = None, - vvars: str | None = None, - runner: Runner | None = None, -) -> V3dLmerOutputs: - """ - Program for Voxelwise Linear Mixed-Effects (LME) Analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - data_table: List the data structure with a header as the first line. - model: Specify the model structure for all the variables. - prefix: Output file name. - bound_lower: Specify the lower and upper bounds for outlier removal. - bound_upper: Specify the lower and upper bounds for outlier removal. - cio: Use AFNI's C io functions. - debug_args: Enable R to save the parameters for debugging. - glf_code: Specify a general linear F-style (GLF) formulation. - glt_code: Specify the label and weights of interest in a general linear\ - t-style (GLT) formulation. - help_: Display the help message. - input_file_column: Specify the column name for input files of effect\ - estimate. - jobs: Number of jobs for parallel computing. - mask: Process voxels inside this mask only. - qvar_centers: Specify centering values for quantitative variables. - qvars: Identify quantitative variables (or covariates). - resid: Output file name for the residuals. - rio: Use R's io functions. - show_options: List of allowed options. - ss_type: Specify the type for sums of squares in the F-statistics. - trr: Perform test-retest reliability analysis. - vvar_centers: Specify centering values for voxel-wise covariates. - vvars: Identify voxel-wise covariates. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLmerOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LMER_METADATA) - cargs = [] - cargs.append("3dLMEr") - if bound_lower is not None: - cargs.append(str(bound_lower)) - if bound_upper is not None: - cargs.append(str(bound_upper)) - if cio: - cargs.append("-cio") - cargs.extend([ - "-dataTable", - execution.input_file(data_table) - ]) - if debug_args: - cargs.append("-dbgArgs") - if glf_code is not None: - cargs.extend([ - "-glfCode", - glf_code - ]) - if glt_code is not None: - cargs.extend([ - "-gltCode", - glt_code - ]) - if help_: - cargs.append("-help") - if input_file_column is not None: - cargs.extend([ - "-IF", - input_file_column - ]) - if jobs is not None: - cargs.extend([ - "-jobs", - str(jobs) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.extend([ - "-model", - model - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if qvar_centers is not None: - cargs.extend([ - "-qVarCenters", - qvar_centers - ]) - if qvars is not None: - cargs.extend([ - "-qVars", - qvars - ]) - if resid is not None: - cargs.extend([ - "-resid", - resid - ]) - if rio: - cargs.append("-Rio") - if show_options: - cargs.append("-show_allowed_options") - if ss_type is not None: - cargs.extend([ - "-SS_type", - str(ss_type) - ]) - if trr: - cargs.append("-TRR") - if vvar_centers is not None: - cargs.extend([ - "-vVarCenters", - vvar_centers - ]) - if vvars is not None: - cargs.extend([ - "-vVars", - vvars - ]) - ret = V3dLmerOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz"), - residuals_file=execution.output_file(resid + ".nii.gz") if (resid is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLmerOutputs", - "V_3D_LMER_METADATA", - "v_3d_lmer", -] diff --git a/python/src/niwrap/afni/v_3d_local_acf.py b/python/src/niwrap/afni/v_3d_local_acf.py deleted file mode 100644 index fd65afd31..000000000 --- a/python/src/niwrap/afni/v_3d_local_acf.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_ACF_METADATA = Metadata( - id="f028a3db36733d5d221d8a591e5ff6f090858574.boutiques", - name="3dLocalACF", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalAcfOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_acf(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset with ACF estimates""" - - -def v_3d_local_acf( - prefix: str, - input_file: InputPathType, - neighborhood: str | None = None, - mask_file: InputPathType | None = None, - auto_mask: bool = False, - runner: Runner | None = None, -) -> V3dLocalAcfOutputs: - """ - Estimate the spatial AutoCorrelation Function (ACF) locally in a neighborhood - around each voxel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for output dataset. - input_file: Input time series dataset. - neighborhood: Neighborhood specification (e.g., SPHERE(25)). - mask_file: Dataset to mask the analysis. - auto_mask: Automatically generate brain mask from input dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalAcfOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_ACF_METADATA) - cargs = [] - cargs.append("3dLocalACF") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append(execution.input_file(input_file)) - if neighborhood is not None: - cargs.extend([ - "-nbhd", - neighborhood - ]) - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - if auto_mask: - cargs.append("-automask") - ret = V3dLocalAcfOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalAcfOutputs", - "V_3D_LOCAL_ACF_METADATA", - "v_3d_local_acf", -] diff --git a/python/src/niwrap/afni/v_3d_local_bistat.py b/python/src/niwrap/afni/v_3d_local_bistat.py deleted file mode 100644 index 185bfe2ab..000000000 --- a/python/src/niwrap/afni/v_3d_local_bistat.py +++ /dev/null @@ -1,144 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_BISTAT_METADATA = Metadata( - id="5b350e2de3b46f339f4193bdf88828d0f13c5833.boutiques", - name="3dLocalBistat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalBistatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_bistat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType - """Output dataset header for AFNI format""" - output_brik: OutputPathType - """Output dataset BRIK for AFNI format""" - - -def v_3d_local_bistat( - nbhd: str, - stats: list[str], - prefix: str, - dataset1: InputPathType, - dataset2: InputPathType, - mask: InputPathType | None = None, - automask: bool = False, - weight: InputPathType | None = None, - histpow: float | None = None, - histbin: float | None = None, - hclip1: list[str] | None = None, - hclip2: list[str] | None = None, - runner: Runner | None = None, -) -> V3dLocalBistatOutputs: - """ - Compute statistics between 2 datasets at each voxel based on a local - neighborhood. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - nbhd: Specifies the neighborhood around each voxel for statistics\ - calculation. Types include: SPHERE(r), RECT(a,b,c), RHDD(r), TOHD(r). - stats: Statistic to compute in the region around each voxel. Multiple\ - options allowed. Includes: pearson, spearman, quadrant, mutinfo,\ - normuti, jointent, hellinger, crU, crM, crA, L2slope, L1slope, num,\ - ALL. - prefix: Prefix of the output dataset. - dataset1: The first input dataset (e.g. data1.nii). - dataset2: The second input dataset (e.g. data2.nii). - mask: Read in a dataset to use as a mask. Non-zero voxels define the\ - mask region. - automask: Compute the mask as in program 3dAutomask. Mutually exclusive\ - with -mask. - weight: Use dataset as a weight (applies to pearson). - histpow: Sets the exponent for the number of bins in the histogram used\ - for Hellinger, Mutual Information, and Correlation Ratio statistics. - histbin: Sets the number of bins directly in the histogram used for\ - Hellinger, Mutual Information, and Correlation Ratio statistics. - hclip1: Clip dataset1 to lie between specified values. - hclip2: Clip dataset2 to lie between specified values. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalBistatOutputs`). - """ - if hclip1 is not None and (len(hclip1) != 2): - raise ValueError(f"Length of 'hclip1' must be 2 but was {len(hclip1)}") - if hclip2 is not None and (len(hclip2) != 2): - raise ValueError(f"Length of 'hclip2' must be 2 but was {len(hclip2)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_BISTAT_METADATA) - cargs = [] - cargs.append("3dLocalBistat") - cargs.extend([ - "-nbhd", - nbhd - ]) - cargs.extend([ - "-stat", - *stats - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - if weight is not None: - cargs.extend([ - "-weight", - execution.input_file(weight) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if histpow is not None: - cargs.extend([ - "-histpow", - str(histpow) - ]) - if histbin is not None: - cargs.extend([ - "-histbin", - str(histbin) - ]) - if hclip1 is not None: - cargs.extend([ - "-hclip1", - *hclip1 - ]) - if hclip2 is not None: - cargs.extend([ - "-hclip2", - *hclip2 - ]) - cargs.append(execution.input_file(dataset1)) - cargs.append(execution.input_file(dataset2)) - ret = V3dLocalBistatOutputs( - root=execution.output_file("."), - output_head=execution.output_file(prefix + "+orig.HEAD"), - output_brik=execution.output_file(prefix + "+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalBistatOutputs", - "V_3D_LOCAL_BISTAT_METADATA", - "v_3d_local_bistat", -] diff --git a/python/src/niwrap/afni/v_3d_local_histog.py b/python/src/niwrap/afni/v_3d_local_histog.py deleted file mode 100644 index 84e7169a6..000000000 --- a/python/src/niwrap/afni/v_3d_local_histog.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_HISTOG_METADATA = Metadata( - id="99e523db7c9f0a8693eaccdee82264a6659dc278.boutiques", - name="3dLocalHistog", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalHistogOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_histog(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset_head: OutputPathType - """The output dataset with the specified prefix""" - output_dataset_brik: OutputPathType - """The output dataset with the specified prefix""" - histogram_file: OutputPathType | None - """The overall histogram saved into the specified file""" - - -def v_3d_local_histog( - prefix: str, - input_datasets: list[InputPathType], - nbhd_option: str | None = None, - hsave: str | None = None, - lab_file: InputPathType | None = None, - exclude: list[str] | None = None, - mincount: float | None = None, - runner: Runner | None = None, -) -> V3dLocalHistogOutputs: - """ - This program computes a local histogram at each voxel in the input datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Use string 'ppp' as the prefix for the output dataset. - input_datasets: Input dataset(s) for the 3dLocalHistog tool. - nbhd_option: Defines the region around each voxel to be used for the\ - statistics calculation. Available formats: 'SPHERE(r)', 'RECT(a,b,c)',\ - 'RHDD(a)', 'TOHD(a)'. - hsave: Save the overall histogram into file 'sss'. This file will have\ - 2 columns: value and count. - lab_file: Use file 'LL' as a label file. - exclude: Exclude values from 'a' to 'b' from the counting. This option\ - can be used more than once. - mincount: Exclude values which appear in the overall histogram fewer\ - than 'mm' times. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalHistogOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_HISTOG_METADATA) - cargs = [] - cargs.append("3dLocalHistog") - if nbhd_option is not None: - cargs.extend([ - "-nbhd", - nbhd_option - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if hsave is not None: - cargs.extend([ - "-hsave", - hsave - ]) - if lab_file is not None: - cargs.extend([ - "-lab_file", - execution.input_file(lab_file) - ]) - if exclude is not None: - cargs.extend([ - "-exclude", - *exclude - ]) - if mincount is not None: - cargs.extend([ - "-mincount", - str(mincount) - ]) - cargs.extend([execution.input_file(f) for f in input_datasets]) - ret = V3dLocalHistogOutputs( - root=execution.output_file("."), - output_dataset_head=execution.output_file(prefix + "+orig.HEAD"), - output_dataset_brik=execution.output_file(prefix + "+orig.BRIK"), - histogram_file=execution.output_file(hsave) if (hsave is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalHistogOutputs", - "V_3D_LOCAL_HISTOG_METADATA", - "v_3d_local_histog", -] diff --git a/python/src/niwrap/afni/v_3d_local_pv.py b/python/src/niwrap/afni/v_3d_local_pv.py deleted file mode 100644 index 8e0f49014..000000000 --- a/python/src/niwrap/afni/v_3d_local_pv.py +++ /dev/null @@ -1,137 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_PV_METADATA = Metadata( - id="54b08b1e61d1a55edf0eba3e25c0aa1254ece60a.boutiques", - name="3dLocalPV", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalPvOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_pv(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - svd_vector_result: OutputPathType | None - """SVD vector result dataset""" - second_principal_vector: OutputPathType | None - """Second principal vector dataset""" - singular_value: OutputPathType | None - """Singular value at each voxel dataset""" - - -def v_3d_local_pv( - input_dataset: InputPathType, - mask: InputPathType | None = None, - automask: bool = False, - prefix: str | None = None, - prefix2: str | None = None, - evprefix: str | None = None, - neighborhood: str | None = None, - despike: bool = False, - polort: float | None = None, - vnorm: bool = False, - vproj: str | None = None, - runner: Runner | None = None, -) -> V3dLocalPvOutputs: - """ - Computes the Singular Value Decomposition (SVD) of the time series from a - neighborhood of each voxel in a 3D+time dataset, which serves as a smoothing - method for the dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input time series dataset. - mask: Restrict operations to this mask. - automask: Create a mask from the time series dataset. - prefix: Save SVD vector result into this new dataset [default =\ - 'LocalPV']. - prefix2: Save second principal vector into this new dataset [default =\ - don't save it]. - evprefix: Save singular value at each voxel into this dataset [default\ - = don't save]. - neighborhood: Neighborhood definition (e.g., 'SPHERE(5)', 'TOHD(7)',\ - etc.). - despike: Remove time series spikes from input dataset. - polort: Detrending. - vnorm: Normalize data vectors [strongly recommended]. - vproj: Project central data time series onto local SVD vector; if\ - followed by '2', then the central data time series will be projected on\ - the 2-dimensional subspace spanned by the first 2 principal SVD\ - vectors. [default: just output principal singular vector]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalPvOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_PV_METADATA) - cargs = [] - cargs.append("3dLocalPV") - cargs.append(execution.input_file(input_dataset)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if prefix2 is not None: - cargs.extend([ - "-prefix2", - prefix2 - ]) - if evprefix is not None: - cargs.extend([ - "-evprefix", - evprefix - ]) - if neighborhood is not None: - cargs.extend([ - "-nbhd", - neighborhood - ]) - if despike: - cargs.append("-despike") - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if vnorm: - cargs.append("-vnorm") - if vproj is not None: - cargs.extend([ - "-vproj", - vproj - ]) - ret = V3dLocalPvOutputs( - root=execution.output_file("."), - svd_vector_result=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - second_principal_vector=execution.output_file(prefix2 + ".nii.gz") if (prefix2 is not None) else None, - singular_value=execution.output_file(evprefix + ".nii.gz") if (evprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalPvOutputs", - "V_3D_LOCAL_PV_METADATA", - "v_3d_local_pv", -] diff --git a/python/src/niwrap/afni/v_3d_local_svd.py b/python/src/niwrap/afni/v_3d_local_svd.py deleted file mode 100644 index cb732deb0..000000000 --- a/python/src/niwrap/afni/v_3d_local_svd.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_SVD_METADATA = Metadata( - id="aa9242eacfb8563948c633af4cce28ff22487e6c.boutiques", - name="3dLocalSVD", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalSvdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_svd(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_local_svd( - input_file: InputPathType, - output_file: str, - auto_mask: bool = False, - mask_file: InputPathType | None = None, - nbhd: str | None = None, - polort: str | None = None, - vnorm: bool = False, - vproj: float | None = None, - runner: Runner | None = None, -) -> V3dLocalSvdOutputs: - """ - Computes the SVD of time series from a neighborhood of each voxel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input time series dataset file. - output_file: Prefix for the output SVD vector result dataset file. - auto_mask: Create a mask from time series dataset. - mask_file: Restrict operations to this mask dataset. - nbhd: Neighborhood for SVD calculation, e.g., 'SPHERE(5)'. - polort: Detrending option, ['+' means to add trend back]. - vnorm: Normalize data vectors [strongly recommended]. - vproj: Project central data time series onto local SVD subspace of\ - dimension 'ndim'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalSvdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_SVD_METADATA) - cargs = [] - cargs.append("3dLocalSVD") - if auto_mask: - cargs.append("-automask") - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - output_file - ]) - if nbhd is not None: - cargs.extend([ - "-nbhd", - nbhd - ]) - if polort is not None: - cargs.extend([ - "-polort", - polort - ]) - if vnorm: - cargs.append("-vnorm") - if vproj is not None: - cargs.extend([ - "-vproj", - str(vproj) - ]) - ret = V3dLocalSvdOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalSvdOutputs", - "V_3D_LOCAL_SVD_METADATA", - "v_3d_local_svd", -] diff --git a/python/src/niwrap/afni/v_3d_local_unifize.py b/python/src/niwrap/afni/v_3d_local_unifize.py deleted file mode 100644 index b1d22d112..000000000 --- a/python/src/niwrap/afni/v_3d_local_unifize.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCAL_UNIFIZE_METADATA = Metadata( - id="15f1fc4af844d2f3848e6e3527f1534179ded986.boutiques", - name="3dLocalUnifize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalUnifizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_local_unifize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset file""" - - -def v_3d_local_unifize( - input_: InputPathType, - output: str, - working_dir: str | None = None, - echo: bool = False, - no_clean: bool = False, - local_rad: float | None = None, - local_perc: float | None = None, - local_mask: str | None = None, - filter_thr: float | None = None, - runner: Runner | None = None, -) -> V3dLocalUnifizeOutputs: - """ - This program generates a 'unifized' output volume by estimating the median in - the local neighborhood of each voxel and using that to scale each voxel's - brightness. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - output: Output dataset name, including path. - working_dir: Name of temporary working directory (def:\ - __wdir_LocalUni_, plus a random alphanumeric str). - echo: Run this program very verbosely (default: false). - no_clean: Do not remove the working directory (default: remove it). - local_rad: The spherical neighborhood's radius for the 3dLocalStat step\ - (default: -3). - local_perc: The percentile used in the 3dLocalStat step, generating the\ - scaling volume (default: 50). - local_mask: Provide the masking option for the 3dLocalStat step; to\ - remove any masking, put 'None' as the option value (default:\ - "-automask"). - filter_thr: Ceiling on values in the final, scaled dataset; values <=0\ - turn off this final filtering (default: 1.5). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalUnifizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCAL_UNIFIZE_METADATA) - cargs = [] - cargs.append("3dLocalUnifize") - cargs.append(execution.input_file(input_)) - cargs.extend([ - "-prefix", - output - ]) - if working_dir is not None: - cargs.extend([ - "-wdir_name", - working_dir - ]) - if echo: - cargs.append("-echo") - if no_clean: - cargs.append("-no_clean") - if local_rad is not None: - cargs.extend([ - "-local_rad", - str(local_rad) - ]) - if local_perc is not None: - cargs.extend([ - "-local_perc", - str(local_perc) - ]) - if local_mask is not None: - cargs.extend([ - "-local_mask", - local_mask - ]) - if filter_thr is not None: - cargs.extend([ - "-filter_thr", - str(filter_thr) - ]) - ret = V3dLocalUnifizeOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalUnifizeOutputs", - "V_3D_LOCAL_UNIFIZE_METADATA", - "v_3d_local_unifize", -] diff --git a/python/src/niwrap/afni/v_3d_localstat.py b/python/src/niwrap/afni/v_3d_localstat.py deleted file mode 100644 index 611ccc129..000000000 --- a/python/src/niwrap/afni/v_3d_localstat.py +++ /dev/null @@ -1,191 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOCALSTAT_METADATA = Metadata( - id="f927c9d4ad8b0ef0fa566fe0b9648789d0b3eb44.boutiques", - name="3dLocalstat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLocalstatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_localstat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Output dataset""" - - -def v_3d_localstat( - dataset: InputPathType, - nbhd: str, - stat_: list[str] | None = None, - mask: InputPathType | None = None, - automask: bool = False, - use_nonmask: bool = False, - prefix: str | None = None, - datum: str | None = None, - label_ext: str | None = None, - reduce_grid: list[float] | None = None, - reduce_restore_grid: list[float] | None = None, - reduce_max_vox: float | None = None, - grid_rmode: str | None = None, - quiet: bool = False, - verbose: bool = False, - proceed_small_n: bool = False, - fillvalue: float | None = None, - unfillvalue: float | None = None, - maskvalue: float | None = None, - maskvalue2: float | None = None, - runner: Runner | None = None, -) -> V3dLocalstatOutputs: - """ - This program computes statistics at each voxel, based on a local neighborhood of - that voxel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - nbhd: The region around each voxel that will be extracted for the\ - statistics calculation. - stat_: Compute the specified statistic on the values extracted from the\ - neighborhood. - mask: Read in dataset 'mset' and use the nonzero voxels therein as a\ - mask. - automask: Compute the mask as in program 3dAutomask (mutually exclusive\ - with -mask). - use_nonmask: Compute local statistics from all voxels in the\ - neighborhood that are in the mask, even if the central voxel is not in\ - the mask. - prefix: Use the given string as the prefix for the output dataset. - datum: Coerce the output data to be stored as the given type (byte,\ - short, float). - label_ext: Append given label to each sub-brick label. - reduce_grid: Compute output on a grid that is reduced by the given\ - factor in X, Y, and Z directions of the input dataset. - reduce_restore_grid: Resample the output back to input grid after\ - reducing the grid. - reduce_max_vox: Automatically set Rx Ry Rz so that the computation grid\ - is at a resolution of nbhd/MAX_VOX voxels. - grid_rmode: Interpolant to use when resampling the output with\ - reduce_restore_grid option. - quiet: Stop the highly informative progress reports. - verbose: A little more verbose output. - proceed_small_n: Do not crash if neighborhood is too small for certain\ - estimates. - fillvalue: Value used for filled statistic, default=1. - unfillvalue: Value used for unfilled statistic, default=1. - maskvalue: Value searched for with has_mask option. - maskvalue2: Alternate value for has_mask2 option. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLocalstatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOCALSTAT_METADATA) - cargs = [] - cargs.append("3dLocalstat") - cargs.append(execution.input_file(dataset)) - cargs.extend([ - "-nbhd", - nbhd - ]) - if stat_ is not None: - cargs.extend([ - "-stat", - *stat_ - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - if use_nonmask: - cargs.append("-use_nonmask") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if label_ext is not None: - cargs.extend([ - "-label_ext", - label_ext - ]) - if reduce_grid is not None: - cargs.extend([ - "-reduce_grid", - *map(str, reduce_grid) - ]) - if reduce_restore_grid is not None: - cargs.extend([ - "-reduce_restore_grid", - *map(str, reduce_restore_grid) - ]) - if reduce_max_vox is not None: - cargs.extend([ - "-reduce_max_vox", - str(reduce_max_vox) - ]) - if grid_rmode is not None: - cargs.extend([ - "-grid_rmode", - grid_rmode - ]) - if quiet: - cargs.append("-quiet") - if verbose: - cargs.append("-verb") - if proceed_small_n: - cargs.append("-proceed_small_N") - if fillvalue is not None: - cargs.extend([ - "-fillvalue", - str(fillvalue) - ]) - if unfillvalue is not None: - cargs.extend([ - "-unfillvalue", - str(unfillvalue) - ]) - if maskvalue is not None: - cargs.extend([ - "-maskvalue", - str(maskvalue) - ]) - if maskvalue2 is not None: - cargs.extend([ - "-maskvalue2", - str(maskvalue2) - ]) - ret = V3dLocalstatOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLocalstatOutputs", - "V_3D_LOCALSTAT_METADATA", - "v_3d_localstat", -] diff --git a/python/src/niwrap/afni/v_3d_lomb_scargle.py b/python/src/niwrap/afni/v_3d_lomb_scargle.py deleted file mode 100644 index 1c5cdd6d8..000000000 --- a/python/src/niwrap/afni/v_3d_lomb_scargle.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LOMB_SCARGLE_METADATA = Metadata( - id="4a8cb9c44f40d39fa20b61bfcaa0f24045676f26.boutiques", - name="3dLombScargle", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLombScargleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lomb_scargle(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - time_points: OutputPathType - """1D file of the sampled time points (in units of seconds) of the analyzed - data set""" - frequency_points: OutputPathType - """1D file of the frequency sample points (in units of 1/seconds) of the - output periodogram/spectrum data set""" - amplitude_spectrum: OutputPathType - """Volumetric data set containing a LS-derived amplitude spectrum""" - power_spectrum: OutputPathType - """Volumetric data set containing a LS-derived power spectrum""" - - -def v_3d_lomb_scargle( - prefix: str, - inset: InputPathType, - censor_1d: InputPathType | None = None, - censor_string: str | None = None, - mask_file: InputPathType | None = None, - out_pow_spec: bool = False, - nyquist_multiplier: int | None = None, - nifti: bool = False, - runner: Runner | None = None, -) -> V3dLombScargleOutputs: - """ - Make a periodogram or amplitude-spectrum of a time series that has a - non-constant sampling rate. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output prefix name for data volume, time point 1D file, and\ - frequency 1D file. - inset: Time series of volumes, a 4D volumetric data set. - censor_1d: Single row or column of 1s (keep) and 0s (censored)\ - describing which volumes of FILE are kept in the sampling and which are\ - censored out, respectively. The length of the list of numbers must be\ - of the same length as the number of volumes in FILE. If not entered,\ - then the program will look for subbricks of all-zeros and assume those\ - are censored out. - censor_string: AFNI-style selector string of volumes to *keep* in the\ - analysis. Such as: '[0..4,7,10..$]'. - mask_file: Optional, mask of volume to analyze; additionally, any voxel\ - with uniformly zero values across time will produce a zero-spectrum. - out_pow_spec: Switch to output the amplitude spectrum of the freqs\ - instead of the periodogram. In the formulation used here, for a time\ - series of length N, the power spectral value S is related to the\ - amplitude value X as: S = (X)**2. (Without this opt, default output is\ - amplitude spectrum.). - nyquist_multiplier: L-S periodograms can include frequencies above what\ - would typically be considered Nyquist. By default, the maximum\ - frequency will be what f_N *would* have been if no censoring of points\ - had occurred. Acceptable values are >0. (This sets the 'hifac'\ - parameter). - nifti: Switch to output *.nii.gz volume file (default format is\ - BRIK/HEAD). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLombScargleOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LOMB_SCARGLE_METADATA) - cargs = [] - cargs.append("3dLombScargle") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-inset") - cargs.append(execution.input_file(inset)) - if censor_1d is not None: - cargs.extend([ - "-censor_1D", - execution.input_file(censor_1d) - ]) - if censor_string is not None: - cargs.extend([ - "-censor_str", - censor_string - ]) - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - if out_pow_spec: - cargs.append("-out_pow_spec") - if nyquist_multiplier is not None: - cargs.extend([ - "-nyq_mult", - str(nyquist_multiplier) - ]) - if nifti: - cargs.append("-nifti") - ret = V3dLombScargleOutputs( - root=execution.output_file("."), - time_points=execution.output_file(prefix + "_time.1D"), - frequency_points=execution.output_file(prefix + "_freq.1D"), - amplitude_spectrum=execution.output_file(prefix + "_amp+orig"), - power_spectrum=execution.output_file(prefix + "_pow+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLombScargleOutputs", - "V_3D_LOMB_SCARGLE_METADATA", - "v_3d_lomb_scargle", -] diff --git a/python/src/niwrap/afni/v_3d_lrflip.py b/python/src/niwrap/afni/v_3d_lrflip.py deleted file mode 100644 index d115ce9e6..000000000 --- a/python/src/niwrap/afni/v_3d_lrflip.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LRFLIP_METADATA = Metadata( - id="da9ae489ee4907f481f368db8441cc0a2eb8cfa1.boutiques", - name="3dLRflip", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLrflipOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lrflip(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - flipped_output: OutputPathType | None - """Output dataset after flipping""" - - -def v_3d_lrflip( - datasets: list[InputPathType], - flip_z: bool = False, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> V3dLrflipOutputs: - """ - Flips the rows of a dataset along one of the three axes to correct dataset - direction labeling errors. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Datasets to flip. - flip_z: Flip about the 3rd direction. - output_prefix: Prefix to use for output. If multiple datasets are\ - input, the program will choose a prefix for each output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLrflipOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LRFLIP_METADATA) - cargs = [] - cargs.append("3dLRflip") - if flip_z: - cargs.append("-Z") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - cargs.extend([execution.input_file(f) for f in datasets]) - ret = V3dLrflipOutputs( - root=execution.output_file("."), - flipped_output=execution.output_file(output_prefix + "*") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLrflipOutputs", - "V_3D_LRFLIP_METADATA", - "v_3d_lrflip", -] diff --git a/python/src/niwrap/afni/v_3d_lss.py b/python/src/niwrap/afni/v_3d_lss.py deleted file mode 100644 index afd44e78d..000000000 --- a/python/src/niwrap/afni/v_3d_lss.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_LSS_METADATA = Metadata( - id="d9d964f3581d7546843bb8930c57337b07b0140b.boutiques", - name="3dLSS", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dLssOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_lss(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output dataset containing the LSS estimates of the beta weights for the - '-stim_times_IM' stimuli.""" - save1_d_output: OutputPathType - """Estimator vectors saved in a 1D formatted file.""" - - -def v_3d_lss( - runner: Runner | None = None, -) -> V3dLssOutputs: - """ - Least-Squares-Sum (LSS) estimation tool from a -stim_times_IM matrix for - multivoxel pattern classification analyses. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dLssOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_LSS_METADATA) - cargs = [] - cargs.append("3dLSS") - cargs.append("[OPTIONS]") - ret = V3dLssOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file("LSSout+orig.HEAD"), - save1_d_output=execution.output_file("[QQQ]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dLssOutputs", - "V_3D_LSS_METADATA", - "v_3d_lss", -] diff --git a/python/src/niwrap/afni/v_3d_mann_whitney.py b/python/src/niwrap/afni/v_3d_mann_whitney.py deleted file mode 100644 index 00bd2cff7..000000000 --- a/python/src/niwrap/afni/v_3d_mann_whitney.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MANN_WHITNEY_METADATA = Metadata( - id="f9a86facbfabfbc66d0561e25e3ef982299809ea.boutiques", - name="3dMannWhitney", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMannWhitneyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mann_whitney(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Output files for the estimated population delta and Wilcoxon-Mann-Whitney - statistics.""" - - -def v_3d_mann_whitney( - dset1_x: list[str], - dset2_y: list[str], - output_prefix: str, - workmem: int | None = None, - voxel_num: int | None = None, - runner: Runner | None = None, -) -> V3dMannWhitneyOutputs: - """ - Performs nonparametric Mann-Whitney two-sample test. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset1_x: Data set for X observations. Must specify 1 and only 1\ - sub-brick. - dset2_y: Data set for Y observations. Must specify 1 and only 1\ - sub-brick. - output_prefix: Estimated population delta and Wilcoxon-Mann-Whitney\ - statistics written to file. - workmem: Number of megabytes of RAM to use for statistical workspace. - voxel_num: Screen output for voxel # num. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMannWhitneyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MANN_WHITNEY_METADATA) - cargs = [] - cargs.append("3dMannWhitney") - cargs.extend([ - "-dset 1", - *dset1_x - ]) - cargs.extend([ - "-dset 2", - *dset2_y - ]) - cargs.extend([ - "-out", - output_prefix - ]) - if workmem is not None: - cargs.extend([ - "-workmem", - str(workmem) - ]) - if voxel_num is not None: - cargs.extend([ - "-voxel", - str(voxel_num) - ]) - ret = V3dMannWhitneyOutputs( - root=execution.output_file("."), - output_files=execution.output_file(output_prefix + "*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMannWhitneyOutputs", - "V_3D_MANN_WHITNEY_METADATA", - "v_3d_mann_whitney", -] diff --git a/python/src/niwrap/afni/v_3d_mask_to_ascii.py b/python/src/niwrap/afni/v_3d_mask_to_ascii.py deleted file mode 100644 index 3c881b9e0..000000000 --- a/python/src/niwrap/afni/v_3d_mask_to_ascii.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MASK_TO_ASCII_METADATA = Metadata( - id="dfc4f64758548d800895c3bbc28a5d63199e3174.boutiques", - name="3dMaskToASCII", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMaskToAsciiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mask_to_ascii(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outputfile: OutputPathType - """Output file where ASCII string mask or binary mask will be written.""" - - -def v_3d_mask_to_ascii( - dataset: InputPathType, - tobin_flag: bool = False, - runner: Runner | None = None, -) -> V3dMaskToAsciiOutputs: - """ - Converts a byte-valued 0/1 dataset into an ASCII string, or vice versa. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset (e.g. mask.nii.gz). - tobin_flag: Read ASCII mask, expand it to byte-valued dataset, and\ - write to stdout. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMaskToAsciiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MASK_TO_ASCII_METADATA) - cargs = [] - cargs.append("3dMaskToASCII") - if tobin_flag: - cargs.append("-tobin") - cargs.append(execution.input_file(dataset)) - cargs.append(">") - cargs.append("[OUTPUTFILE]") - ret = V3dMaskToAsciiOutputs( - root=execution.output_file("."), - outputfile=execution.output_file("[OUTPUTFILE]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMaskToAsciiOutputs", - "V_3D_MASK_TO_ASCII_METADATA", - "v_3d_mask_to_ascii", -] diff --git a/python/src/niwrap/afni/v_3d_match.py b/python/src/niwrap/afni/v_3d_match.py deleted file mode 100644 index 9d4767067..000000000 --- a/python/src/niwrap/afni/v_3d_match.py +++ /dev/null @@ -1,133 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MATCH_METADATA = Metadata( - id="5e79a849f1f76bbe598dfba4e01f90d83d62deb0.boutiques", - name="3dMatch", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMatchOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_match(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - ref_brik: OutputPathType - """AFNI BRIK file with the same number of subbricks as the refset file, with - highest weighted correlation.""" - ref_coeff_vals: OutputPathType - """Text file recording original indices and coefficients.""" - in_brik: OutputPathType - """AFNI BRIK file with the same number of subbricks as the inset file, with - highest weighted correlation.""" - in_coeff_vals: OutputPathType - """Text file recording original indices and coefficients.""" - - -def v_3d_match( - inset: InputPathType, - refset: InputPathType, - prefix: str, - mask: InputPathType | None = None, - in_min: float | None = None, - in_max: float | None = None, - ref_min: float | None = None, - ref_max: float | None = None, - only_dice_thr: bool = False, - runner: Runner | None = None, -) -> V3dMatchOutputs: - """ - Find similar subbricks and rearrange order to ease comparison. Part of FATCAT in - AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: File with M subbricks of data to match against another file. - refset: File with N subbricks, serving as a reference for INPUT_FILE. - prefix: Prefix for output name for BRIK/HEAD files and *_coeff.vals\ - text files. - mask: A mask of regions to include in the correlation of datasets. - in_min: Threshold below which values in INPUT_FILE will be zeroed\ - during analysis. - in_max: Threshold above which values in INPUT_FILE will be zeroed\ - during analysis. - ref_min: Threshold below which values in REF_FILE will be zeroed during\ - analysis. - ref_max: Threshold above which values in REF_FILE will be zeroed during\ - analysis. - only_dice_thr: Apply thresholding only during Dice evaluation, not\ - during spatial correlation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMatchOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MATCH_METADATA) - cargs = [] - cargs.append("3dMatch") - cargs.extend([ - "-inset", - execution.input_file(inset) - ]) - cargs.extend([ - "-refset", - execution.input_file(refset) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if in_min is not None: - cargs.extend([ - "-in_min", - str(in_min) - ]) - if in_max is not None: - cargs.extend([ - "-in_max", - str(in_max) - ]) - if ref_min is not None: - cargs.extend([ - "-ref_min", - str(ref_min) - ]) - if ref_max is not None: - cargs.extend([ - "-ref_max", - str(ref_max) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if only_dice_thr: - cargs.append("-only_dice_thr") - ret = V3dMatchOutputs( - root=execution.output_file("."), - ref_brik=execution.output_file(prefix + "_REF+orig.BRIK"), - ref_coeff_vals=execution.output_file(prefix + "_REF_coeff.vals"), - in_brik=execution.output_file(prefix + "_IN+orig.BRIK"), - in_coeff_vals=execution.output_file(prefix + "_IN_coeff.vals"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMatchOutputs", - "V_3D_MATCH_METADATA", - "v_3d_match", -] diff --git a/python/src/niwrap/afni/v_3d_mean.py b/python/src/niwrap/afni/v_3d_mean.py deleted file mode 100644 index b74f353cc..000000000 --- a/python/src/niwrap/afni/v_3d_mean.py +++ /dev/null @@ -1,149 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MEAN_METADATA = Metadata( - id="80356df561331ccb8b8dcf4fa5be1f9056ff0d89.boutiques", - name="3dMean", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMeanOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mean(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output dataset""" - - -def v_3d_mean( - input_files: list[InputPathType], - verbose: bool = False, - prefix: str | None = None, - datum: str | None = None, - fscale: bool = False, - gscale: bool = False, - nscale: bool = False, - non_zero: bool = False, - stdev: bool = False, - sqr: bool = False, - sum_: bool = False, - count: bool = False, - max_: bool = False, - min_: bool = False, - absmax: bool = False, - signed_absmax: bool = False, - mask_inter: bool = False, - mask_union: bool = False, - weightset: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dMeanOutputs: - """ - Takes the voxel-by-voxel mean of all input datasets; designed to be faster than - 3dcalc. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets. - verbose: Print out some information along the way. - prefix: Sets the prefix of the output dataset. - datum: Sets the datum of the output dataset. - fscale: Force scaling of the output to the maximum integer range. - gscale: Force scaling of the output to the maximum integer range, with\ - uniform scaling factor for each sub-brick. - nscale: Don't do any scaling on output to byte or short datasets. Only\ - use if you want the output dataset to be integer-valued. - non_zero: Use only non-zero values for calculation of mean, min, max,\ - sum, squares. - stdev: Calculate the standard deviation, sqrt(variance), instead of the\ - mean (cannot be used with -sqr, -sum or -non_zero). - sqr: Average the squares, instead of the values. - sum_: Just take the sum (don't divide by number of datasets). - count: Compute only the count of non-zero voxels. - max_: Find the maximum at each voxel. - min_: Find the minimum at each voxel. - absmax: Find maximum absolute value at each voxel. - signed_absmax: Find extremes with maximum absolute value but preserve\ - sign. - mask_inter: Create a simple intersection mask. - mask_union: Create a simple union mask. - weightset: Sum of N dsets will be weighted by N volume WSET. This\ - weight dataset must be of type float. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMeanOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MEAN_METADATA) - cargs = [] - cargs.append("3dMean") - cargs.extend([execution.input_file(f) for f in input_files]) - if verbose: - cargs.append("-verbose") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if fscale: - cargs.append("-fscale") - if gscale: - cargs.append("-gscale") - if nscale: - cargs.append("-nscale") - if non_zero: - cargs.append("-non_zero") - if stdev: - cargs.append("-sd") - if sqr: - cargs.append("-sqr") - if sum_: - cargs.append("-sum") - if count: - cargs.append("-count") - if max_: - cargs.append("-max") - if min_: - cargs.append("-min") - if absmax: - cargs.append("-absmax") - if signed_absmax: - cargs.append("-signed_absmax") - if mask_inter: - cargs.append("-mask_inter") - if mask_union: - cargs.append("-mask_union") - if weightset is not None: - cargs.extend([ - "-weightset", - execution.input_file(weightset) - ]) - ret = V3dMeanOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + "<+optional_extension>") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMeanOutputs", - "V_3D_MEAN_METADATA", - "v_3d_mean", -] diff --git a/python/src/niwrap/afni/v_3d_median_filter.py b/python/src/niwrap/afni/v_3d_median_filter.py deleted file mode 100644 index aa8bdda26..000000000 --- a/python/src/niwrap/afni/v_3d_median_filter.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MEDIAN_FILTER_METADATA = Metadata( - id="e4ff1f00010a20a209cf31d2f6355a6142d17c25.boutiques", - name="3dMedianFilter", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMedianFilterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_median_filter(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType | None - """Output dataset is stored in float format.""" - output_head: OutputPathType | None - """Output dataset header file.""" - - -def v_3d_median_filter( - dataset: InputPathType, - irad: float | None = None, - iter_: float | None = None, - verbose: bool = False, - prefix: str | None = None, - automask: bool = False, - runner: Runner | None = None, -) -> V3dMedianFilterOutputs: - """ - Computes the median in a spherical neighborhood around each point in the input - to produce the output. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - irad: Radius in voxels of spherical regions. - iter_: Iterate 'n' times [default=1]. - verbose: Be verbose during run. - prefix: Use 'pp' for prefix of output dataset. - automask: Create a mask (a la 3dAutomask). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMedianFilterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MEDIAN_FILTER_METADATA) - cargs = [] - cargs.append("3dMedianFilter") - if irad is not None: - cargs.extend([ - "-irad", - str(irad) - ]) - if iter_ is not None: - cargs.extend([ - "-iter", - str(iter_) - ]) - if verbose: - cargs.append("-verb") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if automask: - cargs.append("-automask") - cargs.append(execution.input_file(dataset)) - ret = V3dMedianFilterOutputs( - root=execution.output_file("."), - output_brik=execution.output_file(prefix + "+tlrc.BRIK") if (prefix is not None) else None, - output_head=execution.output_file(prefix + "+tlrc.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMedianFilterOutputs", - "V_3D_MEDIAN_FILTER_METADATA", - "v_3d_median_filter", -] diff --git a/python/src/niwrap/afni/v_3d_mema.py b/python/src/niwrap/afni/v_3d_mema.py deleted file mode 100644 index acbe15ada..000000000 --- a/python/src/niwrap/afni/v_3d_mema.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MEMA_METADATA = Metadata( - id="ec08101954b2600252127fccf6a38e224829a161.boutiques", - name="3dMEMA", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMemaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mema(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output file from the analysis""" - - -def v_3d_mema( - runner: Runner | None = None, -) -> V3dMemaOutputs: - """ - 3dMEMA is a program for performing Mixed Effects Meta Analysis at group level - that models both within- and across-subjects variability. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMemaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MEMA_METADATA) - cargs = [] - cargs.append("3dMEMA") - cargs.append("[OPTIONS]") - ret = V3dMemaOutputs( - root=execution.output_file("."), - output_file=execution.output_file("[PREFIX].nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMemaOutputs", - "V_3D_MEMA_METADATA", - "v_3d_mema", -] diff --git a/python/src/niwrap/afni/v_3d_mepfm.py b/python/src/niwrap/afni/v_3d_mepfm.py deleted file mode 100644 index 0e18a72ca..000000000 --- a/python/src/niwrap/afni/v_3d_mepfm.py +++ /dev/null @@ -1,113 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MEPFM_METADATA = Metadata( - id="7de39809ee1b6e1e9f7322fe43a0788c7c86dca9.boutiques", - name="3dMEPFM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMepfmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mepfm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - dr2_output: OutputPathType - """Changes in R2* parameter, assumed to represent neuronal-related signal - changes""" - dr2fit_output: OutputPathType - """Convolution of DR2 with HRF, one volume per echo""" - ds0_output: OutputPathType - """Changes in net magnetization (S0) (if estimated)""" - lambda_output: OutputPathType - """Regularization parameter""" - sigmas_mad_output: OutputPathType - """Estimate of the noise standard deviation after wavelet decomposition for - each input dataset""" - costs_output: OutputPathType - """Cost function to select the regularization parameter (lambda) according - to selection criterion""" - - -def v_3d_mepfm( - input_files: list[str], - dbg_args: bool = False, - mask: InputPathType | None = None, - hrf_model: str | None = None, - verbosity: int | None = None, - runner: Runner | None = None, -) -> V3dMepfmOutputs: - """ - Voxelwise deconvolution of Multiecho fMRI data to yield time-varying estimates - of changes in transverse relaxation (DR2*) and optionally, net magnetization - (DS0). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Dataset to analyze with Multiecho Paradigm Free Mapping,\ - along with the echo time. - dbg_args: Enable R to save the parameters in .3dMEPFM.dbg.AFNI.args in\ - the current directory. - mask: Process voxels inside this mask only. Default is no masking. - hrf_model: Haemodynamic response function used for deconvolution. - verbosity: Verbosity level. 0 for quiet, 1 (default) or more:\ - talkative. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMepfmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MEPFM_METADATA) - cargs = [] - cargs.append("3dMEPFM") - cargs.extend([ - "-input", - *input_files - ]) - if dbg_args: - cargs.append("-dbgArgs") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if hrf_model is not None: - cargs.extend([ - "-hrf", - hrf_model - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - cargs.append("[OTHER_OPTIONS]") - ret = V3dMepfmOutputs( - root=execution.output_file("."), - dr2_output=execution.output_file("DR2_[PREFIX]_*.nii.gz"), - dr2fit_output=execution.output_file("DR2fit_[PREFIX]_*.nii.gz"), - ds0_output=execution.output_file("DS0_[PREFIX]_*.nii.gz"), - lambda_output=execution.output_file("lambda_[PREFIX]_*.nii.gz"), - sigmas_mad_output=execution.output_file("sigmas_MAD_[PREFIX]_*.nii.gz"), - costs_output=execution.output_file("costs_[PREFIX]_*.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMepfmOutputs", - "V_3D_MEPFM_METADATA", - "v_3d_mepfm", -] diff --git a/python/src/niwrap/afni/v_3d_mse.py b/python/src/niwrap/afni/v_3d_mse.py deleted file mode 100644 index 019c4e8c0..000000000 --- a/python/src/niwrap/afni/v_3d_mse.py +++ /dev/null @@ -1,120 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MSE_METADATA = Metadata( - id="ff2e9633405885aec7920f250dba5893cb5b6dda.boutiques", - name="3dMSE", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMseOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mse(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_brik: OutputPathType | None - """Output dataset in BRIK format.""" - out_head: OutputPathType | None - """Output dataset in HEAD format.""" - - -def v_3d_mse( - dset: InputPathType, - polynomial_order: int | None = None, - autoclip: bool = False, - automask: bool = False, - mask: InputPathType | None = None, - prefix: str | None = None, - scales: float | None = None, - entwin: float | None = None, - rthresh: float | None = None, - runner: Runner | None = None, -) -> V3dMseOutputs: - """ - Computes voxelwise multi-scale entropy. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Input dataset (e.g., dset.nii.gz). - polynomial_order: Remove polynomial trend of order 'm' (default is m=1;\ - m=-1 means no detrending). - autoclip: Clip off low-intensity regions in the dataset. - automask: Use automask to clip low-intensity regions. - mask: Mask to define 'in-brain' voxels. - prefix: Prefix for the output dataset (default is 'MSE'). - scales: The number of scales to be used in the calculation (default is\ - 5). - entwin: The window size used in the calculation (default is 2). - rthresh: The radius threshold for determining if values are the same in\ - the SampleEn calculation, in fractions of the standard deviation\ - (default is 0.5). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMseOutputs`). - """ - if polynomial_order is not None and not (-1 <= polynomial_order <= 3): - raise ValueError(f"'polynomial_order' must be between -1 <= x <= 3 but was {polynomial_order}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MSE_METADATA) - cargs = [] - cargs.append("3dMSE") - if polynomial_order is not None: - cargs.extend([ - "-polort", - str(polynomial_order) - ]) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if scales is not None: - cargs.extend([ - "-scales", - str(scales) - ]) - if entwin is not None: - cargs.extend([ - "-entwin", - str(entwin) - ]) - if rthresh is not None: - cargs.extend([ - "-rthresh", - str(rthresh) - ]) - cargs.append(execution.input_file(dset)) - ret = V3dMseOutputs( - root=execution.output_file("."), - out_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - out_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMseOutputs", - "V_3D_MSE_METADATA", - "v_3d_mse", -] diff --git a/python/src/niwrap/afni/v_3d_mss.py b/python/src/niwrap/afni/v_3d_mss.py deleted file mode 100644 index f9bf9452b..000000000 --- a/python/src/niwrap/afni/v_3d_mss.py +++ /dev/null @@ -1,175 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MSS_METADATA = Metadata( - id="ecd8c02c668a204a461a0151f5ebbf32fbc74dce.boutiques", - name="3dMSS", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMssOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mss(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output file in NIfTI format""" - - -def v_3d_mss( - prefix: str, - data_table: InputPathType, - jobs: float | None = None, - mrr_formula: str | None = None, - lme_formula: str | None = None, - random_effect: str | None = None, - qvars: str | None = None, - mask: InputPathType | None = None, - bounds: list[float] | None = None, - prediction_table: InputPathType | None = None, - cio_flag: bool = False, - rio_flag: bool = False, - help_flag: bool = False, - dbg_args_flag: bool = False, - if_name: str | None = None, - show_allowed_options_flag: bool = False, - sdiff_vars: str | None = None, - vt_formula: str | None = None, - runner: Runner | None = None, -) -> V3dMssOutputs: - """ - Voxelwise Multilevel Smoothing Spline (MSS) Analysis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name. For AFNI format, provide prefix only, with no\ - view+suffix needed. Filename for NIfTI format should have .nii\ - attached. - data_table: List the data structure with a header as the first line. - jobs: Number of CPU cores for parallel processing. - mrr_formula: Model formulation through multilevel smoothing splines. - lme_formula: Specify the fixed effect components of the model. - random_effect: Specify the random effect components of the model. - qvars: Identify quantitative variables (or covariates). The list with\ - more than one variable has to be separated with comma without any other\ - characters. - mask: Process voxels inside this mask only. - bounds: Outlier removal bounds. Any values in the input data that are\ - beyond the bounds will be removed and treated as missing. - prediction_table: Provide a data table so that predicted values could\ - be generated for graphical illustration. - cio_flag: Use AFNI's C io functions, which is default. - rio_flag: Use R's io functions. - help_flag: Display help message. - dbg_args_flag: Enable R to save the parameters in a file called\ - .3dMSS.dbg.AFNI.args for debugging. - if_name: Specify the column name that is designated for input files of\ - effect estimate. Default is 'InputFile'. - show_allowed_options_flag: List of allowed options. - sdiff_vars: Specify the factors for group comparisons. - vt_formula: Specify varying smoothing terms. Two components are\ - required: the first one 'var' indicates the variable (e.g., subject)\ - around which the smoothing will vary while the second component\ - specifies the smoothing formulation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMssOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MSS_METADATA) - cargs = [] - cargs.append("3dMSS") - cargs.append(prefix) - if jobs is not None: - cargs.extend([ - "-jobs", - str(jobs) - ]) - if mrr_formula is not None: - cargs.extend([ - "-mrr", - mrr_formula - ]) - if lme_formula is not None: - cargs.extend([ - "-lme", - lme_formula - ]) - if random_effect is not None: - cargs.extend([ - "-ranEff", - random_effect - ]) - if qvars is not None: - cargs.extend([ - "-qVars", - qvars - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if bounds is not None: - cargs.extend([ - "-bounds", - *map(str, bounds) - ]) - if prediction_table is not None: - cargs.extend([ - "-prediction", - execution.input_file(prediction_table) - ]) - cargs.extend([ - "-dataTable", - execution.input_file(data_table) - ]) - if cio_flag: - cargs.append("-cio") - if rio_flag: - cargs.append("-Rio") - if help_flag: - cargs.append("-help") - if dbg_args_flag: - cargs.append("-dbgArgs") - if if_name is not None: - cargs.extend([ - "-IF", - if_name - ]) - if show_allowed_options_flag: - cargs.append("-show_allowed_options") - if sdiff_vars is not None: - cargs.extend([ - "-sdiff", - sdiff_vars - ]) - if vt_formula is not None: - cargs.extend([ - "-vt", - vt_formula - ]) - ret = V3dMssOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMssOutputs", - "V_3D_MSS_METADATA", - "v_3d_mss", -] diff --git a/python/src/niwrap/afni/v_3d_multi_thresh.py b/python/src/niwrap/afni/v_3d_multi_thresh.py deleted file mode 100644 index a50e48eab..000000000 --- a/python/src/niwrap/afni/v_3d_multi_thresh.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MULTI_THRESH_METADATA = Metadata( - id="ac6c6a539a206612134e8a96c0fd7291780ddc36.boutiques", - name="3dMultiThresh", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMultiThreshOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_multi_thresh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Thresholded version of the input dataset.""" - mask_output: OutputPathType | None - """0/1 mask dataset of voxels that survive the process.""" - all_mask_output: OutputPathType | None - """Multi-volume dataset where each volume is the binary mask of voxels that - pass ONE of the tests.""" - - -def v_3d_multi_thresh( - mthresh_file: InputPathType, - input_file: InputPathType, - index: float | None = None, - signed_flag: str | None = None, - positive_sign_flag: bool = False, - negative_sign_flag: bool = False, - prefix: str | None = None, - mask_only_flag: bool = False, - all_mask: str | None = None, - no_zero_flag: bool = False, - quiet_flag: bool = False, - runner: Runner | None = None, -) -> V3dMultiThreshOutputs: - """ - Program to apply a multi-threshold (mthresh) dataset to an input dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - mthresh_file: Multi-threshold dataset from 3dXClustSim, usually via\ - running '3dttest++ -ETAC'. - input_file: Dataset to threshold. - index: Index (sub-brick) on which to threshold. - signed_flag: Indicates if the .mthresh.nii file from 3dXClustSim was\ - created using 1-sided thresholding. Choose sign + or -. - positive_sign_flag: Same as '-signed +'. - negative_sign_flag: Same as '-signed -'. - prefix: Prefix for output dataset. Can be 'NULL' to get no output\ - dataset. - mask_only_flag: Instead of outputting a thresholded version of the\ - input dataset, just output a 0/1 mask dataset of voxels that survive\ - the process. - all_mask: Write out a multi-volume dataset with prefix 'qqq' where each\ - volume is the binary mask of voxels that pass ONE of the tests. - no_zero_flag: Prevents the output of a dataset if it would be all zero. - quiet_flag: Turn off progress report messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMultiThreshOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MULTI_THRESH_METADATA) - cargs = [] - cargs.append("3dMultiThresh") - cargs.extend([ - "-mthresh", - execution.input_file(mthresh_file) - ]) - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if index is not None: - cargs.extend([ - "-1tindex", - str(index) - ]) - if signed_flag is not None: - cargs.extend([ - "-signed", - signed_flag - ]) - if positive_sign_flag: - cargs.append("-pos") - if negative_sign_flag: - cargs.append("-neg") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if mask_only_flag: - cargs.append("-maskonly") - if all_mask is not None: - cargs.extend([ - "-allmask", - all_mask - ]) - if no_zero_flag: - cargs.append("-nozero") - if quiet_flag: - cargs.append("-quiet") - ret = V3dMultiThreshOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - mask_output=execution.output_file(prefix + "_mask.nii.gz") if (prefix is not None) else None, - all_mask_output=execution.output_file(all_mask + ".nii.gz") if (all_mask is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMultiThreshOutputs", - "V_3D_MULTI_THRESH_METADATA", - "v_3d_multi_thresh", -] diff --git a/python/src/niwrap/afni/v_3d_mvm.py b/python/src/niwrap/afni/v_3d_mvm.py deleted file mode 100644 index 65c1e10ab..000000000 --- a/python/src/niwrap/afni/v_3d_mvm.py +++ /dev/null @@ -1,133 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MVM_METADATA = Metadata( - id="41e1dd222d8dc8d40a7419dbf4444dad608de47a.boutiques", - name="3dMVM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMvmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mvm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_head: OutputPathType - """Output HEAD file in AFNI format""" - outfile_brik: OutputPathType - """Output BRIK file in AFNI format""" - - -def v_3d_mvm( - prefix: str, - bs_vars: str, - data_table: str, - dbg_args: str | None = None, - jobs: int | None = None, - mask: InputPathType | None = None, - ws_vars: str | None = None, - q_vars: str | None = None, - q_var_centers: str | None = None, - num_glt: int | None = None, - glt_label: str | None = None, - glt_code: str | None = None, - num_glf: int | None = None, - glf_label: str | None = None, - glf_code: str | None = None, - runner: Runner | None = None, -) -> V3dMvmOutputs: - """ - AFNI Group Analysis Program with Multi-Variate Modeling Approach. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name prefix. - bs_vars: Formula for between-subjects variables. - data_table: Data table for analysis. - dbg_args: Enable R to save parameters in a file for debugging. - jobs: Number of jobs for parallel processing. - mask: Only process voxels inside this mask. - ws_vars: Formula for within-subjects variables. - q_vars: Comma-separated list of quantitative variables (covariates). - q_var_centers: Comma-separated centering values for quantitative\ - variables. - num_glt: Number of general linear t-tests (GLTs). - glt_label: Label for each general linear t-test (GLT). - glt_code: Coding for each general linear t-test (GLT). - num_glf: Number of general linear F-tests (GLFs). - glf_label: Label for each general linear F-test (GLF). - glf_code: Coding for each general linear F-test (GLF). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMvmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MVM_METADATA) - cargs = [] - cargs.append("3dMVM") - if dbg_args is not None: - cargs.append(dbg_args) - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-jobs") - if jobs is not None: - cargs.append(str(jobs)) - cargs.append("-mask") - if mask is not None: - cargs.append(execution.input_file(mask)) - cargs.append("-bsVars") - cargs.append(bs_vars) - cargs.append("-wsVars") - if ws_vars is not None: - cargs.append(ws_vars) - cargs.append("-qVars") - if q_vars is not None: - cargs.append(q_vars) - cargs.append("-qVarCenters") - if q_var_centers is not None: - cargs.append(q_var_centers) - cargs.append("-num_glt") - if num_glt is not None: - cargs.append(str(num_glt)) - cargs.append("-gltLabel") - if glt_label is not None: - cargs.append(glt_label) - cargs.append("-gltCode") - if glt_code is not None: - cargs.append(glt_code) - cargs.append("-num_glf") - if num_glf is not None: - cargs.append(str(num_glf)) - cargs.append("-glfLabel") - if glf_label is not None: - cargs.append(glf_label) - cargs.append("-glfCode") - if glf_code is not None: - cargs.append(glf_code) - cargs.append("-dataTable") - cargs.append(data_table) - ret = V3dMvmOutputs( - root=execution.output_file("."), - outfile_head=execution.output_file(prefix + "+tlrc.HEAD"), - outfile_brik=execution.output_file(prefix + "+tlrc.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMvmOutputs", - "V_3D_MVM_METADATA", - "v_3d_mvm", -] diff --git a/python/src/niwrap/afni/v_3d_mvm_validator.py b/python/src/niwrap/afni/v_3d_mvm_validator.py deleted file mode 100644 index ac7a5d3c3..000000000 --- a/python/src/niwrap/afni/v_3d_mvm_validator.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_MVM_VALIDATOR_METADATA = Metadata( - id="922fe2d0a794693ed3858b8e880aa7f811995c48.boutiques", - name="3dMVM_validator", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dMvmValidatorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_mvm_validator(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - temp_folder: OutputPathType - """Temporary folder created during the shiny app session.""" - - -def v_3d_mvm_validator( - datatable: InputPathType, - shinyfolder: str | None = None, - runner: Runner | None = None, -) -> V3dMvmValidatorOutputs: - """ - Launch the 3dMVM model validation shiny app in a web browser. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datatable: A file containing a data table formatted like the 3dMVM\ - "-dataTable". - shinyfolder: Use a custom shiny folder (for testing purposes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dMvmValidatorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_MVM_VALIDATOR_METADATA) - cargs = [] - cargs.append("3dMVM_validator") - cargs.append(execution.input_file(datatable)) - if shinyfolder is not None: - cargs.extend([ - "-ShinyFolder", - shinyfolder - ]) - ret = V3dMvmValidatorOutputs( - root=execution.output_file("."), - temp_folder=execution.output_file("__*_3dMVM_validator_temp_delete"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dMvmValidatorOutputs", - "V_3D_MVM_VALIDATOR_METADATA", - "v_3d_mvm_validator", -] diff --git a/python/src/niwrap/afni/v_3d_net_corr.py b/python/src/niwrap/afni/v_3d_net_corr.py deleted file mode 100644 index 583316b38..000000000 --- a/python/src/niwrap/afni/v_3d_net_corr.py +++ /dev/null @@ -1,174 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NET_CORR_METADATA = Metadata( - id="958c7038de682b846c408cbd34ee6146fe058e26.boutiques", - name="3dNetCorr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNetCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_net_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_netcc: OutputPathType - """Output correlation matrix file for network 000""" - output_netts: OutputPathType - """Output mean time series per ROI for network 000""" - output_niml: OutputPathType - """NIML/SUMA-esque file for visualizing connectivity info in a 3D brain for - network 000""" - output_roidat: OutputPathType - """Columns contain information for each ROI in the used mask.""" - output_mask_nnull: OutputPathType - """Mask of non-null time series""" - output_indiv: OutputPathType - """Directory containing individual time series files for network 000""" - output_binary_mask_nnull: OutputPathType - """Binary mask of the non-null time series""" - - -def v_3d_net_corr( - prefix: str, - inset: InputPathType, - in_rois: InputPathType, - mask: InputPathType | None = None, - fish_z: bool = False, - part_corr: bool = False, - ts_out: bool = False, - ts_label: bool = False, - ts_indiv: bool = False, - ts_wb_corr: bool = False, - ts_wb_z: bool = False, - weight_ts: InputPathType | None = None, - weight_corr: InputPathType | None = None, - ts_wb_strlabel: bool = False, - nifti: bool = False, - output_mask_nonnull: bool = False, - push_thru_many_zeros: bool = False, - allow_roi_zeros: bool = False, - automask_off: bool = False, - ignore_lt: bool = False, - runner: Runner | None = None, -) -> V3dNetCorrOutputs: - """ - Compute correlation matrix of a set of ROIs based on mean time series. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name prefix. - inset: Time series file (4D data set). - in_rois: Input a set of ROIs each labelled with distinct integers.\ - Multiple subbricks can be input, each will be treated as a separate\ - network. - mask: Whole brain mask within which to calculate correlation. - fish_z: Output Fisher Z-transform matrix along with correlation matrix. - part_corr: Output the partial correlation matrix. - ts_out: Output the mean time series of the ROIs. - ts_label: Insert the integer ROI label at the start of each line of the\ - *.netts file created. - ts_indiv: Create a directory for each network that contains the average\ - time series for each ROI in individual files. - ts_wb_corr: Perform whole brain correlation for each ROI's average time\ - series and output as Pearson 'r' values. - ts_wb_z: Perform whole brain correlation for each ROI's average time\ - series and output as Fisher transformed Z-scores. - weight_ts: Input a 1D file of weights to be applied multiplicatively to\ - each ROI's average time series. - weight_corr: Input a 1D file of weights to estimate a weighted Pearson\ - Correlation. - ts_wb_strlabel: Apply string labels to the WB correlation/Z-score\ - output files. - nifti: Output any correlation map files as NIFTI files. - output_mask_nonnull: Output mask of non-null time series. - push_thru_many_zeros: Push through the calculation even if any ROI\ - contains more than 10 percent of voxels with null time series. - allow_roi_zeros: Allow ROIs to have all-zero time series. - automask_off: Disable internal automasking of where time series are not\ - uniformly zero. - ignore_lt: Ignore any label table labels in the '-in_rois' file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNetCorrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NET_CORR_METADATA) - cargs = [] - cargs.append("3dNetCorr") - cargs.append(prefix) - cargs.append(execution.input_file(inset)) - cargs.append(execution.input_file(in_rois)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if fish_z: - cargs.append("-fish_z") - if part_corr: - cargs.append("-part_corr") - if ts_out: - cargs.append("-ts_out") - if ts_label: - cargs.append("-ts_label") - if ts_indiv: - cargs.append("-ts_indiv") - if ts_wb_corr: - cargs.append("-ts_wb_corr") - if ts_wb_z: - cargs.append("-ts_wb_Z") - if weight_ts is not None: - cargs.extend([ - "-weight_ts", - execution.input_file(weight_ts) - ]) - if weight_corr is not None: - cargs.extend([ - "-weight_corr", - execution.input_file(weight_corr) - ]) - if ts_wb_strlabel: - cargs.append("-ts_wb_strlabel") - if nifti: - cargs.append("-nifti") - if output_mask_nonnull: - cargs.append("-output_mask_nonnull") - if push_thru_many_zeros: - cargs.append("-push_thru_many_zeros") - if allow_roi_zeros: - cargs.append("-allow_roi_zeros") - if automask_off: - cargs.append("-automask_off") - if ignore_lt: - cargs.append("-ignore_LT") - ret = V3dNetCorrOutputs( - root=execution.output_file("."), - output_netcc=execution.output_file(prefix + "_000.netcc"), - output_netts=execution.output_file(prefix + "_000.netts"), - output_niml=execution.output_file(prefix + "_000.niml.dset"), - output_roidat=execution.output_file(prefix + ".roidat"), - output_mask_nnull=execution.output_file(prefix + "_mask_nnull"), - output_indiv=execution.output_file(prefix + "_000_INDIV"), - output_binary_mask_nnull=execution.output_file("PREFIX_mask_nnull"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNetCorrOutputs", - "V_3D_NET_CORR_METADATA", - "v_3d_net_corr", -] diff --git a/python/src/niwrap/afni/v_3d_nlfim.py b/python/src/niwrap/afni/v_3d_nlfim.py deleted file mode 100644 index fabf0bcf8..000000000 --- a/python/src/niwrap/afni/v_3d_nlfim.py +++ /dev/null @@ -1,110 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NLFIM_METADATA = Metadata( - id="a4c9f15cadc6347edfbee179e6d7966fdba5f370.boutiques", - name="3dNLfim", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNlfimOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nlfim(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - freg_outfile: OutputPathType - """F-test for significance of the regression""" - frsqr_outfile: OutputPathType - """R^2 calculation for regression""" - fsmax_outfile: OutputPathType - """Signed maximum signal estimate""" - ftmax_outfile: OutputPathType - """Time of signed maximum estimate""" - fpsmax_outfile: OutputPathType - """Maximum percentage change estimate""" - farea_outfile: OutputPathType - """Area between signal and baseline""" - fparea_outfile: OutputPathType - """Percentage area of signal estimate""" - fscoef_outfile: OutputPathType - """Signal parameter estimate""" - fncoef_outfile: OutputPathType - """Noise parameter estimate""" - tscoef_outfile: OutputPathType - """T-test for significance of signal parameter""" - tncoef_outfile: OutputPathType - """T-test for significance of noise parameter""" - bucket_outfile: OutputPathType - """AFNI 'bucket' dataset""" - sfit_outfile: OutputPathType - """Output 3d+time signal model fit""" - snfit_outfile: OutputPathType - """Output 3d+time signal+noise fit""" - - -def v_3d_nlfim( - input_file: InputPathType, - signal_model: str, - noise_model: str, - runner: Runner | None = None, -) -> V3dNlfimOutputs: - """ - Nonlinear regression for each voxel of the input AFNI 3d+time data set. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Filename of 3d+time data file for input. - signal_model: Name of the nonlinear signal model. - noise_model: Name of the linear noise model. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNlfimOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NLFIM_METADATA) - cargs = [] - cargs.append("3dNLfim") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-signal") - cargs.append(signal_model) - cargs.append("-noise") - cargs.append(noise_model) - cargs.append("[ADDITIONAL_OPTIONS]") - ret = V3dNlfimOutputs( - root=execution.output_file("."), - freg_outfile=execution.output_file("[FREG].fift"), - frsqr_outfile=execution.output_file("[FRSQR].fift"), - fsmax_outfile=execution.output_file("[FSMAX].fift"), - ftmax_outfile=execution.output_file("[FTMAX].fift"), - fpsmax_outfile=execution.output_file("[FPSMAX].fift"), - farea_outfile=execution.output_file("[FAREA].fift"), - fparea_outfile=execution.output_file("[FPAREA].fift"), - fscoef_outfile=execution.output_file("[FSCOEF].fift"), - fncoef_outfile=execution.output_file("[FNCOEF].fift"), - tscoef_outfile=execution.output_file("[TSCOEF].fitt"), - tncoef_outfile=execution.output_file("[TNCOEF].fitt"), - bucket_outfile=execution.output_file("[BUCKET].bucket"), - sfit_outfile=execution.output_file("[SFIT].sfit"), - snfit_outfile=execution.output_file("[SNFIT].snfit"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNlfimOutputs", - "V_3D_NLFIM_METADATA", - "v_3d_nlfim", -] diff --git a/python/src/niwrap/afni/v_3d_normality_test.py b/python/src/niwrap/afni/v_3d_normality_test.py deleted file mode 100644 index 6ea84191d..000000000 --- a/python/src/niwrap/afni/v_3d_normality_test.py +++ /dev/null @@ -1,78 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NORMALITY_TEST_METADATA = Metadata( - id="4b9b077168b2f91f1b97f263797faaf18f2fa6ec.boutiques", - name="3dNormalityTest", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNormalityTestOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_normality_test(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output dataset with results""" - - -def v_3d_normality_test( - input_: InputPathType, - prefix: str, - noexp: bool = False, - pval: bool = False, - runner: Runner | None = None, -) -> V3dNormalityTestOutputs: - """ - This program tests the input values at each voxel for normality using the - Anderson-Darling method. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Specifies the input dataset. - prefix: Specifies the name for the output dataset. - noexp: Do not convert the A-D statistic to an exponentially distributed\ - value. - pval: Output the results as a pure (estimated) p-value. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNormalityTestOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NORMALITY_TEST_METADATA) - cargs = [] - cargs.append("3dNormalityTest") - cargs.append(execution.input_file(input_)) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if noexp: - cargs.append("-noexp") - if pval: - cargs.append("-pval") - ret = V3dNormalityTestOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+orig.*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNormalityTestOutputs", - "V_3D_NORMALITY_TEST_METADATA", - "v_3d_normality_test", -] diff --git a/python/src/niwrap/afni/v_3d_notes.py b/python/src/niwrap/afni/v_3d_notes.py deleted file mode 100644 index 80518175a..000000000 --- a/python/src/niwrap/afni/v_3d_notes.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NOTES_METADATA = Metadata( - id="940bc1c01a30bd95a8de66900c6eff7191dde7e1.boutiques", - name="3dNotes", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNotesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_notes(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_notes( - dataset: InputPathType, - add_note: str | None = None, - append_history: str | None = None, - replace_history: str | None = None, - delete_note: float | None = None, - print_notes: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> V3dNotesOutputs: - """ - A program to add, delete and show notes for AFNI datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: AFNI compatible dataset [required]. - add_note: Add the string 'str' to the list of notes. - append_history: Append the string 'str' to the dataset's history. This\ - can only appear once on the command line. - replace_history: Replace any existing history note with 'str'. This\ - option cannot be used with '-h'. - delete_note: Deletes note number num. - print_notes: Print to stdout the expanded notes. - help_: Displays this help screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNotesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NOTES_METADATA) - cargs = [] - cargs.append("3dNotes") - if add_note is not None: - cargs.extend([ - "-a", - add_note - ]) - if append_history is not None: - cargs.extend([ - "-h", - append_history - ]) - if replace_history is not None: - cargs.extend([ - "-HH", - replace_history - ]) - if delete_note is not None: - cargs.extend([ - "-d", - str(delete_note) - ]) - if print_notes: - cargs.append("-ses") - if help_: - cargs.append("-help") - cargs.append(execution.input_file(dataset)) - ret = V3dNotesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNotesOutputs", - "V_3D_NOTES_METADATA", - "v_3d_notes", -] diff --git a/python/src/niwrap/afni/v_3d_nwarp_adjust.py b/python/src/niwrap/afni/v_3d_nwarp_adjust.py deleted file mode 100644 index 01b64689f..000000000 --- a/python/src/niwrap/afni/v_3d_nwarp_adjust.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NWARP_ADJUST_METADATA = Metadata( - id="0c3ecbaf201c4034c9ca75f6bc8b7c5f5190cfaf.boutiques", - name="3dNwarpAdjust", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNwarpAdjustOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nwarp_adjust(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType | None - """Output mean dataset BRIK file""" - output_head: OutputPathType | None - """Output mean dataset HEAD file""" - - -def v_3d_nwarp_adjust( - input_warps: list[InputPathType], - source_datasets: list[InputPathType] | None = None, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> V3dNwarpAdjustOutputs: - """ - Program to adjust 3D warp datasets by composing them with the inverse of their - average, optionally warping input datasets and generating an output mean - dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_warps: List of input 3D warp datasets (at least 5). - source_datasets: List of input 3D datasets to be warped by the adjusted\ - warp datasets. There must be exactly as many of these datasets as there\ - are input warps. - output_prefix: Prefix for the output mean dataset (only needed if the\ - '-source' option is also given). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNwarpAdjustOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NWARP_ADJUST_METADATA) - cargs = [] - cargs.append("3dNwarpAdjust") - cargs.extend([ - "-nwarp", - *[execution.input_file(f) for f in input_warps] - ]) - if source_datasets is not None: - cargs.extend([ - "-source", - *[execution.input_file(f) for f in source_datasets] - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - ret = V3dNwarpAdjustOutputs( - root=execution.output_file("."), - output_brik=execution.output_file(output_prefix + "+tlrc.BRIK") if (output_prefix is not None) else None, - output_head=execution.output_file(output_prefix + "+tlrc.HEAD") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNwarpAdjustOutputs", - "V_3D_NWARP_ADJUST_METADATA", - "v_3d_nwarp_adjust", -] diff --git a/python/src/niwrap/afni/v_3d_nwarp_apply.py b/python/src/niwrap/afni/v_3d_nwarp_apply.py deleted file mode 100644 index 54ef5f004..000000000 --- a/python/src/niwrap/afni/v_3d_nwarp_apply.py +++ /dev/null @@ -1,153 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NWARP_APPLY_METADATA = Metadata( - id="0a5385bf1fc9acdee0016adc133f63a8ec8a4e36.boutiques", - name="3dNwarpApply", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNwarpApplyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nwarp_apply(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warped_output: OutputPathType | None - """Warped output dataset""" - generated_warp: OutputPathType | None - """Warp dataset generated during application""" - - -def v_3d_nwarp_apply( - nwarp: str, - source: str, - iwarp: bool = False, - master: str | None = None, - newgrid: str | None = None, - dxyz: str | None = None, - interp: str | None = None, - ainterp: str | None = None, - prefix: str | None = None, - suffix: str | None = None, - short: bool = False, - wprefix: str | None = None, - quiet: bool = False, - verb: bool = False, - runner: Runner | None = None, -) -> V3dNwarpApplyOutputs: - """ - Program to apply a nonlinear 3D warp saved from 3dQwarp (or 3dNwarpCat, etc.) to - a 3D dataset, to produce a warped version of the source dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - nwarp: The name of the 3D warp dataset. Multiple warps can be\ - catenated. - source: The name of the source dataset to be warped. Multiple datasets\ - can be supplied. - iwarp: Invert the warp specified in '-nwarp'. - master: The name of the master dataset which defines the output grid. - newgrid: The new grid spacing (cubical voxels, in mm). - dxyz: Specify a different grid spacing (cubical voxels, in mm). - interp: The interpolation mode ('NN', 'linear', 'cubic', 'quintic',\ - 'wsinc5'). - ainterp: Specify a different interpolation mode for the data than the\ - warp. - prefix: The name of the new output dataset. Multiple names can be\ - supplied if more than one source dataset is input. - suffix: Change the default suffix '_Nwarp' to a user-defined suffix. - short: Write output dataset using 16-bit short integers rather than the\ - usual 32-bit floats. - wprefix: Save every warp generated in the process to a separate\ - dataset. - quiet: Don't be verbose. - verb: Be extra verbose. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNwarpApplyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NWARP_APPLY_METADATA) - cargs = [] - cargs.append("3dNwarpApply") - cargs.extend([ - "-nwarp", - nwarp - ]) - if iwarp: - cargs.append("-iwarp") - cargs.extend([ - "-source", - source - ]) - if master is not None: - cargs.extend([ - "-master", - master - ]) - if newgrid is not None: - cargs.extend([ - "-newgrid", - newgrid - ]) - if dxyz is not None: - cargs.extend([ - "-dxyz", - dxyz - ]) - if interp is not None: - cargs.extend([ - "-interp", - interp - ]) - if ainterp is not None: - cargs.extend([ - "-ainterp", - ainterp - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if short: - cargs.append("-short") - if wprefix is not None: - cargs.extend([ - "-wprefix", - wprefix - ]) - if quiet: - cargs.append("-quiet") - if verb: - cargs.append("-verb") - ret = V3dNwarpApplyOutputs( - root=execution.output_file("."), - warped_output=execution.output_file(prefix + "_" + source + "_warped.nii.gz") if (prefix is not None) else None, - generated_warp=execution.output_file(wprefix + "_warp_????.nii.gz") if (wprefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNwarpApplyOutputs", - "V_3D_NWARP_APPLY_METADATA", - "v_3d_nwarp_apply", -] diff --git a/python/src/niwrap/afni/v_3d_nwarp_cat.py b/python/src/niwrap/afni/v_3d_nwarp_cat.py deleted file mode 100644 index 7d1a52076..000000000 --- a/python/src/niwrap/afni/v_3d_nwarp_cat.py +++ /dev/null @@ -1,118 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NWARP_CAT_METADATA = Metadata( - id="e3b5978ed235b04f0d1559137f70db255a2b539c.boutiques", - name="3dNwarpCat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNwarpCatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nwarp_cat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_matrix: OutputPathType - """Output matrix file when only matrix warps are provided.""" - output_dataset: OutputPathType - """Output dataset when warp files are provided.""" - - -def v_3d_nwarp_cat( - output_prefix: str, - warp1: InputPathType, - warp2: InputPathType, - interpolation: str | None = None, - verbosity: bool = False, - space_marker: str | None = None, - additional_warps: list[InputPathType] | None = None, - invert_final_warp: bool = False, - extra_padding: float | None = None, - runner: Runner | None = None, -) -> V3dNwarpCatOutputs: - """ - Catenates (composes) 3D warps defined on a grid or via a matrix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_prefix: Prefix name for the output dataset that holds the warp. - warp1: Specify the first warp. - warp2: Specify the second warp. - interpolation: Interpolation mode: linear, quintic, or wsinc5\ - (default). - verbosity: Print various fun messages during execution. - space_marker: Attach string 'sss' to the output dataset as its atlas\ - space marker. - additional_warps: Additional warp files. - invert_final_warp: Invert the final warp before output. - extra_padding: Pad the nonlinear warps by 'PP' voxels in all\ - directions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNwarpCatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NWARP_CAT_METADATA) - cargs = [] - cargs.append("3dNwarpCat") - if interpolation is not None: - cargs.extend([ - "-interp", - interpolation - ]) - if verbosity: - cargs.append("-verb") - cargs.append("-prefix") - cargs.extend([ - "-prefix", - output_prefix - ]) - if space_marker is not None: - cargs.extend([ - "-space", - space_marker - ]) - cargs.append("-warp1") - cargs.extend([ - "-warp1", - execution.input_file(warp1) - ]) - cargs.append("-warp2") - cargs.extend([ - "-warp2", - execution.input_file(warp2) - ]) - if additional_warps is not None: - cargs.extend([execution.input_file(f) for f in additional_warps]) - if invert_final_warp: - cargs.append("-iwarp") - if extra_padding is not None: - cargs.extend([ - "-expad", - str(extra_padding) - ]) - ret = V3dNwarpCatOutputs( - root=execution.output_file("."), - output_matrix=execution.output_file(output_prefix + ".aff12.1D"), - output_dataset=execution.output_file(output_prefix + "+tlrc.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNwarpCatOutputs", - "V_3D_NWARP_CAT_METADATA", - "v_3d_nwarp_cat", -] diff --git a/python/src/niwrap/afni/v_3d_nwarp_funcs.py b/python/src/niwrap/afni/v_3d_nwarp_funcs.py deleted file mode 100644 index a6965e860..000000000 --- a/python/src/niwrap/afni/v_3d_nwarp_funcs.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NWARP_FUNCS_METADATA = Metadata( - id="048fa4b745e8fa4f529a924ccc5e550b16a79b2f.boutiques", - name="3dNwarpFuncs", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNwarpFuncsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nwarp_funcs(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """The output dataset with the computed functions.""" - - -def v_3d_nwarp_funcs( - input_warp: InputPathType, - output_prefix: str, - bulk_flag: bool = False, - shear_flag: bool = False, - vorticity_flag: bool = False, - all_flag: bool = False, - runner: Runner | None = None, -) -> V3dNwarpFuncsOutputs: - """ - Compute functions of 3D warp displacements, such as bulk volume change, shear - energy, and vorticity energy. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_warp: 'www' is the name of the 3D warp dataset (mandatory\ - option). - output_prefix: 'ppp' is the name of the new output dataset. - bulk_flag: Compute the (fractional) bulk volume change (Jacobian\ - determinant minus 1). - shear_flag: Compute the shear energy. - vorticity_flag: Compute the vorticity energy. - all_flag: Compute all 3 functions: bulk, shear, and vorticity. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNwarpFuncsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NWARP_FUNCS_METADATA) - cargs = [] - cargs.append("3dNwarpFuncs") - cargs.extend([ - "-nwarp", - execution.input_file(input_warp) - ]) - cargs.extend([ - "-prefix", - output_prefix - ]) - if bulk_flag: - cargs.append("-bulk") - if shear_flag: - cargs.append("-shear") - if vorticity_flag: - cargs.append("-vorticity") - if all_flag: - cargs.append("-all") - ret = V3dNwarpFuncsOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + "_output.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNwarpFuncsOutputs", - "V_3D_NWARP_FUNCS_METADATA", - "v_3d_nwarp_funcs", -] diff --git a/python/src/niwrap/afni/v_3d_nwarp_xyz.py b/python/src/niwrap/afni/v_3d_nwarp_xyz.py deleted file mode 100644 index fa0ebf9cb..000000000 --- a/python/src/niwrap/afni/v_3d_nwarp_xyz.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_NWARP_XYZ_METADATA = Metadata( - id="4315d32044436ed76f66a6f11a8a6a58677a9969.boutiques", - name="3dNwarpXYZ", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dNwarpXyzOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_nwarp_xyz(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Warped XYZ coordinates output file""" - - -def v_3d_nwarp_xyz( - xyzfile: InputPathType, - runner: Runner | None = None, -) -> V3dNwarpXyzOutputs: - """ - Transforms the DICOM xyz coordinates in the input XYZfile.1D based on specified - warp. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - xyzfile: XYZ coordinate file containing 3 columns. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dNwarpXyzOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_NWARP_XYZ_METADATA) - cargs = [] - cargs.append("3dNwarpXYZ") - cargs.append("[OPTIONS]") - cargs.append("-nwarp") - cargs.append("[WARP_SPEC]") - cargs.append(execution.input_file(xyzfile)) - cargs.append(">") - cargs.append("[OUTPUT_FILE]") - ret = V3dNwarpXyzOutputs( - root=execution.output_file("."), - output_file=execution.output_file("[OUTPUT_FILE]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dNwarpXyzOutputs", - "V_3D_NWARP_XYZ_METADATA", - "v_3d_nwarp_xyz", -] diff --git a/python/src/niwrap/afni/v_3d_overlap.py b/python/src/niwrap/afni/v_3d_overlap.py deleted file mode 100644 index 663e6a28c..000000000 --- a/python/src/niwrap/afni/v_3d_overlap.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_OVERLAP_METADATA = Metadata( - id="7c4a09783f392121942ba5ea273c38f8724e341b.boutiques", - name="3dOverlap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dOverlapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_overlap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType - """BRIK file with count of overlaps at each voxel (if -save is used)""" - output_head: OutputPathType - """HEAD file with count of overlaps at each voxel (if -save is used)""" - - -def v_3d_overlap( - runner: Runner | None = None, -) -> V3dOverlapOutputs: - """ - Counts the number of voxels that are nonzero in all input datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dOverlapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_OVERLAP_METADATA) - cargs = [] - cargs.append("3dOverlap") - cargs.append("[OPTIONS]") - cargs.append("[DATASET1]") - cargs.append("[DATASET2]") - ret = V3dOverlapOutputs( - root=execution.output_file("."), - output_brik=execution.output_file("[PREFIX]+orig.BRIK"), - output_head=execution.output_file("[PREFIX]+orig.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dOverlapOutputs", - "V_3D_OVERLAP_METADATA", - "v_3d_overlap", -] diff --git a/python/src/niwrap/afni/v_3d_par2_afni.py b/python/src/niwrap/afni/v_3d_par2_afni.py deleted file mode 100644 index 195ea2614..000000000 --- a/python/src/niwrap/afni/v_3d_par2_afni.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_PAR2_AFNI_METADATA = Metadata( - id="14b6e5058913b8a8c4b8f823b3db88ce9943c685.boutiques", - name="3dPAR2AFNI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPar2AfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_par2_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Converted output files""" - - -def v_3d_par2_afni( - input_file: InputPathType, - skip_outliers_test: bool = False, - output_analyze: bool = False, - output_dir: str | None = None, - verbose_flag: bool = False, - gzip_files: bool = False, - byte_swap_4: bool = False, - runner: Runner | None = None, -) -> V3dPar2AfniOutputs: - """ - Convert Philips PAR/REC files to AFNI's BRIK/HEAD, NIfTI, or ANALYZE format. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input PAR file (e.g., subject1.PAR). - skip_outliers_test: Skip the outliers test when converting 4D files.\ - The default is to perform the outliers test. - output_analyze: Output ANALYZE files instead of HEAD/BRIK. - output_dir: The name of the directory where the created files should be\ - placed. If this directory does not exist, the program exits without\ - performing any conversion. - verbose_flag: Be verbose in operation. - gzip_files: Gzip the files created. The default is not to gzip the\ - files. - byte_swap_4: 4-Byte-swap the files created. The default is not to 4\ - byte-swap. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPar2AfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_PAR2_AFNI_METADATA) - cargs = [] - cargs.append("3dPAR2AFNI.pl") - cargs.append(execution.input_file(input_file)) - if skip_outliers_test: - cargs.append("-s") - if output_analyze: - cargs.append("-a") - if output_dir is not None: - cargs.extend([ - "-o", - output_dir - ]) - if verbose_flag: - cargs.append("-v") - if gzip_files: - cargs.append("-g") - if byte_swap_4: - cargs.append("-4") - ret = V3dPar2AfniOutputs( - root=execution.output_file("."), - output_files=execution.output_file(pathlib.Path(input_file).name + "_converted"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPar2AfniOutputs", - "V_3D_PAR2_AFNI_METADATA", - "v_3d_par2_afni", -] diff --git a/python/src/niwrap/afni/v_3d_periodogram.py b/python/src/niwrap/afni/v_3d_periodogram.py deleted file mode 100644 index 6f30fee9b..000000000 --- a/python/src/niwrap/afni/v_3d_periodogram.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_PERIODOGRAM_METADATA = Metadata( - id="14a644a1a26ab708ddcace9516dff73c6c2b3ad6.boutiques", - name="3dPeriodogram", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPeriodogramOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_periodogram(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_header: OutputPathType | None - """Output dataset header file""" - output_brick: OutputPathType | None - """Output dataset brick file""" - - -def v_3d_periodogram( - dataset: InputPathType, - prefix: str | None = None, - taper: float | None = None, - nfft: float | None = None, - runner: Runner | None = None, -) -> V3dPeriodogramOutputs: - """ - Computes the periodogram of each voxel time series. The periodogram is a crude - estimate of the power spectrum. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - prefix: Prefix for the output dataset. - taper: Fraction of data to taper. - nfft: Set FFT length to a specific number of points. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPeriodogramOutputs`). - """ - if taper is not None and not (0 <= taper <= 1): - raise ValueError(f"'taper' must be between 0 <= x <= 1 but was {taper}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_PERIODOGRAM_METADATA) - cargs = [] - cargs.append("3dPeriodogram") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if taper is not None: - cargs.extend([ - "-taper", - str(taper) - ]) - if nfft is not None: - cargs.extend([ - "-nfft", - str(nfft) - ]) - cargs.append(execution.input_file(dataset)) - ret = V3dPeriodogramOutputs( - root=execution.output_file("."), - output_header=execution.output_file(prefix + ".HEAD") if (prefix is not None) else None, - output_brick=execution.output_file(prefix + ".BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPeriodogramOutputs", - "V_3D_PERIODOGRAM_METADATA", - "v_3d_periodogram", -] diff --git a/python/src/niwrap/afni/v_3d_pfm.py b/python/src/niwrap/afni/v_3d_pfm.py deleted file mode 100644 index 2ca316475..000000000 --- a/python/src/niwrap/afni/v_3d_pfm.py +++ /dev/null @@ -1,137 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_PFM_METADATA = Metadata( - id="cec8821f067dfc16b0664eaec6c122f081fa4c1b.boutiques", - name="3dPFM", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPfmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_pfm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - beta: OutputPathType - """Prefix for the neuronal-related (i.e. deconvolved) time series.""" - betafitts: OutputPathType - """Prefix of the convolved neuronal-related time series.""" - fitts: OutputPathType - """Prefix for the fitted time series.""" - resid: OutputPathType - """Prefix for the residuals of the fit to the data.""" - mean: OutputPathType - """Prefix for the intercept of the model.""" - lhsest: OutputPathType - """Prefix for the estimates of the LHS parameters.""" - lhsfitts: OutputPathType - """Prefix for the fitted time series of the LHS parameters.""" - lambda_: OutputPathType - """Prefix for output volume with the regularization parameter of the - deconvolution of each voxel.""" - costs: OutputPathType - """Prefix for output volume of the cost function used to select the - regularization parameter according to the selected criteria.""" - tstats_beta: OutputPathType - """Prefix for the T-statistics of beta at each time point.""" - tdf_beta: OutputPathType - """Prefix for degrees of freedom of the T-statistics of beta.""" - z_tstats_beta: OutputPathType - """Prefix for (normalized) z-scores of the T-statistics of beta.""" - fstats_beta: OutputPathType - """Prefix for the F-statistics of the deconvolved component.""" - fdf_beta: OutputPathType - """Prefix for degrees of freedom of Fstats_beta.""" - z_fstats_beta: OutputPathType - """Prefix for (normalized) z-scores of the Fstats_beta.""" - tstats_lhs: OutputPathType - """Prefix for T-statistics of LHS regressors at each time point.""" - tdf_lhs: OutputPathType - """Prefix for degrees of freedom of the Tstats_LHS.""" - z_tstats_lhs: OutputPathType - """Prefix for (normalized) z-scores of the Tstats_LHS.""" - fstats_lhs: OutputPathType - """Prefix for the F-statistics of the LHS regressors.""" - fdf_lhs: OutputPathType - """Prefix for degrees of freedom of Fstats_LHS.""" - z_fstats_lhs: OutputPathType - """Prefix for (normalized) z-scores of Fstats_LHS.""" - fstats_full: OutputPathType - """Prefix for the F-statistics of the full model.""" - fdf_full: OutputPathType - """Prefix for degrees of freedom of Fstats_full.""" - z_fstats_full: OutputPathType - """Prefix for (normalized) z-scores of Fstats_full.""" - r2_full: OutputPathType - """Prefix for R² (coefficient of determination) of the full model.""" - r2adj_full: OutputPathType - """Prefix for Adjusted R² coefficient for the full model.""" - - -def v_3d_pfm( - runner: Runner | None = None, -) -> V3dPfmOutputs: - """ - Program for identifying brief BOLD events in fMRI time series using Paradigm - Free Mapping. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPfmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_PFM_METADATA) - cargs = [] - cargs.append("3dPFM") - cargs.append("[PARAMETERS]") - ret = V3dPfmOutputs( - root=execution.output_file("."), - beta=execution.output_file("[BETA]"), - betafitts=execution.output_file("[BETAFITTS]"), - fitts=execution.output_file("[FITTS]"), - resid=execution.output_file("[RESID]"), - mean=execution.output_file("[MEAN]"), - lhsest=execution.output_file("[LHSEST]"), - lhsfitts=execution.output_file("[LHSFITTS]"), - lambda_=execution.output_file("[LAMBDA]"), - costs=execution.output_file("[COSTS]"), - tstats_beta=execution.output_file("[TSTATS_BETA]"), - tdf_beta=execution.output_file("[TDF_BETA]"), - z_tstats_beta=execution.output_file("[Z_TSTATS_BETA]"), - fstats_beta=execution.output_file("[FSTATS_BETA]"), - fdf_beta=execution.output_file("[FDF_BETA]"), - z_fstats_beta=execution.output_file("[Z_FSTATS_BETA]"), - tstats_lhs=execution.output_file("[TSTATS_LHS]"), - tdf_lhs=execution.output_file("[TDF_LHS]"), - z_tstats_lhs=execution.output_file("[Z_TSTATS_LHS]"), - fstats_lhs=execution.output_file("[FSTATS_LHS]"), - fdf_lhs=execution.output_file("[FDF_LHS]"), - z_fstats_lhs=execution.output_file("[Z_FSTATS_LHS]"), - fstats_full=execution.output_file("[FSTATS_FULL]"), - fdf_full=execution.output_file("[FDF_FULL]"), - z_fstats_full=execution.output_file("[Z_FSTATS_FULL]"), - r2_full=execution.output_file("[R2_FULL]"), - r2adj_full=execution.output_file("[R2ADJ_FULL]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPfmOutputs", - "V_3D_PFM_METADATA", - "v_3d_pfm", -] diff --git a/python/src/niwrap/afni/v_3d_polyfit.py b/python/src/niwrap/afni/v_3d_polyfit.py deleted file mode 100644 index ba621dc5d..000000000 --- a/python/src/niwrap/afni/v_3d_polyfit.py +++ /dev/null @@ -1,161 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_POLYFIT_METADATA = Metadata( - id="2a45fc385abe30812b6c5994dee4e52581730825.boutiques", - name="3dPolyfit", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPolyfitOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_polyfit(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Fitted output dataset""" - resid_file: OutputPathType | None - """Residual dataset""" - coeff_file: OutputPathType | None - """Coefficient output file""" - - -def v_3d_polyfit( - input_dataset: InputPathType, - poly_order: int | None = None, - blur: float | None = None, - median_radius: float | None = None, - output_prefix: str | None = None, - resid_prefix: str | None = None, - coeff_output: str | None = None, - automask: bool = False, - mask_dataset: InputPathType | None = None, - mean_scale: bool = False, - clip_box: bool = False, - fit_method: int | None = None, - base_dataset: InputPathType | None = None, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dPolyfitOutputs: - """ - Fits a polynomial in space to the input dataset and outputs that fitted dataset. - You can also add your own basis datasets to the fitting mix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g., data.nii.gz). - poly_order: Maximum polynomial order (0..9); [default=3]; [n=0 is the\ - constant 1]; [n=-1 means only use volumes from '-base']. - blur: Gaussian blur input dataset (inside mask) with FWHM='f' (mm). - median_radius: Radius (voxels) of preliminary median filter of input;\ - default is no blurring. - output_prefix: Use 'pp' for prefix of output dataset (the fit); default\ - prefix is 'Polyfit'; use NULL to skip this output. - resid_prefix: Use 'rr' for the prefix of the residual dataset; default\ - is not to output residuals. - coeff_output: Save coefficients of fit into text file cc.1D; default is\ - not to save these coefficients. - automask: Create a mask (a la 3dAutomask). - mask_dataset: Create a mask from nonzero voxels in 'mset'; default is\ - not to use a mask. - mean_scale: Scale the mean value of the fit (inside the mask) to 1;\ - probably this option is not useful for anything. - clip_box: Clip fit values outside the rectilinear box containing the\ - mask to the edge of that box, to avoid weird artifacts. - fit_method: Set 'mm' to 2 for least squares fit; set it to 1 for L1 fit\ - [default method=2]; [Note that L1 fitting is slower than L2 fitting]. - base_dataset: In addition to the polynomial fit, also use the volumes\ - in dataset 'bb' as extra basis functions. - verbose: Print fun and useful progress reports. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPolyfitOutputs`). - """ - if poly_order is not None and not (-1 <= poly_order <= 9): - raise ValueError(f"'poly_order' must be between -1 <= x <= 9 but was {poly_order}") - if fit_method is not None and not (1 <= fit_method <= 2): - raise ValueError(f"'fit_method' must be between 1 <= x <= 2 but was {fit_method}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_POLYFIT_METADATA) - cargs = [] - cargs.append("3dPolyfit") - cargs.append(execution.input_file(input_dataset)) - if poly_order is not None: - cargs.extend([ - "-nord", - str(poly_order) - ]) - if blur is not None: - cargs.extend([ - "-blur", - str(blur) - ]) - if median_radius is not None: - cargs.extend([ - "-mrad", - str(median_radius) - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if resid_prefix is not None: - cargs.extend([ - "-resid", - resid_prefix - ]) - if coeff_output is not None: - cargs.extend([ - "-1Dcoef", - coeff_output - ]) - if automask: - cargs.append("-automask") - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if mean_scale: - cargs.append("-mone") - if clip_box: - cargs.append("-mclip") - if fit_method is not None: - cargs.extend([ - "-meth", - str(fit_method) - ]) - if base_dataset is not None: - cargs.extend([ - "-base", - execution.input_file(base_dataset) - ]) - if verbose: - cargs.append("-verb") - ret = V3dPolyfitOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + ".nii.gz") if (output_prefix is not None) else None, - resid_file=execution.output_file(resid_prefix + ".nii.gz") if (resid_prefix is not None) else None, - coeff_file=execution.output_file(coeff_output + ".1D") if (coeff_output is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPolyfitOutputs", - "V_3D_POLYFIT_METADATA", - "v_3d_polyfit", -] diff --git a/python/src/niwrap/afni/v_3d_pval.py b/python/src/niwrap/afni/v_3d_pval.py deleted file mode 100644 index e6e7041db..000000000 --- a/python/src/niwrap/afni/v_3d_pval.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_PVAL_METADATA = Metadata( - id="46c925a4b50a70594f3798bcdbc07a858aad1fa6.boutiques", - name="3dPval", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPvalOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_pval(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output dataset with converted statistical values. Default output filename - is 'Pval.nii.gz'.""" - - -def v_3d_pval( - input_dataset: InputPathType, - zscore: bool = False, - log2: bool = False, - log10: bool = False, - qval: bool = False, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dPvalOutputs: - """ - Convert a dataset's statistical sub-bricks to p-values or other statistical - representations. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g., InputDataset.nii). - zscore: Convert statistic to a z-score instead, an N(0,1) deviate that\ - represents the same p-value. - log2: Convert statistic to -log2(p). - log10: Convert statistic to -log10(p). - qval: Convert statistic to a q-value (FDR) instead. This option only\ - works with datasets that have FDR curves inserted in their headers. - prefix: Prefix name for output file (default name is 'Pval'). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPvalOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_PVAL_METADATA) - cargs = [] - cargs.append("3dPval") - cargs.append(execution.input_file(input_dataset)) - if zscore: - cargs.append("-zscore") - if log2: - cargs.append("-log2") - if log10: - cargs.append("-log10") - if qval: - cargs.append("-qval") - cargs.append("-prefix") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = V3dPvalOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPvalOutputs", - "V_3D_PVAL_METADATA", - "v_3d_pval", -] diff --git a/python/src/niwrap/afni/v_3d_pvmap.py b/python/src/niwrap/afni/v_3d_pvmap.py deleted file mode 100644 index 159e2ac2a..000000000 --- a/python/src/niwrap/afni/v_3d_pvmap.py +++ /dev/null @@ -1,87 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_PVMAP_METADATA = Metadata( - id="700496e9e3cf92a89b9939044ee84ddeec463b04.boutiques", - name="3dPVmap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dPvmapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_pvmap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outbrik: OutputPathType | None - """Output PVmap file""" - outhead: OutputPathType | None - """Output PVmap header file""" - pc_vectors: OutputPathType | None - """Principal component time series vectors""" - - -def v_3d_pvmap( - inputdataset: InputPathType, - prefix: str | None = None, - mask: InputPathType | None = None, - automask: bool = False, - runner: Runner | None = None, -) -> V3dPvmapOutputs: - """ - Computes the first two principal component vectors of a time series dataset, - then outputs the R-squared coefficient of each voxel time series with these - first two components. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inputdataset: Input dataset (e.g., fred.nii). - prefix: Output prefix for generated files. - mask: Mask dataset (e.g., brainmask.nii). - automask: Automatically generate a mask from the input dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dPvmapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_PVMAP_METADATA) - cargs = [] - cargs.append("3dPVmap") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - cargs.append(execution.input_file(inputdataset)) - ret = V3dPvmapOutputs( - root=execution.output_file("."), - outbrik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - outhead=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - pc_vectors=execution.output_file(prefix + ".1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dPvmapOutputs", - "V_3D_PVMAP_METADATA", - "v_3d_pvmap", -] diff --git a/python/src/niwrap/afni/v_3d_qwarp.py b/python/src/niwrap/afni/v_3d_qwarp.py deleted file mode 100644 index 9050f99b0..000000000 --- a/python/src/niwrap/afni/v_3d_qwarp.py +++ /dev/null @@ -1,147 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_QWARP_METADATA = Metadata( - id="b31e14a7b7123e83340819abf222feefbe217a71.boutiques", - name="3dQwarp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dQwarpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_qwarp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warped_dataset: OutputPathType - """Warped dataset""" - warp_dataset: OutputPathType - """Warp dataset""" - inverse_warp_dataset: OutputPathType - """Inverse warp dataset""" - - -def v_3d_qwarp( - base_dataset: InputPathType, - source_dataset: InputPathType, - prefix: str, - no_warp: bool = False, - inverse_warp: bool = False, - no_dataset: bool = False, - a_warp: bool = False, - pcl: bool = False, - pear: bool = False, - hel: bool = False, - mi: bool = False, - nmi: bool = False, - lpc: bool = False, - lpa: bool = False, - noneg: bool = False, - nopenalty: bool = False, - minpatch: float | None = None, - maxlev: float | None = None, - verbose: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dQwarpOutputs: - """ - Computes a nonlinearly warped version of source_dataset to match base_dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base_dataset: Base dataset. - source_dataset: Source dataset. - prefix: Prefix for the output datasets. - no_warp: Do not save the _WARP file. - inverse_warp: Compute and save the _WARPINV file. - no_dataset: Do not save the warped source dataset. - a_warp: Output the nonlinear warp when -allineate is used. - pcl: Clipped Pearson correlation (default method). - pear: Use strict Pearson correlation for matching. - hel: Use Hellinger metric for matching. - mi: Use Mutual Information for matching. - nmi: Use Normalized Mutual Information for matching. - lpc: Use Local Pearson correlation (signed) for matching. - lpa: Use Local Pearson correlation (absolute value) for matching. - noneg: Replace negative values in either input volume with 0. - nopenalty: Don't use a penalty on the cost functional. - minpatch: Set the minimum patch size for warp searching. - maxlev: Set the maximum refinement level. - verbose: Print out very verbose progress messages. - quiet: Cut out most progress messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dQwarpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_QWARP_METADATA) - cargs = [] - cargs.append("3dQwarp") - cargs.append(execution.input_file(base_dataset)) - cargs.append(execution.input_file(source_dataset)) - cargs.append(prefix) - if no_warp: - cargs.append("-nowarp") - if inverse_warp: - cargs.append("-iwarp") - if no_dataset: - cargs.append("-nodset") - if a_warp: - cargs.append("-awarp") - if pcl: - cargs.append("-pcl") - if pear: - cargs.append("-pear") - if hel: - cargs.append("-hel") - if mi: - cargs.append("-mi") - if nmi: - cargs.append("-nmi") - if lpc: - cargs.append("-lpc") - if lpa: - cargs.append("-lpa") - if noneg: - cargs.append("-noneg") - if nopenalty: - cargs.append("-nopenalty") - if minpatch is not None: - cargs.extend([ - "-minpatch", - str(minpatch) - ]) - if maxlev is not None: - cargs.extend([ - "-maxlev", - str(maxlev) - ]) - if verbose: - cargs.append("-verb") - if quiet: - cargs.append("-quiet") - ret = V3dQwarpOutputs( - root=execution.output_file("."), - warped_dataset=execution.output_file("{PREFIX}+tlrc"), - warp_dataset=execution.output_file("{PREFIX}_WARP+tlrc"), - inverse_warp_dataset=execution.output_file("{PREFIX}_WARPINV+tlrc"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dQwarpOutputs", - "V_3D_QWARP_METADATA", - "v_3d_qwarp", -] diff --git a/python/src/niwrap/afni/v_3d_rank.py b/python/src/niwrap/afni/v_3d_rank.py deleted file mode 100644 index 920f35110..000000000 --- a/python/src/niwrap/afni/v_3d_rank.py +++ /dev/null @@ -1,87 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RANK_METADATA = Metadata( - id="f24b152482b10fa0b6611d0411ec1b16078a8ea8.boutiques", - name="3dRank", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRankOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_rank(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset_head: OutputPathType | None - """Main output dataset in AFNI format (.HEAD file)""" - output_dataset_brik: OutputPathType | None - """Main output dataset in AFNI format (.BRIK file)""" - rank_map_file: OutputPathType | None - """Rank map 1D file showing the mapping from the rank to the integral values - in the input dataset""" - - -def v_3d_rank( - input_datasets: list[InputPathType], - output_prefix: str | None = None, - version_info: bool = False, - help_info: bool = False, - runner: Runner | None = None, -) -> V3dRankOutputs: - """ - Replaces voxel values by their rank in the set of values collected over all - voxels in all input datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_datasets: Input datasets. Acceptable data types are: byte, short,\ - and floats. - output_prefix: Output prefix. If you have multiple datasets on input,\ - the prefix is preceded by r00., r01., etc. If no prefix is given, the\ - default is rank.DATASET1, rank.DATASET2, etc. - version_info: Print author and version info. - help_info: Print this help screen. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRankOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RANK_METADATA) - cargs = [] - cargs.append("3dRank") - cargs.extend([execution.input_file(f) for f in input_datasets]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if version_info: - cargs.append("-ver") - if help_info: - cargs.append("-help") - ret = V3dRankOutputs( - root=execution.output_file("."), - output_dataset_head=execution.output_file(output_prefix + "*.HEAD") if (output_prefix is not None) else None, - output_dataset_brik=execution.output_file(output_prefix + "*.BRIK") if (output_prefix is not None) else None, - rank_map_file=execution.output_file(output_prefix + "*.1D") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRankOutputs", - "V_3D_RANK_METADATA", - "v_3d_rank", -] diff --git a/python/src/niwrap/afni/v_3d_rankizer.py b/python/src/niwrap/afni/v_3d_rankizer.py deleted file mode 100644 index 5e1166655..000000000 --- a/python/src/niwrap/afni/v_3d_rankizer.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RANKIZER_METADATA = Metadata( - id="e854a99a853a99ed471d7da08fb007bec90426d2.boutiques", - name="3dRankizer", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRankizerOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_rankizer(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output float-format dataset containing ranked voxel values""" - - -def v_3d_rankizer( - dataset: InputPathType, - prefix: str, - base_rank: float | None = None, - mask: InputPathType | None = None, - percentize: bool = False, - percentize_mask: bool = False, - runner: Runner | None = None, -) -> V3dRankizerOutputs: - """ - Tool to rank each voxel as sorted into increasing value. Ties get the average - rank. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input MRI dataset. - prefix: Write results into float-format output dataset. - base_rank: Set the 'base' rank instead of 1. - mask: Use the specified dataset as a mask. Only voxels with nonzero\ - values in this mask will be used from the input dataset. Voxels outside\ - the mask will get rank 0. - percentize: Divide rank by the number of voxels in the dataset and\ - multiply by 100.0. - percentize_mask: Divide rank by the number of voxels in the mask and\ - multiply by 100.0. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRankizerOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RANKIZER_METADATA) - cargs = [] - cargs.append("3dRankizer") - cargs.append(execution.input_file(dataset)) - if base_rank is not None: - cargs.extend([ - "-brank", - str(base_rank) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if percentize: - cargs.append("-percentize") - if percentize_mask: - cargs.append("-percentize_mask") - ret = V3dRankizerOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+tlrc.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRankizerOutputs", - "V_3D_RANKIZER_METADATA", - "v_3d_rankizer", -] diff --git a/python/src/niwrap/afni/v_3d_re_ho.py b/python/src/niwrap/afni/v_3d_re_ho.py deleted file mode 100644 index a2c99bd9d..000000000 --- a/python/src/niwrap/afni/v_3d_re_ho.py +++ /dev/null @@ -1,169 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RE_HO_METADATA = Metadata( - id="dda32945e21f34bdcf109d39ffa140b210c47ae4.boutiques", - name="3dReHo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dReHoOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_re_ho(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - reho_output: OutputPathType - """Output file containing ReHo/Kendall's W value per voxel.""" - roi_reho_vals: OutputPathType - """List of ROI ReHo values.""" - chi_square: OutputPathType - """Optional output subbrick containing Friedman chi-square value per - voxel.""" - roi_chi_vals: OutputPathType - """ROI Chi-square values file.""" - - -def v_3d_re_ho( - prefix: str, - inset: InputPathType, - nneigh: str | None = None, - chi_sq: bool = False, - mask: InputPathType | None = None, - neigh_rad: float | None = None, - neigh_x: float | None = None, - neigh_y: float | None = None, - neigh_z: float | None = None, - box_rad: float | None = None, - box_x: float | None = None, - box_y: float | None = None, - box_z: float | None = None, - in_rois: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dReHoOutputs: - """ - 3dReHo calculates Kendall's W per voxel using neighborhood voxels from 4D time - series data set. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name part. - inset: Time series input file. - nneigh: Number of voxels in neighborhood, inclusive; can be 7 (for\ - facewise neighbors), 19 (for face- and edge-wise neighbors), 27 (for\ - face-, edge-, and node-wise neighbors). Default is 27. - chi_sq: Switch to output Friedman chi-square value per voxel as a\ - subbrick. - mask: Include a whole brain mask within which to calculate ReHo.\ - Otherwise, data should be masked already. - neigh_rad: Radius R of a desired neighborhood for voxelwise control,\ - must be a floating point number >1. Examples: R=2.0 -> V=33, R=2.3 ->\ - V=57, etc. - neigh_x: Semi-radius length A for ellipsoidal neighborhood. - neigh_y: Semi-radius length B for ellipsoidal neighborhood. - neigh_z: Semi-radius length C for ellipsoidal neighborhood. - box_rad: Cubic box radius BR centered on a given voxel for neighborhood\ - control. Examples: BR=1 -> V=27, BR=2 -> V=125, etc. - box_x: Box volume neighborhood dimension X. Values put in get added in\ - the +/- directions of each axis. - box_y: Box volume neighborhood dimension Y. Values put in get added in\ - the +/- directions of each axis. - box_z: Box volume neighborhood dimension Z. Values put in get added in\ - the +/- directions of each axis. - in_rois: Input a set of ROIs, each labeled with distinct integers. ReHo\ - will be calculated per ROI. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dReHoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RE_HO_METADATA) - cargs = [] - cargs.append("3dReHo") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-inset") - cargs.append(execution.input_file(inset)) - if nneigh is not None: - cargs.extend([ - "-nneigh", - nneigh - ]) - if chi_sq: - cargs.append("-chi_sq") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if neigh_rad is not None: - cargs.extend([ - "-neigh_RAD", - str(neigh_rad) - ]) - if neigh_x is not None: - cargs.extend([ - "-neigh_X", - str(neigh_x) - ]) - if neigh_y is not None: - cargs.extend([ - "-neigh_Y", - str(neigh_y) - ]) - if neigh_z is not None: - cargs.extend([ - "-neigh_Z", - str(neigh_z) - ]) - if box_rad is not None: - cargs.extend([ - "-box_RAD", - str(box_rad) - ]) - if box_x is not None: - cargs.extend([ - "-box_X", - str(box_x) - ]) - if box_y is not None: - cargs.extend([ - "-box_Y", - str(box_y) - ]) - if box_z is not None: - cargs.extend([ - "-box_Z", - str(box_z) - ]) - if in_rois is not None: - cargs.extend([ - "-in_rois", - execution.input_file(in_rois) - ]) - ret = V3dReHoOutputs( - root=execution.output_file("."), - reho_output=execution.output_file(prefix + "+orig.BRIK"), - roi_reho_vals=execution.output_file(prefix + "_ROI_reho.vals"), - chi_square=execution.output_file(prefix + "+orig.BRIK[1]"), - roi_chi_vals=execution.output_file(prefix + "_ROI_reho.chi"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dReHoOutputs", - "V_3D_RE_HO_METADATA", - "v_3d_re_ho", -] diff --git a/python/src/niwrap/afni/v_3d_reg_ana.py b/python/src/niwrap/afni/v_3d_reg_ana.py deleted file mode 100644 index 025586141..000000000 --- a/python/src/niwrap/afni/v_3d_reg_ana.py +++ /dev/null @@ -1,177 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_REG_ANA_METADATA = Metadata( - id="8af9eec0649daeefe16e2e2f175d5a50fcc2daf0.boutiques", - name="3dRegAna", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRegAnaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_reg_ana(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_fift: OutputPathType - """Output fift dataset""" - output_fith: OutputPathType - """Output fith dataset""" - output_fitt: OutputPathType - """Output fitt dataset""" - output_bucket: OutputPathType - """Output bucket dataset""" - output_bucket_brik: OutputPathType - """Output bucket BRIK file""" - - -def v_3d_reg_ana( - rows: float, - cols: float, - xydata: list[str], - model: str, - diskspace: bool = False, - workmem: float | None = None, - rmsmin: float | None = None, - fdisp: float | None = None, - flof: float | None = None, - fcoef: list[str] | None = None, - rcoef: list[str] | None = None, - tcoef: list[str] | None = None, - bucket: str | None = None, - brick: list[str] | None = None, - datum: str | None = None, - runner: Runner | None = None, -) -> V3dRegAnaOutputs: - """ - Multiple linear regression analysis for AFNI datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - rows: Number of input datasets. - cols: Number of X variables. - xydata: X variables and Y observations. - model: Definition of linear regression model: reduced model (Y =\ - f(Xj1,...,Xjr)) and full model (Y = f(Xj1,...,Xjr,Xi1,...,Xiq)). - diskspace: Print out disk space required for program execution. - workmem: Number of megabytes of RAM to use for statistical workspace\ - (default = 750). - rmsmin: Minimum rms error to reject constant model. - fdisp: Display results for voxels whose F-statistic is > fval. - flof: Minimum p value for F due to lack of fit. - fcoef: Estimate of kth regression coefficient along with F-test for the\ - regression is written to AFNI `fift` dataset. - rcoef: Estimate of kth regression coefficient along with coef. of mult.\ - deter. R^2 is written to AFNI `fith` dataset. - tcoef: Estimate of kth regression coefficient along with t-test for the\ - coefficient is written to AFNI `fitt` dataset. - bucket: Create one AFNI 'bucket' dataset having n sub-bricks; n=0\ - creates default output. - brick: Specify the contents of the mth sub-brick in the bucket dataset. - datum: Write the output in DATUM format. Choose from short (default) or\ - float. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRegAnaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_REG_ANA_METADATA) - cargs = [] - cargs.append("3dRegAna") - cargs.append("-rows") - cargs.extend([ - "-rows", - str(rows) - ]) - cargs.append("-cols") - cargs.extend([ - "-cols", - str(cols) - ]) - cargs.extend([ - "-xydata", - *xydata - ]) - cargs.extend([ - "-model", - model - ]) - if diskspace: - cargs.append("-diskspace") - if workmem is not None: - cargs.extend([ - "-workmem", - str(workmem) - ]) - if rmsmin is not None: - cargs.extend([ - "-rmsmin", - str(rmsmin) - ]) - if fdisp is not None: - cargs.extend([ - "-fdisp", - str(fdisp) - ]) - if flof is not None: - cargs.extend([ - "-flof", - str(flof) - ]) - if fcoef is not None: - cargs.extend([ - "-fcoef", - *fcoef - ]) - if rcoef is not None: - cargs.extend([ - "-rcoef", - *rcoef - ]) - if tcoef is not None: - cargs.extend([ - "-tcoef", - *tcoef - ]) - if bucket is not None: - cargs.extend([ - "-bucket", - bucket - ]) - if brick is not None: - cargs.extend([ - "-brick", - *brick - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - ret = V3dRegAnaOutputs( - root=execution.output_file("."), - output_fift=execution.output_file("[PREFIX].fift+orig.HEAD"), - output_fith=execution.output_file("[PREFIX].fith+orig.HEAD"), - output_fitt=execution.output_file("[PREFIX].fitt+orig.HEAD"), - output_bucket=execution.output_file("[PREFIX].bucket+orig.HEAD"), - output_bucket_brik=execution.output_file("[PREFIX].bucket+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRegAnaOutputs", - "V_3D_REG_ANA_METADATA", - "v_3d_reg_ana", -] diff --git a/python/src/niwrap/afni/v_3d_remlfit.py b/python/src/niwrap/afni/v_3d_remlfit.py deleted file mode 100644 index 978b2f49d..000000000 --- a/python/src/niwrap/afni/v_3d_remlfit.py +++ /dev/null @@ -1,144 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_REMLFIT_METADATA = Metadata( - id="90e07df8872d257e94b52e0a2439cbfa1131aa4d.boutiques", - name="3dREMLfit", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRemlfitOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_remlfit(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Main default output of 3dREMLfit""" - rvar_file: OutputPathType | None - """REML variance parameters""" - rbeta_file: OutputPathType | None - """REML beta weights""" - rbuck_file: OutputPathType | None - """REML estimates and statistics""" - rfitts_file: OutputPathType | None - """REML fitted model""" - rerrts_file: OutputPathType | None - """REML residuals""" - - -def v_3d_remlfit( - input_file: InputPathType, - regression_matrix: InputPathType, - baseline_files: list[str] | None = None, - sort_nods: bool = False, - temp_storage: bool = False, - mask: InputPathType | None = None, - output_prefix: str | None = None, - go_for_it: bool = False, - max_b_param: float | None = None, - grid_param: float | None = None, - negative_corr: bool = False, - runner: Runner | None = None, -) -> V3dRemlfitOutputs: - """ - Generalized least squares time series fit, with REML estimation of the temporal - auto-correlation structure. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Read time series dataset. - regression_matrix: Read the regression matrix, which should have been\ - output from 3dDeconvolve via the '-x1D' option. - baseline_files: Add baseline model columns to the matrix. Each column\ - in the specified .1D file will be appended to the matrix. - sort_nods: If '-dsort' is used, the output datasets reflect the impact\ - of the voxel-wise regressor(s). If you want to compare those results to\ - the case where you did NOT give the '-dsort' option, then also use\ - '-dsort_nods'. - temp_storage: Write intermediate output to disk, to economize on RAM. - mask: Read dataset as a mask for the input; voxels outside the mask\ - will not be fit by the regression model. - output_prefix: Dataset prefix for saving REML variance parameters. - go_for_it: Force the program to continue past a failed collinearity\ - check. - max_b_param: Set max allowed MA b parameter. - grid_param: Set the number of grid divisions in the (a,b) grid. - negative_corr: Allows negative correlations to be used. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRemlfitOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_REMLFIT_METADATA) - cargs = [] - cargs.append("3dREMLfit") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - cargs.extend([ - "-matrix", - execution.input_file(regression_matrix) - ]) - if baseline_files is not None: - cargs.extend([ - "-addbase", - *baseline_files - ]) - if sort_nods: - cargs.append("-dsort_nods") - if temp_storage: - cargs.append("-usetemp") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if output_prefix is not None: - cargs.extend([ - "-Rvar", - output_prefix - ]) - if go_for_it: - cargs.append("-GOFORIT") - if max_b_param is not None: - cargs.extend([ - "-MAXb", - str(max_b_param) - ]) - if grid_param is not None: - cargs.extend([ - "-Grid", - str(grid_param) - ]) - if negative_corr: - cargs.append("-NEGcor") - ret = V3dRemlfitOutputs( - root=execution.output_file("."), - outfile=execution.output_file(output_prefix + ".nii.gz") if (output_prefix is not None) else None, - rvar_file=execution.output_file(output_prefix + "_Rvar.nii.gz") if (output_prefix is not None) else None, - rbeta_file=execution.output_file(output_prefix + "_Rbeta.nii.gz") if (output_prefix is not None) else None, - rbuck_file=execution.output_file(output_prefix + "_Rbuck.nii.gz") if (output_prefix is not None) else None, - rfitts_file=execution.output_file(output_prefix + "_Rfitts.nii.gz") if (output_prefix is not None) else None, - rerrts_file=execution.output_file(output_prefix + "_Rerrts.nii.gz") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRemlfitOutputs", - "V_3D_REMLFIT_METADATA", - "v_3d_remlfit", -] diff --git a/python/src/niwrap/afni/v_3d_retino_phase.py b/python/src/niwrap/afni/v_3d_retino_phase.py deleted file mode 100644 index 43046a686..000000000 --- a/python/src/niwrap/afni/v_3d_retino_phase.py +++ /dev/null @@ -1,172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RETINO_PHASE_METADATA = Metadata( - id="3db78d8b872cbcd25d2278819aa85d3e6ecbba57.boutiques", - name="3dRetinoPhase", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRetinoPhaseOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_retino_phase(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - ecc_plus: OutputPathType - """Output file for positive (expanding) eccentricity""" - ecc_minus: OutputPathType - """Output file for negative (contracting) eccentricity""" - pol_plus: OutputPathType - """Output file for clockwise polar angle mapping""" - pol_minus: OutputPathType - """Output file for counterclockwise polar angle mapping""" - - -def v_3d_retino_phase( - prefix: str, - dataset: InputPathType, - exp: str | None = None, - con: str | None = None, - clw: str | None = None, - ccw: str | None = None, - spectra: bool = False, - tstim: float | None = None, - nrings: float | None = None, - nwedges: float | None = None, - ort_adjust: float | None = None, - pre_stim: float | None = None, - sum_adjust: str | None = None, - phase_estimate: str | None = None, - ref_ts: InputPathType | None = None, - multi_ref_ts: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dRetinoPhaseOutputs: - """ - Process time series from retinotopy stimuli to create phase datasets and visual - field angle datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix of output datasets. - dataset: Time series from a retinotopy stimulus. - exp: Expanding rings stimulus. - con: Contracting rings stimulus. - clw: Clockwise moving polar angle mapping stimulus. - ccw: Counterclockwise moving polar angle mapping stimulus. - spectra: Output amplitude and phase spectra datasets. - tstim: Period of stimulus in seconds. - nrings: Number of rings in the stimulus. Default is 1. - nwedges: Number of wedges in the stimulus. Default is 1. - ort_adjust: Number of DOF lost in detrending outside of this program. - pre_stim: Blank period, in seconds, before stimulus began. - sum_adjust: Adjust sum of angles for wrapping based on the angle\ - difference. Default is 'y'. - phase_estimate: Method of phase estimation. - ref_ts: 0 lag reference time series of response for DELAY phase\ - estimation method. - multi_ref_ts: Multiple 0 lag reference time series. This allows you to\ - test multiple regressors. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRetinoPhaseOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RETINO_PHASE_METADATA) - cargs = [] - cargs.append("3dRetinoPhase") - cargs.append(prefix) - cargs.append(execution.input_file(dataset)) - if exp is not None: - cargs.extend([ - "-exp", - exp - ]) - if con is not None: - cargs.extend([ - "-con", - con - ]) - if clw is not None: - cargs.extend([ - "-clw", - clw - ]) - if ccw is not None: - cargs.extend([ - "-ccw", - ccw - ]) - if spectra: - cargs.append("-spectra") - if tstim is not None: - cargs.extend([ - "-Tstim", - str(tstim) - ]) - if nrings is not None: - cargs.extend([ - "-nrings", - str(nrings) - ]) - if nwedges is not None: - cargs.extend([ - "-nwedges", - str(nwedges) - ]) - if ort_adjust is not None: - cargs.extend([ - "-ort_adjust", - str(ort_adjust) - ]) - if pre_stim is not None: - cargs.extend([ - "-pre_stim", - str(pre_stim) - ]) - if sum_adjust is not None: - cargs.extend([ - "-sum_adjust", - sum_adjust - ]) - if phase_estimate is not None: - cargs.extend([ - "-phase_estimate", - phase_estimate - ]) - if ref_ts is not None: - cargs.extend([ - "-ref_ts", - execution.input_file(ref_ts) - ]) - if multi_ref_ts is not None: - cargs.extend([ - "-multi_ref_ts", - execution.input_file(multi_ref_ts) - ]) - ret = V3dRetinoPhaseOutputs( - root=execution.output_file("."), - ecc_plus=execution.output_file(prefix + ".ecc+"), - ecc_minus=execution.output_file(prefix + ".ecc-"), - pol_plus=execution.output_file(prefix + ".pol+"), - pol_minus=execution.output_file(prefix + ".pol-"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRetinoPhaseOutputs", - "V_3D_RETINO_PHASE_METADATA", - "v_3d_retino_phase", -] diff --git a/python/src/niwrap/afni/v_3d_roistats.py b/python/src/niwrap/afni/v_3d_roistats.py deleted file mode 100644 index 59bf653f8..000000000 --- a/python/src/niwrap/afni/v_3d_roistats.py +++ /dev/null @@ -1,162 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ROISTATS_METADATA = Metadata( - id="42c325b0e5191cea0a53e686cc2eaab286bb4cf2.boutiques", - name="3dROIstats", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRoistatsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_roistats(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output file.""" - out_file_: OutputPathType - """Output tab-separated values file.""" - - -def v_3d_roistats( - in_file: InputPathType, - mask: InputPathType | None = None, - debug: bool = False, - format1_d: bool = False, - format1_dr: bool = False, - mask_f2short: bool = False, - mask_file: InputPathType | None = None, - nobriklab: bool = False, - nomeanout: bool = False, - num_roi: int | None = None, - quiet: bool = False, - roisel: InputPathType | None = None, - stat_: list[InputPathType] | None = None, - zerofill: str | None = None, - runner: Runner | None = None, -) -> V3dRoistatsOutputs: - """ - Display statistics over masked regions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input dataset. - mask: Input mask. - debug: Print debug information. - format1_d: Output results in a 1d format that includes commented\ - labels. - format1_dr: Output results in a 1d format that includes uncommented\ - labels. may not work optimally with typical 1d functions, but is useful\ - for r functions. - mask_f2short: Tells the program to convert a float mask to short\ - integers, by simple rounding. - mask_file: Input mask. - nobriklab: Do not print the sub-brick label next to its index. - nomeanout: Do not include the (zero-inclusive) mean among computed\ - stats. - num_roi: Forces the assumption that the mask dataset's rois are denoted\ - by 1 to n inclusive. normally, the program figures out the rois on its\ - own. this option is useful if a) you are certain that the mask dataset\ - has no values outside the range [0 n], b) there may be some rois\ - missing between [1 n] in the mask data-set and c) you want those\ - columns in the output any-way so the output lines up with the output\ - from other invocations of 3droistats. - quiet: Execute quietly. - roisel: Only considers rois denoted by values found in the specified\ - file. note that the order of the rois as specified in the file is not\ - preserved. so an sel.1d of '2 8 20' produces the same output as '8 20\ - 2'. - stat_: A list of items which are 'mean' or 'sum' or 'voxels' or\ - 'minmax' or 'sigma' or 'median' or 'mode' or 'summary' or 'zerominmax'\ - or 'zerosigma' or 'zeromedian' or 'zeromode'. Statistics to compute.\ - options include: * mean = compute the mean using only non_zero voxels.\ - implies the opposite for the mean computed by default. * median =\ - compute the median of nonzero voxels * mode = compute the mode of\ - nonzero voxels. (integral valued sets only) * minmax = compute the\ - min/max of nonzero voxels * sum = compute the sum using only nonzero\ - voxels. * voxels = compute the number of nonzero voxels * sigma =\ - compute the standard deviation of nonzero voxelsstatistics that include\ - zero-valued voxels: * zerominmax = compute the min/max of all voxels. *\ - zerosigma = compute the standard deviation of all voxels. * zeromedian\ - = compute the median of all voxels. * zeromode = compute the mode of\ - all voxels. * summary = only output a summary line with the grand mean\ - across all briks in the input dataset. this option cannot be used with\ - nomeanout.more that one option can be specified. - zerofill: For roi labels not found, use the provided string instead of\ - a '0' in the output file. only active if `num_roi` is enabled. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRoistatsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ROISTATS_METADATA) - cargs = [] - cargs.append("3dROIstats") - cargs.append(execution.input_file(in_file)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("[OUT_FILE]") - if debug: - cargs.append("-debug") - if format1_d: - cargs.append("-1Dformat") - if format1_dr: - cargs.append("-1DRformat") - if mask_f2short: - cargs.append("-mask_f2short") - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - if nobriklab: - cargs.append("-nobriklab") - if nomeanout: - cargs.append("-nomeanout") - if num_roi is not None: - cargs.extend([ - "-numroi", - str(num_roi) - ]) - if quiet: - cargs.append("-quiet") - if roisel is not None: - cargs.extend([ - "-roisel", - execution.input_file(roisel) - ]) - if stat_ is not None: - cargs.extend([execution.input_file(f) for f in stat_]) - if zerofill is not None: - cargs.extend([ - "-zerofill", - zerofill - ]) - ret = V3dRoistatsOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_roistat.1D"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRoistatsOutputs", - "V_3D_ROISTATS_METADATA", - "v_3d_roistats", -] diff --git a/python/src/niwrap/afni/v_3d_row_fillin.py b/python/src/niwrap/afni/v_3d_row_fillin.py deleted file mode 100644 index ed2845292..000000000 --- a/python/src/niwrap/afni/v_3d_row_fillin.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ROW_FILLIN_METADATA = Metadata( - id="216cbd8c6bdc4939ecc4b570de017d7e915867b9.boutiques", - name="3dRowFillin", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRowFillinOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_row_fillin(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType | None - """Output dataset in BRIK format""" - output_head: OutputPathType | None - """Output dataset in HEAD format""" - - -def v_3d_row_fillin( - input_dataset: InputPathType, - maxgap: float | None = None, - dir_: str | None = None, - binary: bool = False, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dRowFillinOutputs: - """ - Fills in blank regions in 1D rows extracted from a 3D dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input 3D dataset (e.g., dataset+orig). - maxgap: Set the maximum length of a blank region that will be filled in. - dir_: Set the direction of fill, e.g., A-P, P-A, I-S, S-I, L-R, R-L, x,\ - y, z, XYZ.OR, XYZ.AND. - binary: Turn input dataset to binary (0 and 1) before filling in.\ - Output will also be binary. - prefix: Set the prefix for the output dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRowFillinOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ROW_FILLIN_METADATA) - cargs = [] - cargs.append("3dRowFillin") - if maxgap is not None: - cargs.extend([ - "-maxgap", - str(maxgap) - ]) - if dir_ is not None: - cargs.extend([ - "-dir", - dir_ - ]) - if binary: - cargs.append("-binary") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append(execution.input_file(input_dataset)) - ret = V3dRowFillinOutputs( - root=execution.output_file("."), - output_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - output_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRowFillinOutputs", - "V_3D_ROW_FILLIN_METADATA", - "v_3d_row_fillin", -] diff --git a/python/src/niwrap/afni/v_3d_rprog_demo.py b/python/src/niwrap/afni/v_3d_rprog_demo.py deleted file mode 100644 index 10393c997..000000000 --- a/python/src/niwrap/afni/v_3d_rprog_demo.py +++ /dev/null @@ -1,113 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RPROG_DEMO_METADATA = Metadata( - id="0022cdac85c42f7bbf65ae09bb726c5230da1a47.boutiques", - name="3dRprogDemo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRprogDemoOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_rprog_demo(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output file with the specified prefix.""" - - -def v_3d_rprog_demo( - input_dsets: list[InputPathType], - scale: float, - prefix: str, - mask: InputPathType | None = None, - help_aspx: bool = False, - help_raw: bool = False, - help_spx: bool = False, - help_txt: bool = False, - help_: bool = False, - show_allowed_options: bool = False, - verbosity_level: float | None = None, - runner: Runner | None = None, -) -> V3dRprogDemoOutputs: - """ - Template program to help users write their own R processing routines on MRI - volumes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dsets: Input dataset(s) to be scaled. - scale: Multiply each voxel by SS. - prefix: Output prefix (just prefix, no view+suffix needed). - mask: Process voxels inside this mask only. Default is no masking. - help_aspx: Display help message with autolabeling. - help_raw: Display raw help message as in the code. - help_spx: Display help message in sphinx format. - help_txt: Display help message in simple text. - help_: Display help message in simple text. - show_allowed_options: List of allowed options. - verbosity_level: Verbosity level. 0 for quiet (Default). 1 or more:\ - talkative. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRprogDemoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RPROG_DEMO_METADATA) - cargs = [] - cargs.append("3dRprogDemo") - cargs.extend([execution.input_file(f) for f in input_dsets]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.extend([ - "-scale", - str(scale) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if help_aspx: - cargs.append("-h_aspx") - if help_raw: - cargs.append("-h_raw") - if help_spx: - cargs.append("-h_spx") - if help_txt: - cargs.append("-h_txt") - if help_: - cargs.append("-help") - if show_allowed_options: - cargs.append("-show_allowed_options") - if verbosity_level is not None: - cargs.extend([ - "-verb", - str(verbosity_level) - ]) - ret = V3dRprogDemoOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRprogDemoOutputs", - "V_3D_RPROG_DEMO_METADATA", - "v_3d_rprog_demo", -] diff --git a/python/src/niwrap/afni/v_3d_rsfc.py b/python/src/niwrap/afni/v_3d_rsfc.py deleted file mode 100644 index b1f78421a..000000000 --- a/python/src/niwrap/afni/v_3d_rsfc.py +++ /dev/null @@ -1,72 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_RSFC_METADATA = Metadata( - id="6ce9640d970ae6c3fe9057ee6cdd1cbb5363c7cb.boutiques", - name="3dRSFC", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dRsfcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_rsfc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - filtered_time_series: OutputPathType - """Filtered time series output""" - un_bandpassed_series: OutputPathType - """Un-bandpassed series output""" - - -def v_3d_rsfc( - fbot: float, - ftop: float, - input_dataset: InputPathType, - runner: Runner | None = None, -) -> V3dRsfcOutputs: - """ - Program to calculate common resting state functional connectivity (RSFC) - parameters. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fbot: Lowest frequency in the passband, in Hz. - ftop: Highest frequency in the passband (must be > fbot). - input_dataset: Input dataset (3D+time sequence of volumes). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dRsfcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_RSFC_METADATA) - cargs = [] - cargs.append("3dRSFC") - cargs.append("[OPTIONS]") - cargs.append(str(fbot)) - cargs.append(str(ftop)) - cargs.append(execution.input_file(input_dataset)) - ret = V3dRsfcOutputs( - root=execution.output_file("."), - filtered_time_series=execution.output_file("[PREFIX]_LFF+orig.*"), - un_bandpassed_series=execution.output_file("[PREFIX]_unBP+orig.*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dRsfcOutputs", - "V_3D_RSFC_METADATA", - "v_3d_rsfc", -] diff --git a/python/src/niwrap/afni/v_3d_seg.py b/python/src/niwrap/afni/v_3d_seg.py deleted file mode 100644 index a103926a5..000000000 --- a/python/src/niwrap/afni/v_3d_seg.py +++ /dev/null @@ -1,217 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SEG_METADATA = Metadata( - id="3bd6f94c8da11d9b229d06d9fdc731915ae9d41f.boutiques", - name="3dSeg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSegOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_seg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - segmented_volume: OutputPathType | None - """Segmented brain volume output""" - bias_field: OutputPathType | None - """Bias field estimate output""" - classified_volume: OutputPathType | None - """Classified volume output""" - - -def v_3d_seg( - anat: InputPathType, - mask: str | None = None, - blur_meth: str | None = None, - bias_fwhm: float | None = None, - classes: str | None = None, - bmrf: float | None = None, - bias_classes: str | None = None, - prefix: str | None = None, - overwrite: bool = False, - debug: float | None = None, - mixfrac: str | None = None, - mixfloor: float | None = None, - gold: InputPathType | None = None, - gold_bias: InputPathType | None = None, - main_n: float | None = None, - cset: InputPathType | None = None, - labeltable: InputPathType | None = None, - vox_debug: str | None = None, - vox_debug_file: str | None = None, - runner: Runner | None = None, -) -> V3dSegOutputs: - """ - Segments brain volumes into tissue classes with optional global and voxelwise - priors. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - anat: Volume to segment. - mask: Mask of the volume to be segmented. Can be a dataset or 'AUTO' to\ - use AFNI's automask function. - blur_meth: Blurring method for bias field estimation. Options: BFT,\ - BIM, BNN, LSB. Default: BFT. - bias_fwhm: The amount of blurring used when estimating the field bias.\ - Default: 25.0. - classes: String of class labels separated by semicolons. Default: 'CSF;\ - GM; WM'. - bmrf: Weighting factor controlling spatial homogeneity of\ - classifications. Default: 0.0. - bias_classes: Classes that contribute to the estimation of the bias\ - field. Default: 'GM; WM'. - prefix: Prefix for all output volume. - overwrite: Automatically overwrite existing files with the same prefix. - debug: Set debug level (0, 1, or 2). - mixfrac: Volume-wide mixing fractions for initialization. Options: '0.1\ - 0.45 0.45', 'UNI', 'AVG152_BRAIN_MASK', 'IGNORE'. Default: UNI. - mixfloor: Set the minimum value for any class's mixing fraction.\ - Default: 0.0001. - gold: Goldstandard segmentation volume for comparison. - gold_bias: Goldstandard bias volume for comparison. - main_n: Number of iterations to perform. Default: 5. - cset: Initial classification. Uses 3dkmean's engine if not provided. - labeltable: Label table containing integer keys and corresponding\ - labels. - vox_debug: 1D index of voxel to debug or 3D voxel indices. - vox_debug_file: File in which debug information is output, use '-' for\ - stdout, '+' for stderr. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSegOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SEG_METADATA) - cargs = [] - cargs.append("3dSeg") - cargs.append("-anat") - cargs.append(execution.input_file(anat)) - cargs.append("-mask") - if mask is not None: - cargs.append(mask) - cargs.append("-blur_meth") - if blur_meth is not None: - cargs.extend([ - "-blur_meth", - blur_meth - ]) - cargs.append("-bias_fwhm") - if bias_fwhm is not None: - cargs.extend([ - "-bias_fwhm", - str(bias_fwhm) - ]) - cargs.append("-classes") - if classes is not None: - cargs.extend([ - "-classes", - classes - ]) - cargs.append("-Bmrf") - if bmrf is not None: - cargs.extend([ - "-Bmrf", - str(bmrf) - ]) - cargs.append("-bias_classes") - if bias_classes is not None: - cargs.extend([ - "-bias_classes", - bias_classes - ]) - cargs.append("-prefix") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-overwrite") - if overwrite: - cargs.append("-overwrite") - cargs.append("-debug") - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - cargs.append("-mixfrac") - if mixfrac is not None: - cargs.extend([ - "-mixfrac", - mixfrac - ]) - cargs.append("-mixfloor") - if mixfloor is not None: - cargs.extend([ - "-mixfloor", - str(mixfloor) - ]) - cargs.append("-gold") - if gold is not None: - cargs.extend([ - "-gold", - execution.input_file(gold) - ]) - cargs.append("-gold_bias") - if gold_bias is not None: - cargs.extend([ - "-gold_bias", - execution.input_file(gold_bias) - ]) - cargs.append("-main_N") - if main_n is not None: - cargs.extend([ - "-main_N", - str(main_n) - ]) - cargs.append("-cset") - if cset is not None: - cargs.extend([ - "-cset", - execution.input_file(cset) - ]) - cargs.append("-labeltable") - if labeltable is not None: - cargs.extend([ - "-labeltable", - execution.input_file(labeltable) - ]) - cargs.append("-vox_debug") - if vox_debug is not None: - cargs.extend([ - "-vox_debug", - vox_debug - ]) - cargs.append("-vox_debug_file") - if vox_debug_file is not None: - cargs.extend([ - "-vox_debug_file", - vox_debug_file - ]) - ret = V3dSegOutputs( - root=execution.output_file("."), - segmented_volume=execution.output_file(prefix + "_Segsy+orig.HEAD") if (prefix is not None) else None, - bias_field=execution.output_file(prefix + "_BiasField+orig.HEAD") if (prefix is not None) else None, - classified_volume=execution.output_file(prefix + "_Classes+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSegOutputs", - "V_3D_SEG_METADATA", - "v_3d_seg", -] diff --git a/python/src/niwrap/afni/v_3d_setup_group_in_corr.py b/python/src/niwrap/afni/v_3d_setup_group_in_corr.py deleted file mode 100644 index 6ee21829f..000000000 --- a/python/src/niwrap/afni/v_3d_setup_group_in_corr.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SETUP_GROUP_IN_CORR_METADATA = Metadata( - id="de29e68b50548580e79210d656042b141dbd77c7.boutiques", - name="3dSetupGroupInCorr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSetupGroupInCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_setup_group_in_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - niml_file: OutputPathType - """Text file containing the header information describing the data file.""" - data_file: OutputPathType - """Data file containing all the time series from all the datasets.""" - - -def v_3d_setup_group_in_corr( - datasets: list[InputPathType], - prefix: str, - mask_dataset: InputPathType | None = None, - short_flag: bool = False, - byte_flag: bool = False, - labels_file: InputPathType | None = None, - delete_flag: bool = False, - prep_method: str | None = None, - lr_pairs: list[str] | None = None, - runner: Runner | None = None, -) -> V3dSetupGroupInCorrOutputs: - """ - Pre-process a collection of AFNI 3D+time datasets for use with Group InstaCorr. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: AFNI 3D+time datasets to be processed. - prefix: Prefix for output dataset names. - mask_dataset: Mask dataset for voxel selection. - short_flag: Store data as 16-bit shorts. - byte_flag: Store data as 8-bit bytes. - labels_file: File containing a list of labels for each dataset. - delete_flag: Delete input datasets from disk after processing. - prep_method: Preprocess each data time series with the specified\ - method. - lr_pairs: Set the domains for left and right hemisphere surfaces and\ - indicate that the datasets are arranged in (Left, Right) pairs. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSetupGroupInCorrOutputs`). - """ - if lr_pairs is not None and not (len(lr_pairs) <= 2): - raise ValueError(f"Length of 'lr_pairs' must be less than 2 but was {len(lr_pairs)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SETUP_GROUP_IN_CORR_METADATA) - cargs = [] - cargs.append("3dSetupGroupInCorr") - cargs.extend([execution.input_file(f) for f in datasets]) - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if short_flag: - cargs.append("-short") - if byte_flag: - cargs.append("-byte") - if labels_file is not None: - cargs.extend([ - "-labels", - execution.input_file(labels_file) - ]) - if delete_flag: - cargs.append("-DELETE") - if prep_method is not None: - cargs.extend([ - "-prep", - prep_method - ]) - if lr_pairs is not None: - cargs.extend([ - "-LRpairs", - *lr_pairs - ]) - ret = V3dSetupGroupInCorrOutputs( - root=execution.output_file("."), - niml_file=execution.output_file(prefix + ".grpincorr.niml"), - data_file=execution.output_file(prefix + ".grpincorr.data"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSetupGroupInCorrOutputs", - "V_3D_SETUP_GROUP_IN_CORR_METADATA", - "v_3d_setup_group_in_corr", -] diff --git a/python/src/niwrap/afni/v_3d_sharpen.py b/python/src/niwrap/afni/v_3d_sharpen.py deleted file mode 100644 index 2e5d02610..000000000 --- a/python/src/niwrap/afni/v_3d_sharpen.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SHARPEN_METADATA = Metadata( - id="44eead3d035544b0d1ef18d1ea40f5df1b442bcb.boutiques", - name="3dSharpen", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSharpenOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_sharpen(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Sharpened output dataset.""" - - -def v_3d_sharpen( - input_dataset: InputPathType, - output_prefix: str, - sharpening_factor: float | None = None, - runner: Runner | None = None, -) -> V3dSharpenOutputs: - """ - Applies a simple 3D sharpening filter to the positive values in the #0 volume of - the input dataset, and writes out a new dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g., input.nii.gz). - output_prefix: Name of the output dataset (e.g., output.nii.gz) which\ - will be in floating point format. - sharpening_factor: Sharpening factor, between 0.1 and 0.9 (inclusive).\ - Larger values mean more sharpening. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSharpenOutputs`). - """ - if sharpening_factor is not None and not (0.1 <= sharpening_factor <= 0.9): - raise ValueError(f"'sharpening_factor' must be between 0.1 <= x <= 0.9 but was {sharpening_factor}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SHARPEN_METADATA) - cargs = [] - cargs.append("3dSharpen") - if sharpening_factor is not None: - cargs.extend([ - "-phi", - str(sharpening_factor) - ]) - cargs.append(execution.input_file(input_dataset)) - cargs.extend([ - "-prefix", - output_prefix - ]) - ret = V3dSharpenOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(output_prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSharpenOutputs", - "V_3D_SHARPEN_METADATA", - "v_3d_sharpen", -] diff --git a/python/src/niwrap/afni/v_3d_signatures.py b/python/src/niwrap/afni/v_3d_signatures.py deleted file mode 100644 index 61173f73a..000000000 --- a/python/src/niwrap/afni/v_3d_signatures.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SIGNATURES_METADATA = Metadata( - id="3a8c36dbe73fad66aa2f0bc3b1c2c29ec32ab76b.boutiques", - name="3dSignatures", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSignaturesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_signatures(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - results_file: OutputPathType - """Main analysis results file""" - - -def v_3d_signatures( - infile: InputPathType, - outfile: str, - segmentation: bool = False, - filter_: bool = False, - threshold: float | None = None, - smoothing: float | None = None, - runner: Runner | None = None, -) -> V3dSignaturesOutputs: - """ - 3dSignatures analysis tool for 3D genome organization. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file containing 3D genome data (e.g. genome_data.txt). - outfile: Output file to store analysis results (e.g.\ - analysis_results.txt). - segmentation: Flag to apply genome segmentation. - filter_: Flag to apply data filtering. - threshold: Threshold level for data filtering; default=0.5. - smoothing: Apply smoothing with specified kernel size. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSignaturesOutputs`). - """ - if threshold is not None and not (0 <= threshold <= 1): - raise ValueError(f"'threshold' must be between 0 <= x <= 1 but was {threshold}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SIGNATURES_METADATA) - cargs = [] - cargs.append("3dSignatures") - cargs.append(execution.input_file(infile)) - cargs.append(outfile) - if segmentation: - cargs.append("--segmentation") - if filter_: - cargs.append("--filter") - if threshold is not None: - cargs.extend([ - "--threshold", - str(threshold) - ]) - if smoothing is not None: - cargs.extend([ - "--smoothing", - str(smoothing) - ]) - ret = V3dSignaturesOutputs( - root=execution.output_file("."), - results_file=execution.output_file(outfile + ".txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSignaturesOutputs", - "V_3D_SIGNATURES_METADATA", - "v_3d_signatures", -] diff --git a/python/src/niwrap/afni/v_3d_skull_strip.py b/python/src/niwrap/afni/v_3d_skull_strip.py deleted file mode 100644 index 645286ea0..000000000 --- a/python/src/niwrap/afni/v_3d_skull_strip.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SKULL_STRIP_METADATA = Metadata( - id="9ff59b0414e6f85087ff55c31a85f270361e0af9.boutiques", - name="3dSkullStrip", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSkullStripOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_skull_strip(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_skull_strip( - in_file: InputPathType, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - runner: Runner | None = None, -) -> V3dSkullStripOutputs: - """ - A program to extract the brain from surrounding tissue from MRI T1-weighted - images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dskullstrip. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSkullStripOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SKULL_STRIP_METADATA) - cargs = [] - cargs.append("3dSkullStrip") - cargs.extend([ - "-input", - execution.input_file(in_file) - ]) - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - ret = V3dSkullStripOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_skullstrip"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSkullStripOutputs", - "V_3D_SKULL_STRIP_METADATA", - "v_3d_skull_strip", -] diff --git a/python/src/niwrap/afni/v_3d_slice_ndice.py b/python/src/niwrap/afni/v_3d_slice_ndice.py deleted file mode 100644 index bf18503ca..000000000 --- a/python/src/niwrap/afni/v_3d_slice_ndice.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SLICE_NDICE_METADATA = Metadata( - id="d342ea12e7304645ed3af49b8a60039dae05237d.boutiques", - name="3dSliceNDice", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSliceNdiceOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_slice_ndice(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_rl: OutputPathType - """Output file containing Dice coefficients along the right-left axis.""" - output_ap: OutputPathType - """Output file containing Dice coefficients along the anterior-posterior - axis.""" - output_is: OutputPathType - """Output file containing Dice coefficients along the inferior-superior - axis.""" - - -def v_3d_slice_ndice( - infile_a: InputPathType, - infile_b: InputPathType, - output_prefix: str, - out_domain: typing.Literal["all", "AorB", "AandB", "Amask", "Bmask"] | None = None, - no_cmd_echo: bool = False, - runner: Runner | None = None, -) -> V3dSliceNdiceOutputs: - """ - Calculates the Dice coefficient between two volumes on a slice-by-slice basis. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile_a: Input dataset A (e.g. mask_1.nii.gz). - infile_b: Input dataset B (e.g. mask_2.nii.gz). - output_prefix: Prefix for output files (e.g. result_prefix). - out_domain: Specify which slices to include in the Dice coefficient\ - report. Options are: all (default), AorB, AandB, Amask, Bmask. - no_cmd_echo: Turn OFF recording the command line call in the output\ - *.1D files. Default is to do the recording. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSliceNdiceOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SLICE_NDICE_METADATA) - cargs = [] - cargs.append("3dSliceNDice") - cargs.append("-insetA") - cargs.append(execution.input_file(infile_a)) - cargs.append("-insetB") - cargs.append(execution.input_file(infile_b)) - cargs.append("-prefix") - cargs.append(output_prefix) - if out_domain is not None: - cargs.extend([ - "-out_domain", - out_domain - ]) - if no_cmd_echo: - cargs.append("-no_cmd_echo") - ret = V3dSliceNdiceOutputs( - root=execution.output_file("."), - output_rl=execution.output_file(output_prefix + "_0_RL.1D"), - output_ap=execution.output_file(output_prefix + "_1_AP.1D"), - output_is=execution.output_file(output_prefix + "_2_IS.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSliceNdiceOutputs", - "V_3D_SLICE_NDICE_METADATA", - "v_3d_slice_ndice", -] diff --git a/python/src/niwrap/afni/v_3d_space_time_corr.py b/python/src/niwrap/afni/v_3d_space_time_corr.py deleted file mode 100644 index ee3d4caa8..000000000 --- a/python/src/niwrap/afni/v_3d_space_time_corr.py +++ /dev/null @@ -1,109 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SPACE_TIME_CORR_METADATA = Metadata( - id="e49ac047acfb7ca32e517432f948534977777fb0.boutiques", - name="3dSpaceTimeCorr", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSpaceTimeCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_space_time_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """Output data set with space-time correlation coefficients.""" - - -def v_3d_space_time_corr( - inset_a: InputPathType, - inset_b: InputPathType, - prefix: str, - mask: InputPathType | None = None, - out_zcorr: bool = False, - freeze_inset_a_ijk: list[float] | None = None, - freeze_inset_a_xyz: list[float] | None = None, - runner: Runner | None = None, -) -> V3dSpaceTimeCorrOutputs: - """ - Calculates correlation coefficients between two 4D datasets using space+time - patterns. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset_a: First 4D data set. - inset_b: Second 4D data set. Must have the same spatial dimensions and\ - number of time points as insetA. - prefix: Output filename/base. - mask: Optional mask for calculations. Recommended for speed and\ - interpretability. - out_zcorr: Switch to output Fisher Z transform of spatial map\ - correlation instead of Pearson r values. - freeze_inset_a_ijk: Freeze the seed voxel location in the insetA data\ - set using ijk indices while the seed location in insetB moves\ - throughout the volume or mask. Provide three ijk values. - freeze_inset_a_xyz: Freeze the seed voxel location in the insetA data\ - set using xyz coordinates while the seed location in insetB moves\ - throughout the volume or mask. Provide three xyz values. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSpaceTimeCorrOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SPACE_TIME_CORR_METADATA) - cargs = [] - cargs.append("3dSpaceTimeCorr") - cargs.extend([ - "-insetA", - execution.input_file(inset_a) - ]) - cargs.extend([ - "-insetB", - execution.input_file(inset_b) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if out_zcorr: - cargs.append("-out_Zcorr") - if freeze_inset_a_ijk is not None: - cargs.extend([ - "-freeze_insetA_ijk", - *map(str, freeze_inset_a_ijk) - ]) - if freeze_inset_a_xyz is not None: - cargs.extend([ - "-freeze_insetA_xyz", - *map(str, freeze_inset_a_xyz) - ]) - ret = V3dSpaceTimeCorrOutputs( - root=execution.output_file("."), - output=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSpaceTimeCorrOutputs", - "V_3D_SPACE_TIME_CORR_METADATA", - "v_3d_space_time_corr", -] diff --git a/python/src/niwrap/afni/v_3d_spat_norm.py b/python/src/niwrap/afni/v_3d_spat_norm.py deleted file mode 100644 index a6d8cdd42..000000000 --- a/python/src/niwrap/afni/v_3d_spat_norm.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SPAT_NORM_METADATA = Metadata( - id="d614dd87f9e1a9bb874634386657b6651c14bbe6.boutiques", - name="3dSpatNorm", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSpatNormOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_spat_norm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_head: OutputPathType | None - """Output dataset (HEAD file)""" - out_brik: OutputPathType | None - """Output dataset (BRIK file)""" - - -def v_3d_spat_norm( - dataset: InputPathType, - prefix: str | None = None, - orig_space: bool = False, - verbose: bool = False, - monkey: bool = False, - marmot: bool = False, - rat: bool = False, - human: bool = False, - bottom_cuts: str | None = None, - runner: Runner | None = None, -) -> V3dSpatNormOutputs: - """ - An obsolete tool for spatial normalization. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - prefix: Write output dataset using 'ppp' for the prefix. - orig_space: Write output dataset using the same grid as dataset. - verbose: Write out progress reports. - monkey: Monkey business. - marmot: Marmoset head. - rat: Rat head. - human: Bone head (default). - bottom_cuts: Make approximate cuts at the bottom to shave non-brain\ - areas. CUTFLAGS is a string of characters indicating which sides to\ - cut: 'A' for anterior, 'P' for posterior, 'R' for right, 'L' for left.\ - Example: -bottom_cuts APLR. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSpatNormOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SPAT_NORM_METADATA) - cargs = [] - cargs.append("3dSpatNorm") - cargs.append(execution.input_file(dataset)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if orig_space: - cargs.append("-orig_space") - if verbose: - cargs.append("-verb") - if monkey: - cargs.append("-monkey") - if marmot: - cargs.append("-marmost") - if rat: - cargs.append("-rat") - if human: - cargs.append("-human") - if bottom_cuts is not None: - cargs.extend([ - "-bottom_cuts", - bottom_cuts - ]) - ret = V3dSpatNormOutputs( - root=execution.output_file("."), - out_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - out_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSpatNormOutputs", - "V_3D_SPAT_NORM_METADATA", - "v_3d_spat_norm", -] diff --git a/python/src/niwrap/afni/v_3d_stat_clust.py b/python/src/niwrap/afni/v_3d_stat_clust.py deleted file mode 100644 index 4f821f147..000000000 --- a/python/src/niwrap/afni/v_3d_stat_clust.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_STAT_CLUST_METADATA = Metadata( - id="6a70f7b418a765318fd3dcc97f525db45ce69ab8.boutiques", - name="3dStatClust", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dStatClustOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_stat_clust(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType | None - """Output dataset header""" - output_brick: OutputPathType | None - """Output dataset brick""" - - -def v_3d_stat_clust( - thresh: str, - nclust: float, - datasets: list[str], - prefix: str | None = None, - session_dir: str | None = None, - verbose: bool = False, - dist_cor: bool = False, - runner: Runner | None = None, -) -> V3dStatClustOutputs: - """ - Perform agglomerative hierarchical clustering for user specified parameter - sub-bricks, for all voxels whose threshold statistic is above a user specified - value. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - thresh: Threshold statistic from file tname. Only voxels whose\ - threshold statistic is greater than t in absolute value will be\ - considered. If file tname contains more than 1 sub-brick, the threshold\ - stat. sub-brick must be specified. - nclust: Maximum number of clusters for output (= number of sub-bricks\ - in output dataset). - datasets: Parameter datasets. - prefix: Use 'pname' for the output dataset prefix name. - session_dir: Use 'dir' for the output dataset session directory. - verbose: Print out verbose output as the program proceeds. - dist_cor: Statistical distance for correlated parameters. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dStatClustOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_STAT_CLUST_METADATA) - cargs = [] - cargs.append("3dStatClust") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if session_dir is not None: - cargs.extend([ - "-session", - session_dir - ]) - if verbose: - cargs.append("-verb") - if dist_cor: - cargs.append("-dist_cor") - cargs.extend([ - "-thresh", - thresh - ]) - cargs.extend([ - "-nclust", - str(nclust) - ]) - cargs.extend(datasets) - ret = V3dStatClustOutputs( - root=execution.output_file("."), - output_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - output_brick=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dStatClustOutputs", - "V_3D_STAT_CLUST_METADATA", - "v_3d_stat_clust", -] diff --git a/python/src/niwrap/afni/v_3d_surf2_vol.py b/python/src/niwrap/afni/v_3d_surf2_vol.py deleted file mode 100644 index 61e84522a..000000000 --- a/python/src/niwrap/afni/v_3d_surf2_vol.py +++ /dev/null @@ -1,218 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SURF2_VOL_METADATA = Metadata( - id="cea1a70189199505281359212683a7a695d294f2.boutiques", - name="3dSurf2Vol", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSurf2VolOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_surf2_vol(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset""" - - -def v_3d_surf2_vol( - spec: InputPathType, - surface_volume: InputPathType, - surf_a: str, - grid_parent: InputPathType, - map_func: str, - prefix: str, - surf_b: str | None = None, - surf_xyz_1d: InputPathType | None = None, - sdata_1d: InputPathType | None = None, - sdata: InputPathType | None = None, - f_steps: float | None = None, - f_index: str | None = None, - f_p1_fr: float | None = None, - f_pn_fr: float | None = None, - f_p1_mm: float | None = None, - f_pn_mm: float | None = None, - stop_gap: bool = False, - cmask: str | None = None, - data_expr: str | None = None, - datum: str | None = None, - debug: int | None = None, - dnode: int | None = None, - dvoxel: int | None = None, - noscale: bool = False, - sxyz_orient_as_gpar: bool = False, - runner: Runner | None = None, -) -> V3dSurf2VolOutputs: - """ - Map data from a surface domain to an AFNI volume domain. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec: SUMA spec file. - surface_volume: AFNI surface volume dataset. - surf_a: Specify surface A from spec file. - grid_parent: AFNI grid parent dataset. - map_func: Surface to dataset function. - prefix: Prefix for the output dataset. - surf_b: Specify surface B from spec file. - surf_xyz_1d: 1D coordinate file. - sdata_1d: 1D sub-surface data file. - sdata: NIML or GIFTI formatted dataset. - f_steps: Partition segments into this many steps. - f_index: Index by points or voxels. - f_p1_fr: Offset p1 by a fraction of the length. - f_pn_fr: Offset pn by a fraction of the length. - f_p1_mm: Offset p1 by a distance in mm. - f_pn_mm: Offset pn by a distance in mm. - stop_gap: Stop when a zero gap has been hit. - cmask: Command for dataset mask. - data_expr: Apply expression to surface input. - datum: Set data type in output dataset. - debug: Verbose output level. - dnode: Extra output for specified node. - dvoxel: Extra output for specified voxel. - noscale: No scale factor in output dataset. - sxyz_orient_as_gpar: Assume grid parent orientation for surface xyz. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSurf2VolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SURF2_VOL_METADATA) - cargs = [] - cargs.append("3dSurf2Vol") - cargs.extend([ - "-spec", - execution.input_file(spec) - ]) - cargs.extend([ - "-sv", - execution.input_file(surface_volume) - ]) - cargs.extend([ - "-surf_A", - surf_a - ]) - if surf_b is not None: - cargs.extend([ - "-surf_B", - surf_b - ]) - cargs.extend([ - "-grid_parent", - execution.input_file(grid_parent) - ]) - cargs.extend([ - "-map_func", - map_func - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if surf_xyz_1d is not None: - cargs.extend([ - "-surf_xyz_1D", - execution.input_file(surf_xyz_1d) - ]) - if sdata_1d is not None: - cargs.extend([ - "-sdata_1D", - execution.input_file(sdata_1d) - ]) - if sdata is not None: - cargs.extend([ - "-sdata", - execution.input_file(sdata) - ]) - if f_steps is not None: - cargs.extend([ - "-f_steps", - str(f_steps) - ]) - if f_index is not None: - cargs.extend([ - "-f_index", - f_index - ]) - if f_p1_fr is not None: - cargs.extend([ - "-f_p1_fr", - str(f_p1_fr) - ]) - if f_pn_fr is not None: - cargs.extend([ - "-f_pn_fr", - str(f_pn_fr) - ]) - if f_p1_mm is not None: - cargs.extend([ - "-f_p1_mm", - str(f_p1_mm) - ]) - if f_pn_mm is not None: - cargs.extend([ - "-f_pn_mm", - str(f_pn_mm) - ]) - if stop_gap: - cargs.append("-stop_gap") - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if data_expr is not None: - cargs.extend([ - "-data_expr", - data_expr - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if debug is not None: - cargs.extend([ - "-debug", - str(debug) - ]) - if dnode is not None: - cargs.extend([ - "-dnode", - str(dnode) - ]) - if dvoxel is not None: - cargs.extend([ - "-dvoxel", - str(dvoxel) - ]) - if noscale: - cargs.append("-noscale") - if sxyz_orient_as_gpar: - cargs.append("-sxyz_orient_as_gpar") - ret = V3dSurf2VolOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + "+*[gz]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSurf2VolOutputs", - "V_3D_SURF2_VOL_METADATA", - "v_3d_surf2_vol", -] diff --git a/python/src/niwrap/afni/v_3d_surf_mask.py b/python/src/niwrap/afni/v_3d_surf_mask.py deleted file mode 100644 index 1c64cd8c2..000000000 --- a/python/src/niwrap/afni/v_3d_surf_mask.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SURF_MASK_METADATA = Metadata( - id="55dc0c4e1d7ff3d126a0dfcd22e6d94d6ee4130c.boutiques", - name="3dSurfMask", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSurfMaskOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_surf_mask(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_mask: OutputPathType - """Main output mask dataset.""" - distance_dataset: OutputPathType - """Dataset reflecting voxel shortest distances to the surface.""" - - -def v_3d_surf_mask( - surface_type: str, - surface_file: InputPathType, - prefix: str, - grid_parent: InputPathType, - fill_method: str | None = None, - surface_volume: InputPathType | None = None, - mask_only: bool = False, - flip_orientation: bool = False, - no_distance: bool = False, - runner: Runner | None = None, -) -> V3dSurfMaskOutputs: - """ - Creates volumetric datasets marking voxels based on their location relative to a - surface. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - surface_type: Specify input surface. - surface_file: Specify input surface filename. - prefix: Prefix of output dataset. - grid_parent: Specifies the grid for the output volume. - fill_method: Fill method: SLOW or FAST (default: FAST). - surface_volume: Specify the surface volume. - mask_only: Produce an output dataset where voxels are 1 inside the\ - surface and 0 outside. - flip_orientation: Flip triangle winding of surface mesh. - no_distance: Do not compute the distances, just the mask from the first\ - step. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSurfMaskOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SURF_MASK_METADATA) - cargs = [] - cargs.append("3dSurfMask") - cargs.append(surface_type) - cargs.append(execution.input_file(surface_file)) - cargs.append(prefix) - cargs.append(execution.input_file(grid_parent)) - if fill_method is not None: - cargs.extend([ - "-fill_method", - fill_method - ]) - if surface_volume is not None: - cargs.extend([ - "-sv", - execution.input_file(surface_volume) - ]) - if mask_only: - cargs.append("-mask_only") - if flip_orientation: - cargs.append("-flip_orientation") - if no_distance: - cargs.append("-no_dist") - ret = V3dSurfMaskOutputs( - root=execution.output_file("."), - output_mask=execution.output_file(prefix + ".m+orig.BRIK"), - distance_dataset=execution.output_file(prefix + ".d+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSurfMaskOutputs", - "V_3D_SURF_MASK_METADATA", - "v_3d_surf_mask", -] diff --git a/python/src/niwrap/afni/v_3d_synthesize.py b/python/src/niwrap/afni/v_3d_synthesize.py deleted file mode 100644 index 1a72410d6..000000000 --- a/python/src/niwrap/afni/v_3d_synthesize.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_SYNTHESIZE_METADATA = Metadata( - id="1b7574324cf89a065c709504493c7ed745313d61.boutiques", - name="3dSynthesize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dSynthesizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_synthesize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_synthesize( - c_bucket: InputPathType, - matrix: InputPathType, - select_: str, - prefix: str, - dry_flag: bool = False, - tr: float | None = None, - cenfill: typing.Literal["zero", "nbhr", "none"] | None = None, - runner: Runner | None = None, -) -> V3dSynthesizeOutputs: - """ - Reads a '-cbucket' dataset and a '.xmat.1D' matrix from 3dDeconvolve, and - synthesizes a fit dataset using selected sub-bricks and matrix columns. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - c_bucket: Input dataset from 3dDeconvolve via the '-cbucket' option. - matrix: Matrix file from 3dDeconvolve via the '-x1D' option. - select_: Select columns from the matrix and corresponding sub-bricks\ - from the cbucket. Can use forms like 'baseline', 'polort', 'allfunc',\ - 'allstim', 'all', 'something', or numbers/ranges. - prefix: Output result into dataset with the specified name. - dry_flag: Don't compute the output, just check the inputs. - tr: Set TR in the output to the specified value. - cenfill: How censored time points from 3dDeconvolve will be filled\ - (options: 'zero', 'nbhr', 'none'). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dSynthesizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_SYNTHESIZE_METADATA) - cargs = [] - cargs.append("3dSynthesize") - cargs.append("-cbucket") - cargs.append(execution.input_file(c_bucket)) - cargs.append("-matrix") - cargs.append(execution.input_file(matrix)) - cargs.append("-select") - cargs.append(select_) - cargs.append("-prefix") - cargs.append(prefix) - if dry_flag: - cargs.append("-dry") - if tr is not None: - cargs.extend([ - "-TR", - str(tr) - ]) - if cenfill is not None: - cargs.extend([ - "-cenfill", - cenfill - ]) - ret = V3dSynthesizeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dSynthesizeOutputs", - "V_3D_SYNTHESIZE_METADATA", - "v_3d_synthesize", -] diff --git a/python/src/niwrap/afni/v_3d_tagalign.py b/python/src/niwrap/afni/v_3d_tagalign.py deleted file mode 100644 index de88009ed..000000000 --- a/python/src/niwrap/afni/v_3d_tagalign.py +++ /dev/null @@ -1,144 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TAGALIGN_METADATA = Metadata( - id="72f062732ebd3946f6103ba90212bf73566a6b67.boutiques", - name="3dTagalign", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTagalignOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tagalign(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset_head: OutputPathType | None - """Output dataset in AFNI format (.HEAD)""" - output_dataset_brick: OutputPathType | None - """Output dataset in AFNI format (.BRIK)""" - output_matvec_file: OutputPathType | None - """Output transformation matrix and vector file""" - - -def v_3d_tagalign( - input_dataset: InputPathType, - master_dataset: InputPathType, - tagset_file: InputPathType | None = None, - no_keep_tags: bool = False, - matvec_file: str | None = None, - rotate: bool = False, - affine: bool = False, - rotscl: bool = False, - prefix: str | None = None, - verbose: bool = False, - dummy: bool = False, - linear_interpolation: bool = False, - cubic_interpolation: bool = False, - nearest_neighbor_interpolation: bool = False, - quintic_interpolation: bool = False, - runner: Runner | None = None, -) -> V3dTagalignOutputs: - """ - Rotates/translates dataset 'dset' to be aligned with the master using the - tagsets embedded in their .HEAD files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset to align. - master_dataset: Use dataset 'mset' as the master dataset. This option\ - is mandatory. - tagset_file: Use the tagset in the .tag file instead of dset. - no_keep_tags: Don't put transformed locations of dset's tags into the\ - output dataset [default = keep tags]. - matvec_file: Write the matrix+vector transformation to file 'mfile'.\ - This can be used with 3dWarp's '-matvec_in2out' option to align other\ - datasets in the same way (e.g., functional datasets). - rotate: Compute the transformation as a rotation + shift (default). - affine: Compute the transformation as a general affine map, where the\ - matrix is a general 3x3 matrix. - rotscl: Compute transformation as a rotation times an isotropic\ - scaling; where matrix is an orthogonal matrix times a scalar. - prefix: Specify the prefix for the output dataset. - verbose: Print progress reports. - dummy: Don't actually rotate the dataset, just compute the\ - transformation matrix and vector. If '-matvec' is used, the mfile will\ - be written. - linear_interpolation: Use linear interpolation method. - cubic_interpolation: Use cubic interpolation method (default). - nearest_neighbor_interpolation: Use nearest neighbour interpolation\ - method. - quintic_interpolation: Use quintic interpolation method. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTagalignOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TAGALIGN_METADATA) - cargs = [] - cargs.append("3dTagalign") - cargs.append(execution.input_file(input_dataset)) - cargs.extend([ - "-master", - execution.input_file(master_dataset) - ]) - if tagset_file is not None: - cargs.extend([ - "-tagset", - execution.input_file(tagset_file) - ]) - if no_keep_tags: - cargs.append("-nokeeptags") - if matvec_file is not None: - cargs.extend([ - "-matvec", - matvec_file - ]) - if rotate: - cargs.append("-rotate") - if affine: - cargs.append("-affine") - if rotscl: - cargs.append("-rotscl") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose: - cargs.append("-verb") - if dummy: - cargs.append("-dummy") - if linear_interpolation: - cargs.append("-linear") - if cubic_interpolation: - cargs.append("-cubic") - if nearest_neighbor_interpolation: - cargs.append("-NN") - if quintic_interpolation: - cargs.append("-quintic") - ret = V3dTagalignOutputs( - root=execution.output_file("."), - output_dataset_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - output_dataset_brick=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - output_matvec_file=execution.output_file(matvec_file) if (matvec_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTagalignOutputs", - "V_3D_TAGALIGN_METADATA", - "v_3d_tagalign", -] diff --git a/python/src/niwrap/afni/v_3d_tcat.py b/python/src/niwrap/afni/v_3d_tcat.py deleted file mode 100644 index e5cb021c2..000000000 --- a/python/src/niwrap/afni/v_3d_tcat.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TCAT_METADATA = Metadata( - id="e98dd59fb5002701fc6ef51eddca5ee6f7e1397b.boutiques", - name="3dTcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_tcat( - in_files: InputPathType, - rlt: typing.Literal["", "+", "++"] | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dTcatOutputs: - """ - Concatenate sub-bricks from input datasets into one big 3D+time dataset. - TODO Replace InputMultiPath in_files with Traits.List, if possible. Current - version adds extra whitespace. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_files: Input file to 3dtcat. - rlt: '' or '+' or '++'. Remove linear trends in each voxel time series\ - loaded from each input dataset, separately. option -rlt removes the\ - least squares fit of 'a+b*t' to each voxel time series. option -rlt+\ - adds dataset mean back in. option -rlt++ adds overall mean of all\ - dataset timeseries back in. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - verbose: Print out some verbose output as the program. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTcatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TCAT_METADATA) - cargs = [] - cargs.append("3dTcat") - if rlt is not None: - cargs.extend([ - "-rlt", - rlt - ]) - cargs.append(execution.input_file(in_files)) - cargs.append("[OUT_FILE]") - if outputtype is not None: - cargs.append(outputtype) - if verbose: - cargs.append("-verb") - ret = V3dTcatOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_files).name + "_tcat"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTcatOutputs", - "V_3D_TCAT_METADATA", - "v_3d_tcat", -] diff --git a/python/src/niwrap/afni/v_3d_tcorr1_d.py b/python/src/niwrap/afni/v_3d_tcorr1_d.py deleted file mode 100644 index da047b540..000000000 --- a/python/src/niwrap/afni/v_3d_tcorr1_d.py +++ /dev/null @@ -1,92 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TCORR1_D_METADATA = Metadata( - id="28502a6e2b45dfa6629df5e5bdaf7c4dde7d82f6.boutiques", - name="3dTcorr1D", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTcorr1DOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tcorr1_d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output filename prefix.""" - out_file_: OutputPathType - """Output file containing correlations.""" - - -def v_3d_tcorr1_d( - xset: InputPathType, - y_1d: InputPathType, - ktaub: bool = False, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - pearson: bool = False, - quadrant: bool = False, - spearman: bool = False, - runner: Runner | None = None, -) -> V3dTcorr1DOutputs: - """ - Computes the correlation coefficient between each voxel time series in the input - 3D+time dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - xset: 3d+time dataset input. - y_1d: 1d time series file input. - ktaub: Correlation is the kendall's tau_b correlation coefficient. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - pearson: Correlation is the normal pearson correlation coefficient. - quadrant: Correlation is the quadrant correlation coefficient. - spearman: Correlation is the spearman (rank) correlation coefficient. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTcorr1DOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TCORR1_D_METADATA) - cargs = [] - cargs.append("3dTcorr1D") - if ktaub: - cargs.append("-ktaub") - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if pearson: - cargs.append("-pearson") - if quadrant: - cargs.append("-quadrant") - if spearman: - cargs.append("-spearman") - cargs.append(execution.input_file(xset)) - cargs.append(execution.input_file(y_1d)) - ret = V3dTcorr1DOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(xset).name + "_correlation.nii.gz"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTcorr1DOutputs", - "V_3D_TCORR1_D_METADATA", - "v_3d_tcorr1_d", -] diff --git a/python/src/niwrap/afni/v_3d_tcorr_map.py b/python/src/niwrap/afni/v_3d_tcorr_map.py deleted file mode 100644 index 78398cccc..000000000 --- a/python/src/niwrap/afni/v_3d_tcorr_map.py +++ /dev/null @@ -1,176 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TCORR_MAP_METADATA = Metadata( - id="197d89aea57496a500d08e514c10454efb723051.boutiques", - name="3dTcorrMap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTcorrMapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tcorr_map(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_tcorr_map( - input_: InputPathType, - seed: InputPathType | None = None, - mask: InputPathType | None = None, - automask: bool = False, - mean: str | None = None, - zmean: str | None = None, - qmean: str | None = None, - pmean: str | None = None, - thresh: str | None = None, - varthresh: str | None = None, - norm_varthresh: str | None = None, - corrmap: str | None = None, - corrmask: bool = False, - aexpr: str | None = None, - cexpr: str | None = None, - sexpr: str | None = None, - hist: str | None = None, - runner: Runner | None = None, -) -> V3dTcorrMapOutputs: - """ - AFNI program to compute correlation maps of input time series data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Read 3D+time dataset 'dd'. This provides the time series to be\ - correlated en masse. This is a mandatory option. - seed: Read 3D+time dataset 'bb'. It correlates the -seed voxel time\ - series with every voxel in the -input dataset. - mask: Read dataset 'mmm' as a voxel mask. - automask: Create a mask from the input dataset. - mean: Save average correlations into dataset prefix 'pp'. - zmean: Save tanh of mean arctanh(correlation) into 'pp'. - qmean: Save RMS(correlation) into 'pp'. - pmean: Save average of squared positive correlations into 'pp'. - thresh: Save the COUNT of how many voxels survived thresholding at\ - level abs(correlation) >= tt. - varthresh: Save the COUNT of how many voxels survive thresholding at\ - multiple levels abs(correlation) >= tt. - norm_varthresh: Like '-VarThresh', but the output counts are\ - 'Normalized'. - corrmap: Output at each voxel the entire correlation map, into a\ - dataset with prefix 'pp'. - corrmask: By default, -CorrMap outputs a sub-brick for EACH input\ - dataset voxel. Eliminates these sub-bricks using this option. - aexpr: For each correlation 'r', compute the calc-style expression\ - 'expr', and average these values to get the output that goes into\ - dataset 'ppp'. - cexpr: As in '-Aexpr', but only average together nonzero values\ - computed by 'expr'. - sexpr: As above, but the sum of the expressions is computed rather than\ - the average. - hist: For each voxel, save a histogram of the correlation coefficients\ - into dataset ppp. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTcorrMapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TCORR_MAP_METADATA) - cargs = [] - cargs.append("3dTcorrMap") - cargs.append(execution.input_file(input_)) - if seed is not None: - cargs.extend([ - "-seed", - execution.input_file(seed) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask: - cargs.append("-automask") - if mean is not None: - cargs.extend([ - "-Mean", - mean - ]) - if zmean is not None: - cargs.extend([ - "-Zmean", - zmean - ]) - if qmean is not None: - cargs.extend([ - "-Qmean", - qmean - ]) - if pmean is not None: - cargs.extend([ - "-Pmean", - pmean - ]) - if thresh is not None: - cargs.extend([ - "-Thresh", - thresh - ]) - if varthresh is not None: - cargs.extend([ - "-VarThresh", - varthresh - ]) - if norm_varthresh is not None: - cargs.extend([ - "-VarThreshN", - norm_varthresh - ]) - if corrmap is not None: - cargs.extend([ - "-CorrMap", - corrmap - ]) - if corrmask: - cargs.append("-CorrMask") - if aexpr is not None: - cargs.extend([ - "-Aexpr", - aexpr - ]) - if cexpr is not None: - cargs.extend([ - "-Cexpr", - cexpr - ]) - if sexpr is not None: - cargs.extend([ - "-Sexpr", - sexpr - ]) - if hist is not None: - cargs.extend([ - "-Hist", - hist - ]) - ret = V3dTcorrMapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTcorrMapOutputs", - "V_3D_TCORR_MAP_METADATA", - "v_3d_tcorr_map", -] diff --git a/python/src/niwrap/afni/v_3d_tcorrelate.py b/python/src/niwrap/afni/v_3d_tcorrelate.py deleted file mode 100644 index 5d2274fca..000000000 --- a/python/src/niwrap/afni/v_3d_tcorrelate.py +++ /dev/null @@ -1,155 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TCORRELATE_METADATA = Metadata( - id="2240f8304c0c2cc0d1686fc4d8af67efdb5198a4.boutiques", - name="3dTcorrelate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTcorrelateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tcorrelate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType | None - """Output image file name.""" - - -def v_3d_tcorrelate( - xset: InputPathType, - yset: InputPathType, - pearson: bool = False, - spearman: bool = False, - quadrant: bool = False, - ktaub: bool = False, - covariance: bool = False, - partial: InputPathType | None = None, - ycoef: bool = False, - fisher: bool = False, - polort: int | None = None, - ort: InputPathType | None = None, - autoclip: bool = False, - automask: bool = False, - zcensor: bool = False, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dTcorrelateOutputs: - """ - 3dTcorrelate. Computes the correlation coefficient between corresponding voxel - time series in two input 3D+time datasets 'xset' and 'yset'. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - xset: Input xset. - yset: Input yset. - pearson: Correlation is the normal pearson correlation coefficient. - spearman: Correlation is the Spearman (rank) correlation coefficient. - quadrant: Correlation is the quadrant coefficient. - ktaub: Correlation is Kendall's tau_b coefficient. For continuous or\ - finely discretized data, tau_b and rank correlation are nearly\ - equivalent. - covariance: Covariance instead of correlation. That would be Pearson\ - correlation without scaling by the product of the standard deviations. - partial: Partial Pearson's correlation of X & Y, adjusting for Z (the\ - dataset provided here). - ycoef: Least squares coefficient that best fits y(t) to x(t), after\ - detrending. That is, if yd(t) is the detrended y(t) and xd(t) is the\ - detrended x(t), then the ycoef value is from the OLSQ fit to xd(t) =\ - ycoef & y(t) + error. - fisher: Apply the Fisher (inverse hyperbolic tangent) transformation to\ - correlation results. Does not make sense with ktaub, covariance, or\ - ycoef. - polort: Remove polynomial trend of order m. Using m=-1 mean no\ - detrending; this is only useful fro data that has been preprocessed. - ort: A 1D file. Also detrend using the columbs of the 1D file provided\ - here. Only one -ort option can be given, so if you would like to use\ - more than one, create a temporary file using 1dcat. - autoclip: Clip off low-intensity regions in the two datasets, so that\ - the correlation is only computed between high-intensity (presumably\ - brain) voxels. The intensity level is determined the same way that\ - 3dClipLevel works. - automask: Clip off low-intensity regions in the two datasets, so that\ - the correlation is only computed between high-intensity (presumably\ - brain) voxels. The intensity level is determined the same way that\ - 3dClipLevel works. - zcensor: Omit (censor out) any time points where the xset volume is all\ - zero OR where the yset volume is all zero (in mask). Please note that\ - using -zcensor with any detrending is unlikely to be useful. - prefix: Save output into a dataset with this prefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTcorrelateOutputs`). - """ - if polort is not None and not (-1 <= polort <= 9): - raise ValueError(f"'polort' must be between -1 <= x <= 9 but was {polort}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TCORRELATE_METADATA) - cargs = [] - cargs.append("3dTcorrelate") - cargs.append(execution.input_file(xset)) - cargs.append(execution.input_file(yset)) - if pearson: - cargs.append("-pearson") - if spearman: - cargs.append("-spearman") - if quadrant: - cargs.append("-quadrant") - if ktaub: - cargs.append("-ktaub") - if covariance: - cargs.append("-covariance") - if partial is not None: - cargs.extend([ - "-partial", - execution.input_file(partial) - ]) - if ycoef: - cargs.append("-ycoef") - if fisher: - cargs.append("-Fisher") - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if ort is not None: - cargs.extend([ - "-ort", - execution.input_file(ort) - ]) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if zcensor: - cargs.append("-zcensor") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = V3dTcorrelateOutputs( - root=execution.output_file("."), - out_file=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTcorrelateOutputs", - "V_3D_TCORRELATE_METADATA", - "v_3d_tcorrelate", -] diff --git a/python/src/niwrap/afni/v_3d_tfilter.py b/python/src/niwrap/afni/v_3d_tfilter.py deleted file mode 100644 index 06e169120..000000000 --- a/python/src/niwrap/afni/v_3d_tfilter.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TFILTER_METADATA = Metadata( - id="0604d522cb0075ad07593c0f28482b95f959239c.boutiques", - name="3dTfilter", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTfilterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tfilter(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Filtered output dataset""" - - -def v_3d_tfilter( - inputdataset: InputPathType, - outputdataset: str, - filters: list[str], - runner: Runner | None = None, -) -> V3dTfilterOutputs: - """ - 3dTfilter filters the time series in each voxel according to the user-specified - filter functions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inputdataset: Input dataset. - outputdataset: Output dataset. - filters: Filter function(s) to apply. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTfilterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TFILTER_METADATA) - cargs = [] - cargs.append("3dTfilter") - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(inputdataset) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - outputdataset - ]) - cargs.extend([ - "-filter", - *filters - ]) - ret = V3dTfilterOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(outputdataset), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTfilterOutputs", - "V_3D_TFILTER_METADATA", - "v_3d_tfilter", -] diff --git a/python/src/niwrap/afni/v_3d_tfitter.py b/python/src/niwrap/afni/v_3d_tfitter.py deleted file mode 100644 index 8e42becce..000000000 --- a/python/src/niwrap/afni/v_3d_tfitter.py +++ /dev/null @@ -1,198 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TFITTER_METADATA = Metadata( - id="8451a7cd8aa8de8047fb4bbe324982a2fbf6f94a.boutiques", - name="3dTfitter", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTfitterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tfitter(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_prefix: OutputPathType | None - """Output dataset for LHS parameters.""" - fitted_time_series: OutputPathType | None - """Output fitted time series dataset.""" - error_sums: OutputPathType | None - """Output error sums dataset.""" - - -def v_3d_tfitter( - rhs: str, - lhs: list[str] | None = None, - polort: float | None = None, - vthr: float | None = None, - faltung: list[str] | None = None, - lsqfit: bool = False, - l1fit: bool = False, - l2lasso: list[str] | None = None, - lasso_centro_block: list[str] | None = None, - l2sqrtlasso: list[str] | None = None, - consign: list[str] | None = None, - cons_fal: str | None = None, - prefix: str | None = None, - label: list[str] | None = None, - fitts: str | None = None, - errsum: str | None = None, - mask: str | None = None, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dTfitterOutputs: - """ - * At each voxel, assembles and solves a set of linear equations. - ++ The matrix at each voxel may be the same or may be different. - ++ This flexibility (for voxel-wise regressors) is one feature - that makes 3dTfitter different from 3dDeconvolve. - ++ Another distinguishing feature is that 3dTfitter allows for - L2, L1, and L2+L1 (LASSO) regression solvers, and allows you - to impose sign constraints on the solution parameters. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - rhs: Specifies the right-hand-side 3D+time dataset. ('rset' can also be\ - a 1D file with 1 column). - lhs: Specifies a column (or columns) of the left-hand-side matrix. More\ - than one 'lset' can follow the '-LHS' option. - polort: Add 'p+1' Legendre polynomial columns to the LHS matrix. - vthr: The value 'v' (between 0.0 and 0.09, inclusive) defines the\ - threshold below which LHS vectors will be omitted from the regression\ - analysis. - faltung: Specifies a convolution (German: Faltung) model to be added to\ - the LHS matrix. Followed by four arguments: 'fset', 'fpre', 'pen',\ - 'fac'. - lsqfit: Solve equations via least squares [the default method]. - l1fit: Solve equations via least sum of absolute residuals. - l2lasso: Solve equations via least squares with a LASSO (L1) penalty on\ - the coefficients. Followed by 'lam' and optional 'i j k ...'. - lasso_centro_block: Defines a block of coefficients that will be\ - penalized together. - l2sqrtlasso: Similar to '-l2lasso', but aims to minimize\ - sqrt(Q2)+lam*L1. - consign: Indicates that the sign of some output LHS parameters should\ - be constrained in the solution. - cons_fal: Constrain the deconvolution time series from '-FALTUNG' to be\ - positive if 'c' is '+' or to be negative if 'c' is '-'. - prefix: Prefix for the output dataset (LHS parameters) filename. - label: Specifies sub-brick labels in the output LHS parameter dataset. - fitts: Prefix filename for the output fitted time series dataset. - errsum: Prefix filename for the error sums dataset. - mask: Read in dataset 'ms' to use as a mask; only voxels with nonzero\ - values in the mask will be processed. - quiet: Don't print progress report messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTfitterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TFITTER_METADATA) - cargs = [] - cargs.append("3dTfitter") - cargs.extend([ - "-RHS", - rhs - ]) - if lhs is not None: - cargs.extend([ - "-LHS", - *lhs - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if vthr is not None: - cargs.extend([ - "-vthr", - str(vthr) - ]) - if faltung is not None: - cargs.extend([ - "-FALTUNG", - *faltung - ]) - if lsqfit: - cargs.append("-lsqfit") - if l1fit: - cargs.append("-l1fit") - if l2lasso is not None: - cargs.extend([ - "-l2lasso", - *l2lasso - ]) - if lasso_centro_block is not None: - cargs.extend([ - "-lasso_centro_block", - *lasso_centro_block - ]) - if l2sqrtlasso is not None: - cargs.extend([ - "-l2sqrtlasso", - *l2sqrtlasso - ]) - if consign is not None: - cargs.extend([ - "-consign", - *consign - ]) - if cons_fal is not None: - cargs.extend([ - "-consFAL", - cons_fal - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if label is not None: - cargs.extend([ - "-label", - *label - ]) - if fitts is not None: - cargs.extend([ - "-fitts", - fitts - ]) - if errsum is not None: - cargs.extend([ - "-errsum", - errsum - ]) - if mask is not None: - cargs.extend([ - "-mask", - mask - ]) - if quiet: - cargs.append("-quiet") - ret = V3dTfitterOutputs( - root=execution.output_file("."), - output_prefix=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - fitted_time_series=execution.output_file(fitts + ".nii.gz") if (fitts is not None) else None, - error_sums=execution.output_file(errsum + ".nii.gz") if (errsum is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTfitterOutputs", - "V_3D_TFITTER_METADATA", - "v_3d_tfitter", -] diff --git a/python/src/niwrap/afni/v_3d_threeto_rgb.py b/python/src/niwrap/afni/v_3d_threeto_rgb.py deleted file mode 100644 index 4d5e8e53c..000000000 --- a/python/src/niwrap/afni/v_3d_threeto_rgb.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_THREETO_RGB_METADATA = Metadata( - id="c2dc1030d39780e10c75c90a735a91d0208be497.boutiques", - name="3dThreetoRGB", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dThreetoRgbOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_threeto_rgb(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset_head: OutputPathType | None - """RGB-valued dataset output""" - output_dataset_brik: OutputPathType | None - """RGB-valued dataset output""" - - -def v_3d_threeto_rgb( - input_dataset: InputPathType, - output_prefix: str | None = None, - scale_factor: float | None = None, - mask_dataset: InputPathType | None = None, - fim: bool = False, - anat: bool = False, - input_dataset2: InputPathType | None = None, - input_dataset3: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dThreetoRgbOutputs: - """ - Converts 3 sub-bricks of input to an RGB-valued dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset or first dataset if three datasets are\ - provided. - output_prefix: Write output into dataset with specified prefix. - scale_factor: Multiply input values by this factor before using as RGB. - mask_dataset: Only output nonzero values where the mask dataset is\ - nonzero. - fim: Write result as a 'fim' type dataset (default behavior). - anat: Write result as a anatomical type dataset. - input_dataset2: Second dataset, required only if three datasets are\ - provided. - input_dataset3: Third dataset, required only if three datasets are\ - provided. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dThreetoRgbOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_THREETO_RGB_METADATA) - cargs = [] - cargs.append("3dThreetoRGB") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if scale_factor is not None: - cargs.extend([ - "-scale", - str(scale_factor) - ]) - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if fim: - cargs.append("-fim") - if anat: - cargs.append("-anat") - cargs.append(execution.input_file(input_dataset)) - cargs.append("[DATASET1]") - if input_dataset2 is not None: - cargs.append(execution.input_file(input_dataset2)) - if input_dataset3 is not None: - cargs.append(execution.input_file(input_dataset3)) - ret = V3dThreetoRgbOutputs( - root=execution.output_file("."), - output_dataset_head=execution.output_file(output_prefix + "+rgb.HEAD") if (output_prefix is not None) else None, - output_dataset_brik=execution.output_file(output_prefix + "+rgb.BRIK") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dThreetoRgbOutputs", - "V_3D_THREETO_RGB_METADATA", - "v_3d_threeto_rgb", -] diff --git a/python/src/niwrap/afni/v_3d_tnorm.py b/python/src/niwrap/afni/v_3d_tnorm.py deleted file mode 100644 index adee15963..000000000 --- a/python/src/niwrap/afni/v_3d_tnorm.py +++ /dev/null @@ -1,95 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TNORM_METADATA = Metadata( - id="3ab7928628832800408347f169adeb33cff9fd8f.boutiques", - name="3dTnorm", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTnormOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tnorm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Normalized output dataset""" - - -def v_3d_tnorm( - input_dataset: InputPathType, - prefix: str | None = None, - norm2: bool = False, - norm_r: bool = False, - norm1: bool = False, - normx: bool = False, - polort: float | None = None, - l1fit: bool = False, - runner: Runner | None = None, -) -> V3dTnormOutputs: - """ - Normalizes each voxel time series by multiplicative scaling. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g. data.nii). - prefix: Prefix for the output dataset. - norm2: L2 normalize (sum of squares = 1). - norm_r: Normalize so sum of squares = number of time points. - norm1: L1 normalize (sum of absolute values = 1). - normx: Scale so max absolute value = 1 (L_infinity norm). - polort: Detrend with polynomials of order p before normalizing. - l1fit: Detrend with L1 regression (L2 is default). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTnormOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TNORM_METADATA) - cargs = [] - cargs.append("3dTnorm") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if norm2: - cargs.append("-norm2") - if norm_r: - cargs.append("-normR") - if norm1: - cargs.append("-norm1") - if normx: - cargs.append("-normx") - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if l1fit: - cargs.append("-L1fit") - cargs.append(execution.input_file(input_dataset)) - ret = V3dTnormOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTnormOutputs", - "V_3D_TNORM_METADATA", - "v_3d_tnorm", -] diff --git a/python/src/niwrap/afni/v_3d_tortoiseto_here.py b/python/src/niwrap/afni/v_3d_tortoiseto_here.py deleted file mode 100644 index b76f9dafc..000000000 --- a/python/src/niwrap/afni/v_3d_tortoiseto_here.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TORTOISETO_HERE_METADATA = Metadata( - id="83f372724dc58e7674ba98fc48a12133c4132934.boutiques", - name="3dTORTOISEtoHere", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTortoisetoHereOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tortoiseto_here(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dt_file: OutputPathType - """Output AFNI-style DT file with the following ordering of the 6 bricks: - Dxx, Dxy, Dyy, Dxz, Dyz, Dzz.""" - - -def v_3d_tortoiseto_here( - dt_tort: InputPathType, - prefix: str, - scale_factor: float | None = None, - flip_x: bool = False, - flip_y: bool = False, - flip_z: bool = False, - runner: Runner | None = None, -) -> V3dTortoisetoHereOutputs: - """ - Convert standard TORTOISE DTs (diagonal-first format) to standard AFNI (lower - triangular, row-wise) format. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dt_tort: Diffusion tensor file with six bricks of DT components ordered\ - in the TORTOISE manner (Dxx, Dyy, Dzz, Dxy, Dxz, Dyz). - prefix: Output file name prefix. Will have N+1 bricks when GRADFILE has\ - N rows of gradients. - scale_factor: Optional switch to rescale the DT elements, dividing by a\ - number X>0. - flip_x: Change sign of the first element of (inner) eigenvectors. - flip_y: Change sign of the second element of (inner) eigenvectors. - flip_z: Change sign of the third element of (inner) eigenvectors. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTortoisetoHereOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TORTOISETO_HERE_METADATA) - cargs = [] - cargs.append("3dTORTOISEtoHere") - cargs.append("-dt_tort") - cargs.extend([ - "-dt_tort", - execution.input_file(dt_tort) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if scale_factor is not None: - cargs.extend([ - "-scale_fac", - str(scale_factor) - ]) - if flip_x: - cargs.append("-flip_x") - if flip_y: - cargs.append("-flip_y") - if flip_z: - cargs.append("-flip_z") - ret = V3dTortoisetoHereOutputs( - root=execution.output_file("."), - output_dt_file=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTortoisetoHereOutputs", - "V_3D_TORTOISETO_HERE_METADATA", - "v_3d_tortoiseto_here", -] diff --git a/python/src/niwrap/afni/v_3d_toutcount.py b/python/src/niwrap/afni/v_3d_toutcount.py deleted file mode 100644 index 34963f31d..000000000 --- a/python/src/niwrap/afni/v_3d_toutcount.py +++ /dev/null @@ -1,117 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TOUTCOUNT_METADATA = Metadata( - id="b726a8742694b4a0acfdfd929608a00118e5b42b.boutiques", - name="3dToutcount", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dToutcountOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_toutcount(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_afni_head: OutputPathType | None - """Output dataset in AFNI format (HEAD file).""" - output_afni_brik: OutputPathType | None - """Output dataset in AFNI format (BRIK file).""" - - -def v_3d_toutcount( - input_dataset: str, - output_prefix: str | None = None, - mask_dataset: str | None = None, - q_threshold: float | None = None, - autoclip: bool = False, - automask: bool = False, - fraction: bool = False, - range_: bool = False, - polort_order: float | None = None, - legendre: bool = False, - runner: Runner | None = None, -) -> V3dToutcountOutputs: - """ - Calculates the number of 'outliers' in a 3D+time dataset at each time point. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input 3D+time dataset (e.g. dataset+orig). - output_prefix: Prefix of the new dataset saved with the outlier Q\ - values, applicable with the -save option. - mask_dataset: Only count voxels in the provided mask dataset. - q_threshold: Use 'q' instead of 0.001 in the calculation of alpha. Must\ - be within range 0 < q < 1. - autoclip: Clip off 'small' voxels (as in 3dClipLevel). Cannot use with\ - -mask. - automask: Automatically mask the dataset. Cannot use with -mask. - fraction: Output the fraction of (masked) voxels which are outliers at\ - each time point, instead of the count. - range_: Print out median+3.5*MAD of outlier count with each time point. - polort_order: Detrend each voxel time series with polynomials of order\ - 'nn'. Default value is 0, which removes the median. - legendre: Use Legendre polynomials for detrending (also allows -polort\ - > 3). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dToutcountOutputs`). - """ - if q_threshold is not None and not (0 <= q_threshold <= 1): - raise ValueError(f"'q_threshold' must be between 0 <= x <= 1 but was {q_threshold}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TOUTCOUNT_METADATA) - cargs = [] - cargs.append("3dToutcount") - cargs.append(input_dataset) - if output_prefix is not None: - cargs.append(output_prefix) - if mask_dataset is not None: - cargs.extend([ - "-mask", - mask_dataset - ]) - if q_threshold is not None: - cargs.extend([ - "-qthr", - str(q_threshold) - ]) - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if fraction: - cargs.append("-fraction") - if range_: - cargs.append("-range") - if polort_order is not None: - cargs.extend([ - "-polort", - str(polort_order) - ]) - if legendre: - cargs.append("-legendre") - ret = V3dToutcountOutputs( - root=execution.output_file("."), - output_afni_head=execution.output_file(output_prefix + ".HEAD") if (output_prefix is not None) else None, - output_afni_brik=execution.output_file(output_prefix + ".BRIK") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dToutcountOutputs", - "V_3D_TOUTCOUNT_METADATA", - "v_3d_toutcount", -] diff --git a/python/src/niwrap/afni/v_3d_toy_prog.py b/python/src/niwrap/afni/v_3d_toy_prog.py deleted file mode 100644 index 5af7bf5ec..000000000 --- a/python/src/niwrap/afni/v_3d_toy_prog.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TOY_PROG_METADATA = Metadata( - id="1311a81e171aae35dd519b54379bb3bfad692a46.boutiques", - name="3dToyProg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dToyProgOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_toy_prog(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_toy_prog( - input_dataset: InputPathType, - output_prefix: str | None = None, - mask_dataset: InputPathType | None = None, - output_datum: typing.Literal["float", "short"] | None = None, - runner: Runner | None = None, -) -> V3dToyProgOutputs: - """ - A program to illustrate dataset creation and manipulation in C using AFNI's API. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Reference dataset. - output_prefix: Prefix of the output datasets. - mask_dataset: Restrict analysis to non-zero voxels in the mask dataset. - output_datum: Output datum type for one of the datasets. Choose from\ - 'float' or 'short'. Default is 'float'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dToyProgOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TOY_PROG_METADATA) - cargs = [] - cargs.append("3dToyProg") - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if output_datum is not None: - cargs.extend([ - "-datum", - output_datum - ]) - ret = V3dToyProgOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dToyProgOutputs", - "V_3D_TOY_PROG_METADATA", - "v_3d_toy_prog", -] diff --git a/python/src/niwrap/afni/v_3d_tproject.py b/python/src/niwrap/afni/v_3d_tproject.py deleted file mode 100644 index 43dfa9437..000000000 --- a/python/src/niwrap/afni/v_3d_tproject.py +++ /dev/null @@ -1,211 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TPROJECT_METADATA = Metadata( - id="9de8d2fa7cd54923a6ee13c1f64cf49bd6c80920.boutiques", - name="3dTproject", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTprojectOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tproject(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output file.""" - - -def v_3d_tproject( - in_file: InputPathType, - tr: float | None = None, - automask: bool = False, - bandpass: list[float] | None = None, - blur: float | None = None, - cenmode: typing.Literal["KILL", "ZERO", "NTRP"] | None = None, - censor: InputPathType | None = None, - censortr: list[str] | None = None, - concat: InputPathType | None = None, - dsort: list[InputPathType] | None = None, - mask: InputPathType | None = None, - noblock: bool = False, - norm: bool = False, - ort: InputPathType | None = None, - polort: int | None = None, - stopband: list[float] | None = None, - runner: Runner | None = None, -) -> V3dTprojectOutputs: - """ - This program projects (detrends) out various 'nuisance' time series from each - voxel in the input dataset. Note that all the projections are done via linear - regression, including the frequency-based options such as '-passband'. In this - way, you can bandpass time-censored data, and at the same time, remove other - time series of no interest (e.g., physiological estimates, motion parameters). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dtproject. - tr: Use time step dd for the frequency calculations,rather than the\ - value stored in the dataset header. - automask: Generate a mask automatically. - bandpass: (a float, a float). Remove all frequencies except those in\ - the range. - blur: Blur (inside the mask only) with a filter that haswidth (fwhm) of\ - fff millimeters.spatial blurring (if done) is after the timeseries\ - filtering. - cenmode: 'kill' or 'zero' or 'ntrp'. Specifies how censored time points\ - are treated in the output dataset:* mode = zero -- put zero values in\ - their place; output dataset is same length as input* mode = kill --\ - remove those time points; output dataset is shorter than input* mode =\ - ntrp -- censored values are replaced by interpolated neighboring (in\ - time) non-censored values, before any projections, and then the\ - analysis proceeds without actual removal of any time points -- this\ - feature is to keep the spanish inquisition happy.* the default mode is\ - kill !!!. - censor: Filename of censor .1d time series.this is a file of 1s and 0s,\ - indicating whichtime points are to be included (1) and which areto be\ - excluded (0). - censortr: List of strings that specify time indexes to be removed from\ - the analysis. each string isof one of the following forms:* ``37`` =>\ - remove global time index #37* ``2:37`` => remove time index #37 in run\ - #2* ``37..47`` => remove global time indexes #37-47* ``37-47`` => same\ - as above* ``2:37..47`` => remove time indexes #37-47 in run #2*\ - ``*:0-2`` => remove time indexes #0-2 in all runs * time indexes within\ - each run start at 0. * run indexes start at 1 (just be to confusing). *\ - n.b.: 2:37,47 means index #37 in run #2 and global time index 47; it\ - does not mean index #37 in run #2 and index #47 in run #2. - concat: The catenation file, as in 3ddeconvolve, containing thetr\ - indexes of the start points for each contiguous runwithin the input\ - dataset (the first entry should be 0).* also as in 3ddeconvolve, if the\ - input dataset is automatically catenated from a collection of datasets,\ - then the run start indexes are determined directly, and '-concat' is\ - not needed (and will be ignored).* each run must have at least 9 time\ - points after censoring, or the program will not work!* the only use\ - made of this input is in setting up the bandpass/stopband regressors.*\ - '-ort' and '-dsort' regressors run through all time points, as read in.\ - if you want separate projections in each run, then you must either\ - break these ort files into appropriate components, or you must run\ - 3dtproject for each run separately, using the appropriate pieces from\ - the ort files via the ``{...}`` selector for the 1d files and the\ - ``[...]`` selector for the datasets. - dsort: Remove the 3d+time time series in dataset fset.* that is, 'fset'\ - contains a different nuisance time series for each voxel (e.g., from\ - anaticor).* multiple -dsort options are allowed. - mask: Only operate on voxels nonzero in the mset dataset.* voxels\ - outside the mask will be filled with zeros.* if no masking option is\ - given, then all voxels will be processed. - noblock: Also as in 3ddeconvolve, if you want the program to treatan\ - auto-catenated dataset as one long run, use this option.however,\ - '-noblock' will not affect catenation if you usethe '-concat' option. - norm: normalize each output time series to have sum ofsquares = 1. this\ - is the last operation. - ort: Remove each column in file.each column will have its mean removed. - polort: Remove polynomials up to and including degree pp.* default\ - value is 2.* it makes no sense to use a value of pp greater than 2, if\ - you are bandpassing out the lower frequencies!* for catenated datasets,\ - each run gets a separate set set of pp+1 legendre polynomial\ - regressors.* use of -polort -1 is not advised (if data mean != 0), even\ - if -ort contains constant terms, as all means are removed. - stopband: (a float, a float). Remove all frequencies in the range. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTprojectOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TPROJECT_METADATA) - cargs = [] - cargs.append("3dTproject") - if tr is not None: - cargs.extend([ - "-TR", - str(tr) - ]) - if automask: - cargs.append("-automask") - if bandpass is not None: - cargs.extend([ - "-bandpass", - *map(str, bandpass) - ]) - if blur is not None: - cargs.extend([ - "-blur", - str(blur) - ]) - if cenmode is not None: - cargs.extend([ - "-cenmode", - cenmode - ]) - if censor is not None: - cargs.extend([ - "-censor", - execution.input_file(censor) - ]) - if censortr is not None: - cargs.extend([ - "-CENSORTR", - *censortr - ]) - if concat is not None: - cargs.extend([ - "-concat", - execution.input_file(concat) - ]) - if dsort is not None: - cargs.extend([ - "-dsort", - *[execution.input_file(f) for f in dsort] - ]) - cargs.extend([ - "-input", - execution.input_file(in_file) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if noblock: - cargs.append("-noblock") - if norm: - cargs.append("-norm") - if ort is not None: - cargs.extend([ - "-ort", - execution.input_file(ort) - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if stopband is not None: - cargs.extend([ - "-stopband", - *map(str, stopband) - ]) - ret = V3dTprojectOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTprojectOutputs", - "V_3D_TPROJECT_METADATA", - "v_3d_tproject", -] diff --git a/python/src/niwrap/afni/v_3d_tqual.py b/python/src/niwrap/afni/v_3d_tqual.py deleted file mode 100644 index d9a0492dd..000000000 --- a/python/src/niwrap/afni/v_3d_tqual.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TQUAL_METADATA = Metadata( - id="a5953b420d22f8f6c2b20824e280582d44af991c.boutiques", - name="3dTqual", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTqualOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tqual(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - time_series: OutputPathType - """The 1D time series with the quality index for each sub-brick""" - - -def v_3d_tqual( - dataset: InputPathType, - spearman: bool = False, - quadrant: bool = False, - autoclip: bool = False, - automask: bool = False, - clip: float | None = None, - mask: InputPathType | None = None, - range_: bool = False, - runner: Runner | None = None, -) -> V3dTqualOutputs: - """ - Computes a quality index for each sub-brick in a 3D+time dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input 3D+time dataset. - spearman: Quality index is 1 minus the Spearman (rank) correlation\ - coefficient of each sub-brick with the median sub-brick (default\ - method). - quadrant: Quality index is 1 minus the quadrant correlation coefficient\ - as the quality index. - autoclip: Clip off low-intensity regions in the median sub-brick, only\ - compute correlation between high-intensity voxels. - automask: Automatically mask and compute correlation only across\ - high-intensity (presumably brain) voxels. - clip: Clip off values below given threshold in the median sub-brick. - mask: Compute correlation only across masked voxels from the given\ - dataset. - range_: Print the median-3.5*MAD and median+3.5*MAD values with each\ - quality index for plotting. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTqualOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TQUAL_METADATA) - cargs = [] - cargs.append("3dTqual") - cargs.append(execution.input_file(dataset)) - if spearman: - cargs.append("-spearman") - if quadrant: - cargs.append("-quadrant") - if autoclip: - cargs.append("-autoclip") - if automask: - cargs.append("-automask") - if clip is not None: - cargs.extend([ - "-clip", - str(clip) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if range_: - cargs.append("-range") - ret = V3dTqualOutputs( - root=execution.output_file("."), - time_series=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTqualOutputs", - "V_3D_TQUAL_METADATA", - "v_3d_tqual", -] diff --git a/python/src/niwrap/afni/v_3d_track_id.py b/python/src/niwrap/afni/v_3d_track_id.py deleted file mode 100644 index 684c23ff4..000000000 --- a/python/src/niwrap/afni/v_3d_track_id.py +++ /dev/null @@ -1,264 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TRACK_ID_METADATA = Metadata( - id="8ab0520e610553f06eae7348796632b2a5eda40e.boutiques", - name="3dTrackID", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTrackIdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_track_id(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - indimap: OutputPathType - """Output of INDIMAP""" - pairmap: OutputPathType - """Output of PAIRMAP""" - grid: OutputPathType - """Text file output of statistics of WM-ROIs""" - niml_tract: OutputPathType - """Track-like output for viewing in SUMA""" - niml_dset: OutputPathType - """Dataset output for use with *.niml.tract""" - trk: OutputPathType - """TrackVis-like output for viewing in TrackVis""" - pairmap_labeltable: OutputPathType - """Output of PAIRMAP labeltable""" - roi_labels: OutputPathType - """Output file of all ROI labels""" - option_values: OutputPathType - """Output of all option values""" - - -def v_3d_track_id( - mode: typing.Literal["DET", "MINIP", "PROB"], - netrois: InputPathType, - prefix: str, - logic: typing.Literal["OR", "AND"], - dti_in: str | None = None, - dti_list: InputPathType | None = None, - dti_extra: str | None = None, - dti_search_no: bool = False, - hardi_gfa: InputPathType | None = None, - hardi_dirs: InputPathType | None = None, - hardi_pars: str | None = None, - mask: InputPathType | None = None, - thru_mask: InputPathType | None = None, - targ_surf_stop: bool = False, - targ_surf_twixt: bool = False, - mini_num: float | None = None, - uncert: InputPathType | None = None, - unc_min_fa: float | None = None, - unc_min_v: float | None = None, - algopt: InputPathType | None = None, - alg_thresh_fa: float | None = None, - alg_thresh_ang: float | None = None, - alg_thresh_len: float | None = None, - alg_nseed_x: float | None = None, - alg_nseed_y: float | None = None, - alg_nseed_z: float | None = None, - alg_thresh_frac: float | None = None, - alg_nseed_vox: float | None = None, - alg_nmonte: float | None = None, - extra_tr_par: bool = False, - uncut_at_rois: bool = False, - dump_rois: typing.Literal["DUMP", "AFNI", "BOTH", "AFNI_MAP"] | None = None, - dump_no_labtab: bool = False, - dump_lab_consec: bool = False, - posteriori: bool = False, - rec_orig: bool = False, - do_trk_out: bool = False, - trk_opp_orient: bool = False, - nifti: bool = False, - no_indipair_out: bool = False, - write_rois: bool = False, - write_opts: bool = False, - pair_out_power: bool = False, - verb: float | None = None, - runner: Runner | None = None, -) -> V3dTrackIdOutputs: - """ - FACTID-based tractography code for AFNI, part of FATCAT. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - mode: The mode of tracking: DET, MINIP, or PROB. - netrois: Network ROI mask(s). - prefix: Prefix for output files. - logic: Control logic connections among target ROIs per network. - dti_in: Input DTI volumes basename. - dti_list: Alternative way to specify DTI input files, a NIML-formatted\ - text file. - dti_extra: Option for extra scalar for WM skeleton thresholding. - dti_search_no: Turn off automatic search for additional scalar files to\ - include in output. - hardi_gfa: Single brik dataset with generalized FA (GFA) info. - hardi_dirs: Directions file for HARDI data containing directions\ - components. - hardi_pars: Prefix to search for scalar files naming format. - mask: Mask within which tracking is done. Optional but highly\ - recommended. - thru_mask: Extra restrictor mask through which paths are strictly\ - required to pass. - targ_surf_stop: Make tracts stop at outer surfaces of the target ROIs. - targ_surf_twixt: Make tracts stop just before entering target surfaces. - mini_num: Number of whole brain Monte Carlo iterations for\ - mini-probabilistic tracking. - uncert: Uncertainty values file. - unc_min_fa: Minimum stdev for perturbing FA. - unc_min_v: Minimum stdev for perturbing direction-vectors. - algopt: Specify tracking parameter quantities file in ASCII. - alg_thresh_fa: Set threshold for FA map or other WM proxy. - alg_thresh_ang: Set maximum angle for turning during propagation. - alg_thresh_len: Set minimum physical length of tracts to keep. - alg_nseed_x: Number of seeds per voxel in x-direction. - alg_nseed_y: Number of seeds per voxel in y-direction. - alg_nseed_z: Number of seeds per voxel in z-direction. - alg_thresh_frac: Value for thresholding the fraction of tracks through\ - a voxel for a given connection. - alg_nseed_vox: Number of seeds per voxel per Monte Carlo iteration. - alg_nmonte: Number of Monte Carlo iterations. - extra_tr_par: Run three extra track parameter scalings for each\ - connection. - uncut_at_rois: Keep entire track even if overshoots a target. - dump_rois: Output individual masks of ROI connections. - dump_no_labtab: Turn off label table use in ROI dump output. - dump_lab_consec: DON'T apply numerical labels of original ROIs in dump\ - output. - posteriori: Output individual files with number of tracks per voxel per\ - pair. - rec_orig: Record dataset origin in header of *.trk file. - do_trk_out: Output *.trk files for viewing in TrackVis. - trk_opp_orient: Oppositize voxel_order for TRK files. - nifti: Output files in *.nii.gz format. - no_indipair_out: Do not output INDIMAP and PAIRMAP volumes. - write_rois: Write out ROI labels. - write_opts: Write out all option values. - pair_out_power: Switch to use powers of two labelling for PAIRMAP. - verb: Set verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTrackIdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TRACK_ID_METADATA) - cargs = [] - cargs.append("3dTrackID") - cargs.append(mode) - cargs.append(execution.input_file(netrois)) - cargs.append(prefix) - if dti_in is not None: - cargs.append(dti_in) - if dti_list is not None: - cargs.append(execution.input_file(dti_list)) - if dti_extra is not None: - cargs.append(dti_extra) - if dti_search_no: - cargs.append("-dti_search_NO") - if hardi_gfa is not None: - cargs.append(execution.input_file(hardi_gfa)) - if hardi_dirs is not None: - cargs.append(execution.input_file(hardi_dirs)) - if hardi_pars is not None: - cargs.append(hardi_pars) - if mask is not None: - cargs.append(execution.input_file(mask)) - if thru_mask is not None: - cargs.append(execution.input_file(thru_mask)) - if targ_surf_stop: - cargs.append("-targ_surf_stop") - if targ_surf_twixt: - cargs.append("-targ_surf_twixt") - cargs.append(logic) - if mini_num is not None: - cargs.append(str(mini_num)) - if uncert is not None: - cargs.append(execution.input_file(uncert)) - if unc_min_fa is not None: - cargs.append(str(unc_min_fa)) - if unc_min_v is not None: - cargs.append(str(unc_min_v)) - if algopt is not None: - cargs.append(execution.input_file(algopt)) - if alg_thresh_fa is not None: - cargs.append(str(alg_thresh_fa)) - if alg_thresh_ang is not None: - cargs.append(str(alg_thresh_ang)) - if alg_thresh_len is not None: - cargs.append(str(alg_thresh_len)) - if alg_nseed_x is not None: - cargs.append(str(alg_nseed_x)) - if alg_nseed_y is not None: - cargs.append(str(alg_nseed_y)) - if alg_nseed_z is not None: - cargs.append(str(alg_nseed_z)) - if alg_thresh_frac is not None: - cargs.append(str(alg_thresh_frac)) - if alg_nseed_vox is not None: - cargs.append(str(alg_nseed_vox)) - if alg_nmonte is not None: - cargs.append(str(alg_nmonte)) - if extra_tr_par: - cargs.append("-extra_tr_par") - if uncut_at_rois: - cargs.append("-uncut_at_rois") - if dump_rois is not None: - cargs.append(dump_rois) - if dump_no_labtab: - cargs.append("-dump_no_labtab") - if dump_lab_consec: - cargs.append("-dump_lab_consec") - if posteriori: - cargs.append("-posteriori") - if rec_orig: - cargs.append("-rec_orig") - if do_trk_out: - cargs.append("-do_trk_out") - if trk_opp_orient: - cargs.append("-trk_opp_orient") - if nifti: - cargs.append("-nifti") - if no_indipair_out: - cargs.append("-no_indipair_out") - if write_rois: - cargs.append("-write_rois") - if write_opts: - cargs.append("-write_opts") - if pair_out_power: - cargs.append("-pair_out_power") - if verb is not None: - cargs.append(str(verb)) - ret = V3dTrackIdOutputs( - root=execution.output_file("."), - indimap=execution.output_file(prefix + "_INDIMAP.nii.gz"), - pairmap=execution.output_file(prefix + "_PAIRMAP.nii.gz"), - grid=execution.output_file(prefix + ".grid"), - niml_tract=execution.output_file(prefix + ".niml.tract"), - niml_dset=execution.output_file(prefix + ".niml.dset"), - trk=execution.output_file(prefix + ".trk"), - pairmap_labeltable=execution.output_file(prefix + "_PAIRS.niml.lt"), - roi_labels=execution.output_file(prefix + "_roi.labs"), - option_values=execution.output_file(prefix + ".niml.opts"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTrackIdOutputs", - "V_3D_TRACK_ID_METADATA", - "v_3d_track_id", -] diff --git a/python/src/niwrap/afni/v_3d_trfix.py b/python/src/niwrap/afni/v_3d_trfix.py deleted file mode 100644 index 088b3ada0..000000000 --- a/python/src/niwrap/afni/v_3d_trfix.py +++ /dev/null @@ -1,100 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TRFIX_METADATA = Metadata( - id="63787e0b442f5bc7d31aadfce8d88397d77c286e.boutiques", - name="3dTRfix", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTrfixOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_trfix(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file_head: OutputPathType - """Output dataset header file""" - output_file_brik: OutputPathType - """Output dataset brik file""" - - -def v_3d_trfix( - input_file: InputPathType, - prefix: str, - tr_list: InputPathType | None = None, - time_list: InputPathType | None = None, - output_tr: float | None = None, - runner: Runner | None = None, -) -> V3dTrfixOutputs: - """ - Re-sample dataset with irregular time grid to regular time grid via linear - interpolation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input dataset. - prefix: Prefix name for output dataset. - tr_list: File of time gaps between sub-bricks in input dataset. - time_list: File with times at each sub-brick in the input dataset. - output_tr: TR value for output dataset (in seconds). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTrfixOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TRFIX_METADATA) - cargs = [] - cargs.append("3dTRfix") - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - cargs.append("-TRlist") - if tr_list is not None: - cargs.extend([ - "-TRlist", - execution.input_file(tr_list) - ]) - cargs.append("-TIMElist") - if time_list is not None: - cargs.extend([ - "-TIMElist", - execution.input_file(time_list) - ]) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-TRout") - if output_tr is not None: - cargs.extend([ - "-TRout", - str(output_tr) - ]) - ret = V3dTrfixOutputs( - root=execution.output_file("."), - output_file_head=execution.output_file(prefix + "+orig.HEAD"), - output_file_brik=execution.output_file(prefix + "+orig.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTrfixOutputs", - "V_3D_TRFIX_METADATA", - "v_3d_trfix", -] diff --git a/python/src/niwrap/afni/v_3d_tsgen.py b/python/src/niwrap/afni/v_3d_tsgen.py deleted file mode 100644 index 074469e07..000000000 --- a/python/src/niwrap/afni/v_3d_tsgen.py +++ /dev/null @@ -1,136 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSGEN_METADATA = Metadata( - id="99758b64781663ffd508cccdf61b5f963c784b4a.boutiques", - name="3dTSgen", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTsgenOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tsgen(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_tsgen( - input_file: InputPathType, - signal_label: str, - noise_label: str, - sigma_value: float, - output_file: str, - in_tr_flag: bool = False, - signal_constr: str | None = None, - noise_constr: str | None = None, - voxel_number: float | None = None, - signal_coef: str | None = None, - noise_coef: str | None = None, - bucket_config: str | None = None, - runner: Runner | None = None, -) -> V3dTsgenOutputs: - """ - This program generates an AFNI 3d+time data set based on user-specified signal - and noise models for each voxel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Filename of prototype 3d + time data file. - signal_label: Name of the (non-linear) signal model. - noise_label: Name of the (linear) noise model. - sigma_value: Standard deviation of additive Gaussian noise. - output_file: Filename of output 3d + time data file. - in_tr_flag: Set the TR of the created timeseries to be the TR of the\ - prototype dataset. The default is TR = 1. - signal_constr: Constraints for kth signal parameter. Format: k c d\ - where c <= gs[k] <= d. - noise_constr: Constraints for kth noise parameter. Format: k c d where\ - c+b[k] <= gn[k] <= d+b[k]. - voxel_number: Screen output for voxel number. - signal_coef: Write kth signal parameter gs[k]. Output 'fim' is written\ - to prefix filename. - noise_coef: Write kth noise parameter gn[k]. Output 'fim' is written to\ - prefix filename. - bucket_config: Create one AFNI 'bucket' dataset containing n\ - sub-bricks. n=0 creates the default output. Output 'bucket' is written\ - to prefixname. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTsgenOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSGEN_METADATA) - cargs = [] - cargs.append("3dTSgen") - cargs.append(execution.input_file(input_file)) - if in_tr_flag: - cargs.append("-inTR") - cargs.extend([ - "-signal", - signal_label - ]) - cargs.extend([ - "-noise", - noise_label - ]) - if signal_constr is not None: - cargs.extend([ - "-sconstr", - signal_constr - ]) - if noise_constr is not None: - cargs.extend([ - "-nconstr", - noise_constr - ]) - cargs.extend([ - "-sigma", - str(sigma_value) - ]) - if voxel_number is not None: - cargs.extend([ - "-voxel", - str(voxel_number) - ]) - cargs.extend([ - "-output", - output_file - ]) - if signal_coef is not None: - cargs.extend([ - "-scoef", - signal_coef - ]) - if noise_coef is not None: - cargs.extend([ - "-ncoef", - noise_coef - ]) - if bucket_config is not None: - cargs.extend([ - "-bucket", - bucket_config - ]) - ret = V3dTsgenOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTsgenOutputs", - "V_3D_TSGEN_METADATA", - "v_3d_tsgen", -] diff --git a/python/src/niwrap/afni/v_3d_tshift.py b/python/src/niwrap/afni/v_3d_tshift.py deleted file mode 100644 index e68cd8e45..000000000 --- a/python/src/niwrap/afni/v_3d_tshift.py +++ /dev/null @@ -1,166 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSHIFT_METADATA = Metadata( - id="da659a82f35577017cc02e2a49aea005b4e38e2f.boutiques", - name="3dTshift", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTshiftOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tshift(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - timing_file: OutputPathType - """Afni formatted timing file, if ``slice_timing`` is a list.""" - - -def v_3d_tshift( - in_file: InputPathType, - ignore: int | None = None, - interp: typing.Literal["Fourier", "linear", "cubic", "quintic", "heptic"] | None = None, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - rlt: bool = False, - rltplus: bool = False, - slice_encoding_direction: typing.Literal["k", "k-"] | None = None, - slice_timing: InputPathType | None = None, - slice_timing_2: list[float] | None = None, - tpattern: typing.Literal["alt+z", "altplus", "alt+z2", "alt-z", "altminus", "alt-z2", "seq+z", "seqplus", "seq-z", "seqminus"] | None = None, - tpattern_2: str | None = None, - tr: str | None = None, - tslice: int | None = None, - tzero: float | None = None, - runner: Runner | None = None, -) -> V3dTshiftOutputs: - """ - Shifts voxel time series from input so that separate slices are aligned to the - same temporal origin. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dtshift. - ignore: Ignore the first set of points specified. - interp: 'fourier' or 'linear' or 'cubic' or 'quintic' or 'heptic'.\ - Different interpolation methods (see 3dtshift for details) default =\ - fourier. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - rlt: Before shifting, remove the mean and linear trend. - rltplus: Before shifting, remove the mean and linear trend and later\ - put back the mean. - slice_encoding_direction: 'k' or 'k-'. Direction in which slice_timing\ - is specified (default: k). if negative,slice_timing is defined in\ - reverse order, that is, the first entry corresponds to the slice with\ - the largest index, and the final entry corresponds to slice index zero.\ - only in effect when slice_timing is passed as list, not when it is\ - passed as file. - slice_timing: file or string or a list of items which are a float. Time\ - offsets from the volume acquisition onset for each slice. - slice_timing_2: file or string or a list of items which are a float.\ - Time offsets from the volume acquisition onset for each slice. - tpattern: 'alt+z' or 'altplus' or 'alt+z2' or 'alt-z' or 'altminus' or\ - 'alt-z2' or 'seq+z' or 'seqplus' or 'seq-z' or 'seqminus' or a string.\ - Use specified slice time pattern rather than one in header. - tpattern_2: 'alt+z' or 'altplus' or 'alt+z2' or 'alt-z' or 'altminus'\ - or 'alt-z2' or 'seq+z' or 'seqplus' or 'seq-z' or 'seqminus' or a\ - string. Use specified slice time pattern rather than one in header. - tr: Manually set the tr. you can attach suffix "s" for seconds or "ms"\ - for milliseconds. - tslice: Align each slice to time offset of given slice. - tzero: Align each slice to given time offset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTshiftOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSHIFT_METADATA) - cargs = [] - cargs.append("3dTshift") - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - cargs.append(execution.input_file(in_file)) - if interp is not None: - cargs.extend([ - "-", - interp - ]) - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if rlt: - cargs.append("-rlt") - if rltplus: - cargs.append("-rlt+") - if slice_encoding_direction is not None: - cargs.append(slice_encoding_direction) - if slice_timing is not None: - cargs.extend([ - "-tpattern @", - execution.input_file(slice_timing) - ]) - if slice_timing_2 is not None: - cargs.extend([ - "-tpattern @", - *map(str, slice_timing_2) - ]) - if tpattern is not None: - cargs.extend([ - "-tpattern", - tpattern - ]) - if tpattern_2 is not None: - cargs.extend([ - "-tpattern", - tpattern_2 - ]) - if tr is not None: - cargs.extend([ - "-TR", - tr - ]) - if tslice is not None: - cargs.extend([ - "-slice", - str(tslice) - ]) - if tzero is not None: - cargs.extend([ - "-tzero", - str(tzero) - ]) - ret = V3dTshiftOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_tshift"), - out_file_=execution.output_file("out_file"), - timing_file=execution.output_file("timing_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTshiftOutputs", - "V_3D_TSHIFT_METADATA", - "v_3d_tshift", -] diff --git a/python/src/niwrap/afni/v_3d_tsmooth.py b/python/src/niwrap/afni/v_3d_tsmooth.py deleted file mode 100644 index 59fc6db27..000000000 --- a/python/src/niwrap/afni/v_3d_tsmooth.py +++ /dev/null @@ -1,141 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSMOOTH_METADATA = Metadata( - id="b237186199e1da14b990e2891bc27f1f59ceede0.boutiques", - name="3dTsmooth", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTsmoothOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tsmooth(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Smoothed 3D+time dataset""" - - -def v_3d_tsmooth( - input_dataset: InputPathType, - prefix: str | None = None, - datum_type: str | None = None, - lin_filter: bool = False, - med_filter: bool = False, - osf_filter: bool = False, - lin_filter_custom: float | None = None, - hamming: int | None = None, - blackman: int | None = None, - custom_filter: InputPathType | None = None, - extend: bool = False, - zero: bool = False, - trend: bool = False, - adaptive: int | None = None, - runner: Runner | None = None, -) -> V3dTsmoothOutputs: - """ - Smooths each voxel time series in a 3D+time dataset and produces as output a new - 3D+time dataset (e.g., lowpass filter in time). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: The input 3D+time dataset. - prefix: Sets the prefix of the output dataset. - datum_type: Coerce output dataset to be stored as the given type. - lin_filter: 3 point linear filter: 0.15*a + 0.70*b + 0.15*c. - med_filter: 3 point median filter: median(a,b,c). - osf_filter: 3 point order statistics filter: 0.15*min(a,b,c) +\ - 0.70*median(a,b,c) + 0.15*max(a,b,c). - lin_filter_custom: 3 point linear filter with custom weight:\ - 0.5*(1-m)*a + m*b + 0.5*(1-m)*c. - hamming: Use N point Hamming window filter. - blackman: Use N point Blackman window filter. - custom_filter: Use custom filter with coefficients from a specified\ - file. - extend: BEFORE: use the first value; AFTER: use the last value. - zero: BEFORE and AFTER: use zero. - trend: Compute a linear trend, and extrapolate BEFORE and AFTER. - adaptive: Use adaptive mean filtering of width N (N must be odd and\ - bigger than 3). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTsmoothOutputs`). - """ - if lin_filter_custom is not None and not (0 <= lin_filter_custom <= 1): - raise ValueError(f"'lin_filter_custom' must be between 0 <= x <= 1 but was {lin_filter_custom}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSMOOTH_METADATA) - cargs = [] - cargs.append("3dTsmooth") - cargs.append(execution.input_file(input_dataset)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum_type is not None: - cargs.extend([ - "-datum", - datum_type - ]) - if lin_filter: - cargs.append("-lin") - if med_filter: - cargs.append("-med") - if osf_filter: - cargs.append("-osf") - if lin_filter_custom is not None: - cargs.extend([ - "-3lin", - str(lin_filter_custom) - ]) - if hamming is not None: - cargs.extend([ - "-hamming", - str(hamming) - ]) - if blackman is not None: - cargs.extend([ - "-blackman", - str(blackman) - ]) - if custom_filter is not None: - cargs.extend([ - "-custom", - execution.input_file(custom_filter) - ]) - if extend: - cargs.append("-EXTEND") - if zero: - cargs.append("-ZERO") - if trend: - cargs.append("-TREND") - if adaptive is not None: - cargs.extend([ - "-adaptive", - str(adaptive) - ]) - ret = V3dTsmoothOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTsmoothOutputs", - "V_3D_TSMOOTH_METADATA", - "v_3d_tsmooth", -] diff --git a/python/src/niwrap/afni/v_3d_tsort.py b/python/src/niwrap/afni/v_3d_tsort.py deleted file mode 100644 index 68f5795fc..000000000 --- a/python/src/niwrap/afni/v_3d_tsort.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSORT_METADATA = Metadata( - id="9582bd99d8599dfb4a866ed6cf00ba5f5a847ebe.boutiques", - name="3dTsort", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTsortOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tsort(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Main default output of 3dTsort""" - - -def v_3d_tsort( - input_file: InputPathType, - prefix: str | None = None, - dec: bool = False, - rank: bool = False, - ind: bool = False, - val: bool = False, - random_: bool = False, - ranfft: bool = False, - randft: bool = False, - datum: str | None = None, - runner: Runner | None = None, -) -> V3dTsortOutputs: - """ - Sorts each voxel in a dataset and produces a new dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input dataset to be sorted. - prefix: Prefix for the output dataset. - dec: Sort into decreasing order. - rank: Output rank instead of sorted values; ranks range from 1 to Nvals. - ind: Output sorting index (0 to Nvals -1). - val: Output sorted values (default). - random_: Randomly shuffle (permute) the time points in each voxel. - ranfft: Randomize each time series by scrambling the FFT phase. - randft: Randomize each time series by scrambling the DFT phase. - datum: Coerce the output data to be stored as the given type (byte,\ - short, or float). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTsortOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSORT_METADATA) - cargs = [] - cargs.append("3dTsort") - cargs.append(execution.input_file(input_file)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if dec: - cargs.append("-dec") - if rank: - cargs.append("-rank") - if ind: - cargs.append("-ind") - if val: - cargs.append("-val") - if random_: - cargs.append("-random") - if ranfft: - cargs.append("-ranFFT") - if randft: - cargs.append("-ranDFT") - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - ret = V3dTsortOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTsortOutputs", - "V_3D_TSORT_METADATA", - "v_3d_tsort", -] diff --git a/python/src/niwrap/afni/v_3d_tsplit4_d.py b/python/src/niwrap/afni/v_3d_tsplit4_d.py deleted file mode 100644 index 70d7ecebf..000000000 --- a/python/src/niwrap/afni/v_3d_tsplit4_d.py +++ /dev/null @@ -1,78 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSPLIT4_D_METADATA = Metadata( - id="501ddadcbbb7f97f47c1b740f0aae3aed7a2a8c3.boutiques", - name="3dTsplit4D", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTsplit4DOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tsplit4_d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfiles: OutputPathType - """Multiple 3D single-brick output files""" - - -def v_3d_tsplit4_d( - prefix: str, - infile: InputPathType, - keep_datum: bool = False, - digits: float | None = None, - runner: Runner | None = None, -) -> V3dTsplit4DOutputs: - """ - Convert a 3D+time dataset into multiple 3D single-brick files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix of the output datasets (e.g., out/epi). - infile: Input 3D+time dataset (e.g., epi_r1+orig). - keep_datum: Output uses original datum (no conversion to float). - digits: Number of digits to use for output filenames. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTsplit4DOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSPLIT4_D_METADATA) - cargs = [] - cargs.append("3dTsplit4D") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append(execution.input_file(infile)) - if keep_datum: - cargs.append("-keep_datum") - if digits is not None: - cargs.extend([ - "-digits", - str(digits) - ]) - ret = V3dTsplit4DOutputs( - root=execution.output_file("."), - outfiles=execution.output_file(prefix + "*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTsplit4DOutputs", - "V_3D_TSPLIT4_D_METADATA", - "v_3d_tsplit4_d", -] diff --git a/python/src/niwrap/afni/v_3d_tstat.py b/python/src/niwrap/afni/v_3d_tstat.py deleted file mode 100644 index 8b4492ef8..000000000 --- a/python/src/niwrap/afni/v_3d_tstat.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TSTAT_METADATA = Metadata( - id="a4a735ff0a0504c29b4133276ff755cc4b6eaa8f.boutiques", - name="3dTstat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTstatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tstat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3d_tstat( - in_file: InputPathType, - mask: InputPathType | None = None, - num_threads: int | None = None, - options: str | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - runner: Runner | None = None, -) -> V3dTstatOutputs: - """ - Compute voxel-wise statistics using AFNI 3dTstat command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dtstat. - mask: Mask file. - num_threads: Set number of threads. - options: Selected statistical output. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTstatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TSTAT_METADATA) - cargs = [] - cargs.append("3dTstat") - cargs.append(execution.input_file(in_file)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if num_threads is not None: - cargs.append(str(num_threads)) - if options is not None: - cargs.append(options) - if outputtype is not None: - cargs.append(outputtype) - ret = V3dTstatOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_tstat"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTstatOutputs", - "V_3D_TSTAT_METADATA", - "v_3d_tstat", -] diff --git a/python/src/niwrap/afni/v_3d_tto1_d.py b/python/src/niwrap/afni/v_3d_tto1_d.py deleted file mode 100644 index d393fb9c5..000000000 --- a/python/src/niwrap/afni/v_3d_tto1_d.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TTO1_D_METADATA = Metadata( - id="cad19c8c36d58b1690c78ef0d6c215e09c7e7cce.boutiques", - name="3dTto1D", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTto1DOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_tto1_d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output 1D time series file""" - - -def v_3d_tto1_d( - input_dataset: InputPathType, - method: str, - automask: bool = False, - mask: InputPathType | None = None, - prefix: str | None = None, - verbose: float | None = None, - runner: Runner | None = None, -) -> V3dTto1DOutputs: - """ - Collapse a 4D time series to a 1D time series. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Specify input dataset. This should be a set of 3D time\ - series. If the input is in 1D format, a transpose operator will\ - typically be required. - method: Specify 4D to 1D conversion method. Methods include: enorm,\ - dvars, srms, shift_srms, mdiff, smdiff, 4095_count, 4095_frac,\ - 4095_warn. - automask: Restrict computation to automask. - mask: Restrict computation to given mask. - prefix: Specify output file. Default is stdout. - verbose: Specify verbose level. Default is 1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTto1DOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TTO1_D_METADATA) - cargs = [] - cargs.append("3dTto1D") - cargs.append("-input") - cargs.append(execution.input_file(input_dataset)) - cargs.append("-method") - cargs.extend([ - "-method", - method - ]) - if automask: - cargs.append("-automask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - ret = V3dTto1DOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTto1DOutputs", - "V_3D_TTO1_D_METADATA", - "v_3d_tto1_d", -] diff --git a/python/src/niwrap/afni/v_3d_twoto_complex.py b/python/src/niwrap/afni/v_3d_twoto_complex.py deleted file mode 100644 index efb470dbe..000000000 --- a/python/src/niwrap/afni/v_3d_twoto_complex.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_TWOTO_COMPLEX_METADATA = Metadata( - id="bf9493b3c937b76d0584de14a9b270a71cce9ca0.boutiques", - name="3dTwotoComplex", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dTwotoComplexOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_twoto_complex(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_brick: OutputPathType | None - """Output complex-valued dataset with prefix""" - out_head: OutputPathType | None - """Header for the complex-valued dataset""" - - -def v_3d_twoto_complex( - dataset1: InputPathType, - dataset2: InputPathType | None = None, - prefix: str | None = None, - ri: bool = False, - mp: bool = False, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dTwotoComplexOutputs: - """ - Converts 2 sub-bricks of input to a complex-valued dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset1: Input dataset (either as 1 dataset with 2 sub-bricks or 2\ - separate datasets). - dataset2: Second input dataset (optional if 2 sub-bricks in the first\ - dataset). - prefix: Prefix for the output dataset [default='cmplx']. - ri: Specify that the 2 inputs are real and imaginary parts [this is the\ - default]. - mp: Specify that the 2 inputs are magnitude and phase [phase is in\ - radians]. - mask: Only output nonzero values where the mask dataset is nonzero. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dTwotoComplexOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_TWOTO_COMPLEX_METADATA) - cargs = [] - cargs.append("3dTwotoComplex") - cargs.append(execution.input_file(dataset1)) - if dataset2 is not None: - cargs.append(execution.input_file(dataset2)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if ri: - cargs.append("-RI") - if mp: - cargs.append("-MP") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - ret = V3dTwotoComplexOutputs( - root=execution.output_file("."), - out_brick=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - out_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dTwotoComplexOutputs", - "V_3D_TWOTO_COMPLEX_METADATA", - "v_3d_twoto_complex", -] diff --git a/python/src/niwrap/afni/v_3d_undump.py b/python/src/niwrap/afni/v_3d_undump.py deleted file mode 100644 index 6285049f7..000000000 --- a/python/src/niwrap/afni/v_3d_undump.py +++ /dev/null @@ -1,159 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_UNDUMP_METADATA = Metadata( - id="f2538bc9ff4b0df64cd201f00d892051a11fe2c2.boutiques", - name="3dUndump", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dUndumpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_undump(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Main output dataset""" - - -def v_3d_undump( - input_files: list[InputPathType], - prefix: str | None = None, - master: InputPathType | None = None, - dimensions: list[float] | None = None, - mask: InputPathType | None = None, - datatype: str | None = None, - dval: float | None = None, - fval: float | None = None, - xyz: bool = False, - sphere_radius: float | None = None, - cube_mode: bool = False, - orient: str | None = None, - head_only: bool = False, - roimask: InputPathType | None = None, - allow_nan: bool = False, - runner: Runner | None = None, -) -> V3dUndumpOutputs: - """ - Assembles a 3D dataset from an ASCII list of coordinates and optionally values. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input ASCII file(s), with one voxel specification per\ - line. - prefix: 'ppp' is the prefix for the output dataset [default = undump]. - master: 'mmm' is the master dataset, whose geometry will determine the\ - geometry of the output. - dimensions: Sets the dimensions of the output dataset to be I by J by K\ - voxels. - mask: Specifies a mask dataset 'MMM', which will control which voxels\ - are allowed to get values set. - datatype: 'type' determines the voxel data type of the output, which\ - may be byte, short, or float [default = short]. - dval: 'vvv' is the default value stored in each input voxel that does\ - not have a value supplied in the input file [default = 1]. - fval: 'fff' is the fill value, used for each voxel in the output\ - dataset that is NOT listed in the input file [default = 0]. - xyz: Coordinates in the input file are (x,y,z) spatial coordinates, in\ - mm. - sphere_radius: Specifies that a sphere of radius 'rrr' will be filled\ - about each input (x,y,z) or (i,j,k) voxel. - cube_mode: Put cubes down instead of spheres. The 'radius' then is half\ - the length of a side. - orient: Specifies the coordinate order used by -xyz. The code must be 3\ - letters, one each from the pairs {R,L} {A,P} {I,S}. - head_only: Creates only the .HEAD file. - roimask: Specifies which voxels get what numbers by using a dataset\ - 'rrr', instead of coordinates. - allow_nan: Allow NaN (not-a-number) values to be entered. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dUndumpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_UNDUMP_METADATA) - cargs = [] - cargs.append("3dUndump") - cargs.extend([execution.input_file(f) for f in input_files]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if master is not None: - cargs.extend([ - "-master", - execution.input_file(master) - ]) - if dimensions is not None: - cargs.extend([ - "-dimen", - *map(str, dimensions) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if datatype is not None: - cargs.extend([ - "-datum", - datatype - ]) - if dval is not None: - cargs.extend([ - "-dval", - str(dval) - ]) - if fval is not None: - cargs.extend([ - "-fval", - str(fval) - ]) - if xyz: - cargs.append("-xyz") - if sphere_radius is not None: - cargs.extend([ - "-srad", - str(sphere_radius) - ]) - if cube_mode: - cargs.append("-cubes") - if orient is not None: - cargs.extend([ - "-orient", - orient - ]) - if head_only: - cargs.append("-head_only") - if roimask is not None: - cargs.extend([ - "-ROImask", - execution.input_file(roimask) - ]) - if allow_nan: - cargs.append("-allow_NaN") - ret = V3dUndumpOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dUndumpOutputs", - "V_3D_UNDUMP_METADATA", - "v_3d_undump", -] diff --git a/python/src/niwrap/afni/v_3d_unifize.py b/python/src/niwrap/afni/v_3d_unifize.py deleted file mode 100644 index 5486d1c06..000000000 --- a/python/src/niwrap/afni/v_3d_unifize.py +++ /dev/null @@ -1,172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_UNIFIZE_METADATA = Metadata( - id="4939198692fcd53c992cee61612265ccd7c9ddca.boutiques", - name="3dUnifize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dUnifizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_unifize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Unifized file.""" - scale_file_outfile: OutputPathType | None - """Scale factor file.""" - - -def v_3d_unifize( - in_file: InputPathType, - cl_frac: float | None = None, - epi: bool = False, - gm: bool = False, - no_duplo: bool = False, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - quiet: bool = False, - rbt: list[float] | None = None, - scale_file: InputPathType | None = None, - t2: bool = False, - t2_up: float | None = None, - urad: float | None = None, - runner: Runner | None = None, -) -> V3dUnifizeOutputs: - """ - 3dUnifize - for uniformizing image intensity - * The input dataset is supposed to be a T1-weighted volume, possibly already - skull-stripped (e.g., via 3dSkullStrip). However, this program can be a - useful step to take BEFORE 3dSkullStrip, since the latter program can fail - if the input volume is strongly shaded -- 3dUnifize will (mostly) remove - such shading artifacts. - * The output dataset has the white matter (WM) intensity approximately - uniformized across space, and scaled to peak at about 1000. - * The output dataset is always stored in float format! - * If the input dataset has more than 1 sub-brick, only sub-brick #0 will be - processed! - * Want to correct EPI datasets for nonuniformity? You can try the new and - experimental [Mar 2017] '-EPI' option. - * The principal motive for this program is for use in an image registration - script, and it may or may not be useful otherwise. - * This program replaces the older (and very different) 3dUniformize, which - is no longer maintained and may sublimate at any moment. (In other words, we - do not recommend the use of 3dUniformize.). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dunifize. - cl_frac: Option for afni experts only.set the automask 'clip level\ - fraction'. must be between 0.1 and 0.9. a small fraction means to make\ - the initial threshold for clipping (a la 3dcliplevel) smaller, which\ - will tend to make the mask larger. [default=0.1]. - epi: Assume the input dataset is a t2 (or t2\\*) weighted epi time\ - series. after computing the scaling, apply it to all volumes (trs) in\ - the input dataset. that is, a given voxel will be scaled by the same\ - factor at each tr. this option also implies '-noduplo' and '-t2'.this\ - option turns off '-gm' if you turned it on. - gm: Also scale to unifize 'gray matter' = lower intensity voxels (to\ - aid in registering images from different scanners). - no_duplo: Do not use the 'duplo down' step; this can be useful for\ - lower resolution datasets. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - quiet: Don't print the progress messages. - rbt: (a float, a float, a float). Option for afni experts only.specify\ - the 3 parameters for the algorithm:r = radius; same as given by option\ - '-urad', [default=18.3]b = bottom percentile of normalizing data range,\ - [default=70.0]r = top percentile of normalizing data range,\ - [default=80.0]. - scale_file: Output file name to save the scale factor used at each\ - voxel . - t2: Treat the input as if it were t2-weighted, rather than t1-weighted.\ - this processing is done simply by inverting the image contrast,\ - processing it as if that result were t1-weighted, and then re-inverting\ - the results counts of voxel overlap, i.e., each voxel will contain the\ - number of masks that it is set in. - t2_up: Option for afni experts only.set the upper percentile point used\ - for t2-t1 inversion. allowed to be anything between 90 and 100\ - (inclusive), with default to 98.5 (for no good reason). - urad: Sets the radius (in voxels) of the ball used for the sneaky\ - trick. default value is 18.3, and should be changed proportionally if\ - the dataset voxel size differs significantly from 1 mm. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dUnifizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_UNIFIZE_METADATA) - cargs = [] - cargs.append("3dUnifize") - if cl_frac is not None: - cargs.extend([ - "-clfrac", - str(cl_frac) - ]) - if epi: - cargs.append("-EPI") - if gm: - cargs.append("-GM") - cargs.extend([ - "-input", - execution.input_file(in_file) - ]) - if no_duplo: - cargs.append("-noduplo") - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if quiet: - cargs.append("-quiet") - if rbt is not None: - cargs.extend([ - "-rbt", - *map(str, rbt) - ]) - if scale_file is not None: - cargs.extend([ - "-ssave", - execution.input_file(scale_file) - ]) - if t2: - cargs.append("-T2") - if t2_up is not None: - cargs.extend([ - "-T2up", - str(t2_up) - ]) - if urad is not None: - cargs.extend([ - "-Urad", - str(urad) - ]) - ret = V3dUnifizeOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_unifized"), - out_file_=execution.output_file("out_file"), - scale_file_outfile=execution.output_file(pathlib.Path(scale_file).name) if (scale_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dUnifizeOutputs", - "V_3D_UNIFIZE_METADATA", - "v_3d_unifize", -] diff --git a/python/src/niwrap/afni/v_3d_upsample.py b/python/src/niwrap/afni/v_3d_upsample.py deleted file mode 100644 index df58ee9f0..000000000 --- a/python/src/niwrap/afni/v_3d_upsample.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_UPSAMPLE_METADATA = Metadata( - id="e15a35601ca3dbf1d8bf47d2d707df818a6560ac.boutiques", - name="3dUpsample", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dUpsampleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_upsample(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brik: OutputPathType | None - """Upsampled dataset in BRIK format.""" - output_head: OutputPathType | None - """Header information for the upsampled dataset.""" - - -def v_3d_upsample( - upsample_factor: int, - input_dataset: str, - linear_interpolation: bool = False, - output_prefix: str | None = None, - verbose_flag: bool = False, - datatype: str | None = None, - runner: Runner | None = None, -) -> V3dUpsampleOutputs: - """ - Upsamples a 3D+time dataset in the time direction by a specified factor. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - upsample_factor: Upsampling factor; must be between 2 and 320\ - (inclusive). - input_dataset: Input dataset. - linear_interpolation: Use linear interpolation instead of 7th order\ - polynomial interpolation. - output_prefix: Define the prefix name of the output dataset; default is\ - 'Upsam'. - verbose_flag: Print verbose output. - datatype: Specify the datatype for the output dataset (float, short,\ - byte); default is float. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dUpsampleOutputs`). - """ - if not (2 <= upsample_factor <= 320): - raise ValueError(f"'upsample_factor' must be between 2 <= x <= 320 but was {upsample_factor}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_UPSAMPLE_METADATA) - cargs = [] - cargs.append("3dUpsample") - cargs.extend([ - "-n", - str(upsample_factor) - ]) - cargs.extend([ - "-input", - input_dataset - ]) - if linear_interpolation: - cargs.append("-1") - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if verbose_flag: - cargs.append("-verb") - if datatype is not None: - cargs.extend([ - "-datum", - datatype - ]) - ret = V3dUpsampleOutputs( - root=execution.output_file("."), - output_brik=execution.output_file(output_prefix + "+orig.BRIK") if (output_prefix is not None) else None, - output_head=execution.output_file(output_prefix + "+orig.HEAD") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dUpsampleOutputs", - "V_3D_UPSAMPLE_METADATA", - "v_3d_upsample", -] diff --git a/python/src/niwrap/afni/v_3d_vec_rgb_to_hsl.py b/python/src/niwrap/afni/v_3d_vec_rgb_to_hsl.py deleted file mode 100644 index 201a815df..000000000 --- a/python/src/niwrap/afni/v_3d_vec_rgb_to_hsl.py +++ /dev/null @@ -1,89 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_VEC_RGB_TO_HSL_METADATA = Metadata( - id="6117ba68b426e9e30b15374be67ca0934595ccef.boutiques", - name="3dVecRGB_to_HSL", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dVecRgbToHslOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_vec_rgb_to_hsl(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_hsl_dataset: OutputPathType - """Output HSL dataset""" - - -def v_3d_vec_rgb_to_hsl( - prefix: str, - in_vec: InputPathType, - mask: InputPathType | None = None, - in_scal: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dVecRgbToHslOutputs: - """ - Convert a 3-brick RGB (red, green, blue) data set to an HSL (hue, saturation, - luminance) one. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name part. - in_vec: Input RGB vector file of three bricks, presumably each having\ - values in the interval [0,1]. - mask: Whole brain mask within which to calculate things. Otherwise,\ - data should be masked already. - in_scal: Scalar file (single brick) which will be appended to the\ - output file, mainly aimed at loading in an FA data set for tract volume\ - coloration. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dVecRgbToHslOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_VEC_RGB_TO_HSL_METADATA) - cargs = [] - cargs.append("3dVecRGB_to_HSL") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-in_vec", - execution.input_file(in_vec) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if in_scal is not None: - cargs.extend([ - "-in_scal", - execution.input_file(in_scal) - ]) - ret = V3dVecRgbToHslOutputs( - root=execution.output_file("."), - output_hsl_dataset=execution.output_file(prefix + "_HSL+*.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dVecRgbToHslOutputs", - "V_3D_VEC_RGB_TO_HSL_METADATA", - "v_3d_vec_rgb_to_hsl", -] diff --git a/python/src/niwrap/afni/v_3d_vol2_surf.py b/python/src/niwrap/afni/v_3d_vol2_surf.py deleted file mode 100644 index 38d12319d..000000000 --- a/python/src/niwrap/afni/v_3d_vol2_surf.py +++ /dev/null @@ -1,306 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_VOL2_SURF_METADATA = Metadata( - id="c02eb3df673097f601aee76ef3ab0760f92ddec8.boutiques", - name="3dVol2Surf", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dVol2SurfOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_vol2_surf(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_1d_file: OutputPathType | None - """1D output file""" - out_niml_file: OutputPathType | None - """NIML output file""" - seg_coords_file: OutputPathType | None - """Segment coordinates output file""" - - -def v_3d_vol2_surf( - spec_file: InputPathType, - sv: InputPathType, - grid_parent: InputPathType, - map_func: str, - surf_a: str, - surf_b: str | None = None, - out_1_d: str | None = None, - out_niml: str | None = None, - use_norms: bool = False, - norm_len: float | None = None, - first_node: float | None = None, - last_node: float | None = None, - debug_level: float | None = None, - dnode: float | None = None, - f_steps: float | None = None, - f_index: str | None = None, - f_p1_mm: float | None = None, - f_pn_mm: float | None = None, - f_p1_fr: float | None = None, - f_pn_fr: float | None = None, - skip_col_nodes: bool = False, - skip_col_1dindex: bool = False, - skip_col_i: bool = False, - skip_col_j: bool = False, - skip_col_k: bool = False, - skip_col_vals: bool = False, - no_headers: bool = False, - save_seg_coords: str | None = None, - cmask: str | None = None, - gp_index: float | None = None, - oob_index: float | None = None, - oob_value: float | None = None, - oom_value: float | None = None, - outcols_afni_nsd: bool = False, - outcols_1_result: bool = False, - outcols_results: bool = False, - outcols_nsd_format: bool = False, - help_: bool = False, - hist: bool = False, - version: bool = False, - keep_norm_dir: bool = False, - reverse_norm_dir: bool = False, - runner: Runner | None = None, -) -> V3dVol2SurfOutputs: - """ - Map data from a volume domain to a surface domain. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: SUMA spec file. - sv: AFNI volume dataset mapped by the surface. - grid_parent: AFNI volume dataset used as a grid and orientation master\ - for output. - map_func: Filter for values along the segment. - surf_a: Name of surface A from the spec file. - surf_b: Name of surface B from the spec file. - out_1_d: Specify a 1D file for the output. - out_niml: Specify a niml file for the output. - use_norms: Use normals for second surface. - norm_len: Length for node normals. - first_node: Skip all previous nodes. - last_node: Skip all following nodes. - debug_level: Verbose output level. - dnode: Node for debug. - f_steps: Number of steps along each segment (defines the number of\ - evenly spaced points along each segment). - f_index: Whether to use all segment point values or only those\ - corresponding to unique volume voxels. - f_p1_mm: Distance in millimeters to add to the first point of each line\ - segment. - f_pn_mm: Distance in millimeters to add to the second point of each\ - line segment. - f_p1_fr: Fractional distance to add to the first point of each line\ - segment. - f_pn_fr: Fractional distance to add to the second point of each line\ - segment. - skip_col_nodes: Do not output node column. - skip_col_1dindex: Do not output 1dindex column. - skip_col_i: Do not output i column. - skip_col_j: Do not output j column. - skip_col_k: Do not output k column. - skip_col_vals: Do not output vals column. - no_headers: Do not output column headers. - save_seg_coords: Save segment coordinates to a file. - cmask: Command for dataset mask. - gp_index: Choose grid_parent sub-brick. - oob_index: Specify default index for out of bounds nodes. - oob_value: Specify default value for out of bounds nodes. - oom_value: Specify default value for out of mask nodes. - outcols_afni_nsd: Output nodes and one result column. - outcols_1_result: Output only one result column. - outcols_results: Output only all result columns. - outcols_nsd_format: Output nodes and all results (NI_SURF_DSET format). - help_: Show this help. - hist: Show revision history. - version: Show version information. - keep_norm_dir: Keep the direction of the normals. - reverse_norm_dir: Reverse the normal directions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dVol2SurfOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_VOL2_SURF_METADATA) - cargs = [] - cargs.append("3dVol2Surf") - cargs.append(execution.input_file(spec_file)) - cargs.extend([ - "-sv", - execution.input_file(sv) - ]) - cargs.extend([ - "-grid_parent", - execution.input_file(grid_parent) - ]) - cargs.extend([ - "-map_func", - map_func - ]) - cargs.extend([ - "-surf_A", - surf_a - ]) - if surf_b is not None: - cargs.extend([ - "-surf_B", - surf_b - ]) - if out_1_d is not None: - cargs.extend([ - "-out_1D", - out_1_d - ]) - if out_niml is not None: - cargs.extend([ - "-out_niml", - out_niml - ]) - if use_norms: - cargs.append("-use_norms") - if norm_len is not None: - cargs.extend([ - "-norm_len", - str(norm_len) - ]) - if first_node is not None: - cargs.extend([ - "-first_node", - str(first_node) - ]) - if last_node is not None: - cargs.extend([ - "-last_node", - str(last_node) - ]) - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if dnode is not None: - cargs.extend([ - "-dnode", - str(dnode) - ]) - if f_steps is not None: - cargs.extend([ - "-f_steps", - str(f_steps) - ]) - if f_index is not None: - cargs.extend([ - "-f_index", - f_index - ]) - if f_p1_mm is not None: - cargs.extend([ - "-f_p1_mm", - str(f_p1_mm) - ]) - if f_pn_mm is not None: - cargs.extend([ - "-f_pn_mm", - str(f_pn_mm) - ]) - if f_p1_fr is not None: - cargs.extend([ - "-f_p1_fr", - str(f_p1_fr) - ]) - if f_pn_fr is not None: - cargs.extend([ - "-f_pn_fr", - str(f_pn_fr) - ]) - if skip_col_nodes: - cargs.append("-skip_col_nodes") - if skip_col_1dindex: - cargs.append("-skip_col_1dindex") - if skip_col_i: - cargs.append("-skip_col_i") - if skip_col_j: - cargs.append("-skip_col_j") - if skip_col_k: - cargs.append("-skip_col_k") - if skip_col_vals: - cargs.append("-skip_col_vals") - if no_headers: - cargs.append("-no_headers") - if save_seg_coords is not None: - cargs.extend([ - "-save_seg_coords", - save_seg_coords - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if gp_index is not None: - cargs.extend([ - "-gp_index", - str(gp_index) - ]) - if oob_index is not None: - cargs.extend([ - "-oob_index", - str(oob_index) - ]) - if oob_value is not None: - cargs.extend([ - "-oob_value", - str(oob_value) - ]) - if oom_value is not None: - cargs.extend([ - "-oom_value", - str(oom_value) - ]) - if outcols_afni_nsd: - cargs.append("-outcols_afni_NSD") - if outcols_1_result: - cargs.append("-outcols_1_result") - if outcols_results: - cargs.append("-outcols_results") - if outcols_nsd_format: - cargs.append("-outcols_NSD_format") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if version: - cargs.append("-version") - if keep_norm_dir: - cargs.append("-keep_norm_dir") - if reverse_norm_dir: - cargs.append("-reverse_norm_dir") - ret = V3dVol2SurfOutputs( - root=execution.output_file("."), - out_1d_file=execution.output_file(out_1_d) if (out_1_d is not None) else None, - out_niml_file=execution.output_file(out_niml) if (out_niml is not None) else None, - seg_coords_file=execution.output_file(save_seg_coords) if (save_seg_coords is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dVol2SurfOutputs", - "V_3D_VOL2_SURF_METADATA", - "v_3d_vol2_surf", -] diff --git a/python/src/niwrap/afni/v_3d_warp.py b/python/src/niwrap/afni/v_3d_warp.py deleted file mode 100644 index de68e7d68..000000000 --- a/python/src/niwrap/afni/v_3d_warp.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_WARP_METADATA = Metadata( - id="88d290dfb4d4ef49e72b5e10be676165a5596dc2.boutiques", - name="3dWarp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dWarpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_warp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3d_warp( - dataset: str, - runner: Runner | None = None, -) -> V3dWarpOutputs: - """ - Warp (spatially transform) one 3D dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset to be warped. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dWarpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_WARP_METADATA) - cargs = [] - cargs.append("3dWarp") - cargs.append("[OPTIONS]") - cargs.append(dataset) - ret = V3dWarpOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dWarpOutputs", - "V_3D_WARP_METADATA", - "v_3d_warp", -] diff --git a/python/src/niwrap/afni/v_3d_warp_drive.py b/python/src/niwrap/afni/v_3d_warp_drive.py deleted file mode 100644 index 503466bf3..000000000 --- a/python/src/niwrap/afni/v_3d_warp_drive.py +++ /dev/null @@ -1,270 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_WARP_DRIVE_METADATA = Metadata( - id="0c165837a84160290a1d8256b9238ca4ea37da6a.boutiques", - name="3dWarpDrive", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dWarpDriveOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_warp_drive(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Warped dataset output""" - output_summary: OutputPathType | None - """Summary of calculations""" - oned_output_file: OutputPathType | None - """File with warping parameters""" - matrix_output_file: OutputPathType | None - """File with transformation matrices""" - - -def v_3d_warp_drive( - dataset: InputPathType, - base_dataset: InputPathType, - prefix: str, - shift_only: bool = False, - shift_rotate: bool = False, - shift_rotate_scale: bool = False, - affine_general: bool = False, - bilinear_general: bool = False, - linear: bool = False, - cubic: bool = False, - nn: bool = False, - quintic: bool = False, - input_dataset: InputPathType | None = None, - verbosity_flag: bool = False, - summary_file: str | None = None, - max_iterations: int | None = None, - delta: float | None = None, - weight: str | None = None, - convergence_thresh: float | None = None, - twopass: bool = False, - final_mode: str | None = None, - parfix: list[str] | None = None, - oned_file: InputPathType | None = None, - float_format: bool = False, - coarserot_init: bool = False, - oned_matrix_save: InputPathType | None = None, - sdu_order: bool = False, - sud_order: bool = False, - dsu_order: bool = False, - dus_order: bool = False, - usd_order: bool = False, - uds_order: bool = False, - supper_s_matrix: bool = False, - slower_s_matrix: bool = False, - ashift: bool = False, - bshift: bool = False, - runner: Runner | None = None, -) -> V3dWarpDriveOutputs: - """ - Warp a dataset to match another one (the base) using an affine transformation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - base_dataset: Load dataset as the base to which the input dataset will\ - be matched. This is a mandatory option. - prefix: Sets the prefix of the output dataset. If 'NULL', no output\ - dataset is written. - shift_only: 3 parameters (shifts). - shift_rotate: 6 parameters (shifts + angles). - shift_rotate_scale: 9 parameters (shifts + angles + scale factors). - affine_general: 12 parameters (3 shifts + 3x3 matrix). - bilinear_general: 39 parameters (3 + 3x3 + 3x3x3). Not implemented and\ - will never be. - linear: Linear interpolation method. - cubic: Cubic interpolation method. - nn: Nearest neighbor interpolation method [default]. - quintic: Quintic interpolation method. - input_dataset: Specify the input dataset anywhere in the command line\ - option list. - verbosity_flag: Print out lots of information along the way. - summary_file: Save summary of calculations into text file. If value is\ - '-', summary goes to stdout. - max_iterations: Allow up to 'm' iterations for convergence. - delta: Distance, in voxel size, used to compute image derivatives using\ - finite differences. [Default=1.0]. - weight: Set the weighting applied to each voxel proportional to the\ - brick specified here. [Default=computed by program from base]. - convergence_thresh: Set the convergence parameter to be RMS 't' voxels\ - movement between iterations. [Default=0.03]. - twopass: Do the parameter estimation in two passes, coarse-but-fast\ - first, then fine-but-slow second. - final_mode: Set the final warp to be interpolated using 'mode'. - parfix: Fix the n'th parameter of the warp model to the value 'v'. More\ - than one -parfix option can be used. - oned_file: Write out the warping parameters to this file. - float_format: Write output dataset in float format, even if input\ - dataset is short or byte. - coarserot_init: Initialize shift+rotation parameters by a brute force\ - coarse search. - oned_matrix_save: Save base-to-input transformation matrices in\ - specified file. If the file does not end in '.1D', the program will\ - append '.aff12.1D'. - sdu_order: Set the order of the matrix multiplication for the affine\ - transformations (S=triangular shear, D=diagonal scaling matrix,\ - U=rotation matrix). - sud_order: Set the order of the matrix multiplication for the affine\ - transformations (S=triangular shear, U=rotation matrix, D=diagonal\ - scaling matrix). - dsu_order: Set the order of the matrix multiplication for the affine\ - transformations (D=diagonal scaling matrix, S=triangular shear,\ - U=rotation matrix). - dus_order: Set the order of the matrix multiplication for the affine\ - transformations (D=diagonal scaling matrix, U=rotation matrix,\ - S=triangular shear). - usd_order: Set the order of the matrix multiplication for the affine\ - transformations (U=rotation matrix, S=triangular shear, D=diagonal\ - scaling matrix). - uds_order: Set the order of the matrix multiplication for the affine\ - transformations (U=rotation matrix, D=diagonal scaling matrix,\ - S=triangular shear). - supper_s_matrix: Set the S matrix to be upper triangular. - slower_s_matrix: Set the S matrix to be lower triangular. - ashift: Apply the shift parameters after the matrix transformation. - bshift: Apply the shift parameters before the matrix transformation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dWarpDriveOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_WARP_DRIVE_METADATA) - cargs = [] - cargs.append("3dWarpDrive") - cargs.append(execution.input_file(dataset)) - cargs.extend([ - "-base", - execution.input_file(base_dataset) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if shift_only: - cargs.append("-shift_only") - if shift_rotate: - cargs.append("-shift_rotate") - if shift_rotate_scale: - cargs.append("-shift_rotate_scale") - if affine_general: - cargs.append("-affine_general") - if bilinear_general: - cargs.append("-bilinear_general") - if linear: - cargs.append("-linear") - if cubic: - cargs.append("-cubic") - if nn: - cargs.append("-NN") - if quintic: - cargs.append("-quintic") - if input_dataset is not None: - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if verbosity_flag: - cargs.append("-verb") - if summary_file is not None: - cargs.extend([ - "-summ", - summary_file - ]) - if max_iterations is not None: - cargs.extend([ - "-maxite", - str(max_iterations) - ]) - if delta is not None: - cargs.extend([ - "-delta", - str(delta) - ]) - if weight is not None: - cargs.extend([ - "-weight", - weight - ]) - if convergence_thresh is not None: - cargs.extend([ - "-thresh", - str(convergence_thresh) - ]) - if twopass: - cargs.append("-twopass") - if final_mode is not None: - cargs.extend([ - "-final", - final_mode - ]) - if parfix is not None: - cargs.extend([ - "-parfix", - *parfix - ]) - if oned_file is not None: - cargs.extend([ - "-1Dfile", - execution.input_file(oned_file) - ]) - if float_format: - cargs.append("-float") - if coarserot_init: - cargs.append("-coarserot") - if oned_matrix_save is not None: - cargs.extend([ - "-1Dmatrix_save", - execution.input_file(oned_matrix_save) - ]) - if sdu_order: - cargs.append("-SDU") - if sud_order: - cargs.append("-SUD") - if dsu_order: - cargs.append("-DSU") - if dus_order: - cargs.append("-DUS") - if usd_order: - cargs.append("-USD") - if uds_order: - cargs.append("-UDS") - if supper_s_matrix: - cargs.append("-Supper") - if slower_s_matrix: - cargs.append("-Slower") - if ashift: - cargs.append("-ashift") - if bshift: - cargs.append("-bshift") - ret = V3dWarpDriveOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+orig"), - output_summary=execution.output_file(summary_file) if (summary_file is not None) else None, - oned_output_file=execution.output_file(pathlib.Path(oned_file).name) if (oned_file is not None) else None, - matrix_output_file=execution.output_file(pathlib.Path(oned_matrix_save).name) if (oned_matrix_save is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dWarpDriveOutputs", - "V_3D_WARP_DRIVE_METADATA", - "v_3d_warp_drive", -] diff --git a/python/src/niwrap/afni/v_3d_wilcoxon.py b/python/src/niwrap/afni/v_3d_wilcoxon.py deleted file mode 100644 index 2e52a6af6..000000000 --- a/python/src/niwrap/afni/v_3d_wilcoxon.py +++ /dev/null @@ -1,92 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_WILCOXON_METADATA = Metadata( - id="55a623ddd594ec6685ecd7e70c06f3041abe13f4.boutiques", - name="3dWilcoxon", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dWilcoxonOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_wilcoxon(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Estimated population delta and Wilcoxon signed-rank statistics""" - - -def v_3d_wilcoxon( - dset1_x: list[InputPathType], - dset2_y: list[InputPathType], - output_prefix: str, - workmem: float | None = None, - voxel: float | None = None, - runner: Runner | None = None, -) -> V3dWilcoxonOutputs: - """ - Nonparametric Wilcoxon signed-rank test for paired comparisons of two samples. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset1_x: Data set for X observations. The user must specify 1 and only\ - 1 sub-brick with each -dset command. - dset2_y: Data set for Y observations. The user must specify 1 and only\ - 1 sub-brick with each -dset command. - output_prefix: Estimated population delta and Wilcoxon signed-rank\ - statistics are written to file. - workmem: Number of megabytes of RAM to use for statistical workspace. - voxel: Screen output for voxel # num. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dWilcoxonOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_WILCOXON_METADATA) - cargs = [] - cargs.append("3dWilcoxon") - if workmem is not None: - cargs.extend([ - "-workmem", - str(workmem) - ]) - if voxel is not None: - cargs.extend([ - "-voxel", - str(voxel) - ]) - cargs.append("-dset") - cargs.append("1") - cargs.extend([execution.input_file(f) for f in dset1_x]) - cargs.append("-dset") - cargs.append("2") - cargs.extend([execution.input_file(f) for f in dset2_y]) - cargs.append("-out") - cargs.extend([ - "-out", - output_prefix - ]) - ret = V3dWilcoxonOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dWilcoxonOutputs", - "V_3D_WILCOXON_METADATA", - "v_3d_wilcoxon", -] diff --git a/python/src/niwrap/afni/v_3d_winsor.py b/python/src/niwrap/afni/v_3d_winsor.py deleted file mode 100644 index 5854ad837..000000000 --- a/python/src/niwrap/afni/v_3d_winsor.py +++ /dev/null @@ -1,121 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_WINSOR_METADATA = Metadata( - id="9dc1eb891036fda34b014deb117eea532cef4f42.boutiques", - name="3dWinsor", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dWinsorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_winsor(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_head: OutputPathType | None - """Output dataset with Winsorizing filter applied.""" - outfile_brik: OutputPathType | None - """Output dataset with Winsorizing filter applied.""" - - -def v_3d_winsor( - dataset: InputPathType, - irad: float | None = None, - cbot: float | None = None, - ctop: float | None = None, - nrep: float | None = None, - keepzero: bool = False, - clip: float | None = None, - prefix: str | None = None, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dWinsorOutputs: - """ - Apply a 3D 'Winsorizing' filter to a short-valued dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset to apply the filter on. - irad: Include all points within 'distance' rr in the operation, where\ - distance is defined as sqrt(i*i+j*j+k*k), and (i,j,k) are voxel index\ - offsets. - cbot: Set bottom clip index to bb. - ctop: Set top clip index to tt. - nrep: Repeat filter nn times. If nn < 0, means to repeat filter until\ - less than abs(n) voxels change. - keepzero: Don't filter voxels that are zero. - clip: Set voxels at or below 'xx' to zero. - prefix: Use 'pp' as the prefix for the output dataset. - mask: Use 'mmm' as a mask dataset - voxels NOT in the mask won't be\ - filtered. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dWinsorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_WINSOR_METADATA) - cargs = [] - cargs.append("3dWinsor") - if irad is not None: - cargs.extend([ - "-irad", - str(irad) - ]) - if cbot is not None: - cargs.extend([ - "-cbot", - str(cbot) - ]) - if ctop is not None: - cargs.extend([ - "-ctop", - str(ctop) - ]) - if nrep is not None: - cargs.extend([ - "-nrep", - str(nrep) - ]) - if keepzero: - cargs.append("-keepzero") - if clip is not None: - cargs.extend([ - "-clip", - str(clip) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append(execution.input_file(dataset)) - ret = V3dWinsorOutputs( - root=execution.output_file("."), - outfile_head=execution.output_file(prefix + "+*.HEAD") if (prefix is not None) else None, - outfile_brik=execution.output_file(prefix + "+*.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dWinsorOutputs", - "V_3D_WINSOR_METADATA", - "v_3d_winsor", -] diff --git a/python/src/niwrap/afni/v_3d_xclust_sim.py b/python/src/niwrap/afni/v_3d_xclust_sim.py deleted file mode 100644 index ebf8a75f8..000000000 --- a/python/src/niwrap/afni/v_3d_xclust_sim.py +++ /dev/null @@ -1,162 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_XCLUST_SIM_METADATA = Metadata( - id="8ab2d50a137adbe81fde33f72be07849436f466b.boutiques", - name="3dXClustSim", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dXclustSimOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_xclust_sim(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_mthresh: OutputPathType | None - """Output multi-threshold files for each -ncase input""" - - -def v_3d_xclust_sim( - inset: InputPathType, - insdat: InputPathType | None = None, - nn: float | None = None, - sid: float | None = None, - hpow: list[float] | None = None, - ncase: list[str] | None = None, - pthr: list[float] | None = None, - fpr: float | None = None, - multi_fpr: bool = False, - minclust: float | None = None, - local: bool = False, - global_: bool = False, - nolocal: bool = False, - noglobal: bool = False, - splitfrac: float | None = None, - prefix: str | None = None, - verbose: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dXclustSimOutputs: - """ - ETAC processing tool to find cluster figure of merit (FOM) thresholds. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: Mask sdata file (from 3dtoXdataset or 3dttest++). - insdat: Data files in the '.sdat' format. - nn: Neighborhood connectivity (1, 2, or 3). Default is 2. - sid: Sidedness: 1 (one-sided) or 2 (two-sided). Default is 2. - hpow: H power values (can be a subset of 0, 1, 2). Default is 2. - ncase: Number of cases with labels. Default is 1 A. - pthr: List of p-value thresholds. Default is 0.0100 0.0056 0.0031\ - 0.0018 0.0010. - fpr: Set global FPR goal to an integer ff between 2 and 9. Default is\ - 5. - multi_fpr: Compute results for multiple FPR goals (2%, 3%, ... 9%). - minclust: Minimum cluster size in voxels. Default is 5. - local: Do voxel-wise (local) ETAC computations. - global_: Do volume-wise (global) ETAC computations. - nolocal: Do not perform voxel-wise ETAC computations. - noglobal: Do not perform volume-wise ETAC computations. - splitfrac: Fraction to split simulations into pieces (0.2 < F < 0.8). - prefix: Output filename prefix. - verbose: Be more verbose. - quiet: Silent mode. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dXclustSimOutputs`). - """ - if fpr is not None and not (2 <= fpr <= 9): - raise ValueError(f"'fpr' must be between 2 <= x <= 9 but was {fpr}") - if splitfrac is not None and not (0.2 <= splitfrac <= 0.8): - raise ValueError(f"'splitfrac' must be between 0.2 <= x <= 0.8 but was {splitfrac}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_XCLUST_SIM_METADATA) - cargs = [] - cargs.append("3dXClustSim") - cargs.append(execution.input_file(inset)) - if insdat is not None: - cargs.append(execution.input_file(insdat)) - if nn is not None: - cargs.extend([ - "-NN", - str(nn) - ]) - if sid is not None: - cargs.extend([ - "-sid", - str(sid) - ]) - if hpow is not None: - cargs.extend([ - "-hpow", - *map(str, hpow) - ]) - if ncase is not None: - cargs.extend([ - "-ncase", - *ncase - ]) - if pthr is not None: - cargs.extend([ - "-pthr", - *map(str, pthr) - ]) - if fpr is not None: - cargs.extend([ - "-FPR", - str(fpr) - ]) - if multi_fpr: - cargs.append("-multiFPR") - if minclust is not None: - cargs.extend([ - "-minclust", - str(minclust) - ]) - if local: - cargs.append("-local") - if global_: - cargs.append("-global") - if nolocal: - cargs.append("-nolocal") - if noglobal: - cargs.append("-noglobal") - if splitfrac is not None: - cargs.extend([ - "-splitfrac", - str(splitfrac) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose: - cargs.append("-verb") - if quiet: - cargs.append("-quiet") - ret = V3dXclustSimOutputs( - root=execution.output_file("."), - out_mthresh=execution.output_file(prefix + ".mthresh.*.nii") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dXclustSimOutputs", - "V_3D_XCLUST_SIM_METADATA", - "v_3d_xclust_sim", -] diff --git a/python/src/niwrap/afni/v_3d_xyzcat.py b/python/src/niwrap/afni/v_3d_xyzcat.py deleted file mode 100644 index 0e521eb79..000000000 --- a/python/src/niwrap/afni/v_3d_xyzcat.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_XYZCAT_METADATA = Metadata( - id="8a4860f37963febfdb2c89e484f03c649d9a4d4b.boutiques", - name="3dXYZcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dXyzcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_xyzcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brainfile: OutputPathType | None - """Output concatenated dataset.""" - output_headerfile: OutputPathType | None - """Output concatenated dataset header.""" - - -def v_3d_xyzcat( - datasets: list[InputPathType], - direction: str | None = None, - prefix: str | None = None, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dXyzcatOutputs: - """ - Catenates datasets spatially. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input datasets to concatenate. - direction: Catenate along direction 'Q' (X, Y, Z, or their synonyms I,\ - J, K). - prefix: Use 'pname' for the output dataset prefix name. - verbose: Print out some verbositiness as the program proceeds. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dXyzcatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_XYZCAT_METADATA) - cargs = [] - cargs.append("3dXYZcat") - if direction is not None: - cargs.extend([ - "-dir", - direction - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose: - cargs.append("-verb") - cargs.extend([execution.input_file(f) for f in datasets]) - ret = V3dXyzcatOutputs( - root=execution.output_file("."), - output_brainfile=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - output_headerfile=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dXyzcatOutputs", - "V_3D_XYZCAT_METADATA", - "v_3d_xyzcat", -] diff --git a/python/src/niwrap/afni/v_3d_zcat.py b/python/src/niwrap/afni/v_3d_zcat.py deleted file mode 100644 index 6478ce239..000000000 --- a/python/src/niwrap/afni/v_3d_zcat.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ZCAT_METADATA = Metadata( - id="a00d1d033ba00163e081549b0d7b74b2c667d65a.boutiques", - name="3dZcat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dZcatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_zcat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_head: OutputPathType | None - """AFNI HEAD file of the output dataset""" - out_brik: OutputPathType | None - """AFNI BRIK file of the output dataset""" - - -def v_3d_zcat( - input_files: list[InputPathType], - prefix: str | None = None, - datum: typing.Literal["byte", "short", "float"] | None = None, - fscale: bool = False, - nscale: bool = False, - verb: bool = False, - frugal: bool = False, - runner: Runner | None = None, -) -> V3dZcatOutputs: - """ - Concatenates datasets in the slice (z) direction. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets. - prefix: Use 'pname' for the output dataset prefix name.\ - [default='zcat']. - datum: Coerce the output data to be stored as the given type, which may\ - be byte, short, or float. - fscale: Force scaling of the output to the maximum integer range. This\ - only has effect if the output datum is byte or short (either forced or\ - defaulted). This option is sometimes necessary to eliminate unpleasant\ - truncation artifacts. - nscale: Don't do any scaling on output to byte or short datasets. This\ - may be especially useful when operating on mask datasets whose output\ - values are only 0's and 1's. - verb: Print out some verbosity as the program proceeds. - frugal: Be 'frugal' in the use of memory, at the cost of I/O time. Only\ - needed if the program runs out of memory. Note frugality cannot be\ - combined with NIFTI output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dZcatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ZCAT_METADATA) - cargs = [] - cargs.append("3dZcat") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if fscale: - cargs.append("-fscale") - if nscale: - cargs.append("-nscale") - if verb: - cargs.append("-verb") - if frugal: - cargs.append("-frugal") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V3dZcatOutputs( - root=execution.output_file("."), - out_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - out_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dZcatOutputs", - "V_3D_ZCAT_METADATA", - "v_3d_zcat", -] diff --git a/python/src/niwrap/afni/v_3d_zcutup.py b/python/src/niwrap/afni/v_3d_zcutup.py deleted file mode 100644 index 7f378c802..000000000 --- a/python/src/niwrap/afni/v_3d_zcutup.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ZCUTUP_METADATA = Metadata( - id="8c920bae16b4f66fede4e699038867e56e5e2b1d.boutiques", - name="3dZcutup", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dZcutupOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_zcutup(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_head: OutputPathType | None - """The output dataset HEAD file""" - output_brik: OutputPathType | None - """The output dataset BRIK file""" - - -def v_3d_zcutup( - keep_slices: str, - dataset: InputPathType, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dZcutupOutputs: - """ - Cut slices off a dataset in its z-direction and write a new dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - keep_slices: Keep slices numbered 'b' through 't', inclusive. This is a\ - mandatory option. Slice numbers start at 0. - dataset: The input dataset (e.g., epi07+orig). You can use a sub-brick\ - selector on the input dataset. - prefix: Write result into dataset with the given prefix [default =\ - 'zcutup']. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dZcutupOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ZCUTUP_METADATA) - cargs = [] - cargs.append("3dZcutup") - cargs.append("-keep") - cargs.extend([ - "-keep", - keep_slices - ]) - cargs.append("-prefix") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append(execution.input_file(dataset)) - ret = V3dZcutupOutputs( - root=execution.output_file("."), - output_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - output_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dZcutupOutputs", - "V_3D_ZCUTUP_METADATA", - "v_3d_zcutup", -] diff --git a/python/src/niwrap/afni/v_3d_zeropad.py b/python/src/niwrap/afni/v_3d_zeropad.py deleted file mode 100644 index 656789d4c..000000000 --- a/python/src/niwrap/afni/v_3d_zeropad.py +++ /dev/null @@ -1,165 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ZEROPAD_METADATA = Metadata( - id="69b80943bdd6b997541b13be76f096b8bce260d4.boutiques", - name="3dZeropad", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dZeropadOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_zeropad(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset_brik: OutputPathType | None - """Output dataset (BRIK format)""" - output_dataset_head: OutputPathType | None - """Output dataset (HEAD format)""" - - -def v_3d_zeropad( - dataset: InputPathType, - i: float | None = None, - s: float | None = None, - a: float | None = None, - p: float | None = None, - l: float | None = None, - r: float | None = None, - z: float | None = None, - rl: float | None = None, - ap: float | None = None, - is_: float | None = None, - pad2even: bool = False, - mm_flag: bool = False, - master_dataset: InputPathType | None = None, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dZeropadOutputs: - """ - Adds planes of zeros to a dataset (i.e., pads it out). Negative 'add' count - means to cut a dataset down in size. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - i: Adds 'n' planes of zero at the Inferior edge. - s: Adds 'n' planes of zero at the Superior edge. - a: Adds 'n' planes of zero at the Anterior edge. - p: Adds 'n' planes of zero at the Posterior edge. - l: Adds 'n' planes of zero at the Left edge. - r: Adds 'n' planes of zero at the Right edge. - z: Adds 'n' planes of zeros on EACH of the dataset z-axis\ - (slice-direction) faces. - rl: Add/cut planes symmetrically to make the resulting volume have 'a'\ - slices in the Right/Left direction. - ap: Add/cut planes symmetrically to make the resulting volume have 'b'\ - slices in the Anterior/Posterior direction. - is_: Add/cut planes symmetrically to make the resulting volume have 'c'\ - slices in the Inferior/Superior direction. - pad2even: Add 0 or 1 plane in each of the R/A/S directions, giving each\ - axis an even number of slices. - mm_flag: Pad counts 'n' are in mm instead of slices. - master_dataset: Match the volume described in dataset 'mset'. 'mset'\ - must have the same orientation and grid spacing as dataset to be\ - padded. - prefix: Write result into dataset with prefix 'ppp'. Default is\ - 'zeropad'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dZeropadOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ZEROPAD_METADATA) - cargs = [] - cargs.append("3dZeropad") - cargs.append(execution.input_file(dataset)) - if i is not None: - cargs.extend([ - "-I", - str(i) - ]) - if s is not None: - cargs.extend([ - "-S", - str(s) - ]) - if a is not None: - cargs.extend([ - "-A", - str(a) - ]) - if p is not None: - cargs.extend([ - "-P", - str(p) - ]) - if l is not None: - cargs.extend([ - "-L", - str(l) - ]) - if r is not None: - cargs.extend([ - "-R", - str(r) - ]) - if z is not None: - cargs.extend([ - "-z", - str(z) - ]) - if rl is not None: - cargs.extend([ - "-RL", - str(rl) - ]) - if ap is not None: - cargs.extend([ - "-AP", - str(ap) - ]) - if is_ is not None: - cargs.extend([ - "-IS", - str(is_) - ]) - if pad2even: - cargs.append("-pad2evens") - if mm_flag: - cargs.append("-mm") - if master_dataset is not None: - cargs.extend([ - "-master", - execution.input_file(master_dataset) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = V3dZeropadOutputs( - root=execution.output_file("."), - output_dataset_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - output_dataset_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dZeropadOutputs", - "V_3D_ZEROPAD_METADATA", - "v_3d_zeropad", -] diff --git a/python/src/niwrap/afni/v_3d_zipper_zapper.py b/python/src/niwrap/afni/v_3d_zipper_zapper.py deleted file mode 100644 index 394347556..000000000 --- a/python/src/niwrap/afni/v_3d_zipper_zapper.py +++ /dev/null @@ -1,172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ZIPPER_ZAPPER_METADATA = Metadata( - id="2ba2cdb11947ea00198430901e3d2367101ee603.boutiques", - name="3dZipperZapper", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dZipperZapperOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_zipper_zapper(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - bad_slice_mask: OutputPathType - """Mask of potentially bad slices across the input dataset.""" - bad_volumes_list: OutputPathType - """1D file containing a list of the bad volumes.""" - per_volume_params: OutputPathType - """1D file of the per-volume parameters used to detect badness.""" - calculated_slices: OutputPathType - """1D file of the slices within which calculations were made.""" - good_volumes_selector: OutputPathType - """Text file with the selector string of *good* volumes.""" - - -def v_3d_zipper_zapper( - input_file: InputPathType, - output_prefix: str, - mask_file: InputPathType | None = None, - min_slice_nvox: float | None = None, - min_streak_len: float | None = None, - do_out_slice_param: bool = False, - no_out_bad_mask: bool = False, - no_out_text_vals: bool = False, - dont_use_streak: bool = False, - dont_use_drop: bool = False, - dont_use_corr: bool = False, - min_streak_val: float | None = None, - min_drop_frac: float | None = None, - min_drop_diff: float | None = None, - min_corr_len: float | None = None, - min_corr_corr: float | None = None, - runner: Runner | None = None, -) -> V3dZipperZapperOutputs: - """ - A basic program to highlight problematic volumes in data sets, especially - EPI/DWI data sets with interleaved acquisition. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input 3D+time file of DWIs or EPIs. - output_prefix: Prefix for output file name. - mask_file: Optional input of a single volume mask file, which gets\ - applied to each volume in the input file. - min_slice_nvox: Set the minimum number of voxels to be in the mask for\ - a given slice to be included in the calculations. - min_streak_len: Minimum number of slices in a row to look for\ - fluctuations within. - do_out_slice_param: Output the map of slice parameters. - no_out_bad_mask: Do not output the mask of 'bad' slices. - no_out_text_vals: Do not output the 1D files of the slice parameter\ - values. - dont_use_streak: Turn off the 'streak' criterion for identifying bad\ - slices. - dont_use_drop: Turn off the 'drop' criterion for identifying bad\ - slices. - dont_use_corr: Turn off the 'corr' criterion for identifying bad\ - slices. - min_streak_val: Minimum magnitude of voxelwise relative differences to\ - perhaps be problematic. - min_drop_frac: Minimum fraction for judging if the change in 'slice\ - parameter' differences between neighboring slices might be a sign of\ - badness. - min_drop_diff: Minimum 'slice parameter' value within a single slice\ - that might be considered a bad sign. - min_corr_len: Minimum number of slices in a row to look for consecutive\ - anticorrelations in brightness differences. - min_corr_corr: Threshold for the magnitude of anticorrelations to be\ - considered potentially bad. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dZipperZapperOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ZIPPER_ZAPPER_METADATA) - cargs = [] - cargs.append("3dZipperZapper") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-prefix") - cargs.append(output_prefix) - if mask_file is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_file) - ]) - if min_slice_nvox is not None: - cargs.extend([ - "-min_slice_nvox", - str(min_slice_nvox) - ]) - if min_streak_len is not None: - cargs.extend([ - "-min_streak_len", - str(min_streak_len) - ]) - if do_out_slice_param: - cargs.append("-do_out_slice_param") - if no_out_bad_mask: - cargs.append("-no_out_bad_mask") - if no_out_text_vals: - cargs.append("-no_out_text_vals") - if dont_use_streak: - cargs.append("-dont_use_streak") - if dont_use_drop: - cargs.append("-dont_use_drop") - if dont_use_corr: - cargs.append("-dont_use_corr") - if min_streak_val is not None: - cargs.extend([ - "-min_streak_val", - str(min_streak_val) - ]) - if min_drop_frac is not None: - cargs.extend([ - "-min_drop_frac", - str(min_drop_frac) - ]) - if min_drop_diff is not None: - cargs.extend([ - "-min_drop_diff", - str(min_drop_diff) - ]) - if min_corr_len is not None: - cargs.extend([ - "-min_corr_len", - str(min_corr_len) - ]) - if min_corr_corr is not None: - cargs.extend([ - "-min_corr_corr", - str(min_corr_corr) - ]) - ret = V3dZipperZapperOutputs( - root=execution.output_file("."), - bad_slice_mask=execution.output_file(output_prefix + "_badmask.nii.gz"), - bad_volumes_list=execution.output_file(output_prefix + "_badvols.1D"), - per_volume_params=execution.output_file(output_prefix + "_param.1D"), - calculated_slices=execution.output_file(output_prefix + "_sli.1D"), - good_volumes_selector=execution.output_file(output_prefix + "_goodvols.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dZipperZapperOutputs", - "V_3D_ZIPPER_ZAPPER_METADATA", - "v_3d_zipper_zapper", -] diff --git a/python/src/niwrap/afni/v_3d_zregrid.py b/python/src/niwrap/afni/v_3d_zregrid.py deleted file mode 100644 index db7eb5e3d..000000000 --- a/python/src/niwrap/afni/v_3d_zregrid.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3D_ZREGRID_METADATA = Metadata( - id="b6a8ac20dbb69c9f1827ab515948687aad33cc26.boutiques", - name="3dZregrid", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dZregridOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3d_zregrid(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_head: OutputPathType | None - """Output dataset with new grid""" - outfile_brik: OutputPathType | None - """Output dataset with new grid""" - - -def v_3d_zregrid( - infile: InputPathType, - z_thickness: float | None = None, - slice_count: float | None = None, - z_size: float | None = None, - prefix: str | None = None, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dZregridOutputs: - """ - Alters the input dataset's slice thickness and/or number. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input dataset. - z_thickness: Set slice thickness to D mm. - slice_count: Set slice count to N. - z_size: Set thickness of dataset (center-to-center of first and last\ - slices) to Z mm. - prefix: Write result to dataset with prefix P. - verbose: Write progress reports to stderr. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dZregridOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3D_ZREGRID_METADATA) - cargs = [] - cargs.append("3dZregrid") - if z_thickness is not None: - cargs.extend([ - "-dz", - str(z_thickness) - ]) - if slice_count is not None: - cargs.extend([ - "-nz", - str(slice_count) - ]) - if z_size is not None: - cargs.extend([ - "-zsize", - str(z_size) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append(execution.input_file(infile)) - if verbose: - cargs.append("-verb") - ret = V3dZregridOutputs( - root=execution.output_file("."), - outfile_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - outfile_brik=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dZregridOutputs", - "V_3D_ZREGRID_METADATA", - "v_3d_zregrid", -] diff --git a/python/src/niwrap/afni/v_3danisosmooth.py b/python/src/niwrap/afni/v_3danisosmooth.py deleted file mode 100644 index a80eaa510..000000000 --- a/python/src/niwrap/afni/v_3danisosmooth.py +++ /dev/null @@ -1,204 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DANISOSMOOTH_METADATA = Metadata( - id="0f940845485d0f2e6aa4a1bbafdccc58018a21a2.boutiques", - name="3danisosmooth", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3danisosmoothOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3danisosmooth(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Output dataset after anisotropic smoothing""" - gradient_data: OutputPathType - """Gradient dataset saved at each iteration""" - eigens_data: OutputPathType - """Eigens dataset saved at each iteration""" - phi_data: OutputPathType - """Phi dataset saved at each iteration""" - dtensor_data: OutputPathType - """Dtensor dataset saved at each iteration""" - ematrix_data: OutputPathType - """Ematrix dataset saved at the first sub-brick iteration""" - flux_data: OutputPathType - """Flux dataset saved at the first sub-brick iteration""" - gmatrix_data: OutputPathType - """Gmatrix dataset saved at the first sub-brick iteration""" - diff_measures_data: OutputPathType - """Dataset containing FA, MD, Cl, Cp, and Cs values saved at each - iteration""" - - -def v_3danisosmooth( - input_dataset: InputPathType, - prefix: str | None = None, - iterations: float | None = None, - v_2d_flag: bool = False, - v_3d_flag: bool = False, - mask_dataset: InputPathType | None = None, - automask_flag: bool = False, - viewer_flag: bool = False, - nosmooth_flag: bool = False, - sigma1: float | None = None, - sigma2: float | None = None, - deltat: float | None = None, - savetempdata_flag: bool = False, - save_temp_with_diff_measures_flag: bool = False, - phiding_flag: bool = False, - phiexp_flag: bool = False, - noneg_flag: bool = False, - setneg_value: float | None = None, - edgefraction: float | None = None, - datum_type: str | None = None, - matchorig_flag: bool = False, - help_flag: bool = False, - runner: Runner | None = None, -) -> V3danisosmoothOutputs: - """ - Smooths a dataset using an anisotropic smoothing technique. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset to be smoothed. - prefix: Output dataset prefix name. - iterations: Number of iterations (default=10). - v_2d_flag: Smooth a slice at a time (default). - v_3d_flag: Smooth through slices. - mask_dataset: Use specified dataset as mask to include/exclude voxels. - automask_flag: Automatically compute mask for dataset. - viewer_flag: Show central axial slice image every iteration. - nosmooth_flag: Do not do intermediate smoothing of gradients. - sigma1: Gaussian smoothing sigma before gradient computation\ - (default=0.5). - sigma2: Gaussian smoothing sigma after gradient computation\ - (default=1.0). - deltat: Pseudo-time step (default=0.25). - savetempdata_flag: Save temporary datasets each iteration. - save_temp_with_diff_measures_flag: Save temporary datasets with\ - different measures in a dataset. - phiding_flag: Use Ding method for computing phi (default). - phiexp_flag: Use exponential method for computing phi. - noneg_flag: Set negative voxels to 0. - setneg_value: Set negative voxels to specified value. - edgefraction: Adjust the fraction of the anisotropic component added (0\ - to 1, default=0.5). - datum_type: Specify type for output data (byte, short, float)\ - [default=float]. - matchorig_flag: Match datum type and clip min/max to input data. - help_flag: Print help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3danisosmoothOutputs`). - """ - if edgefraction is not None and not (0 <= edgefraction <= 1): - raise ValueError(f"'edgefraction' must be between 0 <= x <= 1 but was {edgefraction}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DANISOSMOOTH_METADATA) - cargs = [] - cargs.append("3danisosmooth") - cargs.append(execution.input_file(input_dataset)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if iterations is not None: - cargs.extend([ - "-iters", - str(iterations) - ]) - if v_2d_flag: - cargs.append("-2D") - if v_3d_flag: - cargs.append("-3D") - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if automask_flag: - cargs.append("-automask") - if viewer_flag: - cargs.append("-viewer") - if nosmooth_flag: - cargs.append("-nosmooth") - if sigma1 is not None: - cargs.extend([ - "-sigma1", - str(sigma1) - ]) - if sigma2 is not None: - cargs.extend([ - "-sigma2", - str(sigma2) - ]) - if deltat is not None: - cargs.extend([ - "-deltat", - str(deltat) - ]) - if savetempdata_flag: - cargs.append("-savetempdata") - if save_temp_with_diff_measures_flag: - cargs.append("-save_temp_with_diff_measures") - if phiding_flag: - cargs.append("-phiding") - if phiexp_flag: - cargs.append("-phiexp") - if noneg_flag: - cargs.append("-noneg") - if setneg_value is not None: - cargs.extend([ - "-setneg", - str(setneg_value) - ]) - if edgefraction is not None: - cargs.extend([ - "-edgefraction", - str(edgefraction) - ]) - if datum_type is not None: - cargs.extend([ - "-datum", - datum_type - ]) - if matchorig_flag: - cargs.append("-matchorig") - if help_flag: - cargs.append("-help") - ret = V3danisosmoothOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+smooth") if (prefix is not None) else None, - gradient_data=execution.output_file("Gradient.ITER"), - eigens_data=execution.output_file("Eigens.ITER"), - phi_data=execution.output_file("phi.ITER"), - dtensor_data=execution.output_file("Dtensor.ITER"), - ematrix_data=execution.output_file("Ematrix.ITER"), - flux_data=execution.output_file("Flux.ITER"), - gmatrix_data=execution.output_file("Gmatrix.ITER"), - diff_measures_data=execution.output_file("Diff_measures.ITER"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3danisosmoothOutputs", - "V_3DANISOSMOOTH_METADATA", - "v_3danisosmooth", -] diff --git a/python/src/niwrap/afni/v_3daxialize.py b/python/src/niwrap/afni/v_3daxialize.py deleted file mode 100644 index 90084548e..000000000 --- a/python/src/niwrap/afni/v_3daxialize.py +++ /dev/null @@ -1,98 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DAXIALIZE_METADATA = Metadata( - id="bcc8e30177064f95c8a4e5b95029e8dd46cb1692.boutiques", - name="3daxialize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3daxializeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3daxialize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType | None - """Output dataset with axial slices orientation""" - - -def v_3daxialize( - infile: InputPathType, - prefix: str | None = None, - verb: bool = False, - sagittal: bool = False, - coronal: bool = False, - axial: bool = False, - orient_code: str | None = None, - frugal: bool = False, - runner: Runner | None = None, -) -> V3daxializeOutputs: - """ - Read and write dataset as new dataset with data brick oriented as axial slices. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Dataset to be axially oriented. - prefix: Use specified prefix for the new dataset. Default is\ - 'axialize'. - verb: Print out a progress report. - sagittal: Write dataset in sagittal slice order. - coronal: Write dataset in coronal slice order. - axial: Write dataset in axial slice order, the default orientation. - orient_code: Orientation code for output. 3 letters: one from {R,L},\ - {A,P}, {I,S}. - frugal: Write data as it is rotated, saving memory. Not available with\ - NIFTI datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3daxializeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DAXIALIZE_METADATA) - cargs = [] - cargs.append("3daxialize") - cargs.append(execution.input_file(infile)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verb: - cargs.append("-verb") - if sagittal: - cargs.append("-sagittal") - if coronal: - cargs.append("-coronal") - if axial: - cargs.append("-axial") - if orient_code is not None: - cargs.extend([ - "-orient", - orient_code - ]) - if frugal: - cargs.append("-frugal") - ret = V3daxializeOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + "+orig") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3daxializeOutputs", - "V_3DAXIALIZE_METADATA", - "v_3daxialize", -] diff --git a/python/src/niwrap/afni/v_3dbucket.py b/python/src/niwrap/afni/v_3dbucket.py deleted file mode 100644 index 5e250ce63..000000000 --- a/python/src/niwrap/afni/v_3dbucket.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DBUCKET_METADATA = Metadata( - id="a07bb3d6d6114eb899f05be41e593f262e6cd274.boutiques", - name="3dbucket", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dbucketOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dbucket(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3dbucket( - input_files: list[str], - prefix: str | None = None, - session: str | None = None, - glueto: str | None = None, - aglueto: str | None = None, - dry: bool = False, - verbose: bool = False, - fbuc: bool = False, - abuc: bool = False, - runner: Runner | None = None, -) -> V3dbucketOutputs: - """ - Concatenate sub-bricks from input datasets into one big bucket dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets with optional sub-brick selection. - prefix: Use 'pname' for the output dataset prefix name. - session: Use 'dir' for the output dataset session directory.\ - [default='./'=current working directory]. - glueto: Append bricks to the end of the 'fname' dataset. - aglueto: If fname dataset does not exist, create it (like -prefix).\ - Otherwise append to fname (like -glueto). - dry: Execute a 'dry run'; only print out what would be done. - verbose: Print out some verbose output as the program proceeds. - fbuc: Create a functional bucket. - abuc: Create an anatomical bucket. If neither of these options is\ - given, the output type is determined from the first input type. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dbucketOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DBUCKET_METADATA) - cargs = [] - cargs.append("3dbucket") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if session is not None: - cargs.extend([ - "-session", - session - ]) - if glueto is not None: - cargs.extend([ - "-glueto", - glueto - ]) - if aglueto is not None: - cargs.extend([ - "-aglueto", - aglueto - ]) - if dry: - cargs.append("-dry") - if verbose: - cargs.append("-verb") - if fbuc: - cargs.append("-fbuc") - if abuc: - cargs.append("-abuc") - cargs.extend(input_files) - ret = V3dbucketOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dbucketOutputs", - "V_3DBUCKET_METADATA", - "v_3dbucket", -] diff --git a/python/src/niwrap/afni/v_3dcalc.py b/python/src/niwrap/afni/v_3dcalc.py deleted file mode 100644 index eec41e7a4..000000000 --- a/python/src/niwrap/afni/v_3dcalc.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DCALC_METADATA = Metadata( - id="66f28a66a111cc3612e13fb86d7e368e7be0a5a2.boutiques", - name="3dcalc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dcalcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dcalc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - - -def v_3dcalc( - expr: str, - in_file_a: InputPathType, - in_file_b: InputPathType | None = None, - in_file_c: InputPathType | None = None, - other: InputPathType | None = None, - overwrite: bool = False, - single_idx: int | None = None, - start_idx: int | None = None, - stop_idx: int | None = None, - runner: Runner | None = None, -) -> V3dcalcOutputs: - """ - AFNI's calculator program. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - expr: Expr. - in_file_a: Input file to 3dcalc. - in_file_b: Operand file to 3dcalc. - in_file_c: Operand file to 3dcalc. - other: Other options. - overwrite: Overwrite output. - single_idx: Volume index for in_file_a. - start_idx: Start index for in_file_a. - stop_idx: Stop index for in_file_a. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dcalcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DCALC_METADATA) - cargs = [] - cargs.append("3dcalc") - cargs.append(expr) - cargs.extend([ - "-a", - execution.input_file(in_file_a) - ]) - if in_file_b is not None: - cargs.extend([ - "-b", - execution.input_file(in_file_b) - ]) - if in_file_c is not None: - cargs.extend([ - "-c", - execution.input_file(in_file_c) - ]) - if other is not None: - cargs.append(execution.input_file(other)) - if overwrite: - cargs.append("-overwrite") - if single_idx is not None: - cargs.append(str(single_idx)) - if start_idx is not None: - cargs.append(str(start_idx)) - if stop_idx is not None: - cargs.append(str(stop_idx)) - ret = V3dcalcOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file_a).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dcalcOutputs", - "V_3DCALC_METADATA", - "v_3dcalc", -] diff --git a/python/src/niwrap/afni/v_3dclust.py b/python/src/niwrap/afni/v_3dclust.py deleted file mode 100644 index 1f5f8fb4f..000000000 --- a/python/src/niwrap/afni/v_3dclust.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DCLUST_METADATA = Metadata( - id="3ce8cefee5cef3ba7b1a972b0fcad6cd5a2fd94f.boutiques", - name="3dclust", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dclustOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dclust(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - prefixed_output: OutputPathType | None - """New dataset with clusters set to zero based on prefix.""" - ordered_mask_output: OutputPathType | None - """Ordered mask dataset based on savemask prefix.""" - - -def v_3dclust( - datasets: list[InputPathType], - rmm: float | None = None, - vmul: float | None = None, - nn1: bool = False, - nn2: bool = False, - nn3: bool = False, - noabs: bool = False, - summarize: bool = False, - nosum: bool = False, - verb: bool = False, - oned_format: bool = False, - no_oned_format: bool = False, - quiet: bool = False, - mni: bool = False, - isovalue: bool = False, - isomerge: bool = False, - inmask: bool = False, - prefix: str | None = None, - savemask: str | None = None, - binary: bool = False, - runner: Runner | None = None, -) -> V3dclustOutputs: - """ - Performs simple-minded cluster detection in 3D datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input dataset(s). More than one allowed, but only the first\ - sub-brick of the dataset. - rmm: Cluster connection radius in millimeters. - vmul: Minimum cluster volume in micro-liters or minimum number of\ - voxels if negative. - nn1: 1st nearest-neighbor clustering (faces touching). - nn2: 2nd nearest-neighbor clustering (edges touching). - nn3: 3rd nearest-neighbor clustering (corners touching). - noabs: Use the signed voxel intensities for calculations. - summarize: Write out only the total nonzero voxel count and volume for\ - each dataset. - nosum: Suppress printout of the totals. - verb: Print out a progress report to stderr as computations proceed. - oned_format: Write output in 1D format (default). - no_oned_format: Do not write output in 1D format. - quiet: Suppress all non-essential output. - mni: Transform output xyz-coordinates from TLRC to MNI space if the\ - input dataset has the +tlrc view. - isovalue: Clusters will be formed only from contiguous voxels that also\ - have the same value. - isomerge: Clusters will be formed from each distinct value in the\ - dataset; spatial contiguity will not be used. - inmask: Use an internal mask from the dataset to eliminate voxels\ - before clustering. - prefix: Write a new dataset that is a copy of the input, but with all\ - voxels not in a cluster set to zero; provide a prefix for the new\ - dataset. - savemask: Write a new dataset that is an ordered mask where the largest\ - cluster is labeled '1', the next largest '2', and so forth. - binary: Turn the output of '-savemask' into a binary (0 or 1) mask. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dclustOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DCLUST_METADATA) - cargs = [] - cargs.append("3dclust") - if rmm is not None: - cargs.append(str(rmm)) - if vmul is not None: - cargs.append(str(vmul)) - cargs.extend([execution.input_file(f) for f in datasets]) - if nn1: - cargs.append("-NN1") - if nn2: - cargs.append("-NN2") - if nn3: - cargs.append("-NN3") - if noabs: - cargs.append("-noabs") - if summarize: - cargs.append("-summarize") - if nosum: - cargs.append("-nosum") - if verb: - cargs.append("-verb") - if oned_format: - cargs.append("-1Dformat") - if no_oned_format: - cargs.append("-no_1Dformat") - if quiet: - cargs.append("-quiet") - if mni: - cargs.append("-mni") - if isovalue: - cargs.append("-isovalue") - if isomerge: - cargs.append("-isomerge") - if inmask: - cargs.append("-inmask") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if savemask is not None: - cargs.extend([ - "-savemask", - savemask - ]) - if binary: - cargs.append("-binary") - ret = V3dclustOutputs( - root=execution.output_file("."), - prefixed_output=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ordered_mask_output=execution.output_file(savemask + ".nii.gz") if (savemask is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dclustOutputs", - "V_3DCLUST_METADATA", - "v_3dclust", -] diff --git a/python/src/niwrap/afni/v_3dcopy.py b/python/src/niwrap/afni/v_3dcopy.py deleted file mode 100644 index 43920970c..000000000 --- a/python/src/niwrap/afni/v_3dcopy.py +++ /dev/null @@ -1,65 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DCOPY_METADATA = Metadata( - id="4b8187d004c6f4ba95518e709ad1f9b3eb4ed322.boutiques", - name="3dcopy", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dcopyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dcopy(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3dcopy( - verbose: bool = False, - denote: bool = False, - runner: Runner | None = None, -) -> V3dcopyOutputs: - """ - 3dcopy copies datasets with or without altering prefixes and converting formats. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - verbose: Print progress reports. - denote: Remove any Notes from the file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dcopyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DCOPY_METADATA) - cargs = [] - cargs.append("3dcopy") - if verbose: - cargs.append("-verb") - if denote: - cargs.append("-denote") - cargs.append("{OLD_PREFIX}+{VIEW}") - cargs.append("{NEW_PREFIX}") - ret = V3dcopyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dcopyOutputs", - "V_3DCOPY_METADATA", - "v_3dcopy", -] diff --git a/python/src/niwrap/afni/v_3ddelay.py b/python/src/niwrap/afni/v_3ddelay.py deleted file mode 100644 index 07839ee93..000000000 --- a/python/src/niwrap/afni/v_3ddelay.py +++ /dev/null @@ -1,198 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DDELAY_METADATA = Metadata( - id="1b3372c0560d1ae26e638ccf8c8abca50668017f.boutiques", - name="3ddelay", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3ddelayOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3ddelay(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_brick: OutputPathType | None - """Primary output results Brick for Delay""" - output_asc: OutputPathType | None - """Output ASCII file for results""" - output_asc_log: OutputPathType | None - """Log file containing parameter settings and warnings""" - output_asc_ts: OutputPathType | None - """Output ASCII file with time series""" - - -def v_3ddelay( - input_file: InputPathType, - reference_file: InputPathType, - sampling_freq: float, - stim_period: float, - prefix: str | None = None, - polort: float | None = None, - nodtrnd: bool = False, - units_seconds: bool = False, - units_degrees: bool = False, - units_radians: bool = False, - phzwrp: bool = False, - nophzwrp: bool = False, - phzreverse: bool = False, - phzscale: float | None = None, - bias: bool = False, - nobias: bool = False, - dsamp: bool = False, - nodsamp: bool = False, - mask: InputPathType | None = None, - nfirst: float | None = None, - nlast: float | None = None, - co: float | None = None, - asc: str | None = None, - ascts: str | None = None, - runner: Runner | None = None, -) -> V3ddelayOutputs: - """ - Estimates the time delay between each voxel time series in a 3D+time dataset and - a reference time series. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Filename of the input 3D+time dataset. - reference_file: Input ideal time series file name. - sampling_freq: Sampling frequency in Hz. of data time series (1/TR). - stim_period: Stimulus period in seconds. Set to 0 if stimulus is not\ - periodic. - prefix: The prefix for the results Brick. - polort: Detrend input time series with polynomial of specified order.\ - Default is -1 for auto selection. - nodtrnd: Remove only the mean (equivalent to polort 0). - units_seconds: Units for delay estimates in seconds. - units_degrees: Units for delay estimates in degrees. Requires Tstim > 0. - units_radians: Units for delay estimates in radians. Requires Tstim > 0. - phzwrp: Wrap delay (or phase) values. - nophzwrp: Do not wrap phase (default). - phzreverse: Reverse phase such that phase -> (T-phase). - phzscale: Scale phase: phase -> phase*SC (default no scaling). - bias: Do not correct for the bias in the estimates. - nobias: Correct for the bias in the estimates (default). - dsamp: Correct for slice timing differences (default). - nodsamp: Do not correct for slice timing differences. - mask: Filename of mask dataset. Only voxels with non-zero values in the\ - mask will be considered. - nfirst: Number of first dataset image to use in the delay estimate. - nlast: Number of last dataset image to use in the delay estimate. - co: Cross Correlation Coefficient threshold value to limit ascii output. - asc: Write the results to an ascii file for voxels with cross\ - correlation coefficients larger than CCT. - ascts: Write the results and time series to an ascii file for voxels\ - with cross correlation coefficients larger than CCT. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3ddelayOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DDELAY_METADATA) - cargs = [] - cargs.append("3ddelay") - cargs.append(execution.input_file(input_file)) - cargs.append(execution.input_file(reference_file)) - cargs.extend([ - "-fs", - str(sampling_freq) - ]) - cargs.extend([ - "-T", - str(stim_period) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if nodtrnd: - cargs.append("-nodtrnd") - if units_seconds: - cargs.append("-uS") - if units_degrees: - cargs.append("-uD") - if units_radians: - cargs.append("-uR") - if phzwrp: - cargs.append("-phzwrp") - if nophzwrp: - cargs.append("-nophzwrp") - if phzreverse: - cargs.append("-phzreverse") - if phzscale is not None: - cargs.extend([ - "-phzscale", - str(phzscale) - ]) - if bias: - cargs.append("-bias") - if nobias: - cargs.append("-nobias") - if dsamp: - cargs.append("-dsamp") - if nodsamp: - cargs.append("-nodsamp") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if nfirst is not None: - cargs.extend([ - "-nfirst", - str(nfirst) - ]) - if nlast is not None: - cargs.extend([ - "-nlast", - str(nlast) - ]) - if co is not None: - cargs.extend([ - "-co", - str(co) - ]) - if asc is not None: - cargs.extend([ - "-asc", - asc - ]) - if ascts is not None: - cargs.extend([ - "-ascts", - ascts - ]) - ret = V3ddelayOutputs( - root=execution.output_file("."), - output_brick=execution.output_file(prefix + ".DEL+orig.BRIK") if (prefix is not None) else None, - output_asc=execution.output_file(prefix + ".ASC") if (prefix is not None) else None, - output_asc_log=execution.output_file(prefix + ".ASC.log") if (prefix is not None) else None, - output_asc_ts=execution.output_file(prefix + ".ASC.ts") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3ddelayOutputs", - "V_3DDELAY_METADATA", - "v_3ddelay", -] diff --git a/python/src/niwrap/afni/v_3ddot.py b/python/src/niwrap/afni/v_3ddot.py deleted file mode 100644 index e80dfdda3..000000000 --- a/python/src/niwrap/afni/v_3ddot.py +++ /dev/null @@ -1,129 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DDOT_METADATA = Metadata( - id="4d259267b87f75dc1b81e232092499e6d326d8fd.boutiques", - name="3ddot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3ddotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3ddot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - result: OutputPathType - """Resulting coefficient or statistical values printed to stdout""" - - -def v_3ddot( - input_datasets: list[InputPathType], - mask: InputPathType | None = None, - mrange: list[float] | None = None, - demean: bool = False, - docor: bool = False, - dodot: bool = False, - docoef: bool = False, - dosums: bool = False, - doeta2: bool = False, - dodice: bool = False, - show_labels: bool = False, - upper: bool = False, - full: bool = False, - v_1_d: bool = False, - niml: bool = False, - runner: Runner | None = None, -) -> V3ddotOutputs: - """ - Computes correlation coefficients between sub-brick pairs. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_datasets: List of input datasets to be used (e.g. img1+orig,\ - img2+orig). - mask: Dataset to be used as a mask; only voxels with nonzero values\ - will be averaged. - mrange: Restrict mask values to those between a and b (inclusive) for\ - masking purposes. - demean: Remove the mean from each volume prior to computing the\ - correlation. - docor: Return the correlation coefficient (default). - dodot: Return the dot product (unscaled). - docoef: Return the least square fit coefficients {a,b}. - dosums: Return xbar, ybar, variance, covariance, and correlation\ - coefficient. - doeta2: Return eta-squared (Cohen, NeuroImage 2008). - dodice: Return the Dice coefficient (the Sorensen-Dice index). - show_labels: Print sub-brick labels to help identify what is being\ - correlated. - upper: Compute upper triangular matrix. - full: Compute the whole matrix. - v_1_d: Add comment headings for the 1D format. - niml: Write output in NIML 1D format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3ddotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DDOT_METADATA) - cargs = [] - cargs.append("3ddot") - cargs.extend([execution.input_file(f) for f in input_datasets]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mrange is not None: - cargs.extend([ - "-mrange", - *map(str, mrange) - ]) - if demean: - cargs.append("-demean") - if docor: - cargs.append("-docor") - if dodot: - cargs.append("-dodot") - if docoef: - cargs.append("-docoef") - if dosums: - cargs.append("-dosums") - if doeta2: - cargs.append("-doeta2") - if dodice: - cargs.append("-dodice") - if show_labels: - cargs.append("-show_labels") - if upper: - cargs.append("-upper") - if full: - cargs.append("-full") - if v_1_d: - cargs.append("-1D") - if niml: - cargs.append("-NIML") - ret = V3ddotOutputs( - root=execution.output_file("."), - result=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3ddotOutputs", - "V_3DDOT_METADATA", - "v_3ddot", -] diff --git a/python/src/niwrap/afni/v_3ddot_beta.py b/python/src/niwrap/afni/v_3ddot_beta.py deleted file mode 100644 index 1fd2a2f49..000000000 --- a/python/src/niwrap/afni/v_3ddot_beta.py +++ /dev/null @@ -1,81 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DDOT_BETA_METADATA = Metadata( - id="150f193e49f2c831ea62fc4bf529ec24ba411853.boutiques", - name="3ddot_beta", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3ddotBetaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3ddot_beta(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output text file containing the correlation-like matrix""" - - -def v_3ddot_beta( - input_file: InputPathType, - prefix: str, - doeta2: bool = False, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3ddotBetaOutputs: - """ - Beta version of updating 3ddot, currently only performing eta2 tests and - outputting a full matrix to a text file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input file with N bricks. - prefix: Output prefix for the result file. - doeta2: Required flag for performing eta2 tests. - mask: Optional mask file within which to take values. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3ddotBetaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DDOT_BETA_METADATA) - cargs = [] - cargs.append("3ddot_beta") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if doeta2: - cargs.append("-doeta2") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - ret = V3ddotBetaOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + "_eta2.dat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3ddotBetaOutputs", - "V_3DDOT_BETA_METADATA", - "v_3ddot_beta", -] diff --git a/python/src/niwrap/afni/v_3dedge3.py b/python/src/niwrap/afni/v_3dedge3.py deleted file mode 100644 index 3ed4821ce..000000000 --- a/python/src/niwrap/afni/v_3dedge3.py +++ /dev/null @@ -1,108 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DEDGE3_METADATA = Metadata( - id="313abf8e7b3a12af92fa8fc519ae8bca1a87eaf0.boutiques", - name="3dedge3", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dedge3Outputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dedge3(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output dataset""" - - -def v_3dedge3( - input_file: InputPathType, - verbose: bool = False, - prefix: str | None = None, - datum: str | None = None, - fscale: bool = False, - gscale: bool = False, - nscale: bool = False, - scale_floats: float | None = None, - automask: bool = False, - runner: Runner | None = None, -) -> V3dedge3Outputs: - """ - Does 3D Edge detection using the library 3DEdge. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input dataset. - verbose: Print out some information along the way. - prefix: Sets the prefix of the output dataset. - datum: Sets the datum of the output dataset. - fscale: Force scaling of the output to the maximum integer range. - gscale: Same as '-fscale', but also forces each output sub-brick to get\ - the same scaling factor. - nscale: Don't do any scaling on output to byte or short datasets. - scale_floats: Multiply input by VAL, but only if the input datum is\ - float. - automask: For automatic internal calculation of a mask in the usual\ - AFNI way. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dedge3Outputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DEDGE3_METADATA) - cargs = [] - cargs.append("3dedge3") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if verbose: - cargs.append("-verbose") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if fscale: - cargs.append("-fscale") - if gscale: - cargs.append("-gscale") - if nscale: - cargs.append("-nscale") - if scale_floats is not None: - cargs.extend([ - "-scale_floats", - str(scale_floats) - ]) - if automask: - cargs.append("-automask") - ret = V3dedge3Outputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dedge3Outputs", - "V_3DEDGE3_METADATA", - "v_3dedge3", -] diff --git a/python/src/niwrap/afni/v_3dedgedog.py b/python/src/niwrap/afni/v_3dedgedog.py deleted file mode 100644 index 0a6f38c54..000000000 --- a/python/src/niwrap/afni/v_3dedgedog.py +++ /dev/null @@ -1,153 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DEDGEDOG_METADATA = Metadata( - id="9e99566b54cfbbe32a2b727088bdd1879b2a5924.boutiques", - name="3dedgedog", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dedgedogOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dedgedog(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_edge: OutputPathType - """Output edge dataset""" - out_dog: OutputPathType - """Output difference of Gaussian dataset""" - out_edt2: OutputPathType - """Output Euclidean Distance Transform squared dataset""" - out_blur_inner: OutputPathType - """Output inner Gaussian blurred dataset""" - out_blur_outer: OutputPathType - """Output outer Gaussian blurred dataset""" - - -def v_3dedgedog( - input_: InputPathType, - prefix: str, - mask: InputPathType | None = None, - automask: str | None = None, - sigma_rad: float | None = None, - sigma_nvox: float | None = None, - ratio_sigma: float | None = None, - output_intermed: bool = False, - edge_bnd_nn: float | None = None, - edge_bnd_side: str | None = None, - edge_bnd_scale: bool = False, - only2d: str | None = None, - runner: Runner | None = None, -) -> V3dedgedogOutputs: - """ - Calculate edges in an image using the Difference of Gaussians (DOG) method with - extensions/tweaks of the Marr-Hildreth algorithm. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - prefix: Output prefix name. - mask: Mask dataset applied after Euclidean Distance Transform\ - calculation. - automask: Calculate mask automatically. Optionally, you can provide an\ - integer X to dilate the initial automask X times (e.g., -automask+X). - sigma_rad: Radius for 'inner' Gaussian, in mm; must be greater than 0\ - (default: 1.40). - sigma_nvox: Define radius for 'inner' Gaussian by providing a\ - multiplicative factor for voxel edge length greater than 0 (default:\ - use sigma_rad). - ratio_sigma: Ratio of inner and outer Gaussian sigma values (default:\ - 1.40). - output_intermed: Output intermediate datasets: DOG, EDT2, BLURS\ - (default: not output). - edge_bnd_nn: Nearest neighbor (NN) value for connectedness of\ - boundaries; must be 1 (face only), 2 (face+edge), or 3 (face+edge+node)\ - (default: 1). - edge_bnd_side: Specify boundary layer to use: NEG, POS, BOTH, BOTH_SIGN\ - (default: NEG). - edge_bnd_scale: Scale edge values to have relative magnitude between 0\ - and 100 (default: edge locations have value=1). - only2d: Calculate edges in 2D per plane specified by SLI: 'axi', 'cor',\ - 'sag'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dedgedogOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DEDGEDOG_METADATA) - cargs = [] - cargs.append("3dedgedog") - cargs.append(execution.input_file(input_)) - cargs.append(prefix) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if automask is not None: - cargs.extend([ - "-automask", - automask - ]) - if sigma_rad is not None: - cargs.extend([ - "-sigma_rad", - str(sigma_rad) - ]) - if sigma_nvox is not None: - cargs.extend([ - "-sigma_nvox", - str(sigma_nvox) - ]) - if ratio_sigma is not None: - cargs.extend([ - "-ratio_sigma", - str(ratio_sigma) - ]) - if output_intermed: - cargs.append("-output_intermed") - if edge_bnd_nn is not None: - cargs.extend([ - "-edge_bnd_NN", - str(edge_bnd_nn) - ]) - if edge_bnd_side is not None: - cargs.extend([ - "-edge_bnd_side", - edge_bnd_side - ]) - if edge_bnd_scale: - cargs.append("-edge_bnd_scale") - if only2d is not None: - cargs.extend([ - "-only2D", - only2d - ]) - ret = V3dedgedogOutputs( - root=execution.output_file("."), - out_edge=execution.output_file(prefix + "_edge.nii.gz"), - out_dog=execution.output_file(prefix + "_dog.nii.gz"), - out_edt2=execution.output_file(prefix + "_edt2.nii.gz"), - out_blur_inner=execution.output_file(prefix + "_blur_inner.nii.gz"), - out_blur_outer=execution.output_file(prefix + "_blur_outer.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dedgedogOutputs", - "V_3DEDGEDOG_METADATA", - "v_3dedgedog", -] diff --git a/python/src/niwrap/afni/v_3dfim_.py b/python/src/niwrap/afni/v_3dfim_.py deleted file mode 100644 index 3ff5ba8d4..000000000 --- a/python/src/niwrap/afni/v_3dfim_.py +++ /dev/null @@ -1,162 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DFIM__METADATA = Metadata( - id="bc809f4b3edfb691248a034084e93881b2cf1fd0.boutiques", - name="3dfim+", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dfimOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dfim_(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile_tlrc_head: OutputPathType | None - """Output bucket dataset containing fit parameters, in TLRC space.""" - outfile_tlrc_brk: OutputPathType | None - """Output bucket dataset containing fit parameters, in TLRC space.""" - outfile_orig_head: OutputPathType | None - """Output bucket dataset containing fit parameters, in original space.""" - outfile_orig_brk: OutputPathType | None - """Output bucket dataset containing fit parameters, in original space.""" - - -def v_3dfim_( - infile: InputPathType, - ideal_file: InputPathType, - input1dfile: InputPathType | None = None, - maskfile: InputPathType | None = None, - first_image: float | None = None, - last_image: float | None = None, - baseline_polynomial: float | None = None, - threshold: float | None = None, - cdisp_value: float | None = None, - ort_file: InputPathType | None = None, - output_params: list[str] | None = None, - output_bucket: str | None = None, - runner: Runner | None = None, -) -> V3dfimOutputs: - """ - Program to calculate the cross-correlation of an ideal reference waveform with - the measured FMRI time series for each voxel. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Filename of input 3d+time dataset. - ideal_file: Input ideal time series file name. Can be used multiple\ - times. - input1dfile: Filename of single (fMRI) .1D time series. - maskfile: Filename of 3d mask dataset. - first_image: Number of first dataset image to use in the\ - cross-correlation procedure (default = 0). - last_image: Number of last dataset image to use in the\ - cross-correlation procedure (default = last). - baseline_polynomial: Degree of polynomial corresponding to the baseline\ - model (default: 1). Use -1 for no baseline model. - threshold: FIM internal mask threshold value (0 <= p <= 1) to get rid\ - of low intensity voxels (default: 0.0999). - cdisp_value: Write (to screen) results for voxels whose correlation\ - stat. > cval (0 <= cval <= 1; default: disabled). - ort_file: Input ort time series file name. Can be used multiple times. - output_params: Output the specified parameter. Can be used multiple\ - times. Possible values are: 'Fit Coef', 'Best Index', '% Change',\ - 'Baseline', 'Correlation', '% From Ave', 'Average', '% From Top',\ - 'Topline', 'Sigma Resid', 'All', 'Spearman CC', 'Quadrant CC'. - output_bucket: Create one AFNI 'bucket' dataset containing the\ - parameters of interest, as specified by the '-out' commands. The output\ - 'bucket' dataset is written to a file with the prefix name bprefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dfimOutputs`). - """ - if threshold is not None and not (0 <= threshold <= 1): - raise ValueError(f"'threshold' must be between 0 <= x <= 1 but was {threshold}") - if cdisp_value is not None and not (0 <= cdisp_value <= 1): - raise ValueError(f"'cdisp_value' must be between 0 <= x <= 1 but was {cdisp_value}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DFIM__METADATA) - cargs = [] - cargs.append("3dfim+") - cargs.append(execution.input_file(infile)) - if input1dfile is not None: - cargs.extend([ - "-input1D", - execution.input_file(input1dfile) - ]) - if maskfile is not None: - cargs.extend([ - "-mask", - execution.input_file(maskfile) - ]) - if first_image is not None: - cargs.extend([ - "-nfirst", - str(first_image) - ]) - if last_image is not None: - cargs.extend([ - "-nlast", - str(last_image) - ]) - if baseline_polynomial is not None: - cargs.extend([ - "-polort", - str(baseline_polynomial) - ]) - if threshold is not None: - cargs.extend([ - "-fim_thr", - str(threshold) - ]) - if cdisp_value is not None: - cargs.extend([ - "-cdisp", - str(cdisp_value) - ]) - if ort_file is not None: - cargs.extend([ - "-ort_file", - execution.input_file(ort_file) - ]) - cargs.extend([ - "-ideal_file", - execution.input_file(ideal_file) - ]) - if output_params is not None: - cargs.extend([ - "-out", - *output_params - ]) - if output_bucket is not None: - cargs.extend([ - "-bucket", - output_bucket - ]) - ret = V3dfimOutputs( - root=execution.output_file("."), - outfile_tlrc_head=execution.output_file(output_bucket + "+tlrc.HEAD") if (output_bucket is not None) else None, - outfile_tlrc_brk=execution.output_file(output_bucket + "+tlrc.BRIK") if (output_bucket is not None) else None, - outfile_orig_head=execution.output_file(output_bucket + "+orig.HEAD") if (output_bucket is not None) else None, - outfile_orig_brk=execution.output_file(output_bucket + "+orig.BRIK") if (output_bucket is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dfimOutputs", - "V_3DFIM__METADATA", - "v_3dfim_", -] diff --git a/python/src/niwrap/afni/v_3dfractionize.py b/python/src/niwrap/afni/v_3dfractionize.py deleted file mode 100644 index 1778ccaf3..000000000 --- a/python/src/niwrap/afni/v_3dfractionize.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DFRACTIONIZE_METADATA = Metadata( - id="700df8ed70958c3087524da2a286d3508d1bd05d.boutiques", - name="3dfractionize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dfractionizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dfractionize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType | None - """Output dataset with the specified prefix.""" - - -def v_3dfractionize( - template: InputPathType, - input_: InputPathType, - prefix: str | None = None, - clip: float | None = None, - warp: InputPathType | None = None, - preserve: bool = False, - vote: bool = False, - runner: Runner | None = None, -) -> V3dfractionizeOutputs: - """ - For each voxel in the output dataset, computes the fraction of it that is - occupied by nonzero voxels from the input. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - template: Use dataset as a template for the output. The output dataset\ - will be on the same grid as this dataset. - input_: Use dataset for the input. Only the sub-brick #0 of the input\ - is used. - prefix: Prefix for the output dataset. - clip: Clip off voxels that are less than the specified occupancy\ - fraction. - warp: Dataset that provides a transformation (warp) from +orig\ - coordinates to the coordinates of the input dataset. - preserve: Preserve the nonzero values of input voxels in the output\ - dataset rather than creating a fractional mask. - vote: Vote for which input value to preserve when using the preserve\ - flag. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dfractionizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DFRACTIONIZE_METADATA) - cargs = [] - cargs.append("3dfractionize") - cargs.extend([ - "-template", - execution.input_file(template) - ]) - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if clip is not None: - cargs.extend([ - "-clip", - str(clip) - ]) - if warp is not None: - cargs.extend([ - "-warp", - execution.input_file(warp) - ]) - if preserve: - cargs.append("-preserve") - if vote: - cargs.append("-vote") - ret = V3dfractionizeOutputs( - root=execution.output_file("."), - output=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dfractionizeOutputs", - "V_3DFRACTIONIZE_METADATA", - "v_3dfractionize", -] diff --git a/python/src/niwrap/afni/v_3dhistog.py b/python/src/niwrap/afni/v_3dhistog.py deleted file mode 100644 index 21f939151..000000000 --- a/python/src/niwrap/afni/v_3dhistog.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DHISTOG_METADATA = Metadata( - id="e7bd0d2e8a320bbb6bd63ecc03a72a5a7207b971.boutiques", - name="3dhistog", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dhistogOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dhistog(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - histogram_output: OutputPathType - """Histogram output when -prefix option is used""" - - -def v_3dhistog( - dataset: InputPathType, - nbin: float | None = None, - dind: float | None = None, - omit: list[float] | None = None, - mask: InputPathType | None = None, - roi_mask: InputPathType | None = None, - doall: bool = False, - noempty: bool = False, - notitle: bool = False, - log10: bool = False, - pdf: bool = False, - min_: float | None = None, - max_: float | None = None, - igfac: bool = False, - int_: bool = False, - float_: bool = False, - unq: str | None = None, - prefix: str | None = None, - runner: Runner | None = None, -) -> V3dhistogOutputs: - """ - Compute histogram of a 3D dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input dataset. - nbin: Use specified number of bins. - dind: Use data from specified sub-brick index. - omit: Omit specified value from the count. - mask: Use mask dataset to determine which voxels to use. - roi_mask: Create histogram for each non-zero value in 'r' dataset. - doall: Include all sub-bricks in the calculation. - noempty: Only output bins that are not empty. - notitle: Leave the title line off the output. - log10: Output log10() of the counts. - pdf: Output the counts divided by the number of samples. - min_: Specify minimum (inclusive) of histogram. - max_: Specify maximum (inclusive) of histogram. - igfac: Ignore sub-brick scale factors and histogram-ize the 'raw' data. - int_: Treat data and output as integers. - float_: Treat data and output as floats. - unq: Writes out the sorted unique values to file. - prefix: Write a copy of the histogram into specified file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dhistogOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DHISTOG_METADATA) - cargs = [] - cargs.append("3dhistog") - cargs.append(execution.input_file(dataset)) - if nbin is not None: - cargs.extend([ - "-nbin", - str(nbin) - ]) - if dind is not None: - cargs.extend([ - "-dind", - str(dind) - ]) - if omit is not None: - cargs.extend([ - "-omit", - *map(str, omit) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if roi_mask is not None: - cargs.extend([ - "-roi_mask", - execution.input_file(roi_mask) - ]) - if doall: - cargs.append("-doall") - if noempty: - cargs.append("-noempty") - if notitle: - cargs.append("-notitle") - if log10: - cargs.append("-log10") - if pdf: - cargs.append("-pdf") - if min_ is not None: - cargs.extend([ - "-min", - str(min_) - ]) - if max_ is not None: - cargs.extend([ - "-max", - str(max_) - ]) - if igfac: - cargs.append("-igfac") - if int_: - cargs.append("-int") - if float_: - cargs.append("-float") - if unq is not None: - cargs.extend([ - "-unq", - unq - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = V3dhistogOutputs( - root=execution.output_file("."), - histogram_output=execution.output_file("HOUT.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dhistogOutputs", - "V_3DHISTOG_METADATA", - "v_3dhistog", -] diff --git a/python/src/niwrap/afni/v_3dinfill.py b/python/src/niwrap/afni/v_3dinfill.py deleted file mode 100644 index 885910a9e..000000000 --- a/python/src/niwrap/afni/v_3dinfill.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DINFILL_METADATA = Metadata( - id="fbd1b7cc59f1f5f4fa7e41073958d3e52dfad929.boutiques", - name="3dinfill", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dinfillOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dinfill(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_filled: OutputPathType | None - """Filled volume output""" - - -def v_3dinfill( - input_: InputPathType, - prefix: str | None = None, - niter: float | None = None, - blend: typing.Literal["MODE", "AVG", "AUTO", "SOLID", "SOLID_CLEAN"] | None = None, - minhits: float | None = None, - ed: list[float] | None = None, - mask: InputPathType | None = None, - mask_range: list[float] | None = None, - mrange: list[float] | None = None, - cmask: str | None = None, - runner: Runner | None = None, -) -> V3dinfillOutputs: - """ - A program to fill holes in volumes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Fill volume dataset. - prefix: Use PREF for output prefix. - niter: Do not allow the fill function to do more than NITER passes. - blend: Method for assigning a value to a hole. - minhits: Criterion for considering a zero voxel to be a hole. Can only\ - be used with -blend SOLID. - ed: Erode N times then dilate N times to get rid of hanging chunks.\ - Values filled in by this process get value V. - mask: Provide mask dataset to select subset of input. - mask_range: Specify the range of values to consider from mask dataset. - mrange: Alias for -mask_range option. - cmask: Provide cmask expression. Voxels where expression is 0 are\ - excluded from computations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dinfillOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DINFILL_METADATA) - cargs = [] - cargs.append("3dinfill") - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if niter is not None: - cargs.extend([ - "-Niter", - str(niter) - ]) - if blend is not None: - cargs.extend([ - "-blend", - blend - ]) - if minhits is not None: - cargs.extend([ - "-minhits", - str(minhits) - ]) - if ed is not None: - cargs.extend([ - "-ed", - *map(str, ed) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mask_range is not None: - cargs.extend([ - "-mask_range", - *map(str, mask_range) - ]) - if mrange is not None: - cargs.extend([ - "-mrange", - *map(str, mrange) - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - ret = V3dinfillOutputs( - root=execution.output_file("."), - output_filled=execution.output_file(prefix + "_filled.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dinfillOutputs", - "V_3DINFILL_METADATA", - "v_3dinfill", -] diff --git a/python/src/niwrap/afni/v_3dinfo.py b/python/src/niwrap/afni/v_3dinfo.py deleted file mode 100644 index 387d55d07..000000000 --- a/python/src/niwrap/afni/v_3dinfo.py +++ /dev/null @@ -1,556 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DINFO_METADATA = Metadata( - id="616677dc5c795aa5868596f1b7559dd21a0f20c6.boutiques", - name="3dinfo", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dinfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dinfo(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3dinfo( - dataset: list[InputPathType], - orient: bool = False, - lextent: bool = False, - rextent: bool = False, - aextent: bool = False, - pextent: bool = False, - iextent: bool = False, - sextent: bool = False, - all_names: bool = False, - verb: bool = False, - very_verbose: bool = False, - short: bool = False, - no_hist: bool = False, - h: bool = False, - help_: bool = False, - extreme_help: bool = False, - h_view: bool = False, - h_web: bool = False, - h_find: str | None = None, - h_raw: bool = False, - h_spx: bool = False, - h_aspx: bool = False, - all_opts: bool = False, - label2index: str | None = None, - niml_hdr: bool = False, - subbrick_info: bool = False, - exists: bool = False, - id_: bool = False, - is_atlas: bool = False, - is_atlas_or_labeltable: bool = False, - is_nifti: bool = False, - dset_extension: bool = False, - storage_mode: bool = False, - space: bool = False, - gen_space: bool = False, - av_space: bool = False, - nifti_code: bool = False, - is_oblique: bool = False, - handedness: bool = False, - obliquity: bool = False, - prefix: bool = False, - prefix_noext: bool = False, - ni: bool = False, - nj: bool = False, - nk: bool = False, - nijk: bool = False, - nv: bool = False, - nt_: bool = False, - n4: bool = False, - nvi: bool = False, - nti: bool = False, - ntimes: bool = False, - max_node: bool = False, - di: bool = False, - dj: bool = False, - dk: bool = False, - d3: bool = False, - adi: bool = False, - adj: bool = False, - adk: bool = False, - ad3: bool = False, - voxvol: bool = False, - oi: bool = False, - oj: bool = False, - ok: bool = False, - o3: bool = False, - dcx: bool = False, - dcy: bool = False, - dcz: bool = False, - dc3: bool = False, - tr: bool = False, - dmin: bool = False, - dmax: bool = False, - dminus: bool = False, - dmaxus: bool = False, - smode: bool = False, - header_name: bool = False, - brick_name: bool = False, - iname: bool = False, - extent: bool = False, - fac: bool = False, - label: bool = False, - datum: bool = False, - min_: bool = False, - max_: bool = False, - minus: bool = False, - maxus: bool = False, - labeltable: bool = False, - labeltable_as_atlas_points: bool = False, - atlas_points: bool = False, - history: bool = False, - slice_timing: bool = False, - header_line: bool = False, - hdr: bool = False, - sb_delim: str | None = None, - na_flag: str | None = None, - atr_delim: str | None = None, - aform_real: bool = False, - aform_real_oneline: bool = False, - aform_real_refit_ori: bool = False, - is_aform_real_orth: bool = False, - aform_orth: bool = False, - perm_to_orient: str | None = None, - same_grid: bool = False, - same_dim: bool = False, - same_delta: bool = False, - same_orient: bool = False, - same_center: bool = False, - same_obl: bool = False, - same_all_grid: bool = False, - val_diff: bool = False, - sval_diff: bool = False, - monog_pairs: bool = False, - runner: Runner | None = None, -) -> V3dinfoOutputs: - """ - Prints out sort-of-useful information from a 3D dataset's header. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Datasets to retrieve information from. - orient: Value of orientation string. For example, LPI means: i\ - direction grows from Left(negative) to Right(positive). j direction\ - grows from Posterior (neg.) to Anterior (pos.) k direction grows from\ - Inferior (neg.) to Superior (pos.). - lextent: Extent along L. - rextent: Extent along R. - aextent: Extent along A. - pextent: Extent along P. - iextent: Extent along I. - sextent: Extent along S. - all_names: Value of various dset structures handling filenames. - verb: Print out lots of information. - very_verbose: Print out even more information including slice time\ - offsets. - short: Print out less information (default). - no_hist: Omit the HISTORY text. - h: Mini help. - help_: Display entire help output. - extreme_help: Extreme help. - h_view: Open help in text editor. - h_web: Open help in web browser. - h_find: Look for lines in help output that match WORD. - h_raw: Display unedited help string. - h_spx: Help string in sphinx format without autoformatting options. - h_aspx: Help string in sphinx format with autoformatting options. - all_opts: Try to identify all options for the program from the help\ - output. - label2index: Output index corresponding to label. - niml_hdr: Output entire NIML-formatted header. - subbrick_info: Output only sub-brick part of information. - exists: 1 if dset is loadable, 0 otherwise. This works on prefix also. - id_: Idcodestring of dset. - is_atlas: 1 if dset is an atlas. - is_atlas_or_labeltable: 1 if dset has an atlas or labeltable. - is_nifti: 1 if dset is NIFTI format, 0 otherwise. - dset_extension: Show filename extension for valid dataset (e.g.\ - .nii.gz). - storage_mode: Show internal storage mode of dataset (e.g. NIFTI). - space: Dataset's space. - gen_space: Dataset's generic space. - av_space: AFNI format's view extension for the space. - nifti_code: What AFNI would use for an output NIFTI (q)sform_code. - is_oblique: 1 if dset is oblique. - handedness: L if orientation is Left handed, R if it is right handed. - obliquity: Angle from plumb direction. Angles of 0 (or close) are for\ - cardinal orientations. - prefix: Return the prefix. - prefix_noext: Return the prefix without extensions. - ni: Return the number of voxels in i dimension. - nj: Return the number of voxels in j dimension. - nk: Return the number of voxels in k dimension. - nijk: Return ni*nj*nk. - nv: Return number of points in time or the number of sub-bricks. - nt_: Same as -nv. - n4: Same as -ni -nj -nk -nv. - nvi: The maximum sub-brick index (= nv -1 ). - nti: Same as -nvi. - ntimes: Return number of sub-bricks points in time. This is an option\ - for debugging use, stay away from it. - max_node: For a surface-based dset, return the maximum node index. - di: Signed displacement per voxel along i direction, aka dx. - dj: Signed displacement per voxel along j direction, aka dy. - dk: Signed displacement per voxel along k direction, aka dz. - d3: Same as -di -dj -dk. - adi: Voxel size along i direction (abs(di)). - adj: Voxel size along j direction (abs(dj)). - adk: Voxel size along k direction (abs(dk)). - ad3: Same as -adi -adj -adk. - voxvol: Voxel volume in cubic millimeters. - oi: Volume origin along the i direction. - oj: Volume origin along the j direction. - ok: Volume origin along the k direction. - o3: Same as -oi -oj -ok. - dcx: Volumetric center in x direction (DICOM coordinates). - dcy: Volumetric center in y direction (DICOM coordinates). - dcz: Volumetric center in z direction (DICOM coordinates). - dc3: Same as -dcx -dcy -dcz. - tr: The TR value in seconds. - dmin: The dataset's minimum value, scaled by fac. - dmax: The dataset's maximum value, scaled by fac. - dminus: The dataset's minimum value, unscaled. - dmaxus: The dataset's maximum value, unscaled. - smode: Dset storage mode string. - header_name: Value of dset structure (sub)field 'header_name'. - brick_name: Value of dset structure (sub)field 'brick_name'. - iname: Name of dset as input on the command line. - extent: The spatial extent of the dataset along R, L, A, P, I and S. - fac: Return the float scaling factor. - label: The label of each sub-brick. - datum: The data storage type. - min_: The minimum value, scaled by fac. - max_: The maximum value, scaled by fac. - minus: The minimum value, unscaled. - maxus: The maximum value, unscaled. - labeltable: Show label table, if any. - labeltable_as_atlas_points: Show label table in atlas point format. - atlas_points: Show atlas points list, if any. - history: History note. - slice_timing: Show slice timing. - header_line: Output as the first line the names of attributes in each\ - field (column). - hdr: Same as -header_line. - sb_delim: Delimiter string between sub-brick values. Default SB_DELIM\ - is '|'. - na_flag: String to use when a field is not found or not applicable.\ - Default is 'NA'. - atr_delim: Delimiter string between attributes. Default ATR_DELIM is\ - the tab character. - aform_real: Display full 3x4 'aform_real' matrix (AFNI's RAI equivalent\ - of the sform matrix in NIFTI, may contain obliquity info), with comment\ - line first. - aform_real_oneline: Display full 'aform_real' matrix (see\ - '-aform_real') as 1 row of 12 numbers. No additional comment. - aform_real_refit_ori: Display full 3x4 'aform_real' matrix (see\ - '-aform_real') *if* the dset were reoriented (via 3drefit) to new\ - orient XXX. Includes comment line first. - is_aform_real_orth: If true, aform_real == aform_orth, which should be\ - a very common occurrence. - aform_orth: Display full 3x4 'aform_orth' matrix (AFNI's RAI matrix\ - equivalent of the NIFTI quaternion, which may contain obliquity info),\ - with comment line first. This matrix is the orthogonalized form of\ - aform_real, and very often AFNI-produced dsets, we will have:\ - aform_orth == aform_real. - perm_to_orient: Display 3x3 permutation matrix to go from the dset's\ - current orientation to the YYY orient. - same_grid: Output 1 if the grid is identical between two dsets, 0\ - otherwise. For -same_grid to be 1, all of -same_dim, -same_delta,\ - -same_orient, -same_center, and -same_obl must return 1. - same_dim: 1 if dimensions (nx, ny, nz) are the same between dset pairs. - same_delta: 1 if voxel sizes are the same between dset pairs. - same_orient: 1 if orientation is the same between dset pairs. - same_center: 1 if geometric center is the same between dset pairs. - same_obl: 1 if obliquity is the same between dset pairs. - same_all_grid: Equivalent to listing all of -same_dim, -same_delta,\ - -same_orient, -same_center, and -same_obl on the command line. - val_diff: Output the sum of absolute differences of all voxels in the\ - dataset pair. A -1.0 value indicates a grid mismatch between volume\ - pairs. - sval_diff: Same as -val_diff, but the sum is divided (scaled) by the\ - total number of voxels that are not zero in at least one of the two\ - datasets. - monog_pairs: Instead of pairing each dset with the first, pair each\ - couple separately. This requires you to have an even number of dsets on\ - the command line. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dinfoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DINFO_METADATA) - cargs = [] - cargs.append("3dinfo") - if orient: - cargs.append("-orient") - if lextent: - cargs.append("-Lextent") - if rextent: - cargs.append("-Rextent") - if aextent: - cargs.append("-Aextent") - if pextent: - cargs.append("-Pextent") - if iextent: - cargs.append("-Iextent") - if sextent: - cargs.append("-Sextent") - if all_names: - cargs.append("-all_names") - if verb: - cargs.append("-verb") - if very_verbose: - cargs.append("-VERB") - if short: - cargs.append("-short") - if no_hist: - cargs.append("-no_hist") - if h: - cargs.append("-h") - if help_: - cargs.append("-help") - if extreme_help: - cargs.append("-HELP") - if h_view: - cargs.append("-h_view") - if h_web: - cargs.append("-h_web") - if h_find is not None: - cargs.extend([ - "-h_find", - h_find - ]) - if h_raw: - cargs.append("-h_raw") - if h_spx: - cargs.append("-h_spx") - if h_aspx: - cargs.append("-h_aspx") - if all_opts: - cargs.append("-all_opts") - if label2index is not None: - cargs.extend([ - "-label2index", - label2index - ]) - if niml_hdr: - cargs.append("-niml_hdr") - if subbrick_info: - cargs.append("-subbrick_info") - if exists: - cargs.append("-exists") - if id_: - cargs.append("-id") - if is_atlas: - cargs.append("-is_atlas") - if is_atlas_or_labeltable: - cargs.append("-is_atlas_or_labeltable") - if is_nifti: - cargs.append("-is_nifti") - if dset_extension: - cargs.append("-dset_extension") - if storage_mode: - cargs.append("-storage_mode") - if space: - cargs.append("-space") - if gen_space: - cargs.append("-gen_space") - if av_space: - cargs.append("-av_space") - if nifti_code: - cargs.append("-nifti_code") - if is_oblique: - cargs.append("-is_oblique") - if handedness: - cargs.append("-handedness") - if obliquity: - cargs.append("-obliquity") - if prefix: - cargs.append("-prefix") - if prefix_noext: - cargs.append("-prefix_noext") - if ni: - cargs.append("-ni") - if nj: - cargs.append("-nj") - if nk: - cargs.append("-nk") - if nijk: - cargs.append("-nijk") - if nv: - cargs.append("-nv") - if nt_: - cargs.append("-nt") - if n4: - cargs.append("-n4") - if nvi: - cargs.append("-nvi") - if nti: - cargs.append("-nti") - if ntimes: - cargs.append("-ntimes") - if max_node: - cargs.append("-max_node") - if di: - cargs.append("-di") - if dj: - cargs.append("-dj") - if dk: - cargs.append("-dk") - if d3: - cargs.append("-d3") - if adi: - cargs.append("-adi") - if adj: - cargs.append("-adj") - if adk: - cargs.append("-adk") - if ad3: - cargs.append("-ad3") - if voxvol: - cargs.append("-voxvol") - if oi: - cargs.append("-oi") - if oj: - cargs.append("-oj") - if ok: - cargs.append("-ok") - if o3: - cargs.append("-o3") - if dcx: - cargs.append("-dcx") - if dcy: - cargs.append("-dcy") - if dcz: - cargs.append("-dcz") - if dc3: - cargs.append("-dc3") - if tr: - cargs.append("-tr") - if dmin: - cargs.append("-dmin") - if dmax: - cargs.append("-dmax") - if dminus: - cargs.append("-dminus") - if dmaxus: - cargs.append("-dmaxus") - if smode: - cargs.append("-smode") - if header_name: - cargs.append("-header_name") - if brick_name: - cargs.append("-brick_name") - if iname: - cargs.append("-iname") - if extent: - cargs.append("-extent") - if fac: - cargs.append("-fac") - if label: - cargs.append("-label") - if datum: - cargs.append("-datum") - if min_: - cargs.append("-min") - if max_: - cargs.append("-max") - if minus: - cargs.append("-minus") - if maxus: - cargs.append("-maxus") - if labeltable: - cargs.append("-labeltable") - if labeltable_as_atlas_points: - cargs.append("-labeltable_as_atlas_points") - if atlas_points: - cargs.append("-atlas_points") - if history: - cargs.append("-history") - if slice_timing: - cargs.append("-slice_timing") - if header_line: - cargs.append("-header_line") - if hdr: - cargs.append("-hdr") - if sb_delim is not None: - cargs.extend([ - "-sb_delim", - sb_delim - ]) - if na_flag is not None: - cargs.extend([ - "-NA_flag", - na_flag - ]) - if atr_delim is not None: - cargs.extend([ - "-atr_delim", - atr_delim - ]) - if aform_real: - cargs.append("-aform_real") - if aform_real_oneline: - cargs.append("-aform_real_oneline") - if aform_real_refit_ori: - cargs.append("-aform_real_refit_ori") - if is_aform_real_orth: - cargs.append("-is_aform_real_orth") - if aform_orth: - cargs.append("-aform_orth") - if perm_to_orient is not None: - cargs.extend([ - "-perm_to_orient", - perm_to_orient - ]) - if same_grid: - cargs.append("-same_grid") - if same_dim: - cargs.append("-same_dim") - if same_delta: - cargs.append("-same_delta") - if same_orient: - cargs.append("-same_orient") - if same_center: - cargs.append("-same_center") - if same_obl: - cargs.append("-same_obl") - if same_all_grid: - cargs.append("-same_all_grid") - if val_diff: - cargs.append("-val_diff") - if sval_diff: - cargs.append("-sval_diff") - if monog_pairs: - cargs.append("-monog_pairs") - cargs.extend([execution.input_file(f) for f in dataset]) - ret = V3dinfoOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dinfoOutputs", - "V_3DINFO_METADATA", - "v_3dinfo", -] diff --git a/python/src/niwrap/afni/v_3dkmeans.py b/python/src/niwrap/afni/v_3dkmeans.py deleted file mode 100644 index 7a9ae729c..000000000 --- a/python/src/niwrap/afni/v_3dkmeans.py +++ /dev/null @@ -1,214 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DKMEANS_METADATA = Metadata( - id="4536293f2db1b50ebead4293161f46a508afd8a7.boutiques", - name="3dkmeans", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dkmeansOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dkmeans(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - cluster_membership: OutputPathType | None - """Output volume for the cluster membership.""" - cluster_distance: OutputPathType | None - """Output volume for the cluster distance measures.""" - distances_text_file: OutputPathType - """Output text file containing distances between clusters.""" - centroids_text_file: OutputPathType - """Output text file containing cluster centroids.""" - within_cluster_sum_text_file: OutputPathType - """Output text file containing within cluster sum of distances.""" - max_distance_text_file: OutputPathType - """Output text file containing maximum distance within each cluster.""" - voxel_distance_to_centroid: OutputPathType - """Output text file containing distance from voxel to its centroid.""" - - -def v_3dkmeans( - input_: list[InputPathType], - version: bool = False, - mask: InputPathType | None = None, - mask_range: list[float] | None = None, - cmask: str | None = None, - jobname: str | None = None, - prefix: str | None = None, - distance_measure: float | None = None, - num_clusters: float | None = None, - remap_method: str | None = None, - labeltable: InputPathType | None = None, - clabels: list[str] | None = None, - clust_init: InputPathType | None = None, - num_repeats: float | None = None, - rsigs: InputPathType | None = None, - verbose: bool = False, - write_dists: bool = False, - voxdbg: list[float] | None = None, - seed: float | None = None, - runner: Runner | None = None, -) -> V3dkmeansOutputs: - """ - 3d+t Clustering segmentation based on The C clustering library. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input data to be clustered. You can specify multiple filenames\ - in sequence and they will be concatenated internally. - version:. - mask: Dataset to be used as a mask; only voxels with nonzero values in\ - 'mset' will be used. - mask_range: Restrict the voxels from 'mset' to only those mask values\ - between 'a' and 'b' (inclusive). - cmask: Execute the options enclosed in single quotes as a 3dcalc-like\ - program to produce a mask from the resulting 3D brick. - jobname: Specify a different name for the output files. Default is\ - derived from the input file name. - prefix: Specify a prefix for the output volumes. Default is the same as\ - jobname. - distance_measure: Specifies distance measure for clustering. Supported\ - values: 0 (No clustering), 1 (Uncentered correlation distance), 2\ - (Pearson distance), 3 (Uncentered correlation distance, absolute\ - value), 4 (Pearson distance, absolute value), 5 (Spearman's rank\ - distance), 6 (Kendall's distance), 7 (Euclidean distance), 8\ - (City-block distance). - num_clusters: Specify number of clusters. - remap_method: Reassign clusters numbers based on METHOD: NONE\ - (default), COUNT, iCOUNT, MAG, iMAG. - labeltable: Attach labeltable to clustering output. - clabels: Provide a label for each cluster. Labels cannot start with\ - '-'. - clust_init: Specify a dataset to initialize clustering. If provided,\ - sets -r 0. - num_repeats: Number of times the k-means clustering algorithm is run. - rsigs: Calculate distances from each voxel's signature to the\ - signatures in this multi-column file. No clustering done. - verbose: Enable verbose mode. - write_dists: Output text files containing various distance measures. - voxdbg: Output debugging info for specified voxel (I J K). - seed: Seed for the random number generator. Default is 1234567. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dkmeansOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DKMEANS_METADATA) - cargs = [] - cargs.append("3dkmeans") - if version: - cargs.append("--version") - cargs.extend([ - "-f", - *[execution.input_file(f) for f in input_] - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if mask_range is not None: - cargs.extend([ - "-mrange", - *map(str, mask_range) - ]) - if cmask is not None: - cargs.extend([ - "-cmask", - cmask - ]) - if jobname is not None: - cargs.extend([ - "-u", - jobname - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if distance_measure is not None: - cargs.extend([ - "-g", - str(distance_measure) - ]) - if num_clusters is not None: - cargs.extend([ - "-k", - str(num_clusters) - ]) - if remap_method is not None: - cargs.extend([ - "-remap", - remap_method - ]) - if labeltable is not None: - cargs.extend([ - "-labeltable", - execution.input_file(labeltable) - ]) - if clabels is not None: - cargs.extend([ - "-clabels", - *clabels - ]) - if clust_init is not None: - cargs.extend([ - "-clust_init", - execution.input_file(clust_init) - ]) - if num_repeats is not None: - cargs.extend([ - "-r", - str(num_repeats) - ]) - if rsigs is not None: - cargs.extend([ - "-rsigs", - execution.input_file(rsigs) - ]) - if verbose: - cargs.append("-verb") - if write_dists: - cargs.append("-write_dists") - if voxdbg is not None: - cargs.extend([ - "-voxdbg", - *map(str, voxdbg) - ]) - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - ret = V3dkmeansOutputs( - root=execution.output_file("."), - cluster_membership=execution.output_file(jobname + "_membership.nii.gz") if (jobname is not None) else None, - cluster_distance=execution.output_file(jobname + "_distance.nii.gz") if (jobname is not None) else None, - distances_text_file=execution.output_file("FILE.dis.1D"), - centroids_text_file=execution.output_file("FILE.cen.1D"), - within_cluster_sum_text_file=execution.output_file("FILE.info1.1D"), - max_distance_text_file=execution.output_file("FILE.info2.1D"), - voxel_distance_to_centroid=execution.output_file("FILE.vcd.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dkmeansOutputs", - "V_3DKMEANS_METADATA", - "v_3dkmeans", -] diff --git a/python/src/niwrap/afni/v_3dmask_svd.py b/python/src/niwrap/afni/v_3dmask_svd.py deleted file mode 100644 index 1e5103441..000000000 --- a/python/src/niwrap/afni/v_3dmask_svd.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMASK_SVD_METADATA = Metadata( - id="35a41f546084a553fd9cc0738b19f404d7380c06.boutiques", - name="3dmaskSVD", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaskSvdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmask_svd(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - svd_output: OutputPathType - """Singular vector output redirected to this file""" - - -def v_3dmask_svd( - input_dataset: InputPathType, - runner: Runner | None = None, -) -> V3dmaskSvdOutputs: - """ - Computes the principal singular vector of the time series vectors extracted from - the input dataset over the input mask. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaskSvdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMASK_SVD_METADATA) - cargs = [] - cargs.append("3dmaskSVD") - cargs.append("[OPTIONS]") - cargs.append(execution.input_file(input_dataset)) - ret = V3dmaskSvdOutputs( - root=execution.output_file("."), - svd_output=execution.output_file("../stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaskSvdOutputs", - "V_3DMASK_SVD_METADATA", - "v_3dmask_svd", -] diff --git a/python/src/niwrap/afni/v_3dmask_tool.py b/python/src/niwrap/afni/v_3dmask_tool.py deleted file mode 100644 index aaadf02ae..000000000 --- a/python/src/niwrap/afni/v_3dmask_tool.py +++ /dev/null @@ -1,142 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMASK_TOOL_METADATA = Metadata( - id="e7bb0d5afe6f71d2fb57613d5c39c83b7fb4876f.boutiques", - name="3dmask_tool", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaskToolOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmask_tool(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Mask file.""" - - -def v_3dmask_tool( - in_file: InputPathType, - count: bool = False, - datum: typing.Literal["byte", "short", "float"] | None = None, - dilate_inputs: str | None = None, - dilate_results: str | None = None, - fill_dirs: str | None = None, - fill_holes: bool = False, - frac: float | None = None, - inter: bool = False, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - union: bool = False, - verbose: int | None = None, - runner: Runner | None = None, -) -> V3dmaskToolOutputs: - """ - 3dmask_tool - for combining/dilating/eroding/filling masks. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dmask_tool. - count: Instead of created a binary 0/1 mask dataset, create one with\ - counts of voxel overlap, i.e., each voxel will contain the number of\ - masks that it is set in. - datum: 'byte' or 'short' or 'float'. Specify data type for output. - dilate_inputs: Use this option to dilate and/or erode datasets as they\ - are read. ex. '5 -5' to dilate and erode 5 times. - dilate_results: Dilate and/or erode combined mask at the given levels. - fill_dirs: Fill holes only in the given directions. this option is for\ - use with -fill holes. should be a single string that specifies 1-3 of\ - the axes using {x,y,z} labels (i.e. dataset axis order), or using the\ - labels in {r,l,a,p,i,s}. - fill_holes: This option can be used to fill holes in the resulting\ - mask, i.e. after all other processing has been done. - frac: When combining masks (across datasets and sub-bricks), use this\ - option to restrict the result to a certain fraction of the set of\ - volumes. - inter: Intersection, this means -frac 1.0. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - union: Union, this means -frac 0. - verbose: Specify verbosity level, for 0 to 3. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaskToolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMASK_TOOL_METADATA) - cargs = [] - cargs.append("3dmask_tool") - if count: - cargs.append("-count") - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if dilate_inputs is not None: - cargs.extend([ - "-dilate_inputs", - dilate_inputs - ]) - if dilate_results is not None: - cargs.extend([ - "-dilate_results", - dilate_results - ]) - if fill_dirs is not None: - cargs.extend([ - "-fill_dirs", - fill_dirs - ]) - if fill_holes: - cargs.append("-fill_holes") - if frac is not None: - cargs.extend([ - "-frac", - str(frac) - ]) - cargs.extend([ - "-input", - execution.input_file(in_file) - ]) - if inter: - cargs.append("-inter") - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if union: - cargs.append("-union") - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - ret = V3dmaskToolOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_mask"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaskToolOutputs", - "V_3DMASK_TOOL_METADATA", - "v_3dmask_tool", -] diff --git a/python/src/niwrap/afni/v_3dmaskave.py b/python/src/niwrap/afni/v_3dmaskave.py deleted file mode 100644 index 29072d2c0..000000000 --- a/python/src/niwrap/afni/v_3dmaskave.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMASKAVE_METADATA = Metadata( - id="f042c07e22593dec9c151337660698f3bafa0f2a.boutiques", - name="3dmaskave", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaskaveOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmaskave(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - out_file_: OutputPathType - """Output file.""" - - -def v_3dmaskave( - in_file: InputPathType, - mask: InputPathType | None = None, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dmaskaveOutputs: - """ - Computes average of all voxels in the input dataset which satisfy the criterion - in the options list. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dmaskave. - mask: Matrix to align input file. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - quiet: Matrix to align input file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaskaveOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMASKAVE_METADATA) - cargs = [] - cargs.append("3dmaskave") - cargs.append(execution.input_file(in_file)) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if quiet: - cargs.append("-quiet") - ret = V3dmaskaveOutputs( - root=execution.output_file("."), - out_file=execution.output_file(pathlib.Path(in_file).name + "_maskave.1D"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaskaveOutputs", - "V_3DMASKAVE_METADATA", - "v_3dmaskave", -] diff --git a/python/src/niwrap/afni/v_3dmaskdump.py b/python/src/niwrap/afni/v_3dmaskdump.py deleted file mode 100644 index 4d0285ad6..000000000 --- a/python/src/niwrap/afni/v_3dmaskdump.py +++ /dev/null @@ -1,192 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMASKDUMP_METADATA = Metadata( - id="9cb4c849a9357c37ec67fbe234f23f59f3a3a158.boutiques", - name="3dmaskdump", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaskdumpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmaskdump(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output ASCII file with voxel values""" - - -def v_3dmaskdump( - input_files: list[InputPathType], - mask_dataset: InputPathType | None = None, - mask_range: list[str] | None = None, - output_index: bool = False, - output_noijk: bool = False, - output_xyz: bool = False, - output_filename: str | None = None, - calc_mask_opts: str | None = None, - xbox_coords: str | None = None, - dbox_coords: str | None = None, - nbox_coords: str | None = None, - ibox_coords: str | None = None, - xball_coords: str | None = None, - dball_coords: str | None = None, - nball_coords: str | None = None, - nozero_output: bool = False, - random_voxels: float | None = None, - random_seed: float | None = None, - output_niml: str | None = None, - quiet_mode: bool = False, - runner: Runner | None = None, -) -> V3dmaskdumpOutputs: - """ - Outputs voxel values from AFNI datasets satisfying mask criteria to an ASCII - file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets to dump voxel values. - mask_dataset: Use the dataset as a mask. Only voxels with nonzero\ - values in the mask will be printed from the input dataset. - mask_range: Further restrict the voxels from mask dataset to those mask\ - values between 'a' and 'b' (inclusive). - output_index: Write out the dataset index values. - output_noijk: Do not write out the i,j,k values. - output_xyz: Write the x,y,z coordinates from the first input dataset at\ - the start of each output line. - output_filename: Write output to specified file. - calc_mask_opts: Execute options enclosed as a 3dcalc-like program to\ - produce a mask from the resulting 3D brick. - xbox_coords: Put a 'mask' at dataset coordinates 'x y z' mm. - dbox_coords: Put a 'mask' at RAI/DICOM coordinates of 'x y z' mm. - nbox_coords: Put a 'mask' at LPI/SPM coordinates of 'x y z' mm. - ibox_coords: Put a 'mask' at voxel indexes 'i j k'. - xball_coords: Put a ball (sphere) mask at dataset coordinates (x,y,z)\ - with radius r. - dball_coords: Put a ball (sphere) mask at RAI/DICOM coordinates (x,y,z)\ - with radius r. - nball_coords: Put a ball (sphere) mask at LPI/SPM coordinates (x,y,z)\ - with radius r. - nozero_output: Skip output of any voxel where all the data values are\ - zero. - random_voxels: Keep only N_RAND randomly selected voxels from what\ - would have been the output. - random_seed: Seed the random number generator with SEED. - output_niml: Output data in the XML/NIML format compatible with input\ - back to AFNI via the READ_NIML_FILE command. - quiet_mode: Do not print progress messages to stderr. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaskdumpOutputs`). - """ - if mask_range is not None and (len(mask_range) != 2): - raise ValueError(f"Length of 'mask_range' must be 2 but was {len(mask_range)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMASKDUMP_METADATA) - cargs = [] - cargs.append("3dmaskdump") - cargs.extend([execution.input_file(f) for f in input_files]) - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - if mask_range is not None: - cargs.extend([ - "-mrange", - *mask_range - ]) - if output_index: - cargs.append("-index") - if output_noijk: - cargs.append("-noijk") - if output_xyz: - cargs.append("-xyz") - if output_filename is not None: - cargs.extend([ - "-o", - output_filename - ]) - if calc_mask_opts is not None: - cargs.extend([ - "-cmask", - calc_mask_opts - ]) - if xbox_coords is not None: - cargs.extend([ - "-xbox", - xbox_coords - ]) - if dbox_coords is not None: - cargs.extend([ - "-dbox", - dbox_coords - ]) - if nbox_coords is not None: - cargs.extend([ - "-nbox", - nbox_coords - ]) - if ibox_coords is not None: - cargs.extend([ - "-ibox", - ibox_coords - ]) - if xball_coords is not None: - cargs.extend([ - "-xball", - xball_coords - ]) - if dball_coords is not None: - cargs.extend([ - "-dball", - dball_coords - ]) - if nball_coords is not None: - cargs.extend([ - "-nball", - nball_coords - ]) - if nozero_output: - cargs.append("-nozero") - if random_voxels is not None: - cargs.extend([ - "-n_rand", - str(random_voxels) - ]) - if random_seed is not None: - cargs.extend([ - "-n_randseed", - str(random_seed) - ]) - if output_niml is not None: - cargs.extend([ - "-niml", - output_niml - ]) - if quiet_mode: - cargs.append("-quiet") - ret = V3dmaskdumpOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_filename) if (output_filename is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaskdumpOutputs", - "V_3DMASKDUMP_METADATA", - "v_3dmaskdump", -] diff --git a/python/src/niwrap/afni/v_3dmatcalc.py b/python/src/niwrap/afni/v_3dmatcalc.py deleted file mode 100644 index f9e58de94..000000000 --- a/python/src/niwrap/afni/v_3dmatcalc.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMATCALC_METADATA = Metadata( - id="4a12ce66d0030ed964e44d50ee57940da8cb40ca.boutiques", - name="3dmatcalc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmatcalcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmatcalc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_header: OutputPathType - """Output dataset header file.""" - output_brick: OutputPathType - """Output dataset brick file.""" - - -def v_3dmatcalc( - input_dataset: InputPathType, - input_matrix: InputPathType, - output_dataset: str, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dmatcalcOutputs: - """ - Apply a matrix to a dataset, voxel-by-voxel, to produce a new dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset to be processed. - input_matrix: The matrix to be applied, specified as a .1D file or as\ - an expression in the syntax of 1dmatcalc. - output_dataset: Prefix for the output dataset. - mask: Apply the matrix only to voxels in the mask; other voxels will be\ - set to all zeroes. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmatcalcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMATCALC_METADATA) - cargs = [] - cargs.append("3dmatcalc") - cargs.append("-input") - cargs.append(execution.input_file(input_dataset)) - cargs.append("-matrix") - cargs.append(execution.input_file(input_matrix)) - cargs.append("-prefix") - cargs.append(output_dataset) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - ret = V3dmatcalcOutputs( - root=execution.output_file("."), - output_header=execution.output_file(output_dataset + "+tlrc.HEAD"), - output_brick=execution.output_file(output_dataset + "+tlrc.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmatcalcOutputs", - "V_3DMATCALC_METADATA", - "v_3dmatcalc", -] diff --git a/python/src/niwrap/afni/v_3dmatmult.py b/python/src/niwrap/afni/v_3dmatmult.py deleted file mode 100644 index 657c08180..000000000 --- a/python/src/niwrap/afni/v_3dmatmult.py +++ /dev/null @@ -1,90 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMATMULT_METADATA = Metadata( - id="bea93458f5d83ed6c92115a4be77dc317657f789.boutiques", - name="3dmatmult", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmatmultOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmatmult(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset from the matrix multiplication""" - - -def v_3dmatmult( - input_a: InputPathType, - input_b: InputPathType, - prefix: str, - datum: str | None = None, - verb: float | None = None, - runner: Runner | None = None, -) -> V3dmatmultOutputs: - """ - Multiply AFNI datasets slice-by-slice as matrices. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_a: Specify first (matrix) dataset. - input_b: Specify second (matrix) dataset. - prefix: Specify output dataset prefix. - datum: Specify output data type ('byte', 'short', 'float'). - verb: Specify verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmatmultOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMATMULT_METADATA) - cargs = [] - cargs.append("3dmatmult") - cargs.extend([ - "-inputA", - execution.input_file(input_a) - ]) - cargs.extend([ - "-inputB", - execution.input_file(input_b) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if datum is not None: - cargs.extend([ - "-datum", - datum - ]) - if verb is not None: - cargs.extend([ - "-verb", - str(verb) - ]) - ret = V3dmatmultOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmatmultOutputs", - "V_3DMATMULT_METADATA", - "v_3dmatmult", -] diff --git a/python/src/niwrap/afni/v_3dmaxdisp.py b/python/src/niwrap/afni/v_3dmaxdisp.py deleted file mode 100644 index eb59de959..000000000 --- a/python/src/niwrap/afni/v_3dmaxdisp.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMAXDISP_METADATA = Metadata( - id="a49e0f7320d7281bb7e55504f4a58566bf8a8b49.boutiques", - name="3dmaxdisp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaxdispOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmaxdisp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - displacement_output: OutputPathType - """Results showing average and maximum displacements.""" - - -def v_3dmaxdisp( - inset: InputPathType, - matrix: InputPathType, - verbose: bool = False, - runner: Runner | None = None, -) -> V3dmaxdispOutputs: - """ - Reads in a 3D dataset and a DICOM-based affine matrix to output the average and - maximum displacement applied to the edge voxels of the 3D dataset's automask. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: Input dataset file used to form the mask over which\ - displacements will be computed. - matrix: 3x4 affine transformation matrix file applied to the\ - coordinates of the voxels in the dataset mask. - verbose: Print a few progress reports. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaxdispOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMAXDISP_METADATA) - cargs = [] - cargs.append("3dmaxdisp") - cargs.extend([ - "-inset", - execution.input_file(inset) - ]) - cargs.extend([ - "-matrix", - execution.input_file(matrix) - ]) - if verbose: - cargs.append("-verb") - ret = V3dmaxdispOutputs( - root=execution.output_file("."), - displacement_output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaxdispOutputs", - "V_3DMAXDISP_METADATA", - "v_3dmaxdisp", -] diff --git a/python/src/niwrap/afni/v_3dmaxima.py b/python/src/niwrap/afni/v_3dmaxima.py deleted file mode 100644 index 7d71e712a..000000000 --- a/python/src/niwrap/afni/v_3dmaxima.py +++ /dev/null @@ -1,155 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMAXIMA_METADATA = Metadata( - id="a3267c6a7bbfdd552d053f3793bb3dee1493afcc.boutiques", - name="3dmaxima", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmaximaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmaxima(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_mask: OutputPathType | None - """Output mask dataset with extrema locations""" - - -def v_3dmaxima( - input_dataset: InputPathType, - output_prefix: str | None = None, - threshold: float | None = None, - min_dist: float | None = None, - out_rad: float | None = None, - input_flag: bool = False, - spheres_1_flag: bool = False, - spheres_1to_n_flag: bool = False, - spheres_nto1_flag: bool = False, - neg_ext_flag: bool = False, - true_max_flag: bool = False, - dset_coords_flag: bool = False, - no_text_flag: bool = False, - coords_only_flag: bool = False, - n_style_sort_flag: bool = False, - n_style_weight_ave_flag: bool = False, - debug_level: float | None = None, - help_flag: bool = False, - hist_flag: bool = False, - ver_flag: bool = False, - runner: Runner | None = None, -) -> V3dmaximaOutputs: - """ - Locate extrema in a functional dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Specify input dataset (e.g. func+orig'[7]'). - output_prefix: Prefix for an output mask dataset (e.g. -prefix\ - maskNto1). - threshold: Provides a cutoff value for extrema (e.g. -thresh 17.4). - min_dist: Minimum acceptable distance between extrema in voxels (e.g.\ - -min_dist 4). - out_rad: Set the output radius around extrema voxels in voxel units\ - (e.g. -out_rad 9). - input_flag: Specify input dataset (e.g. -input func+orig'[7]'). - spheres_1_flag: Set all output values to 1. - spheres_1to_n_flag: Output values will range from 1 to N. - spheres_nto1_flag: Output values will range from N to 1. - neg_ext_flag: Search for negative extrema (minima). - true_max_flag: Extrema may not have equal neighbors. - dset_coords_flag: Display output in the dataset orientation. - no_text_flag: Do not display the extrema points as text. - coords_only_flag: Only output coordinates (no text or values). - n_style_sort_flag: Use 'Sort-n-Remove' style (default). - n_style_weight_ave_flag: Use 'Weighted-Average' style. - debug_level: Output extra information to the terminal (e.g. -debug 2). - help_flag: Display help information. - hist_flag: Display module history. - ver_flag: Display version number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmaximaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMAXIMA_METADATA) - cargs = [] - cargs.append("3dmaxima") - cargs.append(execution.input_file(input_dataset)) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if threshold is not None: - cargs.extend([ - "-thresh", - str(threshold) - ]) - if min_dist is not None: - cargs.extend([ - "-min_dist", - str(min_dist) - ]) - if out_rad is not None: - cargs.extend([ - "-out_rad", - str(out_rad) - ]) - if input_flag: - cargs.append("-input") - if spheres_1_flag: - cargs.append("-spheres_1") - if spheres_1to_n_flag: - cargs.append("-spheres_1toN") - if spheres_nto1_flag: - cargs.append("-spheres_Nto1") - if neg_ext_flag: - cargs.append("-neg_ext") - if true_max_flag: - cargs.append("-true_max") - if dset_coords_flag: - cargs.append("-dset_coords") - if no_text_flag: - cargs.append("-no_text") - if coords_only_flag: - cargs.append("-coords_only") - if n_style_sort_flag: - cargs.append("-n_style_sort") - if n_style_weight_ave_flag: - cargs.append("-n_style_weight_ave") - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if help_flag: - cargs.append("-help") - if hist_flag: - cargs.append("-hist") - if ver_flag: - cargs.append("-ver") - ret = V3dmaximaOutputs( - root=execution.output_file("."), - output_mask=execution.output_file(output_prefix + "_mask+orig.[HEAD | BRIK]") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmaximaOutputs", - "V_3DMAXIMA_METADATA", - "v_3dmaxima", -] diff --git a/python/src/niwrap/afni/v_3dmerge.py b/python/src/niwrap/afni/v_3dmerge.py deleted file mode 100644 index 5fc9d8710..000000000 --- a/python/src/niwrap/afni/v_3dmerge.py +++ /dev/null @@ -1,126 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DMERGE_METADATA = Metadata( - id="7f1c2ca1745d4893ae0eaf6d19b9cf828f0a6f25.boutiques", - name="3dmerge", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dmergeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dmerge(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Output dataset file""" - - -def v_3dmerge( - input_files: list[InputPathType], - output_file: str, - blur_fwhm: float | None = None, - threshold: float | None = None, - clust: list[float] | None = None, - dindex: float | None = None, - tindex: float | None = None, - absolute: bool = False, - dxyz: bool = False, - gmean: bool = False, - gmax: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> V3dmergeOutputs: - """ - 3dmerge edits and merges 3D datasets by applying various operations like - thresholding, blurring, clustering, and more. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input dataset files. - output_file: Output dataset prefix. - blur_fwhm: Gaussian blur with FWHM in mm. - threshold: Threshold data to censor the intensities; only valid for\ - 'fith', 'fico', or 'fitt' datasets. - clust: Form clusters with connection distance and clip off data not in\ - clusters of a minimum volume. - dindex: Specify sub-brick #j as the data source. - tindex: Specify sub-brick #k as the threshold source. - absolute: Take absolute values of intensities. - dxyz: Force cluster editing to behave as if all voxel dimensions were\ - set to 1 mm. - gmean: Combine datasets by averaging intensities (default). - gmax: Combine datasets by taking max intensity. - quiet: Reduce the number of messages shown. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dmergeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DMERGE_METADATA) - cargs = [] - cargs.append("3dmerge") - cargs.extend([execution.input_file(f) for f in input_files]) - cargs.extend([ - "-prefix", - output_file - ]) - if blur_fwhm is not None: - cargs.extend([ - "-1blur_fwhm", - str(blur_fwhm) - ]) - if threshold is not None: - cargs.extend([ - "-1thresh", - str(threshold) - ]) - if clust is not None: - cargs.extend([ - "-1clust", - *map(str, clust) - ]) - if dindex is not None: - cargs.extend([ - "-1dindex", - str(dindex) - ]) - if tindex is not None: - cargs.extend([ - "-1tindex", - str(tindex) - ]) - if absolute: - cargs.append("-1abs") - if dxyz: - cargs.append("-dxyz=1") - if gmean: - cargs.append("-gmean") - if gmax: - cargs.append("-gmax") - if quiet: - cargs.append("-quiet") - ret = V3dmergeOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(output_file), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dmergeOutputs", - "V_3DMERGE_METADATA", - "v_3dmerge", -] diff --git a/python/src/niwrap/afni/v_3dnewid.py b/python/src/niwrap/afni/v_3dnewid.py deleted file mode 100644 index 62835ea4d..000000000 --- a/python/src/niwrap/afni/v_3dnewid.py +++ /dev/null @@ -1,92 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DNEWID_METADATA = Metadata( - id="acbbcc60d614fe39bf285beddcf6984090e82ecf.boutiques", - name="3dnewid", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dnewidOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dnewid(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3dnewid( - datasets: list[InputPathType], - fun: float | None = None, - fun11: bool = False, - int_: bool = False, - hash_: str | None = None, - md5: str | None = None, - runner: Runner | None = None, -) -> V3dnewidOutputs: - """ - Assigns a new ID code to a dataset, ensuring internal ID codes remain unique. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input datasets to assign new ID codes. - fun: Generate n randomly generated ID codes. If n is not present, 1 ID\ - code is printed. - fun11: Generate an 11 character ID code for use in scripting. - int_: Generate a random positive integer between 1 million and 1\ - billion. - hash_: Generate a unique hash code of the provided string. The same\ - string produces the same hash code. - md5: Generate the MD5 hash of the provided string. Output should be the\ - same as the -hash output without the prefix and without the + and /\ - char substitutions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dnewidOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DNEWID_METADATA) - cargs = [] - cargs.append("3dnewid") - cargs.extend([execution.input_file(f) for f in datasets]) - if fun is not None: - cargs.extend([ - "-fun", - str(fun) - ]) - if fun11: - cargs.append("-fun11") - if int_: - cargs.append("-int") - if hash_ is not None: - cargs.extend([ - "-hash", - hash_ - ]) - if md5 is not None: - cargs.extend([ - "-MD5", - md5 - ]) - ret = V3dnewidOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dnewidOutputs", - "V_3DNEWID_METADATA", - "v_3dnewid", -] diff --git a/python/src/niwrap/afni/v_3dnvals.py b/python/src/niwrap/afni/v_3dnvals.py deleted file mode 100644 index 669d1a531..000000000 --- a/python/src/niwrap/afni/v_3dnvals.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DNVALS_METADATA = Metadata( - id="d7ef1cfaf0a24a61ba64fc6419199d6758fdcf7a.boutiques", - name="3dnvals", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dnvalsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dnvals(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3dnvals( - datasets: list[InputPathType], - all_flag: bool = False, - verbose_flag: bool = False, - runner: Runner | None = None, -) -> V3dnvalsOutputs: - """ - Tool to print the number of sub-bricks in a 3D dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input 3D dataset(s). - all_flag: Print out all 4 dimensions: Nx, Ny, Nz, Nvals. - verbose_flag: Print the header name of the dataset first. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dnvalsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DNVALS_METADATA) - cargs = [] - cargs.append("3dnvals") - cargs.extend([execution.input_file(f) for f in datasets]) - if all_flag: - cargs.append("-all") - if verbose_flag: - cargs.append("-verbose") - ret = V3dnvalsOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dnvalsOutputs", - "V_3DNVALS_METADATA", - "v_3dnvals", -] diff --git a/python/src/niwrap/afni/v_3dpc.py b/python/src/niwrap/afni/v_3dpc.py deleted file mode 100644 index 093113179..000000000 --- a/python/src/niwrap/afni/v_3dpc.py +++ /dev/null @@ -1,149 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DPC_METADATA = Metadata( - id="987590dc34e13c6e990d98f4bc903e998e6cb77f.boutiques", - name="3dpc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dpcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dpc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Output dataset file""" - output_header: OutputPathType | None - """Output dataset header file""" - output_eig: OutputPathType | None - """File with computed eigenvalues""" - output_vec: OutputPathType | None - """File with all eigen-timeseries""" - output_individual_vec: OutputPathType | None - """File with individual eigenvalue timeseries""" - - -def v_3dpc( - datasets: list[InputPathType], - dmean: bool = False, - vmean: bool = False, - vnorm: bool = False, - normalize: bool = False, - nscale: bool = False, - pcsave: str | None = None, - reduce: list[str] | None = None, - prefix: str | None = None, - dummy_lines: int | None = None, - verbose: bool = False, - quiet: bool = False, - eigonly: bool = False, - float_: bool = False, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dpcOutputs: - """ - Principal Component Analysis of 3D Datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - datasets: Input dataset(s) with sub-brick selector list support. - dmean: Remove the mean from each input brick (across space). - vmean: Remove the mean from each input voxel (across bricks). - vnorm: L2 normalize each input voxel time series. - normalize: L2 normalize each input brick (after mean subtraction). - nscale: Scale the covariance matrix by the number of samples. - pcsave: 'sss' is the number of components to save in the output. - reduce: Compute a dimensionally reduced dataset with top 'r'\ - eigenvalues and write to disk in dataset 'pp'. - prefix: Name for the output dataset. - dummy_lines: Add 'ddd' dummy lines to the top of each *.1D file. - verbose: Print progress reports during the computations. - quiet: Don't print progress reports. - eigonly: Only compute eigenvalues, write them to 'pname'_eig.1D, then\ - stop. - float_: Save eigen-bricks as floats (default = shorts). - mask: Use the 0 sub-brick of dataset 'mset' as a mask indicating which\ - voxels to analyze. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dpcOutputs`). - """ - if reduce is not None and (len(reduce) != 2): - raise ValueError(f"Length of 'reduce' must be 2 but was {len(reduce)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DPC_METADATA) - cargs = [] - cargs.append("3dpc") - cargs.extend([execution.input_file(f) for f in datasets]) - if dmean: - cargs.append("-dmean") - if vmean: - cargs.append("-vmean") - if vnorm: - cargs.append("-vnorm") - if normalize: - cargs.append("-normalize") - if nscale: - cargs.append("-nscale") - if pcsave is not None: - cargs.extend([ - "-pcsave", - pcsave - ]) - if reduce is not None: - cargs.extend([ - "-reduce", - *reduce - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if dummy_lines is not None: - cargs.extend([ - "-1ddum", - str(dummy_lines) - ]) - if verbose: - cargs.append("-verbose") - if quiet: - cargs.append("-quiet") - if eigonly: - cargs.append("-eigonly") - if float_: - cargs.append("-float") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - ret = V3dpcOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - output_header=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - output_eig=execution.output_file(prefix + "_eig.1D") if (prefix is not None) else None, - output_vec=execution.output_file(prefix + "_vec.1D") if (prefix is not None) else None, - output_individual_vec=execution.output_file(prefix + "[NN].1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dpcOutputs", - "V_3DPC_METADATA", - "v_3dpc", -] diff --git a/python/src/niwrap/afni/v_3drefit.py b/python/src/niwrap/afni/v_3drefit.py deleted file mode 100644 index 4e62efe38..000000000 --- a/python/src/niwrap/afni/v_3drefit.py +++ /dev/null @@ -1,189 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DREFIT_METADATA = Metadata( - id="06de6783b355a9c9229965dac381564aa2c28b36.boutiques", - name="3drefit", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3drefitOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3drefit(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output file.""" - - -def v_3drefit( - in_file: InputPathType, - atrcopy: list[str] | None = None, - atrfloat: list[str] | None = None, - atrint: list[str] | None = None, - atrstring: list[str] | None = None, - deoblique: bool = False, - duporigin_file: InputPathType | None = None, - nosaveatr: bool = False, - saveatr: bool = False, - space: typing.Literal["TLRC", "MNI", "ORIG"] | None = None, - xdel: float | None = None, - xorigin: str | None = None, - xyzscale: float | None = None, - ydel: float | None = None, - yorigin: str | None = None, - zdel: float | None = None, - zorigin: str | None = None, - runner: Runner | None = None, -) -> V3drefitOutputs: - """ - Changes some of the information inside a 3D dataset's header. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3drefit. - atrcopy: (file, string). Copy afni header attribute from the given file\ - into the header of the dataset(s) being modified. for more information\ - on afni header attributes, see documentation file readme.attributes.\ - more than one '-atrcopy' option can be used. for afni advanced users\ - only. do not use -atrcopy or -atrstring with other modification\ - options. see also -copyaux. - atrfloat: (a string, a string). Create or modify floating point\ - attributes. the input values may be specified as a single string in\ - quotes or as a 1d filename or string, example '1 0.2 0 0 -0.2 1 0 0 0 0\ - 1 0' or flipz.1d or '1d:1,0.2,2@0,-0.2,1,2@0,2@0,1,0'. - atrint: (a string, a string). Create or modify integer attributes. the\ - input values may be specified as a single string in quotes or as a 1d\ - filename or string, example '1 0 0 0 0 1 0 0 0 0 1 0' or flipz.1d or\ - '1d:1,0,2@0,-0,1,2@0,2@0,1,0'. - atrstring: (a string, a string). Copy the last given string into the\ - dataset(s) being modified, giving it the attribute name given by the\ - last string.to be safe, the last string should be in quotes. - deoblique: Replace current transformation matrix with cardinal matrix. - duporigin_file: Copies the xorigin, yorigin, and zorigin values from\ - the header of the given dataset. - nosaveatr: Opposite of -saveatr. - saveatr: (default) copy the attributes that are known to afni into the\ - dset->dblk structure thereby forcing changes to known attributes to be\ - present in the output. this option only makes sense with -atrcopy. - space: 'tlrc' or 'mni' or 'orig'. Associates the dataset with a\ - specific template type, e.g. tlrc, mni, orig. - xdel: New x voxel dimension in mm. - xorigin: X distance for edge voxel offset. - xyzscale: Scale the size of the dataset voxels by the given factor. - ydel: New y voxel dimension in mm. - yorigin: Y distance for edge voxel offset. - zdel: New z voxel dimension in mm. - zorigin: Z distance for edge voxel offset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3drefitOutputs`). - """ - if atrcopy is not None and (len(atrcopy) != 2): - raise ValueError(f"Length of 'atrcopy' must be 2 but was {len(atrcopy)}") - if atrfloat is not None and (len(atrfloat) != 2): - raise ValueError(f"Length of 'atrfloat' must be 2 but was {len(atrfloat)}") - if atrint is not None and (len(atrint) != 2): - raise ValueError(f"Length of 'atrint' must be 2 but was {len(atrint)}") - if atrstring is not None and (len(atrstring) != 2): - raise ValueError(f"Length of 'atrstring' must be 2 but was {len(atrstring)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DREFIT_METADATA) - cargs = [] - cargs.append("3drefit") - if atrcopy is not None: - cargs.extend([ - "-atrcopy", - *atrcopy - ]) - if atrfloat is not None: - cargs.extend([ - "-atrfloat", - *atrfloat - ]) - if atrint is not None: - cargs.extend([ - "-atrint", - *atrint - ]) - if atrstring is not None: - cargs.extend([ - "-atrstring", - *atrstring - ]) - if deoblique: - cargs.append("-deoblique") - if duporigin_file is not None: - cargs.extend([ - "-duporigin", - execution.input_file(duporigin_file) - ]) - cargs.append(execution.input_file(in_file, mutable=True)) - if nosaveatr: - cargs.append("-nosaveatr") - if saveatr: - cargs.append("-saveatr") - if space is not None: - cargs.extend([ - "-space", - space - ]) - if xdel is not None: - cargs.extend([ - "-xdel", - str(xdel) - ]) - if xorigin is not None: - cargs.extend([ - "-xorigin", - xorigin - ]) - if xyzscale is not None: - cargs.extend([ - "-xyzscale", - str(xyzscale) - ]) - if ydel is not None: - cargs.extend([ - "-ydel", - str(ydel) - ]) - if yorigin is not None: - cargs.extend([ - "-yorigin", - yorigin - ]) - if zdel is not None: - cargs.extend([ - "-zdel", - str(zdel) - ]) - if zorigin is not None: - cargs.extend([ - "-zorigin", - zorigin - ]) - ret = V3drefitOutputs( - root=execution.output_file("."), - out_file=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3drefitOutputs", - "V_3DREFIT_METADATA", - "v_3drefit", -] diff --git a/python/src/niwrap/afni/v_3drename.py b/python/src/niwrap/afni/v_3drename.py deleted file mode 100644 index 4f20e4b5b..000000000 --- a/python/src/niwrap/afni/v_3drename.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DRENAME_METADATA = Metadata( - id="3c508d8f5e6d69689dd267857ef13efbf3693249.boutiques", - name="3drename", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3drenameOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3drename(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_3drename( - old_prefix: str, - new_prefix: str, - runner: Runner | None = None, -) -> V3drenameOutputs: - """ - Tool to rename AFNI datasets by changing the dataset prefix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - old_prefix: Old prefix of the datasets to rename. - new_prefix: New prefix for the datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3drenameOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DRENAME_METADATA) - cargs = [] - cargs.append("3drename") - cargs.append(old_prefix) - cargs.append(new_prefix) - ret = V3drenameOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3drenameOutputs", - "V_3DRENAME_METADATA", - "v_3drename", -] diff --git a/python/src/niwrap/afni/v_3dresample.py b/python/src/niwrap/afni/v_3dresample.py deleted file mode 100644 index 722abef89..000000000 --- a/python/src/niwrap/afni/v_3dresample.py +++ /dev/null @@ -1,104 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DRESAMPLE_METADATA = Metadata( - id="c83781747d57d6711aacd279863d94d024042037.boutiques", - name="3dresample", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dresampleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dresample(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType - """Output image file name.""" - - -def v_3dresample( - in_file: InputPathType, - prefix: str, - master: InputPathType | None = None, - orientation: typing.Literal["AIL", "AIR", "ASL", "ASR", "PIL", "PIR", "PSL", "PSR", "ALI", "ALS", "ARI", "ARS", "PLI", "PLS", "PRI", "PRS", "IAL", "IAR", "IPL", "IPR", "SAL", "SAR", "SPL", "SPR", "ILA", "ILP", "IRA", "IRP", "SLA", "SLP", "SRA", "SRP", "LAI", "LAS", "LPI", "LPS", "RAI", "RAS", "RPI", "RPS", "LIA", "LIP", "LSA", "LSP", "RIA", "RIP", "RSA", "RSP"] | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - resample_mode: typing.Literal["NN", "Li", "Cu", "Bk"] | None = None, - voxel_size: list[float] | None = None, - runner: Runner | None = None, -) -> V3dresampleOutputs: - """ - Resample or reorient an image using AFNI 3dresample command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dresample. - prefix: required prefix for output dataset. - master: Align dataset grid to a reference file. - orientation: New orientation code. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - resample_mode: 'nn' or 'li' or 'cu' or 'bk'. Resampling method from set\ - {"nn", "li", "cu", "bk"}. these are for "nearest neighbor", "linear",\ - "cubic" and "blocky"interpolation, respectively. default is nn. - voxel_size: (a float, a float, a float). Resample to new dx, dy and dz. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dresampleOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DRESAMPLE_METADATA) - cargs = [] - cargs.append("3dresample") - cargs.extend([ - "-inset", - execution.input_file(in_file) - ]) - if master is not None: - cargs.extend([ - "-master", - execution.input_file(master) - ]) - if orientation is not None: - cargs.extend([ - "-orient", - orientation - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if outputtype is not None: - cargs.append(outputtype) - if resample_mode is not None: - cargs.extend([ - "-rmode", - resample_mode - ]) - if voxel_size is not None: - cargs.extend([ - "-dxyz", - *map(str, voxel_size) - ]) - ret = V3dresampleOutputs( - root=execution.output_file("."), - out_file=execution.output_file(prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dresampleOutputs", - "V_3DRESAMPLE_METADATA", - "v_3dresample", -] diff --git a/python/src/niwrap/afni/v_3dretroicor.py b/python/src/niwrap/afni/v_3dretroicor.py deleted file mode 100644 index 560bd2622..000000000 --- a/python/src/niwrap/afni/v_3dretroicor.py +++ /dev/null @@ -1,128 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DRETROICOR_METADATA = Metadata( - id="0b8e3bbd9eaa6f16498a0393158cdcd367502347.boutiques", - name="3dretroicor", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dretroicorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dretroicor(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_dataset: OutputPathType | None - """Corrected dataset output.""" - output_cardiac_phase: OutputPathType | None - """Cardiac phase output file.""" - output_resp_phase: OutputPathType | None - """Respiratory phase output file.""" - - -def v_3dretroicor( - dataset: InputPathType, - ignore: float | None = None, - prefix: str | None = None, - card: InputPathType | None = None, - cardphase: str | None = None, - threshold: float | None = None, - resp: InputPathType | None = None, - respphase: str | None = None, - order: float | None = None, - runner: Runner | None = None, -) -> V3dretroicorOutputs: - """ - Performs Retrospective Image Correction for physiological motion effects using a - modified RETROICOR algorithm. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: 3D+time dataset to process. - ignore: The number of initial timepoints to ignore in the input. These\ - points will be passed through uncorrected. - prefix: Prefix for new, corrected dataset. - card: 1D cardiac data file for cardiac correction. - cardphase: Filename for 1D cardiac phase output. - threshold: Threshold for detection of R-wave peaks in input. Make sure\ - it's above the background noise level; try 3/4 or 4/5 times range plus\ - minimum. - resp: 1D respiratory waveform data for correction. - respphase: Filename for 1D respiratory phase output. - order: The order of the correction. Higher-order terms yield little\ - improvement according to Glover et al. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dretroicorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DRETROICOR_METADATA) - cargs = [] - cargs.append("3dretroicor") - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if card is not None: - cargs.extend([ - "-card", - execution.input_file(card) - ]) - if cardphase is not None: - cargs.extend([ - "-cardphase", - cardphase - ]) - if threshold is not None: - cargs.extend([ - "-threshold", - str(threshold) - ]) - if resp is not None: - cargs.extend([ - "-resp", - execution.input_file(resp) - ]) - if respphase is not None: - cargs.extend([ - "-respphase", - respphase - ]) - if order is not None: - cargs.extend([ - "-order", - str(order) - ]) - cargs.append(execution.input_file(dataset)) - ret = V3dretroicorOutputs( - root=execution.output_file("."), - corrected_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - output_cardiac_phase=execution.output_file(cardphase) if (cardphase is not None) else None, - output_resp_phase=execution.output_file(respphase) if (respphase is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dretroicorOutputs", - "V_3DRETROICOR_METADATA", - "v_3dretroicor", -] diff --git a/python/src/niwrap/afni/v_3drotate.py b/python/src/niwrap/afni/v_3drotate.py deleted file mode 100644 index cdecf43cf..000000000 --- a/python/src/niwrap/afni/v_3drotate.py +++ /dev/null @@ -1,216 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DROTATE_METADATA = Metadata( - id="dae9478b93184d9121e61e24d56f3c564e520ade.boutiques", - name="3drotate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3drotateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3drotate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_head: OutputPathType | None - """Output dataset header file""" - out_brick: OutputPathType | None - """Output dataset brick file""" - - -def v_3drotate( - dataset: InputPathType, - prefix: str | None = None, - verbose: bool = False, - ashift: list[float] | None = None, - bshift: list[float] | None = None, - rotate: list[str] | None = None, - rotparent: InputPathType | None = None, - gridparent: InputPathType | None = None, - matvec_dicom: InputPathType | None = None, - matvec_order: InputPathType | None = None, - matvec_dset: InputPathType | None = None, - dfile: InputPathType | None = None, - v_1_dfile: InputPathType | None = None, - points: bool = False, - origin: list[float] | None = None, - fourier: bool = False, - nn: bool = False, - linear: bool = False, - cubic: bool = False, - quintic: bool = False, - heptic: bool = False, - fourier_nopad: bool = False, - clipit: bool = False, - noclip: bool = False, - zpad: float | None = None, - runner: Runner | None = None, -) -> V3drotateOutputs: - """ - Rotates and/or translates all bricks from an AFNI dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset: Input AFNI dataset, may contain a sub-brick selector list. - prefix: Sets the output dataset prefix name. - verbose: Prints out progress reports (to stderr). - ashift: Shifts the dataset by specified distances (dx, dy, dz) in mm in\ - x, y, z directions respectively, AFTER rotation. - bshift: Shifts the dataset by specified distances (dx, dy, dz) in mm in\ - x, y, z directions respectively, BEFORE rotation. - rotate: Specifies the 3D rotation angles (th1, th2, th3) about certain\ - axes. - rotparent: Rotation and translation should be taken from the first\ - 3dvolreg transformation found in the header of dataset 'rset'. - gridparent: Output dataset should be shifted to match the grid of\ - dataset 'gset'. Can only be used with -rotparent. - matvec_dicom: Rotation and translation should be read from DICOM file\ - 'mfile'. - matvec_order: Rotation and translation should be read from file 'mfile'\ - with dataset coordinate order. - matvec_dset: Rotation and translation should be read from the .HEAD\ - file of dataset 'mset' created by 3dTagalign. - dfile: Reads movement parameters for each sub-brick from an ASCII file\ - 'dname'. - v_1_dfile: Reads movement parameters for each sub-brick from a 1D ASCII\ - file 'dname'. - points: Specifies that (x,y,z) points are to be rotated instead of a\ - dataset. - origin: Specifies the rotation origin point (xo, yo, zo). - fourier: Use Fourier interpolation method during transformation. - nn: Use nearest neighbor interpolation method during transformation. - linear: Use linear interpolation (1st order polynomial) during\ - transformation. - cubic: Use cubic interpolation (3rd order polynomial) during\ - transformation. - quintic: Use quintic interpolation (5th order Lagrange polynomial)\ - during transformation. - heptic: Use heptic interpolation (7th order Lagrange polynomial) during\ - transformation. - fourier_nopad: Use the Fourier method WITHOUT padding. - clipit: Clip results to input brick range [default option]. - noclip: Do not clip results to input brick range. - zpad: Zero pad around the edges by 'n' voxels during rotations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3drotateOutputs`). - """ - if rotate is not None and (len(rotate) != 3): - raise ValueError(f"Length of 'rotate' must be 3 but was {len(rotate)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DROTATE_METADATA) - cargs = [] - cargs.append("3drotate") - cargs.append(execution.input_file(dataset)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if verbose: - cargs.append("-verbose") - if ashift is not None: - cargs.extend([ - "-ashift", - *map(str, ashift) - ]) - if bshift is not None: - cargs.extend([ - "-bshift", - *map(str, bshift) - ]) - if rotate is not None: - cargs.extend([ - "-rotate", - *rotate - ]) - if rotparent is not None: - cargs.extend([ - "-rotparent", - execution.input_file(rotparent) - ]) - if gridparent is not None: - cargs.extend([ - "-gridparent", - execution.input_file(gridparent) - ]) - if matvec_dicom is not None: - cargs.extend([ - "-matvec_dicom", - execution.input_file(matvec_dicom) - ]) - if matvec_order is not None: - cargs.extend([ - "-matvec_order", - execution.input_file(matvec_order) - ]) - if matvec_dset is not None: - cargs.extend([ - "-matvec_dset", - execution.input_file(matvec_dset) - ]) - if dfile is not None: - cargs.extend([ - "-dfile", - execution.input_file(dfile) - ]) - if v_1_dfile is not None: - cargs.extend([ - "-1Dfile", - execution.input_file(v_1_dfile) - ]) - if points: - cargs.append("-points") - if origin is not None: - cargs.extend([ - "-origin", - *map(str, origin) - ]) - if fourier: - cargs.append("-Fourier") - if nn: - cargs.append("-NN") - if linear: - cargs.append("-linear") - if cubic: - cargs.append("-cubic") - if quintic: - cargs.append("-quintic") - if heptic: - cargs.append("-heptic") - if fourier_nopad: - cargs.append("-Fourier_nopad") - if clipit: - cargs.append("-clipit") - if noclip: - cargs.append("-noclip") - if zpad is not None: - cargs.extend([ - "-zpad", - str(zpad) - ]) - ret = V3drotateOutputs( - root=execution.output_file("."), - out_head=execution.output_file(prefix + "+orig.HEAD") if (prefix is not None) else None, - out_brick=execution.output_file(prefix + "+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3drotateOutputs", - "V_3DROTATE_METADATA", - "v_3drotate", -] diff --git a/python/src/niwrap/afni/v_3dsvm.py b/python/src/niwrap/afni/v_3dsvm.py deleted file mode 100644 index a8ab09a0f..000000000 --- a/python/src/niwrap/afni/v_3dsvm.py +++ /dev/null @@ -1,243 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DSVM_METADATA = Metadata( - id="561addc870b41a8529b3ab4135131a6bc7b9089a.boutiques", - name="3dsvm", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dsvmOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dsvm(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_model: OutputPathType - """Output model file in .1D format.""" - out_alpha: OutputPathType - """Output alphas file in .1D format.""" - out_bucket: OutputPathType - """Output bucket file in .1D format.""" - out_predictions: OutputPathType - """Output predictions file in .1D format.""" - - -def v_3dsvm( - model: str, - train_vol: InputPathType | None = None, - train_labels: InputPathType | None = None, - mask: InputPathType | None = None, - no_model_mask: bool = False, - alpha: str | None = None, - bucket: str | None = None, - type_: typing.Literal["classification", "regression"] | None = None, - c_value: float | None = None, - epsilon: float | None = None, - kernel: typing.Literal["linear", "polynomial", "rbf", "sigmoid"] | None = None, - d_value: float | None = None, - gamma: float | None = None, - s_value: float | None = None, - r_value: float | None = None, - max_iterations: float | None = None, - wout: bool = False, - test_vol: InputPathType | None = None, - predictions: str | None = None, - classout: bool = False, - nopred_censored: bool = False, - nodetrend: bool = False, - nopred_scale: bool = False, - test_labels: InputPathType | None = None, - multiclass: typing.Literal["DAG", "vote"] | None = None, - help_: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> V3dsvmOutputs: - """ - Support vector machine analysis of brain data using the SVM-light package. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - model: The basename for the model brik containing the SVM model during\ - training or testing. - train_vol: A 3D+t AFNI brik dataset to be used for training. - train_labels: Filename of class category .1D labels corresponding to\ - the stimulus paradigm for the training data set. - mask: Specify a mask dataset to only perform the analysis on non-zero\ - mask voxels. - no_model_mask: Flag to enable the omission of a mask file. Required if\ - '-mask' is not used. - alpha: Write the alphas to a specified .1D file. - bucket: Outputs the sum of weighted linear support vectors written out\ - to a functional (fim) brik file. - type_: Specify type: classification (default) or regression. - c_value: Control SVM model complexity (C value). - epsilon: Specify epsilon for regression. - kernel: Specify type of kernel function. - d_value: D parameter in polynomial kernel. - gamma: Gamma parameter in rbf kernel. - s_value: S parameter in sigmoid/poly kernel. - r_value: R parameter in sigmoid/poly kernel. - max_iterations: Specify the maximum number of iterations for the\ - optimization. Default is 1 million. - wout: Flag to output sum of weighted linear support vectors to the\ - bucket file. - test_vol: A 3D or 3D+t AFNI brik dataset to be used for testing. - predictions: Basename for .1D prediction files. - classout: Flag to specify that prediction files should be\ - integer-valued, corresponding to class category decisions. - nopred_censored: Do not write predicted values for censored time-points\ - to predictions file. - nodetrend: Flag to specify that prediction files should NOT be linearly\ - detrended. - nopred_scale: Do not scale predictions. Values below 0.0 correspond to\ - (class A) and values above 0.0 to (class B). - test_labels: Filename of 'true' class category .1D labels for the test\ - dataset. - multiclass: Specify the multiclass algorithm for classification. - help_: Print help message. - version: Print version history. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dsvmOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DSVM_METADATA) - cargs = [] - cargs.append("3dsvm") - if train_vol is not None: - cargs.extend([ - "-trainvol", - execution.input_file(train_vol) - ]) - if train_labels is not None: - cargs.extend([ - "-trainlabels", - execution.input_file(train_labels) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if no_model_mask: - cargs.append("-nomodelmask") - cargs.extend([ - "-model", - model - ]) - if alpha is not None: - cargs.extend([ - "-alpha", - alpha - ]) - if bucket is not None: - cargs.extend([ - "-bucket", - bucket - ]) - if type_ is not None: - cargs.extend([ - "-type", - type_ - ]) - if c_value is not None: - cargs.extend([ - "-c", - str(c_value) - ]) - if epsilon is not None: - cargs.extend([ - "-e", - str(epsilon) - ]) - if kernel is not None: - cargs.extend([ - "-kernel", - kernel - ]) - if d_value is not None: - cargs.extend([ - "-d", - str(d_value) - ]) - if gamma is not None: - cargs.extend([ - "-g", - str(gamma) - ]) - if s_value is not None: - cargs.extend([ - "-s", - str(s_value) - ]) - if r_value is not None: - cargs.extend([ - "-r", - str(r_value) - ]) - if max_iterations is not None: - cargs.extend([ - "-max_iterations", - str(max_iterations) - ]) - if wout: - cargs.append("-wout") - if test_vol is not None: - cargs.extend([ - "-testvol", - execution.input_file(test_vol) - ]) - if predictions is not None: - cargs.extend([ - "-predictions", - predictions - ]) - if classout: - cargs.append("-classout") - if nopred_censored: - cargs.append("-nopredcensored") - if nodetrend: - cargs.append("-nodetrend") - if nopred_scale: - cargs.append("-nopredscale") - if test_labels is not None: - cargs.extend([ - "-testlabels", - execution.input_file(test_labels) - ]) - if multiclass is not None: - cargs.extend([ - "-multiclass", - multiclass - ]) - if help_: - cargs.append("-help") - if version: - cargs.append("-version") - ret = V3dsvmOutputs( - root=execution.output_file("."), - out_model=execution.output_file("model_{output}.1D"), - out_alpha=execution.output_file("alpha_{output}.1D"), - out_bucket=execution.output_file("bucket_{output}.1D"), - out_predictions=execution.output_file("predictions_{output}.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dsvmOutputs", - "V_3DSVM_METADATA", - "v_3dsvm", -] diff --git a/python/src/niwrap/afni/v_3dsvm_linpredict.py b/python/src/niwrap/afni/v_3dsvm_linpredict.py deleted file mode 100644 index c1e81545d..000000000 --- a/python/src/niwrap/afni/v_3dsvm_linpredict.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DSVM_LINPREDICT_METADATA = Metadata( - id="14a78538db163a43a9541ef88dc8c18dcef61d1a.boutiques", - name="3dsvm_linpredict", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dsvmLinpredictOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dsvm_linpredict(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - stdout_output: OutputPathType - """The result is a number printed to stdout""" - - -def v_3dsvm_linpredict( - weight_vector: InputPathType, - input_dataset: str, - mask_dataset: InputPathType | None = None, - runner: Runner | None = None, -) -> V3dsvmLinpredictOutputs: - """ - Linear prediction for weights from 3dsvm. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - weight_vector: Weight vector dataset. - input_dataset: Input dataset, potentially with sub-brick and/or\ - sub-range selectors. - mask_dataset: Dataset to be used as a mask. Only voxels with nonzero\ - values in 'mset' will be averaged from 'dataset'. The mask dataset and\ - the input dataset must have the same number of voxels. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dsvmLinpredictOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DSVM_LINPREDICT_METADATA) - cargs = [] - cargs.append("3dsvm_linpredict") - if mask_dataset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dataset) - ]) - cargs.append(execution.input_file(weight_vector)) - cargs.append(input_dataset) - ret = V3dsvmLinpredictOutputs( - root=execution.output_file("."), - stdout_output=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dsvmLinpredictOutputs", - "V_3DSVM_LINPREDICT_METADATA", - "v_3dsvm_linpredict", -] diff --git a/python/src/niwrap/afni/v_3dto_xdataset.py b/python/src/niwrap/afni/v_3dto_xdataset.py deleted file mode 100644 index d1e76b924..000000000 --- a/python/src/niwrap/afni/v_3dto_xdataset.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DTO_XDATASET_METADATA = Metadata( - id="659cded4451a7073e735922b9f1fad33b442c502.boutiques", - name="3dtoXdataset", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dtoXdatasetOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dto_xdataset(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_sdat: OutputPathType - """Output file in .sdat format""" - - -def v_3dto_xdataset( - prefix: str, - mask: InputPathType, - input_files: list[InputPathType], - runner: Runner | None = None, -) -> V3dtoXdatasetOutputs: - """ - Convert input datasets to the format needed for 3dClustSimX. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for the output file. - mask: Mask dataset file. - input_files: Input datasets to be converted. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dtoXdatasetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DTO_XDATASET_METADATA) - cargs = [] - cargs.append("3dtoXdataset") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append(execution.input_file(mask)) - cargs.extend([execution.input_file(f) for f in input_files]) - ret = V3dtoXdatasetOutputs( - root=execution.output_file("."), - output_sdat=execution.output_file(prefix + ".sdat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dtoXdatasetOutputs", - "V_3DTO_XDATASET_METADATA", - "v_3dto_xdataset", -] diff --git a/python/src/niwrap/afni/v_3dttest__.py b/python/src/niwrap/afni/v_3dttest__.py deleted file mode 100644 index 35959c7b9..000000000 --- a/python/src/niwrap/afni/v_3dttest__.py +++ /dev/null @@ -1,205 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DTTEST___METADATA = Metadata( - id="9816ba0be883f397c48e16a5a699629ad3d438ae.boutiques", - name="3dttest++", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dttestOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dttest__(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_file: OutputPathType | None - """Main output dataset""" - residuals: OutputPathType | None - """Output residuals dataset""" - - -def v_3dttest__( - set_a: list[str], - set_b: list[str] | None = None, - set_a_long: list[str] | None = None, - set_b_long: list[str] | None = None, - covariates: InputPathType | None = None, - label_a: str | None = None, - label_b: str | None = None, - setweight_a: InputPathType | None = None, - setweight_b: InputPathType | None = None, - prefix: str | None = None, - resid: str | None = None, - paired: bool = False, - unpooled: bool = False, - mask: InputPathType | None = None, - exblur: int | None = None, - randomsign: bool = False, - permute: bool = False, - etac: bool = False, - etac_blur: list[float] | None = None, - etac_opt: list[str] | None = None, - seed: float | None = None, - runner: Runner | None = None, -) -> V3dttestOutputs: - """ - Gosset (Student) t-test of sets of 3D datasets in AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - set_a: Set A in short form, e.g., 'a+tlrc[3]' b+tlrc[3] ...'. - set_b: Set B in short form, e.g., 'x+tlrc[3]' y+tlrc[3] ...'. - set_a_long: Specify an overall name for the set of datasets (Long\ - form). Example: -setA Green sub001 a+tlrc[3] sub002 b+tlrc[3] ... - set_b_long: Specify an overall name for the set of datasets (Long\ - form). Example: -setB Blue sub001 x+tlrc[3] sub002 y+tlrc[3] ... - covariates: File containing covariates. - label_a: Label for the set (for Set A). Limited to 12 characters. - label_b: Label for the set (for Set B). Limited to 12 characters. - setweight_a: File with voxel-wise weights for -setA datasets. - setweight_b: File with voxel-wise weights for -setB datasets. - prefix: Output the prefix name of the dataset result. For surface-based\ - datasets, use -prefix p.niml.dset or -prefix p.gii.dset. - resid: Residuals will be output into a dataset with the given prefix. - paired: Specify to use a paired-sample t-test to compare setA and setB.\ - Both sets must have the same cardinality. - unpooled: Specify separate variance estimates for setA and setB (not\ - pooled together). - mask: Set mask for dataset analysis. - exblur: Add extra Gaussian blurring kernel FWHM (mm). Example: -exblur\ - 6. - randomsign: Randomize signs of datasets. Used with output from -resid\ - to generate null hypothesis statistics. - permute: With -randomsign, adds inter-set permutation to randomization\ - when both sets are used. - etac: Apply the Equitable Thresholding And Clustering (ETAC) method for\ - thresholding results. - etac_blur: List of multiple levels of spatial blurring for ETAC.\ - Example: -ETAC_blur 4 6. - etac_opt: Specify options for ETAC. Example: -ETAC_opt\ - NN=2:sid=2:hpow=0,2:pthr=0.01,0.005,0.002,0.01:name=Fred. - seed: Random number seed for -randomsign and -permute/ETAC. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dttestOutputs`). - """ - if exblur is not None and not (0 <= exblur <= 100): - raise ValueError(f"'exblur' must be between 0 <= x <= 100 but was {exblur}") - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DTTEST___METADATA) - cargs = [] - cargs.append("3dttest++") - cargs.extend([ - "-setA", - *set_a - ]) - if set_b is not None: - cargs.extend([ - "-setB", - *set_b - ]) - if set_a_long is not None: - cargs.extend([ - "-setA", - *set_a_long - ]) - if set_b_long is not None: - cargs.extend([ - "-setB", - *set_b_long - ]) - if covariates is not None: - cargs.extend([ - "-covariates", - execution.input_file(covariates) - ]) - if label_a is not None: - cargs.extend([ - "-labelA", - label_a - ]) - if label_b is not None: - cargs.extend([ - "-labelB", - label_b - ]) - if setweight_a is not None: - cargs.extend([ - "-setweightA", - execution.input_file(setweight_a) - ]) - if setweight_b is not None: - cargs.extend([ - "-setweightB", - execution.input_file(setweight_b) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if resid is not None: - cargs.extend([ - "-resid", - resid - ]) - if paired: - cargs.append("-paired") - if unpooled: - cargs.append("-unpooled") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if exblur is not None: - cargs.extend([ - "-exblur", - str(exblur) - ]) - if randomsign: - cargs.append("-randomsign") - if permute: - cargs.append("-permute") - if etac: - cargs.append("-ETAC") - if etac_blur is not None: - cargs.extend([ - "-ETAC_blur", - *map(str, etac_blur) - ]) - if etac_opt is not None: - cargs.extend([ - "-ETAC_opt", - *etac_opt - ]) - if seed is not None: - cargs.extend([ - "-seed", - str(seed) - ]) - ret = V3dttestOutputs( - root=execution.output_file("."), - out_file=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - residuals=execution.output_file(resid + ".nii.gz") if (resid is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dttestOutputs", - "V_3DTTEST___METADATA", - "v_3dttest__", -] diff --git a/python/src/niwrap/afni/v_3dvolreg.py b/python/src/niwrap/afni/v_3dvolreg.py deleted file mode 100644 index 4f6d037d8..000000000 --- a/python/src/niwrap/afni/v_3dvolreg.py +++ /dev/null @@ -1,142 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_3DVOLREG_METADATA = Metadata( - id="087e3e120bd964570162eccb6ea11ca03ce6e7d4.boutiques", - name="3dvolreg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V3dvolregOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_3dvolreg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - md1d_file: OutputPathType - """Max displacement output file.""" - oned_file: OutputPathType - """1d movement parameters output file.""" - oned_matrix_save: OutputPathType - """Save the matrix transformation.""" - out_file: OutputPathType - """Output image file name.""" - md1d_file_: OutputPathType - """Max displacement info file.""" - oned_file_: OutputPathType - """Movement parameters info file.""" - oned_matrix_save_: OutputPathType - """Matrix transformation from base to input.""" - out_file_: OutputPathType - """Registered file.""" - - -def v_3dvolreg( - in_file: InputPathType, - basefile: InputPathType | None = None, - copyorigin: bool = False, - in_weight_volume: list[str] | None = None, - in_weight_volume_2: InputPathType | None = None, - interp: typing.Literal["Fourier", "cubic", "heptic", "quintic", "linear"] | None = None, - num_threads: int | None = None, - outputtype: typing.Literal["NIFTI", "AFNI", "NIFTI_GZ"] | None = None, - timeshift: bool = False, - verbose: bool = False, - zpad: int | None = None, - runner: Runner | None = None, -) -> V3dvolregOutputs: - """ - Register input volumes to a base volume using AFNI 3dvolreg command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_file: Input file to 3dvolreg. - basefile: Base file for registration. - copyorigin: Copy base file origin coords to output. - in_weight_volume: (file or string, an integer) or file or string.\ - Weights for each voxel specified by a file with an optional volume\ - number (defaults to 0). - in_weight_volume_2: (file or string, an integer) or file or string.\ - Weights for each voxel specified by a file with an optional volume\ - number (defaults to 0). - interp: 'fourier' or 'cubic' or 'heptic' or 'quintic' or 'linear'.\ - Spatial interpolation methods [default = heptic]. - num_threads: Set number of threads. - outputtype: 'nifti' or 'afni' or 'nifti_gz'. Afni output filetype. - timeshift: Time shift to mean slice time offset. - verbose: More detailed description of the process. - zpad: Zeropad around the edges by 'n' voxels during rotations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V3dvolregOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_3DVOLREG_METADATA) - cargs = [] - cargs.append("3dvolreg") - if basefile is not None: - cargs.extend([ - "-base", - execution.input_file(basefile) - ]) - if copyorigin: - cargs.append("-twodup") - cargs.append(execution.input_file(in_file)) - if in_weight_volume is not None: - cargs.extend([ - "-weight '", - *in_weight_volume - ]) - if in_weight_volume_2 is not None: - cargs.extend([ - "-weight '", - execution.input_file(in_weight_volume_2) - ]) - if interp is not None: - cargs.extend([ - "-", - interp - ]) - if num_threads is not None: - cargs.append(str(num_threads)) - if outputtype is not None: - cargs.append(outputtype) - if timeshift: - cargs.append("-tshift 0") - if verbose: - cargs.append("-verbose") - if zpad is not None: - cargs.extend([ - "-zpad", - str(zpad) - ]) - ret = V3dvolregOutputs( - root=execution.output_file("."), - md1d_file=execution.output_file(pathlib.Path(in_file).name + "_md.1D"), - oned_file=execution.output_file(pathlib.Path(in_file).name + ".1D"), - oned_matrix_save=execution.output_file(pathlib.Path(in_file).name + ".aff12.1D"), - out_file=execution.output_file(pathlib.Path(in_file).name + "_volreg"), - md1d_file_=execution.output_file("md1d_file"), - oned_file_=execution.output_file("oned_file"), - oned_matrix_save_=execution.output_file("oned_matrix_save"), - out_file_=execution.output_file("out_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V3dvolregOutputs", - "V_3DVOLREG_METADATA", - "v_3dvolreg", -] diff --git a/python/src/niwrap/afni/v_4swap.py b/python/src/niwrap/afni/v_4swap.py deleted file mode 100644 index 28ffaa098..000000000 --- a/python/src/niwrap/afni/v_4swap.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V_4SWAP_METADATA = Metadata( - id="a08537876585898a9e19a9d024e3c6d15fdcf425.boutiques", - name="4swap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V4swapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v_4swap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v_4swap( - files: list[InputPathType], - quiet: bool = False, - runner: Runner | None = None, -) -> V4swapOutputs: - """ - Swaps byte quadruples on the listed files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: List of files to process. - quiet: Work quietly; suppress output messages. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V4swapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V_4SWAP_METADATA) - cargs = [] - cargs.append("4swap") - cargs.extend([execution.input_file(f) for f in files]) - if quiet: - cargs.append("-q") - ret = V4swapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V4swapOutputs", - "V_4SWAP_METADATA", - "v_4swap", -] diff --git a/python/src/niwrap/afni/v__1d_diff_mag.py b/python/src/niwrap/afni/v__1d_diff_mag.py deleted file mode 100644 index 6f9f7d791..000000000 --- a/python/src/niwrap/afni/v__1d_diff_mag.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__1D_DIFF_MAG_METADATA = Metadata( - id="ccbd06979574a6fa073f5c90b06eebc4b39093fe.boutiques", - name="@1dDiffMag", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V1dDiffMagOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__1d_diff_mag(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - result_stdout: OutputPathType - """The result as a single number displayed on stdout""" - - -def v__1d_diff_mag( - infile: InputPathType, - runner: Runner | None = None, -) -> V1dDiffMagOutputs: - """ - Computes a magnitude estimate of the first differences of a 1D file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: 1D input file to compute the magnitude estimate of the first\ - differences. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V1dDiffMagOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__1D_DIFF_MAG_METADATA) - cargs = [] - cargs.append("@1dDiffMag") - cargs.append(execution.input_file(infile)) - ret = V1dDiffMagOutputs( - root=execution.output_file("."), - result_stdout=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V1dDiffMagOutputs", - "V__1D_DIFF_MAG_METADATA", - "v__1d_diff_mag", -] diff --git a/python/src/niwrap/afni/v__2dwarper.py b/python/src/niwrap/afni/v__2dwarper.py deleted file mode 100644 index 7bb25f1b1..000000000 --- a/python/src/niwrap/afni/v__2dwarper.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__2DWARPER_METADATA = Metadata( - id="84ef515295a9aa7008fa07f5cd21d7b371f8a9f0.boutiques", - name="@2dwarper", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2dwarperOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__2dwarper(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Warped output image from the dataset""" - - -def v__2dwarper( - input_dataset: InputPathType, - runner: Runner | None = None, -) -> V2dwarperOutputs: - """ - 2D image warping tool. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset (e.g., image to be warped). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2dwarperOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__2DWARPER_METADATA) - cargs = [] - cargs.append("@2dwarper") - cargs.append(execution.input_file(input_dataset)) - ret = V2dwarperOutputs( - root=execution.output_file("."), - output_file=execution.output_file("warped_output"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2dwarperOutputs", - "V__2DWARPER_METADATA", - "v__2dwarper", -] diff --git a/python/src/niwrap/afni/v__2dwarper_allin.py b/python/src/niwrap/afni/v__2dwarper_allin.py deleted file mode 100644 index b731d38a8..000000000 --- a/python/src/niwrap/afni/v__2dwarper_allin.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__2DWARPER_ALLIN_METADATA = Metadata( - id="025f4fd73449077a7f27f71bce48a9a34a8bfe9d.boutiques", - name="@2dwarper.Allin", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V2dwarperAllinOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__2dwarper_allin(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - reg_output: OutputPathType | None - """Output registered dataset""" - param_files: OutputPathType | None - """Output registration parameter files""" - - -def v__2dwarper_allin( - input_prefix: str, - mask_prefix: str | None = None, - output_prefix: str | None = None, - runner: Runner | None = None, -) -> V2dwarperAllinOutputs: - """ - Perform 2D registration on each slice of a 3D+time dataset, and combine the - results. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_prefix: Prefix for the input 3D+time dataset. - mask_prefix: Prefix of an existing mask dataset. - output_prefix: Prefix for output datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V2dwarperAllinOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__2DWARPER_ALLIN_METADATA) - cargs = [] - cargs.append("@2dwarper.Allin") - cargs.append(input_prefix) - if mask_prefix is not None: - cargs.extend([ - "-mask", - mask_prefix - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - ret = V2dwarperAllinOutputs( - root=execution.output_file("."), - reg_output=execution.output_file(output_prefix + "_reg+orig.HEAD") if (output_prefix is not None) else None, - param_files=execution.output_file(output_prefix + "_param_*.1D") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V2dwarperAllinOutputs", - "V__2DWARPER_ALLIN_METADATA", - "v__2dwarper_allin", -] diff --git a/python/src/niwrap/afni/v__4_daverage.py b/python/src/niwrap/afni/v__4_daverage.py deleted file mode 100644 index c620a30a0..000000000 --- a/python/src/niwrap/afni/v__4_daverage.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__4_DAVERAGE_METADATA = Metadata( - id="539f6118b726725db3041382540750353fc522e5.boutiques", - name="@4Daverage", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class V4DaverageOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__4_daverage(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__4_daverage( - output_prefix: str, - runner: Runner | None = None, -) -> V4DaverageOutputs: - """ - Script for computing average 3D+time bricks using 3Dcalc. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - output_prefix: Prefix for the output 3D+t brick. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `V4DaverageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__4_DAVERAGE_METADATA) - cargs = [] - cargs.append("@4Daverage") - cargs.append(output_prefix) - cargs.append("[INPUT_FILES...]") - ret = V4DaverageOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "V4DaverageOutputs", - "V__4_DAVERAGE_METADATA", - "v__4_daverage", -] diff --git a/python/src/niwrap/afni/v__add_edge.py b/python/src/niwrap/afni/v__add_edge.py deleted file mode 100644 index 0296d5e60..000000000 --- a/python/src/niwrap/afni/v__add_edge.py +++ /dev/null @@ -1,150 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ADD_EDGE_METADATA = Metadata( - id="cc6bd7e8e964e6139e3ad4af63985ce234097620.boutiques", - name="@AddEdge", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAddEdgeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__add_edge(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - dset_nn_ec: OutputPathType - """Edge composite image of dataset with its own edges""" - base_dset_dset_nn_ec: OutputPathType - """Edge composite image of base dataset together with the edges of the input - dset_nn dataset""" - base_dset_e3: OutputPathType - """Edge-only datasets - used in single edge display option""" - dset_nn_e3: OutputPathType - """Edge-only input datasets - used in single edge display option""" - - -def v__add_edge( - input_files: list[InputPathType], - examine_list: str | None = None, - ax_mont: str | None = None, - ax_geom: str | None = None, - sag_geom: str | None = None, - layout_file: str | None = None, - no_layout: bool = False, - edge_percentile: int | None = None, - single_edge: bool = False, - opacity: int | None = None, - keep_temp: bool = False, - no_deoblique: bool = False, - auto_record: bool = False, - auto: bool = False, - no_auto: bool = False, - runner: Runner | None = None, -) -> VAddEdgeOutputs: - """ - A script to create composite edge-enhanced datasets and drive the AFNI interface - to display the results. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input datasets. - examine_list: Use list of paired datasets from file. - ax_mont: Axial montage string (default='2x2:24'). - ax_geom: Axial image window geometry (default='777x702+433+334'). - sag_geom: Sagittal image window geometry (default='540x360+4+436'). - layout_file: Use AFNI layout file for display. - no_layout: Do not use layout. Use AFNI as it is open. - edge_percentile: Specify edge threshold value (default=30%). - single_edge: Show only a single edge in composite image. - opacity: Set opacity of overlay (default=9 opaque). - keep_temp: Do not remove temporary files. - no_deoblique: Do not deoblique any data to show overlap. - auto_record: Save JPEG files of current slices without prompting. - auto: Closes old AFNI sessions and relaunches a new one ready to listen\ - to @AddEdge in review mode. - no_auto: Opposite of -auto. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAddEdgeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ADD_EDGE_METADATA) - cargs = [] - cargs.append("@AddEdge") - cargs.extend([execution.input_file(f) for f in input_files]) - if examine_list is not None: - cargs.extend([ - "-examinelist", - examine_list - ]) - if ax_mont is not None: - cargs.extend([ - "-ax_mont", - ax_mont - ]) - if ax_geom is not None: - cargs.extend([ - "-ax_geom", - ax_geom - ]) - if sag_geom is not None: - cargs.extend([ - "-sag_geom", - sag_geom - ]) - if layout_file is not None: - cargs.extend([ - "-layout", - layout_file - ]) - if no_layout: - cargs.append("-no_layout") - if edge_percentile is not None: - cargs.extend([ - "-edge_percentile", - str(edge_percentile) - ]) - if single_edge: - cargs.append("-single_edge") - if opacity is not None: - cargs.extend([ - "-opa", - str(opacity) - ]) - if keep_temp: - cargs.append("-keep_temp") - if no_deoblique: - cargs.append("-no_deoblique") - if auto_record: - cargs.append("-auto_record") - if auto: - cargs.append("-auto") - if no_auto: - cargs.append("-no_auto") - ret = VAddEdgeOutputs( - root=execution.output_file("."), - dset_nn_ec=execution.output_file("dset_nn_ec"), - base_dset_dset_nn_ec=execution.output_file("base_dset_dset_nn_ec"), - base_dset_e3=execution.output_file("base_dset_e3"), - dset_nn_e3=execution.output_file("dset_nn_e3"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAddEdgeOutputs", - "V__ADD_EDGE_METADATA", - "v__add_edge", -] diff --git a/python/src/niwrap/afni/v__afni_env.py b/python/src/niwrap/afni/v__afni_env.py deleted file mode 100644 index 7458126d8..000000000 --- a/python/src/niwrap/afni/v__afni_env.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_ENV_METADATA = Metadata( - id="16f129198419674aa6c4039e01dd5d599fafb94f.boutiques", - name="@AfniEnv", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniEnvOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_env(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__afni_env( - set_flag: list[str] | None = None, - unset_flag: str | None = None, - get_flag: str | None = None, - help_flag: bool = False, - help_web_flag_alias: bool = False, - help_view_flag_alias: bool = False, - all_opts_flag: bool = False, - help_find_flag: str | None = None, - runner: Runner | None = None, -) -> VAfniEnvOutputs: - """ - Script to set or unset an AFNI environment variable in your .afnirc file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - set_flag: Set environment variable NAME to value VALUE. - unset_flag: Unset environment variable NAME. - get_flag: Get the value of environment variable NAME. - help_flag: Display the help message for @AfniEnv script. - help_web_flag_alias: Same as -h_web. - help_view_flag_alias: Same as -h_view. - all_opts_flag: List all of the options for this script. - help_find_flag: Search for lines containing WORD in -help output.\ - Search is approximate. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniEnvOutputs`). - """ - if set_flag is not None and (len(set_flag) != 2): - raise ValueError(f"Length of 'set_flag' must be 2 but was {len(set_flag)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_ENV_METADATA) - cargs = [] - cargs.append("@AfniEnv") - if set_flag is not None: - cargs.extend([ - "-set", - *set_flag - ]) - if unset_flag is not None: - cargs.extend([ - "-unset", - unset_flag - ]) - if get_flag is not None: - cargs.extend([ - "-get", - get_flag - ]) - if help_flag: - cargs.append("-help") - if help_web_flag_alias: - cargs.append("-hweb") - if help_view_flag_alias: - cargs.append("-hview") - if all_opts_flag: - cargs.append("-all_opts") - if help_find_flag is not None: - cargs.extend([ - "-h_find", - help_find_flag - ]) - ret = VAfniEnvOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniEnvOutputs", - "V__AFNI_ENV_METADATA", - "v__afni_env", -] diff --git a/python/src/niwrap/afni/v__afni_orient2_raimap.py b/python/src/niwrap/afni/v__afni_orient2_raimap.py deleted file mode 100644 index 4f65fb8ba..000000000 --- a/python/src/niwrap/afni/v__afni_orient2_raimap.py +++ /dev/null @@ -1,58 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_ORIENT2_RAIMAP_METADATA = Metadata( - id="ade1258888a2ab4d7104b72e6f2921d74eaf281c.boutiques", - name="@AfniOrient2RAImap", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniOrient2RaimapOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_orient2_raimap(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__afni_orient2_raimap( - orientation_code: str, - runner: Runner | None = None, -) -> VAfniOrient2RaimapOutputs: - """ - Returns the index map for the RAI directions. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - orientation_code: Orientation code (e.g., RAI, LSP). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniOrient2RaimapOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_ORIENT2_RAIMAP_METADATA) - cargs = [] - cargs.append("@AfniOrient2RAImap") - cargs.append(orientation_code) - ret = VAfniOrient2RaimapOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniOrient2RaimapOutputs", - "V__AFNI_ORIENT2_RAIMAP_METADATA", - "v__afni_orient2_raimap", -] diff --git a/python/src/niwrap/afni/v__afni_orient_sign.py b/python/src/niwrap/afni/v__afni_orient_sign.py deleted file mode 100644 index ab7c95c72..000000000 --- a/python/src/niwrap/afni/v__afni_orient_sign.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_ORIENT_SIGN_METADATA = Metadata( - id="e1bbba0e6f37200e4ecc08d0b497112ae8daf6df.boutiques", - name="@AfniOrientSign", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniOrientSignOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_orient_sign(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file containing the orientation signs of the dataset""" - - -def v__afni_orient_sign( - infile: InputPathType, - runner: Runner | None = None, -) -> VAfniOrientSignOutputs: - """ - A tool within the AFNI suite to determine the orientation signs of datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input image file to determine orientation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniOrientSignOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_ORIENT_SIGN_METADATA) - cargs = [] - cargs.append("@AfniOrientSign") - cargs.append("-orient") - cargs.append(execution.input_file(infile)) - ret = VAfniOrientSignOutputs( - root=execution.output_file("."), - outfile=execution.output_file(pathlib.Path(infile).name + "_orient.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniOrientSignOutputs", - "V__AFNI_ORIENT_SIGN_METADATA", - "v__afni_orient_sign", -] diff --git a/python/src/niwrap/afni/v__afni_r_package_install.py b/python/src/niwrap/afni/v__afni_r_package_install.py deleted file mode 100644 index 2d2c5bef0..000000000 --- a/python/src/niwrap/afni/v__afni_r_package_install.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_R_PACKAGE_INSTALL_METADATA = Metadata( - id="eed9df9300a8edee772f45decbc84c556498020e.boutiques", - name="@afni_R_package_install", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniRPackageInstallOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_r_package_install(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - install_log: OutputPathType - """A log file listing all installed R packages.""" - - -def v__afni_r_package_install( - afni: bool = False, - shiny: bool = False, - bayes_view: bool = False, - circos: bool = False, - custom_packages: str | None = None, - mirror: str | None = None, - help_: bool = False, - runner: Runner | None = None, -) -> VAfniRPackageInstallOutputs: - """ - Helper script to install R packages for various afni-ish purposes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - afni: Install AFNI related R packages. - shiny: Install AFNI related shiny app packages. - bayes_view: Install R packages for bayes_view. - circos: Install OmicCircos for FATCAT_matplot. - custom_packages: Install custom R packages (space-separated list). Must\ - start and end with double quotes. - mirror: Set the CRAN mirror to a custom URL. - help_: Show help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniRPackageInstallOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_R_PACKAGE_INSTALL_METADATA) - cargs = [] - cargs.append("@afni_R_package_install") - if afni: - cargs.append("-afni") - if shiny: - cargs.append("-shiny") - if bayes_view: - cargs.append("-bayes_view") - if circos: - cargs.append("-circos") - if custom_packages is not None: - cargs.extend([ - "-custom", - custom_packages - ]) - if mirror is not None: - cargs.extend([ - "-mirror", - mirror - ]) - if help_: - cargs.append("-help") - ret = VAfniRPackageInstallOutputs( - root=execution.output_file("."), - install_log=execution.output_file("R_packages_installed.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniRPackageInstallOutputs", - "V__AFNI_R_PACKAGE_INSTALL_METADATA", - "v__afni_r_package_install", -] diff --git a/python/src/niwrap/afni/v__afni_refacer_make_master.py b/python/src/niwrap/afni/v__afni_refacer_make_master.py deleted file mode 100644 index 5f73f620c..000000000 --- a/python/src/niwrap/afni/v__afni_refacer_make_master.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_REFACER_MAKE_MASTER_METADATA = Metadata( - id="5d171c695cab39d1411b8652cb05c15ab1caaa20.boutiques", - name="@afni_refacer_make_master", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniRefacerMakeMasterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_refacer_make_master(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_shell_dataset: OutputPathType - """Output dataset containing the average 'face' (non-brain tissue).""" - - -def v__afni_refacer_make_master( - input_datasets: list[InputPathType], - runner: Runner | None = None, -) -> VAfniRefacerMakeMasterOutputs: - """ - This script makes a new mask/shell dataset for use with @afni_refacer_run by - averaging 'faces' (non-brain tissue) from input datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_datasets: List of T1-weighted datasets that have NOT been\ - skull-stripped, defaced, or refaced. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniRefacerMakeMasterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_REFACER_MAKE_MASTER_METADATA) - cargs = [] - cargs.append("@afni_refacer_make_master") - cargs.extend([execution.input_file(f) for f in input_datasets]) - ret = VAfniRefacerMakeMasterOutputs( - root=execution.output_file("."), - output_shell_dataset=execution.output_file("afni_refacer_shell.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniRefacerMakeMasterOutputs", - "V__AFNI_REFACER_MAKE_MASTER_METADATA", - "v__afni_refacer_make_master", -] diff --git a/python/src/niwrap/afni/v__afni_refacer_make_onebig_a12.py b/python/src/niwrap/afni/v__afni_refacer_make_onebig_a12.py deleted file mode 100644 index 08e7ac2f6..000000000 --- a/python/src/niwrap/afni/v__afni_refacer_make_onebig_a12.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_REFACER_MAKE_ONEBIG_A12_METADATA = Metadata( - id="385413dfddf67125c769d1505e8d24529d5a0ed5.boutiques", - name="@afni_refacer_make_onebigA12", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniRefacerMakeOnebigA12Outputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_refacer_make_onebig_a12(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - aligned_output: OutputPathType - """Aligned T1w dataset to MNI template with expanded 'big' grid""" - - -def v__afni_refacer_make_onebig_a12( - t1w_dataset: InputPathType, - runner: Runner | None = None, -) -> VAfniRefacerMakeOnebigA12Outputs: - """ - Script to align a single T1w dataset to the MNI template and expand it to a - 'big' grid. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - t1w_dataset: Input T1w dataset name. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniRefacerMakeOnebigA12Outputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_REFACER_MAKE_ONEBIG_A12_METADATA) - cargs = [] - cargs.append("@afni_refacer_make_onebigA12") - cargs.append(execution.input_file(t1w_dataset)) - ret = VAfniRefacerMakeOnebigA12Outputs( - root=execution.output_file("."), - aligned_output=execution.output_file(pathlib.Path(t1w_dataset).name + "_aligned_to_MNI.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniRefacerMakeOnebigA12Outputs", - "V__AFNI_REFACER_MAKE_ONEBIG_A12_METADATA", - "v__afni_refacer_make_onebig_a12", -] diff --git a/python/src/niwrap/afni/v__afni_refacer_run.py b/python/src/niwrap/afni/v__afni_refacer_run.py deleted file mode 100644 index d0e27f78b..000000000 --- a/python/src/niwrap/afni/v__afni_refacer_run.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_REFACER_RUN_METADATA = Metadata( - id="468955e38481aae9c781599f1f8a7945f4d29bc2.boutiques", - name="@afni_refacer_run", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniRefacerRunOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_refacer_run(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_deface: OutputPathType - """Defaced volume (face+ears replaced with zeros)""" - output_reface: OutputPathType - """Refaced volume (face+ears replaced with artificial values)""" - output_reface_plus: OutputPathType - """Reface_plused volume (face+ears+skull replaced with artificial values)""" - output_face: OutputPathType - """Face+ears used to replace or remove subject data""" - output_face_plus: OutputPathType - """Face+ears+skull used to replace subject data""" - - -def v__afni_refacer_run( - input_file: InputPathType, - prefix: str, - mode_all: bool = False, - anonymize_output: bool = False, - cost_function: str | None = None, - shell_option: str | None = None, - no_clean: bool = False, - no_images: bool = False, - overwrite: bool = False, - verbose: bool = False, - runner: Runner | None = None, -) -> VAfniRefacerRunOutputs: - """ - This script re-faces one input dataset, using a master shell dataset to write - over the subject's 'face' region. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Name of input dataset; can contain path information. - prefix: Name of output dataset. - mode_all: Output three volumes: one defaced, one refaced and one\ - reface_plused. - anonymize_output: Use 3drefit and nifti_tool to anonymize the output\ - datasets. - cost_function: Specify any cost function that is allowed by 3dAllineate\ - (default: lpa). - shell_option: Specify which shell to use. Options:\ - afni_refacer_shell_sym_1.0.nii.gz (traditional),\ - afni_refacer_shell_sym_2.0.nii.gz (more face/neck removal). Default:\ - afni_refacer_shell_sym_1.0.nii.gz. - no_clean: Don't delete temp working directory (default: remove working\ - directory). - no_images: Don't make pretty images to automatically view the results\ - of re/defacing. - overwrite: Final two file outputs will overwrite any existing files of\ - the same name (default: don't do this). NB: this option does not apply\ - to the working directory. - verbose: Run the 3dAllineate part herein with '-verb' (for verbosity). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniRefacerRunOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_REFACER_RUN_METADATA) - cargs = [] - cargs.append("@afni_refacer_run") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - if mode_all: - cargs.append("-mode_all") - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - if anonymize_output: - cargs.append("-anonymize_output") - if cost_function is not None: - cargs.extend([ - "-cost", - cost_function - ]) - if shell_option is not None: - cargs.extend([ - "-shell", - shell_option - ]) - if no_clean: - cargs.append("-no_clean") - if no_images: - cargs.append("-no_images") - if overwrite: - cargs.append("-overwrite") - if verbose: - cargs.append("-verb_allin") - ret = VAfniRefacerRunOutputs( - root=execution.output_file("."), - output_deface=execution.output_file(prefix + ".deface.nii.gz"), - output_reface=execution.output_file(prefix + ".reface.nii.gz"), - output_reface_plus=execution.output_file(prefix + ".reface_plus.nii.gz"), - output_face=execution.output_file(prefix + ".face.nii.gz"), - output_face_plus=execution.output_file(prefix + ".face_plus.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniRefacerRunOutputs", - "V__AFNI_REFACER_RUN_METADATA", - "v__afni_refacer_run", -] diff --git a/python/src/niwrap/afni/v__afni_run_me.py b/python/src/niwrap/afni/v__afni_run_me.py deleted file mode 100644 index 50471e278..000000000 --- a/python/src/niwrap/afni/v__afni_run_me.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AFNI_RUN_ME_METADATA = Metadata( - id="48d4641b6ea60cfbc0c8108552ea5e637c57a409.boutiques", - name="@afni.run.me", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAfniRunMeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__afni_run_me(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__afni_run_me( - go: bool = False, - curl: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> VAfniRunMeOutputs: - """ - A tool to execute a specific command. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - go: Execute the work. - curl: Default to curl instead of wget. - help_: Show help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAfniRunMeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AFNI_RUN_ME_METADATA) - cargs = [] - cargs.append("@afni.run.me") - if go: - cargs.append("-go") - if curl: - cargs.append("-curl") - if help_: - cargs.append("-help") - ret = VAfniRunMeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAfniRunMeOutputs", - "V__AFNI_RUN_ME_METADATA", - "v__afni_run_me", -] diff --git a/python/src/niwrap/afni/v__align_centers.py b/python/src/niwrap/afni/v__align_centers.py deleted file mode 100644 index bcc8bb9ac..000000000 --- a/python/src/niwrap/afni/v__align_centers.py +++ /dev/null @@ -1,135 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ALIGN_CENTERS_METADATA = Metadata( - id="f29fbec7d33b88a11144d9ab1edf49dc32ae31cf.boutiques", - name="@Align_Centers", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAlignCentersOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__align_centers(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - transform_matrix: OutputPathType - """Transform matrix needed for the shift applied to DSET.""" - shifted_dset: OutputPathType | None - """Shifted Dataset aligned with the base volume.""" - shifted_child_dsets: OutputPathType | None - """Shifted child datasets aligned with the base volume.""" - - -def v__align_centers( - base: InputPathType, - dset: InputPathType, - children: list[InputPathType] | None = None, - echo: bool = False, - overwrite: bool = False, - prefix: str | None = None, - matrix_only: bool = False, - matrix_only_no_dset: bool = False, - no_cp: bool = False, - center_grid: bool = False, - center_cm: bool = False, - center_cm_no_amask: bool = False, - shift_xform: InputPathType | None = None, - shift_xform_inv: InputPathType | None = None, - runner: Runner | None = None, -) -> VAlignCentersOutputs: - """ - Moves the center of a dataset (DSET) to the center of a base volume (BASE) and - optionally creates a transform matrix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base: Base volume, typically a template. Can also specify RAI\ - coordinates for center alignment. - dset: Dataset to be aligned to BASE. - children: Additional datasets (originally in register with DSET) that\ - should be shifted in the same way. - echo: Echo all commands to terminal for debugging. - overwrite: Overwrite existing output files. - prefix: Custom prefix for the result files. - matrix_only: Only output the transform needed to align the centers\ - without shifting any child volumes. - matrix_only_no_dset: Like -1Dmat_only, but no datasets are created or\ - changed. - no_cp: Do not create new data; shift existing ones. Use with caution. - center_grid: Center is that of the volume's grid (default). - center_cm: Center is the center of mass of the volume. - center_cm_no_amask: Like -cm, but with no automask. - shift_xform: Apply shift translation from a 1D file. - shift_xform_inv: Apply inverse of shift translation from a 1D file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAlignCentersOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ALIGN_CENTERS_METADATA) - cargs = [] - cargs.append("@Align_Centers") - cargs.append(execution.input_file(base)) - cargs.append(execution.input_file(dset)) - if children is not None: - cargs.extend([ - "-child", - *[execution.input_file(f) for f in children] - ]) - if echo: - cargs.append("-echo") - if overwrite: - cargs.append("-overwrite") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if matrix_only: - cargs.append("-1Dmat_only") - if matrix_only_no_dset: - cargs.append("-1Dmat_only_nodset") - if no_cp: - cargs.append("-no_cp") - if center_grid: - cargs.append("-grid") - if center_cm: - cargs.append("-cm") - if center_cm_no_amask: - cargs.append("-cm_no_amask") - if shift_xform is not None: - cargs.extend([ - "-shift_xform", - execution.input_file(shift_xform) - ]) - if shift_xform_inv is not None: - cargs.extend([ - "-shift_xform_inv", - execution.input_file(shift_xform_inv) - ]) - ret = VAlignCentersOutputs( - root=execution.output_file("."), - transform_matrix=execution.output_file(pathlib.Path(dset).name + "_shft.1D"), - shifted_dset=execution.output_file(prefix + "_shft+orig.BRIK") if (prefix is not None) else None, - shifted_child_dsets=execution.output_file(prefix + "_child_shft+orig.BRIK") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAlignCentersOutputs", - "V__ALIGN_CENTERS_METADATA", - "v__align_centers", -] diff --git a/python/src/niwrap/afni/v__align_partial_oblique.py b/python/src/niwrap/afni/v__align_partial_oblique.py deleted file mode 100644 index fd5253ad6..000000000 --- a/python/src/niwrap/afni/v__align_partial_oblique.py +++ /dev/null @@ -1,119 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ALIGN_PARTIAL_OBLIQUE_METADATA = Metadata( - id="6972a40122eb255cb7faab42312dcbea8ad1c3c1.boutiques", - name="@align_partial_oblique", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAlignPartialObliqueOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__align_partial_oblique(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - aligned_output: OutputPathType - """Aligned partial coverage T1 weighted dataset""" - - -def v__align_partial_oblique( - base: InputPathType, - input_: InputPathType, - suffix: str | None = None, - keep_tmp: bool = False, - clean: bool = False, - dxyz: float | None = None, - dx: float | None = None, - dy: float | None = None, - dz: float | None = None, - runner: Runner | None = None, -) -> VAlignPartialObliqueOutputs: - """ - A script to align a full coverage T1 weighted non-oblique dataset to match a - partial coverage T1 weighted non-oblique dataset. Alignment is done with a - rotation and shift (6 parameters) transform only. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base: Reference anatomical full coverage volume. - input_: Partial coverage T1 weighted non-oblique dataset. - suffix: Output dataset name is formed by adding SUF to the prefix of\ - the base dataset. The default suffix is _alnd_PartialCoverageObliqueT1. - keep_tmp: Keep temporary files. - clean: Clean all temp files, likely left from -keep_tmp option then\ - exit. - dxyz: Cubic voxel size of output dataset in TLRC space Default MM is 1. - dx: Size of voxel in the x direction (Right-Left). Default is 1mm. - dy: Size of voxel in the y direction (Anterior-Posterior). Default is\ - 1mm. - dz: Size of voxel in the z direction (Inferior-Superior). Default is\ - 1mm. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAlignPartialObliqueOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ALIGN_PARTIAL_OBLIQUE_METADATA) - cargs = [] - cargs.append("@align_partial_oblique") - cargs.extend([ - "-base", - execution.input_file(base) - ]) - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if keep_tmp: - cargs.append("-keep_tmp") - if clean: - cargs.append("-clean") - if dxyz is not None: - cargs.extend([ - "-dxyz", - str(dxyz) - ]) - if dx is not None: - cargs.extend([ - "-dx", - str(dx) - ]) - if dy is not None: - cargs.extend([ - "-dy", - str(dy) - ]) - if dz is not None: - cargs.extend([ - "-dz", - str(dz) - ]) - ret = VAlignPartialObliqueOutputs( - root=execution.output_file("."), - aligned_output=execution.output_file(pathlib.Path(base).name + "_alnd_" + pathlib.Path(input_).name + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAlignPartialObliqueOutputs", - "V__ALIGN_PARTIAL_OBLIQUE_METADATA", - "v__align_partial_oblique", -] diff --git a/python/src/niwrap/afni/v__anaticor.py b/python/src/niwrap/afni/v__anaticor.py deleted file mode 100644 index fd07bc194..000000000 --- a/python/src/niwrap/afni/v__anaticor.py +++ /dev/null @@ -1,135 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ANATICOR_METADATA = Metadata( - id="19a07ddcd930ceba8e3715284916aa97a383d5bb.boutiques", - name="@ANATICOR", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAnaticorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__anaticor(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Output files with the prefix specified by the -prefix option.""" - - -def v__anaticor( - ts: InputPathType, - polort: str, - motion: InputPathType, - aseg: InputPathType, - prefix: str, - radius: float | None = None, - view: str | None = None, - nuisance: InputPathType | None = None, - no_ventricles: bool = False, - rsq_wme: bool = False, - coverage: bool = False, - verb: bool = False, - dirty: bool = False, - echo: bool = False, - runner: Runner | None = None, -) -> VAnaticorOutputs: - """ - Script to produce a residual time series cleaned by ANATICOR model. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - ts: Time series volume which should have already undergone\ - preprocessing steps such as despiking, RetroIcor, RVT correction, time\ - shifting, and volume registration. - polort: Polynomial for linear trend removal. Use the same order as for\ - afni_proc.py. - motion: Head motion parameters from 3dvolreg, also created by\ - afni_proc.py. - aseg: Aseg file from FreeSurfer's segmentation. This aseg volume must\ - be in register with the EPI time series. - prefix: Use output (residual time series) for a prefix. - radius: The radius of a local sphere mask in mm. Default is 15 mm for\ - high resolution 1.7x1.7x3mm data. - view: Set the view of the output data. Default is +orig. Choose from\ - +orig, +acpc, or +tlrc. - nuisance: Other nuisance regressors. Each regressor is a column in .1D\ - file. - no_ventricles: Do not include LVe regressor. - rsq_wme: Produce an explained variance map for WMeLOCAL regressor. - coverage: Produce a spatial coverage map of WMeLOCAL regressor. - verb: Verbose flag. - dirty: Keep temporary files. - echo: Echo each script command for debugging. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAnaticorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ANATICOR_METADATA) - cargs = [] - cargs.append("@ANATICOR") - cargs.extend([ - "-ts", - execution.input_file(ts) - ]) - cargs.extend([ - "-polort", - polort - ]) - cargs.extend([ - "-motion", - execution.input_file(motion) - ]) - cargs.append(execution.input_file(aseg)) - cargs.extend([ - "-prefix", - prefix - ]) - if radius is not None: - cargs.extend([ - "-radius", - str(radius) - ]) - if view is not None: - cargs.append(view) - if nuisance is not None: - cargs.extend([ - "-nuisance", - execution.input_file(nuisance) - ]) - if no_ventricles: - cargs.append("-no_ventricles") - if rsq_wme: - cargs.append("-Rsq_WMe") - if coverage: - cargs.append("-coverage") - if verb: - cargs.append("-verb") - if dirty: - cargs.append("-dirty") - if echo: - cargs.append("-echo") - ret = VAnaticorOutputs( - root=execution.output_file("."), - output_files=execution.output_file(prefix), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAnaticorOutputs", - "V__ANATICOR_METADATA", - "v__anaticor", -] diff --git a/python/src/niwrap/afni/v__animal_warper.py b/python/src/niwrap/afni/v__animal_warper.py deleted file mode 100644 index 548f3f540..000000000 --- a/python/src/niwrap/afni/v__animal_warper.py +++ /dev/null @@ -1,289 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ANIMAL_WARPER_METADATA = Metadata( - id="d579a65017cdc0a556b0c069e8808dbbad954c1f.boutiques", - name="@animal_warper", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAnimalWarperOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__animal_warper(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warp2std: OutputPathType - """input dataset nonlinearly warped to template""" - qc_image_initial: OutputPathType - """initial QC image montage showing overlap of source and base dataset""" - qc_image_initial_sh: OutputPathType - """initial QC image montage after shifting centers of source and base - dataset""" - dset_followers_out: OutputPathType - """copy(s) of -dset_followers mapped to template space""" - roidset_followers_out: OutputPathType - """copy(s) of -roidset_followers mapped to template space""" - animal_outs_guide: OutputPathType - """guide to data in output directory""" - - -def v__animal_warper( - input_file: InputPathType, - base_template: InputPathType, - output_dir: str, - brainmask: InputPathType | None = None, - atlases: list[InputPathType] | None = None, - atlas_followers: list[InputPathType] | None = None, - seg_followers: list[InputPathType] | None = None, - template_followers: list[InputPathType] | None = None, - dset_followers: list[InputPathType] | None = None, - roidset_followers: list[InputPathType] | None = None, - input_abbrev: str | None = None, - base_abbrev: str | None = None, - atlas_abbrevs: list[str] | None = None, - template_abbrevs: list[str] | None = None, - seg_abbrevs: list[str] | None = None, - dset_abbrevs: list[str] | None = None, - roidset_abbrevs: list[str] | None = None, - align_centers_meth: str | None = None, - aff_move_opt: str | None = None, - cost: str | None = None, - maxlev: float | None = None, - no_surfaces: bool = False, - feature_size: float | None = None, - supersize: bool = False, - init_scale: float | None = None, - mode_smooth_size: float | None = None, - mode_smooth_replacement_off: bool = False, - center_out: str | None = None, - align_type: str | None = None, - extra_qw_opts: str | None = None, - keep_temp: bool = False, - version: bool = False, - ok_to_exist: bool = False, - echo: bool = False, - runner: Runner | None = None, -) -> VAnimalWarperOutputs: - """ - Align a subject structural dataset to a template and perform several - post-alignment operations. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: input dataset to align to base template. - base_template: base dataset (template) to align with. - output_dir: output directory where all processing will be performed. - brainmask: provide a brainmask in the base template space. - atlases: one or more atlas datasets in the base volume space. - atlas_followers: one or more atlas datasets in the base volume space. - seg_followers: one or more segmentation datasets in the base volume\ - space. - template_followers: one or more datasets in the template volume space. - dset_followers: one or more datasets in the input volume space. - roidset_followers: one or more (int-valued) datasets in the input\ - volume space. - input_abbrev: specify abbreviation for input dataset. - base_abbrev: specify abbreviation for base dataset. - atlas_abbrevs: specify an abbreviation for each atlas follower dataset. - template_abbrevs: specify an abbreviation for each template follower\ - dataset. - seg_abbrevs: specify an abbreviation for each segmentation follower\ - dataset. - dset_abbrevs: specify an abbreviation for each dataset follower dataset. - roidset_abbrevs: specify an abbreviation for each ROI dataset follower\ - dataset. - align_centers_meth: center alignment method to use. - aff_move_opt: alignment movement options for affine alignment step. - cost: cost function for affine and nonlinear alignment. - maxlev: Max level for nonlinear warping. Final patch size is determined\ - based on this value. - no_surfaces: Do not make surfaces for atlas regions in native space. - feature_size: Set feature size for affine alignment (in mm). - supersize: Allow up to 50% size difference between subject and template. - init_scale: Approximate length ratio of input to template for initial\ - scaling. - mode_smooth_size: Modal smoothing kernel size in voxels. - mode_smooth_replacement_off: Turn off replacement in modal smoothing. - center_out: Center native-space output to native original space or\ - template space center-shifted. - align_type: Specify level of alignment. - extra_qw_opts: Additional options to add to existing options for\ - 3dQwarp. - keep_temp: Keep temporary files including awpy directory and other\ - intermediate datasets. - version: Display the program version. - ok_to_exist: Reuse and do not overwrite existing datasets. - echo: Copy all commands being run into the terminal. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAnimalWarperOutputs`). - """ - if maxlev is not None and not (0 <= maxlev <= 11): - raise ValueError(f"'maxlev' must be between 0 <= x <= 11 but was {maxlev}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__ANIMAL_WARPER_METADATA) - cargs = [] - cargs.append("@animal_warper") - cargs.append(execution.input_file(input_file)) - cargs.append(execution.input_file(base_template)) - cargs.append(output_dir) - if brainmask is not None: - cargs.append(execution.input_file(brainmask)) - if atlases is not None: - cargs.extend([ - "-atlas", - *[execution.input_file(f) for f in atlases] - ]) - if atlas_followers is not None: - cargs.extend([ - "-atlas_followers", - *[execution.input_file(f) for f in atlas_followers] - ]) - if seg_followers is not None: - cargs.extend([ - "-seg_followers", - *[execution.input_file(f) for f in seg_followers] - ]) - if template_followers is not None: - cargs.extend([ - "-template_followers", - *[execution.input_file(f) for f in template_followers] - ]) - if dset_followers is not None: - cargs.extend([ - "-dset_followers", - *[execution.input_file(f) for f in dset_followers] - ]) - if roidset_followers is not None: - cargs.extend([ - "-roidset_followers", - *[execution.input_file(f) for f in roidset_followers] - ]) - if input_abbrev is not None: - cargs.extend([ - "-input_abbrev", - input_abbrev - ]) - if base_abbrev is not None: - cargs.extend([ - "-base_abbrev", - base_abbrev - ]) - if atlas_abbrevs is not None: - cargs.extend([ - "-atlas_abbrevs", - *atlas_abbrevs - ]) - if template_abbrevs is not None: - cargs.extend([ - "-template_abbrevs", - *template_abbrevs - ]) - if seg_abbrevs is not None: - cargs.extend([ - "-seg_abbrevs", - *seg_abbrevs - ]) - if dset_abbrevs is not None: - cargs.extend([ - "-dset_abbrevs", - *dset_abbrevs - ]) - if roidset_abbrevs is not None: - cargs.extend([ - "-roidset_abbrevs", - *roidset_abbrevs - ]) - if align_centers_meth is not None: - cargs.extend([ - "-align_centers_meth", - align_centers_meth - ]) - if aff_move_opt is not None: - cargs.extend([ - "-aff_move_opt", - aff_move_opt - ]) - if cost is not None: - cargs.extend([ - "-cost", - cost - ]) - if maxlev is not None: - cargs.extend([ - "-maxlev", - str(maxlev) - ]) - if no_surfaces: - cargs.append("-no_surfaces") - if feature_size is not None: - cargs.extend([ - "-feature_size", - str(feature_size) - ]) - if supersize: - cargs.append("-supersize") - if init_scale is not None: - cargs.extend([ - "-init_scale", - str(init_scale) - ]) - if mode_smooth_size is not None: - cargs.extend([ - "-mode_smooth_size", - str(mode_smooth_size) - ]) - if mode_smooth_replacement_off: - cargs.append("-mode_smooth_replacement_off") - if center_out is not None: - cargs.extend([ - "-center_out", - center_out - ]) - if align_type is not None: - cargs.extend([ - "-align_type", - align_type - ]) - if extra_qw_opts is not None: - cargs.extend([ - "-extra_qw_opts", - extra_qw_opts - ]) - if keep_temp: - cargs.append("-keep_temp") - if version: - cargs.append("-ver") - if ok_to_exist: - cargs.append("-ok_to_exist") - if echo: - cargs.append("-echo") - ret = VAnimalWarperOutputs( - root=execution.output_file("."), - warp2std=execution.output_file("aw_results/" + pathlib.Path(input_file).name + "_warp2std.nii.gz"), - qc_image_initial=execution.output_file("aw_results/init_qc_00.input+base*.jpg"), - qc_image_initial_sh=execution.output_file("aw_results/init_qc_01.input_sh+base*.jpg"), - dset_followers_out=execution.output_file("aw_results/DSET_FOLL.nii.gz"), - roidset_followers_out=execution.output_file("aw_results/ROIDSET_FOLL.nii.gz"), - animal_outs_guide=execution.output_file("aw_results/animal_outs.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAnimalWarperOutputs", - "V__ANIMAL_WARPER_METADATA", - "v__animal_warper", -] diff --git a/python/src/niwrap/afni/v__atlasize.py b/python/src/niwrap/afni/v__atlasize.py deleted file mode 100644 index c42caddb8..000000000 --- a/python/src/niwrap/afni/v__atlasize.py +++ /dev/null @@ -1,180 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ATLASIZE_METADATA = Metadata( - id="f51d59e8bc780f981002a3321567e77ca2e2ade3.boutiques", - name="@Atlasize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAtlasizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__atlasize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - niml_file: OutputPathType | None - """Generated NIML file for the atlas""" - - -def v__atlasize( - dset: InputPathType | None = None, - space: str | None = None, - lab_file: list[str] | None = None, - lab_file_delim: str | None = None, - longnames: float | None = None, - last_longname_col: float | None = None, - atlas_type: str | None = None, - atlas_description: str | None = None, - atlas_name: str | None = None, - auto_backup: bool = False, - centers: bool = False, - centertype: str | None = None, - centermask: InputPathType | None = None, - skip_novoxels: bool = False, - h_web: bool = False, - h_view: bool = False, - all_opts: bool = False, - h_find: str | None = None, - runner: Runner | None = None, -) -> VAtlasizeOutputs: - """ - Script to turn a volumetric dataset into an AFNI atlas. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Make DSET an atlas. - space: Mark DSET as being in space SPACE. - lab_file: Labels and keys are in text file FILE. cLAB is the index of\ - column containing labels, vVAL is the index of column containing keys\ - (1st column is indexed at 0). - lab_file_delim: Set column delimiter for -lab_file option. Default is '\ - ' (space), but you can set your own. ';' for example. - longnames: Additionally, allow for another column of long names for\ - regions, e.g., amygdala for AMY. cLONGNAME is the starting column for\ - the long name continuing to the last name of the output. - last_longname_col: Limit long names to nth column. - atlas_type: Set the atlas type where TP is 'S' for subject-based and\ - 'G' for group-based atlases, respectively. - atlas_description: A description for the atlas. Default is 'My Atlas'. - atlas_name: Name for the atlas. Default name is based on prefix of\ - DSET. - auto_backup: Back up the dataset if it already exists in the custom\ - atlas directory and allows an overwrite. - centers: Add center of mass coordinates to atlas. - centertype: Choose Icent, Dcent, or cm for different ways to compute\ - centers. - centermask: Calculate center of mass locations for each ROI using a\ - subset of voxels. Useful for atlases with identical labels in both\ - hemispheres. - skip_novoxels: Skip regions without any voxels in the dataset. - h_web: Open webpage with help for this program. - h_view: Open -help output in a GUI editor. - all_opts: List all of the options for this script. - h_find: Search for lines containing WORD in -help output. Search is\ - approximate. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAtlasizeOutputs`). - """ - if lab_file is not None and not (len(lab_file) <= 3): - raise ValueError(f"Length of 'lab_file' must be less than 3 but was {len(lab_file)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__ATLASIZE_METADATA) - cargs = [] - cargs.append("@Atlasize") - if dset is not None: - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if space is not None: - cargs.extend([ - "-space", - space - ]) - if lab_file is not None: - cargs.extend([ - "-lab_file", - *lab_file - ]) - if lab_file_delim is not None: - cargs.extend([ - "-lab_file_delim", - lab_file_delim - ]) - if longnames is not None: - cargs.extend([ - "-longnames", - str(longnames) - ]) - if last_longname_col is not None: - cargs.extend([ - "-last_longname_col", - str(last_longname_col) - ]) - if atlas_type is not None: - cargs.extend([ - "-atlas_type", - atlas_type - ]) - if atlas_description is not None: - cargs.extend([ - "-atlas_description", - atlas_description - ]) - if atlas_name is not None: - cargs.extend([ - "-atlas_name", - atlas_name - ]) - if auto_backup: - cargs.append("-auto_backup") - if centers: - cargs.append("-centers") - if centertype is not None: - cargs.extend([ - "-centertype", - centertype - ]) - if centermask is not None: - cargs.extend([ - "-centermask", - execution.input_file(centermask) - ]) - if skip_novoxels: - cargs.append("-skip_novoxels") - if h_web: - cargs.append("-h_web") - if h_view: - cargs.append("-h_view") - if all_opts: - cargs.append("-all_opts") - if h_find is not None: - cargs.extend([ - "-h_find", - h_find - ]) - ret = VAtlasizeOutputs( - root=execution.output_file("."), - niml_file=execution.output_file(pathlib.Path(dset).name + ".niml") if (dset is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAtlasizeOutputs", - "V__ATLASIZE_METADATA", - "v__atlasize", -] diff --git a/python/src/niwrap/afni/v__auto_tlrc.py b/python/src/niwrap/afni/v__auto_tlrc.py deleted file mode 100644 index 950b0d3c8..000000000 --- a/python/src/niwrap/afni/v__auto_tlrc.py +++ /dev/null @@ -1,296 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__AUTO_TLRC_METADATA = Metadata( - id="22feaa9f6bac760643cabb253973d50074192acb.boutiques", - name="@auto_tlrc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VAutoTlrcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__auto_tlrc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType | None - """Transformed anatomical volume dataset in TLRC space.""" - transform_file: OutputPathType | None - """Transform used to align the anatomical dataset to the template.""" - - -def v__auto_tlrc( - base_template: InputPathType, - input_anat: InputPathType, - apar: InputPathType, - input_dataset: InputPathType, - no_ss: bool = False, - warp_orig_vol: bool = False, - dxyz: float | None = None, - dx: float | None = None, - dy: float | None = None, - dz: float | None = None, - pad_base: float | None = None, - keep_tmp: bool = False, - clean: bool = False, - xform: str | None = None, - no_avoid_eyes: bool = False, - ncr: bool = False, - onepass: bool = False, - twopass: bool = False, - maxite: float | None = None, - not_ok_maxite: bool = False, - inweight: bool = False, - rigid_equiv: bool = False, - init_xform: str | None = None, - no_pre: bool = False, - out_space: str | None = None, - v_3d_allineate: bool = False, - v_3d_alcost: str | None = None, - overwrite: bool = False, - pad_input: float | None = None, - onewarp: bool = False, - twowarp: bool = False, - rmode: str | None = None, - prefix: str | None = None, - suffix: str | None = None, - keep_view: bool = False, - base_copy: str | None = None, - base_list: bool = False, - use_gz: bool = False, - verb: bool = False, - runner: Runner | None = None, -) -> VAutoTlrcOutputs: - """ - A script to transform an anatomical dataset to align with some standard space - template and to apply the same TLRC transform obtained with @auto_tlrc in Usage - 1 mode to other datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base_template: Reference anatomical volume. Usually this volume is in\ - some standard space like TLRC or MNI space. - input_anat: Original anatomical volume (+orig). The skull is removed by\ - this script unless instructed otherwise (-no_ss). - apar: An anatomical dataset in TLRC space created using Usage 1 of\ - @auto_tlrc. - input_dataset: Dataset (typically EPI time series or statistical\ - dataset) to transform to TLRC space per the transform in TLRC_parent. - no_ss: Do not strip skull of input data set because the skull has\ - already been removed or because the template still has the skull. - warp_orig_vol: Produce a TLRC version of the input volume, rather than\ - a TLRC version of the skull-stripped input. - dxyz: Cubic voxel size of output DSET in TLRC space. Default is the\ - resolution of the template. - dx: Size of voxel in the x direction (Right-Left). Default is 1mm. - dy: Size of voxel in the y direction (Anterior-Posterior). Default is\ - 1mm. - dz: Size of voxel in the z direction (Inferior-Superior). Default is\ - 1mm. - pad_base: Pad the base dataset by MM mm in each direction. Default is\ - 15 mm. - keep_tmp: Keep temporary files. - clean: Clean all temporary files, likely left from -keep_tmp option\ - then exit. - xform: Transform to use for warping: Choose from affine_general or\ - shift_rotate_scale. Default is affine_general. - no_avoid_eyes: An option that gets passed to 3dSkullStrip. Use it when\ - parts of the frontal lobes get clipped. - ncr: Do not use -coarserot option for 3dWarpDrive, which is a default. - onepass: Turns off -twopass option for 3dWarpDrive. This will speed up\ - the registration but might fail if the datasets are far apart. - twopass: Opposite of -onepass, default. - maxite: Maximum number of iterations for 3dWarpDrive. Default is 50 for\ - first pass and then doubled to 100 in second pass. - not_ok_maxite: Continue running even if maximum iterations is reached. - inweight: Apply -weight INPUT (in 3dWarpDrive). By default, 3dWarpDrive\ - uses the BASE dataset to weight the alignment cost. - rigid_equiv: Output the rigid-body version of the alignment. Resultant\ - volume is NOT in TLRC space. - init_xform: Apply affine transform in XFORM0.1D before beginning\ - registration and then include XFORM0.1D in the final transform. - no_pre: Delete temporary dataset created by -init_xform. - out_space: Set the output to a particular space. - v_3d_allineate: Use 3dAllineate with the lpa+ZZ cost function instead\ - of 3dWarpDrive. - v_3d_alcost: Use another cost function like nmi for 3dAllineate. - overwrite: Overwrite existing output. - pad_input: Pad the input dataset by MM mm in each direction. - onewarp: Create follower data with one interpolation step, instead of\ - two. This option reduces blurring of the output data. - twowarp: Create follower data with two interpolations step, instead of\ - one. This option is for backward compatibility. - rmode: Resampling mode. Choose from: linear, cubic, NN or quintic.\ - Default for 'Usage 1' is cubic. - prefix: Name of the output dataset. - suffix: Name the output dataset by appending this suffix to the prefix\ - of the input data. - keep_view: Do not mark output dataset as +tlrc. - base_copy: Copy base (template) dataset into COPY_PREFIX. - base_list: List the full path of the base dataset. - use_gz: When using '-suffix ..', behave as if you had provided a prefix\ - with '*.gz' at the end. - verb: Increase verbosity of the script. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VAutoTlrcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__AUTO_TLRC_METADATA) - cargs = [] - cargs.append("@auto_tlrc") - cargs.extend([ - "-base", - execution.input_file(base_template) - ]) - cargs.extend([ - "-input", - execution.input_file(input_anat) - ]) - if no_ss: - cargs.append("-no_ss") - if warp_orig_vol: - cargs.append("-warp_orig_vol") - if dxyz is not None: - cargs.extend([ - "-dxyz", - str(dxyz) - ]) - if dx is not None: - cargs.extend([ - "-dx", - str(dx) - ]) - if dy is not None: - cargs.extend([ - "-dy", - str(dy) - ]) - if dz is not None: - cargs.extend([ - "-dz", - str(dz) - ]) - if pad_base is not None: - cargs.extend([ - "-pad_base", - str(pad_base) - ]) - if keep_tmp: - cargs.append("-keep_tmp") - if clean: - cargs.append("-clean") - if xform is not None: - cargs.extend([ - "-xform", - xform - ]) - if no_avoid_eyes: - cargs.append("-no_avoid_eyes") - if ncr: - cargs.append("-ncr") - if onepass: - cargs.append("-onepass") - if twopass: - cargs.append("-twopass") - if maxite is not None: - cargs.extend([ - "-maxite", - str(maxite) - ]) - if not_ok_maxite: - cargs.append("-not_OK_maxite") - if inweight: - cargs.append("-inweight") - if rigid_equiv: - cargs.append("-rigid_equiv") - if init_xform is not None: - cargs.extend([ - "-init_xform", - init_xform - ]) - if no_pre: - cargs.append("-no_pre") - if out_space is not None: - cargs.extend([ - "-out_space", - out_space - ]) - if v_3d_allineate: - cargs.append("-3dAllineate") - if v_3d_alcost is not None: - cargs.extend([ - "-3dAlcost", - v_3d_alcost - ]) - if overwrite: - cargs.append("-overwrite") - cargs.extend([ - "-apar", - execution.input_file(apar) - ]) - cargs.extend([ - "-input", - execution.input_file(input_dataset) - ]) - if pad_input is not None: - cargs.extend([ - "-pad_input", - str(pad_input) - ]) - if onewarp: - cargs.append("-onewarp") - if twowarp: - cargs.append("-twowarp") - if rmode is not None: - cargs.extend([ - "-rmode", - rmode - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - if keep_view: - cargs.append("-keep_view") - if base_copy is not None: - cargs.extend([ - "-base_copy", - base_copy - ]) - if base_list: - cargs.append("-base_list") - if use_gz: - cargs.append("-use_gz") - if verb: - cargs.append("-verb") - ret = VAutoTlrcOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - transform_file=execution.output_file(prefix + ".Xat.1D") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VAutoTlrcOutputs", - "V__AUTO_TLRC_METADATA", - "v__auto_tlrc", -] diff --git a/python/src/niwrap/afni/v__build_afni_xlib.py b/python/src/niwrap/afni/v__build_afni_xlib.py deleted file mode 100644 index 251e590b1..000000000 --- a/python/src/niwrap/afni/v__build_afni_xlib.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__BUILD_AFNI_XLIB_METADATA = Metadata( - id="121cbb94304d7b6be810fff619244ff26d2a3235.boutiques", - name="@build_afni_Xlib", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VBuildAfniXlibOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__build_afni_xlib(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__build_afni_xlib( - packages: list[str], - localinstall: bool = False, - debug_symbols: bool = False, - lib64: bool = False, - runner: Runner | None = None, -) -> VBuildAfniXlibOutputs: - """ - Compile and install lesstif, openmotif, and/or libXt. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - packages: Packages to compile and install (e.g., lesstif, openmotif,\ - libXt). - localinstall: Install under each package directory. - debug_symbols: Compile with -g to add symbols. - lib64: Install libs under lib64 (default is lib). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VBuildAfniXlibOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__BUILD_AFNI_XLIB_METADATA) - cargs = [] - cargs.append("@build_afni_Xlib") - if localinstall: - cargs.append("-localinstall") - if debug_symbols: - cargs.append("-g") - if lib64: - cargs.append("-lib64") - cargs.extend(packages) - ret = VBuildAfniXlibOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VBuildAfniXlibOutputs", - "V__BUILD_AFNI_XLIB_METADATA", - "v__build_afni_xlib", -] diff --git a/python/src/niwrap/afni/v__center_distance.py b/python/src/niwrap/afni/v__center_distance.py deleted file mode 100644 index ea95dc621..000000000 --- a/python/src/niwrap/afni/v__center_distance.py +++ /dev/null @@ -1,65 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CENTER_DISTANCE_METADATA = Metadata( - id="4b982bfe6d3c78b30fa9e3ce7498dab0a904c2d6.boutiques", - name="@Center_Distance", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VCenterDistanceOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__center_distance(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - distance_output: OutputPathType - """The calculated distance between the centers of DSET_1 and DSET_2""" - - -def v__center_distance( - dset1: InputPathType, - dset2: InputPathType, - runner: Runner | None = None, -) -> VCenterDistanceOutputs: - """ - Tool to calculate the distance between the centers of two datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset1: First dataset file (e.g. file1.nii.gz). - dset2: Second dataset file (e.g. file2.nii.gz). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VCenterDistanceOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CENTER_DISTANCE_METADATA) - cargs = [] - cargs.append("@Center_Distance") - cargs.append("-dset") - cargs.append(execution.input_file(dset1)) - cargs.append(execution.input_file(dset2)) - ret = VCenterDistanceOutputs( - root=execution.output_file("."), - distance_output=execution.output_file("distance.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VCenterDistanceOutputs", - "V__CENTER_DISTANCE_METADATA", - "v__center_distance", -] diff --git a/python/src/niwrap/afni/v__chauffeur_afni.py b/python/src/niwrap/afni/v__chauffeur_afni.py deleted file mode 100644 index 7ade77acd..000000000 --- a/python/src/niwrap/afni/v__chauffeur_afni.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CHAUFFEUR_AFNI_METADATA = Metadata( - id="1c876be7c5930cd8b1fe92c47fded0de8c44feca.boutiques", - name="@chauffeur_afni", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VChauffeurAfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__chauffeur_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """Generated montage image""" - cluster_report: OutputPathType - """Clusterization report""" - whereami_report: OutputPathType - """Whereami report for clusterized data""" - - -def v__chauffeur_afni( - ulay: InputPathType, - prefix: str, - olay: InputPathType | None = None, - runner: Runner | None = None, -) -> VChauffeurAfniOutputs: - """ - Automated QC snapshots generator in AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - ulay: Name of underlay dataset (required); can be 3D or 4D set. - prefix: Prefix for output files (required). - olay: Name of overlay dataset (optional). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VChauffeurAfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CHAUFFEUR_AFNI_METADATA) - cargs = [] - cargs.append("@chauffeur_afni") - cargs.append(execution.input_file(ulay)) - if olay is not None: - cargs.append(execution.input_file(olay)) - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("[options]") - ret = VChauffeurAfniOutputs( - root=execution.output_file("."), - output_image=execution.output_file(prefix + ".png"), - cluster_report=execution.output_file(prefix + "_clust_rep.txt"), - whereami_report=execution.output_file(prefix + "_clust_whereami.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VChauffeurAfniOutputs", - "V__CHAUFFEUR_AFNI_METADATA", - "v__chauffeur_afni", -] diff --git a/python/src/niwrap/afni/v__check_for_afni_dset.py b/python/src/niwrap/afni/v__check_for_afni_dset.py deleted file mode 100644 index 987bc29c1..000000000 --- a/python/src/niwrap/afni/v__check_for_afni_dset.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CHECK_FOR_AFNI_DSET_METADATA = Metadata( - id="fe3233871c90874d4e2c2e24abac6304db035192.boutiques", - name="@CheckForAfniDset", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VCheckForAfniDsetOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__check_for_afni_dset(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_status: OutputPathType - """Text file containing the status code of the dataset""" - - -def v__check_for_afni_dset( - dataset_name: str, - runner: Runner | None = None, -) -> VCheckForAfniDsetOutputs: - """ - Check for the existence of AFNI datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset_name: Path to the AFNI dataset (e.g.,\ - /Data/stuff/Hello+orig.HEAD). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VCheckForAfniDsetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CHECK_FOR_AFNI_DSET_METADATA) - cargs = [] - cargs.append("@CheckForAfniDset") - cargs.append(dataset_name) - ret = VCheckForAfniDsetOutputs( - root=execution.output_file("."), - output_status=execution.output_file(dataset_name + "_status.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VCheckForAfniDsetOutputs", - "V__CHECK_FOR_AFNI_DSET_METADATA", - "v__check_for_afni_dset", -] diff --git a/python/src/niwrap/afni/v__clip_volume.py b/python/src/niwrap/afni/v__clip_volume.py deleted file mode 100644 index dbdcb6991..000000000 --- a/python/src/niwrap/afni/v__clip_volume.py +++ /dev/null @@ -1,171 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CLIP_VOLUME_METADATA = Metadata( - id="7bfb440cf4d5cd2d5ca3418b3dc2ad19927c0963.boutiques", - name="@clip_volume", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VClipVolumeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__clip_volume(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_clipped_volume: OutputPathType | None - """Output clipped or cropped volume""" - output_followers: OutputPathType | None - """Output for follower datasets after clipping/cropping""" - - -def v__clip_volume( - input_volume: InputPathType, - below_zmm: float | None = None, - above_zmm: float | None = None, - left_xmm: float | None = None, - right_xmm: float | None = None, - anterior_ymm: float | None = None, - posterior_ymm: float | None = None, - box: list[float] | None = None, - mask_box: list[float] | None = None, - and_logic: bool = False, - or_logic: bool = False, - verbosity: bool = False, - crop_allzero: bool = False, - crop_greedy: bool = False, - crop: bool = False, - crop_npad: float | None = None, - output_prefix: str | None = None, - followers: list[InputPathType] | None = None, - runner: Runner | None = None, -) -> VClipVolumeOutputs: - """ - A tool to clip regions of a volume in various ways, such as above/below certain - coordinates or within a specified box. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_volume: Volume to clip. - below_zmm: Set to 0 slices below Zmm. - above_zmm: Set to 0 slices above Zmm. - left_xmm: Set to 0 slices left of Xmm. - right_xmm: Set to 0 slices right of Xmm. - anterior_ymm: Set to 0 slices anterior to Ymm. - posterior_ymm: Set to 0 slices posterior to Ymm. - box: Clip the volume to a box centered at Cx, Cy, Cz (RAI mm), and of\ - dimensions Dx Dy Dz (RAI mm). - mask_box: Set all values inside the box to 1. Box centered at Cx, Cy,\ - Cz (RAI mm), and of dimensions Dx Dy Dz (RAI mm). - and_logic: Combine with next clipping planes using 'and'. - or_logic: Combine with next clipping planes using 'or'. - verbosity: Show command details (verbose output). - crop_allzero: Crop the output volume with 3dAutobox -noclust. - crop_greedy: Crop the output volume with 3dAutobox. - crop: Same as -crop_greedy, kept for backward compatibility. - crop_npad: Set 3dAutobox's -npad option to NPAD. NPAD fattens the\ - volume a little after cropping. - output_prefix: Output prefix for the resultant volume. Default is the\ - input prefix with _clp suffixed to it. - followers: Apply the same clipping or cropping treatment to the\ - follower datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VClipVolumeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CLIP_VOLUME_METADATA) - cargs = [] - cargs.append("@clip_volume") - cargs.append(execution.input_file(input_volume)) - if below_zmm is not None: - cargs.extend([ - "-below", - str(below_zmm) - ]) - if above_zmm is not None: - cargs.extend([ - "-above", - str(above_zmm) - ]) - if left_xmm is not None: - cargs.extend([ - "-left", - str(left_xmm) - ]) - if right_xmm is not None: - cargs.extend([ - "-right", - str(right_xmm) - ]) - if anterior_ymm is not None: - cargs.extend([ - "-anterior", - str(anterior_ymm) - ]) - if posterior_ymm is not None: - cargs.extend([ - "-posterior", - str(posterior_ymm) - ]) - if box is not None: - cargs.extend([ - "-box", - *map(str, box) - ]) - if mask_box is not None: - cargs.extend([ - "-mask_box", - *map(str, mask_box) - ]) - if and_logic: - cargs.append("-and") - if or_logic: - cargs.append("-or") - if verbosity: - cargs.append("-verb") - if crop_allzero: - cargs.append("-crop_allzero") - if crop_greedy: - cargs.append("-crop_greedy") - if crop: - cargs.append("-crop") - if crop_npad is not None: - cargs.extend([ - "-crop_npad", - str(crop_npad) - ]) - if output_prefix is not None: - cargs.extend([ - "-prefix", - output_prefix - ]) - if followers is not None: - cargs.extend([ - "-followers", - *[execution.input_file(f) for f in followers] - ]) - ret = VClipVolumeOutputs( - root=execution.output_file("."), - output_clipped_volume=execution.output_file(output_prefix + "_clp.nii.gz") if (output_prefix is not None) else None, - output_followers=execution.output_file(output_prefix + "_follow_clp.nii.gz") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VClipVolumeOutputs", - "V__CLIP_VOLUME_METADATA", - "v__clip_volume", -] diff --git a/python/src/niwrap/afni/v__clust_exp_cat_lab.py b/python/src/niwrap/afni/v__clust_exp_cat_lab.py deleted file mode 100644 index 8714c982c..000000000 --- a/python/src/niwrap/afni/v__clust_exp_cat_lab.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CLUST_EXP_CAT_LAB_METADATA = Metadata( - id="e7f57e6679bc4f1f5b1d6785c2f9a75f5472a1b4.boutiques", - name="@ClustExp_CatLab", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VClustExpCatLabOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__clust_exp_cat_lab(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output data set concatenating labeled subbriks""" - - -def v__clust_exp_cat_lab( - prefix: str, - input_file: InputPathType, - help_: bool = False, - runner: Runner | None = None, -) -> VClustExpCatLabOutputs: - """ - Helper script to concatenate and label a group of data sets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file name. - input_file: Name of file containing the labels and data sets table\ - (e.g. subjects.csv). - help_: Show help information. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VClustExpCatLabOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CLUST_EXP_CAT_LAB_METADATA) - cargs = [] - cargs.append("@ClustExp_CatLab") - cargs.append("-prefix") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if help_: - cargs.append("-help") - ret = VClustExpCatLabOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VClustExpCatLabOutputs", - "V__CLUST_EXP_CAT_LAB_METADATA", - "v__clust_exp_cat_lab", -] diff --git a/python/src/niwrap/afni/v__clust_exp_run_shiny.py b/python/src/niwrap/afni/v__clust_exp_run_shiny.py deleted file mode 100644 index bc10f8005..000000000 --- a/python/src/niwrap/afni/v__clust_exp_run_shiny.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__CLUST_EXP_RUN_SHINY_METADATA = Metadata( - id="e53b2b78817a474292cc479044cd6b22d354c3ef.boutiques", - name="@ClustExp_run_shiny", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VClustExpRunShinyOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__clust_exp_run_shiny(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__clust_exp_run_shiny( - directory: str, - help_: bool = False, - runner: Runner | None = None, -) -> VClustExpRunShinyOutputs: - """ - Launch a shiny app that was created by ClustExp_StatParse.py. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - directory: Folder created by ClustExp_StatParse.py. - help_: Show help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VClustExpRunShinyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__CLUST_EXP_RUN_SHINY_METADATA) - cargs = [] - cargs.append("@ClustExp_run_shiny") - cargs.append(directory) - if help_: - cargs.append("-help") - ret = VClustExpRunShinyOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VClustExpRunShinyOutputs", - "V__CLUST_EXP_RUN_SHINY_METADATA", - "v__clust_exp_run_shiny", -] diff --git a/python/src/niwrap/afni/v__command_globb.py b/python/src/niwrap/afni/v__command_globb.py deleted file mode 100644 index 0f5728174..000000000 --- a/python/src/niwrap/afni/v__command_globb.py +++ /dev/null @@ -1,81 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__COMMAND_GLOBB_METADATA = Metadata( - id="3fcaa2b9f57f4c3a8e88b6f2a4841a766c684dcf.boutiques", - name="@CommandGlobb", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VCommandGlobbOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__command_globb(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """Output files generated by the specified program command line.""" - - -def v__command_globb( - program_command: str, - output_dir: str, - brick_list: list[str], - extension: str | None = None, - runner: Runner | None = None, -) -> VCommandGlobbOutputs: - """ - A command-line tool to execute a specified program command line on a list of - input bricks. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - program_command: The entire command line for the program desired. The\ - command is best put between single quotes, do not use the \\ to break a\ - long line within the quotes. - output_dir: The output directory where the results will be saved. - brick_list: A list of bricks (or anything) on which the program command\ - will be executed. - extension: If the program requires a -prefix option, then you can\ - specify the extension which will get appended to the Brick names before\ - +orig. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VCommandGlobbOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__COMMAND_GLOBB_METADATA) - cargs = [] - cargs.append("@CommandGlobb") - cargs.append("-com") - cargs.append(program_command) - cargs.append("-session") - cargs.append(output_dir) - cargs.append("-newxt") - if extension is not None: - cargs.append(extension) - cargs.append("-list") - cargs.extend(brick_list) - ret = VCommandGlobbOutputs( - root=execution.output_file("."), - output_files=execution.output_file(output_dir + "/*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VCommandGlobbOutputs", - "V__COMMAND_GLOBB_METADATA", - "v__command_globb", -] diff --git a/python/src/niwrap/afni/v__compute_gcor.py b/python/src/niwrap/afni/v__compute_gcor.py deleted file mode 100644 index 352ecfe70..000000000 --- a/python/src/niwrap/afni/v__compute_gcor.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__COMPUTE_GCOR_METADATA = Metadata( - id="d9410dfe3cb0b268e03a4b833a2d567c23593843.boutiques", - name="@compute_gcor", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VComputeGcorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__compute_gcor(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corr_vol_brik: OutputPathType | None - """Output correlation volume BRIK file""" - corr_vol_head: OutputPathType | None - """Output correlation volume HEAD file""" - - -def v__compute_gcor( - input_: InputPathType, - mask: InputPathType | None = None, - corr_vol_prefix: str | None = None, - initial_trs: float | None = None, - no_demean: bool = False, - save_tmp: bool = False, - verbose: float | None = None, - runner: Runner | None = None, -) -> VComputeGcorOutputs: - """ - Compute GCOR, the global correlation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Specify input dataset to compute the GCOR over. - mask: Specify mask dataset, for restricting the computation. - corr_vol_prefix: Specify prefix for correlation volume output. - initial_trs: Specify number of initial TRs to ignore. - no_demean: Do not demean as the first step. - save_tmp: Save temporary files (do not remove at end). - verbose: Set verbose level (0=quiet, 3=max). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VComputeGcorOutputs`). - """ - if verbose is not None and not (0 <= verbose <= 3): - raise ValueError(f"'verbose' must be between 0 <= x <= 3 but was {verbose}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__COMPUTE_GCOR_METADATA) - cargs = [] - cargs.append("@compute_gcor") - cargs.append(execution.input_file(input_)) - if mask is not None: - cargs.append(execution.input_file(mask)) - if corr_vol_prefix is not None: - cargs.extend([ - "-corr_vol", - corr_vol_prefix - ]) - if initial_trs is not None: - cargs.extend([ - "-nfirst", - str(initial_trs) - ]) - if no_demean: - cargs.append("-no_demean") - if save_tmp: - cargs.append("-savetmp") - if verbose is not None: - cargs.extend([ - "-verb", - str(verbose) - ]) - ret = VComputeGcorOutputs( - root=execution.output_file("."), - corr_vol_brik=execution.output_file(corr_vol_prefix + "+tlrc.BRIK") if (corr_vol_prefix is not None) else None, - corr_vol_head=execution.output_file(corr_vol_prefix + "+tlrc.HEAD") if (corr_vol_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VComputeGcorOutputs", - "V__COMPUTE_GCOR_METADATA", - "v__compute_gcor", -] diff --git a/python/src/niwrap/afni/v__compute_oc_weights.py b/python/src/niwrap/afni/v__compute_oc_weights.py deleted file mode 100644 index 3c5783663..000000000 --- a/python/src/niwrap/afni/v__compute_oc_weights.py +++ /dev/null @@ -1,121 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__COMPUTE_OC_WEIGHTS_METADATA = Metadata( - id="4427220e56bd9be0b0fb6b294b7d2992dca6669c.boutiques", - name="@compute_OC_weights", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VComputeOcWeightsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__compute_oc_weights(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_oc_weights: OutputPathType | None - """Resulting OC weights dataset""" - - -def v__compute_oc_weights( - echo_dsets: list[str], - echo_times: str | None = None, - prefix: str | None = None, - def_to_equal: str | None = None, - oc_method: str | None = None, - sum_weight_tolerance: float | None = None, - t2_star_limit: float | None = None, - work_dir: str | None = None, - verbosity: bool = False, - runner: Runner | None = None, -) -> VComputeOcWeightsOutputs: - """ - Compute optimal combined weights dataset for multi-echo EPI data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - echo_dsets: Specify one run of multi-echo EPI data. - echo_times: Specify echo times as list (e.g., "15 30.5 41"). Use either\ - -echo_times or -echo_times_files. - prefix: Specify prefix of resulting OC weights dataset (e.g.,\ - OC.weights.SUBJ). - def_to_equal: Specify whether to default to equal weights (default =\ - no). - oc_method: Specify which OC method to employ (default = OC_A). - sum_weight_tolerance: Tolerance for summed weight difference from 1.0\ - (default = 0.001). - t2_star_limit: Specify limit for T2* values (default = 300). - work_dir: Specify directory to compute results in. - verbosity: Increase verbosity of output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VComputeOcWeightsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__COMPUTE_OC_WEIGHTS_METADATA) - cargs = [] - cargs.append("@compute_OC_weights") - if echo_times is not None: - cargs.extend([ - "-echo_times", - echo_times - ]) - cargs.extend([ - "-echo_dsets", - *echo_dsets - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if def_to_equal is not None: - cargs.extend([ - "-def_to_equal", - def_to_equal - ]) - if oc_method is not None: - cargs.extend([ - "-oc_method", - oc_method - ]) - if sum_weight_tolerance is not None: - cargs.extend([ - "-sum_weight_tolerance", - str(sum_weight_tolerance) - ]) - if t2_star_limit is not None: - cargs.extend([ - "-t2_star_limit", - str(t2_star_limit) - ]) - if work_dir is not None: - cargs.extend([ - "-work_dir", - work_dir - ]) - if verbosity: - cargs.append("-verb") - ret = VComputeOcWeightsOutputs( - root=execution.output_file("."), - output_oc_weights=execution.output_file(prefix + "+tlrc.HEAD") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VComputeOcWeightsOutputs", - "V__COMPUTE_OC_WEIGHTS_METADATA", - "v__compute_oc_weights", -] diff --git a/python/src/niwrap/afni/v__deblank_file_names.py b/python/src/niwrap/afni/v__deblank_file_names.py deleted file mode 100644 index c6870cf74..000000000 --- a/python/src/niwrap/afni/v__deblank_file_names.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DEBLANK_FILE_NAMES_METADATA = Metadata( - id="f8ade1cbfe9a1ee930f5bb24bfe83955ccad0cf1.boutiques", - name="@DeblankFileNames", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDeblankFileNamesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__deblank_file_names(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__deblank_file_names( - move: bool = False, - nobrac: bool = False, - demo_set: bool = False, - echo: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> VDeblankFileNamesOutputs: - """ - A script to remove blanks and other annoying characters ([], ()) from filenames. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - move: Actually rename the files (opposite of -dry_run). - nobrac: Do not replace () and [] in filenames, just spaces. - demo_set: Create a toy directory with bad names for testing. - echo: Turn on script echo. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDeblankFileNamesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DEBLANK_FILE_NAMES_METADATA) - cargs = [] - cargs.append("@DeblankFileNames") - if move: - cargs.append("-move") - if nobrac: - cargs.append("-nobrac") - if demo_set: - cargs.append("-demo_set") - if echo: - cargs.append("-echo") - if help_: - cargs.append("-help") - cargs.append("[FILES...]") - ret = VDeblankFileNamesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDeblankFileNamesOutputs", - "V__DEBLANK_FILE_NAMES_METADATA", - "v__deblank_file_names", -] diff --git a/python/src/niwrap/afni/v__demo_prompt.py b/python/src/niwrap/afni/v__demo_prompt.py deleted file mode 100644 index 6ccfd0b58..000000000 --- a/python/src/niwrap/afni/v__demo_prompt.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DEMO_PROMPT_METADATA = Metadata( - id="28759d07ed8faa73243bb8713758a156bb9ca999.boutiques", - name="@demo_prompt", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDemoPromptOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__demo_prompt(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - status: OutputPathType - """Status output: 0 if user presses OK, 1 if user cancels""" - - -def v__demo_prompt( - message: str, - runner: Runner | None = None, -) -> VDemoPromptOutputs: - """ - Prompts user with a message and waits for acknowledgment. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - message: The message to display in the prompt. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDemoPromptOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DEMO_PROMPT_METADATA) - cargs = [] - cargs.append("@demo_prompt") - cargs.append(message) - ret = VDemoPromptOutputs( - root=execution.output_file("."), - status=execution.output_file("status"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDemoPromptOutputs", - "V__DEMO_PROMPT_METADATA", - "v__demo_prompt", -] diff --git a/python/src/niwrap/afni/v__dice_metric.py b/python/src/niwrap/afni/v__dice_metric.py deleted file mode 100644 index 112c87c0d..000000000 --- a/python/src/niwrap/afni/v__dice_metric.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DICE_METRIC_METADATA = Metadata( - id="ce7547e49f36deb620867bdddcd49d28cf822476.boutiques", - name="@DiceMetric", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDiceMetricOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__dice_metric(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__dice_metric( - base: InputPathType, - dsets: list[InputPathType], - max_roi: float | None = None, - forceoutput: InputPathType | None = None, - forceoutput_: InputPathType | None = None, - echo: bool = False, - save_match: bool = False, - save_diff: bool = False, - do_not_mask_by_base: bool = False, - mask_by_base: bool = False, - prefix: str | None = None, - ignore_bad: bool = False, - keep_tmp: bool = False, - runner: Runner | None = None, -) -> VDiceMetricOutputs: - """ - Computes Dice Metric between BASE and each of the DSET volumes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - base: Name of base (reference) segmentation. - dsets: Data sets for which the Dice Metric with BASE is computed. This\ - should be the last option on the command line. - max_roi: The maximum possible ROI index. Default is 12 or based on\ - LTFILE if specified. - forceoutput: If given, force output for each class in LTFILE. - forceoutput_: If given, force output for each class in LTFILE. - echo: Set echo. - save_match: Save volume showing BASE*equals(BASE,DSET). - save_diff: Save volume showing BASE*(1-equals(BASE,DSET)). - do_not_mask_by_base: Do not mask dset by step(base) before computing\ - Dice coefficient. - mask_by_base: Mask dset by the step(base) before computing Dice\ - coefficient. - prefix: Use PREFIX for the output table. Default is separate results\ - for each dset to stdout. - ignore_bad: Warn if encountering bad scenarios, but do not create a\ - zero entry. - keep_tmp: Keep temporary files for debugging. Note that you should\ - delete temporary files before rerunning the script. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDiceMetricOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DICE_METRIC_METADATA) - cargs = [] - cargs.append("@DiceMetric") - cargs.extend([ - "-base", - execution.input_file(base) - ]) - cargs.extend([ - "-dsets", - *[execution.input_file(f) for f in dsets] - ]) - if max_roi is not None: - cargs.extend([ - "-max_N_roi", - str(max_roi) - ]) - if forceoutput is not None: - cargs.extend([ - "-forceoutput", - execution.input_file(forceoutput) - ]) - if forceoutput_ is not None: - cargs.extend([ - "-forceoutput", - execution.input_file(forceoutput_) - ]) - if echo: - cargs.append("-echo") - if save_match: - cargs.append("-save_match") - if save_diff: - cargs.append("-save_diff") - if do_not_mask_by_base: - cargs.append("-do_not_mask_by_base") - if mask_by_base: - cargs.append("-mask_by_base") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if ignore_bad: - cargs.append("-ignore_bad") - if keep_tmp: - cargs.append("-keep_tmp") - ret = VDiceMetricOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDiceMetricOutputs", - "V__DICE_METRIC_METADATA", - "v__dice_metric", -] diff --git a/python/src/niwrap/afni/v__diff_files.py b/python/src/niwrap/afni/v__diff_files.py deleted file mode 100644 index dd94ffe1a..000000000 --- a/python/src/niwrap/afni/v__diff_files.py +++ /dev/null @@ -1,108 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DIFF_FILES_METADATA = Metadata( - id="edd2d42b0097cf74079def4a47b5ad005afd8f78.boutiques", - name="@diff.files", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDiffFilesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__diff_files(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__diff_files( - files: list[str], - old_dir: str, - diff_opts: str | None = None, - diff_prog: str | None = None, - ignore_missing: bool = False, - longlist: bool = False, - save: bool = False, - show: bool = False, - xxdiff: bool = False, - x_flag: bool = False, - verbosity: float | None = None, - runner: Runner | None = None, -) -> VDiffFilesOutputs: - """ - Show file differences (between specified files and those in another directory). - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - files: List of files to compare. - old_dir: Directory containing the files to compare against. - diff_opts: Add options to diff command (e.g., -w). - diff_prog: Display diffs using a specified program (e.g., meld, xxdiff). - ignore_missing: Continue even if files are missing. - longlist: Run 'ls -l' on both directories instead of listing files. - save: Create PDFs of diffs. - show: Show diffs using 'diff'. - xxdiff: Show diffs using 'xxdiff'. - x_flag: Implies -xxdiff and -ignore_missing. - verbosity: Set verbosity level (2 or 3). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDiffFilesOutputs`). - """ - if verbosity is not None and not (1 <= verbosity <= 3): - raise ValueError(f"'verbosity' must be between 1 <= x <= 3 but was {verbosity}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__DIFF_FILES_METADATA) - cargs = [] - cargs.append("@diff.files") - cargs.extend(files) - cargs.append(old_dir) - if diff_opts is not None: - cargs.extend([ - "-diff_opts", - diff_opts - ]) - if diff_prog is not None: - cargs.extend([ - "-diff_prog", - diff_prog - ]) - if ignore_missing: - cargs.append("-ignore_missing") - if longlist: - cargs.append("-longlist") - if save: - cargs.append("-save") - if show: - cargs.append("-show") - if xxdiff: - cargs.append("-xxdiff") - if x_flag: - cargs.append("-X") - if verbosity is not None: - cargs.extend([ - "-verb", - str(verbosity) - ]) - ret = VDiffFilesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDiffFilesOutputs", - "V__DIFF_FILES_METADATA", - "v__diff_files", -] diff --git a/python/src/niwrap/afni/v__diff_tree.py b/python/src/niwrap/afni/v__diff_tree.py deleted file mode 100644 index 4017cf89b..000000000 --- a/python/src/niwrap/afni/v__diff_tree.py +++ /dev/null @@ -1,149 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DIFF_TREE_METADATA = Metadata( - id="11a09e53b48435f523465bdd52c5dc27b5e1cb04.boutiques", - name="@diff.tree", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDiffTreeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__diff_tree(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__diff_tree( - new_dir: str, - old_dir: str, - diff_opts: str | None = None, - ignore_append: str | None = None, - ia: str | None = None, - ignore_list: str | None = None, - il: str | None = None, - ignore_missing: bool = False, - no_diffs: bool = False, - quiet: bool = False, - save: bool = False, - show: bool = False, - show_list_comp: bool = False, - skip_data: bool = False, - verb: str | None = None, - diff_prog: str | None = None, - xxdiff: bool = False, - x_option: bool = False, - runner: Runner | None = None, -) -> VDiffTreeOutputs: - """ - Show file differences between 2 directories. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - new_dir: New directory to compare. - old_dir: Old directory to compare. - diff_opts: Apply OPTS as options in diff commands. - ignore_append: Append to ignore_list (list in quotes). - ia: Short for -ignore_append. - ignore_list: Create new ignore_list (list in quotes). - il: Short for -ignore_list. - ignore_missing: Only compare overlapping files, if different files,\ - fail. - no_diffs: Only compare existence of files. - quiet: Only list files with diffs. - save: Save actual file differences (txt and pdf). - show: Show actual file differences. - show_list_comp: Show any pairwise differences in file lists (terminate\ - after showing comparison). - skip_data: Skip binary diff of select data files (.BRIK, .dcm,\ - .BRIK.gz). - verb: Set verbosity level (0,1,2) (default 1). - diff_prog: Use PROG to show diffs (e.g. xxdiff, meld). - xxdiff: Use xxdiff to show diffs. - x_option: Implies -xxdiff -ignore_missing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDiffTreeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DIFF_TREE_METADATA) - cargs = [] - cargs.append("@diff.tree") - cargs.append(new_dir) - cargs.append(old_dir) - if diff_opts is not None: - cargs.extend([ - "-diff_opts", - diff_opts - ]) - if ignore_append is not None: - cargs.extend([ - "-ignore_append", - ignore_append - ]) - if ia is not None: - cargs.extend([ - "-ia", - ia - ]) - if ignore_list is not None: - cargs.extend([ - "-ignore_list", - ignore_list - ]) - if il is not None: - cargs.extend([ - "-il", - il - ]) - if ignore_missing: - cargs.append("-ignore_missing") - if no_diffs: - cargs.append("-no_diffs") - if quiet: - cargs.append("-quiet") - if save: - cargs.append("-save") - if show: - cargs.append("-show") - if show_list_comp: - cargs.append("-show_list_comp") - if skip_data: - cargs.append("-skip_data") - if verb is not None: - cargs.extend([ - "-verb", - verb - ]) - if diff_prog is not None: - cargs.extend([ - "-diff_prog", - diff_prog - ]) - if xxdiff: - cargs.append("-xxdiff") - if x_option: - cargs.append("-X") - ret = VDiffTreeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDiffTreeOutputs", - "V__DIFF_TREE_METADATA", - "v__diff_tree", -] diff --git a/python/src/niwrap/afni/v__djunct_4d_imager.py b/python/src/niwrap/afni/v__djunct_4d_imager.py deleted file mode 100644 index 41409ee13..000000000 --- a/python/src/niwrap/afni/v__djunct_4d_imager.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_4D_IMAGER_METADATA = Metadata( - id="bd2c4d28906cfd2cf3f2ad964cccb79356c459e9.boutiques", - name="@djunct_4d_imager", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunct4dImagerOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_4d_imager(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - onescl_png: OutputPathType - """Output montage image with constant brightness range""" - sepscl_png: OutputPathType - """Output montage image with varying brightness range""" - onescl_mpeg: OutputPathType - """Output movie with constant brightness range (one slice at a time)""" - sepscl_mpeg: OutputPathType - """Output movie with varying brightness range (one slice at a time)""" - onescl_gif: OutputPathType - """Output animated GIF with constant brightness range (one slice at a - time)""" - sepscl_gif: OutputPathType - """Output animated GIF with varying brightness range (one slice at a - time)""" - - -def v__djunct_4d_imager( - inset: InputPathType, - prefix: str, - do_movie: typing.Literal["MPEG", "AGIF"] | None = None, - no_clean: bool = False, - runner: Runner | None = None, -) -> VDjunct4dImagerOutputs: - """ - The program is useful for viewing the same slice across the 'time' dimension of - a 4D data set. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: ULay dataset, probably 4D (required). - prefix: Prefix for output files (required). - do_movie: Specify type of movie file. Options: MPEG, AGIF. - no_clean: Keep the final intermediate files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunct4dImagerOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_4D_IMAGER_METADATA) - cargs = [] - cargs.append("@djunct_4d_imager") - cargs.append(execution.input_file(inset)) - cargs.append(prefix) - if do_movie is not None: - cargs.extend([ - "-do_movie", - do_movie - ]) - if no_clean: - cargs.append("-no_clean") - ret = VDjunct4dImagerOutputs( - root=execution.output_file("."), - onescl_png=execution.output_file(prefix + "_onescl.png"), - sepscl_png=execution.output_file(prefix + "_sepscl.png"), - onescl_mpeg=execution.output_file(prefix + "_onescl.mpg"), - sepscl_mpeg=execution.output_file(prefix + "_sepscl.mpg"), - onescl_gif=execution.output_file(prefix + "_onescl.gif"), - sepscl_gif=execution.output_file(prefix + "_sepscl.gif"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunct4dImagerOutputs", - "V__DJUNCT_4D_IMAGER_METADATA", - "v__djunct_4d_imager", -] diff --git a/python/src/niwrap/afni/v__djunct_4d_slices_to_3d_vol.py b/python/src/niwrap/afni/v__djunct_4d_slices_to_3d_vol.py deleted file mode 100644 index 9c48fc4ff..000000000 --- a/python/src/niwrap/afni/v__djunct_4d_slices_to_3d_vol.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_4D_SLICES_TO_3D_VOL_METADATA = Metadata( - id="8d8b25bb61f82477360f8ede43990dc80402d458.boutiques", - name="@djunct_4d_slices_to_3d_vol", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunct4dSlicesTo3dVolOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_4d_slices_to_3d_vol(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output file generated by the tool""" - - -def v__djunct_4d_slices_to_3d_vol( - do_something: bool = False, - runner: Runner | None = None, -) -> VDjunct4dSlicesTo3dVolOutputs: - """ - Tool description goes here. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - do_something: Do something really useful. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunct4dSlicesTo3dVolOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_4D_SLICES_TO_3D_VOL_METADATA) - cargs = [] - cargs.append("@djunct_4d_slices_to_3d_vol") - if do_something: - cargs.append("-do-something") - ret = VDjunct4dSlicesTo3dVolOutputs( - root=execution.output_file("."), - outfile=execution.output_file("output_file"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunct4dSlicesTo3dVolOutputs", - "V__DJUNCT_4D_SLICES_TO_3D_VOL_METADATA", - "v__djunct_4d_slices_to_3d_vol", -] diff --git a/python/src/niwrap/afni/v__djunct_anonymize.py b/python/src/niwrap/afni/v__djunct_anonymize.py deleted file mode 100644 index 67779231e..000000000 --- a/python/src/niwrap/afni/v__djunct_anonymize.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_ANONYMIZE_METADATA = Metadata( - id="08092598b752b9fd2011da8ce44ca2cb1929ac90.boutiques", - name="@djunct_anonymize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctAnonymizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_anonymize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__djunct_anonymize( - input_: InputPathType, - add_note: str | None = None, - copy_to: InputPathType | None = None, - overwrite: bool = False, - runner: Runner | None = None, -) -> VDjunctAnonymizeOutputs: - """ - Helper program to anonymize files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Input dataset. - add_note: Add a note to the history after anonymizing. - copy_to: Copy the input to a new file, which is then anonymized. - overwrite: Overwrite the existing file if using -copy_to. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctAnonymizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_ANONYMIZE_METADATA) - cargs = [] - cargs.append("@djunct_anonymize") - cargs.append(execution.input_file(input_)) - if add_note is not None: - cargs.extend([ - "-add_note", - add_note - ]) - if copy_to is not None: - cargs.extend([ - "-copy_to", - execution.input_file(copy_to) - ]) - if overwrite: - cargs.append("-overwrite") - ret = VDjunctAnonymizeOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctAnonymizeOutputs", - "V__DJUNCT_ANONYMIZE_METADATA", - "v__djunct_anonymize", -] diff --git a/python/src/niwrap/afni/v__djunct_dwi_selector.py b/python/src/niwrap/afni/v__djunct_dwi_selector.py deleted file mode 100644 index f52576302..000000000 --- a/python/src/niwrap/afni/v__djunct_dwi_selector.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_DWI_SELECTOR_METADATA = Metadata( - id="322cd55e91869cfd3befcc11394010a6d10dddc6.boutiques", - name="@djunct_dwi_selector", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctDwiSelectorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_dwi_selector(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """The main output file""" - - -def v__djunct_dwi_selector( - dwi: InputPathType, - png: InputPathType, - outfile: str, - runner: Runner | None = None, -) -> VDjunctDwiSelectorOutputs: - """ - Selects DWI data and creates a representative image. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dwi: Input DWI file. - png: Output PNG image. - outfile: Path to the output file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctDwiSelectorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_DWI_SELECTOR_METADATA) - cargs = [] - cargs.append("@djunct_dwi_selector.tcsh") - cargs.append(execution.input_file(dwi)) - cargs.append(execution.input_file(png)) - cargs.append(outfile) - ret = VDjunctDwiSelectorOutputs( - root=execution.output_file("."), - outfile=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctDwiSelectorOutputs", - "V__DJUNCT_DWI_SELECTOR_METADATA", - "v__djunct_dwi_selector", -] diff --git a/python/src/niwrap/afni/v__djunct_edgy_align_check.py b/python/src/niwrap/afni/v__djunct_edgy_align_check.py deleted file mode 100644 index b7d1743ae..000000000 --- a/python/src/niwrap/afni/v__djunct_edgy_align_check.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_EDGY_ALIGN_CHECK_METADATA = Metadata( - id="6e6402be94f04390f2f7e2dd812c1c7ccc881b97.boutiques", - name="@djunct_edgy_align_check", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctEdgyAlignCheckOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_edgy_align_check(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__djunct_edgy_align_check( - ulay: str, - olay: str, - prefix: str, - set_dicom_xyz: list[float] | None = None, - box_focus_slices: str | None = None, - montgap: float | None = None, - montcolor: str | None = None, - cbar: str | None = None, - save_ftype: str | None = None, - umin_fac: float | None = None, - montx: float | None = None, - monty: float | None = None, - use_olay_grid: str | None = None, - label_mode: str | None = None, - ulay_range: list[float] | None = None, - ulay_range_nz: list[float] | None = None, - ulay_range_am: list[float] | None = None, - runner: Runner | None = None, -) -> VDjunctEdgyAlignCheckOutputs: - """ - Helper script for various tasks, heavily modeled on RW Cox's '@snapshot_volreg' - script. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - ulay: ULAY dataset. - olay: OLAY dataset. - prefix: Prefix for output files. - set_dicom_xyz: DICOM coordinates {XX YY ZZ}. - box_focus_slices: Dataset to focus slices. - montgap: Gap between slices in montage. - montcolor: Color for montage. - cbar: Color bar for overlay. - save_ftype: File type to save. - umin_fac: Scaling factor for underlay minimum. - montx: Number of slices in X-direction for montage. - monty: Number of slices in Y-direction for montage. - use_olay_grid: Grid interpolation method for overlay. - label_mode: Mode for labeling. - ulay_range: Range for underlay {umin umax}. - ulay_range_nz: Range for non-zero underlay {umin umax}. - ulay_range_am: Range for auto-mask underlay {umin umax}. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctEdgyAlignCheckOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_EDGY_ALIGN_CHECK_METADATA) - cargs = [] - cargs.append("@djunct_edgy_align_check") - cargs.append(ulay) - cargs.append(olay) - cargs.append(prefix) - if set_dicom_xyz is not None: - cargs.extend(map(str, set_dicom_xyz)) - if box_focus_slices is not None: - cargs.append(box_focus_slices) - if montgap is not None: - cargs.append(str(montgap)) - if montcolor is not None: - cargs.append(montcolor) - if cbar is not None: - cargs.append(cbar) - if save_ftype is not None: - cargs.append(save_ftype) - if umin_fac is not None: - cargs.append(str(umin_fac)) - if montx is not None: - cargs.append(str(montx)) - if monty is not None: - cargs.append(str(monty)) - if use_olay_grid is not None: - cargs.append(use_olay_grid) - if label_mode is not None: - cargs.append(label_mode) - cargs.append("[help_flag]") - cargs.append("[ver_flag]") - cargs.append("[echo_flag]") - cargs.append("[sharpen_ulay_off_flag]") - cargs.append("[mask_olay_edges_flag]") - cargs.append("[no_cor_flag]") - cargs.append("[no_sag_flag]") - cargs.append("[no_axi_flag]") - cargs.append("[no_clean_flag]") - if ulay_range is not None: - cargs.extend(map(str, ulay_range)) - if ulay_range_nz is not None: - cargs.extend(map(str, ulay_range_nz)) - if ulay_range_am is not None: - cargs.extend(map(str, ulay_range_am)) - ret = VDjunctEdgyAlignCheckOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctEdgyAlignCheckOutputs", - "V__DJUNCT_EDGY_ALIGN_CHECK_METADATA", - "v__djunct_edgy_align_check", -] diff --git a/python/src/niwrap/afni/v__djunct_modal_smoothing_with_rep.py b/python/src/niwrap/afni/v__djunct_modal_smoothing_with_rep.py deleted file mode 100644 index 8ba3631e6..000000000 --- a/python/src/niwrap/afni/v__djunct_modal_smoothing_with_rep.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_MODAL_SMOOTHING_WITH_REP_METADATA = Metadata( - id="48dc1b5524804bba87c6d83bc663f26d6dab2418.boutiques", - name="@djunct_modal_smoothing_with_rep", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctModalSmoothingWithRepOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_modal_smoothing_with_rep(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file_head: OutputPathType - """Output dataset after modal smoothing""" - output_file_brik: OutputPathType - """Output dataset after modal smoothing""" - - -def v__djunct_modal_smoothing_with_rep( - input_file: InputPathType, - output_prefix: str, - modesmooth: float | None = None, - help_view: bool = False, - help_: bool = False, - version: bool = False, - overwrite: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> VDjunctModalSmoothingWithRepOutputs: - """ - A script to perform modal smoothing of ROI maps and check for eliminated ROIs. - If any ROIs are eliminated during smoothing, they are restored, potentially in a - degraded form. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input dataset (assumes < 10^5 subbricks). - output_prefix: Prefix for output dataset. - modesmooth: Fill in X in: 3dLocalstat -nbhd "SPHERE(-X)" ... - help_view: Display help in a viewable format. - help_: Display help information. - version: Display version information. - overwrite: Overwrite existing output files. - no_clean: Do not clean up intermediate files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctModalSmoothingWithRepOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_MODAL_SMOOTHING_WITH_REP_METADATA) - cargs = [] - cargs.append("@djunct_modal_smoothing_with_rep") - cargs.append(execution.input_file(input_file)) - cargs.append(output_prefix) - if modesmooth is not None: - cargs.extend([ - "-modesmooth", - str(modesmooth) - ]) - if help_view: - cargs.append("-hview") - if help_: - cargs.append("-help") - if version: - cargs.append("-ver") - if overwrite: - cargs.append("-overwrite") - if no_clean: - cargs.append("-no_clean") - ret = VDjunctModalSmoothingWithRepOutputs( - root=execution.output_file("."), - output_file_head=execution.output_file(output_prefix + "+tlrc.HEAD"), - output_file_brik=execution.output_file(output_prefix + "+tlrc.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctModalSmoothingWithRepOutputs", - "V__DJUNCT_MODAL_SMOOTHING_WITH_REP_METADATA", - "v__djunct_modal_smoothing_with_rep", -] diff --git a/python/src/niwrap/afni/v__djunct_montage_coordinator.py b/python/src/niwrap/afni/v__djunct_montage_coordinator.py deleted file mode 100644 index 501205b05..000000000 --- a/python/src/niwrap/afni/v__djunct_montage_coordinator.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_MONTAGE_COORDINATOR_METADATA = Metadata( - id="f3048da50feab9a5431a35d3b1470ddb44c8feb7.boutiques", - name="@djunct_montage_coordinator", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctMontageCoordinatorOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_montage_coordinator(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_coords: OutputPathType - """Output coordinates (IJK or XYZ) for the montage setup.""" - - -def v__djunct_montage_coordinator( - input_file: InputPathType, - montx: float, - monty: float, - out_xyz: bool = False, - help_: bool = False, - version: bool = False, - runner: Runner | None = None, -) -> VDjunctMontageCoordinatorOutputs: - """ - Small program to calculate how to evenly space a certain number of slices within - each view plane of a dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Name of input dataset. - montx: Montage dimension: number of panels along x-axis (i.e., number\ - of cols). - monty: Montage dimension: number of panels along y-axis (i.e., number\ - of rows). - out_xyz: Make program output 'X Y Z' values. - help_: See helpfile. - version: See version number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctMontageCoordinatorOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_MONTAGE_COORDINATOR_METADATA) - cargs = [] - cargs.append("@djunct_montage_coordinator") - cargs.extend([ - "-inset", - execution.input_file(input_file) - ]) - cargs.extend([ - "-montx", - str(montx) - ]) - cargs.extend([ - "-monty", - str(monty) - ]) - if out_xyz: - cargs.append("-out_xyz") - if help_: - cargs.append("-help") - if version: - cargs.append("-ver") - ret = VDjunctMontageCoordinatorOutputs( - root=execution.output_file("."), - output_coords=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctMontageCoordinatorOutputs", - "V__DJUNCT_MONTAGE_COORDINATOR_METADATA", - "v__djunct_montage_coordinator", -] diff --git a/python/src/niwrap/afni/v__djunct_overlap_check.py b/python/src/niwrap/afni/v__djunct_overlap_check.py deleted file mode 100644 index a5ea01504..000000000 --- a/python/src/niwrap/afni/v__djunct_overlap_check.py +++ /dev/null @@ -1,187 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_OVERLAP_CHECK_METADATA = Metadata( - id="61eef1d6dc1535a1dc4452ab3c3b8b5da02a1e6d.boutiques", - name="@djunct_overlap_check", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctOverlapCheckOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_overlap_check(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__djunct_overlap_check( - ulay: InputPathType, - olay: InputPathType, - prefix: str, - box_focus_slices: InputPathType | None = None, - montgap: float | None = None, - montcolor: str | None = None, - cbar: str | None = None, - opacity: float | None = None, - zerocolor: str | None = None, - set_dicom_xyz: list[float] | None = None, - ulay_range: list[float] | None = None, - ulay_range_nz: list[float] | None = None, - montx: float | None = None, - monty: float | None = None, - montx_cat: float | None = None, - monty_cat: float | None = None, - label_mode: str | None = None, - pbar_posonly_off: bool = False, - edgy_ulay: bool = False, - set_dicom_xyz_off: bool = False, - no_cor: bool = False, - no_axi: bool = False, - no_sag: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> VDjunctOverlapCheckOutputs: - """ - A helper script for visualizing overlap between datasets in AFNI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - ulay: Dataset to use as the underlay (background). - olay: Dataset to use as the overlay (foreground). - prefix: Prefix for the output files. - box_focus_slices: Dataset for box focus slices. - montgap: Gap between montage slices. - montcolor: Color of the montage gap. - cbar: Colorbar for the overlay. - opacity: Opacity of the overlay. - zerocolor: Color for zero values. - set_dicom_xyz: Set DICOM coordinates for slice location. - ulay_range: Range for underlay values. - ulay_range_nz: Range for non-zero underlay values. - montx: Number of panels in X direction in montage. - monty: Number of panels in Y direction in montage. - montx_cat: Number of X panes per image in montage. - monty_cat: Number of Y panes per image in montage. - label_mode: Label mode. - pbar_posonly_off: Turn off position-only p-bar. - edgy_ulay: Edgify the underlay. - set_dicom_xyz_off: Turn off DICOM coordinates setting. - no_cor: Skip coronal slices. - no_axi: Skip axial slices. - no_sag: Skip sagittal slices. - no_clean: Do not clean up temporary files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctOverlapCheckOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_OVERLAP_CHECK_METADATA) - cargs = [] - cargs.append("@djunct_overlap_check") - cargs.append(execution.input_file(ulay)) - cargs.append(execution.input_file(olay)) - cargs.append(prefix) - if box_focus_slices is not None: - cargs.append(execution.input_file(box_focus_slices)) - if montgap is not None: - cargs.extend([ - "-montgap", - str(montgap) - ]) - if montcolor is not None: - cargs.extend([ - "-montcolor", - montcolor - ]) - if cbar is not None: - cargs.extend([ - "-cbar", - cbar - ]) - if opacity is not None: - cargs.extend([ - "-opacity", - str(opacity) - ]) - if zerocolor is not None: - cargs.extend([ - "-zerocolor", - zerocolor - ]) - if set_dicom_xyz is not None: - cargs.extend([ - "-set_dicom_xyz", - *map(str, set_dicom_xyz) - ]) - if ulay_range is not None: - cargs.extend([ - "-ulay_range", - *map(str, ulay_range) - ]) - if ulay_range_nz is not None: - cargs.extend([ - "-ulay_range_nz", - *map(str, ulay_range_nz) - ]) - if montx is not None: - cargs.extend([ - "-montx", - str(montx) - ]) - if monty is not None: - cargs.extend([ - "-monty", - str(monty) - ]) - if montx_cat is not None: - cargs.extend([ - "-montx_cat", - str(montx_cat) - ]) - if monty_cat is not None: - cargs.extend([ - "-monty_cat", - str(monty_cat) - ]) - if label_mode is not None: - cargs.extend([ - "-label_mode", - label_mode - ]) - if pbar_posonly_off: - cargs.append("-pbar_posonly_off") - if edgy_ulay: - cargs.append("-edgy_ulay") - if set_dicom_xyz_off: - cargs.append("-set_dicom_xyz_off") - if no_cor: - cargs.append("-no_cor") - if no_axi: - cargs.append("-no_axi") - if no_sag: - cargs.append("-no_sag") - if no_clean: - cargs.append("-no_clean") - ret = VDjunctOverlapCheckOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctOverlapCheckOutputs", - "V__DJUNCT_OVERLAP_CHECK_METADATA", - "v__djunct_overlap_check", -] diff --git a/python/src/niwrap/afni/v__djunct_ssw_intermed_edge_imgs.py b/python/src/niwrap/afni/v__djunct_ssw_intermed_edge_imgs.py deleted file mode 100644 index d7ad70523..000000000 --- a/python/src/niwrap/afni/v__djunct_ssw_intermed_edge_imgs.py +++ /dev/null @@ -1,131 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DJUNCT_SSW_INTERMED_EDGE_IMGS_METADATA = Metadata( - id="2bca379c9dd8353dbea05fedc86aa2835a2f2819.boutiques", - name="@djunct_ssw_intermed_edge_imgs", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDjunctSswIntermedEdgeImgsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__djunct_ssw_intermed_edge_imgs(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__djunct_ssw_intermed_edge_imgs( - prefix: str, - ulay: InputPathType, - olay: InputPathType, - box_focus_slices: str | None = None, - montgap: str | None = None, - cbar: str | None = None, - ulay_range: str | None = None, - montx: str | None = None, - monty: str | None = None, - help_view: bool = False, - help_: bool = False, - version: bool = False, - no_clean: bool = False, - runner: Runner | None = None, -) -> VDjunctSswIntermedEdgeImgsOutputs: - """ - Helper script to generate intermediate edge images for SSW-related processing. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Prefix for generated output files. - ulay: Underlay dataset. - olay: Overlay dataset. - box_focus_slices: Slices of interest for focus box. - montgap: Gap between montage slices. - cbar: Color bar specification for AFNI. - ulay_range: Range for underlay data mapping. - montx: Number of slices along x dimension in montage. - monty: Number of slices along y dimension in montage. - help_view: View help file in viewer. - help_: Displays help information. - version: Displays version information. - no_clean: Don't clean up intermediate files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDjunctSswIntermedEdgeImgsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DJUNCT_SSW_INTERMED_EDGE_IMGS_METADATA) - cargs = [] - cargs.append("@djunct_ssw_intermed_edge_imgs") - cargs.extend([ - "-prefix", - prefix - ]) - cargs.extend([ - "-ulay", - execution.input_file(ulay) - ]) - cargs.extend([ - "-olay", - execution.input_file(olay) - ]) - if box_focus_slices is not None: - cargs.extend([ - "-box_focus_slices", - box_focus_slices - ]) - if montgap is not None: - cargs.extend([ - "-montgap", - montgap - ]) - if cbar is not None: - cargs.extend([ - "-cbar", - cbar - ]) - if ulay_range is not None: - cargs.extend([ - "-ulay_range", - ulay_range - ]) - if montx is not None: - cargs.extend([ - "-montx", - montx - ]) - if monty is not None: - cargs.extend([ - "-monty", - monty - ]) - if help_view: - cargs.append("-hview") - if help_: - cargs.append("-help") - if version: - cargs.append("-ver") - if no_clean: - cargs.append("-no_clean") - ret = VDjunctSswIntermedEdgeImgsOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDjunctSswIntermedEdgeImgsOutputs", - "V__DJUNCT_SSW_INTERMED_EDGE_IMGS_METADATA", - "v__djunct_ssw_intermed_edge_imgs", -] diff --git a/python/src/niwrap/afni/v__do_examples.py b/python/src/niwrap/afni/v__do_examples.py deleted file mode 100644 index 7e4ca6de9..000000000 --- a/python/src/niwrap/afni/v__do_examples.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__DO_EXAMPLES_METADATA = Metadata( - id="538eacefe9e5af2072fbb4d26ece78b45d00afab.boutiques", - name="@DO.examples", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VDoExamplesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__do_examples(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_log: OutputPathType - """Output log file when running in auto test mode""" - - -def v__do_examples( - auto_test: bool = False, - runner: Runner | None = None, -) -> VDoExamplesOutputs: - """ - A script to illustrate the use of Displayable Objects in SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - auto_test: Run this script in test mode where user prompts are timed\ - out at 2 seconds, and the command output log is preserved in a file\ - called __testlog.txt. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VDoExamplesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__DO_EXAMPLES_METADATA) - cargs = [] - cargs.append("@DO.examples") - if auto_test: - cargs.append("-auto_test") - ret = VDoExamplesOutputs( - root=execution.output_file("."), - output_log=execution.output_file("__testlog.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VDoExamplesOutputs", - "V__DO_EXAMPLES_METADATA", - "v__do_examples", -] diff --git a/python/src/niwrap/afni/v__electro_grid.py b/python/src/niwrap/afni/v__electro_grid.py deleted file mode 100644 index 3881b516f..000000000 --- a/python/src/niwrap/afni/v__electro_grid.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ELECTRO_GRID_METADATA = Metadata( - id="8d964e948445e43b1078948d73794b4d6f87e09a.boutiques", - name="@ElectroGrid", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VElectroGridOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__electro_grid(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_surface: OutputPathType | None - """Output surface file""" - - -def v__electro_grid( - strip: int | None = None, - grid: list[int] | None = None, - prefix: str | None = None, - coords: InputPathType | None = None, - with_markers: bool = False, - echo: bool = False, - runner: Runner | None = None, -) -> VElectroGridOutputs: - """ - Creates a mesh representation of an electrode grid for use with SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - strip: Make an Nx strip (array) of electrodes. - grid: Make an Nx by Ny grid of electrodes. A node at (i,j) has a node\ - ID = i+Nx*j with 0<=i VExamineGenFeatDistsOutputs: - """ - Examine histograms produced by 3dGenFeatDists. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - features_dir: Output directory of 3dGenFeatDists. - wildcards: Wildcards used to select feature histograms under the\ - directory. - output_suffix: Output suffix, added to output images. Default is\ - 'nosuff'. - exclude_features: Exclude following features. String matching is\ - partial. - exclude_classes: Exclude following classes. String matching is partial. - output_dir: Output directory, default is the same as -fdir. - panels_horizontal: Set number of panels along the horizontal direction. - echo: Set echo. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VExamineGenFeatDistsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__EXAMINE_GEN_FEAT_DISTS_METADATA) - cargs = [] - cargs.append("@ExamineGenFeatDists") - cargs.append("-fdir") - cargs.extend([ - "-fdir", - features_dir - ]) - cargs.append("-fwild") - if wildcards is not None: - cargs.extend([ - "-fwild", - *wildcards - ]) - cargs.append("-suffix") - if output_suffix is not None: - cargs.extend([ - "-suffix", - output_suffix - ]) - cargs.append("-exfeat") - if exclude_features is not None: - cargs.extend([ - "-exfeat", - *exclude_features - ]) - cargs.append("-exclass") - if exclude_classes is not None: - cargs.extend([ - "-exclass", - *exclude_classes - ]) - cargs.append("-odir") - if output_dir is not None: - cargs.extend([ - "-odir", - output_dir - ]) - cargs.append("-nx") - if panels_horizontal is not None: - cargs.extend([ - "-nx", - str(panels_horizontal) - ]) - cargs.append("-echo") - if echo: - cargs.append("-echo") - cargs.append("-help") - if help_: - cargs.append("-help") - ret = VExamineGenFeatDistsOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VExamineGenFeatDistsOutputs", - "V__EXAMINE_GEN_FEAT_DISTS_METADATA", - "v__examine_gen_feat_dists", -] diff --git a/python/src/niwrap/afni/v__extract_meica_ortvec.py b/python/src/niwrap/afni/v__extract_meica_ortvec.py deleted file mode 100644 index 536b29105..000000000 --- a/python/src/niwrap/afni/v__extract_meica_ortvec.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__EXTRACT_MEICA_ORTVEC_METADATA = Metadata( - id="fac98a48e14c87361c42bae79b0be7419401be47.boutiques", - name="@extract_meica_ortvec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VExtractMeicaOrtvecOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__extract_meica_ortvec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output 1D ortvec file""" - - -def v__extract_meica_ortvec( - prefix: str, - meica_dir: str | None = None, - reject_ignored: int | None = None, - reject_midk: int | None = None, - work_dir: str | None = None, - verbosity: str | None = None, - runner: Runner | None = None, -) -> VExtractMeicaOrtvecOutputs: - """ - Project good MEICA components out of bad ones. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Name for output 1D ortvec file. - meica_dir: Directory for MEICA files. - reject_ignored: Do we reject ignored components (0=keep, 1=reject),\ - default is 0. - reject_midk: Do we reject midk components (0=keep, 1=reject), default\ - is 1. - work_dir: Sub-directory for work. - verbosity: Set verbosity level. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VExtractMeicaOrtvecOutputs`). - """ - if reject_ignored is not None and not (0 <= reject_ignored <= 1): - raise ValueError(f"'reject_ignored' must be between 0 <= x <= 1 but was {reject_ignored}") - if reject_midk is not None and not (0 <= reject_midk <= 1): - raise ValueError(f"'reject_midk' must be between 0 <= x <= 1 but was {reject_midk}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__EXTRACT_MEICA_ORTVEC_METADATA) - cargs = [] - cargs.append("@extract_meica_ortvec") - cargs.extend([ - "-prefix", - prefix - ]) - if meica_dir is not None: - cargs.extend([ - "-meica_dir", - meica_dir - ]) - if reject_ignored is not None: - cargs.extend([ - "-reject_ignored", - str(reject_ignored) - ]) - if reject_midk is not None: - cargs.extend([ - "-reject_midk", - str(reject_midk) - ]) - if work_dir is not None: - cargs.extend([ - "-work_dir", - work_dir - ]) - if verbosity is not None: - cargs.extend([ - "-verb", - verbosity - ]) - ret = VExtractMeicaOrtvecOutputs( - root=execution.output_file("."), - outfile=execution.output_file(prefix + ".1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VExtractMeicaOrtvecOutputs", - "V__EXTRACT_MEICA_ORTVEC_METADATA", - "v__extract_meica_ortvec", -] diff --git a/python/src/niwrap/afni/v__fast_roi.py b/python/src/niwrap/afni/v__fast_roi.py deleted file mode 100644 index ac480f529..000000000 --- a/python/src/niwrap/afni/v__fast_roi.py +++ /dev/null @@ -1,121 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FAST_ROI_METADATA = Metadata( - id="a9103cde8ec905ab8b9986de691baf45b33e4630.boutiques", - name="@fast_roi", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFastRoiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__fast_roi(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - roi_output: OutputPathType - """ROI output volume with the specified prefix.""" - - -def v__fast_roi( - region: list[str], - anat: InputPathType, - base: InputPathType, - roi_grid: InputPathType, - prefix: str, - drawn_roi: InputPathType | None = None, - anat_ns: InputPathType | None = None, - time_: bool = False, - twopass: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> VFastRoiOutputs: - """ - Creates Atlas-based ROI masked in ANAT's original space. The script executes - rapidly for realtime fMRI applications. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - region: Symbolic atlas-based region name. Use repeated instances to\ - specify a mask of numerous regions. Each region is assigned a power of\ - 2 integer in the output mask. - anat: ANAT is the volume to be put in standard space. If ANAT is\ - already in TLRC space, there is no need for -base option. - base: Name of the reference TLRC volume. - roi_grid: The volume that defines the final ROI's grid. - prefix: Prefix used to tag the names the ROIs output. - drawn_roi: A user drawn ROI in standard (tlrc) space. This ROI gets\ - added with the REGION ROI. - anat_ns: Same as -anat, but indicates that the skull has been removed\ - already. - time_: Output elapsed time reports. - twopass: Make TLRC transformation more robust. Use it if TLRC transform\ - step fails. - help_: Output help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFastRoiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FAST_ROI_METADATA) - cargs = [] - cargs.append("@fast_roi") - cargs.extend([ - "-region", - *region - ]) - if drawn_roi is not None: - cargs.extend([ - "-drawn_roi", - execution.input_file(drawn_roi) - ]) - cargs.extend([ - "-anat", - execution.input_file(anat) - ]) - if anat_ns is not None: - cargs.extend([ - "-anat_ns", - execution.input_file(anat_ns) - ]) - cargs.extend([ - "-base", - execution.input_file(base) - ]) - cargs.extend([ - "-roi_grid", - execution.input_file(roi_grid) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if time_: - cargs.append("--time") - if twopass: - cargs.append("--twopass") - if help_: - cargs.append("--help") - ret = VFastRoiOutputs( - root=execution.output_file("."), - roi_output=execution.output_file("ROI." + prefix + "+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFastRoiOutputs", - "V__FAST_ROI_METADATA", - "v__fast_roi", -] diff --git a/python/src/niwrap/afni/v__fat_tract_colorize.py b/python/src/niwrap/afni/v__fat_tract_colorize.py deleted file mode 100644 index b245ca668..000000000 --- a/python/src/niwrap/afni/v__fat_tract_colorize.py +++ /dev/null @@ -1,106 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FAT_TRACT_COLORIZE_METADATA = Metadata( - id="419b2426fef682d260fe27e3825ba60780b27064.boutiques", - name="@fat_tract_colorize", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFatTractColorizeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__fat_tract_colorize(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_hue_volume: OutputPathType - """HSL coloration volume file with four bricks from the V1 and FA volumes: - Hue, Saturation, Luminosity, and Brightness""" - output_iso_surface: OutputPathType - """Slightly smoothed isosurface file made by IsoSurface""" - output_iso_spec: OutputPathType - """Spec file made by quickspec""" - output_proj_surface: OutputPathType - """Projection of appropriate coloration onto the surface""" - - -def v__fat_tract_colorize( - in_fa: InputPathType, - in_v1: InputPathType, - in_tracts: str, - prefix: str, - in_ulay: InputPathType | None = None, - no_view: bool = False, - only_view: bool = False, - runner: Runner | None = None, -) -> VFatTractColorizeOutputs: - """ - Visualize tractographic output from 3dTrackID, particularly in probabilistic - mode. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - in_fa: FA values of the DT fitting, used to modulate the brightness of\ - the RGB coloration. - in_v1: First eigenvector of the DT fitting. A unit vector volume with 3\ - components (0-1 range). - in_tracts: The INDIMAP or PAIRMAP file output by 3dTrackID, specifying\ - the subbrick if >1 (e.g., NAME_INDIMAP+orig'[0]'). - prefix: Prefix for all output files. - in_ulay: Optional underlay dataset for AFNI/SUMA viewing. Default is to\ - use the FA dataset. - no_view: Turn off auto-running of AFNI_SUMA commands to view the output\ - immediately. - only_view: Only view the data with AFNI+SUMA, assuming the command has\ - been run before. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFatTractColorizeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FAT_TRACT_COLORIZE_METADATA) - cargs = [] - cargs.append("@fat_tract_colorize") - cargs.append("-in_fa") - cargs.append(execution.input_file(in_fa)) - cargs.append("-in_v1") - cargs.append(execution.input_file(in_v1)) - cargs.append("-in_tracts") - cargs.append(in_tracts) - cargs.append("-prefix") - cargs.append(prefix) - if in_ulay is not None: - cargs.extend([ - "-in_ulay", - execution.input_file(in_ulay) - ]) - if no_view: - cargs.append("-no_view") - if only_view: - cargs.append("-only_view") - ret = VFatTractColorizeOutputs( - root=execution.output_file("."), - output_hue_volume=execution.output_file(prefix + "_RGB_HUE.nii.gz"), - output_iso_surface=execution.output_file(prefix + "_RGB_iso.ply"), - output_iso_spec=execution.output_file(prefix + "_RGB_iso.spec"), - output_proj_surface=execution.output_file(prefix + "_RGB.niml.dset"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFatTractColorizeOutputs", - "V__FAT_TRACT_COLORIZE_METADATA", - "v__fat_tract_colorize", -] diff --git a/python/src/niwrap/afni/v__find_afni_dset_path.py b/python/src/niwrap/afni/v__find_afni_dset_path.py deleted file mode 100644 index 45f017f34..000000000 --- a/python/src/niwrap/afni/v__find_afni_dset_path.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FIND_AFNI_DSET_PATH_METADATA = Metadata( - id="dd1fcbc6d020074e2a73ad6f104cf658c6f5188f.boutiques", - name="@FindAfniDsetPath", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFindAfniDsetPathOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__find_afni_dset_path(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__find_afni_dset_path( - dsetname: str, - append_file: bool = False, - full_path: bool = False, - help_: bool = False, - runner: Runner | None = None, -) -> VFindAfniDsetPathOutputs: - """ - Searches various AFNI directories for a specified dataset and returns its path. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dsetname: Name of the dataset to search for. - append_file: Show the file appended to (even with atlas name). - full_path: Print full path instead of '.'. - help_: Display help message. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFindAfniDsetPathOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FIND_AFNI_DSET_PATH_METADATA) - cargs = [] - cargs.append("@FindAfniDsetPath") - cargs.append(dsetname) - if append_file: - cargs.append("-append_file") - if full_path: - cargs.append("-full_path") - if help_: - cargs.append("-help") - ret = VFindAfniDsetPathOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFindAfniDsetPathOutputs", - "V__FIND_AFNI_DSET_PATH_METADATA", - "v__find_afni_dset_path", -] diff --git a/python/src/niwrap/afni/v__fix_fssphere.py b/python/src/niwrap/afni/v__fix_fssphere.py deleted file mode 100644 index 51a643ac7..000000000 --- a/python/src/niwrap/afni/v__fix_fssphere.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FIX_FSSPHERE_METADATA = Metadata( - id="b742177d5b0ebe3a73650e2f92bfe87238f0bcca.boutiques", - name="@fix_FSsphere", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFixFssphereOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__fix_fssphere(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_surface: OutputPathType - """Corrected surface""" - - -def v__fix_fssphere( - spec_file: InputPathType, - sphere_file: InputPathType, - num_iterations: int | None = None, - extent_lim: float | None = None, - project_first: bool = False, - keep_temp: bool = False, - runner: Runner | None = None, -) -> VFixFssphereOutputs: - """ - Tool for fixing errors in FreeSurfer spherical surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - spec_file: Spec file. - sphere_file: SPHERE.asc is the sphere to be used. - num_iterations: Number of local smoothing operations. Default is 3000. - extent_lim: Extent, in mm, by which troubled sections are fattened.\ - Default is 6. - project_first: Project to a sphere, before smoothing. Default is 0. - keep_temp: Keep temporary files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFixFssphereOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FIX_FSSPHERE_METADATA) - cargs = [] - cargs.append("@fix_FSsphere") - cargs.extend([ - "-spec", - execution.input_file(spec_file) - ]) - cargs.extend([ - "-sphere", - execution.input_file(sphere_file) - ]) - if num_iterations is not None: - cargs.extend([ - "-niter", - str(num_iterations) - ]) - if extent_lim is not None: - cargs.extend([ - "-lim", - str(extent_lim) - ]) - if project_first: - cargs.append("-project_first") - if keep_temp: - cargs.append("-keep_temp") - ret = VFixFssphereOutputs( - root=execution.output_file("."), - corrected_surface=execution.output_file("[SPHERE]_fxd.asc"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFixFssphereOutputs", - "V__FIX_FSSPHERE_METADATA", - "v__fix_fssphere", -] diff --git a/python/src/niwrap/afni/v__float_fix.py b/python/src/niwrap/afni/v__float_fix.py deleted file mode 100644 index 2431f3a10..000000000 --- a/python/src/niwrap/afni/v__float_fix.py +++ /dev/null @@ -1,60 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FLOAT_FIX_METADATA = Metadata( - id="69c8566d3c52dcfb93a135adaaa38398077c4bc6.boutiques", - name="@float_fix", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFloatFixOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__float_fix(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__float_fix( - input_files: list[InputPathType], - runner: Runner | None = None, -) -> VFloatFixOutputs: - """ - Check whether the input files have any IEEE floating point numbers for illegal - values: infinities and not-a-number (NaN) values. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input files to be checked for illegal IEEE floating point\ - values. Wildcards can be used, but filenames must end with .HEAD. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFloatFixOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FLOAT_FIX_METADATA) - cargs = [] - cargs.append("@float_fix") - cargs.extend([execution.input_file(f) for f in input_files]) - ret = VFloatFixOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFloatFixOutputs", - "V__FLOAT_FIX_METADATA", - "v__float_fix", -] diff --git a/python/src/niwrap/afni/v__from_rai.py b/python/src/niwrap/afni/v__from_rai.py deleted file mode 100644 index 38f0df762..000000000 --- a/python/src/niwrap/afni/v__from_rai.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FROM_RAI_METADATA = Metadata( - id="56d1cf4aa050e32c8eaaa4d15256aa1725dd125d.boutiques", - name="@FromRAI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFromRaiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__from_rai(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__from_rai( - rai_coordinates: list[float], - orientation: str, - runner: Runner | None = None, -) -> VFromRaiOutputs: - """ - Changes the RAI coordinates to the specified orientation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - rai_coordinates: RAI coordinates X, Y, and Z. - orientation: Orientation format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFromRaiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FROM_RAI_METADATA) - cargs = [] - cargs.append("@FromRAI") - cargs.extend([ - "-xyz", - *map(str, rai_coordinates) - ]) - cargs.extend([ - "-or", - orientation - ]) - ret = VFromRaiOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFromRaiOutputs", - "V__FROM_RAI_METADATA", - "v__from_rai", -] diff --git a/python/src/niwrap/afni/v__fs_roi_label.py b/python/src/niwrap/afni/v__fs_roi_label.py deleted file mode 100644 index 08ff724dc..000000000 --- a/python/src/niwrap/afni/v__fs_roi_label.py +++ /dev/null @@ -1,121 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FS_ROI_LABEL_METADATA = Metadata( - id="1309e970f178ba30ffa735edd056d5c550b135f1.boutiques", - name="@FS_roi_label", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFsRoiLabelOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__fs_roi_label(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__fs_roi_label( - label_int: float | None = None, - lab_flag: float | None = None, - rank_int: float | None = None, - rankmap_file: InputPathType | None = None, - name: str | None = None, - labeltable_file: InputPathType | None = None, - surf_annot_cmap: InputPathType | None = None, - slab_int: float | None = None, - sname_name: str | None = None, - runner: Runner | None = None, -) -> VFsRoiLabelOutputs: - """ - Tool to get labels associated with FreeSurfer's parcellation and annotation - files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - label_int: Integer labeled area in FreeSurfer's parcellation. - lab_flag: Return the name of an integer labeled area in FreeSurfer's\ - parcellation. - rank_int: Return the name of ranked integer labeled area from the\ - output of 3dRank or 3dmerge -1rank. - rankmap_file: Path to the rank map file. - name: Return entries matching NAME (case insensitive, partial match)\ - from FreeSurfer's FreeSurferColorLUT.txt. - labeltable_file: Path to the label table file. - surf_annot_cmap: CMAP file output by FSread_annot's -roi_1D option. - slab_int: Return the name of an integer labeled area in FreeSurfer's\ - surface-based annotation. - sname_name: Return the entries matching NAME (case insensitive, partial\ - match) from the CMAP file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFsRoiLabelOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FS_ROI_LABEL_METADATA) - cargs = [] - cargs.append("@FS_roi_label") - if label_int is not None: - cargs.append(str(label_int)) - if lab_flag is not None: - cargs.extend([ - "-lab", - str(lab_flag) - ]) - if rank_int is not None: - cargs.extend([ - "-rank", - str(rank_int) - ]) - if rankmap_file is not None: - cargs.extend([ - "-rankmap", - execution.input_file(rankmap_file) - ]) - if name is not None: - cargs.extend([ - "-name", - name - ]) - if labeltable_file is not None: - cargs.extend([ - "-labeltable", - execution.input_file(labeltable_file) - ]) - if surf_annot_cmap is not None: - cargs.extend([ - "-surf_annot_cmap", - execution.input_file(surf_annot_cmap) - ]) - if slab_int is not None: - cargs.extend([ - "-slab", - str(slab_int) - ]) - if sname_name is not None: - cargs.extend([ - "-sname", - sname_name - ]) - ret = VFsRoiLabelOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFsRoiLabelOutputs", - "V__FS_ROI_LABEL_METADATA", - "v__fs_roi_label", -] diff --git a/python/src/niwrap/afni/v__fslabel2dset.py b/python/src/niwrap/afni/v__fslabel2dset.py deleted file mode 100644 index edaee1f0b..000000000 --- a/python/src/niwrap/afni/v__fslabel2dset.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__FSLABEL2DSET_METADATA = Metadata( - id="d0c250b2d9ce4006072d80b03d43f73189a4ea50.boutiques", - name="@FSlabel2dset", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VFslabel2dsetOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__fslabel2dset(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__fslabel2dset( - fs_label_file: InputPathType, - val: float | None = None, - help_: bool = False, - echo: bool = False, - keep_tmp: bool = False, - runner: Runner | None = None, -) -> VFslabel2dsetOutputs: - """ - A script to convert a FreeSurfer ASCII label file into a SUMA dataset and a SUMA - ROI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fs_label_file: Specify the ASCII label file from FreeSurfer. - val: Assign integer VAL to the nodes in FS_LABEL_FILE (Default is 1). - help_: Display help message. - echo: Turn echo for debugging. - keep_tmp: Don't cleanup temp files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VFslabel2dsetOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__FSLABEL2DSET_METADATA) - cargs = [] - cargs.append("@FSlabel2dset") - cargs.append("-fs") - cargs.extend([ - "-fs", - execution.input_file(fs_label_file) - ]) - cargs.append("-val") - if val is not None: - cargs.extend([ - "-val", - str(val) - ]) - if help_: - cargs.append("-help") - if echo: - cargs.append("-echo") - if keep_tmp: - cargs.append("-keep_tmp") - ret = VFslabel2dsetOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VFslabel2dsetOutputs", - "V__FSLABEL2DSET_METADATA", - "v__fslabel2dset", -] diff --git a/python/src/niwrap/afni/v__get_afni_dims.py b/python/src/niwrap/afni/v__get_afni_dims.py deleted file mode 100644 index be8800b36..000000000 --- a/python/src/niwrap/afni/v__get_afni_dims.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_DIMS_METADATA = Metadata( - id="f97a44456525900e074fddba78fb715ef2273d20.boutiques", - name="@GetAfniDims", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniDimsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_dims(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - dims_output: OutputPathType - """Text file containing the dimensions of the input dataset""" - - -def v__get_afni_dims( - input_dset: InputPathType, - runner: Runner | None = None, -) -> VGetAfniDimsOutputs: - """ - A utility tool to return dimensions of AFNI dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dset: Input AFNI dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniDimsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_DIMS_METADATA) - cargs = [] - cargs.append("@GetAfniDims") - cargs.append(execution.input_file(input_dset)) - ret = VGetAfniDimsOutputs( - root=execution.output_file("."), - dims_output=execution.output_file("dims_output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniDimsOutputs", - "V__GET_AFNI_DIMS_METADATA", - "v__get_afni_dims", -] diff --git a/python/src/niwrap/afni/v__get_afni_id.py b/python/src/niwrap/afni/v__get_afni_id.py deleted file mode 100644 index 419d48ac9..000000000 --- a/python/src/niwrap/afni/v__get_afni_id.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_ID_METADATA = Metadata( - id="dd714c32ee0347e743e97e9bb31e98977a041122.boutiques", - name="@GetAfniID", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniIdOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_id(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - unique_id: OutputPathType - """Unique identifier of the dataset""" - - -def v__get_afni_id( - dset: InputPathType, - runner: Runner | None = None, -) -> VGetAfniIdOutputs: - """ - Returns the unique identifier of a dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Dataset for which the unique identifier is to be returned. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniIdOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_ID_METADATA) - cargs = [] - cargs.append("@GetAfniID") - cargs.append(execution.input_file(dset)) - ret = VGetAfniIdOutputs( - root=execution.output_file("."), - unique_id=execution.output_file("stdout"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniIdOutputs", - "V__GET_AFNI_ID_METADATA", - "v__get_afni_id", -] diff --git a/python/src/niwrap/afni/v__get_afni_orient.py b/python/src/niwrap/afni/v__get_afni_orient.py deleted file mode 100644 index 1d90ae476..000000000 --- a/python/src/niwrap/afni/v__get_afni_orient.py +++ /dev/null @@ -1,65 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_ORIENT_METADATA = Metadata( - id="eb6a37f8f5592ce57e59b803920fbfd554fdd7f2.boutiques", - name="@GetAfniOrient", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniOrientOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_orient(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_orient_code: OutputPathType - """File containing the orientation code""" - - -def v__get_afni_orient( - infile: InputPathType, - exploratory: bool = False, - runner: Runner | None = None, -) -> VGetAfniOrientOutputs: - """ - Returns the orient code of AFNI datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input AFNI dataset (e.g. Hello+orig.HEAD). - exploratory: Exploratory flag for additional functionalities. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniOrientOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_ORIENT_METADATA) - cargs = [] - cargs.append("@GetAfniOrient") - if exploratory: - cargs.append("-exp") - cargs.append(execution.input_file(infile)) - ret = VGetAfniOrientOutputs( - root=execution.output_file("."), - output_orient_code=execution.output_file(pathlib.Path(infile).name + "_orient_code.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniOrientOutputs", - "V__GET_AFNI_ORIENT_METADATA", - "v__get_afni_orient", -] diff --git a/python/src/niwrap/afni/v__get_afni_prefix.py b/python/src/niwrap/afni/v__get_afni_prefix.py deleted file mode 100644 index 745407915..000000000 --- a/python/src/niwrap/afni/v__get_afni_prefix.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_PREFIX_METADATA = Metadata( - id="ae0f36ac76fa0ee57fb99900eaf3197e4b29bbf6.boutiques", - name="@GetAfniPrefix", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniPrefixOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_prefix(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__get_afni_prefix( - name: InputPathType, - suffix: str | None = None, - runner: Runner | None = None, -) -> VGetAfniPrefixOutputs: - """ - A tool to extract AFNI prefix from a given file path. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - name: Input file path for which the AFNI prefix will be extracted. - suffix: Suffix string to append to the returned prefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniPrefixOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_PREFIX_METADATA) - cargs = [] - cargs.append("@GetAfniPrefix") - cargs.append(execution.input_file(name)) - if suffix is not None: - cargs.append(suffix) - ret = VGetAfniPrefixOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniPrefixOutputs", - "V__GET_AFNI_PREFIX_METADATA", - "v__get_afni_prefix", -] diff --git a/python/src/niwrap/afni/v__get_afni_res.py b/python/src/niwrap/afni/v__get_afni_res.py deleted file mode 100644 index 6ef26eb20..000000000 --- a/python/src/niwrap/afni/v__get_afni_res.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_RES_METADATA = Metadata( - id="7f4762e356d51415e08e98ceebe347dba4909961.boutiques", - name="@GetAfniRes", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniResOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_res(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__get_afni_res( - input_dataset: InputPathType, - output_type: typing.Literal["-min", "-max", "-mean"] | None = None, - runner: Runner | None = None, -) -> VGetAfniResOutputs: - """ - Tool to return the voxel resolution of a dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset. - output_type: Output type specifying whether to return the minimum,\ - maximum, or mean resolution. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniResOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_RES_METADATA) - cargs = [] - cargs.append("@GetAfniRes") - if output_type is not None: - cargs.append(output_type) - cargs.append(execution.input_file(input_dataset)) - ret = VGetAfniResOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniResOutputs", - "V__GET_AFNI_RES_METADATA", - "v__get_afni_res", -] diff --git a/python/src/niwrap/afni/v__get_afni_version.py b/python/src/niwrap/afni/v__get_afni_version.py deleted file mode 100644 index 0cedb74e9..000000000 --- a/python/src/niwrap/afni/v__get_afni_version.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_VERSION_METADATA = Metadata( - id="00b4038dc7dd30e795e94e467e6a777717d8d741.boutiques", - name="@get.afni.version", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniVersionOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_version(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - src_dir: OutputPathType - """Directory containing the downloaded AFNI source code for the specified - version.""" - - -def v__get_afni_version( - version: str, - runner: Runner | None = None, -) -> VGetAfniVersionOutputs: - """ - Downloads the source code for a specified AFNI version. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - version: AFNI version number to get (e.g., 16.0.01). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniVersionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_VERSION_METADATA) - cargs = [] - cargs.append("@get.afni.version") - cargs.append(version) - ret = VGetAfniVersionOutputs( - root=execution.output_file("."), - src_dir=execution.output_file("AFNI_" + version + "/AFNI/src"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniVersionOutputs", - "V__GET_AFNI_VERSION_METADATA", - "v__get_afni_version", -] diff --git a/python/src/niwrap/afni/v__get_afni_view.py b/python/src/niwrap/afni/v__get_afni_view.py deleted file mode 100644 index aa28345e5..000000000 --- a/python/src/niwrap/afni/v__get_afni_view.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GET_AFNI_VIEW_METADATA = Metadata( - id="b44ca052f95999a3103f1c034eafbccc904bf06c.boutiques", - name="@GetAfniView", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGetAfniViewOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__get_afni_view(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - afni_view: OutputPathType - """The AFNI view extension retrieved from the dataset name""" - - -def v__get_afni_view( - dataset_name: str, - runner: Runner | None = None, -) -> VGetAfniViewOutputs: - """ - A tool to retrieve the AFNI view of a given dataset name. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dataset_name: Name of the dataset (including path) from which to\ - retrieve the AFNI view (+orig, +acpc, etc.). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGetAfniViewOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GET_AFNI_VIEW_METADATA) - cargs = [] - cargs.append("@GetAfniView") - cargs.append(dataset_name) - ret = VGetAfniViewOutputs( - root=execution.output_file("."), - afni_view=execution.output_file("view_extension.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGetAfniViewOutputs", - "V__GET_AFNI_VIEW_METADATA", - "v__get_afni_view", -] diff --git a/python/src/niwrap/afni/v__grad_flip_test.py b/python/src/niwrap/afni/v__grad_flip_test.py deleted file mode 100644 index f857efccc..000000000 --- a/python/src/niwrap/afni/v__grad_flip_test.py +++ /dev/null @@ -1,160 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GRAD_FLIP_TEST_METADATA = Metadata( - id="210fc606c6595f8a6ddeb4428fbcf9ed120ad2c4.boutiques", - name="@GradFlipTest", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGradFlipTestOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__grad_flip_test(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Text file that stores recommended flip option""" - temp_directory: OutputPathType - """Temporary working directory to store intermediate files""" - - -def v__grad_flip_test( - dwi: InputPathType, - grad_col_mat_t: InputPathType | None = None, - grad_col_mat_t_: InputPathType | None = None, - grad_col_mat_t_2: InputPathType | None = None, - grad_col_mat_t_3: InputPathType | None = None, - mask: InputPathType | None = None, - bvals: InputPathType | None = None, - thresh_fa: float | None = None, - thresh_len: float | None = None, - prefix: str | None = None, - check_abs_min: float | None = None, - scale_out_1000: bool = False, - wdir: str | None = None, - do_clean: bool = False, - runner: Runner | None = None, -) -> VGradFlipTestOutputs: - """ - Script to test the correct flip for a data set when using 1dDW_Grad_o_Mat++. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dwi: Set of DWIs (N total volumes). - grad_col_mat_t: Set of column-wise g- or b-matrix elements\ - ("TORTOISE"-style format, "row-first"). - grad_col_mat_t_: Set of column-wise g- or b-matrix elements\ - ("TORTOISE"-style format, "row-first"). - grad_col_mat_t_2: Set of column-wise g- or b-matrix elements\ - ("TORTOISE"-style format, "row-first"). - grad_col_mat_t_3: Set of column-wise g- or b-matrix elements\ - ("TORTOISE"-style format, "row-first"). - mask: Optional mask (probably whole brain); otherwise, automasking is\ - performed. - bvals: Can input bvals, if necessary (but shouldn't be necessary?). - thresh_fa: Set minimum FA value for tracking (default X=0.2). - thresh_len: Set minimum tract length to keep a tract when propagating\ - (default L=30mm). - prefix: Output name of text file that stores recommended flip option. - check_abs_min: Handle tiny negative values in gradient vectors. - scale_out_1000: Scale output to 1000, as in 3dDWItoDT (probably not\ - necessary). - wdir: Rename working directory output; useful if running multiple\ - iterations. - do_clean: Remove temporary directory. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGradFlipTestOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GRAD_FLIP_TEST_METADATA) - cargs = [] - cargs.append("@GradFlipTest") - cargs.extend([ - "-in_dwi", - execution.input_file(dwi) - ]) - if grad_col_mat_t is not None: - cargs.extend([ - "-in_col_matT", - execution.input_file(grad_col_mat_t) - ]) - if grad_col_mat_t_ is not None: - cargs.extend([ - "-in_col_matT", - execution.input_file(grad_col_mat_t_) - ]) - if grad_col_mat_t_2 is not None: - cargs.extend([ - "-in_col_matT", - execution.input_file(grad_col_mat_t_2) - ]) - if grad_col_mat_t_3 is not None: - cargs.extend([ - "-in_col_matT", - execution.input_file(grad_col_mat_t_3) - ]) - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if bvals is not None: - cargs.extend([ - "-in_bvals", - execution.input_file(bvals) - ]) - if thresh_fa is not None: - cargs.extend([ - "-alg_Thresh_FA", - str(thresh_fa) - ]) - if thresh_len is not None: - cargs.extend([ - "-alg_Thresh_Len", - str(thresh_len) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if check_abs_min is not None: - cargs.extend([ - "-check_abs_min", - str(check_abs_min) - ]) - if scale_out_1000: - cargs.append("-scale_out_1000") - if wdir is not None: - cargs.extend([ - "-wdir", - wdir - ]) - if do_clean: - cargs.append("-do_clean") - ret = VGradFlipTestOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".txt") if (prefix is not None) else None, - temp_directory=execution.output_file("_tmp_TESTFLIP"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGradFlipTestOutputs", - "V__GRAD_FLIP_TEST_METADATA", - "v__grad_flip_test", -] diff --git a/python/src/niwrap/afni/v__grayplot.py b/python/src/niwrap/afni/v__grayplot.py deleted file mode 100644 index 78d153edd..000000000 --- a/python/src/niwrap/afni/v__grayplot.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__GRAYPLOT_METADATA = Metadata( - id="a79d52434d1f28bc1368da93681c4dcd66c5d2fd.boutiques", - name="@grayplot", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VGrayplotOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__grayplot(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - grayplot_img: OutputPathType - """Output grayplot image""" - - -def v__grayplot( - dirname: str, - allorder: bool = False, - runner: Runner | None = None, -) -> VGrayplotOutputs: - """ - Script to read files from an afni_proc.py results directory and produce a - grayplot from the errts dataset(s), combined with a motion magnitude indicator - graph. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dirname: Directory containing afni_proc.py results. - allorder: Create grayplots for all ordering methods. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VGrayplotOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__GRAYPLOT_METADATA) - cargs = [] - cargs.append("@grayplot") - cargs.append(dirname) - if allorder: - cargs.append("-ALLorder") - ret = VGrayplotOutputs( - root=execution.output_file("."), - grayplot_img=execution.output_file("Grayplot.errts.*.png"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VGrayplotOutputs", - "V__GRAYPLOT_METADATA", - "v__grayplot", -] diff --git a/python/src/niwrap/afni/v__help_afni.py b/python/src/niwrap/afni/v__help_afni.py deleted file mode 100644 index 8e42b4e56..000000000 --- a/python/src/niwrap/afni/v__help_afni.py +++ /dev/null @@ -1,56 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__HELP_AFNI_METADATA = Metadata( - id="0da8970548aba50182152f89948bd1dc8d152c37.boutiques", - name="@help.AFNI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VHelpAfniOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__help_afni(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__help_afni( - runner: Runner | None = None, -) -> VHelpAfniOutputs: - """ - A script to retrieve and search AFNI's help page for all programs. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VHelpAfniOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__HELP_AFNI_METADATA) - cargs = [] - cargs.append("@help.AFNI") - cargs.append("[OPTIONS]") - ret = VHelpAfniOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VHelpAfniOutputs", - "V__HELP_AFNI_METADATA", - "v__help_afni", -] diff --git a/python/src/niwrap/afni/v__is_oblique.py b/python/src/niwrap/afni/v__is_oblique.py deleted file mode 100644 index 42e777b3d..000000000 --- a/python/src/niwrap/afni/v__is_oblique.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__IS_OBLIQUE_METADATA = Metadata( - id="54857cd8a0a9212b334725fe8970cb7791379363.boutiques", - name="@isOblique", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VIsObliqueOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__is_oblique(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - result: OutputPathType - """Output result indicating if the file is oblique or plumb""" - - -def v__is_oblique( - infile: InputPathType, - runner: Runner | None = None, -) -> VIsObliqueOutputs: - """ - Determine if a file is oblique or plumb. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input file (e.g., Hello+orig.HEAD). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VIsObliqueOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__IS_OBLIQUE_METADATA) - cargs = [] - cargs.append("@isOblique") - cargs.append(execution.input_file(infile)) - ret = VIsObliqueOutputs( - root=execution.output_file("."), - result=execution.output_file("oblique_check_result.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VIsObliqueOutputs", - "V__IS_OBLIQUE_METADATA", - "v__is_oblique", -] diff --git a/python/src/niwrap/afni/v__iso_masks.py b/python/src/niwrap/afni/v__iso_masks.py deleted file mode 100644 index bc365a143..000000000 --- a/python/src/niwrap/afni/v__iso_masks.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ISO_MASKS_METADATA = Metadata( - id="b73304663d5c985016c46fca12dbb67249f9bdf2.boutiques", - name="@IsoMasks", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VIsoMasksOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__iso_masks(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__iso_masks( - input_dataset: InputPathType, - isovals: list[float] | None = None, - runner: Runner | None = None, -) -> VIsoMasksOutputs: - """ - Creates isosurfaces from isovolume envelopes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset for creating isosurfaces. - isovals: Isovalue thresholds for creating isosurfaces. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VIsoMasksOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ISO_MASKS_METADATA) - cargs = [] - cargs.append("@IsoMasks") - cargs.append("-mask") - cargs.extend([ - "-mask", - execution.input_file(input_dataset) - ]) - if isovals is not None: - cargs.extend(map(str, isovals)) - ret = VIsoMasksOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VIsoMasksOutputs", - "V__ISO_MASKS_METADATA", - "v__iso_masks", -] diff --git a/python/src/niwrap/afni/v__make_label_table.py b/python/src/niwrap/afni/v__make_label_table.py deleted file mode 100644 index 872bd7b95..000000000 --- a/python/src/niwrap/afni/v__make_label_table.py +++ /dev/null @@ -1,283 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MAKE_LABEL_TABLE_METADATA = Metadata( - id="ed5ca968ee83794fda1307ebaf226a6eedebf580.boutiques", - name="@MakeLabelTable", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMakeLabelTableOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__make_label_table(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_labeltable: OutputPathType - """Output label table file""" - output_atlas_pointlist: OutputPathType | None - """Output atlas point list file""" - output_csv: OutputPathType | None - """Output CSV file from label table""" - output_niml_atlas: OutputPathType | None - """Output NIML file after atlasizing labeled dataset""" - - -def v__make_label_table( - labeltable: str, - atlas_pointlist: str | None = None, - lab_r: list[str] | None = None, - lab_v: list[str] | None = None, - lab_file: list[str] | None = None, - dset: InputPathType | None = None, - longnames: float | None = None, - last_longname_col: float | None = None, - centers: bool = False, - centertype: str | None = None, - centermask: str | None = None, - skip_novoxels: bool = False, - all_labels: bool = False, - all_keys: bool = False, - lkeys: str | None = None, - rkeys: str | None = None, - klabel: str | None = None, - match_label: str | None = None, - labeltable_of_dset: InputPathType | None = None, - word_label_match: bool = False, - quiet_death: bool = False, - lt_to_atlas_pl: str | None = None, - dset_lt_to_atlas_pl: list[InputPathType] | None = None, - lt_to_csv: InputPathType | None = None, - atlasize_labeled_dset: InputPathType | None = None, - atlas_file: str | None = None, - atlas_name: str | None = None, - atlas_description: str | None = None, - replace: bool = False, - add_atlas_dset: InputPathType | None = None, - h_web: bool = False, - h_view: bool = False, - all_opts: bool = False, - h_find: str | None = None, - runner: Runner | None = None, -) -> VMakeLabelTableOutputs: - """ - Script used to create, modify, and transform label tables. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - labeltable: Name of output label table. - atlas_pointlist: Instead of a label table, produce an atlas point list. - lab_r: Define a label with its minimum and maximum key values. - lab_v: Define a label and its value. - lab_file: Specify labels and keys from a text file. - dset: Attach the label table (or atlas point list) to dataset. - longnames: Allow for another column of long names for regions. - last_longname_col: Limit long names to nth column. - centers: Compute center of mass location for each ROI. - centertype: Different ways to compute centers (Icent, Dcent, cm). - centermask: Calculate center of mass locations using a subset of voxels. - skip_novoxels: Skip regions without voxels. - all_labels: Return a listing of all labels. - all_keys: Return a listing of all keys. - lkeys: Return the keys whose labels match a given label. - rkeys: Return the range (min max) of keys whose labels match a given\ - label. - klabel: Return the label associated with a given key. - match_label: Return labels matching a given label. - labeltable_of_dset: Dump the labeltable from a dataset. - word_label_match: Use word matching for labels. - quiet_death: Do not give error messages when failing. - lt_to_atlas_pl: Transform Label Table to Atlas Point List. - dset_lt_to_atlas_pl: Get Label Table in dataset and write as an Atlas\ - Point List. - lt_to_csv: Transform Label Table to CSV format. - atlasize_labeled_dset: Transform a labeled ROI dataset into an atlas. - atlas_file: Specify the name of the NIML file where atlas attributes\ - are stored. - atlas_name: Name of the Atlas. - atlas_description: Description of the Atlas, which appears in AFNI's\ - whereami window. - replace: Replace existing Atlas if the name already exists in the NIML\ - file. - add_atlas_dset: Add an existing atlas to an atlas file. - h_web: Open webpage with help for this program. - h_view: Open -help output in a GUI editor. - all_opts: List all of the options for this script. - h_find: Search for lines containing a specific word in the help output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMakeLabelTableOutputs`). - """ - if lab_file is not None and not (1 <= len(lab_file) <= 2): - raise ValueError(f"Length of 'lab_file' must be between 1 and 2 but was {len(lab_file)}") - if dset_lt_to_atlas_pl is not None and (len(dset_lt_to_atlas_pl) != 2): - raise ValueError(f"Length of 'dset_lt_to_atlas_pl' must be 2 but was {len(dset_lt_to_atlas_pl)}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__MAKE_LABEL_TABLE_METADATA) - cargs = [] - cargs.append("@MakeLabelTable") - cargs.extend([ - "-labeltable", - labeltable - ]) - if atlas_pointlist is not None: - cargs.extend([ - "-atlas_pointlist", - atlas_pointlist - ]) - if lab_r is not None: - cargs.extend([ - "-lab_r", - *lab_r - ]) - if lab_v is not None: - cargs.extend([ - "-lab_v", - *lab_v - ]) - if lab_file is not None: - cargs.extend([ - "-lab_file", - *lab_file - ]) - if dset is not None: - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if longnames is not None: - cargs.extend([ - "-longnames", - str(longnames) - ]) - if last_longname_col is not None: - cargs.extend([ - "-last_longname_col", - str(last_longname_col) - ]) - if centers: - cargs.append("-centers") - if centertype is not None: - cargs.extend([ - "-centertype", - centertype - ]) - if centermask is not None: - cargs.extend([ - "-centermask", - centermask - ]) - if skip_novoxels: - cargs.append("-skip_novoxels") - if all_labels: - cargs.append("-all_labels") - if all_keys: - cargs.append("-all_keys") - if lkeys is not None: - cargs.extend([ - "-lkeys", - lkeys - ]) - if rkeys is not None: - cargs.extend([ - "-rkeys", - rkeys - ]) - if klabel is not None: - cargs.extend([ - "-klabel", - klabel - ]) - if match_label is not None: - cargs.extend([ - "-match_label", - match_label - ]) - if labeltable_of_dset is not None: - cargs.extend([ - "-labeltable_of_dset", - execution.input_file(labeltable_of_dset) - ]) - if word_label_match: - cargs.append("-word_label_match") - if quiet_death: - cargs.append("-quiet_death") - if lt_to_atlas_pl is not None: - cargs.extend([ - "-LT_to_atlas_PL", - lt_to_atlas_pl - ]) - if dset_lt_to_atlas_pl is not None: - cargs.extend([ - "-dset_LT_to_atlas_PL", - *[execution.input_file(f) for f in dset_lt_to_atlas_pl] - ]) - if lt_to_csv is not None: - cargs.extend([ - "-LT_to_CSV", - execution.input_file(lt_to_csv) - ]) - if atlasize_labeled_dset is not None: - cargs.extend([ - "-atlasize_labeled_dset", - execution.input_file(atlasize_labeled_dset) - ]) - if atlas_file is not None: - cargs.extend([ - "-atlas_file", - atlas_file - ]) - if atlas_name is not None: - cargs.extend([ - "-atlas_name", - atlas_name - ]) - if atlas_description is not None: - cargs.extend([ - "-atlas_description", - atlas_description - ]) - if replace: - cargs.append("-replace") - if add_atlas_dset is not None: - cargs.extend([ - "-add_atlas_dset", - execution.input_file(add_atlas_dset) - ]) - if h_web: - cargs.append("-h_web") - if h_view: - cargs.append("-h_view") - if all_opts: - cargs.append("-all_opts") - if h_find is not None: - cargs.extend([ - "-h_find", - h_find - ]) - ret = VMakeLabelTableOutputs( - root=execution.output_file("."), - output_labeltable=execution.output_file(labeltable + ".niml.lt"), - output_atlas_pointlist=execution.output_file(atlas_pointlist + ".niml.atlas") if (atlas_pointlist is not None) else None, - output_csv=execution.output_file(pathlib.Path(lt_to_csv).name + ".csv") if (lt_to_csv is not None) else None, - output_niml_atlas=execution.output_file(pathlib.Path(atlasize_labeled_dset).name + ".niml") if (atlasize_labeled_dset is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMakeLabelTableOutputs", - "V__MAKE_LABEL_TABLE_METADATA", - "v__make_label_table", -] diff --git a/python/src/niwrap/afni/v__make_plug_diff.py b/python/src/niwrap/afni/v__make_plug_diff.py deleted file mode 100644 index 8a07a9478..000000000 --- a/python/src/niwrap/afni/v__make_plug_diff.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MAKE_PLUG_DIFF_METADATA = Metadata( - id="04657da55e97a5ef906b2bfec20e16f6d1e28b7b.boutiques", - name="@make_plug_diff", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMakePlugDiffOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__make_plug_diff(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__make_plug_diff( - vtk_dir: str, - xm_dir: str, - afni_src_dir: str, - afni_bin_dir: str, - diff_dir: str, - comments: bool = False, - linux: bool = False, - runner: Runner | None = None, -) -> VMakePlugDiffOutputs: - """ - Compiles AFNI's diffusion plugin. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - vtk_dir: Directory where vtk is installed. - xm_dir: Directory where motif is installed. - afni_src_dir: Full path to AFNI's src/ directory. - afni_bin_dir: Path, relative to ASRCDIR, to abin. - diff_dir: Name of directory containing diffusion code. - comments: Output comments only. - linux: Flag for doing linuxy things. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMakePlugDiffOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__MAKE_PLUG_DIFF_METADATA) - cargs = [] - cargs.append("@make_plug_diff") - cargs.append("-vtk") - cargs.extend([ - "-vtk", - vtk_dir - ]) - cargs.append("-xm") - cargs.extend([ - "-xm", - xm_dir - ]) - cargs.append("-asrc") - cargs.extend([ - "-asrc", - afni_src_dir - ]) - cargs.append("-abin") - cargs.extend([ - "-abin", - afni_bin_dir - ]) - if comments: - cargs.append("-comments") - if linux: - cargs.append("-linux") - cargs.extend([ - "-diff", - diff_dir - ]) - ret = VMakePlugDiffOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMakePlugDiffOutputs", - "V__MAKE_PLUG_DIFF_METADATA", - "v__make_plug_diff", -] diff --git a/python/src/niwrap/afni/v__measure_bb_thick.py b/python/src/niwrap/afni/v__measure_bb_thick.py deleted file mode 100644 index 48a3ad5bd..000000000 --- a/python/src/niwrap/afni/v__measure_bb_thick.py +++ /dev/null @@ -1,160 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MEASURE_BB_THICK_METADATA = Metadata( - id="cfc08b06be4be34dbe86515a4f42ca26d14b7282.boutiques", - name="@measure_bb_thick", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMeasureBbThickOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__measure_bb_thick(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - maxfill: OutputPathType | None - """Thickness/depth dataset""" - bb_thick: OutputPathType | None - """Volumetric thickness dataset""" - bb_thick_smooth: OutputPathType | None - """Smoothed volumetric thickness dataset""" - bb_thick_niml: OutputPathType | None - """Unsmoothed thickness mapped to surface nodes""" - bb_thick_smooth_niml: OutputPathType | None - """Smoothed thickness mapped to surface nodes""" - maskset_output: OutputPathType | None - """Mask dataset""" - maskset_resampled: OutputPathType | None - """Resampled mask dataset""" - anat_surface: OutputPathType | None - """Surface representation of mask volume""" - quick_spec: OutputPathType | None - """Simple specification file for surface to use with suma commands""" - - -def v__measure_bb_thick( - maskset: InputPathType, - surfset: InputPathType, - outdir: str | None = None, - resample: str | None = None, - increment: float | None = None, - surfsmooth: float | None = None, - smoothmm: float | None = None, - maxthick: float | None = None, - depth_search: float | None = None, - keep_temp_files: bool = False, - balls_only: bool = False, - surfsmooth_method: str | None = None, - runner: Runner | None = None, -) -> VMeasureBbThickOutputs: - """ - Compute thickness of mask using ball and box method. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - maskset: Mask dataset for input. - surfset: Surface dataset onto which to map thickness (e.g., pial/gray\ - matter surface). - outdir: Output directory. - resample: Resample input to mm in millimeters (e.g., half a voxel or\ - 'auto'). No resampling is done by default. - increment: Test thickness at increments of sub-voxel distance. Default\ - is 1/4 voxel minimum distance (in-plane). - surfsmooth: Smooth surface map of thickness by mm millimeters. Default\ - is 6 mm. - smoothmm: Smooth volume by mm FWHM in mask. Default is 2*voxelsize of\ - mask or resampled mask. - maxthick: Search for maximum thickness value of mm millimeters. Default\ - is 6 mm. - depth_search: Map to surface by looking for max along mm millimeter\ - normal vectors. Default is 3 mm. - keep_temp_files: Do not delete the intermediate files (for testing). - balls_only: Calculate only with spheres and skip boxes. - surfsmooth_method: Heat method used for smoothing surfaces. Default is\ - HEAT_07 but HEAT_05 is also useful for models. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMeasureBbThickOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__MEASURE_BB_THICK_METADATA) - cargs = [] - cargs.append("@measure_bb_thick") - cargs.append("-maskset") - cargs.append(execution.input_file(maskset)) - cargs.append("-surfset") - cargs.append(execution.input_file(surfset)) - cargs.append("-outdir") - if outdir is not None: - cargs.append(outdir) - if resample is not None: - cargs.extend([ - "-resample", - resample - ]) - if increment is not None: - cargs.extend([ - "-increment", - str(increment) - ]) - if surfsmooth is not None: - cargs.extend([ - "-surfsmooth", - str(surfsmooth) - ]) - if smoothmm is not None: - cargs.extend([ - "-smoothmm", - str(smoothmm) - ]) - if maxthick is not None: - cargs.extend([ - "-maxthick", - str(maxthick) - ]) - if depth_search is not None: - cargs.extend([ - "-depthsearch", - str(depth_search) - ]) - if keep_temp_files: - cargs.append("-keep_temp_files") - if balls_only: - cargs.append("-balls_only") - if surfsmooth_method is not None: - cargs.extend([ - "-surfsmooth_method", - surfsmooth_method - ]) - ret = VMeasureBbThickOutputs( - root=execution.output_file("."), - maxfill=execution.output_file(outdir + "/maxfill.nii.gz") if (outdir is not None) else None, - bb_thick=execution.output_file(outdir + "/bb_thick.nii.gz") if (outdir is not None) else None, - bb_thick_smooth=execution.output_file(outdir + "/bb_thick_smooth.nii.gz") if (outdir is not None) else None, - bb_thick_niml=execution.output_file(outdir + "/bb_thick.niml.dset") if (outdir is not None) else None, - bb_thick_smooth_niml=execution.output_file(outdir + "/bb_thick_smooth.niml.dset") if (outdir is not None) else None, - maskset_output=execution.output_file(outdir + "/maskset.nii.gz") if (outdir is not None) else None, - maskset_resampled=execution.output_file(outdir + "/maskset_rs.nii.gz") if (outdir is not None) else None, - anat_surface=execution.output_file(outdir + "/anat.gii") if (outdir is not None) else None, - quick_spec=execution.output_file(outdir + "/quick.spec") if (outdir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMeasureBbThickOutputs", - "V__MEASURE_BB_THICK_METADATA", - "v__measure_bb_thick", -] diff --git a/python/src/niwrap/afni/v__measure_erosion_thick.py b/python/src/niwrap/afni/v__measure_erosion_thick.py deleted file mode 100644 index 8ecc6bd5c..000000000 --- a/python/src/niwrap/afni/v__measure_erosion_thick.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MEASURE_EROSION_THICK_METADATA = Metadata( - id="744d10f8875a0e0bb50de2078a93479596a98437.boutiques", - name="@measure_erosion_thick", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMeasureErosionThickOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__measure_erosion_thick(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - erosion_depth: OutputPathType - """Depth dataset.""" - erosion_thick: OutputPathType - """Volumetric thickness dataset.""" - erosion_thick_smooth: OutputPathType - """Smoothed volumetric thickness dataset.""" - erosion_thick_niml: OutputPathType - """Unsmoothed thickness mapped to surface nodes.""" - erosion_thick_smooth_niml: OutputPathType - """Smoothed thickness mapped to surface nodes.""" - maskset_output: OutputPathType - """Mask dataset.""" - resampled_maskset: OutputPathType - """Resampled mask dataset.""" - anat_gii: OutputPathType - """Surface representation of mask volume.""" - quick_spec: OutputPathType - """Simple specification file for surface to use with suma commands.""" - - -def v__measure_erosion_thick( - maskset: InputPathType, - surfset: InputPathType, - outdir: str | None = None, - resample: str | None = None, - surfsmooth: float | None = None, - smoothmm: float | None = None, - maxthick: float | None = None, - depthsearch: float | None = None, - keep_temp_files: bool = False, - surfsmooth_method: str | None = None, - runner: Runner | None = None, -) -> VMeasureErosionThickOutputs: - """ - Compute thickness of mask using erosion method. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - maskset: Mask dataset for input. - surfset: Surface dataset onto which to map thickness (probably a\ - pial/gray matter surface). - outdir: Output directory. If not specified, erosion_thickdir is used. - resample: Resample input to mm in millimeters (put a number here).\ - Recommended for most 1mm data. - surfsmooth: Smooth surface map of thickness by mm millimeters. Default\ - is 8 mm. - smoothmm: Smooth volume by mm FWHM in mask. Default is 2*voxelsize of\ - mask or resampled mask. - maxthick: Search for maximum thickness value of mm millimeters. Default\ - is 6 mm. - depthsearch: Map to surface by looking for max along mm millimeter\ - normal vectors. Default is 3 mm. - keep_temp_files: Do not delete the intermediate files (for testing). - surfsmooth_method: Heat method used for smoothing surfaces. Default is\ - HEAT_07 but HEAT_05 is also useful for models. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMeasureErosionThickOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__MEASURE_EROSION_THICK_METADATA) - cargs = [] - cargs.append("@measure_erosion_thick") - cargs.append("-maskset") - cargs.append(execution.input_file(maskset)) - cargs.append("-surfset") - cargs.append(execution.input_file(surfset)) - cargs.append("-outdir") - if outdir is not None: - cargs.append(outdir) - if resample is not None: - cargs.extend([ - "-resample", - resample - ]) - if surfsmooth is not None: - cargs.extend([ - "-surfsmooth", - str(surfsmooth) - ]) - if smoothmm is not None: - cargs.extend([ - "-smoothmm", - str(smoothmm) - ]) - if maxthick is not None: - cargs.extend([ - "-maxthick", - str(maxthick) - ]) - if depthsearch is not None: - cargs.extend([ - "-depthsearch", - str(depthsearch) - ]) - if keep_temp_files: - cargs.append("-keep_temp_files") - if surfsmooth_method is not None: - cargs.extend([ - "-surfsmooth_method", - surfsmooth_method - ]) - ret = VMeasureErosionThickOutputs( - root=execution.output_file("."), - erosion_depth=execution.output_file("erosion_depth.nii.gz"), - erosion_thick=execution.output_file("erosion_thick.nii.gz"), - erosion_thick_smooth=execution.output_file("erosion_thick_smooth.nii.gz"), - erosion_thick_niml=execution.output_file("erosion_thick.niml.dset"), - erosion_thick_smooth_niml=execution.output_file("erosion_thick_smooth_nn_mm.niml.dset"), - maskset_output=execution.output_file("maskset.nii.gz"), - resampled_maskset=execution.output_file("maskset_rs.nii.gz"), - anat_gii=execution.output_file("anat.gii"), - quick_spec=execution.output_file("quick.spec"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMeasureErosionThickOutputs", - "V__MEASURE_EROSION_THICK_METADATA", - "v__measure_erosion_thick", -] diff --git a/python/src/niwrap/afni/v__measure_in2out.py b/python/src/niwrap/afni/v__measure_in2out.py deleted file mode 100644 index 753c37992..000000000 --- a/python/src/niwrap/afni/v__measure_in2out.py +++ /dev/null @@ -1,161 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MEASURE_IN2OUT_METADATA = Metadata( - id="4a0fafb32ed5b72823a2f2c3620ce2533eb5d2af.boutiques", - name="@measure_in2out", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMeasureIn2outOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__measure_in2out(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - inout_dist: OutputPathType - """Volumetric thickness/distance from in to out""" - in_and_out: OutputPathType - """Volumetric distance to inside and outside in 2 volumes""" - inout_thick: OutputPathType - """Unsmoothed thickness mapped to surface nodes""" - inout_thick_smooth: OutputPathType - """Smoothed thickness mapped to surface nodes""" - maskset_output: OutputPathType - """Mask file""" - maskset_rs: OutputPathType - """Resampled mask file""" - anat_gii: OutputPathType - """Surface representation of mask volume""" - quick_spec: OutputPathType - """Simple specification file for surface to use with suma commands""" - - -def v__measure_in2out( - maskset: InputPathType, - surfset: InputPathType, - outdir: str, - resample: str | None = None, - increment: float | None = None, - surfsmooth: float | None = None, - maxthick: float | None = None, - depthsearch: float | None = None, - maskinoutvals: list[float] | None = None, - keep_temp_files: bool = False, - surfsmooth_method: str | None = None, - fs_cort_dir: str | None = None, - runner: Runner | None = None, -) -> VMeasureIn2outOutputs: - """ - Compute thickness of mask using in2out method. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - maskset: Mask dataset for input. - surfset: Surface dataset onto which to map thickness (probably a\ - pial/gray matter surface). - outdir: Output directory. If not specified, in2out_thickdir is used. - resample: Resample input to mm in millimeters (put a number here). Set\ - this to half a voxel or "auto". No resampling is done by default.\ - Resampling is highly recommended for most 1mm data. - increment: Test thickness at increments of sub-voxel distance. Default\ - is 1/4 voxel minimum distance (in-plane). - surfsmooth: Smooth surface map of thickness by mm millimeters. Default\ - is 6 mm. - maxthick: Search for maximum thickness value of mm millimeters. Default\ - is 6 mm. - depthsearch: Map to surface by looking for max along mm millimeter\ - normal vectors. Default is 3 mm. - maskinoutvals: Use v1 for value of mask, v2 and v3 for inside and\ - outside mask values (e.g., '1 -2 -1'). - keep_temp_files: Do not delete the intermediate files (for testing). - surfsmooth_method: Heat method used for smoothing surfaces. Default is\ - HEAT_07 but HEAT_05 is also useful for some models. - fs_cort_dir: Use FreeSurfer SUMA directory from @SUMA_Make_Spec_FS for\ - processing. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMeasureIn2outOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__MEASURE_IN2OUT_METADATA) - cargs = [] - cargs.append("@measure_in2out") - cargs.append("-maskset") - cargs.append(execution.input_file(maskset)) - cargs.append("-surfset") - cargs.append(execution.input_file(surfset)) - cargs.append("-outdir") - cargs.append(outdir) - if resample is not None: - cargs.extend([ - "-resample", - resample - ]) - if increment is not None: - cargs.extend([ - "-increment", - str(increment) - ]) - if surfsmooth is not None: - cargs.extend([ - "-surfsmooth", - str(surfsmooth) - ]) - if maxthick is not None: - cargs.extend([ - "-maxthick", - str(maxthick) - ]) - if depthsearch is not None: - cargs.extend([ - "-depthsearch", - str(depthsearch) - ]) - if maskinoutvals is not None: - cargs.extend([ - "-maskinoutvals", - *map(str, maskinoutvals) - ]) - if keep_temp_files: - cargs.append("-keep_temp_files") - if surfsmooth_method is not None: - cargs.extend([ - "-surfsmooth_method", - surfsmooth_method - ]) - if fs_cort_dir is not None: - cargs.extend([ - "-fs_cort_dir", - fs_cort_dir - ]) - ret = VMeasureIn2outOutputs( - root=execution.output_file("."), - inout_dist=execution.output_file("inout_dist.nii.gz"), - in_and_out=execution.output_file("in_and_out.nii.gz"), - inout_thick=execution.output_file("inout_thick.niml.dset"), - inout_thick_smooth=execution.output_file("inout_thick_smooth.niml.dset"), - maskset_output=execution.output_file("maskset.nii.gz"), - maskset_rs=execution.output_file("maskset_rs.nii.gz"), - anat_gii=execution.output_file("anat.gii"), - quick_spec=execution.output_file("quick.spec"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMeasureIn2outOutputs", - "V__MEASURE_IN2OUT_METADATA", - "v__measure_in2out", -] diff --git a/python/src/niwrap/afni/v__move_to_series_dirs.py b/python/src/niwrap/afni/v__move_to_series_dirs.py deleted file mode 100644 index a8c5defa0..000000000 --- a/python/src/niwrap/afni/v__move_to_series_dirs.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__MOVE_TO_SERIES_DIRS_METADATA = Metadata( - id="43e65ff4ccb7c662ae1bcaef0b7fb14c99b76809.boutiques", - name="@move.to.series.dirs", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VMoveToSeriesDirsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__move_to_series_dirs(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__move_to_series_dirs( - dicom_files: list[InputPathType], - action: typing.Literal["copy", "move"] | None = None, - dprefix: str | None = None, - tag: str | None = None, - test: bool = False, - help_: bool = False, - hist: bool = False, - ver: bool = False, - runner: Runner | None = None, -) -> VMoveToSeriesDirsOutputs: - """ - Partition DICOM files into series directories by copying or moving them to new - series directories. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dicom_files: Specify input DICOM files (e.g., IMG*). - action: Specify action to perform: copy or move. Default is copy. - dprefix: Specify directory root for output series directories. Default\ - is current directory. - tag: Specify the DICOM tag to use for partitioning. Default is\ - 0020,0011 (REL Series Number). - test: Run in test mode, only show what would be done without actually\ - moving any files. - help_: Show help information. - hist: Show modification history. - ver: Show version number. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VMoveToSeriesDirsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__MOVE_TO_SERIES_DIRS_METADATA) - cargs = [] - cargs.append("@move.to.series.dirs") - if action is not None: - cargs.extend([ - "-action", - action - ]) - if dprefix is not None: - cargs.extend([ - "-dprefix", - dprefix - ]) - if tag is not None: - cargs.extend([ - "-tag", - tag - ]) - if test: - cargs.append("-test") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if ver: - cargs.append("-ver") - cargs.extend([execution.input_file(f) for f in dicom_files]) - ret = VMoveToSeriesDirsOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VMoveToSeriesDirsOutputs", - "V__MOVE_TO_SERIES_DIRS_METADATA", - "v__move_to_series_dirs", -] diff --git a/python/src/niwrap/afni/v__no_ext.py b/python/src/niwrap/afni/v__no_ext.py deleted file mode 100644 index 575e590ec..000000000 --- a/python/src/niwrap/afni/v__no_ext.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__NO_EXT_METADATA = Metadata( - id="c6cf8e39158c82ff94f016b9c38f20ee91c053de.boutiques", - name="@NoExt", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VNoExtOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__no_ext(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """File name with specified extensions removed""" - - -def v__no_ext( - extensions: list[str] | None = None, - runner: Runner | None = None, -) -> VNoExtOutputs: - """ - Tool for removing specified extensions from filenames. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - extensions: Extensions to be removed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VNoExtOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__NO_EXT_METADATA) - cargs = [] - cargs.append("@NoExt") - cargs.append("") - if extensions is not None: - cargs.extend(extensions) - ret = VNoExtOutputs( - root=execution.output_file("."), - outfile=execution.output_file("output"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VNoExtOutputs", - "V__NO_EXT_METADATA", - "v__no_ext", -] diff --git a/python/src/niwrap/afni/v__no_pound.py b/python/src/niwrap/afni/v__no_pound.py deleted file mode 100644 index 2bd871589..000000000 --- a/python/src/niwrap/afni/v__no_pound.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__NO_POUND_METADATA = Metadata( - id="27d35f86a77d04034e08074da72efd10ccb9fa51.boutiques", - name="@NoPound", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VNoPoundOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__no_pound(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__no_pound( - afni_files: list[str], - runner: Runner | None = None, -) -> VNoPoundOutputs: - """ - Replaces all # characters in AFNI filenames with a -. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - afni_files: List of AFNI files where # characters should be replaced\ - with -. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VNoPoundOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__NO_POUND_METADATA) - cargs = [] - cargs.append("@NoPound") - cargs.extend(afni_files) - ret = VNoPoundOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VNoPoundOutputs", - "V__NO_POUND_METADATA", - "v__no_pound", -] diff --git a/python/src/niwrap/afni/v__noisy_skull_strip.py b/python/src/niwrap/afni/v__noisy_skull_strip.py deleted file mode 100644 index a79f34f29..000000000 --- a/python/src/niwrap/afni/v__noisy_skull_strip.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__NOISY_SKULL_STRIP_METADATA = Metadata( - id="c7ff4d34b7c1585d06f46e9b52322c91389d58c8.boutiques", - name="@NoisySkullStrip", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VNoisySkullStripOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__noisy_skull_strip(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - anat_ns: OutputPathType - """Skull stripped version of ANAT""" - anat_air: OutputPathType - """Special mask output - air""" - anat_skl: OutputPathType - """Special mask output - skull""" - anat_lsp: OutputPathType - """Volume used to threshold 'air' out of the volume to be stripped""" - - -def v__noisy_skull_strip( - input_file: InputPathType, - keep_tmp: bool = False, - v_3dskullstrip_opts: str | None = None, - runner: Runner | None = None, -) -> VNoisySkullStripOutputs: - """ - Strips the skull of anatomical datasets with low SNR. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: The anatomical dataset. - keep_tmp: Do not erase temporary files at the end. - v_3dskullstrip_opts: Anything following this option is passed to\ - 3dSkullStrip. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VNoisySkullStripOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__NOISY_SKULL_STRIP_METADATA) - cargs = [] - cargs.append("@NoisySkullStrip") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - if keep_tmp: - cargs.append("-keep_tmp") - if v_3dskullstrip_opts is not None: - cargs.extend([ - "-3dSkullStrip_opts", - v_3dskullstrip_opts - ]) - ret = VNoisySkullStripOutputs( - root=execution.output_file("."), - anat_ns=execution.output_file(pathlib.Path(input_file).name + ".ns"), - anat_air=execution.output_file(pathlib.Path(input_file).name + ".air"), - anat_skl=execution.output_file(pathlib.Path(input_file).name + ".skl"), - anat_lsp=execution.output_file(pathlib.Path(input_file).name + ".lsp"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VNoisySkullStripOutputs", - "V__NOISY_SKULL_STRIP_METADATA", - "v__noisy_skull_strip", -] diff --git a/python/src/niwrap/afni/v__np.py b/python/src/niwrap/afni/v__np.py deleted file mode 100644 index 3c4d71182..000000000 --- a/python/src/niwrap/afni/v__np.py +++ /dev/null @@ -1,63 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__NP_METADATA = Metadata( - id="19475e309cca046197768d1ade01d7e521898bd3.boutiques", - name="@np", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VNpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__np(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - outfile: OutputPathType - """Output text file with the appropriate new prefix.""" - - -def v__np( - prefix: str, - runner: Runner | None = None, -) -> VNpOutputs: - """ - Finds an appropriate new prefix to use, given the files you already have in your - directory. It automatically creates a valid prefix when you are repeatedly - running similar commands but do not want to delete previous output. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: The prefix to be checked. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VNpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__NP_METADATA) - cargs = [] - cargs.append("@np") - cargs.append(prefix) - ret = VNpOutputs( - root=execution.output_file("."), - outfile=execution.output_file("appropriate_prefix.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VNpOutputs", - "V__NP_METADATA", - "v__np", -] diff --git a/python/src/niwrap/afni/v__parse_afni_name.py b/python/src/niwrap/afni/v__parse_afni_name.py deleted file mode 100644 index 9f2a3adab..000000000 --- a/python/src/niwrap/afni/v__parse_afni_name.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__PARSE_AFNI_NAME_METADATA = Metadata( - id="6b460b863377f6ef2cf8dd2bc95819c049ae8246.boutiques", - name="@parse_afni_name", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VParseAfniNameOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__parse_afni_name(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_path: OutputPathType - """Output path parsed from the AFNI name""" - output_prefix: OutputPathType - """Output prefix parsed from the AFNI name""" - output_view: OutputPathType - """Output view parsed from the AFNI name""" - output_subbrick: OutputPathType - """Output sub-brick selection string parsed from the AFNI name""" - - -def v__parse_afni_name( - afni_name: str, - runner: Runner | None = None, -) -> VParseAfniNameOutputs: - """ - A script to parse an AFNI name, outputting the path, prefix, view, and sub-brick - selection string. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - afni_name: The AFNI name to be parsed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VParseAfniNameOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__PARSE_AFNI_NAME_METADATA) - cargs = [] - cargs.append("@parse_afni_name") - cargs.append(afni_name) - ret = VParseAfniNameOutputs( - root=execution.output_file("."), - output_path=execution.output_file("parsed_name_path.txt"), - output_prefix=execution.output_file("parsed_name_prefix.txt"), - output_view=execution.output_file("parsed_name_view.txt"), - output_subbrick=execution.output_file("parsed_name_subbrick.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VParseAfniNameOutputs", - "V__PARSE_AFNI_NAME_METADATA", - "v__parse_afni_name", -] diff --git a/python/src/niwrap/afni/v__purify_1_d.py b/python/src/niwrap/afni/v__purify_1_d.py deleted file mode 100644 index 648a507d5..000000000 --- a/python/src/niwrap/afni/v__purify_1_d.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__PURIFY_1_D_METADATA = Metadata( - id="f151d6221d30e4482e4401cc1da254b8c8b2ea5b.boutiques", - name="@Purify_1D", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VPurify1DOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__purify_1_d(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__purify_1_d( - input_files: list[InputPathType], - sub_brick: str | None = None, - suffix: str | None = None, - runner: Runner | None = None, -) -> VPurify1DOutputs: - """ - Purifies a series of 1D files for faster I/O into matlab. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: Input 1D dataset files. - sub_brick: The sub-brick selection mode to output a select number of\ - columns, following AFNI conventions. - suffix: STRING is attached to the output prefix which is formed from\ - the input names. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VPurify1DOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__PURIFY_1_D_METADATA) - cargs = [] - cargs.append("@Purify_1D") - if sub_brick is not None: - cargs.extend([ - "-sub", - sub_brick - ]) - if suffix is not None: - cargs.extend([ - "-suf", - suffix - ]) - cargs.extend([execution.input_file(f) for f in input_files]) - ret = VPurify1DOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VPurify1DOutputs", - "V__PURIFY_1_D_METADATA", - "v__purify_1_d", -] diff --git a/python/src/niwrap/afni/v__quiet_talkers.py b/python/src/niwrap/afni/v__quiet_talkers.py deleted file mode 100644 index da7cec67a..000000000 --- a/python/src/niwrap/afni/v__quiet_talkers.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__QUIET_TALKERS_METADATA = Metadata( - id="86ed5dd2f27f074888e57e7b970f449c289482ab.boutiques", - name="@Quiet_Talkers", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VQuietTalkersOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__quiet_talkers(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__quiet_talkers( - sudo: bool = False, - prog: list[str] | None = None, - npb_val: list[float] | None = None, - npb_range: list[float] | None = None, - pif_key: str | None = None, - no_npb: bool = False, - list_: bool = False, - quiet: bool = False, - runner: Runner | None = None, -) -> VQuietTalkersOutputs: - """ - A script to find and kill AFNI processes. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - sudo: Invoke higher powers to kill processes that you do not own. - prog: Instead of the default program list, only kill the specified\ - program. You can use multiple -prog options. - npb_val: Kill those programs using NIML port block NV. - npb_range: Kill those using NIML port blocks between NV0 and NV1. - pif_key: Kill those programs that have a string matching KEY_STRING in\ - their commandline. - no_npb: Kill any program in the list regardless of -npb options or -pif. - list_: Just list process numbers, don't run kill command. - quiet: Do it quietly. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VQuietTalkersOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__QUIET_TALKERS_METADATA) - cargs = [] - cargs.append("@Quiet_Talkers") - if sudo: - cargs.append("-sudo") - if prog is not None: - cargs.extend([ - "-prog", - *prog - ]) - if npb_val is not None: - cargs.extend([ - "-npb_val", - *map(str, npb_val) - ]) - if npb_range is not None: - cargs.extend([ - "-npb_range", - *map(str, npb_range) - ]) - if pif_key is not None: - cargs.extend([ - "-pif", - pif_key - ]) - if no_npb: - cargs.append("-no_npb") - if list_: - cargs.append("-list") - if quiet: - cargs.append("-quiet") - ret = VQuietTalkersOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VQuietTalkersOutputs", - "V__QUIET_TALKERS_METADATA", - "v__quiet_talkers", -] diff --git a/python/src/niwrap/afni/v__radial_correlate.py b/python/src/niwrap/afni/v__radial_correlate.py deleted file mode 100644 index 5ffb14658..000000000 --- a/python/src/niwrap/afni/v__radial_correlate.py +++ /dev/null @@ -1,182 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__RADIAL_CORRELATE_METADATA = Metadata( - id="1cbb44d20d4e3ca23ba7981bb4c49932fce75bf0.boutiques", - name="@radial_correlate", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRadialCorrelateOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__radial_correlate(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corr_volumes: OutputPathType | None - """Directory containing correlation volumes""" - - -def v__radial_correlate( - input_files: list[InputPathType], - results_dir: str | None = None, - do_corr: str | None = None, - do_clust: str | None = None, - mask_dset: InputPathType | None = None, - cthresh: float | None = None, - frac_limit: float | None = None, - sphere_rad: float | None = None, - use_3dmerge: str | None = None, - percentile: float | None = None, - min_thr: float | None = None, - nfirst: float | None = None, - ver: bool = False, - verbose: bool = False, - help_: bool = False, - hist: bool = False, - corr_mask: str | None = None, - do_clean: str | None = None, - polort: float | None = None, - merge_frad: float | None = None, - runner: Runner | None = None, -) -> VRadialCorrelateOutputs: - """ - Check datasets for correlation artifacts. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_files: A list of EPI datasets. - results_dir: Results directory for correlations. - do_corr: Create correlation volumes (yes/no). - do_clust: Cluster correlation volumes (yes/no). - mask_dset: Specify a mask dataset to replace automask. - cthresh: Threshold on correlation values. - frac_limit: Minimum mask fraction surviving cluster. - sphere_rad: Generate correlations within voxel spheres. - use_3dmerge: Use 3dmerge rather than 3dLocalstat (yes/no). - percentile: Percentile to use as threshold. - min_thr: Minimum percentile threshold to be considered. - nfirst: Number of initial TRs to remove. - ver: Show version number. - verbose: Make verbose: set echo. - help_: Show help. - hist: Show modification history. - corr_mask: Mask time series before correlation blurring (yes/no). - do_clean: Clean up at end, leaving only correlations (yes/no). - polort: Detrend time series with given polynomial degree. - merge_frad: Specify a radius fraction for 3dmerge blurring. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRadialCorrelateOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__RADIAL_CORRELATE_METADATA) - cargs = [] - cargs.append("@radial_correlate") - cargs.extend([execution.input_file(f) for f in input_files]) - if results_dir is not None: - cargs.extend([ - "-rdir", - results_dir - ]) - if do_corr is not None: - cargs.extend([ - "-do_corr", - do_corr - ]) - if do_clust is not None: - cargs.extend([ - "-do_clust", - do_clust - ]) - if mask_dset is not None: - cargs.extend([ - "-mask", - execution.input_file(mask_dset) - ]) - if cthresh is not None: - cargs.extend([ - "-cthresh", - str(cthresh) - ]) - if frac_limit is not None: - cargs.extend([ - "-frac_limit", - str(frac_limit) - ]) - if sphere_rad is not None: - cargs.extend([ - "-sphere_rad", - str(sphere_rad) - ]) - if use_3dmerge is not None: - cargs.extend([ - "-use_3dmerge", - use_3dmerge - ]) - if percentile is not None: - cargs.extend([ - "-percentile", - str(percentile) - ]) - if min_thr is not None: - cargs.extend([ - "-min_thr", - str(min_thr) - ]) - if nfirst is not None: - cargs.extend([ - "-nfirst", - str(nfirst) - ]) - if ver: - cargs.append("-ver") - if verbose: - cargs.append("-verb") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if corr_mask is not None: - cargs.extend([ - "-corr_mask", - corr_mask - ]) - if do_clean is not None: - cargs.extend([ - "-do_clean", - do_clean - ]) - if polort is not None: - cargs.extend([ - "-polort", - str(polort) - ]) - if merge_frad is not None: - cargs.extend([ - "-merge_frad", - str(merge_frad) - ]) - ret = VRadialCorrelateOutputs( - root=execution.output_file("."), - corr_volumes=execution.output_file(results_dir + "/correlation_volumes") if (results_dir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRadialCorrelateOutputs", - "V__RADIAL_CORRELATE_METADATA", - "v__radial_correlate", -] diff --git a/python/src/niwrap/afni/v__rename_panga.py b/python/src/niwrap/afni/v__rename_panga.py deleted file mode 100644 index 65763cad2..000000000 --- a/python/src/niwrap/afni/v__rename_panga.py +++ /dev/null @@ -1,111 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__RENAME_PANGA_METADATA = Metadata( - id="914311314765b2437055f3aa454e935f0c2186ed.boutiques", - name="@RenamePanga", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRenamePangaOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__rename_panga(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - head_file: OutputPathType | None - """Main output file (HEAD)""" - brik_file: OutputPathType | None - """Main output file (BRIK)""" - log_file: OutputPathType | None - """Log file created in the current directory""" - - -def v__rename_panga( - dir_number: str, - first_image_number: str, - num_slices: float, - num_reps: float, - output_root: str, - keep_prefix: bool = False, - interactive: bool = False, - outliers_check: bool = False, - slice_pattern: str | None = None, - output_directory: str | None = None, - runner: Runner | None = None, -) -> VRenamePangaOutputs: - """ - Creates AFNI bricks from RealTime GE EPI series. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dir_number: The directory number where the first image of the series is\ - stored. - first_image_number: The number of the first image in the series. - num_slices: The number of slices making up the imaged volume. - num_reps: The number of samples in your time series. - output_root: The prefix for the output brick. - keep_prefix: Forces @RenamePanga to use the prefix you designate\ - without modification. - interactive: Launches to3d in interactive mode. This allows you to\ - double check the automated settings. - outliers_check: Performs outliers check and writes the outliers to a\ - .1D file placed in the output directory. - slice_pattern: Sets the slice acquisition pattern. The default option\ - is alt+z. - output_directory: Directory where the output (bricks and 1D files) will\ - be stored. The default directory is ./afni. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRenamePangaOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__RENAME_PANGA_METADATA) - cargs = [] - cargs.append("@RenamePanga") - cargs.append(dir_number) - cargs.append(first_image_number) - cargs.append(str(num_slices)) - cargs.append(str(num_reps)) - cargs.append(output_root) - if keep_prefix: - cargs.append("-kp") - if interactive: - cargs.append("-i") - if outliers_check: - cargs.append("-oc") - if slice_pattern is not None: - cargs.extend([ - "-sp", - slice_pattern - ]) - if output_directory is not None: - cargs.extend([ - "-od", - output_directory - ]) - ret = VRenamePangaOutputs( - root=execution.output_file("."), - head_file=execution.output_file(output_directory + "/" + output_root + "_r#.HEAD") if (output_directory is not None) else None, - brik_file=execution.output_file(output_directory + "/" + output_root + "_r#.BRIK") if (output_directory is not None) else None, - log_file=execution.output_file(output_directory + "/MAPLOG_Panga") if (output_directory is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRenamePangaOutputs", - "V__RENAME_PANGA_METADATA", - "v__rename_panga", -] diff --git a/python/src/niwrap/afni/v__reorder.py b/python/src/niwrap/afni/v__reorder.py deleted file mode 100644 index fe5aa33ee..000000000 --- a/python/src/niwrap/afni/v__reorder.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__REORDER_METADATA = Metadata( - id="a4930cc004546fe6ae9b0d7fcb027aaf3f005ee2.boutiques", - name="@Reorder", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VReorderOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__reorder(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_dataset: OutputPathType - """Reordered output dataset""" - - -def v__reorder( - input_dataset: InputPathType, - mapfile: InputPathType, - prefix: str, - offset: float | None = None, - save_work: bool = False, - test: bool = False, - runner: Runner | None = None, -) -> VReorderOutputs: - """ - Reorder sub-bricks of a dataset based on event mapping. Works similarly to the - Reorder plugin. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dataset: Input dataset to reorder (e.g. EPI+tlrc). - mapfile: TR to event mapping file (e.g. events.txt). - prefix: Prefix for the output dataset. - offset: Offset mapfile TR indices by OFFSET (in TRs). - save_work: Do not delete work directory (reorder.work.dir) at the end. - test: Just report sub-bricks, do not create datasets. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VReorderOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__REORDER_METADATA) - cargs = [] - cargs.append("@Reorder") - cargs.append(execution.input_file(input_dataset)) - cargs.append(execution.input_file(mapfile)) - cargs.append(prefix) - if offset is not None: - cargs.extend([ - "-offset", - str(offset) - ]) - if save_work: - cargs.append("-save_work") - if test: - cargs.append("-test") - ret = VReorderOutputs( - root=execution.output_file("."), - output_dataset=execution.output_file(prefix + "+tlrc"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VReorderOutputs", - "V__REORDER_METADATA", - "v__reorder", -] diff --git a/python/src/niwrap/afni/v__retino_proc.py b/python/src/niwrap/afni/v__retino_proc.py deleted file mode 100644 index 0510bf56b..000000000 --- a/python/src/niwrap/afni/v__retino_proc.py +++ /dev/null @@ -1,323 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__RETINO_PROC_METADATA = Metadata( - id="0836ad099b5ae0ebd794fce9bafc7b29723fb572.boutiques", - name="@RetinoProc", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRetinoProcOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__retino_proc(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__retino_proc( - tr: float, - period_ecc: float, - period_pol: float, - ccw: list[InputPathType] | None = None, - clw: list[InputPathType] | None = None, - exp: list[InputPathType] | None = None, - con: list[InputPathType] | None = None, - epi_ref: InputPathType | None = None, - epi_anat_ref: InputPathType | None = None, - anat_vol: InputPathType | None = None, - anat_vol_epi: InputPathType | None = None, - surf_vol: InputPathType | None = None, - surf_vol_epi: InputPathType | None = None, - phase: bool = False, - delay: bool = False, - pre_ecc: float | None = None, - pre_pol: float | None = None, - on_ecc: str | None = None, - on_pol: str | None = None, - var_on_ecc: str | None = None, - var_on_pol: str | None = None, - nwedges: float | None = None, - nrings: float | None = None, - fwhm_pol: float | None = None, - fwhm_ecc: float | None = None, - ignore: float | None = None, - no_tshift: bool = False, - spec_left: InputPathType | None = None, - spec_right: InputPathType | None = None, - dorts: InputPathType | None = None, - ccw_orts: list[InputPathType] | None = None, - clw_orts: list[InputPathType] | None = None, - exp_orts: list[InputPathType] | None = None, - con_orts: list[InputPathType] | None = None, - sid: str | None = None, - out_dir: str | None = None, - echo: bool = False, - echo_edu: bool = False, - a2e_opts: str | None = None, - aea_opts: str | None = None, - runner: Runner | None = None, -) -> VRetinoProcOutputs: - """ - A script to process retinotopic FMRI data, using AFNI's 3dRetinoPhase and - SurfRetinMap. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - tr: TR, in seconds, of retinotopic scans. - period_ecc: Period, in seconds, of eccentricity stimuli. - period_pol: Period, in seconds, of polar angle stimuli. - ccw: Input time series dataset for counterclockwise stimulus. - clw: Input time series dataset for clockwise stimulus. - exp: Input time series dataset for expanding stimulus. - con: Input time series dataset for contracting stimulus. - epi_ref: Specify a volume from the EPI time series to which all EPI\ - volumes are aligned. - epi_anat_ref: Specify a volume from the EPI time series that is better\ - suited for aligning the T1 to it than EpiRef might be. - anat_vol: T1 volume acquired during the same session as the retinotopic\ - scans. - anat_vol_epi: Anatomical volume aligned to EPI reference. - surf_vol: Surface Volume for the cortical surfaces. - surf_vol_epi: Surface volume aligned to experiment's EPI data. - phase: Use phase of fundamental frequency to estimate latency. - delay: Use delay relative to reference time series to estimate latency. - pre_ecc: Duration, in seconds, before eccentricity stimulus. - pre_pol: Duration, in seconds, before polar angle stimulus. - on_ecc: Number of stimulation blocks and duration of stimulation for\ - eccentricity stimulus. - on_pol: Number of stimulation blocks and duration of stimulation for\ - polar angle stimulus. - var_on_ecc: Multiple on durations for eccentricity stimulus. - var_on_pol: Multiple on durations for polar angle stimulus. - nwedges: Number of wedges in polar stimulus. - nrings: Number of rings in eccentricity stimulus. - fwhm_pol: Target smoothness for polar stimulus. - fwhm_ecc: Target smoothness for eccentricity stimulus. - ignore: Ignore volumes from the beginning of each time series. - no_tshift: Do not correct for slice timing. - spec_left: Spec file for left hemisphere. - spec_right: Spec file for right hemisphere. - dorts: Detrend time series using columns in ORT1D file. - ccw_orts: Detrend time series for counterclockwise stimulus. - clw_orts: Detrend time series for clockwise stimulus. - exp_orts: Detrend time series for expanding stimulus. - con_orts: Detrend time series for contracting stimulus. - sid: SID is a flag identifying the subject. - out_dir: Directory where processing results are to be stored. - echo: Turn on the command echoing to help with debugging script failure. - echo_edu: Turn on command echoing for certain programs only. - a2e_opts: Pass options to @SUMA_AlignToExperiment script. - aea_opts: Pass options to align_epi_anat.py. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRetinoProcOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__RETINO_PROC_METADATA) - cargs = [] - cargs.append("@RetinoProc") - if ccw is not None: - cargs.extend([ - "-ccw", - *[execution.input_file(f) for f in ccw] - ]) - if clw is not None: - cargs.extend([ - "-clw", - *[execution.input_file(f) for f in clw] - ]) - if exp is not None: - cargs.extend([ - "-exp", - *[execution.input_file(f) for f in exp] - ]) - if con is not None: - cargs.extend([ - "-con", - *[execution.input_file(f) for f in con] - ]) - if epi_ref is not None: - cargs.extend([ - "-epi_ref", - execution.input_file(epi_ref) - ]) - if epi_anat_ref is not None: - cargs.extend([ - "-epi_anat_ref", - execution.input_file(epi_anat_ref) - ]) - if anat_vol is not None: - cargs.extend([ - "-anat_vol", - execution.input_file(anat_vol) - ]) - if anat_vol_epi is not None: - cargs.extend([ - "-anat_vol@epi", - execution.input_file(anat_vol_epi) - ]) - if surf_vol is not None: - cargs.extend([ - "-surf_vol", - execution.input_file(surf_vol) - ]) - if surf_vol_epi is not None: - cargs.extend([ - "-surf_vol@epi", - execution.input_file(surf_vol_epi) - ]) - if phase: - cargs.append("-phase") - if delay: - cargs.append("-delay") - cargs.extend([ - "-TR", - str(tr) - ]) - cargs.extend([ - "-period_ecc", - str(period_ecc) - ]) - cargs.extend([ - "-period_pol", - str(period_pol) - ]) - if pre_ecc is not None: - cargs.extend([ - "-pre_ecc", - str(pre_ecc) - ]) - if pre_pol is not None: - cargs.extend([ - "-pre_pol", - str(pre_pol) - ]) - if on_ecc is not None: - cargs.extend([ - "-on_ecc", - on_ecc - ]) - if on_pol is not None: - cargs.extend([ - "-on_pol", - on_pol - ]) - if var_on_ecc is not None: - cargs.extend([ - "-var_on_ecc", - var_on_ecc - ]) - if var_on_pol is not None: - cargs.extend([ - "-var_on_pol", - var_on_pol - ]) - if nwedges is not None: - cargs.extend([ - "-nwedges", - str(nwedges) - ]) - if nrings is not None: - cargs.extend([ - "-nrings", - str(nrings) - ]) - if fwhm_pol is not None: - cargs.extend([ - "-fwhm_pol", - str(fwhm_pol) - ]) - if fwhm_ecc is not None: - cargs.extend([ - "-fwhm_ecc", - str(fwhm_ecc) - ]) - if ignore is not None: - cargs.extend([ - "-ignore", - str(ignore) - ]) - if no_tshift: - cargs.append("-no_tshift") - if spec_left is not None: - cargs.extend([ - "-spec_left", - execution.input_file(spec_left) - ]) - if spec_right is not None: - cargs.extend([ - "-spec_right", - execution.input_file(spec_right) - ]) - if dorts is not None: - cargs.extend([ - "-dorts", - execution.input_file(dorts) - ]) - if ccw_orts is not None: - cargs.extend([ - "-ccw_orts", - *[execution.input_file(f) for f in ccw_orts] - ]) - if clw_orts is not None: - cargs.extend([ - "-clw_orts", - *[execution.input_file(f) for f in clw_orts] - ]) - if exp_orts is not None: - cargs.extend([ - "-exp_orts", - *[execution.input_file(f) for f in exp_orts] - ]) - if con_orts is not None: - cargs.extend([ - "-con_orts", - *[execution.input_file(f) for f in con_orts] - ]) - if sid is not None: - cargs.extend([ - "-sid", - sid - ]) - if out_dir is not None: - cargs.extend([ - "-out_dir", - out_dir - ]) - if echo: - cargs.append("-echo") - if echo_edu: - cargs.append("-echo_edu") - if a2e_opts is not None: - cargs.extend([ - "-A2E_opts", - a2e_opts - ]) - if aea_opts is not None: - cargs.extend([ - "-AEA_opts", - aea_opts - ]) - ret = VRetinoProcOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRetinoProcOutputs", - "V__RETINO_PROC_METADATA", - "v__retino_proc", -] diff --git a/python/src/niwrap/afni/v__roi_corr_mat.py b/python/src/niwrap/afni/v__roi_corr_mat.py deleted file mode 100644 index d798b45b5..000000000 --- a/python/src/niwrap/afni/v__roi_corr_mat.py +++ /dev/null @@ -1,114 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ROI_CORR_MAT_METADATA = Metadata( - id="d27741a76bf8e8edaca6216979d5f299279d17c6.boutiques", - name="@ROI_Corr_Mat", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRoiCorrMatOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__roi_corr_mat(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - matrix_1d: OutputPathType - """Correlation matrix in .1D format""" - matrix_brick: OutputPathType - """Correlation matrix in .BRIK format""" - - -def v__roi_corr_mat( - ts_vol: InputPathType, - roi_vol: InputPathType, - prefix: str, - roisel: InputPathType | None = None, - zval: bool = False, - mat_opt: str | None = None, - dirty: bool = False, - keep_tmp: bool = False, - echo: bool = False, - verb: bool = False, - runner: Runner | None = None, -) -> VRoiCorrMatOutputs: - """ - Script to produce an NxN ROI correlation matrix of N ROIs. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - ts_vol: Time series volume. - roi_vol: ROI volume. - prefix: Use output for a prefix. - roisel: Force processing of ROI label (integers) listed in ROISEL 1D\ - file. - zval: Output a zscore version of the correlation matrix. - mat_opt: Output matrix in different manners. - dirty: Keep temporary files. - keep_tmp: Keep temporary files. - echo: Set echo (echo all commands to screen). - verb: Verbose flag. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRoiCorrMatOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__ROI_CORR_MAT_METADATA) - cargs = [] - cargs.append("@ROI_Corr_Mat") - cargs.extend([ - "-ts", - execution.input_file(ts_vol) - ]) - cargs.extend([ - "-roi", - execution.input_file(roi_vol) - ]) - cargs.extend([ - "-prefix", - prefix - ]) - if roisel is not None: - cargs.extend([ - "-roisel", - execution.input_file(roisel) - ]) - if zval: - cargs.append("-zval") - if mat_opt is not None: - cargs.extend([ - "-mat", - mat_opt - ]) - if dirty: - cargs.append("-dirty") - if keep_tmp: - cargs.append("-keep_tmp") - if echo: - cargs.append("-echo") - if verb: - cargs.append("-verb") - ret = VRoiCorrMatOutputs( - root=execution.output_file("."), - matrix_1d=execution.output_file(prefix + "_matrix.1D"), - matrix_brick=execution.output_file(prefix + "_matrix.BRIK"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRoiCorrMatOutputs", - "V__ROI_CORR_MAT_METADATA", - "v__roi_corr_mat", -] diff --git a/python/src/niwrap/afni/v__roi_decluster.py b/python/src/niwrap/afni/v__roi_decluster.py deleted file mode 100644 index d9d0364de..000000000 --- a/python/src/niwrap/afni/v__roi_decluster.py +++ /dev/null @@ -1,105 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ROI_DECLUSTER_METADATA = Metadata( - id="c565e19b7f5a74c17db9a508d6eb500dd6dc0e98.boutiques", - name="@ROI_decluster", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRoiDeclusterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__roi_decluster(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Final output dataset""" - - -def v__roi_decluster( - input_dset: InputPathType, - output_dir: str | None = None, - nvox_thresh: float | None = None, - frac_thresh: float | None = None, - prefix: str | None = None, - neighborhood_type: int | None = None, - runner: Runner | None = None, -) -> VRoiDeclusterOutputs: - """ - Script to remove small clusters or standalone voxels from an ROI/atlas dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dset: Required input dataset. This dataset should be set of\ - integer values. The program mostly assumes approximate isotropic\ - voxels. - output_dir: Directory name for output. All output goes to this\ - directory. - nvox_thresh: Number of voxels in a cluster to keep. - frac_thresh: Fraction of voxels in a cluster to keep [0.0-1.0]. - prefix: Base name of final output dataset, i.e. baseprefix.nii.gz. - neighborhood_type: Neighborhood type using in finding mode: 1 - facing\ - neighbors, 2 - edges, 3 - corners. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRoiDeclusterOutputs`). - """ - if neighborhood_type is not None and not (1 <= neighborhood_type <= 3): - raise ValueError(f"'neighborhood_type' must be between 1 <= x <= 3 but was {neighborhood_type}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__ROI_DECLUSTER_METADATA) - cargs = [] - cargs.append("@ROI_decluster") - cargs.extend([ - "-input", - execution.input_file(input_dset) - ]) - if output_dir is not None: - cargs.extend([ - "-outdir", - output_dir - ]) - if nvox_thresh is not None: - cargs.extend([ - "-nvox_thresh", - str(nvox_thresh) - ]) - if frac_thresh is not None: - cargs.extend([ - "-frac_thresh", - str(frac_thresh) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if neighborhood_type is not None: - cargs.extend([ - "-NN", - str(neighborhood_type) - ]) - ret = VRoiDeclusterOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRoiDeclusterOutputs", - "V__ROI_DECLUSTER_METADATA", - "v__roi_decluster", -] diff --git a/python/src/niwrap/afni/v__roi_modal_grow.py b/python/src/niwrap/afni/v__roi_modal_grow.py deleted file mode 100644 index 2b1c8f5c0..000000000 --- a/python/src/niwrap/afni/v__roi_modal_grow.py +++ /dev/null @@ -1,113 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__ROI_MODAL_GROW_METADATA = Metadata( - id="e8f66331d7e1f46be263001d8f84462116ac0792.boutiques", - name="@ROI_modal_grow", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VRoiModalGrowOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__roi_modal_grow(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Final output dataset""" - - -def v__roi_modal_grow( - input_dset: InputPathType, - niters: float, - outdir: str | None = None, - mask: InputPathType | None = None, - prefix: str | None = None, - neighborhood_type: int | None = None, - runner: Runner | None = None, -) -> VRoiModalGrowOutputs: - """ - Script to grow a set of regions in a volumetric dataset using modal smoothing. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_dset: Required input dataset. This dataset should be a set of\ - integer values, assuming approximate isotropic voxels. - niters: Number of iterations for modal growth, generally making sense\ - for values from about 1-10. - outdir: Directory name for output. All output goes to this directory.\ - Default is rmgrow. - mask: Mask dataset at the same grid as the input dataset. Could be a\ - dilated version of the original mask or a larger region like a cortical\ - ribbon mask. Not required but often desirable. - prefix: Base name of the final output dataset, i.e., baseprefix.nii.gz.\ - Default is rmg, so output would be rmg.nii.gz. - neighborhood_type: Neighborhood type used in finding mode. 1 - facing\ - neighbors, 2 - edges, 3 - corners. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VRoiModalGrowOutputs`). - """ - if neighborhood_type is not None and not (1 <= neighborhood_type <= 3): - raise ValueError(f"'neighborhood_type' must be between 1 <= x <= 3 but was {neighborhood_type}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__ROI_MODAL_GROW_METADATA) - cargs = [] - cargs.append("@ROI_modal_grow") - cargs.append("-input") - cargs.extend([ - "-input", - execution.input_file(input_dset) - ]) - cargs.append("-niters") - cargs.extend([ - "-niters", - str(niters) - ]) - cargs.append("-outdir") - if outdir is not None: - cargs.extend([ - "-outdir", - outdir - ]) - cargs.append("-mask") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - cargs.append("-prefix") - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - cargs.append("-NN") - if neighborhood_type is not None: - cargs.extend([ - "-NN", - str(neighborhood_type) - ]) - ret = VRoiModalGrowOutputs( - root=execution.output_file("."), - output_file=execution.output_file(outdir + "/" + prefix + ".nii.gz") if (outdir is not None and prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VRoiModalGrowOutputs", - "V__ROI_MODAL_GROW_METADATA", - "v__roi_modal_grow", -] diff --git a/python/src/niwrap/afni/v__scale_volume.py b/python/src/niwrap/afni/v__scale_volume.py deleted file mode 100644 index 5e8e012c7..000000000 --- a/python/src/niwrap/afni/v__scale_volume.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SCALE_VOLUME_METADATA = Metadata( - id="6e46cf21f8a20a776ceb86c492abbe680f609ab9.boutiques", - name="@ScaleVolume", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VScaleVolumeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__scale_volume(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output scaled dataset""" - - -def v__scale_volume( - val_clip: list[float] | None = None, - perc_clip: list[float] | None = None, - scale_by_mean: bool = False, - scale_by_median: bool = False, - norm: bool = False, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> VScaleVolumeOutputs: - """ - A tool to scale the volume of datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - val_clip: Min and Max of output dataset. Default V0 = 0 and V1 = 255. - perc_clip: Set lowest P0 percentile to Min and highest P1 percentile to\ - Max. Default P0 = 2 and P1 = 98. - scale_by_mean: Divide each sub-brick by mean of non-zero voxels. - scale_by_median: Divide each sub-brick by median of non-zero voxels. - norm: For each time series T, Tnorm = (T - mean(T)) / stdev(T). - mask: Restrict to non-zero values of given mask dataset. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VScaleVolumeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SCALE_VOLUME_METADATA) - cargs = [] - cargs.append("@ScaleVolume") - cargs.append("[<-input") - cargs.append("DSET>]") - cargs.append("[<-prefix") - cargs.append("PREFIX>]") - if val_clip is not None: - cargs.extend([ - "-val_clip", - *map(str, val_clip) - ]) - if perc_clip is not None: - cargs.extend([ - "-perc_clip", - *map(str, perc_clip) - ]) - if scale_by_mean: - cargs.append("-scale_by_mean") - if scale_by_median: - cargs.append("-scale_by_median") - if norm: - cargs.append("-norm") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - ret = VScaleVolumeOutputs( - root=execution.output_file("."), - output_file=execution.output_file("<-prefix PREFIX>_scaled"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VScaleVolumeOutputs", - "V__SCALE_VOLUME_METADATA", - "v__scale_volume", -] diff --git a/python/src/niwrap/afni/v__script_check.py b/python/src/niwrap/afni/v__script_check.py deleted file mode 100644 index 76a745c99..000000000 --- a/python/src/niwrap/afni/v__script_check.py +++ /dev/null @@ -1,75 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SCRIPT_CHECK_METADATA = Metadata( - id="1ec7bab89de6f0062a23a1361628a4abde50ae24.boutiques", - name="@ScriptCheck", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VScriptCheckOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__script_check(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - uncleaned_file: OutputPathType - """Uncleaned original file with specified suffix""" - cleaned_file: OutputPathType - """Cleaned file if -clean option is used""" - - -def v__script_check( - scripts: list[InputPathType], - clean: bool = False, - suffix: str | None = None, - runner: Runner | None = None, -) -> VScriptCheckOutputs: - """ - Checks scripts for improperly terminated lines and optionally cleans them. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - scripts: Scripts to be checked for improperly terminated lines. - clean: Clean bad line breaks. - suffix: Rename uncleaned file with specified suffix. Default is .uncln. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VScriptCheckOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SCRIPT_CHECK_METADATA) - cargs = [] - cargs.append("@ScriptCheck") - if clean: - cargs.append("-clean") - if suffix is not None: - cargs.extend([ - "-suffix", - suffix - ]) - cargs.extend([execution.input_file(f) for f in scripts]) - ret = VScriptCheckOutputs( - root=execution.output_file("."), - uncleaned_file=execution.output_file("{SCRIPT}.uncln"), - cleaned_file=execution.output_file("{SCRIPT}"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VScriptCheckOutputs", - "V__SCRIPT_CHECK_METADATA", - "v__script_check", -] diff --git a/python/src/niwrap/afni/v__shift_volume.py b/python/src/niwrap/afni/v__shift_volume.py deleted file mode 100644 index dee73f0a3..000000000 --- a/python/src/niwrap/afni/v__shift_volume.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SHIFT_VOLUME_METADATA = Metadata( - id="c0376ba183601d3473954360e9ced14b9b6366b5.boutiques", - name="@Shift_Volume", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VShiftVolumeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__shift_volume(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Shifted output dataset.""" - - -def v__shift_volume( - dset: InputPathType, - prefix: str, - rai_shift_vector: list[float] | None = None, - mni_anat_to_mni: bool = False, - mni_to_mni_anat: bool = False, - no_cp: bool = False, - runner: Runner | None = None, -) -> VShiftVolumeOutputs: - """ - Tool to shift a dataset in the RAI coordinate system or between MNI anatomical - space and MNI space. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Input dataset, typically an anatomical dataset to be aligned to\ - BASE. - prefix: Prefix for the output dataset. - rai_shift_vector: Move dataset by dR, dA, dI mm (RAI coordinate system). - mni_anat_to_mni: Move dataset from MNI Anatomical space to MNI space\ - (equivalent to -rai_shift 0 -4 -5). - mni_to_mni_anat: Move dataset from MNI space to MNI Anatomical space\ - (equivalent to -rai_shift 0 4 5). - no_cp: Do not create new data, shift the existing ones (use with\ - caution). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VShiftVolumeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SHIFT_VOLUME_METADATA) - cargs = [] - cargs.append("@Shift_Volume") - if rai_shift_vector is not None: - cargs.extend([ - "-rai_shift", - *map(str, rai_shift_vector) - ]) - if mni_anat_to_mni: - cargs.append("-MNI_Anat_to_MNI") - if mni_to_mni_anat: - cargs.append("-MNI_to_MNI_Anat") - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if no_cp: - cargs.append("-no_cp") - cargs.extend([ - "-prefix", - prefix - ]) - ret = VShiftVolumeOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VShiftVolumeOutputs", - "V__SHIFT_VOLUME_METADATA", - "v__shift_volume", -] diff --git a/python/src/niwrap/afni/v__show_dynamic_range.py b/python/src/niwrap/afni/v__show_dynamic_range.py deleted file mode 100644 index 1e9f784d6..000000000 --- a/python/src/niwrap/afni/v__show_dynamic_range.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SHOW_DYNAMIC_RANGE_METADATA = Metadata( - id="e7888caae2b4b5788c19d139f163887f1b35c7f2.boutiques", - name="@ShowDynamicRange", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VShowDynamicRangeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__show_dynamic_range(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - minpercchange_file: OutputPathType - """Dataset showing the percent signal change that an increment of 1 - digitized value in the time series corresponds to.""" - range_file: OutputPathType - """Dataset showing the number of discrete levels used to represent the time - series.""" - - -def v__show_dynamic_range( - infile: InputPathType, - runner: Runner | None = None, -) -> VShowDynamicRangeOutputs: - """ - The script checks the dynamic range of the time series data at locations inside - the brain. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - infile: Input EPI time series dataset (e.g. epi.nii.gz). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VShowDynamicRangeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SHOW_DYNAMIC_RANGE_METADATA) - cargs = [] - cargs.append("@ShowDynamicRange") - cargs.append(execution.input_file(infile)) - ret = VShowDynamicRangeOutputs( - root=execution.output_file("."), - minpercchange_file=execution.output_file(pathlib.Path(infile).name + "_minpercchange.nii.gz"), - range_file=execution.output_file(pathlib.Path(infile).name + ".range.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VShowDynamicRangeOutputs", - "V__SHOW_DYNAMIC_RANGE_METADATA", - "v__show_dynamic_range", -] diff --git a/python/src/niwrap/afni/v__simulate_motion.py b/python/src/niwrap/afni/v__simulate_motion.py deleted file mode 100644 index 116f8f60e..000000000 --- a/python/src/niwrap/afni/v__simulate_motion.py +++ /dev/null @@ -1,150 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SIMULATE_MOTION_METADATA = Metadata( - id="5fc17ce508dbb62923e813f5cff61e70e1accb2d.boutiques", - name="@simulate_motion", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSimulateMotionOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__simulate_motion(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - simulated_motion_output: OutputPathType | None - """Motion simulated EPI time series""" - - -def v__simulate_motion( - epi: InputPathType, - motion_file: InputPathType, - epi_timing: InputPathType | None = None, - prefix: str | None = None, - save_workdir: bool = False, - test: bool = False, - verb_level: float | None = None, - vr_base: float | None = None, - warp_method: str | None = None, - warp_1_d: InputPathType | None = None, - warp_master: InputPathType | None = None, - wsinc5: bool = False, - help_: bool = False, - hist: bool = False, - todo: bool = False, - ver: bool = False, - runner: Runner | None = None, -) -> VSimulateMotionOutputs: - """ - Create simulated motion time series in an EPI dataset based on the provided - motion parameters and an input volume. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - epi: Input EPI volume or time series (only a volreg base is needed,\ - though more is okay). - motion_file: Motion parameter file (as output by 3dvolreg). - epi_timing: Provide EPI dataset with slice timing. - prefix: Prefix for data results (default = motion_sim.NUM_TRS). - save_workdir: Do not remove the 'work' directory. - test: Only test running the program, do not create a simulated motion\ - dataset. - verb_level: Specify a verbose level (default = 1). - vr_base: 0-based index of volreg base in EPI dataset. - warp_method: Specify a method for forward alignment/transform. - warp_1_d: Specify a 12 parameter affine transformation. - warp_master: Specify a grid master dataset for the -warp_1D transform. - wsinc5: Use wsinc5 interpolation in 3dAllineate. - help_: Show help message. - hist: Show program modification history. - todo: Show current todo list. - ver: Show program version. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSimulateMotionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SIMULATE_MOTION_METADATA) - cargs = [] - cargs.append("@simulate_motion") - cargs.extend([ - "-epi", - execution.input_file(epi) - ]) - cargs.extend([ - "-motion_file", - execution.input_file(motion_file) - ]) - if epi_timing is not None: - cargs.extend([ - "-epi_timing", - execution.input_file(epi_timing) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if save_workdir: - cargs.append("-save_workdir") - if test: - cargs.append("-test") - if verb_level is not None: - cargs.extend([ - "-verb", - str(verb_level) - ]) - if vr_base is not None: - cargs.extend([ - "-vr_base", - str(vr_base) - ]) - if warp_method is not None: - cargs.extend([ - "-warp_method", - warp_method - ]) - if warp_1_d is not None: - cargs.extend([ - "-warp_1D", - execution.input_file(warp_1_d) - ]) - if warp_master is not None: - cargs.extend([ - "-warp_master", - execution.input_file(warp_master) - ]) - if wsinc5: - cargs.append("-wsinc5") - if help_: - cargs.append("-help") - if hist: - cargs.append("-hist") - if todo: - cargs.append("-todo") - if ver: - cargs.append("-ver") - ret = VSimulateMotionOutputs( - root=execution.output_file("."), - simulated_motion_output=execution.output_file(prefix + "_simulated_motion.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSimulateMotionOutputs", - "V__SIMULATE_MOTION_METADATA", - "v__simulate_motion", -] diff --git a/python/src/niwrap/afni/v__skull_strip_touch_up.py b/python/src/niwrap/afni/v__skull_strip_touch_up.py deleted file mode 100644 index f3a164b11..000000000 --- a/python/src/niwrap/afni/v__skull_strip_touch_up.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SKULL_STRIP_TOUCH_UP_METADATA = Metadata( - id="c803b7c3e18cf11101f928ee0b08cbc52d5011e4.boutiques", - name="@SkullStrip_TouchUp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSkullStripTouchUpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__skull_strip_touch_up(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_folder: OutputPathType - """Output folder containing the touch-up results""" - output_mask: OutputPathType - """Output binary mask (if -mask_out flag is used)""" - - -def v__skull_strip_touch_up( - prefix: str, - brain_dataset: InputPathType, - head_dataset: InputPathType, - mask_out: bool = False, - orig_dim: bool = False, - runner: Runner | None = None, -) -> VSkullStripTouchUpOutputs: - """ - Helper program to touch up failed skull stripping by resampling data, allowing - manual edits, and outputting corrected data. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - prefix: Output file and folder name. - brain_dataset: Skull stripped data set to touch up. - head_dataset: Whole head anatomical data set. - mask_out: Output a binary mask in addition to actual data. - orig_dim: Edit in the original image dimensions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSkullStripTouchUpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SKULL_STRIP_TOUCH_UP_METADATA) - cargs = [] - cargs.append("@SkullStrip_TouchUp") - cargs.append("-prefix") - cargs.append(prefix) - cargs.append("-brain") - cargs.append(execution.input_file(brain_dataset)) - cargs.append("-head") - cargs.append(execution.input_file(head_dataset)) - if mask_out: - cargs.append("-mask_out") - if orig_dim: - cargs.append("-orig_dim") - ret = VSkullStripTouchUpOutputs( - root=execution.output_file("."), - output_folder=execution.output_file(prefix + "_SS_touch_up"), - output_mask=execution.output_file(prefix + "_mask.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSkullStripTouchUpOutputs", - "V__SKULL_STRIP_TOUCH_UP_METADATA", - "v__skull_strip_touch_up", -] diff --git a/python/src/niwrap/afni/v__snapshot_volreg.py b/python/src/niwrap/afni/v__snapshot_volreg.py deleted file mode 100644 index ddbda40f1..000000000 --- a/python/src/niwrap/afni/v__snapshot_volreg.py +++ /dev/null @@ -1,74 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SNAPSHOT_VOLREG_METADATA = Metadata( - id="e11a34b276acc0a9b81802237e6fe33d1478ea13.boutiques", - name="@snapshot_volreg", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSnapshotVolregOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__snapshot_volreg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_jpeg: OutputPathType | None - """JPEG image showing the edges of the EPI dataset overlayed on the - anatomical dataset""" - - -def v__snapshot_volreg( - anatdataset: InputPathType, - epidataset: InputPathType, - jname: str | None = None, - xdisplay: str | None = None, - runner: Runner | None = None, -) -> VSnapshotVolregOutputs: - """ - Create a JPEG image showing the edges of an EPI dataset overlayed on an - anatomical dataset to judge 3D registration quality. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - anatdataset: Anatomical dataset file. - epidataset: EPI dataset file. - jname: Name for the output JPEG file. - xdisplay: Display number of an already running Xvfb instance. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSnapshotVolregOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SNAPSHOT_VOLREG_METADATA) - cargs = [] - cargs.append("@snapshot_volreg") - cargs.append(execution.input_file(anatdataset)) - cargs.append(execution.input_file(epidataset)) - if jname is not None: - cargs.append(jname) - if xdisplay is not None: - cargs.append(xdisplay) - ret = VSnapshotVolregOutputs( - root=execution.output_file("."), - output_jpeg=execution.output_file(jname + ".jpg") if (jname is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSnapshotVolregOutputs", - "V__SNAPSHOT_VOLREG_METADATA", - "v__snapshot_volreg", -] diff --git a/python/src/niwrap/afni/v__spharm_examples.py b/python/src/niwrap/afni/v__spharm_examples.py deleted file mode 100644 index a1340ff53..000000000 --- a/python/src/niwrap/afni/v__spharm_examples.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SPHARM_EXAMPLES_METADATA = Metadata( - id="7b9dbc8f033f538b7638320e8d57980c476bb1cc.boutiques", - name="@Spharm.examples", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSpharmExamplesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__spharm_examples(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__spharm_examples( - help_web: bool = False, - help_web_alias: bool = False, - help_view: bool = False, - help_view_alias: bool = False, - all_opts: bool = False, - help_find: str | None = None, - runner: Runner | None = None, -) -> VSpharmExamplesOutputs: - """ - A script to demonstrate the usage of spherical harmonics decomposition with - SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - help_web: Open webpage with help for this program. - help_web_alias: Same as -h_web. - help_view: Open -help output in a GUI editor. - help_view_alias: Same as -h_view. - all_opts: List all of the options for this script. - help_find: Search for lines containing WORD in -help output. Search is\ - approximate. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSpharmExamplesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SPHARM_EXAMPLES_METADATA) - cargs = [] - cargs.append("@Spharm.examples") - if help_web: - cargs.append("-h_web") - if help_web_alias: - cargs.append("-hweb") - if help_view: - cargs.append("-h_view") - if help_view_alias: - cargs.append("-hview") - if all_opts: - cargs.append("-all_opts") - if help_find is not None: - cargs.extend([ - "-h_find", - help_find - ]) - ret = VSpharmExamplesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSpharmExamplesOutputs", - "V__SPHARM_EXAMPLES_METADATA", - "v__spharm_examples", -] diff --git a/python/src/niwrap/afni/v__sswarper.py b/python/src/niwrap/afni/v__sswarper.py deleted file mode 100644 index 8b9cbe5ba..000000000 --- a/python/src/niwrap/afni/v__sswarper.py +++ /dev/null @@ -1,221 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SSWARPER_METADATA = Metadata( - id="1cb5786a5affefb03cc2e65aca5873657f0dfd5b.boutiques", - name="@SSwarper", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSswarperOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__sswarper(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - anat_do: OutputPathType - """Deobliqued version of original dataset""" - anat_u: OutputPathType - """Intensity uniform-ized original dataset""" - anat_ua: OutputPathType - """Anisotropically smoothed version of the uniformized dataset""" - anat_uac: OutputPathType - """Ceiling-capped version of the anisotropically smoothed dataset""" - anat_s: OutputPathType - """First pass skull-stripped original dataset""" - anat_ss: OutputPathType - """Second pass skull-stripped original dataset""" - anat_qq: OutputPathType - """Skull-stripped dataset nonlinearly warped to the base template space""" - anat_qq_affine: OutputPathType - """Affine matrix to transform original dataset to base template space""" - anat_qq_warp: OutputPathType - """Incremental warp from affine transformation to nonlinearly aligned - dataset""" - am_snapshot: OutputPathType - """3x3 snapshot image of the nonlinearly warped dataset with edges from the - base template overlaid""" - ma_snapshot: OutputPathType - """Similar to AM_snapshot, but with roles of the template and anatomical - dataset reversed""" - qc_anat_qq: OutputPathType - """3 rows of 8 slices snapshot image for checking alignment""" - qc_anat_ss: OutputPathType - """Snapshot image to check skullstripping in original space""" - init_overlap_qc: OutputPathType - """Montage to check initial overlap of source and base datasets""" - - -def v__sswarper( - input_file: InputPathType, - base_template: InputPathType, - subject_id: str, - output_dir: str | None = None, - min_patch_size: float | None = None, - no_lite: bool = False, - skip_warp: bool = False, - unifize_off: bool = False, - init_skullstr_off: bool = False, - extra_qc_off: bool = False, - jump_to_extra_qc: bool = False, - cost_nl_init: str | None = None, - cost_nl_final: str | None = None, - deoblique: bool = False, - deoblique_refitly: bool = False, - warp_scale: float | None = None, - ssopt_flag: str | None = None, - aniso_off: bool = False, - ceil_off: bool = False, - tmp_name_nice: bool = False, - echo: bool = False, - verbose: bool = False, - noclean: bool = False, - runner: Runner | None = None, -) -> VSswarperOutputs: - """ - Dual purposes for processing a given subject's anatomical volume: skull-strip - the brain and calculate the warp to a reference template/standard space. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: An anatomical dataset, not skull-stripped, with about 1 mm\ - resolution. - base_template: A base template dataset with similar contrast to the\ - input dataset. - subject_id: Name code for output datasets (e.g., 'sub007'). - output_dir: Output directory for all files from this program. - min_patch_size: Minimum patch size on final 3dQwarp. - no_lite: Do not use the '-lite' option with 3dQwarp. - skip_warp: Do not compute past the output of anatSS..nii. - unifize_off: Do not start with a 3dUnifize command. - init_skullstr_off: Do not preprocess with a 3dSkullstrip command. - extra_qc_off: Do not make extra QC images. - jump_to_extra_qc: Just make the two QC*jpg images from a previous run. - cost_nl_init: Specify cost function for initial nonlinear (3dQwarp)\ - part of alignment. - cost_nl_final: Specify cost function for final nonlinear (3dQwarp)\ - parts of alignment. - deoblique: Apply obliquity information to deoblique the input volume. - deoblique_refitly: Purge obliquity information to deoblique the input\ - volume. - warp_scale: Control flexibility of warps in 3dQwarp. - ssopt_flag: Append a string of options for 3dSkullStrip. - aniso_off: Do not preprocess with a 3danisosmooth command. - ceil_off: Turn off capping on values after anisosmoothing. - tmp_name_nice: Use nicer, non-random intermediate file prefix for\ - temporary files. - echo: Run the script with 'set echo' for extra verbosity in the\ - terminal output. - verbose: Apply the '-verb' option to 3dQwarp for verbose progress\ - information. - noclean: Do not delete the 'junk' files at the end of computations. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSswarperOutputs`). - """ - if warp_scale is not None and not (0.1 <= warp_scale <= 1.0): - raise ValueError(f"'warp_scale' must be between 0.1 <= x <= 1.0 but was {warp_scale}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__SSWARPER_METADATA) - cargs = [] - cargs.append("@SSwarper") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-base") - cargs.append(execution.input_file(base_template)) - cargs.append("-subid") - cargs.append(subject_id) - if output_dir is not None: - cargs.extend([ - "-odir", - output_dir - ]) - if min_patch_size is not None: - cargs.extend([ - "-minp", - str(min_patch_size) - ]) - if no_lite: - cargs.append("-nolite") - if skip_warp: - cargs.append("-skipwarp") - if unifize_off: - cargs.append("-unifize_off") - if init_skullstr_off: - cargs.append("-init_skullstr_off") - if extra_qc_off: - cargs.append("-extra_qc_off") - if jump_to_extra_qc: - cargs.append("-jump_to_extra_qc") - if cost_nl_init is not None: - cargs.extend([ - "-cost_nl_init", - cost_nl_init - ]) - if cost_nl_final is not None: - cargs.extend([ - "-cost_nl_final", - cost_nl_final - ]) - if deoblique: - cargs.append("-deoblique") - if deoblique_refitly: - cargs.append("-deoblique_refitly") - if warp_scale is not None: - cargs.extend([ - "-warpscale", - str(warp_scale) - ]) - if ssopt_flag is not None: - cargs.extend([ - "-SSopt", - ssopt_flag - ]) - if aniso_off: - cargs.append("-aniso_off") - if ceil_off: - cargs.append("-ceil_off") - if tmp_name_nice: - cargs.append("-tmp_name_nice") - if echo: - cargs.append("-echo") - if verbose: - cargs.append("-verb") - if noclean: - cargs.append("-noclean") - ret = VSswarperOutputs( - root=execution.output_file("."), - anat_do=execution.output_file("anatDO." + subject_id + ".nii"), - anat_u=execution.output_file("anatU." + subject_id + ".nii"), - anat_ua=execution.output_file("anatUA." + subject_id + ".nii"), - anat_uac=execution.output_file("anatUAC." + subject_id + ".nii"), - anat_s=execution.output_file("anatS." + subject_id + ".nii"), - anat_ss=execution.output_file("anatSS." + subject_id + ".nii"), - anat_qq=execution.output_file("anatQQ." + subject_id + ".nii"), - anat_qq_affine=execution.output_file("anatQQ." + subject_id + ".aff12.1D"), - anat_qq_warp=execution.output_file("anatQQ." + subject_id + "_WARP.nii"), - am_snapshot=execution.output_file("AM" + subject_id + ".jpg"), - ma_snapshot=execution.output_file("MA" + subject_id + ".jpg"), - qc_anat_qq=execution.output_file("QC_anatQQ." + subject_id + ".jpg"), - qc_anat_ss=execution.output_file("QC_anatSS." + subject_id + ".jpg"), - init_overlap_qc=execution.output_file("init_qc_00_overlap_uinp_obase.jpg"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSswarperOutputs", - "V__SSWARPER_METADATA", - "v__sswarper", -] diff --git a/python/src/niwrap/afni/v__statauxcode.py b/python/src/niwrap/afni/v__statauxcode.py deleted file mode 100644 index 1983adc6a..000000000 --- a/python/src/niwrap/afni/v__statauxcode.py +++ /dev/null @@ -1,62 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__STATAUXCODE_METADATA = Metadata( - id="f6c1767e1a9b29b920fca298ee485697451c9d8a.boutiques", - name="@statauxcode", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VStatauxcodeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__statauxcode(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """Output file containing the result of the conversion""" - - -def v__statauxcode( - code_: str, - runner: Runner | None = None, -) -> VStatauxcodeOutputs: - """ - Returns the name or number of a statistics code based on specified mappings. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - code_: The statistical code or its numerical equivalent to be\ - converted. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VStatauxcodeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__STATAUXCODE_METADATA) - cargs = [] - cargs.append("@statauxcode") - cargs.append(code_) - ret = VStatauxcodeOutputs( - root=execution.output_file("."), - output=execution.output_file("output.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VStatauxcodeOutputs", - "V__STATAUXCODE_METADATA", - "v__statauxcode", -] diff --git a/python/src/niwrap/afni/v__suma_acknowledge.py b/python/src/niwrap/afni/v__suma_acknowledge.py deleted file mode 100644 index e7301ea57..000000000 --- a/python/src/niwrap/afni/v__suma_acknowledge.py +++ /dev/null @@ -1,100 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_ACKNOWLEDGE_METADATA = Metadata( - id="d037b40d3b42a963ac007ed6a05e2db450974d09.boutiques", - name="@suma_acknowledge", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaAcknowledgeOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_acknowledge(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output graph dataset""" - - -def v__suma_acknowledge( - input_file: InputPathType, - surface_file: InputPathType, - output_prefix: str, - center_flag: bool = False, - subsurface_file: str | None = None, - scale_factor: float | None = None, - reduce_factor: float | None = None, - runner: Runner | None = None, -) -> VSumaAcknowledgeOutputs: - """ - Demo script to create a graph dataset to show names of individuals and groups, - potentially useful for acknowledgements in a talk. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Required input text file with format for each line: first\ - last groupname. - surface_file: Required surface to place nodes. - output_prefix: Output prefix for graph dataset. - center_flag: Put center coord at x,y,z=0,0,0. Otherwise, uses average\ - xyz in surface. - subsurface_file: Surface for surrounding members of group (use ld2,\ - ld4, ld5, ld6, .... default is ld5). - scale_factor: Scale xyz for group nodes (default is 1.0). - reduce_factor: Scale xyz offsets for member nodes (xyz/r), default is\ - 10. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaAcknowledgeOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_ACKNOWLEDGE_METADATA) - cargs = [] - cargs.append("@suma_acknowledge") - cargs.append("-input") - cargs.append(execution.input_file(input_file)) - cargs.append("-surf") - cargs.append(execution.input_file(surface_file)) - cargs.append("-prefix") - cargs.append(output_prefix) - if center_flag: - cargs.append("-center") - if subsurface_file is not None: - cargs.extend([ - "-subsurf", - subsurface_file - ]) - if scale_factor is not None: - cargs.extend([ - "-scalefactor", - str(scale_factor) - ]) - if reduce_factor is not None: - cargs.extend([ - "-reducefactor", - str(reduce_factor) - ]) - ret = VSumaAcknowledgeOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output_prefix + "_graph_dataset"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaAcknowledgeOutputs", - "V__SUMA_ACKNOWLEDGE_METADATA", - "v__suma_acknowledge", -] diff --git a/python/src/niwrap/afni/v__suma_align_to_experiment.py b/python/src/niwrap/afni/v__suma_align_to_experiment.py deleted file mode 100644 index 3798c5937..000000000 --- a/python/src/niwrap/afni/v__suma_align_to_experiment.py +++ /dev/null @@ -1,189 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_ALIGN_TO_EXPERIMENT_METADATA = Metadata( - id="8f81484159017f8749f8211125315dcfa8d64e88.boutiques", - name="@SUMA_AlignToExperiment", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaAlignToExperimentOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_align_to_experiment(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - aligned_volume: OutputPathType | None - """Output volume after alignment.""" - additional_followers: OutputPathType | None - """Output followers dataset after transforming.""" - - -def v__suma_align_to_experiment( - exp_anat: InputPathType, - surf_anat: InputPathType, - dxyz: float | None = None, - out_dxyz: float | None = None, - wd: bool = False, - al: bool = False, - al_opt: str | None = None, - ok_change_view: bool = False, - strip_skull: str | None = None, - skull_strip_opt: str | None = None, - align_centers: bool = False, - init_xform: InputPathType | None = None, - ea_clip_below: float | None = None, - prefix: str | None = None, - surf_anat_followers: str | None = None, - followers_interp: str | None = None, - atlas_followers: bool = False, - echo: bool = False, - keep_tmp: bool = False, - overwrite_resp: str | None = None, - runner: Runner | None = None, -) -> VSumaAlignToExperimentOutputs: - """ - Creates a version of Surface Anatomy that is registered to Experiment Anatomy. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - exp_anat: Name of high resolution anatomical data set in register with\ - experimental data. - surf_anat: Path and name of high resolution antomical data set used to\ - create the surface. - dxyz: Optional parameter to downsample anatomical volumes to dxyz mm\ - voxel resolution before registration. - out_dxyz: Output the final aligned volume at a cubic voxelsize of\ - DXYZmm. - wd: Use 3dWarpDrive's general affine transform (12 param) instead of\ - 3dvolreg's 6 parameters. - al: Use 3dAllineate to do the 12 parameter alignment. Cost function is\ - 'lpa'. - al_opt: Specify set of options to pass to 3dAllineate. - ok_change_view: Be quiet when view of registered volume is changed to\ - match that of the Experiment_Anatomy. - strip_skull: Use 3dSkullStrip to remove non-brain tissue. - skull_strip_opt: Pass the options to 3dSkullStrip. - align_centers: Add an additional transformation to align the volume\ - centers. - init_xform: Apply affine transform file to Surface_Anatomy before\ - beginning registration. - ea_clip_below: Set slices below CLPmm in 'Experiment Anatomy' to zero. - prefix: Prefix for the output volume. - surf_anat_followers: Apply the same alignment transform to additional\ - datasets. - followers_interp: Set the interpolation mode for the follower datasets. - atlas_followers: Automatically set the followers to be atlases in the\ - directory of -surf_anat. - echo: Echo all commands to terminal for debugging. - keep_tmp: Keep temporary files for debugging. - overwrite_resp: Answer 'overwrite' questions automatically. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaAlignToExperimentOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_ALIGN_TO_EXPERIMENT_METADATA) - cargs = [] - cargs.append("@SUMA_AlignToExperiment") - cargs.extend([ - "-exp_anat", - execution.input_file(exp_anat) - ]) - cargs.extend([ - "-surf_anat", - execution.input_file(surf_anat) - ]) - if dxyz is not None: - cargs.extend([ - "-dxyz", - str(dxyz) - ]) - if out_dxyz is not None: - cargs.extend([ - "-out_dxyz", - str(out_dxyz) - ]) - if wd: - cargs.append("-wd") - if al: - cargs.append("-al") - if al_opt is not None: - cargs.extend([ - "-al_opt", - al_opt - ]) - if ok_change_view: - cargs.append("-ok_change_view") - if strip_skull is not None: - cargs.extend([ - "-strip_skull", - strip_skull - ]) - if skull_strip_opt is not None: - cargs.extend([ - "-skull_strip_opt", - skull_strip_opt - ]) - if align_centers: - cargs.append("-align_centers") - if init_xform is not None: - cargs.extend([ - "-init_xform", - execution.input_file(init_xform) - ]) - if ea_clip_below is not None: - cargs.extend([ - "-EA_clip_below", - str(ea_clip_below) - ]) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - if surf_anat_followers is not None: - cargs.extend([ - "-surf_anat_followers", - surf_anat_followers - ]) - if followers_interp is not None: - cargs.extend([ - "-followers_interp", - followers_interp - ]) - if atlas_followers: - cargs.append("-atlas_followers") - if echo: - cargs.append("-echo") - if keep_tmp: - cargs.append("-keep_tmp") - if overwrite_resp is not None: - cargs.extend([ - "-overwrite_resp", - overwrite_resp - ]) - ret = VSumaAlignToExperimentOutputs( - root=execution.output_file("."), - aligned_volume=execution.output_file(prefix + "_Alnd_Exp.nii.gz") if (prefix is not None) else None, - additional_followers=execution.output_file(prefix + "_Alnd_Exp_Fdset.nii.gz") if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaAlignToExperimentOutputs", - "V__SUMA_ALIGN_TO_EXPERIMENT_METADATA", - "v__suma_align_to_experiment", -] diff --git a/python/src/niwrap/afni/v__suma_fsvol_to_brik.py b/python/src/niwrap/afni/v__suma_fsvol_to_brik.py deleted file mode 100644 index 3b659067d..000000000 --- a/python/src/niwrap/afni/v__suma_fsvol_to_brik.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_FSVOL_TO_BRIK_METADATA = Metadata( - id="64d9c993370a9f2af5b9e1db9a8eec42cf5e5036.boutiques", - name="@SUMA_FSvolToBRIK", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaFsvolToBrikOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_fsvol_to_brik(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_brik: OutputPathType - """Output BRIK volume converted from FreeSurfer data""" - out_head: OutputPathType - """Header file for the output BRIK volume""" - - -def v__suma_fsvol_to_brik( - fs_vol_data: InputPathType, - prefix: str, - runner: Runner | None = None, -) -> VSumaFsvolToBrikOutputs: - """ - A script to convert COR- or .mgz files from FreeSurfer to BRIK format. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - fs_vol_data: Input FreeSurfer volume data (e.g. COR- images or .mgz\ - volume). - prefix: Prefix for output BRIK volume. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaFsvolToBrikOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_FSVOL_TO_BRIK_METADATA) - cargs = [] - cargs.append("@SUMA_FSvolToBRIK") - cargs.append(execution.input_file(fs_vol_data)) - cargs.append(prefix) - ret = VSumaFsvolToBrikOutputs( - root=execution.output_file("."), - out_brik=execution.output_file(prefix + ".BRIK"), - out_head=execution.output_file(prefix + ".HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaFsvolToBrikOutputs", - "V__SUMA_FSVOL_TO_BRIK_METADATA", - "v__suma_fsvol_to_brik", -] diff --git a/python/src/niwrap/afni/v__suma_make_spec_caret.py b/python/src/niwrap/afni/v__suma_make_spec_caret.py deleted file mode 100644 index 7396631fc..000000000 --- a/python/src/niwrap/afni/v__suma_make_spec_caret.py +++ /dev/null @@ -1,69 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_MAKE_SPEC_CARET_METADATA = Metadata( - id="d6c8f4a4c9a4bdbf869e9c12beaa446f3b1adfdb.boutiques", - name="@SUMA_Make_Spec_Caret", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaMakeSpecCaretOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_make_spec_caret(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - left_hemisphere_spec: OutputPathType - """Output spec file for the left hemisphere""" - right_hemisphere_spec: OutputPathType - """Output spec file for the right hemisphere""" - - -def v__suma_make_spec_caret( - subject_id: str, - runner: Runner | None = None, -) -> VSumaMakeSpecCaretOutputs: - """ - Prepare surfaces for viewing in SUMA, tested with Caret-5.2 surfaces. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subject_id: Subject ID for file naming. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaMakeSpecCaretOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_MAKE_SPEC_CARET_METADATA) - cargs = [] - cargs.append("@SUMA_Make_Spec_Caret") - cargs.append("[OPTIONS]") - cargs.append("-sid") - cargs.extend([ - "-sid", - subject_id - ]) - ret = VSumaMakeSpecCaretOutputs( - root=execution.output_file("."), - left_hemisphere_spec=execution.output_file(subject_id + "_lh.spec"), - right_hemisphere_spec=execution.output_file(subject_id + "_rh.spec"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaMakeSpecCaretOutputs", - "V__SUMA_MAKE_SPEC_CARET_METADATA", - "v__suma_make_spec_caret", -] diff --git a/python/src/niwrap/afni/v__suma_make_spec_fs.py b/python/src/niwrap/afni/v__suma_make_spec_fs.py deleted file mode 100644 index a59087a59..000000000 --- a/python/src/niwrap/afni/v__suma_make_spec_fs.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_MAKE_SPEC_FS_METADATA = Metadata( - id="cc2c0be12627063dcfbca9486f07e9956d8d63ee.boutiques", - name="@SUMA_Make_Spec_FS", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaMakeSpecFsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_make_spec_fs(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - suma_output: OutputPathType - """All created files are stored in a new SUMA directory""" - - -def v__suma_make_spec_fs( - subject_id: str, - runner: Runner | None = None, -) -> VSumaMakeSpecFsOutputs: - """ - Prepare for surface viewing in SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subject_id: Required subject ID for file naming. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaMakeSpecFsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_MAKE_SPEC_FS_METADATA) - cargs = [] - cargs.append("@SUMA_Make_Spec_FS") - cargs.append("[OPTIONS]") - cargs.append("-sid") - cargs.extend([ - "-sid", - subject_id - ]) - ret = VSumaMakeSpecFsOutputs( - root=execution.output_file("."), - suma_output=execution.output_file("SUMA/*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaMakeSpecFsOutputs", - "V__SUMA_MAKE_SPEC_FS_METADATA", - "v__suma_make_spec_fs", -] diff --git a/python/src/niwrap/afni/v__suma_make_spec_sf.py b/python/src/niwrap/afni/v__suma_make_spec_sf.py deleted file mode 100644 index efab7ba64..000000000 --- a/python/src/niwrap/afni/v__suma_make_spec_sf.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_MAKE_SPEC_SF_METADATA = Metadata( - id="90885679016acaa65216974003bd8aae196276f4.boutiques", - name="@SUMA_Make_Spec_SF", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaMakeSpecSfOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_make_spec_sf(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_files: OutputPathType - """All created files are stored in SURFACES directory""" - - -def v__suma_make_spec_sf( - subject_id: str, - debug_level: int | None = None, - surface_path: str | None = None, - runner: Runner | None = None, -) -> VSumaMakeSpecSfOutputs: - """ - Prepare for surface viewing in SUMA. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - subject_id: Required subject ID for file naming. - debug_level: Print debug information along the way. - surface_path: Path to directory containing 'SURFACES' and AFNI volume\ - used in creating the surfaces. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaMakeSpecSfOutputs`). - """ - if debug_level is not None and not (debug_level <= 2): - raise ValueError(f"'debug_level' must be less than x <= 2 but was {debug_level}") - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_MAKE_SPEC_SF_METADATA) - cargs = [] - cargs.append("@SUMA_Make_Spec_SF") - if debug_level is not None: - cargs.extend([ - "-debug", - str(debug_level) - ]) - if surface_path is not None: - cargs.extend([ - "-sfpath", - surface_path - ]) - cargs.append("-sid") - cargs.extend([ - "-sid", - subject_id - ]) - ret = VSumaMakeSpecSfOutputs( - root=execution.output_file("."), - output_files=execution.output_file("SURFACES/*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaMakeSpecSfOutputs", - "V__SUMA_MAKE_SPEC_SF_METADATA", - "v__suma_make_spec_sf", -] diff --git a/python/src/niwrap/afni/v__suma_renumber_fs.py b/python/src/niwrap/afni/v__suma_renumber_fs.py deleted file mode 100644 index 5a830c441..000000000 --- a/python/src/niwrap/afni/v__suma_renumber_fs.py +++ /dev/null @@ -1,93 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_RENUMBER_FS_METADATA = Metadata( - id="8a49623824c67c6e033a941294f1334c45b7499b.boutiques", - name="@SUMA_renumber_FS", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaRenumberFsOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_renumber_fs(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - ren_all: OutputPathType - """Whole parcellation/segmentation file with renumbered ROIs.""" - ren_gm: OutputPathType - """Gray matter tissue segmentation map.""" - ren_wmat: OutputPathType - """White matter tissue segmentation map.""" - ren_csf: OutputPathType - """Cerebrospinal fluid tissue segmentation map.""" - ren_vent: OutputPathType - """Ventricles and choroid plexus tissue segmentation map.""" - ren_othr: OutputPathType - """Other tissue segmentation map (optic chiasm, non-WM-hypointens, etc.).""" - ren_unkn: OutputPathType - """Unknown tissue segmentation map (FS-defined 'unknown', with voxel value - >0).""" - ren_gmrois: OutputPathType - """Gray matter ROIs without '*-Cerebral-Cortex' dots.""" - fs_ap_wm: OutputPathType - """White matter mask (excluding the dotted part from FS).""" - fs_ap_latvent: OutputPathType - """Lateral ventricles mask ('*-Lateral-Ventricle').""" - ren_lbl_table: OutputPathType - """Labeltable of the new ROI values.""" - - -def v__suma_renumber_fs( - sumadir: str, - runner: Runner | None = None, -) -> VSumaRenumberFsOutputs: - """ - This script processes FreeSurfer-generated parcellation files and produces - various derived datasets and segmentation maps. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - sumadir: Path to the 'SUMA/' directory created by @SUMA_Make_Spec_FS. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaRenumberFsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_RENUMBER_FS_METADATA) - cargs = [] - cargs.append("@SUMA_renumber_FS") - cargs.append(sumadir) - ret = VSumaRenumberFsOutputs( - root=execution.output_file("."), - ren_all=execution.output_file("*_REN_all.nii.gz"), - ren_gm=execution.output_file("*_REN_gm.nii.gz"), - ren_wmat=execution.output_file("*_REN_wmat.nii.gz"), - ren_csf=execution.output_file("*_REN_csf.nii.gz"), - ren_vent=execution.output_file("*_REN_vent.nii.gz"), - ren_othr=execution.output_file("*_REN_othr.nii.gz"), - ren_unkn=execution.output_file("*_REN_unkn.nii.gz"), - ren_gmrois=execution.output_file("*_REN_gmrois.nii.gz"), - fs_ap_wm=execution.output_file("fs_ap_wm.nii.gz"), - fs_ap_latvent=execution.output_file("fs_ap_latvent.nii.gz"), - ren_lbl_table=execution.output_file("*_REN_all.niml.lt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaRenumberFsOutputs", - "V__SUMA_RENUMBER_FS_METADATA", - "v__suma_renumber_fs", -] diff --git a/python/src/niwrap/afni/v__suma_reprefixize_spec.py b/python/src/niwrap/afni/v__suma_reprefixize_spec.py deleted file mode 100644 index 6f18387cf..000000000 --- a/python/src/niwrap/afni/v__suma_reprefixize_spec.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SUMA_REPREFIXIZE_SPEC_METADATA = Metadata( - id="c73b1698148c7d358f694ab49b85daed836bc3f6.boutiques", - name="@suma_reprefixize_spec", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSumaReprefixizeSpecOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__suma_reprefixize_spec(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - prefixed_spec_files: OutputPathType - """Prefixed SUMA specification files""" - - -def v__suma_reprefixize_spec( - input_file: InputPathType, - prefix: str, - output_dir: str, - work_dir: str, - no_clean: bool = False, - runner: Runner | None = None, -) -> VSumaReprefixizeSpecOutputs: - """ - A tool for prefixing and working with SUMA specification files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_file: Input SUMA specification file. - prefix: Prefix to be added to the file names. - output_dir: Output directory where the prefixed files will be saved. - work_dir: Working directory for temporary files. - no_clean: Flag to avoid cleaning temporary files. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSumaReprefixizeSpecOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SUMA_REPREFIXIZE_SPEC_METADATA) - cargs = [] - cargs.append("@suma_reprefixize_spec") - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - cargs.extend([ - "-preprefix", - prefix - ]) - cargs.extend([ - "-odir", - output_dir - ]) - cargs.extend([ - "-workdir", - work_dir - ]) - if no_clean: - cargs.append("-no_clean") - ret = VSumaReprefixizeSpecOutputs( - root=execution.output_file("."), - prefixed_spec_files=execution.output_file(output_dir + "/*.spec"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSumaReprefixizeSpecOutputs", - "V__SUMA_REPREFIXIZE_SPEC_METADATA", - "v__suma_reprefixize_spec", -] diff --git a/python/src/niwrap/afni/v__surf_smooth_heat_07_examples.py b/python/src/niwrap/afni/v__surf_smooth_heat_07_examples.py deleted file mode 100644 index 1ab2d12e4..000000000 --- a/python/src/niwrap/afni/v__surf_smooth_heat_07_examples.py +++ /dev/null @@ -1,58 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SURF_SMOOTH_HEAT_07_EXAMPLES_METADATA = Metadata( - id="2f39cb563418dd26fe545f29aab0a8d0154170db.boutiques", - name="@SurfSmooth.HEAT_07.examples", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSurfSmoothHeat07ExamplesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__surf_smooth_heat_07_examples(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__surf_smooth_heat_07_examples( - path_to_suma_demo: str, - runner: Runner | None = None, -) -> VSurfSmoothHeat07ExamplesOutputs: - """ - A script to illustrate controlled blurring of data on the surface. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - path_to_suma_demo: Path to SUMA demo directory. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSurfSmoothHeat07ExamplesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SURF_SMOOTH_HEAT_07_EXAMPLES_METADATA) - cargs = [] - cargs.append("@SurfSmooth.HEAT_07.examples") - cargs.append(path_to_suma_demo) - ret = VSurfSmoothHeat07ExamplesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSurfSmoothHeat07ExamplesOutputs", - "V__SURF_SMOOTH_HEAT_07_EXAMPLES_METADATA", - "v__surf_smooth_heat_07_examples", -] diff --git a/python/src/niwrap/afni/v__surf_to_vol_spackle.py b/python/src/niwrap/afni/v__surf_to_vol_spackle.py deleted file mode 100644 index 68ff2ce20..000000000 --- a/python/src/niwrap/afni/v__surf_to_vol_spackle.py +++ /dev/null @@ -1,130 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__SURF_TO_VOL_SPACKLE_METADATA = Metadata( - id="011021ae78f812031308eb2fb155f5817de8a3a0.boutiques", - name="@surf_to_vol_spackle", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VSurfToVolSpackleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__surf_to_vol_spackle(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_volume: OutputPathType - """The primary output volume file with surface measures projected.""" - - -def v__surf_to_vol_spackle( - maskset: InputPathType, - spec: InputPathType, - surf_a: str, - surfset: InputPathType, - prefix: str, - surf_b: str | None = None, - normal_vector_length: float | None = None, - search_radius: float | None = None, - num_steps: float | None = None, - keep_temp_files: bool = False, - max_iters: float | None = None, - use_mode: bool = False, - datum_type: str | None = None, - ignore_unknown_options: bool = False, - runner: Runner | None = None, -) -> VSurfToVolSpackleOutputs: - """ - Project data from a surface dataset into a volume primarily using 3dSurf2Vol but - then filling any holes with an iterative smoothing procedure. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - maskset: Mask dataset in which to project surface measures. - spec: Surface specification file with list of surfaces. - surf_a: Name of the first surface, e.g., smoothwm, pial, etc. - surfset: Dataset of surface measures. - prefix: Basename of output. Final name used is prefix.nii.gz. - surf_b: Name of the second surface. If not included, computes using\ - normal vector. - normal_vector_length: Normal vector length if only using a single\ - surface (default 2 mm). - search_radius: Radius for search for mean to fill holes (default 2 mm). - num_steps: Number of steps on line segments (default 10). - keep_temp_files: Do not remove any of the temporary files (default is\ - to remove them). - max_iters: Maximum number of smoothing and filling iterations (default\ - is 4). - use_mode: Use mode instead of non-zero median (appropriate for ROIs). - datum_type: Set datum type to byte, short, or float instead of maskset\ - type. Mode triggers -datum short. - ignore_unknown_options: Ignore additional options that are not needed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VSurfToVolSpackleOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__SURF_TO_VOL_SPACKLE_METADATA) - cargs = [] - cargs.append("@surf_to_vol_spackle") - cargs.append(execution.input_file(maskset)) - cargs.append(execution.input_file(spec)) - cargs.append(surf_a) - if surf_b is not None: - cargs.append(surf_b) - cargs.append(execution.input_file(surfset)) - cargs.append(prefix) - if normal_vector_length is not None: - cargs.extend([ - "-f_pn_mm", - str(normal_vector_length) - ]) - if search_radius is not None: - cargs.extend([ - "-meanrad", - str(search_radius) - ]) - if num_steps is not None: - cargs.extend([ - "-nsteps", - str(num_steps) - ]) - if keep_temp_files: - cargs.append("-keep_temp_files") - if max_iters is not None: - cargs.extend([ - "-maxiters", - str(max_iters) - ]) - if use_mode: - cargs.append("-mode") - if datum_type is not None: - cargs.extend([ - "-datum", - datum_type - ]) - if ignore_unknown_options: - cargs.append("-ignore_unknown_options") - ret = VSurfToVolSpackleOutputs( - root=execution.output_file("."), - output_volume=execution.output_file(prefix + ".nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VSurfToVolSpackleOutputs", - "V__SURF_TO_VOL_SPACKLE_METADATA", - "v__surf_to_vol_spackle", -] diff --git a/python/src/niwrap/afni/v__t1scale.py b/python/src/niwrap/afni/v__t1scale.py deleted file mode 100644 index 903ee7cf4..000000000 --- a/python/src/niwrap/afni/v__t1scale.py +++ /dev/null @@ -1,139 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__T1SCALE_METADATA = Metadata( - id="da9880f00af155a9d926ce79b579ac25dd00b38c.boutiques", - name="@T1scale", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VT1scaleOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__t1scale(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - uniformized_t1_output: OutputPathType - """Uniformized T1 volume output file""" - masked_uniformized_t1_output: OutputPathType - """Masked Uniformized T1 volume output file""" - aligned_pd_output: OutputPathType - """Aligned PD volume output file in alignment with T1+orig""" - - -def v__t1scale( - t1_volume: InputPathType, - pd_volume: InputPathType | None = None, - output_directory: str | None = None, - align: bool = False, - mask: InputPathType | None = None, - head_mask: bool = False, - unmasked_uni: bool = False, - masked_uni: bool = False, - echo: bool = False, - help_: bool = False, - h_web: bool = False, - h_view: bool = False, - all_opts: bool = False, - h_find_word: str | None = None, - runner: Runner | None = None, -) -> VT1scaleOutputs: - """ - Fix bias field shading in T1 by scaling it with PD image. You can also get a - decent result even without the PD volume. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - t1_volume: The T1 volume. - pd_volume: The PD volume (aligned to T1). - output_directory: Directory where output gets dumped. Default is\ - T1scale/. - align: Align PD volume to T1. Without this option, PDvol is assumed in\ - alignment with T1vol. - mask: Create mask for the output. If not specified, the script will\ - generate one with 3dAutomask on fattened PDvol. - head_mask: Create mask using 3dSkullStrip's -head option. - unmasked_uni: Do not apply masking to uniformized volume (default). - masked_uni: Apply masking to uniformized volume. - echo: Set echo. - help_: Display this help message and exit. - h_web: Open webpage with help for this program. - h_view: Open -help output in a GUI editor. - all_opts: List all of the options for this script. - h_find_word: Search for lines containing WORD in -help output. Search\ - is approximate. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VT1scaleOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__T1SCALE_METADATA) - cargs = [] - cargs.append("@T1scale") - cargs.extend([ - "-T1", - execution.input_file(t1_volume) - ]) - if pd_volume is not None: - cargs.extend([ - "-PD", - execution.input_file(pd_volume) - ]) - if output_directory is not None: - cargs.extend([ - "-odir", - output_directory - ]) - if align: - cargs.append("-align") - if mask is not None: - cargs.extend([ - "-mask", - execution.input_file(mask) - ]) - if head_mask: - cargs.append("-head_mask") - if unmasked_uni: - cargs.append("-unmasked_uni") - if masked_uni: - cargs.append("-masked_uni") - if echo: - cargs.append("-echo") - if help_: - cargs.append("-help") - if h_web: - cargs.append("-h_web") - if h_view: - cargs.append("-hview") - if all_opts: - cargs.append("-all_opts") - if h_find_word is not None: - cargs.extend([ - "-h_find", - h_find_word - ]) - ret = VT1scaleOutputs( - root=execution.output_file("."), - uniformized_t1_output=execution.output_file("T1.uni+orig"), - masked_uniformized_t1_output=execution.output_file("T1_uni_masked+orig"), - aligned_pd_output=execution.output_file("PD+orig"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VT1scaleOutputs", - "V__T1SCALE_METADATA", - "v__t1scale", -] diff --git a/python/src/niwrap/afni/v__thickness_master.py b/python/src/niwrap/afni/v__thickness_master.py deleted file mode 100644 index 29a2bf1bb..000000000 --- a/python/src/niwrap/afni/v__thickness_master.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__THICKNESS_MASTER_METADATA = Metadata( - id="ba36d5a86743210981b04629a836f5e001bb1b00.boutiques", - name="@thickness_master", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VThicknessMasterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__thickness_master(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_bb_dir: OutputPathType | None - """Output directory for ball and box method""" - output_erode_dir: OutputPathType | None - """Output directory for erosion method""" - output_in2out_dir: OutputPathType | None - """Output directory for in2out method""" - - -def v__thickness_master( - maskset: InputPathType, - surfset: InputPathType, - outdir: str | None = None, - runner: Runner | None = None, -) -> VThicknessMasterOutputs: - """ - Compute cortical thickness using mask and surface datasets. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - maskset: Mask dataset to find thickness. - surfset: Surface dataset to use for normals into the volume. - outdir: Output directory base name. The output will be placed in a\ - directory with thick_base in its name (e.g., mmmm_bb, mmmm_erode,\ - mmmm_in2out). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VThicknessMasterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__THICKNESS_MASTER_METADATA) - cargs = [] - cargs.append("@thickness_master") - cargs.append("-maskset") - cargs.append(execution.input_file(maskset)) - cargs.append("-surfset") - cargs.append(execution.input_file(surfset)) - cargs.append("-outdir") - if outdir is not None: - cargs.append(outdir) - ret = VThicknessMasterOutputs( - root=execution.output_file("."), - output_bb_dir=execution.output_file(outdir + "_bb/") if (outdir is not None) else None, - output_erode_dir=execution.output_file(outdir + "_erode/") if (outdir is not None) else None, - output_in2out_dir=execution.output_file(outdir + "_in2out/") if (outdir is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VThicknessMasterOutputs", - "V__THICKNESS_MASTER_METADATA", - "v__thickness_master", -] diff --git a/python/src/niwrap/afni/v__time_diff.py b/python/src/niwrap/afni/v__time_diff.py deleted file mode 100644 index bc431fee6..000000000 --- a/python/src/niwrap/afni/v__time_diff.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__TIME_DIFF_METADATA = Metadata( - id="7889ba0aeecc01a9a55b923b84e149e7cec9417e.boutiques", - name="@TimeDiff", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VTimeDiffOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__time_diff(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__time_diff( - file1: InputPathType, - file2: InputPathType, - runner: Runner | None = None, -) -> VTimeDiffOutputs: - """ - A tool to compare the modification times of two files. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - file1: First file to compare (e.g., file1.txt). - file2: Second file to compare (e.g., file2.txt). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VTimeDiffOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__TIME_DIFF_METADATA) - cargs = [] - cargs.append("@TimeDiff") - cargs.append(execution.input_file(file1)) - cargs.append(execution.input_file(file2)) - ret = VTimeDiffOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VTimeDiffOutputs", - "V__TIME_DIFF_METADATA", - "v__time_diff", -] diff --git a/python/src/niwrap/afni/v__to_mni_awarp.py b/python/src/niwrap/afni/v__to_mni_awarp.py deleted file mode 100644 index 9e7d29ba0..000000000 --- a/python/src/niwrap/afni/v__to_mni_awarp.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__TO_MNI_AWARP_METADATA = Metadata( - id="93b77f09cd479bf6a950c0693a066eccc0f62501.boutiques", - name="@toMNI_Awarp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VToMniAwarpOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__to_mni_awarp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_datasets: OutputPathType - """The transformed datasets in 1x1x1 mm MNI space.""" - - -def v__to_mni_awarp( - directory: str, - datasets: list[InputPathType], - runner: Runner | None = None, -) -> VToMniAwarpOutputs: - """ - Transforms skull-stripped datasets to 1x1x1 mm MNI space using an affine - transformation. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - directory: Name of the directory to be created where results will be\ - stored. - datasets: List of datasets to be transformed. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VToMniAwarpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__TO_MNI_AWARP_METADATA) - cargs = [] - cargs.append("@toMNI_Awarp") - cargs.append(directory) - cargs.extend([execution.input_file(f) for f in datasets]) - ret = VToMniAwarpOutputs( - root=execution.output_file("."), - output_datasets=execution.output_file(directory + "/*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VToMniAwarpOutputs", - "V__TO_MNI_AWARP_METADATA", - "v__to_mni_awarp", -] diff --git a/python/src/niwrap/afni/v__to_mni_qwarpar.py b/python/src/niwrap/afni/v__to_mni_qwarpar.py deleted file mode 100644 index e45ce0f7f..000000000 --- a/python/src/niwrap/afni/v__to_mni_qwarpar.py +++ /dev/null @@ -1,59 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__TO_MNI_QWARPAR_METADATA = Metadata( - id="04e45eb40a57d1fc1e8c94957315562ee18d3086.boutiques", - name="@toMNI_Qwarpar", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VToMniQwarparOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__to_mni_qwarpar(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType - """Output dataset created after processing.""" - - -def v__to_mni_qwarpar( - runner: Runner | None = None, -) -> VToMniQwarparOutputs: - """ - Transforms datasets to MNI space, then collectively re-transforms them to - produce a refined average. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VToMniQwarparOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__TO_MNI_QWARPAR_METADATA) - cargs = [] - cargs.append("@toMNI_Qwarpar") - ret = VToMniQwarparOutputs( - root=execution.output_file("."), - output_file=execution.output_file("*_uni+tlrc.HEAD"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VToMniQwarparOutputs", - "V__TO_MNI_QWARPAR_METADATA", - "v__to_mni_qwarpar", -] diff --git a/python/src/niwrap/afni/v__to_rai.py b/python/src/niwrap/afni/v__to_rai.py deleted file mode 100644 index 98ca01cc9..000000000 --- a/python/src/niwrap/afni/v__to_rai.py +++ /dev/null @@ -1,61 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__TO_RAI_METADATA = Metadata( - id="1a5cc8a5a702a9f62a7296e2f91329b3a241311d.boutiques", - name="@ToRAI", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VToRaiOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__to_rai(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__to_rai( - runner: Runner | None = None, -) -> VToRaiOutputs: - """ - Tool to change the ORIENT coordinates to RAI. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VToRaiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__TO_RAI_METADATA) - cargs = [] - cargs.append("@ToRAI") - cargs.append("<-xyz") - cargs.append("X") - cargs.append("Y") - cargs.append("Z>") - cargs.append("<-or") - cargs.append("ORIENT>") - ret = VToRaiOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VToRaiOutputs", - "V__TO_RAI_METADATA", - "v__to_rai", -] diff --git a/python/src/niwrap/afni/v__update_afni_binaries.py b/python/src/niwrap/afni/v__update_afni_binaries.py deleted file mode 100644 index b5a422af3..000000000 --- a/python/src/niwrap/afni/v__update_afni_binaries.py +++ /dev/null @@ -1,173 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__UPDATE_AFNI_BINARIES_METADATA = Metadata( - id="893694dbbccc046a97eb3b039a42a123a05bfc8f.boutiques", - name="@update.afni.binaries", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VUpdateAfniBinariesOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__update_afni_binaries(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__update_afni_binaries( - defaults_flag: bool = False, - help_flag: bool = False, - help_sys_progs_flag: bool = False, - apsearch: str | None = None, - bindir: str | None = None, - curl_flag: bool = False, - do_dotfiles_flag: bool = False, - do_extras_flag: bool = False, - echo_flag: bool = False, - make_backup: str | None = None, - no_cert_verify_flag: bool = False, - no_recur_flag: bool = False, - proto: str | None = None, - quick_flag: bool = False, - show_obsoletes_flag: bool = False, - show_obsoletes_grep_flag: bool = False, - show_system_progs_flag: bool = False, - sys_ok_flag: bool = False, - test_flag: bool = False, - test_protos_flag: bool = False, - revert_flag: bool = False, - local_package: str | None = None, - prog_list: list[str] | None = None, - package: str | None = None, - runner: Runner | None = None, -) -> VUpdateAfniBinariesOutputs: - """ - Install or update AFNI binaries. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - defaults_flag: Install current package into abin. - help_flag: Show this help. - help_sys_progs_flag: List system programs that block update. - apsearch: Specify getting apsearch updates. - bindir: Set AFNI binary directory to ABIN. - curl_flag: Default to curl instead of wget. - do_dotfiles_flag: Try to initialize dot files if needed. - do_extras_flag: Do extra niceties (beyond simple install). - echo_flag: Turn on shell command echo. - make_backup: Make a backup of binaries before replacing. - no_cert_verify_flag: Do not verify the server CA certificate. - no_recur_flag: Do not download and run new @uab script. - proto: Access afni host via specified PROTOCOL. - quick_flag: Quick mode, no fancies. - show_obsoletes_flag: List any obsolete packages. - show_obsoletes_grep_flag: List any obsolete packages (easy to grep). - show_system_progs_flag: Show system programs that do not belong in\ - abin. - sys_ok_flag: OK to update, even if system progs found. - test_flag: Just attempt the download and quit. - test_protos_flag: Test download protocols and exit. - revert_flag: Revert binaries to previous version. - local_package: Install local PACKAGE.tgz package. - prog_list: Install given programs, not whole PACKAGE. - package: Install distribution package PACKAGE. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VUpdateAfniBinariesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__UPDATE_AFNI_BINARIES_METADATA) - cargs = [] - cargs.append("@update.afni.binaries") - if defaults_flag: - cargs.append("-defaults") - if help_flag: - cargs.append("-help") - if help_sys_progs_flag: - cargs.append("-help_sys_progs") - if apsearch is not None: - cargs.extend([ - "-apsearch", - apsearch - ]) - if bindir is not None: - cargs.extend([ - "-bindir", - bindir - ]) - if curl_flag: - cargs.append("-curl") - if do_dotfiles_flag: - cargs.append("-do_dotfiles") - if do_extras_flag: - cargs.append("-do_extras") - if echo_flag: - cargs.append("-echo") - if make_backup is not None: - cargs.extend([ - "-make_backup", - make_backup - ]) - if no_cert_verify_flag: - cargs.append("-no_cert_verify") - if no_recur_flag: - cargs.append("-no_recur") - if proto is not None: - cargs.extend([ - "-proto", - proto - ]) - if quick_flag: - cargs.append("-quick") - if show_obsoletes_flag: - cargs.append("-show_obsoletes") - if show_obsoletes_grep_flag: - cargs.append("-show_obsoletes_grep") - if show_system_progs_flag: - cargs.append("-show_system_progs") - if sys_ok_flag: - cargs.append("-sys_ok") - if test_flag: - cargs.append("-test") - if test_protos_flag: - cargs.append("-test_protos") - if revert_flag: - cargs.append("-revert") - if local_package is not None: - cargs.extend([ - "-local_package", - local_package - ]) - if prog_list is not None: - cargs.extend([ - "-prog_list", - *prog_list - ]) - if package is not None: - cargs.extend([ - "-package", - package - ]) - ret = VUpdateAfniBinariesOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VUpdateAfniBinariesOutputs", - "V__UPDATE_AFNI_BINARIES_METADATA", - "v__update_afni_binaries", -] diff --git a/python/src/niwrap/afni/v__vol_center.py b/python/src/niwrap/afni/v__vol_center.py deleted file mode 100644 index 8e031e9ff..000000000 --- a/python/src/niwrap/afni/v__vol_center.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__VOL_CENTER_METADATA = Metadata( - id="4ce13662130110b3fd50b4a405a5d296faf47380.boutiques", - name="@VolCenter", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VVolCenterOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__vol_center(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def v__vol_center( - dset: InputPathType, - orient: str | None = None, - runner: Runner | None = None, -) -> VVolCenterOutputs: - """ - Tool to return the center of volume for a given dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - dset: Input volume dataset. - orient: Output coordinate system orientation (e.g., RAI). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VVolCenterOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__VOL_CENTER_METADATA) - cargs = [] - cargs.append("@VolCenter") - cargs.extend([ - "-dset", - execution.input_file(dset) - ]) - if orient is not None: - cargs.extend([ - "-or", - orient - ]) - ret = VVolCenterOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VVolCenterOutputs", - "V__VOL_CENTER_METADATA", - "v__vol_center", -] diff --git a/python/src/niwrap/afni/v__xyz_to_ijk.py b/python/src/niwrap/afni/v__xyz_to_ijk.py deleted file mode 100644 index a313343ce..000000000 --- a/python/src/niwrap/afni/v__xyz_to_ijk.py +++ /dev/null @@ -1,80 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -V__XYZ_TO_IJK_METADATA = Metadata( - id="19759dbb81f9560426ecb6ea27ee2b763e341085.boutiques", - name="@xyz_to_ijk", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VXyzToIjkOutputs(typing.NamedTuple): - """ - Output object returned when calling `v__xyz_to_ijk(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """Output file containing the translated indices""" - - -def v__xyz_to_ijk( - inset: InputPathType, - x_coord: float, - y_coord: float, - z_coord: float, - prefix: str | None = None, - runner: Runner | None = None, -) -> VXyzToIjkOutputs: - """ - Helper script to convert (x, y, z) coordinates to (i, j, k) indices for a - volumetric dataset. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - inset: Volumetric file name (e.g. FILE.nii.gz). - x_coord: Three coordinates (in units of the dataset, like mm). - y_coord: Three coordinates (in units of the dataset, like mm). - z_coord: Three coordinates (in units of the dataset, like mm). - prefix: File name (including path) to output the three indices. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VXyzToIjkOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(V__XYZ_TO_IJK_METADATA) - cargs = [] - cargs.append("@xyz_to_ijk") - cargs.append("-inset") - cargs.append(execution.input_file(inset)) - cargs.append("-xyz") - cargs.append(str(x_coord)) - cargs.append(str(y_coord)) - cargs.append(str(z_coord)) - if prefix is not None: - cargs.extend([ - "-prefix", - prefix - ]) - ret = VXyzToIjkOutputs( - root=execution.output_file("."), - output_file=execution.output_file(prefix) if (prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VXyzToIjkOutputs", - "V__XYZ_TO_IJK_METADATA", - "v__xyz_to_ijk", -] diff --git a/python/src/niwrap/afni/vecwarp.py b/python/src/niwrap/afni/vecwarp.py deleted file mode 100644 index fa294246c..000000000 --- a/python/src/niwrap/afni/vecwarp.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -VECWARP_METADATA = Metadata( - id="66d797ff1f24b0ac64a1a1ccdd71bdfbf2d06237.boutiques", - name="Vecwarp", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class VecwarpOutputs(typing.NamedTuple): - """ - Output object returned when calling `vecwarp(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_file: OutputPathType | None - """The output file containing the transformed 3-vectors.""" - - -def vecwarp( - input_: InputPathType | None = None, - output: str | None = None, - force: bool = False, - runner: Runner | None = None, -) -> VecwarpOutputs: - """ - Transforms (warps) a list of 3-vectors into another list of 3-vectors according - to the specified options. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - input_: Read input 3-vectors from the file 'iii' (from stdin if 'iii'\ - is '-' or the -input option is missing). - output: Write the output to file 'ooo' (to stdout if 'ooo' is '-', or\ - if the -output option is missing). - force: If the output file already exists, use -force to overwrite it.\ - If -force is used, it must come before -output on the command line. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `VecwarpOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(VECWARP_METADATA) - cargs = [] - cargs.append("Vecwarp") - cargs.append("[APAR") - cargs.append("|") - cargs.append("MATVEC]") - cargs.append("[FORWARD_FLAG") - cargs.append("|") - cargs.append("BACKWARD_FLAG]") - if input_ is not None: - cargs.extend([ - "-input", - execution.input_file(input_) - ]) - if output is not None: - cargs.extend([ - "-output", - output - ]) - if force: - cargs.append("-force") - ret = VecwarpOutputs( - root=execution.output_file("."), - output_file=execution.output_file(output) if (output is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "VECWARP_METADATA", - "VecwarpOutputs", - "vecwarp", -] diff --git a/python/src/niwrap/afni/waver.py b/python/src/niwrap/afni/waver.py deleted file mode 100644 index 672270a22..000000000 --- a/python/src/niwrap/afni/waver.py +++ /dev/null @@ -1,210 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -WAVER_METADATA = Metadata( - id="853f5c7b1276e654db54518623370e48705e17ef.boutiques", - name="waver", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class WaverOutputs(typing.NamedTuple): - """ - Output object returned when calling `waver(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_filename: OutputPathType - """The output filename for the result of the waveform.""" - - -def waver( - wav: bool = False, - gam: bool = False, - expr: str | None = None, - file_opt: str | None = None, - delay_time: float | None = None, - rise_time: float | None = None, - fall_time: float | None = None, - undershoot: float | None = None, - restore_time: float | None = None, - gamb: float | None = None, - gamc: float | None = None, - gamd: float | None = None, - peak: float | None = None, - dt: float | None = None, - tr: float | None = None, - xyout: bool = False, - input_file: InputPathType | None = None, - inline_data: str | None = None, - tstim_data: str | None = None, - when_data: str | None = None, - numout: int | None = None, - ver_flag: bool = False, - runner: Runner | None = None, -) -> WaverOutputs: - """ - Creates an ideal waveform timeseries file. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - wav: Sets waveform to Cox special [default]. - gam: Sets waveform to form t^b * exp(-t/c) (cf. Mark Cohen). - expr: Sets waveform to the expression given, which should depend on the\ - variable 't'. - file_opt: Sets waveform to the values read from the file wname, which\ - should be a single column .1D file. The dt value is the time step (in\ - seconds) between lines in wname. - delay_time: Sets delay time to # seconds [2]. - rise_time: Sets rise time to # seconds [4]. - fall_time: Sets fall time to # seconds [6]. - undershoot: Sets undershoot to # times the peak [0.2]. - restore_time: Sets time to restore from undershoot [2]. - gamb: Sets the parameter 'b' to # [8.6]. - gamc: Sets the parameter 'c' to # [0.547]. - gamd: Sets the delay time to # seconds [0.0]. - peak: Sets peak value to # [100]. - dt: Sets time step of output AND input [0.1]. - tr: '-TR' is equivalent to '-dt'. - xyout: Output data in 2 columns: 1=time 2=waveform (useful for\ - graphing) [default is 1 column=waveform]. - input_file: Read timeseries from *.1D formatted 'infile'; convolve with\ - waveform to produce output. - inline_data: Read timeseries from command line DATA; convolve with\ - waveform to produce output. - tstim_data: Read discrete stimulation times from the command line and\ - convolve the waveform with delta-functions at those times. - when_data: Read time blocks when stimulus is 'on' (=1) from the command\ - line and convolve the waveform with with a zero-one input. - numout: Output a timeseries with NN points; if this option is not\ - given, then enough points are output to let the result tail back down\ - to zero. - ver_flag: Output version information and exit. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `WaverOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(WAVER_METADATA) - cargs = [] - cargs.append("waver") - if wav: - cargs.append("-WAV") - if gam: - cargs.append("-GAM") - if expr is not None: - cargs.extend([ - "-EXPR", - expr - ]) - if file_opt is not None: - cargs.extend([ - "-FILE", - file_opt - ]) - if delay_time is not None: - cargs.extend([ - "-delaytime", - str(delay_time) - ]) - if rise_time is not None: - cargs.extend([ - "-risetime", - str(rise_time) - ]) - if fall_time is not None: - cargs.extend([ - "-falltime", - str(fall_time) - ]) - if undershoot is not None: - cargs.extend([ - "-undershoot", - str(undershoot) - ]) - if restore_time is not None: - cargs.extend([ - "-restoretime", - str(restore_time) - ]) - if gamb is not None: - cargs.extend([ - "-gamb", - str(gamb) - ]) - if gamc is not None: - cargs.extend([ - "-gamc", - str(gamc) - ]) - if gamd is not None: - cargs.extend([ - "-gamd", - str(gamd) - ]) - if peak is not None: - cargs.extend([ - "-peak", - str(peak) - ]) - if dt is not None: - cargs.extend([ - "-dt", - str(dt) - ]) - if tr is not None: - cargs.extend([ - "-TR", - str(tr) - ]) - if xyout: - cargs.append("-xyout") - if input_file is not None: - cargs.extend([ - "-input", - execution.input_file(input_file) - ]) - if inline_data is not None: - cargs.extend([ - "-inline", - inline_data - ]) - if tstim_data is not None: - cargs.extend([ - "-tstim", - tstim_data - ]) - if when_data is not None: - cargs.extend([ - "-when", - when_data - ]) - if numout is not None: - cargs.extend([ - "-numout", - str(numout) - ]) - if ver_flag: - cargs.append("-ver") - ret = WaverOutputs( - root=execution.output_file("."), - output_filename=execution.output_file("output_filename"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "WAVER_METADATA", - "WaverOutputs", - "waver", -] diff --git a/python/src/niwrap/afni/whirlgif.py b/python/src/niwrap/afni/whirlgif.py deleted file mode 100644 index 793f7b6e5..000000000 --- a/python/src/niwrap/afni/whirlgif.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -WHIRLGIF_METADATA = Metadata( - id="36f99e4c603427a41d99dee32a8bfe60a5827d92.boutiques", - name="whirlgif", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class WhirlgifOutputs(typing.NamedTuple): - """ - Output object returned when calling `whirlgif(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_gif: OutputPathType | None - """The output GIF file""" - - -def whirlgif( - gif_files: list[InputPathType], - verbose: bool = False, - loop: str | None = None, - transparency_index: float | None = None, - inter_frame_delay: float | None = None, - outfile: str | None = None, - infile: InputPathType | None = None, - runner: Runner | None = None, -) -> WhirlgifOutputs: - """ - A quick program that reads a series of GIF files and produces a single GIF file - composed of those images. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - gif_files: Input GIF files to be combined into a single GIF file. - verbose: Verbose mode. - loop: Add the Netscape 'loop' extension. Optionally specify a loop\ - count. - transparency_index: Set the colormap index 'index' to be transparent. - inter_frame_delay: Inter-frame timing delay. - outfile: Specify the output file to write the results to. - infile: Read a list of filenames from a file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `WhirlgifOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(WHIRLGIF_METADATA) - cargs = [] - cargs.append("whirlgif") - if verbose: - cargs.append("-v") - if loop is not None: - cargs.extend([ - "-loop", - loop - ]) - if transparency_index is not None: - cargs.extend([ - "-trans", - str(transparency_index) - ]) - if inter_frame_delay is not None: - cargs.extend([ - "-time", - str(inter_frame_delay) - ]) - if outfile is not None: - cargs.extend([ - "-o", - outfile - ]) - if infile is not None: - cargs.extend([ - "-i", - execution.input_file(infile) - ]) - cargs.extend([execution.input_file(f) for f in gif_files]) - ret = WhirlgifOutputs( - root=execution.output_file("."), - output_gif=execution.output_file(outfile) if (outfile is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "WHIRLGIF_METADATA", - "WhirlgifOutputs", - "whirlgif", -] diff --git a/python/src/niwrap/afni/xmat_tool_py.py b/python/src/niwrap/afni/xmat_tool_py.py deleted file mode 100644 index 0815a84a4..000000000 --- a/python/src/niwrap/afni/xmat_tool_py.py +++ /dev/null @@ -1,160 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -XMAT_TOOL_PY_METADATA = Metadata( - id="3a6bcb8aee2e7ab05a9a212e21f7dfef419b3b43.boutiques", - name="xmat_tool.py", - package="afni", - container_image_tag="afni/afni_make_build:AFNI_24.2.06", -) - - -class XmatToolPyOutputs(typing.NamedTuple): - """ - Output object returned when calling `xmat_tool_py(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_fitts: OutputPathType - """Output fit time series""" - - -def xmat_tool_py( - no_gui: bool = False, - load_xmat: InputPathType | None = None, - load_1d: InputPathType | None = None, - choose_cols: str | None = None, - choose_nonzero_cols: bool = False, - chrono: bool = False, - cormat_cutoff: float | None = None, - cosmat_cutoff: float | None = None, - cosmat_motion: bool = False, - verb: float | None = None, - show_col_types: bool = False, - show_conds: bool = False, - show_cormat: bool = False, - show_cormat_warnings: bool = False, - show_cosmat: bool = False, - show_cosmat_warnings: bool = False, - show_fit_betas: bool = False, - show_fit_ts: bool = False, - show_xmat: bool = False, - show_1d: bool = False, - gui_plot_xmat_as_one: bool = False, - runner: Runner | None = None, -) -> XmatToolPyOutputs: - """ - A tool for evaluating an AFNI X-matrix. - - Author: AFNI Developers - - URL: https://afni.nimh.nih.gov/ - - Args: - no_gui: Do not start the GUI. - load_xmat: Load the AFNI X-matrix. - load_1d: Load the 1D time series. - choose_cols: Select columns to fit against. - choose_nonzero_cols: Select only non-zero columns. - chrono: Apply options chronologically. - cormat_cutoff: Set min cutoff for correlation matrix warnings. - cosmat_cutoff: Set min cutoff for cosine matrix warnings. - cosmat_motion: Include motion in cosine matrix warnings. - verb: Set the verbose level. Valid levels are currently 0..5. - show_col_types: Display columns by regressor types. - show_conds: Display a list of condition numbers. - show_cormat: Display the correlation matrix. - show_cormat_warnings: Show correlation matrix warnings. - show_cosmat: Display the cosine matrix. - show_cosmat_warnings: Show cosine matrix warnings. - show_fit_betas: Show fit betas. - show_fit_ts: Show fit time series. - show_xmat: Display general X-matrix information. - show_1d: Display general 1D information. - gui_plot_xmat_as_one: Plot Xmat columns on single axis. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `XmatToolPyOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(XMAT_TOOL_PY_METADATA) - cargs = [] - cargs.append("xmat_tool.py") - if no_gui: - cargs.append("-no_gui") - if load_xmat is not None: - cargs.extend([ - "-load_xmat", - execution.input_file(load_xmat) - ]) - if load_1d is not None: - cargs.extend([ - "-load_1D", - execution.input_file(load_1d) - ]) - if choose_cols is not None: - cargs.extend([ - "-choose_cols", - choose_cols - ]) - if choose_nonzero_cols: - cargs.append("-choose_nonzero_cols") - if chrono: - cargs.append("-chrono") - if cormat_cutoff is not None: - cargs.extend([ - "-cormat_cutoff", - str(cormat_cutoff) - ]) - if cosmat_cutoff is not None: - cargs.extend([ - "-cosmat_cutoff", - str(cosmat_cutoff) - ]) - if cosmat_motion: - cargs.append("-cosmat_motion") - if verb is not None: - cargs.extend([ - "-verb", - str(verb) - ]) - if show_col_types: - cargs.append("-show_col_types") - if show_conds: - cargs.append("-show_conds") - if show_cormat: - cargs.append("-show_cormat") - if show_cormat_warnings: - cargs.append("-show_cormat_warnings") - if show_cosmat: - cargs.append("-show_cosmat") - if show_cosmat_warnings: - cargs.append("-show_cosmat_warnings") - if show_fit_betas: - cargs.append("-show_fit_betas") - if show_fit_ts: - cargs.append("-show_fit_ts") - if show_xmat: - cargs.append("-show_xmat") - if show_1d: - cargs.append("-show_1D") - if gui_plot_xmat_as_one: - cargs.append("-gui_plot_xmat_as_one") - ret = XmatToolPyOutputs( - root=execution.output_file("."), - output_fitts=execution.output_file("fitts.1D"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "XMAT_TOOL_PY_METADATA", - "XmatToolPyOutputs", - "xmat_tool_py", -] diff --git a/python/src/niwrap/ants/__init__.py b/python/src/niwrap/ants/__init__.py deleted file mode 100644 index f1bb89ca8..000000000 --- a/python/src/niwrap/ants/__init__.py +++ /dev/null @@ -1,92 +0,0 @@ -""" -ANTs - -Advanced Normalization Tools (ANTs) is a C++ library available through the -command line that computes high-dimensional mappings to capture the statistics -of brain structure and function. It allows one to organize, visualize and -statistically explore large biomedical image sets. Additionally, it integrates -imaging modalities in space + time and works across species or organ systems -with minimal customization. - -The ANTs library is considered a state-of-the-art medical image registration and -segmentation toolkit which depends on the Insight ToolKit, a widely used medical -image processing library to which ANTs developers contribute. ANTs-related tools -have also won several international, unbiased competitions such as MICCAI, -BRATS, and STACOM. - -URL: https://github.com/ANTsX/ANTs -""" -# This file was auto generated by Styx. -# Do not edit this file directly. - -from .add_noise_to_image import * -from .ants_ai import * -from .ants_align_origin import * -from .ants_apply_transforms import * -from .ants_apply_transforms_to_points import * -from .ants_atropos_n4_sh import * -from .ants_brain_extraction_sh import * -from .ants_cortical_thickness_sh import * -from .ants_intermodality_intrasubject_sh import * -from .ants_introduction_sh import * -from .ants_joint_fusion import * -from .ants_joint_label_fusion_sh import * -from .ants_joint_tensor_fusion import * -from .ants_landmark_based_transform_initializer import * -from .ants_motion_corr import * -from .ants_motion_corr_diffusion_direction import * -from .ants_motion_corr_stats import * -from .ants_multivariate_template_construction2_sh import * -from .ants_neuroimaging_battery import * -from .ants_registration import * -from .ants_registration_sy_n_sh import * -from .ants_registration_sy_nquick_sh import * -from .ants_slice_regularized_registration import * -from .ants_transform_info import * -from .antsintegrate_vector_field import * -from .antsjacobian import * -from .antsuse_deformation_field_to_get_affine_transform import * -from .antsuse_landmark_images_to_get_affine_transform import * -from .antsuse_landmark_images_to_get_bspline_displacement_field import * -from .atropos import * -from .convert_scalar_image_to_rgb import * -from .convert_to_jpg import * -from .convert_transform_file import * -from .create_displacement_field import * -from .create_dticohort import * -from .create_tiled_mosaic import * -from .create_warped_grid_image import * -from .denoise_image import * -from .extract_region_from_image import * -from .extract_region_from_image_by_mask import * -from .i_math import * -from .image_intensity_statistics import * -from .image_math import * -from .image_set_statistics import * -from .kelly_kapowski import * -from .label_geometry_measures import * -from .lesion_filling import * -from .multiply_images import * -from .n3_bias_field_correction import * -from .n4_bias_field_correction import * -from .non_local_super_resolution import * -from .paste_image_into_image import * -from .print_header import * -from .rebase_tensor_image import * -from .resample_image import * -from .sccan import * -from .set_spacing import * -from .simple_syn_registration import * -from .simulate_displacement_field import * -from .smooth_displacement_field import * -from .smooth_image import * -from .super_resolution import * -from .surface_based_smoothing import * -from .surface_curvature import * -from .texture_cooccurrence_features import * -from .texture_run_length_features import * -from .threshold_image import * -from .tile_images import * -from .time_sccan import * -from .warp_tensor_image_multi_transform import * -from .warp_time_series_image_multi_transform import * diff --git a/python/src/niwrap/ants/add_noise_to_image.py b/python/src/niwrap/ants/add_noise_to_image.py deleted file mode 100644 index 509ab7b0c..000000000 --- a/python/src/niwrap/ants/add_noise_to_image.py +++ /dev/null @@ -1,94 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ADD_NOISE_TO_IMAGE_METADATA = Metadata( - id="e8efbf11871081a5ad3301baf672f8de93471bd0.boutiques", - name="AddNoiseToImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AddNoiseToImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `add_noise_to_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - noise_corrupted_image: OutputPathType - """The output is the noise corrupted version of the input image.""" - - -def add_noise_to_image( - input_image: InputPathType, - noise_model: typing.Literal["AdditiveGaussian", "SaltAndPepper", "Shot", "Speckle"], - output: InputPathType, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AddNoiseToImageOutputs: - """ - Add various types of noise to an image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: A scalar image is expected as input for noise correction. - noise_model: Use different noise models each with its own (default)\ - parameters. - output: The output consists of the noise corrupted version of the input\ - image. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AddNoiseToImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ADD_NOISE_TO_IMAGE_METADATA) - cargs = [] - cargs.append("AddNoiseToImage") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - cargs.extend([ - "--input-image", - execution.input_file(input_image) - ]) - cargs.extend([ - "--noise-model", - noise_model - ]) - cargs.extend([ - "--output", - execution.input_file(output) - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = AddNoiseToImageOutputs( - root=execution.output_file("."), - noise_corrupted_image=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ADD_NOISE_TO_IMAGE_METADATA", - "AddNoiseToImageOutputs", - "add_noise_to_image", -] diff --git a/python/src/niwrap/ants/ants_ai.py b/python/src/niwrap/ants/ants_ai.py deleted file mode 100644 index cdd596711..000000000 --- a/python/src/niwrap/ants/ants_ai.py +++ /dev/null @@ -1,153 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_AI_METADATA = Metadata( - id="694c77fb3122e7ae7609dc66837caa7834538472.boutiques", - name="antsAI", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsAiOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_ai(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transform: OutputPathType - """The output transform (ITK .mat file).""" - - -def ants_ai( - metric: typing.Literal["Mattes[fixedImage,movingImage]", "GC[fixedImage,movingImage]", "MI[fixedImage,movingImage]"], - transform: typing.Literal["Rigid[gradientStep]", "Affine[gradientStep]", "Similarity[gradientStep]", "AlignGeometricCenters", "AlignCentersOfMass"], - output: str, - dimensionality: typing.Literal[2, 3] | None = None, - align_principal_axes: typing.Literal[0, 1] | None = None, - align_blobs: typing.Literal["numberOfBlobsToExtract", "[numberOfBlobsToExtract,numberOfBlobsToMatch]"] | None = None, - search_factor: typing.Literal["searchFactor", "[searchFactor,arcFraction]"] | None = None, - translation_search_grid: typing.Literal["[stepSize, AxBxC]"] | None = None, - convergence: typing.Literal["numberOfIterations", "[numberOfIterations,convergenceThreshold,convergenceWindowSize]"] | None = None, - masks: typing.Literal["fixedImageMask", "[fixedImageMask,movingImageMask]"] | None = None, - random_seed: int | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsAiOutputs: - """ - Program to calculate the optimal linear transform parameters for aligning two - images. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - metric: These image metrics are available: Mattes: Mattes mutual\ - information (recommended), GC: global correlation, MI: joint histogram\ - mutual information. - transform: Several transform options are available. For the rigid,\ - affine, and similarity transforms, the gradientStep characterizes the\ - gradient descent optimization. The other two transform types finds the\ - simple translation transform which aligns the specified image feature. - output: Specify the output transform (output format an ITK .mat file). - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, we try to infer the\ - dimensionality from the input image. - align_principal_axes: Boolean indicating alignment by principal axes.\ - Alternatively, one can align using blobs. - align_blobs: Boolean indicating alignment by a set of blobs. - search_factor: Incremental search factor (in degrees) which will sample\ - the arc fraction around the principal axis or default axis. - translation_search_grid: Translation search grid in mm, which will\ - translate the moving image in each dimension in increments of the step\ - size. - convergence: Number of iterations. - masks: Image masks to limit voxels considered by the metric. - random_seed: Use a fixed seed for random number generation. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsAiOutputs`). - """ - if random_seed is not None and not (0 <= random_seed): - raise ValueError(f"'random_seed' must be greater than 0 <= x but was {random_seed}") - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_AI_METADATA) - cargs = [] - cargs.append("antsAI") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - cargs.extend([ - "-m", - metric - ]) - cargs.extend([ - "-t", - transform - ]) - if align_principal_axes is not None: - cargs.extend([ - "-p", - str(align_principal_axes) - ]) - if align_blobs is not None: - cargs.extend([ - "-b", - align_blobs - ]) - if search_factor is not None: - cargs.extend([ - "-s", - search_factor - ]) - if translation_search_grid is not None: - cargs.extend([ - "-g", - translation_search_grid - ]) - if convergence is not None: - cargs.extend([ - "-c", - convergence - ]) - if masks is not None: - cargs.extend([ - "-x", - masks - ]) - cargs.extend([ - "-o", - output - ]) - if random_seed is not None: - cargs.extend([ - "--random-seed", - str(random_seed) - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = AntsAiOutputs( - root=execution.output_file("."), - output_transform=execution.output_file(output + ".mat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_AI_METADATA", - "AntsAiOutputs", - "ants_ai", -] diff --git a/python/src/niwrap/ants/ants_align_origin.py b/python/src/niwrap/ants/ants_align_origin.py deleted file mode 100644 index d7235c4ba..000000000 --- a/python/src/niwrap/ants/ants_align_origin.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_ALIGN_ORIGIN_METADATA = Metadata( - id="6857aca2f492ef8646affc2ca57d3ca2675b0b13.boutiques", - name="antsAlignOrigin", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsAlignOriginOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_align_origin(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - aligned_image: OutputPathType - """The output is the aligned image.""" - - -def ants_align_origin( - input_: InputPathType, - reference_image: InputPathType, - output: InputPathType, - dimensionality: typing.Literal[2, 3] | None = None, - runner: Runner | None = None, -) -> AntsAlignOriginOutputs: - """ - antsAlignOrigin, applied to an input image, transforms it according to a - reference image and a transform (or a set of transforms). - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_: Currently, the only input objects supported are image objects.\ - However, the current framework allows for warping of other objects such\ - as meshes and point sets. - reference_image: For warping input images, the reference image defines\ - the spacing, origin, size, and direction of the output warped image. - output: One can either output the warped image or, if the boolean is\ - set, one can print out the displacement field based on the composite\ - transform and the reference image. - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, antsWarp tries to infer\ - the dimensionality from the input image. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsAlignOriginOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_ALIGN_ORIGIN_METADATA) - cargs = [] - cargs.append("antsAlignOrigin") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - cargs.extend([ - "--input", - execution.input_file(input_) - ]) - cargs.extend([ - "--reference-image", - execution.input_file(reference_image) - ]) - cargs.extend([ - "--output", - execution.input_file(output) - ]) - ret = AntsAlignOriginOutputs( - root=execution.output_file("."), - aligned_image=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_ALIGN_ORIGIN_METADATA", - "AntsAlignOriginOutputs", - "ants_align_origin", -] diff --git a/python/src/niwrap/ants/ants_apply_transforms.py b/python/src/niwrap/ants/ants_apply_transforms.py deleted file mode 100644 index 60ca65189..000000000 --- a/python/src/niwrap/ants/ants_apply_transforms.py +++ /dev/null @@ -1,656 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_APPLY_TRANSFORMS_METADATA = Metadata( - id="1e2c5690e55a56e5a6fd164d9abf7d68ef0554d2.boutiques", - name="antsApplyTransforms", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsApplyTransformsWarpedOutputOutputs(typing.NamedTuple): - """ - Output object returned when calling `AntsApplyTransformsWarpedOutput(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_outfile: OutputPathType - """Warped image.""" - - -@dataclasses.dataclass -class AntsApplyTransformsWarpedOutput: - """ - Output the warped image. - """ - warped_output_file_name: str - """Output file name.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(self.warped_output_file_name) - return cargs - - def outputs( - self, - execution: Execution, - ) -> AntsApplyTransformsWarpedOutputOutputs: - """ - Collect output file paths. - - Args: - execution: The execution object. - Returns: - NamedTuple of outputs (described in `AntsApplyTransformsWarpedOutputOutputs`). - """ - ret = AntsApplyTransformsWarpedOutputOutputs( - root=execution.output_file("."), - output_image_outfile=execution.output_file(self.warped_output_file_name), - ) - return ret - - -class AntsApplyTransformsCompositeDisplacementFieldOutputOutputs(typing.NamedTuple): - """ - Output object returned when calling `AntsApplyTransformsCompositeDisplacementFieldOutput(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_outfile: OutputPathType - """Warped image.""" - - -@dataclasses.dataclass -class AntsApplyTransformsCompositeDisplacementFieldOutput: - """ - Print out the displacement field based on the composite transform and the - reference image. - """ - composite_displacement_field: str - """Output file name.""" - print_out_composite_warp_file: typing.Literal[0, 1] | None = None - """Output a composite warp file instead of a transformed image.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.print_out_composite_warp_file is not None: - cargs.append("[" + self.composite_displacement_field + ",printOutCompositeWarpFile=" + str(self.print_out_composite_warp_file) + "]") - return cargs - - def outputs( - self, - execution: Execution, - ) -> AntsApplyTransformsCompositeDisplacementFieldOutputOutputs: - """ - Collect output file paths. - - Args: - execution: The execution object. - Returns: - NamedTuple of outputs (described in `AntsApplyTransformsCompositeDisplacementFieldOutputOutputs`). - """ - ret = AntsApplyTransformsCompositeDisplacementFieldOutputOutputs( - root=execution.output_file("."), - output_image_outfile=execution.output_file(self.composite_displacement_field), - ) - return ret - - -class AntsApplyTransformsGenericAffineTransformOutputOutputs(typing.NamedTuple): - """ - Output object returned when calling `AntsApplyTransformsGenericAffineTransformOutput(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_outfile: OutputPathType - """Warped image.""" - - -@dataclasses.dataclass -class AntsApplyTransformsGenericAffineTransformOutput: - """ - Compose all affine transforms and (if boolean is set) calculate its inverse - which is then written to an ITK file. - """ - generic_affine_transform_file: str - """Output file name.""" - calculate_inverse: typing.Literal[0, 1] | None = None - """Calculate the inverse of the affine transform.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.calculate_inverse is not None: - cargs.append("Linear[" + self.generic_affine_transform_file + ",calculateInverse=" + str(self.calculate_inverse) + "]") - return cargs - - def outputs( - self, - execution: Execution, - ) -> AntsApplyTransformsGenericAffineTransformOutputOutputs: - """ - Collect output file paths. - - Args: - execution: The execution object. - Returns: - NamedTuple of outputs (described in `AntsApplyTransformsGenericAffineTransformOutputOutputs`). - """ - ret = AntsApplyTransformsGenericAffineTransformOutputOutputs( - root=execution.output_file("."), - output_image_outfile=execution.output_file(self.generic_affine_transform_file), - ) - return ret - - -@dataclasses.dataclass -class AntsApplyTransformsLinear: - """ - Linear interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Linear") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsNearestNeighbor: - """ - Nearest neighbor interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("NearestNeighbor") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsMultiLabel: - """ - Multi label interpolation. - """ - sigma: float | None = None - """Sigma value.""" - alpha: float | None = None - """Alpha value.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.sigma is not None or self.alpha is not None: - cargs.append("MultiLabel[" + "sigma=" + (str(self.sigma) if self.sigma is not None else "") + ",alpha=" + (str(self.alpha) if self.alpha is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsGaussian: - """ - Gaussian interpolation. - """ - sigma: float | None = None - """Sigma value.""" - alpha: float | None = None - """Alpha value.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.sigma is not None or self.alpha is not None: - cargs.append("Gaussian[" + "sigma=" + (str(self.sigma) if self.sigma is not None else "") + ",alpha=" + (str(self.alpha) if self.alpha is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsBspline: - """ - BSpline interpolation. - """ - order: int | None = None - """Order value.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.order is not None: - cargs.append("BSpline[" + "order=" + str(self.order) + "]") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsCosineWindowedSinc: - """ - Cosine windowed sinc interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("CosineWindowedSinc") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsWelchWindowedSinc: - """ - Welch windowed sinc interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("WelchWindowedSinc") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsHammingWindowedSinc: - """ - Hamming windowed sinc interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("HammingWindowedSinc") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsLanczosWindowedSinc: - """ - Lanczos windowed sinc interpolation. - """ - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("LanczosWindowedSinc") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsGenericLabel: - """ - Generic label interpolation. - """ - interpolator: str | None = None - """Interpolator value.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.interpolator is not None: - cargs.append("GenericLabel[" + "interpolator=" + self.interpolator + "]") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsTransformFileName: - """ - Transform file name. - """ - transform_file_name: InputPathType - """Transform file name.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(execution.input_file(self.transform_file_name)) - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsUseInverse: - """ - Use inverse. - """ - transform_file_name: InputPathType - """Transform file name.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("[" + execution.input_file(self.transform_file_name) + ",useInverse]") - return cargs - - -class AntsApplyTransformsOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_apply_transforms(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: typing.Union[AntsApplyTransformsWarpedOutputOutputs, AntsApplyTransformsCompositeDisplacementFieldOutputOutputs, AntsApplyTransformsGenericAffineTransformOutputOutputs] - """Outputs from `AntsApplyTransformsWarpedOutput` or - `AntsApplyTransformsCompositeDisplacementFieldOutput` or - `AntsApplyTransformsGenericAffineTransformOutput`.""" - - -def ants_apply_transforms( - input_image: InputPathType, - reference_image: InputPathType, - output: typing.Union[AntsApplyTransformsWarpedOutput, AntsApplyTransformsCompositeDisplacementFieldOutput, AntsApplyTransformsGenericAffineTransformOutput], - dimensionality: typing.Literal[2, 3, 4] | None = None, - input_image_type: typing.Literal[0, 1, 2, 3, 4, 5] | None = None, - interpolation: typing.Union[AntsApplyTransformsLinear, AntsApplyTransformsNearestNeighbor, AntsApplyTransformsMultiLabel, AntsApplyTransformsGaussian, AntsApplyTransformsBspline, AntsApplyTransformsCosineWindowedSinc, AntsApplyTransformsWelchWindowedSinc, AntsApplyTransformsHammingWindowedSinc, AntsApplyTransformsLanczosWindowedSinc, AntsApplyTransformsGenericLabel] | None = None, - output_data_type: typing.Literal["char", "uchar", "short", "int", "float", "double", "default"] | None = None, - transform: list[typing.Union[AntsApplyTransformsTransformFileName, AntsApplyTransformsUseInverse]] | None = None, - default_value: float | None = None, - static_cast_for_r: str | None = None, - float_: typing.Literal[0, 1] | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsApplyTransformsOutputs: - """ - antsApplyTransforms, applied to an input image, transforms it according to a - reference image and a transform (or a set of transforms). - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: Currently, the only input objects supported are image\ - objects. However, the current framework allows for warping of other\ - objects such as meshes and point sets. - reference_image: For warping input images, the reference image defines\ - the spacing, origin, size, and direction of the output warped image. - output: One can either output the warped image or, if the boolean is\ - set, one can print out the displacement field based on the composite\ - transform and the reference image. A third option is to compose all\ - affine transforms and (if boolean is set) calculate its inverse which\ - is then written to an ITK file. - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. if not specified, antswarp tries to infer\ - the dimensionality from the input image. - input_image_type: Option specifying the input image type of scalar\ - (default), vector, tensor, time series, or multi-channel. A time series\ - image is a scalar image defined by an additional dimension for the time\ - component whereas a multi-channel image is a vector image with only\ - spatial dimensions. Five-dimensional images are e.g., AFNI stats image. - interpolation: Several interpolation options are available in ITK.\ - These have all been made available. - output_data_type: Output image data type. This is a direct typecast;\ - output values are not rescaled. Default is to use the internal data\ - type (float or double). uchar is unsigned char; others are signed.\ - WARNING: Outputs will be incorrect (overflowed/reinterpreted) if values\ - exceed the range allowed by your choice. Note that some pixel types are\ - not supported by some image formats. e.g. int is not supported by jpg. - transform: Several transform options are supported including all those\ - defined in the ITK library in addition to a deformation field\ - transform. The ordering of the transformations follows the ordering\ - specified on the command line. An identity transform is pushed onto the\ - transformation stack. Each new transform encountered on the command\ - line is also pushed onto the transformation stack. Then, to warp the\ - input object, each point comprising the input object is warped first\ - according to the last transform pushed onto the stack followed by the\ - second to last transform, etc. until the last transform encountered\ - which is the identity transform. Also, it should be noted that the\ - inverse transform can be accommodated with the usual caveat that such\ - an inverse must be defined by the specified transform class. - default_value: Default voxel value to be used with input images only.\ - Specifies the voxel value when the input point maps outside the output\ - domain. With tensor input images, specifies the default voxel\ - eigenvalues. - static_cast_for_r: Forces static cast in ReadTransform (for R). - float_: Use float instead of double for computations. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsApplyTransformsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_APPLY_TRANSFORMS_METADATA) - cargs = [] - cargs.append("antsApplyTransforms") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - if input_image_type is not None: - cargs.extend([ - "--input-image-type", - str(input_image_type) - ]) - cargs.extend([ - "--input", - execution.input_file(input_image) - ]) - cargs.extend([ - "--reference-image", - execution.input_file(reference_image) - ]) - cargs.extend([ - "--output", - *output.run(execution) - ]) - if interpolation is not None: - cargs.extend([ - "--interpolation", - *interpolation.run(execution) - ]) - if output_data_type is not None: - cargs.extend([ - "--output-data-type", - output_data_type - ]) - if transform is not None: - cargs.extend([ - "--transform", - *[a for c in [s.run(execution) for s in transform] for a in c] - ]) - if default_value is not None: - cargs.extend([ - "--default-value", - str(default_value) - ]) - if static_cast_for_r is not None: - cargs.extend([ - "--static-cast-for-R", - static_cast_for_r - ]) - if float_ is not None: - cargs.extend([ - "--float", - str(float_) - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = AntsApplyTransformsOutputs( - root=execution.output_file("."), - output=output.outputs(execution), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_APPLY_TRANSFORMS_METADATA", - "AntsApplyTransformsBspline", - "AntsApplyTransformsCompositeDisplacementFieldOutput", - "AntsApplyTransformsCompositeDisplacementFieldOutputOutputs", - "AntsApplyTransformsCosineWindowedSinc", - "AntsApplyTransformsGaussian", - "AntsApplyTransformsGenericAffineTransformOutput", - "AntsApplyTransformsGenericAffineTransformOutputOutputs", - "AntsApplyTransformsGenericLabel", - "AntsApplyTransformsHammingWindowedSinc", - "AntsApplyTransformsLanczosWindowedSinc", - "AntsApplyTransformsLinear", - "AntsApplyTransformsMultiLabel", - "AntsApplyTransformsNearestNeighbor", - "AntsApplyTransformsOutputs", - "AntsApplyTransformsTransformFileName", - "AntsApplyTransformsUseInverse", - "AntsApplyTransformsWarpedOutput", - "AntsApplyTransformsWarpedOutputOutputs", - "AntsApplyTransformsWelchWindowedSinc", - "ants_apply_transforms", -] diff --git a/python/src/niwrap/ants/ants_apply_transforms_to_points.py b/python/src/niwrap/ants/ants_apply_transforms_to_points.py deleted file mode 100644 index 2a7fc37d3..000000000 --- a/python/src/niwrap/ants/ants_apply_transforms_to_points.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_APPLY_TRANSFORMS_TO_POINTS_METADATA = Metadata( - id="1ba8745cbb78f985d998ca462d13cc2627bbcd68.boutiques", - name="antsApplyTransformsToPoints", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class AntsApplyTransformsToPointsSingleTransform: - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("[TRANSFORM]") - return cargs - - -@dataclasses.dataclass -class AntsApplyTransformsToPointsInverseTransform: - transform_file: InputPathType - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(execution.input_file(self.transform_file) + ",1") - return cargs - - -class AntsApplyTransformsToPointsOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_apply_transforms_to_points(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warped_points: OutputPathType - """The output is the CSV file containing warped points.""" - - -def ants_apply_transforms_to_points( - input_: InputPathType, - output: str, - dimensionality: typing.Literal[2, 3] | None = None, - precision: typing.Literal[0, 1] | None = None, - forantsr: typing.Literal[0, 1] | None = None, - transform: typing.Union[AntsApplyTransformsToPointsSingleTransform, AntsApplyTransformsToPointsInverseTransform] | None = None, - runner: Runner | None = None, -) -> AntsApplyTransformsToPointsOutputs: - """ - antsApplyTransformsToPoints, applied to an input image, transforms it according - to a reference image and a transform (or a set of transforms). It reads in a CSV - file with the first D columns defining the spatial location where the spatial - location is defined in physical coordinates. The CSV file should have a header - row. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_: Input CSV file with columns including x,y,z,t headers that\ - define the points in physical space, or a 2D .mha binary image file. - output: Output the warped points to a CSV file. - dimensionality: This option forces the points to be treated as a\ - specified-dimensionality. - precision: Use double precision. - forantsr: Set true for ANTsR IO. - transform: Transform file(s) to apply to the input points. Uses an\ - inverse transform if specified as [transformFileName,1]. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsApplyTransformsToPointsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_APPLY_TRANSFORMS_TO_POINTS_METADATA) - cargs = [] - cargs.append("antsApplyTransformsToPoints") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - if precision is not None: - cargs.extend([ - "--precision", - str(precision) - ]) - if forantsr is not None: - cargs.extend([ - "--forantsr", - str(forantsr) - ]) - cargs.extend([ - "-i", - execution.input_file(input_) - ]) - cargs.extend([ - "-o", - output - ]) - if transform is not None: - cargs.extend([ - "-t", - *transform.run(execution) - ]) - ret = AntsApplyTransformsToPointsOutputs( - root=execution.output_file("."), - warped_points=execution.output_file(output), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_APPLY_TRANSFORMS_TO_POINTS_METADATA", - "AntsApplyTransformsToPointsInverseTransform", - "AntsApplyTransformsToPointsOutputs", - "AntsApplyTransformsToPointsSingleTransform", - "ants_apply_transforms_to_points", -] diff --git a/python/src/niwrap/ants/ants_atropos_n4_sh.py b/python/src/niwrap/ants/ants_atropos_n4_sh.py deleted file mode 100644 index 084074145..000000000 --- a/python/src/niwrap/ants/ants_atropos_n4_sh.py +++ /dev/null @@ -1,295 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_ATROPOS_N4_SH_METADATA = Metadata( - id="26f6c01fef89c147f9f9fc215073f4d86231d70b.boutiques", - name="antsAtroposN4.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class AntsAtroposN4ShSegmentationPriors: - """ - Prior probability images initializing the segmentation. Specified using - c-style formatting, e.g. -p labelsPriors%02d.nii.gz. If this is not - specified, k-means initialization is used instead. - """ - segmentation_priors_pattern: str | None = None - """Prior probability images initializing the segmentation. Specified using - c-style formatting, e.g. -p labelsPriors%02d.nii.gz. If this is not - specified, k-means initialization is used instead.""" - segmentation_priors_folder: InputPathType | None = None - """Included so.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.segmentation_priors_pattern is not None or self.segmentation_priors_folder is not None: - cargs.append((self.segmentation_priors_pattern if self.segmentation_priors_pattern is not None else "") + "/" + (execution.input_file(self.segmentation_priors_folder) if self.segmentation_priors_folder is not None else "")) - return cargs - - -class AntsAtroposN4ShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_atropos_n4_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - n4_corrected: OutputPathType - """N4 corrected image.""" - segmentation: OutputPathType - """Segmentation image.""" - segmentation_posteriors: OutputPathType - """Segmentation posteriors image.""" - - -def ants_atropos_n4_sh( - image_dimension: typing.Literal[2, 3], - input_image: InputPathType, - mask_image: InputPathType, - number_of_classes: int, - output_prefix: str, - segmentation_priors: AntsAtroposN4ShSegmentationPriors, - max_n4_atropos_iterations: int | None = None, - max_atropos_iterations: int | None = None, - mrf: str | None = None, - denoise_anatomical_images: typing.Literal[0, 1] | None = None, - posterior_formulation: typing.Literal["Socrates[ 1 ]", "Aristotle[ 1 ]"] | None = None, - label_propagation: str | None = None, - posterior_label_for_n4_weight_mask: str | None = None, - image_file_suffix: str | None = None, - keep_temporary_files: typing.Literal[0, 1] | None = None, - use_random_seeding: typing.Literal[0, 1] | None = None, - atropos_segmentation_prior_weight: float | None = None, - n4_convergence: str | None = None, - n4_shrink_factor: int | None = None, - n4_bspline_params: str | None = None, - atropos_segmentation_icm: str | None = None, - atropos_segmentation_use_euclidean_distance: typing.Literal[0, 1] | None = None, - test_debug_mode: int | None = None, - runner: Runner | None = None, -) -> AntsAtroposN4ShOutputs: - """ - antsAtroposN4.sh iterates between N4 <-> Atropos to improve segmentation - results. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: 2 or 3, for 2- or 3-dimensional image. - input_image: Anatomical image, typically T1. If more than one\ - anatomical image is specified, subsequent images are also used during\ - the segmentation process. - mask_image: Binary mask defining the region of interest. - number_of_classes: Number of classes defining the segmentation. - output_prefix: The following images are created:\ - {output_prefix}N4Corrected.{output_suffix},\ - {output_prefix}Segmentation.{output_suffix},\ - {output_prefix}SegmentationPosteriors.{output_suffix}. - segmentation_priors: Prior probability images initializing the\ - segmentation. Specified using c-style formatting, e.g. -p\ - labelsPriors%02d.nii.gz. If this is not specified, k-means\ - initialization is used instead. - max_n4_atropos_iterations: Maximum number of (outer loop) iterations\ - between N4 <-> Atropos (default = 15). - max_atropos_iterations: Maximum number of (inner loop) iterations in\ - Atropos (default = 3). - mrf: Specifies MRF prior (of the form '[ weight,neighborhood ]', e.g.\ - '[ 0.1,1x1x1 ]' which is default). - denoise_anatomical_images: Denoise anatomical images (1) or not (0)\ - (default = 1). - posterior_formulation: Posterior formulation and whether or not to use\ - mixture model proportions. e.g 'Socrates[ 1 ]' (default) or 'Aristotle[\ - 1 ]'. Choose the latter if you want to use the distance priors, see\ - also the -l option for label propagation control (default = 'Socrates[\ - 1 ]'). - label_propagation: Incorporate a distance prior into the 'Aristotle'\ - posterior formulation. Should be of the form 'label[\ - lambda,boundaryProbability ]' where label is a value of 1,2,3,...\ - denoting label ID. The label probability for anything outside the\ - current label\ - \ - = boundaryProbability * exp( -lambda * distanceFromBoundary )\ - \ - Intuitively, smaller lambda values will increase the spatial\ - capture range of the distance prior. To apply to all label values,\ - simply omit specifying the label, i.e. -l '[\ - lambda,boundaryProbability ]'. - posterior_label_for_n4_weight_mask: Which posterior probability image\ - should be used to define the N4 weight mask. Can also specify multiple\ - posteriors in which case the chosen posteriors are combined. - image_file_suffix: Any of the standard ITK IO formats e.g. nrrd, nii.gz\ - (default), mhd. - keep_temporary_files: Keep temporary files on disk (1) or delete them\ - (0) (default = 0). - use_random_seeding: Use random number generated from system clock in\ - Atropos (default = 1). - atropos_segmentation_prior_weight: Atropos spatial prior probability\ - weight for the segmentation (default = 0.25). - n4_convergence: Convergence parameters for N4, see '-c' option in\ - N4BiasFieldCorrection (default = [50x50x50x50,0.0000001]). - n4_shrink_factor: Shrink factor for N4 (default = 4). - n4_bspline_params: N4 b-spline specification, see '-b' option in\ - N4BiasFieldCorrection (default = [200,0,0,0]). - atropos_segmentation_icm: ICM parameters for segmentation, see '-g'\ - option in Atropos (default = [1,1]). - atropos_segmentation_use_euclidean_distance: Use euclidean distances in\ - distance prior formulation (1) or not (0), see Atropos usage for\ - details (default = 1). - test_debug_mode: If > 0, attempts to continue after errors. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsAtroposN4ShOutputs`). - """ - if max_n4_atropos_iterations is not None and not (1 <= max_n4_atropos_iterations): - raise ValueError(f"'max_n4_atropos_iterations' must be greater than 1 <= x but was {max_n4_atropos_iterations}") - if max_atropos_iterations is not None and not (1 <= max_atropos_iterations): - raise ValueError(f"'max_atropos_iterations' must be greater than 1 <= x but was {max_atropos_iterations}") - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_ATROPOS_N4_SH_METADATA) - cargs = [] - cargs.append("antsAtroposN4.sh") - cargs.extend([ - "-d", - str(image_dimension) - ]) - cargs.extend([ - "-a", - execution.input_file(input_image) - ]) - cargs.extend([ - "-x", - execution.input_file(mask_image) - ]) - cargs.extend([ - "-c", - str(number_of_classes) - ]) - cargs.extend([ - "-o", - output_prefix - ]) - if max_n4_atropos_iterations is not None: - cargs.extend([ - "-m", - str(max_n4_atropos_iterations) - ]) - if max_atropos_iterations is not None: - cargs.extend([ - "-n", - str(max_atropos_iterations) - ]) - cargs.extend([ - "-p", - *segmentation_priors.run(execution) - ]) - if mrf is not None: - cargs.extend([ - "-r", - mrf - ]) - if denoise_anatomical_images is not None: - cargs.extend([ - "-g", - str(denoise_anatomical_images) - ]) - if posterior_formulation is not None: - cargs.extend([ - "-b", - posterior_formulation - ]) - if label_propagation is not None: - cargs.extend([ - "-l", - label_propagation - ]) - if posterior_label_for_n4_weight_mask is not None: - cargs.extend([ - "-y", - posterior_label_for_n4_weight_mask - ]) - if image_file_suffix is not None: - cargs.extend([ - "-s", - image_file_suffix - ]) - if keep_temporary_files is not None: - cargs.extend([ - "-k", - str(keep_temporary_files) - ]) - if use_random_seeding is not None: - cargs.extend([ - "-u", - str(use_random_seeding) - ]) - if atropos_segmentation_prior_weight is not None: - cargs.extend([ - "-w", - str(atropos_segmentation_prior_weight) - ]) - if n4_convergence is not None: - cargs.extend([ - "-e", - n4_convergence - ]) - if n4_shrink_factor is not None: - cargs.extend([ - "-f", - str(n4_shrink_factor) - ]) - if n4_bspline_params is not None: - cargs.extend([ - "-q", - n4_bspline_params - ]) - if atropos_segmentation_icm is not None: - cargs.extend([ - "-i", - atropos_segmentation_icm - ]) - if atropos_segmentation_use_euclidean_distance is not None: - cargs.extend([ - "-j", - str(atropos_segmentation_use_euclidean_distance) - ]) - if test_debug_mode is not None: - cargs.extend([ - "-z", - str(test_debug_mode) - ]) - ret = AntsAtroposN4ShOutputs( - root=execution.output_file("."), - n4_corrected=execution.output_file(output_prefix + "N4Corrected.[OUTPUT_SUFFIX]"), - segmentation=execution.output_file(output_prefix + "Segmentation.[OUTPUT_SUFFIX]"), - segmentation_posteriors=execution.output_file(output_prefix + "SegmentationPosteriors.[OUTPUT_SUFFIX]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_ATROPOS_N4_SH_METADATA", - "AntsAtroposN4ShOutputs", - "AntsAtroposN4ShSegmentationPriors", - "ants_atropos_n4_sh", -] diff --git a/python/src/niwrap/ants/ants_brain_extraction_sh.py b/python/src/niwrap/ants/ants_brain_extraction_sh.py deleted file mode 100644 index d9e6d7400..000000000 --- a/python/src/niwrap/ants/ants_brain_extraction_sh.py +++ /dev/null @@ -1,143 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_BRAIN_EXTRACTION_SH_METADATA = Metadata( - id="5894615eb100790c62c8481f7802b90ba5989720.boutiques", - name="antsBrainExtraction.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsBrainExtractionShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_brain_extraction_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - brain_extracted_image: OutputPathType | None - """Brain extracted image""" - brain_mask: OutputPathType | None - """Brain mask""" - brain_probability_mask: OutputPathType | None - """Brain probability mask""" - - -def ants_brain_extraction_sh( - anatomical_image: InputPathType, - template: InputPathType, - probability_mask: InputPathType, - image_dimension: int = 3, - tissue_classification: str | None = None, - brain_extraction_registration_mask: InputPathType | None = None, - keep_temporary_files: bool = False, - single_floating_point_precision: bool = False, - initial_moving_transform: InputPathType | None = None, - rotation_search_params: str | None = None, - image_file_suffix: str | None = None, - translation_search_params: str | None = None, - random_seeding: bool = False, - debug_mode: bool = False, - output_prefix: str | None = "output", - runner: Runner | None = None, -) -> AntsBrainExtractionShOutputs: - """ - antsBrainExtraction.sh performs template-based brain extraction. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - anatomical_image: Anatomical image (Structural image, typically T1). - template: Brain extraction template (Anatomical template). - probability_mask: Brain extraction probability mask. - image_dimension: Image dimension (2 or 3). - tissue_classification: Tissue classification. - brain_extraction_registration_mask: Brain extraction registration mask. - keep_temporary_files: Keep temporary files. - single_floating_point_precision: Use single floating point precision. - initial_moving_transform: Initial moving transform. - rotation_search_params: Rotation search parameters. - image_file_suffix: Image file suffix. - translation_search_params: Translation search parameters. - random_seeding: Use random seeding. - debug_mode: Test / debug mode. - output_prefix: Output prefix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsBrainExtractionShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_BRAIN_EXTRACTION_SH_METADATA) - cargs = [] - cargs.append("antsBrainExtraction.sh") - cargs.append("-d") - cargs.append(str(image_dimension)) - cargs.append("-a") - cargs.append(execution.input_file(anatomical_image)) - cargs.append("-e") - cargs.append(execution.input_file(template)) - cargs.append("-m") - cargs.append(execution.input_file(probability_mask)) - if tissue_classification is not None: - cargs.extend([ - "-c", - tissue_classification - ]) - if brain_extraction_registration_mask is not None: - cargs.extend([ - "-f", - execution.input_file(brain_extraction_registration_mask) - ]) - if keep_temporary_files: - cargs.append("-k") - if single_floating_point_precision: - cargs.append("-q") - if initial_moving_transform is not None: - cargs.extend([ - "-r", - execution.input_file(initial_moving_transform) - ]) - if rotation_search_params is not None: - cargs.extend([ - "-R", - rotation_search_params - ]) - if image_file_suffix is not None: - cargs.extend([ - "-s", - image_file_suffix - ]) - if translation_search_params is not None: - cargs.extend([ - "-T", - translation_search_params - ]) - if random_seeding: - cargs.append("-u") - if debug_mode: - cargs.append("-z") - cargs.append("-o") - if output_prefix is not None: - cargs.append(output_prefix) - ret = AntsBrainExtractionShOutputs( - root=execution.output_file("."), - brain_extracted_image=execution.output_file(output_prefix + "BrainExtractionBrain.nii.gz") if (output_prefix is not None) else None, - brain_mask=execution.output_file(output_prefix + "BrainExtractionMask.nii.gz") if (output_prefix is not None) else None, - brain_probability_mask=execution.output_file(output_prefix + "BrainExtractionPrior0GenericAffine.mat") if (output_prefix is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_BRAIN_EXTRACTION_SH_METADATA", - "AntsBrainExtractionShOutputs", - "ants_brain_extraction_sh", -] diff --git a/python/src/niwrap/ants/ants_cortical_thickness_sh.py b/python/src/niwrap/ants/ants_cortical_thickness_sh.py deleted file mode 100644 index c053a5bfc..000000000 --- a/python/src/niwrap/ants/ants_cortical_thickness_sh.py +++ /dev/null @@ -1,116 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_CORTICAL_THICKNESS_SH_METADATA = Metadata( - id="a3debb9e7548d8b061c55b2110e40e13a1ee68ec.boutiques", - name="antsCorticalThickness.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsCorticalThicknessShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_cortical_thickness_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - cortical_thickness: OutputPathType - """The output cortical thickness map.""" - brain_extraction_mask: OutputPathType - """The brain extraction mask.""" - brain_segmentation: OutputPathType - """The brain segmentation image.""" - segmentation_posteriors: OutputPathType - """The segmentation posteriors for different tissue classes.""" - - -def ants_cortical_thickness_sh( - image_dimension: typing.Literal[2, 3], - anatomical_image: InputPathType, - brain_template: InputPathType, - brain_extraction_probability_mask: InputPathType, - brain_segmentation_priors: str, - output_prefix: str, - runner: Runner | None = None, -) -> AntsCorticalThicknessShOutputs: - """ - This script performs T1 anatomical brain processing including brain extraction, - brain n-tissue segmentation, cortical thickness estimation, and optional - registration to a template. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: 2 or 3 for 2- or 3-dimensional image. - anatomical_image: Structural intensity image, typically T1. - brain_template: Anatomical intensity template. This template is not\ - skull-stripped. - brain_extraction_probability_mask: Brain probability mask in the\ - segmentation template space. A binary mask is acceptable. - brain_segmentation_priors: Tissue probability priors corresponding to\ - the template image specified with the -e option. At least four priors\ - must exist, corresponding to CSF, Cortical GM, WM, Subcortical GM. - output_prefix: Output prefix for the generated filenames. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsCorticalThicknessShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_CORTICAL_THICKNESS_SH_METADATA) - cargs = [] - cargs.append("antsCorticalThickness.sh") - cargs.append("-d") - cargs.extend([ - "-d", - str(image_dimension) - ]) - cargs.append("-a") - cargs.extend([ - "-a", - execution.input_file(anatomical_image) - ]) - cargs.append("-e") - cargs.extend([ - "-e", - execution.input_file(brain_template) - ]) - cargs.append("-m") - cargs.extend([ - "-m", - execution.input_file(brain_extraction_probability_mask) - ]) - cargs.append("-p") - cargs.extend([ - "-p", - brain_segmentation_priors - ]) - cargs.append("[ADDITIONAL_PARAMETERS]") - cargs.append("-o") - cargs.extend([ - "-o", - output_prefix - ]) - ret = AntsCorticalThicknessShOutputs( - root=execution.output_file("."), - cortical_thickness=execution.output_file(output_prefix + "CorticalThickness.nii.gz"), - brain_extraction_mask=execution.output_file(output_prefix + "BrainExtractionMask.nii.gz"), - brain_segmentation=execution.output_file(output_prefix + "BrainSegmentation.nii.gz"), - segmentation_posteriors=execution.output_file(output_prefix + "BrainSegmentationPosteriors*.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_CORTICAL_THICKNESS_SH_METADATA", - "AntsCorticalThicknessShOutputs", - "ants_cortical_thickness_sh", -] diff --git a/python/src/niwrap/ants/ants_intermodality_intrasubject_sh.py b/python/src/niwrap/ants/ants_intermodality_intrasubject_sh.py deleted file mode 100644 index 7c3f23b29..000000000 --- a/python/src/niwrap/ants/ants_intermodality_intrasubject_sh.py +++ /dev/null @@ -1,154 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_INTERMODALITY_INTRASUBJECT_SH_METADATA = Metadata( - id="a6448dff8e3e5a29418463f13e74dadaaf6941ee.boutiques", - name="antsIntermodalityIntrasubject.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsIntermodalityIntrasubjectShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_intermodality_intrasubject_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transformed_image: OutputPathType - """Output transformed image after registration.""" - output_transform: OutputPathType - """Transformation matrix or warp field from the registration.""" - output_warped_image: OutputPathType - """Output warped image in the template space.""" - - -def ants_intermodality_intrasubject_sh( - dimension: int, - anatomical_t1_image: InputPathType, - scalar_image_to_match: InputPathType, - anatomical_t1brainmask: InputPathType, - transform_type: typing.Literal[0, 1, 2, 3], - t1_to_template_prefix: str, - output_prefix: str, - anatomical_reference_image: InputPathType | None = None, - template_space: str | None = None, - labels_in_template_space: InputPathType | None = None, - auxiliary_scalar_images: InputPathType | None = None, - auxiliary_dt_image: InputPathType | None = None, - runner: Runner | None = None, -) -> AntsIntermodalityIntrasubjectShOutputs: - """ - Performs registration between a scalar image and a T1 image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimension: Dimensionality of the image, typically 3 for 3D images. - anatomical_t1_image: Anatomical T1 image (brain or whole-head) to align\ - to. - scalar_image_to_match: Scalar image to be matched, such as average\ - BOLD, average DWI, etc. - anatomical_t1brainmask: Brain mask for the anatomical T1 image, should\ - mask out regions not appearing in the scalar image. - transform_type: Type of transform: 0=rigid, 1=affine,\ - 2=rigid+small_def, 3=affine+small_def. - t1_to_template_prefix: Prefix for T1 to template transform files. - output_prefix: Prefix for output files. - anatomical_reference_image: Anatomical reference image to warp to,\ - often higher resolution than the anatomical T1 image. - template_space: Template space. - labels_in_template_space: Labels in the template space. - auxiliary_scalar_images: Auxiliary scalar images to warp to the\ - template. - auxiliary_dt_image: Auxiliary DT image to warp to the template. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsIntermodalityIntrasubjectShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_INTERMODALITY_INTRASUBJECT_SH_METADATA) - cargs = [] - cargs.append("antsIntermodalityIntrasubject.sh") - cargs.extend([ - "-d", - str(dimension) - ]) - cargs.append("-r") - cargs.extend([ - "-r", - execution.input_file(anatomical_t1_image) - ]) - cargs.append("-R") - if anatomical_reference_image is not None: - cargs.extend([ - "-R", - execution.input_file(anatomical_reference_image) - ]) - cargs.append("-i") - cargs.extend([ - "-i", - execution.input_file(scalar_image_to_match) - ]) - cargs.append("-x") - cargs.extend([ - "-x", - execution.input_file(anatomical_t1brainmask) - ]) - cargs.append("-t") - cargs.extend([ - "-t", - str(transform_type) - ]) - cargs.append("-w") - cargs.extend([ - "-w", - t1_to_template_prefix - ]) - cargs.append("-T") - if template_space is not None: - cargs.extend([ - "-T", - template_space - ]) - cargs.extend([ - "-o", - output_prefix - ]) - if labels_in_template_space is not None: - cargs.extend([ - "-l", - execution.input_file(labels_in_template_space) - ]) - if auxiliary_scalar_images is not None: - cargs.extend([ - "-a", - execution.input_file(auxiliary_scalar_images) - ]) - if auxiliary_dt_image is not None: - cargs.extend([ - "-b", - execution.input_file(auxiliary_dt_image) - ]) - ret = AntsIntermodalityIntrasubjectShOutputs( - root=execution.output_file("."), - output_transformed_image=execution.output_file(output_prefix + "Transformed.nii.gz"), - output_transform=execution.output_file(output_prefix + "Transform.mat"), - output_warped_image=execution.output_file(output_prefix + "Warped.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_INTERMODALITY_INTRASUBJECT_SH_METADATA", - "AntsIntermodalityIntrasubjectShOutputs", - "ants_intermodality_intrasubject_sh", -] diff --git a/python/src/niwrap/ants/ants_introduction_sh.py b/python/src/niwrap/ants/ants_introduction_sh.py deleted file mode 100644 index ef5bb2297..000000000 --- a/python/src/niwrap/ants/ants_introduction_sh.py +++ /dev/null @@ -1,136 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_INTRODUCTION_SH_METADATA = Metadata( - id="d2cd2290031399860c753b700fceb3b68d1916e4.boutiques", - name="antsIntroduction.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsIntroductionShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_introduction_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def ants_introduction_sh( - image_dimension: typing.Literal[2, 3], - reference_image: InputPathType, - input_image: InputPathType, - force: typing.Literal[0, 1] | None = 1, - labels_in_fixed_image_space: str | None = None, - max_iterations: int | None = None, - n4_bias_field_correction: typing.Literal[0, 1] | None = 0, - outprefix: str | None = None, - quality_check: typing.Literal[0, 1] | None = 0, - similarity_metric: str | None = None, - transformation_model: str | None = None, - runner: Runner | None = None, -) -> AntsIntroductionShOutputs: - """ - Script for registration using ANTS with compulsory and optional arguments. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Image dimension for registration: 2 or 3. - reference_image: Reference image for registration. - input_image: Input image to be registered. - force: Force script to proceed even if headers may be incompatible. - labels_in_fixed_image_space: Labels in fixed image space to deform to\ - moving image. - max_iterations: Maximum number of iterations. - n4_bias_field_correction: N4 Bias Field Correction of moving image: 0\ - for off, 1 for on. - outprefix: A prefix that is prepended to all output files. - quality_check: Perform a Quality Check (QC) of the result: 0 for off, 1\ - for on. - similarity_metric: Type of similarity metric used for registration. - transformation_model: Type of transformation model used for\ - registration. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsIntroductionShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_INTRODUCTION_SH_METADATA) - cargs = [] - cargs.append("antsIntroduction.sh") - cargs.append("-d") - cargs.extend([ - "-d", - str(image_dimension) - ]) - cargs.append("-r") - cargs.extend([ - "-r", - execution.input_file(reference_image) - ]) - cargs.append("-i") - cargs.extend([ - "-i", - execution.input_file(input_image) - ]) - if force is not None: - cargs.extend([ - "-f", - str(force) - ]) - if labels_in_fixed_image_space is not None: - cargs.extend([ - "-l", - labels_in_fixed_image_space - ]) - if max_iterations is not None: - cargs.extend([ - "-m", - str(max_iterations) - ]) - if n4_bias_field_correction is not None: - cargs.extend([ - "-n", - str(n4_bias_field_correction) - ]) - if outprefix is not None: - cargs.extend([ - "-o", - outprefix - ]) - if quality_check is not None: - cargs.extend([ - "-q", - str(quality_check) - ]) - if similarity_metric is not None: - cargs.extend([ - "-s", - similarity_metric - ]) - if transformation_model is not None: - cargs.extend([ - "-t", - transformation_model - ]) - ret = AntsIntroductionShOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_INTRODUCTION_SH_METADATA", - "AntsIntroductionShOutputs", - "ants_introduction_sh", -] diff --git a/python/src/niwrap/ants/ants_joint_fusion.py b/python/src/niwrap/ants/ants_joint_fusion.py deleted file mode 100644 index 8c02a090c..000000000 --- a/python/src/niwrap/ants/ants_joint_fusion.py +++ /dev/null @@ -1,179 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_JOINT_FUSION_METADATA = Metadata( - id="e3c0355412de6dbc842f99d135c2be7604cb670d.boutiques", - name="antsJointFusion", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsJointFusionOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_joint_fusion(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - label_fusion_image: OutputPathType - """The output label fusion image.""" - intensity_fusion_image: OutputPathType - """The output intensity fusion image format.""" - label_posterior_probability_image: OutputPathType - """The output label posterior probability image format.""" - atlas_voting_weight_image: OutputPathType - """The output atlas voting weight image format.""" - - -def ants_joint_fusion( - target_image: list[InputPathType], - atlas_image: list[InputPathType], - atlas_segmentation: InputPathType, - output: str, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - alpha: float | None = 0.1, - beta: float | None = 2.0, - constrain_nonnegative: typing.Literal[0, 1] | None = None, - patch_radius: str | None = "2x2x2", - patch_metric: typing.Literal["PC", "MSQ"] | None = "PC", - search_radius: str | None = "3x3x3", - exclusion_image: InputPathType | None = None, - mask_image: InputPathType | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsJointFusionOutputs: - """ - antsJointFusion is an image fusion algorithm developed by Hongzhi Wang and Paul - Yushkevich. This implementation is based on Paul's original ITK-style - implementation and Brian's ANTsR implementation. The original label fusion - framework was extended to accommodate intensities. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - target_image: The target image (or multimodal target images) assumed to\ - be aligned to a common image domain. - atlas_image: The atlas image (or multimodal atlas images) assumed to be\ - aligned to a common image domain. - atlas_segmentation: The atlas segmentation images. For performing label\ - fusion the number of specified segmentations should be identical to the\ - number of atlas image sets. - output: The output is the intensity and/or label fusion image.\ - Additional optional outputs include the label posterior probability\ - images and the atlas voting weight images. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - alpha: Regularization term added to matrix Mx for calculating the\ - inverse. Default = 0.1. - beta: Exponent for mapping intensity difference to the joint error.\ - Default = 2.0. - constrain_nonnegative: Constrain solution to non-negative weights. - patch_radius: Patch radius for similarity measures. Default = 2x2x2. - patch_metric: Metric to be used in determining the most similar\ - neighborhood patch. Options include Pearson's correlation (PC) and mean\ - squares (MSQ). Default = PC (Pearson correlation). - search_radius: Search radius for similarity measures. Default = 3x3x3.\ - One can also specify an image where the value at the voxel specifies\ - the isotropic search radius at that voxel. - exclusion_image: Specify an exclusion region for the given label. - mask_image: If a mask image is specified, fusion is only performed in\ - the mask region. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsJointFusionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_JOINT_FUSION_METADATA) - cargs = [] - cargs.append("antsJointFusion") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - cargs.extend([ - "--target-image", - *[execution.input_file(f) for f in target_image] - ]) - cargs.extend([ - "--atlas-image", - *[execution.input_file(f) for f in atlas_image] - ]) - cargs.extend([ - "--atlas-segmentation", - execution.input_file(atlas_segmentation) - ]) - if alpha is not None: - cargs.extend([ - "--alpha", - str(alpha) - ]) - if beta is not None: - cargs.extend([ - "--beta", - str(beta) - ]) - if constrain_nonnegative is not None: - cargs.extend([ - "--constrain-nonnegative", - str(constrain_nonnegative) - ]) - if patch_radius is not None: - cargs.extend([ - "--patch-radius", - patch_radius - ]) - if patch_metric is not None: - cargs.extend([ - "--patch-metric", - patch_metric - ]) - if search_radius is not None: - cargs.extend([ - "--search-radius", - search_radius - ]) - if exclusion_image is not None: - cargs.extend([ - "--exclusion-image", - execution.input_file(exclusion_image) - ]) - if mask_image is not None: - cargs.extend([ - "--mask-image", - execution.input_file(mask_image) - ]) - cargs.extend([ - "--output", - output - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = AntsJointFusionOutputs( - root=execution.output_file("."), - label_fusion_image=execution.output_file("[LABELFUSIONIMAGE]"), - intensity_fusion_image=execution.output_file("[INTENSITYFUSIONIMAGEFILENAMEFORMAT]"), - label_posterior_probability_image=execution.output_file("[LABELPOSTERIORPROBABILITYIMAGEFILENAMEFORMAT]"), - atlas_voting_weight_image=execution.output_file("[ATLASVOTINGWEIGHTIMAGEFILENAMEFORMAT]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_JOINT_FUSION_METADATA", - "AntsJointFusionOutputs", - "ants_joint_fusion", -] diff --git a/python/src/niwrap/ants/ants_joint_label_fusion_sh.py b/python/src/niwrap/ants/ants_joint_label_fusion_sh.py deleted file mode 100644 index c23ca4163..000000000 --- a/python/src/niwrap/ants/ants_joint_label_fusion_sh.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_JOINT_LABEL_FUSION_SH_METADATA = Metadata( - id="6ba42b66044013522b649e617a637341a1022d80.boutiques", - name="antsJointLabelFusion.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsJointLabelFusionShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_joint_label_fusion_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - segmentation_output: OutputPathType | None - """Output segmented image.""" - - -def ants_joint_label_fusion_sh( - target_image: str, - mask_image: str, - dimensionality: typing.Literal[2, 3] | None = None, - output: str | None = None, - atlas_image_mrf: str | None = None, - atlas_segmentation_mrf: str | None = None, - rigid_transform: str | None = None, - similarity_metric: str | None = None, - other_options: str | None = None, - verbose: typing.Literal[0, 1] | None = None, - rigid_transform_additional_options: str | None = None, - similarity_metric_additional_options: str | None = None, - runner: Runner | None = None, -) -> AntsJointLabelFusionShOutputs: - """ - The antsJointLabelFusion script is used for performing label fusion using - multiple atlases to improve segmentation accuracy. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - target_image: Image to segment. - mask_image: Mask image. - dimensionality: Image dimensionality (2 or 3). - output: Root directory for the output segmentation. - atlas_image_mrf: Atlas image(s) to be used for MRF initialization. - atlas_segmentation_mrf: Atlas segmentation(s) to be used for MRF\ - initialization. - rigid_transform: Rigid transform initialization. - similarity_metric: Metric used for calculating similarity. - other_options: Additional options for label fusion. - verbose: Verbose output. - rigid_transform_additional_options: Additional options for rigid\ - transform. - similarity_metric_additional_options: Additional options for similarity\ - metric. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsJointLabelFusionShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_JOINT_LABEL_FUSION_SH_METADATA) - cargs = [] - cargs.append("antsJointLabelFusion.sh") - if dimensionality is not None: - cargs.extend([ - "-d", - str(dimensionality) - ]) - if output is not None: - cargs.extend([ - "-o", - output - ]) - if atlas_image_mrf is not None: - cargs.extend([ - "-a", - atlas_image_mrf - ]) - if atlas_segmentation_mrf is not None: - cargs.extend([ - "-l", - atlas_segmentation_mrf - ]) - if rigid_transform is not None: - cargs.extend([ - "-g", - rigid_transform - ]) - if similarity_metric is not None: - cargs.extend([ - "-s", - similarity_metric - ]) - if other_options is not None: - cargs.extend([ - "-k", - other_options - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - cargs.append("-i") - cargs.extend([ - "-i", - target_image - ]) - cargs.append("-m") - cargs.extend([ - "-m", - mask_image - ]) - cargs.append("-g") - if rigid_transform_additional_options is not None: - cargs.extend([ - "-g", - rigid_transform_additional_options - ]) - cargs.append("-x") - if similarity_metric_additional_options is not None: - cargs.extend([ - "-x", - similarity_metric_additional_options - ]) - ret = AntsJointLabelFusionShOutputs( - root=execution.output_file("."), - segmentation_output=execution.output_file(output + ".nii.gz") if (output is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_JOINT_LABEL_FUSION_SH_METADATA", - "AntsJointLabelFusionShOutputs", - "ants_joint_label_fusion_sh", -] diff --git a/python/src/niwrap/ants/ants_joint_tensor_fusion.py b/python/src/niwrap/ants/ants_joint_tensor_fusion.py deleted file mode 100644 index 5391bfb0d..000000000 --- a/python/src/niwrap/ants/ants_joint_tensor_fusion.py +++ /dev/null @@ -1,200 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_JOINT_TENSOR_FUSION_METADATA = Metadata( - id="0060c77e83025b09ff07322e714ad4f9d9337634.boutiques", - name="antsJointTensorFusion", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsJointTensorFusionOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_joint_tensor_fusion(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - label_fusion_image: OutputPathType - """The label fusion image output.""" - intensity_fusion_image: OutputPathType - """The intensity fusion image output.""" - label_posterior_probability_image: OutputPathType - """The label posterior probability images.""" - atlas_voting_weight_image: OutputPathType - """The atlas voting weight images.""" - - -def ants_joint_tensor_fusion( - target_image: list[str], - atlas_image: list[str], - atlas_segmentation: InputPathType, - output: str, - dimensionality: typing.Literal[2, 3, 4] | None = None, - alpha: float | None = 0.1, - beta: float | None = 2.0, - retain_label_posterior_images: typing.Literal[0, 1] | None = None, - retain_atlas_voting_images: typing.Literal[0, 1] | None = None, - constrain_nonnegative: typing.Literal[0, 1] | None = None, - log_euclidean: typing.Literal[0, 1] | None = None, - patch_radius: str | None = None, - patch_metric: typing.Literal["PC", "MSQ"] | None = None, - search_radius: str | None = None, - exclusion_image: str | None = None, - mask_image: InputPathType | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsJointTensorFusionOutputs: - """ - antsJointTensorFusion is an image fusion algorithm developed by Hongzhi Wang and - Paul Yushkevich which won segmentation challenges at MICCAI 2012 and MICCAI - 2013. The original label fusion framework was extended to accommodate - intensities by Brian Avants. This implementation is based on the original - ITK-style implementation and ANTsR implementation. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - target_image: The target image (or multimodal target images) assumed to\ - be aligned to a common image domain. - atlas_image: The atlas image (or multimodal atlas images) assumed to be\ - aligned to a common image domain. - atlas_segmentation: The atlas segmentation images. For performing label\ - fusion the number of specified segmentations should be identical to the\ - number of atlas image sets. - output: The output is the intensity and/or label fusion image.\ - Additional optional outputs include the label posterior probability\ - images and the atlas voting weight images. - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - alpha: Regularization term added to matrix Mx for calculating the\ - inverse. Default = 0.1. - beta: Exponent for mapping intensity difference to the joint error.\ - Default = 2.0. - retain_label_posterior_images: Retain label posterior probability\ - images. Requires atlas segmentations to be specified. Default = false. - retain_atlas_voting_images: Retain atlas voting images. Default = false. - constrain_nonnegative: Constrain solution to non-negative weights. - log_euclidean: Use log Euclidean space for tensor math. - patch_radius: Patch radius for similarity measures. Default = 2x2x2. - patch_metric: Metric to be used in determining the most similar\ - neighborhood patch. Options include Pearson's correlation (PC) and mean\ - squares (MSQ). Default = PC. - search_radius: Search radius for similarity measures. Default = 3x3x3. - exclusion_image: Specify an exclusion region for the given label. - mask_image: If a mask image is specified, fusion is only performed in\ - the mask region. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsJointTensorFusionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_JOINT_TENSOR_FUSION_METADATA) - cargs = [] - cargs.append("antsJointTensorFusion") - if dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(dimensionality) - ]) - cargs.extend([ - "-t", - ",".join(target_image) - ]) - cargs.extend([ - "-g", - ",".join(atlas_image) - ]) - cargs.extend([ - "-l", - execution.input_file(atlas_segmentation) - ]) - if alpha is not None: - cargs.extend([ - "-a", - str(alpha) - ]) - if beta is not None: - cargs.extend([ - "-b", - str(beta) - ]) - if retain_label_posterior_images is not None: - cargs.extend([ - "-r", - str(retain_label_posterior_images) - ]) - if retain_atlas_voting_images is not None: - cargs.extend([ - "-f", - str(retain_atlas_voting_images) - ]) - if constrain_nonnegative is not None: - cargs.extend([ - "-c", - str(constrain_nonnegative) - ]) - if log_euclidean is not None: - cargs.extend([ - "-u", - str(log_euclidean) - ]) - if patch_radius is not None: - cargs.extend([ - "-p", - patch_radius - ]) - if patch_metric is not None: - cargs.extend([ - "-m", - patch_metric - ]) - if search_radius is not None: - cargs.extend([ - "-s", - search_radius - ]) - if exclusion_image is not None: - cargs.extend([ - "-e", - exclusion_image - ]) - if mask_image is not None: - cargs.extend([ - "-x", - execution.input_file(mask_image) - ]) - cargs.extend([ - "-o", - output - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = AntsJointTensorFusionOutputs( - root=execution.output_file("."), - label_fusion_image=execution.output_file(output + "_LabelFusion.nii.gz"), - intensity_fusion_image=execution.output_file(output + "_IntensityFusion.nii.gz"), - label_posterior_probability_image=execution.output_file(output + "_LabelPosterior.nii.gz"), - atlas_voting_weight_image=execution.output_file(output + "_AtlasVoting.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_JOINT_TENSOR_FUSION_METADATA", - "AntsJointTensorFusionOutputs", - "ants_joint_tensor_fusion", -] diff --git a/python/src/niwrap/ants/ants_landmark_based_transform_initializer.py b/python/src/niwrap/ants/ants_landmark_based_transform_initializer.py deleted file mode 100644 index 02ff47e2e..000000000 --- a/python/src/niwrap/ants/ants_landmark_based_transform_initializer.py +++ /dev/null @@ -1,100 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_LANDMARK_BASED_TRANSFORM_INITIALIZER_METADATA = Metadata( - id="e680d25c4b1661ea27d0968828f088b5d76779fa.boutiques", - name="antsLandmarkBasedTransformInitializer", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsLandmarkBasedTransformInitializerOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_landmark_based_transform_initializer(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transform: OutputPathType - """The output file containing the initialized transform.""" - - -def ants_landmark_based_transform_initializer( - dimension: int, - fixed_image: InputPathType, - moving_image: InputPathType, - transform_type: typing.Literal["rigid", "affine", "bspline"], - output_transform: InputPathType, - mesh_size: str | None = None, - number_of_levels: int | None = None, - order: int | None = None, - enforce_stationary_boundaries: typing.Literal[0, 1] | None = None, - landmark_weights: InputPathType | None = None, - runner: Runner | None = None, -) -> AntsLandmarkBasedTransformInitializerOutputs: - """ - This tool initializes a transform between two images based on corresponding - landmarks. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimension: The dimensionality of the registration problem (e.g., 2 for\ - 2D, 3 for 3D). - fixed_image: The fixed image in the registration process. - moving_image: The moving image in the registration process. - transform_type: The type of transform to initialize. Options are\ - 'rigid', 'affine', or 'bspline'. - output_transform: The output transform file that will be created. - mesh_size: The mesh size for the B-spline transform, specified as\ - 'meshSize[0]xmeshSize[1]x...'. Default is '1x1x1'. - number_of_levels: Number of levels for multi-resolution fitting.\ - Default is 4. - order: The polynomial order of the B-spline transform. Default is 3. - enforce_stationary_boundaries: Enforces stationary boundaries for the\ - B-spline transform. Default is 1 (true). - landmark_weights: File containing landmark weights. Each row is either\ - 'label,labelWeight' or 'labelWeight'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsLandmarkBasedTransformInitializerOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_LANDMARK_BASED_TRANSFORM_INITIALIZER_METADATA) - cargs = [] - cargs.append("antsLandmarkBasedTransformInitializer") - cargs.append(str(dimension)) - cargs.append(execution.input_file(fixed_image)) - cargs.append(execution.input_file(moving_image)) - cargs.append(transform_type) - cargs.append(execution.input_file(output_transform)) - if mesh_size is not None: - cargs.append(mesh_size) - if number_of_levels is not None: - cargs.append(str(number_of_levels)) - if order is not None: - cargs.append(str(order)) - if enforce_stationary_boundaries is not None: - cargs.append(str(enforce_stationary_boundaries)) - if landmark_weights is not None: - cargs.append(execution.input_file(landmark_weights)) - ret = AntsLandmarkBasedTransformInitializerOutputs( - root=execution.output_file("."), - output_transform=execution.output_file(pathlib.Path(output_transform).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_LANDMARK_BASED_TRANSFORM_INITIALIZER_METADATA", - "AntsLandmarkBasedTransformInitializerOutputs", - "ants_landmark_based_transform_initializer", -] diff --git a/python/src/niwrap/ants/ants_motion_corr.py b/python/src/niwrap/ants/ants_motion_corr.py deleted file mode 100644 index caf38f1c4..000000000 --- a/python/src/niwrap/ants/ants_motion_corr.py +++ /dev/null @@ -1,186 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_MOTION_CORR_METADATA = Metadata( - id="101179d7b402b3245503ed337e9b9c5479b1f966.boutiques", - name="antsMotionCorr", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsMotionCorrOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_motion_corr(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transform_prefix: OutputPathType - """The output is the transformation matrix.""" - warped_image: OutputPathType - """The output is the warped moving image.""" - average_image_output: OutputPathType - """The output is the averaged image of the input time series.""" - - -def ants_motion_corr( - dimensionality: typing.Literal[2, 3] | None = None, - n_images: int | None = None, - metric: str | None = None, - use_fixed_reference_image: typing.Literal[0, 1] | None = None, - use_scales_estimator: bool = False, - transform: str | None = None, - iterations: str | None = None, - smoothing_sigmas: str | None = None, - shrink_factors: str | None = None, - output: str | None = None, - average_image: bool = False, - write_displacement: bool = False, - use_histogram_matching: typing.Literal[0, 1] | None = None, - random_seed: int | None = None, - interpolation: typing.Literal["Linear", "NearestNeighbor", "BSpline", "BlackmanWindowedSinc", "CosineWindowedSinc", "WelchWindowedSinc", "HammingWindowedSinc", "LanczosWindowedSinc"] | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsMotionCorrOutputs: - """ - ANTS Motion Correction application to perform motion correction on 4D time - series data. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - n_images: This option sets the number of images to use to construct the\ - template image. - metric: Metrics for registration: GC (global correlation), CC (ANTS\ - neighborhood cross correlation), MI (Mutual information), and Demons. - use_fixed_reference_image: Use a fixed reference image to correct all\ - volumes, instead of correcting each image to the prior volume in the\ - time series. - use_scales_estimator: Use the scale estimator to control optimization. - transform: Several transform options are available: Affine, Rigid,\ - GaussianDisplacementField, SyN. - iterations: Specify the number of iterations at each level. - smoothing_sigmas: Specify the sigma for smoothing at each level.\ - Smoothing may be specified in mm units or voxels with 'AxBxCmm' or\ - 'AxBxCvox'. No units implies voxels. - shrink_factors: Specify the shrink factor for the virtual domain\ - (typically the fixed image) at each level. - output: Specify the output transform prefix (output format is .nii.gz\ - ). Optionally, one can choose to warp the moving image to the fixed\ - space and, if the inverse transform exists, one can also output the\ - warped fixed image. - average_image: Average the input time series image. - write_displacement: Write the low-dimensional 3D transforms to a 4D\ - displacement field. - use_histogram_matching: Histogram match the moving images to the\ - reference image. - random_seed: Use a fixed seed for random number generation. - interpolation: Several interpolation options are available in ITK. The\ - above are available (default Linear). - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsMotionCorrOutputs`). - """ - if random_seed is not None and not (1 <= random_seed): - raise ValueError(f"'random_seed' must be greater than 1 <= x but was {random_seed}") - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_MOTION_CORR_METADATA) - cargs = [] - cargs.append("antsMotionCorr") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - if n_images is not None: - cargs.extend([ - "--n-images", - str(n_images) - ]) - if metric is not None: - cargs.extend([ - "--metric", - metric - ]) - if use_fixed_reference_image is not None: - cargs.extend([ - "--useFixedReferenceImage", - str(use_fixed_reference_image) - ]) - if use_scales_estimator: - cargs.append("--useScalesEstimator") - if transform is not None: - cargs.extend([ - "--transform", - transform - ]) - if iterations is not None: - cargs.extend([ - "--iterations", - iterations - ]) - if smoothing_sigmas is not None: - cargs.extend([ - "--smoothingSigmas", - smoothing_sigmas - ]) - if shrink_factors is not None: - cargs.extend([ - "--shrinkFactors", - shrink_factors - ]) - if output is not None: - cargs.extend([ - "--output", - output - ]) - if average_image: - cargs.append("--average-image") - if write_displacement: - cargs.append("--write-displacement") - if use_histogram_matching is not None: - cargs.extend([ - "--use-histogram-matching", - str(use_histogram_matching) - ]) - if random_seed is not None: - cargs.extend([ - "--random-seed", - str(random_seed) - ]) - if interpolation is not None: - cargs.extend([ - "--interpolation", - interpolation - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = AntsMotionCorrOutputs( - root=execution.output_file("."), - output_transform_prefix=execution.output_file("[OUTPUT_TRANSFORM_PREFIX]Affine.mat"), - warped_image=execution.output_file("[OUTPUT_TRANSFORM_PREFIX]Warped.nii.gz"), - average_image_output=execution.output_file("[OUTPUT_TRANSFORM_PREFIX]Average.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_MOTION_CORR_METADATA", - "AntsMotionCorrOutputs", - "ants_motion_corr", -] diff --git a/python/src/niwrap/ants/ants_motion_corr_diffusion_direction.py b/python/src/niwrap/ants/ants_motion_corr_diffusion_direction.py deleted file mode 100644 index 5aa4e6921..000000000 --- a/python/src/niwrap/ants/ants_motion_corr_diffusion_direction.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_MOTION_CORR_DIFFUSION_DIRECTION_METADATA = Metadata( - id="3f81491f1faf2e11f2fe0e69121f28544825a2d4.boutiques", - name="antsMotionCorrDiffusionDirection", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsMotionCorrDiffusionDirectionOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_motion_corr_diffusion_direction(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_scheme: OutputPathType - """The output file for corrected diffusion directions.""" - - -def ants_motion_corr_diffusion_direction( - scheme: InputPathType, - bvec: InputPathType, - physical: InputPathType, - moco: InputPathType, - output: str, - runner: Runner | None = None, -) -> AntsMotionCorrDiffusionDirectionOutputs: - """ - This tool adjusts the diffusion scheme for motion correction. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - scheme: Camino scheme file specify acquisition parameters. - bvec: bvec image specifying diffusion directions. - physical: 3D image in dwi space. - moco: Motion correction parameters from antsMotionCorr. - output: Specify the output file for corrected directions. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsMotionCorrDiffusionDirectionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_MOTION_CORR_DIFFUSION_DIRECTION_METADATA) - cargs = [] - cargs.append("antsMotionCorrDiffusionDirection") - cargs.extend([ - "-s", - execution.input_file(scheme) - ]) - cargs.extend([ - "-b", - execution.input_file(bvec) - ]) - cargs.extend([ - "-p", - execution.input_file(physical) - ]) - cargs.extend([ - "-m", - execution.input_file(moco) - ]) - cargs.extend([ - "-o", - output - ]) - ret = AntsMotionCorrDiffusionDirectionOutputs( - root=execution.output_file("."), - corrected_scheme=execution.output_file(output), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_MOTION_CORR_DIFFUSION_DIRECTION_METADATA", - "AntsMotionCorrDiffusionDirectionOutputs", - "ants_motion_corr_diffusion_direction", -] diff --git a/python/src/niwrap/ants/ants_motion_corr_stats.py b/python/src/niwrap/ants/ants_motion_corr_stats.py deleted file mode 100644 index 19a011125..000000000 --- a/python/src/niwrap/ants/ants_motion_corr_stats.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_MOTION_CORR_STATS_METADATA = Metadata( - id="d29996fec64fd395bafc8947a76eea2b5d1ba04c.boutiques", - name="antsMotionCorrStats", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsMotionCorrStatsOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_motion_corr_stats(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_csv: OutputPathType - """The corrected motion parameters.csv file.""" - - -def ants_motion_corr_stats( - mask: InputPathType, - moco_params: InputPathType, - output: InputPathType, - transform_index: int | None = None, - framewise: typing.Literal[0, 1] | None = None, - spatial_map: bool = False, - timeseries_displacement: bool = False, - runner: Runner | None = None, -) -> AntsMotionCorrStatsOutputs: - """ - Create summary measures of the parameters that are output by antsMotionCorr. - Currently only works for linear transforms. Outputs the mean and max - displacements for the voxels within a provided mask, at each time point. By - default the displacements are relative to the reference space, but the framewise - option may be used to provide displacements between consecutive time points. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - mask: Mask image - compute displacements within mask. - moco_params: Motion correction parameters from antsMotionCorr. - output: Specify the output file. - transform_index: Specify the index for a 3D transform to output. - framewise: Do framewise summary stats. - spatial_map: Output image of displacement magnitude. - timeseries_displacement: Output 4d time-series image of displacement\ - magnitude. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsMotionCorrStatsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_MOTION_CORR_STATS_METADATA) - cargs = [] - cargs.append("antsMotionCorrStats") - cargs.extend([ - "-x", - execution.input_file(mask) - ]) - cargs.extend([ - "-m", - execution.input_file(moco_params) - ]) - cargs.extend([ - "-o", - execution.input_file(output) - ]) - if transform_index is not None: - cargs.extend([ - "-t", - str(transform_index) - ]) - if framewise is not None: - cargs.extend([ - "-f", - str(framewise) - ]) - if spatial_map: - cargs.append("-s") - if timeseries_displacement: - cargs.append("-d") - ret = AntsMotionCorrStatsOutputs( - root=execution.output_file("."), - corrected_csv=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_MOTION_CORR_STATS_METADATA", - "AntsMotionCorrStatsOutputs", - "ants_motion_corr_stats", -] diff --git a/python/src/niwrap/ants/ants_multivariate_template_construction2_sh.py b/python/src/niwrap/ants/ants_multivariate_template_construction2_sh.py deleted file mode 100644 index 0f1de1c09..000000000 --- a/python/src/niwrap/ants/ants_multivariate_template_construction2_sh.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_MULTIVARIATE_TEMPLATE_CONSTRUCTION2_SH_METADATA = Metadata( - id="f693ac4ad31f1a6eadc3feb7c36e205aa70b2373.boutiques", - name="antsMultivariateTemplateConstruction2.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsMultivariateTemplateConstruction2ShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_multivariate_template_construction2_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - template: OutputPathType - """The output multivariate template.""" - - -def ants_multivariate_template_construction2_sh( - input_: str, - runner: Runner | None = None, -) -> AntsMultivariateTemplateConstruction2ShOutputs: - """ - The antsMultivariateTemplateConstruction2.sh script is part of the Advanced - Normalization Tools (ANTs) suite. It is used for constructing multivariate - templates. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_: Options for setting up and running the multivariate template\ - construction process. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsMultivariateTemplateConstruction2ShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_MULTIVARIATE_TEMPLATE_CONSTRUCTION2_SH_METADATA) - cargs = [] - cargs.append("antsMultivariateTemplateConstruction2.sh") - cargs.append(input_) - ret = AntsMultivariateTemplateConstruction2ShOutputs( - root=execution.output_file("."), - template=execution.output_file("Template.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_MULTIVARIATE_TEMPLATE_CONSTRUCTION2_SH_METADATA", - "AntsMultivariateTemplateConstruction2ShOutputs", - "ants_multivariate_template_construction2_sh", -] diff --git a/python/src/niwrap/ants/ants_neuroimaging_battery.py b/python/src/niwrap/ants/ants_neuroimaging_battery.py deleted file mode 100644 index 7e2ce9947..000000000 --- a/python/src/niwrap/ants/ants_neuroimaging_battery.py +++ /dev/null @@ -1,91 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_NEUROIMAGING_BATTERY_METADATA = Metadata( - id="8d5f7d9ec665c8a4728e1d76b9ae72be2a9a3489.boutiques", - name="antsNeuroimagingBattery", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsNeuroimagingBatteryOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_neuroimaging_battery(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transform: OutputPathType - """Output transform files.""" - - -def ants_neuroimaging_battery( - input_directory: str, - output_directory: str, - output_name: str, - anatomical_image: InputPathType, - anatomical_mask: InputPathType, - runner: Runner | None = None, -) -> AntsNeuroimagingBatteryOutputs: - """ - Align MR modalities to a common within-subject (and optional template) space. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_directory: Directory where to look for modality images. - output_directory: Directory where output goes (where\ - antsCorticalThickness output lives). - output_name: File prefix for outputs. - anatomical_image: Reference subject image (usually T1). - anatomical_mask: Mask of anatomical image, should contain cerebrum,\ - cerebellum, and brainstem. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsNeuroimagingBatteryOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_NEUROIMAGING_BATTERY_METADATA) - cargs = [] - cargs.append("antsNeuroimagingBattery.pl") - cargs.extend([ - "--input-directory", - input_directory - ]) - cargs.extend([ - "--output-directory", - output_directory - ]) - cargs.extend([ - "--output-name", - output_name - ]) - cargs.extend([ - "--anatomical", - execution.input_file(anatomical_image) - ]) - cargs.extend([ - "--anatomical-mask", - execution.input_file(anatomical_mask) - ]) - cargs.append("[OPTIONAL_INPUTS]") - ret = AntsNeuroimagingBatteryOutputs( - root=execution.output_file("."), - output_transform=execution.output_file(output_directory + "/" + output_name + ".*"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_NEUROIMAGING_BATTERY_METADATA", - "AntsNeuroimagingBatteryOutputs", - "ants_neuroimaging_battery", -] diff --git a/python/src/niwrap/ants/ants_registration.py b/python/src/niwrap/ants/ants_registration.py deleted file mode 100644 index e3c920fac..000000000 --- a/python/src/niwrap/ants/ants_registration.py +++ /dev/null @@ -1,1172 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_REGISTRATION_METADATA = Metadata( - id="4acaef29989a404d5d21fd8f132f21f4fc28563d.boutiques", - name="antsRegistration", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class AntsRegistrationInitialMovingTransform: - initial_moving_transform: InputPathType - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(execution.input_file(self.initial_moving_transform)) - return cargs - - -@dataclasses.dataclass -class AntsRegistrationInitialMovingTransformUseInverse: - initial_moving_transform: InputPathType - use_inverse: typing.Literal[0, 1] | None = None - """Use the inverse of the initial moving transform.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.use_inverse is not None: - cargs.append("[" + execution.input_file(self.initial_moving_transform) + "," + str(self.use_inverse) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationInitialMovingTransformInitializationFeature: - fixed_image: InputPathType - moving_image: InputPathType - initialization_feature: typing.Literal[0, 1, 2] - """Initialization feature. 0: Geometric center of images, 1: Image - intensities, 2: Origin of images""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("[" + execution.input_file(self.fixed_image) + "," + execution.input_file(self.moving_image) + "," + str(self.initialization_feature) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformRigid: - gradient_step: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Rigid[" + str(self.gradient_step) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformAffine: - gradient_step: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Affine[" + str(self.gradient_step) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformCompositeAffine: - gradient_step: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("CompositeAffine[" + str(self.gradient_step) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformSimilarity: - gradient_step: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Similarity[" + str(self.gradient_step) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformTranslation: - gradient_step: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Translation[" + str(self.gradient_step) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformBspline: - gradient_step: float - mesh_size_at_base_level: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("BSpline[" + str(self.gradient_step) + "," + str(self.mesh_size_at_base_level) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformGaussianDisplacementField: - gradient_step: float - update_field_variance_in_voxel_space: float - total_field_variance_in_voxel_space: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("GaussianDisplacementField[" + str(self.gradient_step) + "," + str(self.update_field_variance_in_voxel_space) + "," + str(self.total_field_variance_in_voxel_space) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformBsplineDisplacementField: - gradient_step: float - update_field_mesh_size_at_base_level: float - total_field_mesh_size_at_base_level: float | None = None - spline_order: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.total_field_mesh_size_at_base_level is not None or self.spline_order is not None: - cargs.append("BSplineDisplacementField[" + str(self.gradient_step) + "," + str(self.update_field_mesh_size_at_base_level) + "," + (str(self.total_field_mesh_size_at_base_level) if self.total_field_mesh_size_at_base_level is not None else "") + (str(self.spline_order) if self.spline_order is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformTimeVaryingVelocityField: - gradient_step: float - number_of_time_indices: float - update_field_variance_in_voxel_space: float - update_field_time_variance: float - total_field_variance_in_voxel_space: float - total_field_time_variance: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("TimeVaryingVelocityField[" + str(self.gradient_step) + "," + str(self.number_of_time_indices) + "," + str(self.update_field_variance_in_voxel_space) + "," + str(self.update_field_time_variance) + "," + str(self.total_field_variance_in_voxel_space) + "," + str(self.total_field_time_variance) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformTimeVaryingBsplineVelocityField: - gradient_step: float - velocity_field_mesh_size: float - number_of_time_point_samples: float | None = None - spline_order: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.number_of_time_point_samples is not None or self.spline_order is not None: - cargs.append("TimeVaryingBSplineVelocityField[" + str(self.gradient_step) + "," + str(self.velocity_field_mesh_size) + "," + (str(self.number_of_time_point_samples) if self.number_of_time_point_samples is not None else "") + "," + (str(self.spline_order) if self.spline_order is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformSyn: - gradient_step: float - update_field_variance_in_voxel_space: float - total_field_variance_in_voxel_space: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("SyN[" + str(self.gradient_step) + "," + str(self.update_field_variance_in_voxel_space) + "," + str(self.total_field_variance_in_voxel_space) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformBsplineSyn: - gradient_step: float - update_field_mesh_size_at_base_level: float - total_field_mesh_size_at_base_level: float | None = None - spline_order: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.total_field_mesh_size_at_base_level is not None or self.spline_order is not None: - cargs.append("BSplineSyN[" + str(self.gradient_step) + "," + str(self.update_field_mesh_size_at_base_level) + "," + (str(self.total_field_mesh_size_at_base_level) if self.total_field_mesh_size_at_base_level is not None else "") + "," + (str(self.spline_order) if self.spline_order is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformExponential: - gradient_step: float - update_field_variance_in_voxel_space: float - velocity_field_variance_in_voxel_space: float - number_of_integration_steps: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("Exponential[" + str(self.gradient_step) + "," + str(self.update_field_variance_in_voxel_space) + "," + str(self.velocity_field_variance_in_voxel_space) + "," + str(self.number_of_integration_steps) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationTransformBsplineExponential: - gradient_step: float - update_field_mesh_size_at_base_level: float - velocity_field_mesh_size_at_base_level: float | None = None - number_of_integration_steps: float | None = None - spline_order: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.velocity_field_mesh_size_at_base_level is not None or self.number_of_integration_steps is not None or self.spline_order is not None: - cargs.append("BSplineExponential[" + str(self.gradient_step) + "," + str(self.update_field_mesh_size_at_base_level) + "," + (str(self.velocity_field_mesh_size_at_base_level) if self.velocity_field_mesh_size_at_base_level is not None else "") + "," + (str(self.number_of_integration_steps) if self.number_of_integration_steps is not None else "") + "," + (str(self.spline_order) if self.spline_order is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricAntsNeighbourhoodCrossCorrelation: - fixed_image: str - moving_image: str - metric_weight: float - radius: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.radius is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("CC[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.radius) if self.radius is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricMutualInformation: - fixed_image: str - moving_image: str - metric_weight: float - number_of_bins: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.number_of_bins is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("MI[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.number_of_bins) if self.number_of_bins is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricMattes: - fixed_image: str - moving_image: str - metric_weight: float - number_of_bins: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.number_of_bins is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("Mattes[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.number_of_bins) if self.number_of_bins is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricMeanSquares: - fixed_image: str - moving_image: str - metric_weight: float - radius: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.radius is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("MeanSquares[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.radius) if self.radius is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricDemons: - fixed_image: str - moving_image: str - metric_weight: float - number_of_bins: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.number_of_bins is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("Demons[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.number_of_bins) if self.number_of_bins is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricGlobalCorrelation: - fixed_image: str - moving_image: str - metric_weight: float - radius: float | None = None - sampling_strategy: typing.Literal["None", "Regular", "Random"] | None = None - sampling_percentage: float | None = None - use_gradient_filter: typing.Literal["true", "false"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.radius is not None or self.sampling_strategy is not None or self.sampling_percentage is not None or self.use_gradient_filter is not None: - cargs.append("GC[" + self.fixed_image + "," + self.moving_image + "," + str(self.metric_weight) + "," + (str(self.radius) if self.radius is not None else "") + "," + (self.sampling_strategy if self.sampling_strategy is not None else "") + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.use_gradient_filter if self.use_gradient_filter is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricEuclideanIcp: - fixed_point_set: str - moving_point_set: str - metric_weight: float - sampling_percentage: float | None = None - boundary_points_only: typing.Literal["0"] | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.sampling_percentage is not None or self.boundary_points_only is not None: - cargs.append("ICP[" + self.fixed_point_set + "," + self.moving_point_set + "," + str(self.metric_weight) + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.boundary_points_only if self.boundary_points_only is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricPointSetExpectation: - metric_weight: float - point_set_sigma: float | None = None - sampling_percentage: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.point_set_sigma is not None or self.sampling_percentage is not None: - cargs.append("PSE[[FIXED_IMAGE],[MOVING_IMAGE]," + str(self.metric_weight) + "," + "," + (str(self.point_set_sigma) if self.point_set_sigma is not None else "") + "[SAMPLING_STRATEGY]" + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "[USE_GRADIENT_FILTER]]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricJensenHavrdaCharvetTsallis: - fixed_point_set: str - moving_point_set: str - metric_weight: float - sampling_percentage: float | None = None - boundary_points_only: typing.Literal["0"] | None = None - point_set_sigma: float | None = None - k_neighborhood: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - if sampling_percentage is not None and not (0 <= sampling_percentage <= 1): - raise ValueError(f"'sampling_percentage' must be between 0 <= x <= 1 but was {sampling_percentage}") - cargs = [] - if self.sampling_percentage is not None or self.boundary_points_only is not None or self.point_set_sigma is not None or self.k_neighborhood is not None: - cargs.append("JHCT[" + self.fixed_point_set + "," + self.moving_point_set + "," + str(self.metric_weight) + "," + (str(self.sampling_percentage) if self.sampling_percentage is not None else "") + "," + (self.boundary_points_only if self.boundary_points_only is not None else "") + "," + (str(self.point_set_sigma) if self.point_set_sigma is not None else "") + "," + (str(self.k_neighborhood) if self.k_neighborhood is not None else "") + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMetricIgdm: - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("IGDM[") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationConvergence: - """ - Convergence is determined from the number of iterations per level and is - determined by fitting a line to the normalized energy profile of the last N - iterations (where N is specified by the window size) and determining the - slope which is then compared with the convergence threshold. . - """ - convergence: str - convergence_threshold: float - convergence_window_size: int - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("[" + self.convergence + "," + str(self.convergence_threshold) + "," + str(self.convergence_window_size) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationStage: - """ - Stages of the registration process. - """ - transform: typing.Union[AntsRegistrationTransformRigid, AntsRegistrationTransformAffine, AntsRegistrationTransformCompositeAffine, AntsRegistrationTransformSimilarity, AntsRegistrationTransformTranslation, AntsRegistrationTransformBspline, AntsRegistrationTransformGaussianDisplacementField, AntsRegistrationTransformBsplineDisplacementField, AntsRegistrationTransformTimeVaryingVelocityField, AntsRegistrationTransformTimeVaryingBsplineVelocityField, AntsRegistrationTransformSyn, AntsRegistrationTransformBsplineSyn, AntsRegistrationTransformExponential, AntsRegistrationTransformBsplineExponential] - """Several transform options are available. The gradientStep or learningRate - characterizes the gradient descent optimization and is scaled appropriately - for each transform using the shift scales estimator. Subsequent parameters - are transform-specific and can be determined from the usage. For the - B-spline transforms one can also specify the smoothing in terms of spline - distance (i.e. knot spacing).""" - metric: typing.Union[AntsRegistrationMetricAntsNeighbourhoodCrossCorrelation, AntsRegistrationMetricMutualInformation, AntsRegistrationMetricMattes, AntsRegistrationMetricMeanSquares, AntsRegistrationMetricDemons, AntsRegistrationMetricGlobalCorrelation, AntsRegistrationMetricEuclideanIcp, AntsRegistrationMetricPointSetExpectation, AntsRegistrationMetricJensenHavrdaCharvetTsallis, AntsRegistrationMetricIgdm] - """These image metrics are available--- CC: ANTS neighborhood cross - correlation, MI: Mutual information, Demons: (Thirion), MeanSquares, and GC: - Global Correlation. The "metricWeight" variable is used to modulate the per - stage weighting of the metrics. The metrics can also employ a sampling - strategy defined by a sampling percentage. The sampling strategy defaults to - 'None' (aka a dense sampling of one sample per voxel), otherwise it defines - a point set over which to optimize the metric. The point set can be on a - regular lattice or a random lattice of points slightly perturbed to minimize - aliasing artifacts. samplingPercentage defines the fraction of points to - select from the domain. useGradientFilter specifies whether a - smoothingfilter is applied when estimating the metric gradient.In addition, - three point set metrics are available: Euclidean (ICP), Point-set - expectation (PSE), and Jensen-Havrda-Charvet-Tsallis (JHCT).""" - convergence: AntsRegistrationConvergence - """Convergence is determined from the number of iterations per level and is - determined by fitting a line to the normalized energy profile of the last N - iterations (where N is specified by the window size) and determining the - slope which is then compared with the convergence threshold. """ - smoothing_sigmas: str - """Specify the sigma of gaussian smoothing at each level. Units are given in - terms of voxels ('vox') or physical spacing ('mm'). Example usage is - '4x2x1mm' and '4x2x1vox' where no units implies voxel spacing.""" - shrink_factors: str - """Specify the shrink factor for the virtual domain (typically the fixed - image) at each level.""" - use_histogram_matching: typing.Literal[0, 1] | None = None - """Use histogram matching.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "--transform", - *self.transform.run(execution) - ]) - cargs.extend([ - "--metric", - *self.metric.run(execution) - ]) - cargs.extend([ - "--convergence", - *self.convergence.run(execution) - ]) - cargs.extend([ - "--smoothing-sigmas", - self.smoothing_sigmas - ]) - cargs.extend([ - "--shrink-factors", - self.shrink_factors - ]) - if self.use_histogram_matching is not None: - cargs.extend([ - "--use-histogram-matching", - str(self.use_histogram_matching) - ]) - return cargs - - -@dataclasses.dataclass -class AntsRegistrationWinsorizeImageIntensities: - """ - Winsorize data based on specified quantiles. - """ - lower_quantile: float - upper_quantile: float - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("[" + str(self.lower_quantile) + str(self.upper_quantile) + "]") - return cargs - - -@dataclasses.dataclass -class AntsRegistrationMasks: - """ - Image masks to limit voxels considered by the metric. Two options are - allowed for mask specification: 1) Either the user specifies a single mask - to be used for all stages or 2) the user specifies a mask for each stage. - With the latter one can select to which stages masks are applied by - supplying valid file names. If the file does not exist, a mask will not be - used for that stage. Note that we handle the fixed and moving masks - separately to enforce this constraint. - """ - fixed_mask: str | None = None - moving_mask: str | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.fixed_mask is not None or self.moving_mask is not None: - cargs.append("[" + (self.fixed_mask if self.fixed_mask is not None else "") + (self.moving_mask if self.moving_mask is not None else "") + "]") - return cargs - - -class AntsRegistrationOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_registration(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - generic_affine: OutputPathType | None - """The output is the generic affine transformation matrix.""" - inverse_warped: OutputPathType | None - """The output is the warped fixed image.""" - inverse_warp: OutputPathType | None - """The output is the inverse warp field.""" - warped: OutputPathType | None - """The output is the warped moving image.""" - warp: OutputPathType | None - """The output is the warp field.""" - - -def ants_registration( - stages: list[AntsRegistrationStage], - dimensionality: typing.Literal[2, 3, 4] | None = None, - output: str | None = None, - save_state: str | None = None, - restore_state: str | None = None, - write_composite_transform: typing.Literal[0, 1] | None = None, - print_similarity_measure_interval: int | None = None, - write_interval_volumes: int | None = None, - collapse_output_transforms: typing.Literal[1, 0] | None = None, - initialize_transforms_per_stage: typing.Literal[1, 0] | None = None, - interpolation: typing.Literal["Linear", "NearestNeighbor", "MultiLabel", "Gaussian", "BSpline", "CosineWindowedSinc", "WelchWindowedSinc", "HammingWindowedSinc", "LanczosWindowedSinc", "GenericLabel"] | None = None, - restrict_deformation: list[typing.Literal[0, 1]] | None = None, - initial_fixed_transform: str | None = None, - initial_moving_transform: typing.Union[AntsRegistrationInitialMovingTransform, AntsRegistrationInitialMovingTransformUseInverse, AntsRegistrationInitialMovingTransformInitializationFeature] | None = None, - winsorize_image_intensities: AntsRegistrationWinsorizeImageIntensities | None = None, - masks: AntsRegistrationMasks | None = None, - minc: typing.Literal[0, 1] | None = None, - random_seed: int | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AntsRegistrationOutputs: - """ - This program is a user-level registration application meant to utilize classes - in ITK v4.0 and later. The user can specify any number of "stages" where a stage - consists of a transform; an image metric; and iterations, shrink factors, and - smoothing sigmas for each level. Note that explicitly setting the - dimensionality, metric, transform, output, convergence, shrink-factors, and - smoothing-sigmas parameters is mandatory. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - stages: Stages of the registration process. - dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, we try to infer the\ - dimensionality from the input image. - output: Specify the output transform prefix (output format is .nii.gz\ - ). Optionally, one can choose to warp the moving image to the fixed\ - space and, if the inverse transform exists, one can also output the\ - warped fixed image. Note that only the images specified in the first\ - metric call are warped. Use antsApplyTransforms to warp other images\ - using the resultant transform(s). When a composite transform is not\ - specified, linear transforms are specified with a '.mat' suffix and\ - displacement fields with a 'Warp.nii.gz' suffix (and\ - 'InverseWarp.nii.gz', when applicable. In addition, for velocity-based\ - transforms, the full velocity field is written to file\ - ('VelocityField.nii.gz') as long as the collapse transforms flag is\ - turned off ('-z 0'). - save_state: Specify the output file for the current state of the\ - registration. The state file is written to an hdf5 composite file. It\ - is specially usefull if we want to save the current state of a SyN\ - registration to the disk, so we can load and restore that later to\ - continue the next registration process directly started from the last\ - saved state. The output file of this flag is the same as the\ - write-composite-transform, unless the last transform is a SyN\ - transform. In that case, the inverse displacement field of the SyN\ - transform is also added to the output composite transform. Again notice\ - that this file cannot be treated as a transform, and restore-state\ - option must be used to load the written file by this flag. - restore_state: Specify the initial state of the registration which get\ - immediately used to directly initialize the registration process. The\ - flag is mutually exclusive with other intialization flags.If this flag\ - is used, none of the initial-moving-transform and\ - initial-fixed-transform cannot be used. - write_composite_transform: Boolean specifying whether or not the\ - composite transform (and its inverse, if it exists) should be written\ - to an hdf5 composite file. This is false by default so that only the\ - transform for each stage is written to file. - print_similarity_measure_interval: Prints out the CC similarity metric\ - measure between the full-size input fixed and the transformed moving\ - images at each iteration a value of 0 (the default) indicates that the\ - full scale computation should not take placeany value greater than 0\ - represents the interval of full scale metric computation. - write_interval_volumes: Writes out the output volume at each iteration.\ - It helps to present the registration process as a short movie a value\ - of 0 (the default) indicates that this option should not take placeany\ - value greater than 0 represents the interval between the iterations\ - which outputs are written to the disk. - collapse_output_transforms: Collapse output transforms. Specifically,\ - enabling this option combines all adjacent transforms where possible.\ - All adjacent linear transforms are written to disk in the form of an\ - itk affine transform (called xxxGenericAffine.mat).\ - Similarly, all adjacent displacement field transforms are combined\ - when written to disk (e.g. xxxWarp.nii.gz and xxxInverseWarp.nii.gz\ - (if available)). Also, an output composite transform including the\ - collapsed transforms is written to the disk (called\ - outputCollapsed(Inverse)Composite). - initialize_transforms_per_stage: Initialize linear transforms from the\ - previous stage. By enabling this option, the current linear stage\ - transform is directly intialized from the previous stage's linear\ - transform; this allows multiple linear stages to be run where each\ - stage directly updates the estimated linear transform from the previous\ - stage. (e.g. Translation -> Rigid -> Affine). - interpolation: Several interpolation options are available in ITK.\ - These have all been made available. Currently the interpolator choice\ - is only used to warp (and possibly inverse warp) the final output\ - image(s). - restrict_deformation: This option allows the user to restrict the\ - optimization of the displacement field, translation, rigid or affine\ - transform on a per-component basis. For example, if one wants to limit\ - the deformation or rotation of 3-D volume to the first two dimensions,\ - this is possible by specifying a weight vector of '1x1x0' for a\ - deformation field or '1x1x0x1x1x0' for a rigid transformation.\ - Low-dimensional restriction only works if there are no preceding\ - transformations.All stages up to and including the desired stage must\ - have this option specified,even if they should not be restricted (in\ - which case specify 1x1x1...). - initial_fixed_transform: Specify the initial fixed transform(s) which\ - get immediately incorporated into the composite transform. The order of\ - the transforms is stack-esque in that the last transform specified on\ - the command line is the first to be applied. In addition to\ - initialization with ITK transforms, the user can perform an initial\ - translation alignment by specifying the fixed and moving images and\ - selecting an initialization feature. These features include using the\ - geometric center of the images (=0), the image intensities (=1), or the\ - origin of the images (=2). - initial_moving_transform: Specify the initial moving transform(s) which\ - get immediately incorporated into the composite transform. The order of\ - the transforms is stack-esque in that the last transform specified on\ - the command line is the first to be applied. In addition to\ - initialization with ITK transforms, the user can perform an initial\ - translation alignment by specifying the fixed and moving images and\ - selecting an initialization feature. These features include using the\ - geometric center of the images (=0), the image intensities (=1), or the\ - origin of the images (=2). - winsorize_image_intensities: Winsorize data based on specified\ - quantiles. - masks: Image masks to limit voxels considered by the metric. Two\ - options are allowed for mask specification: 1) Either the user\ - specifies a single mask to be used for all stages or 2) the user\ - specifies a mask for each stage. With the latter one can select to\ - which stages masks are applied by supplying valid file names. If the\ - file does not exist, a mask will not be used for that stage. Note that\ - we handle the fixed and moving masks separately to enforce this\ - constraint. - minc: Use MINC file formats for transformations. - random_seed: Random seed. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsRegistrationOutputs`). - """ - if write_interval_volumes is not None and not (0 <= write_interval_volumes): - raise ValueError(f"'write_interval_volumes' must be greater than 0 <= x but was {write_interval_volumes}") - if random_seed is not None and not (1 <= random_seed): - raise ValueError(f"'random_seed' must be greater than 1 <= x but was {random_seed}") - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_REGISTRATION_METADATA) - cargs = [] - cargs.append("antsRegistration") - if dimensionality is not None: - cargs.extend([ - "--dimensionality", - str(dimensionality) - ]) - if output is not None: - cargs.extend([ - "-o", - output - ]) - if save_state is not None: - cargs.extend([ - "-j", - save_state - ]) - if restore_state is not None: - cargs.extend([ - "-k", - restore_state - ]) - if write_composite_transform is not None: - cargs.extend([ - "-a", - str(write_composite_transform) - ]) - if print_similarity_measure_interval is not None: - cargs.extend([ - "-p", - str(print_similarity_measure_interval) - ]) - if write_interval_volumes is not None: - cargs.extend([ - "--write-interval-volumes", - str(write_interval_volumes) - ]) - if collapse_output_transforms is not None: - cargs.extend([ - "--collapse-output-transforms", - str(collapse_output_transforms) - ]) - if initialize_transforms_per_stage is not None: - cargs.extend([ - "-i", - str(initialize_transforms_per_stage) - ]) - if interpolation is not None: - cargs.extend([ - "--interpolation", - interpolation - ]) - if restrict_deformation is not None: - cargs.extend([ - "-g", - "x".join(map(str, restrict_deformation)) - ]) - if initial_fixed_transform is not None: - cargs.extend([ - "-q", - initial_fixed_transform - ]) - if initial_moving_transform is not None: - cargs.extend([ - "--initial-moving-transform", - *initial_moving_transform.run(execution) - ]) - cargs.extend([a for c in [s.run(execution) for s in stages] for a in c]) - if winsorize_image_intensities is not None: - cargs.extend([ - "--winsorize-image-intensities", - *winsorize_image_intensities.run(execution) - ]) - if masks is not None: - cargs.extend([ - "--masks", - *masks.run(execution) - ]) - if minc is not None: - cargs.extend([ - "--minc", - str(minc) - ]) - if random_seed is not None: - cargs.extend([ - "--random-seed", - str(random_seed) - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = AntsRegistrationOutputs( - root=execution.output_file("."), - generic_affine=execution.output_file(output + "0GenericAffine.mat") if (output is not None) else None, - inverse_warped=execution.output_file(output + "InverseWarped.nii.gz") if (output is not None) else None, - inverse_warp=execution.output_file(output + "1InverseWarp.nii.gz") if (output is not None) else None, - warped=execution.output_file(output + "Warped.nii.gz") if (output is not None) else None, - warp=execution.output_file(output + "1Warp.nii.gz") if (output is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_REGISTRATION_METADATA", - "AntsRegistrationConvergence", - "AntsRegistrationInitialMovingTransform", - "AntsRegistrationInitialMovingTransformInitializationFeature", - "AntsRegistrationInitialMovingTransformUseInverse", - "AntsRegistrationMasks", - "AntsRegistrationMetricAntsNeighbourhoodCrossCorrelation", - "AntsRegistrationMetricDemons", - "AntsRegistrationMetricEuclideanIcp", - "AntsRegistrationMetricGlobalCorrelation", - "AntsRegistrationMetricIgdm", - "AntsRegistrationMetricJensenHavrdaCharvetTsallis", - "AntsRegistrationMetricMattes", - "AntsRegistrationMetricMeanSquares", - "AntsRegistrationMetricMutualInformation", - "AntsRegistrationMetricPointSetExpectation", - "AntsRegistrationOutputs", - "AntsRegistrationStage", - "AntsRegistrationTransformAffine", - "AntsRegistrationTransformBspline", - "AntsRegistrationTransformBsplineDisplacementField", - "AntsRegistrationTransformBsplineExponential", - "AntsRegistrationTransformBsplineSyn", - "AntsRegistrationTransformCompositeAffine", - "AntsRegistrationTransformExponential", - "AntsRegistrationTransformGaussianDisplacementField", - "AntsRegistrationTransformRigid", - "AntsRegistrationTransformSimilarity", - "AntsRegistrationTransformSyn", - "AntsRegistrationTransformTimeVaryingBsplineVelocityField", - "AntsRegistrationTransformTimeVaryingVelocityField", - "AntsRegistrationTransformTranslation", - "AntsRegistrationWinsorizeImageIntensities", - "ants_registration", -] diff --git a/python/src/niwrap/ants/ants_registration_sy_n_sh.py b/python/src/niwrap/ants/ants_registration_sy_n_sh.py deleted file mode 100644 index f1b9aef33..000000000 --- a/python/src/niwrap/ants/ants_registration_sy_n_sh.py +++ /dev/null @@ -1,202 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_REGISTRATION_SY_N_SH_METADATA = Metadata( - id="029fb8014cb72b8e3e10e60f5b05a9adf14dc918.boutiques", - name="antsRegistrationSyN.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsRegistrationSyNShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_registration_sy_n_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - affine_transform: OutputPathType - """Affine transformation matrix for registration""" - inverse_warp: OutputPathType - """Inverse warp field for registration""" - forward_warp: OutputPathType - """Forward warp field for registration""" - - -def ants_registration_sy_n_sh( - image_dimension: typing.Literal[2, 3], - fixed_image: InputPathType, - moving_image: InputPathType, - output_prefix: str, - threads: int | None = None, - initial_transform: list[str] | None = None, - transform_type: typing.Literal["t", "r", "a", "s", "sr", "so", "b", "br", "bo"] | None = None, - radius: int | None = None, - spline_distance: int | None = None, - gradient_step: float | None = None, - masks: str | None = None, - precision_type: typing.Literal["f", "d"] | None = None, - use_histogram_matching: typing.Literal[0, 1] | None = None, - use_repro_mode: typing.Literal[0, 1] | None = None, - collapse_output_transforms: typing.Literal[0, 1] | None = None, - random_seed: int | None = None, - runner: Runner | None = None, -) -> AntsRegistrationSyNShOutputs: - """ - Script for simplified symmetric image registration using ANTs. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Image dimension: 2 or 3 (for 2 or 3-dimensional\ - registration of a single volume). - fixed_image: Fixed image(s) or source image(s) or reference image(s). - moving_image: Moving image(s) or target image(s). - output_prefix: A prefix that is prepended to all output files. - threads: Number of threads (default =\ - ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS if defined, otherwise 1). - initial_transform: Initial transform(s) --- order specified on the\ - command line matters. - transform_type: Transform type (default = 's'). Options:\ - - t: translation (1 stage)\ - - r: rigid (1 stage)\ - - a: rigid + affine (2 stages)\ - - s: rigid + affine + deformable syn (3 stages)\ - - sr: rigid + deformable syn (2 stages)\ - - so: deformable syn only (1 stage)\ - - b: rigid + affine + deformable b-spline syn (3 stages)\ - - br: rigid + deformable b-spline syn (2 stages)\ - - bo: deformable b-spline syn only (1 stage). - radius: Radius for cross correlation metric used during SyN stage\ - (default = 4). - spline_distance: Spline distance for deformable B-spline SyN transform\ - (default = 26). - gradient_step: Gradient step size for SyN and B-spline SyN (default =\ - 0.1). - masks: Mask(s) for the fixed image space, or for the fixed and moving\ - image space in the format 'fixedMask,MovingMask'. Use -x once to\ - specify mask(s) to be used for all stages or use -x for each 'stage'\ - (cf -t option). If no mask is to be used for a particular stage, the\ - keyword 'NULL' should be used in place of file names. - precision_type: Precision type (default = 'd'). Options:\ - - f: float\ - - d: double. - use_histogram_matching: Use histogram matching (default = 0). Options:\ - - 0: false\ - - 1: true. - use_repro_mode: Use 'repro' mode for exact reproducibility of output.\ - Uses GC metric for linear stages and a fixed random seed (default = 0).\ - Options:\ - - 0: false\ - - 1: true. - collapse_output_transforms: Collapse output transforms (default = 1).\ - Options:\ - - 0: false\ - - 1: true. - random_seed: Fix random seed to an int value. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsRegistrationSyNShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_REGISTRATION_SY_N_SH_METADATA) - cargs = [] - cargs.append("antsRegistrationSyN.sh") - cargs.extend([ - "-d", - str(image_dimension) - ]) - cargs.extend([ - "-f", - execution.input_file(fixed_image) - ]) - cargs.extend([ - "-m", - execution.input_file(moving_image) - ]) - cargs.extend([ - "-o", - output_prefix - ]) - if threads is not None: - cargs.extend([ - "-n", - str(threads) - ]) - if initial_transform is not None: - cargs.extend([ - "-i", - "[" + ",".join(initial_transform) + "]" - ]) - if transform_type is not None: - cargs.extend([ - "-t", - transform_type - ]) - if radius is not None: - cargs.extend([ - "-r", - str(radius) - ]) - if spline_distance is not None: - cargs.extend([ - "-s", - str(spline_distance) - ]) - if gradient_step is not None: - cargs.extend([ - "-g", - str(gradient_step) - ]) - if masks is not None: - cargs.extend([ - "-x", - masks - ]) - if precision_type is not None: - cargs.extend([ - "-p", - precision_type - ]) - if use_histogram_matching is not None: - cargs.extend([ - "-j", - str(use_histogram_matching) - ]) - if use_repro_mode is not None: - cargs.extend([ - "-y", - str(use_repro_mode) - ]) - if collapse_output_transforms is not None: - cargs.extend([ - "-z", - str(collapse_output_transforms) - ]) - if random_seed is not None: - cargs.extend([ - "-e", - str(random_seed) - ]) - ret = AntsRegistrationSyNShOutputs( - root=execution.output_file("."), - affine_transform=execution.output_file(output_prefix + "0GenericAffine.mat"), - inverse_warp=execution.output_file(output_prefix + "1InverseWarp.nii.gz"), - forward_warp=execution.output_file(output_prefix + "1Warp.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_REGISTRATION_SY_N_SH_METADATA", - "AntsRegistrationSyNShOutputs", - "ants_registration_sy_n_sh", -] diff --git a/python/src/niwrap/ants/ants_registration_sy_nquick_sh.py b/python/src/niwrap/ants/ants_registration_sy_nquick_sh.py deleted file mode 100644 index 8aa929da0..000000000 --- a/python/src/niwrap/ants/ants_registration_sy_nquick_sh.py +++ /dev/null @@ -1,101 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_REGISTRATION_SY_NQUICK_SH_METADATA = Metadata( - id="535407e1c874099f70bf4e9fb2487258a6d8d0ad.boutiques", - name="antsRegistrationSyNQuick.sh", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsRegistrationSyNquickShOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_registration_sy_nquick_sh(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_transform: OutputPathType - """Affine transformation matrix resulting from registration.""" - output_warp: OutputPathType - """Warp field resulting from the registration.""" - output_inverse_warp: OutputPathType - """Inverse warp field resulting from the registration.""" - output_warped_image: OutputPathType - """Warped moving image.""" - - -def ants_registration_sy_nquick_sh( - dimensionality: typing.Literal[2, 3], - fixed_image: InputPathType, - moving_image: InputPathType, - output_prefix: str, - transform_type: typing.Literal["s", "b"] | None = None, - runner: Runner | None = None, -) -> AntsRegistrationSyNquickShOutputs: - """ - A script to quickly compute a SyN-based registration between two images using - ANTS. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimensionality: Dimensionality of the images (2 or 3). - fixed_image: Fixed image to which the moving image is registered. - moving_image: Moving image that is registered to the fixed image. - output_prefix: Prefix for the output files. - transform_type: Type of transform: 's' for SyN, 'b' for B-spline SyN.\ - Default is 's'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsRegistrationSyNquickShOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_REGISTRATION_SY_NQUICK_SH_METADATA) - cargs = [] - cargs.append("antsRegistrationSyNQuick.sh") - cargs.append("-d") - cargs.extend([ - "-d", - str(dimensionality) - ]) - cargs.append("-f") - cargs.extend([ - "-f", - execution.input_file(fixed_image) - ]) - cargs.append("-m") - cargs.extend([ - "-m", - execution.input_file(moving_image) - ]) - cargs.append("-o") - cargs.extend([ - "-o", - output_prefix - ]) - if transform_type is not None: - cargs.append(transform_type) - ret = AntsRegistrationSyNquickShOutputs( - root=execution.output_file("."), - output_transform=execution.output_file(output_prefix + "0GenericAffine.mat"), - output_warp=execution.output_file(output_prefix + "1Warp.nii.gz"), - output_inverse_warp=execution.output_file(output_prefix + "1InverseWarp.nii.gz"), - output_warped_image=execution.output_file(output_prefix + "Warped.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_REGISTRATION_SY_NQUICK_SH_METADATA", - "AntsRegistrationSyNquickShOutputs", - "ants_registration_sy_nquick_sh", -] diff --git a/python/src/niwrap/ants/ants_slice_regularized_registration.py b/python/src/niwrap/ants/ants_slice_regularized_registration.py deleted file mode 100644 index 36ac0288e..000000000 --- a/python/src/niwrap/ants/ants_slice_regularized_registration.py +++ /dev/null @@ -1,139 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_SLICE_REGULARIZED_REGISTRATION_METADATA = Metadata( - id="f5c4948fa2560385a828a453a54af7e3a4ab4be7.boutiques", - name="antsSliceRegularizedRegistration", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsSliceRegularizedRegistrationOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_slice_regularized_registration(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - polynomial_fit: OutputPathType - """Output is the polynomial fit to Tx & Ty.""" - transformed_image: OutputPathType - """Output is the transformed image.""" - - -def ants_slice_regularized_registration( - polydegree: int, - output: str, - metric: str, - transform: str, - iterations: str, - shrink_factors: str, - smoothing_sigmas: str, - mask: InputPathType | None = None, - interpolation: typing.Literal["Linear", "NearestNeighbor", "MultiLabel", "Gaussian", "BSpline", "CosineWindowedSinc", "WelchWindowedSinc", "HammingWindowedSinc", "LanczosWindowedSinc", "GenericLabel"] | None = None, - verbose: typing.Literal[0] | None = None, - runner: Runner | None = None, -) -> AntsSliceRegularizedRegistrationOutputs: - """ - This program is a user-level application for slice-by-slice translation - registration. Results are regularized in z using polynomial regression. The - program is targeted at spinal cord MRI. Only one stage is supported where a - stage consists of a transform; an image metric; and iterations, shrink factors, - and smoothing sigmas for each level. Specialized for 3D data: fixed image is 3D, - moving image is 3D. Registration is performed slice-by-slice then regularized in - z. The parameter -p controls the polynomial degree. -p 0 means no - regularization. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - polydegree: Degree of polynomial up to zDimension-2. Controls the\ - polynomial degree. 0 means no regularization. - output: Specify the output transform prefix (output format is .nii.gz).\ - Optionally, one can choose to warp the moving image to the fixed space,\ - and if the inverse transform exists, one can also output the warped\ - fixed image. - metric: Four image metrics are available: GC: global correlation, CC:\ - ANTS neighborhood cross correlation, MI: Mutual information, and\ - MeanSquares: mean-squares intensity difference. - transform: Several transform options are available. The gradientStep or\ - learningRate characterizes the gradient descent optimization. - iterations: Specify the number of iterations at each level. - shrink_factors: Specify the shrink factor for the virtual domain\ - (typically the fixed image) at each level. - smoothing_sigmas: Specify the amount of smoothing at each level. - mask: Fixed image mask to limit voxels considered by the metric. - interpolation: Several interpolation options are available in ITK. - verbose: Verbose option. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsSliceRegularizedRegistrationOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_SLICE_REGULARIZED_REGISTRATION_METADATA) - cargs = [] - cargs.append("antsSliceRegularizedRegistration") - cargs.extend([ - "-p", - str(polydegree) - ]) - cargs.extend([ - "-o", - output - ]) - cargs.extend([ - "-m", - metric - ]) - cargs.extend([ - "-t", - transform - ]) - cargs.extend([ - "-i", - iterations - ]) - cargs.extend([ - "-f", - shrink_factors - ]) - cargs.extend([ - "-s", - smoothing_sigmas - ]) - if mask is not None: - cargs.extend([ - "-x", - execution.input_file(mask) - ]) - if interpolation is not None: - cargs.extend([ - "-n", - interpolation - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = AntsSliceRegularizedRegistrationOutputs( - root=execution.output_file("."), - polynomial_fit=execution.output_file("[OUTPUT_PREFIX]TxTy_poly.csv"), - transformed_image=execution.output_file("[OUTPUT_PREFIX].nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_SLICE_REGULARIZED_REGISTRATION_METADATA", - "AntsSliceRegularizedRegistrationOutputs", - "ants_slice_regularized_registration", -] diff --git a/python/src/niwrap/ants/ants_transform_info.py b/python/src/niwrap/ants/ants_transform_info.py deleted file mode 100644 index d5ea4c178..000000000 --- a/python/src/niwrap/ants/ants_transform_info.py +++ /dev/null @@ -1,66 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTS_TRANSFORM_INFO_METADATA = Metadata( - id="86ecedc218eb7fb64f3c1c30b997395d9f5005ca.boutiques", - name="antsTransformInfo", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsTransformInfoOutputs(typing.NamedTuple): - """ - Output object returned when calling `ants_transform_info(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_info: OutputPathType - """Information of the provided transform file.""" - - -def ants_transform_info( - transform_file: InputPathType, - runner: Runner | None = None, -) -> AntsTransformInfoOutputs: - """ - Provide information about an ITK transform file. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - transform_file: The transform file to read. Supported formats include\ - HDF5, MINC, Matlab, and Txt. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsTransformInfoOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTS_TRANSFORM_INFO_METADATA) - cargs = [] - cargs.append("antsTransformInfo") - cargs.append("--file") - cargs.extend([ - "--file", - execution.input_file(transform_file) - ]) - ret = AntsTransformInfoOutputs( - root=execution.output_file("."), - output_info=execution.output_file("transform_info.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTS_TRANSFORM_INFO_METADATA", - "AntsTransformInfoOutputs", - "ants_transform_info", -] diff --git a/python/src/niwrap/ants/antsintegrate_vector_field.py b/python/src/niwrap/ants/antsintegrate_vector_field.py deleted file mode 100644 index 1284e2890..000000000 --- a/python/src/niwrap/ants/antsintegrate_vector_field.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTSINTEGRATE_VECTOR_FIELD_METADATA = Metadata( - id="25eaf01e25105beba3ae7eb2187714401340f8d4.boutiques", - name="ANTSIntegrateVectorField", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsintegrateVectorFieldOutputs(typing.NamedTuple): - """ - Output object returned when calling `antsintegrate_vector_field(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - fibers_out_vtk: OutputPathType - """The output is the fibers as a VTK text file.""" - length_image_out_nii: OutputPathType - """The output is the length image.""" - - -def antsintegrate_vector_field( - vector_field_input: InputPathType, - roi_mask_input: InputPathType, - fibers_output: str, - length_image_output: str, - runner: Runner | None = None, -) -> AntsintegrateVectorFieldOutputs: - """ - This tool integrates a vector field, where vectors are voxels, using a region of - interest (ROI) mask. The ROI mask controls where the integration is performed - and specifies the starting point region. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - vector_field_input: Input vector field image (e.g., VecImageIN.nii.gz),\ - where vectors are voxels. - roi_mask_input: Input ROI mask image (e.g., ROIMaskIN.nii.gz), an\ - integer image controlling where the integration is performed. - fibers_output: Output VTK text file for fibers (e.g., FibersOUT.vtk). - length_image_output: Output length image (e.g., LengthImageOUT.nii.gz). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsintegrateVectorFieldOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTSINTEGRATE_VECTOR_FIELD_METADATA) - cargs = [] - cargs.append("ANTSIntegrateVectorField") - cargs.append(execution.input_file(vector_field_input)) - cargs.append(execution.input_file(roi_mask_input)) - cargs.append(fibers_output) - cargs.append(length_image_output) - ret = AntsintegrateVectorFieldOutputs( - root=execution.output_file("."), - fibers_out_vtk=execution.output_file(fibers_output), - length_image_out_nii=execution.output_file(length_image_output), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTSINTEGRATE_VECTOR_FIELD_METADATA", - "AntsintegrateVectorFieldOutputs", - "antsintegrate_vector_field", -] diff --git a/python/src/niwrap/ants/antsjacobian.py b/python/src/niwrap/ants/antsjacobian.py deleted file mode 100644 index 53a61d31b..000000000 --- a/python/src/niwrap/ants/antsjacobian.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTSJACOBIAN_METADATA = Metadata( - id="4c1495ce17166625b172b3fbe727bd30b17f079f.boutiques", - name="ANTSJacobian", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsjacobianOutputs(typing.NamedTuple): - """ - Output object returned when calling `antsjacobian(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - jacobian_output: OutputPathType - """Output file containing the Jacobian determinant information.""" - - -def antsjacobian( - imagedim: int, - gwarp: InputPathType, - outfile: str, - uselog: int, - maskfn: InputPathType, - normbytotalbool: int, - projectionvector: str | None = None, - runner: Runner | None = None, -) -> AntsjacobianOutputs: - """ - Calculate the Jacobian determinant of a transformation using ANTs. WARNING: - ANTSJacobian may not be working correctly; see CreateJacobianDeterminantImage - for an alternative method. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - imagedim: The dimensionality of the input image. - gwarp: The input warp image. - outfile: The prefix for the output files. - uselog: Whether to use logarithm in computation. - maskfn: Mask file used in the computation. - normbytotalbool: Normalize the Jacobian by the total in the mask. Use\ - this to adjust for head size. - projectionvector: Projects the warp along the specified direction. Do\ - not add this option if no projection is desired. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsjacobianOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTSJACOBIAN_METADATA) - cargs = [] - cargs.append("ANTSJacobian") - cargs.append(str(imagedim)) - cargs.append(execution.input_file(gwarp)) - cargs.append(outfile) - cargs.append(str(uselog)) - cargs.append(execution.input_file(maskfn)) - cargs.append(str(normbytotalbool)) - if projectionvector is not None: - cargs.append(projectionvector) - ret = AntsjacobianOutputs( - root=execution.output_file("."), - jacobian_output=execution.output_file(outfile + "Jacobian.nii.gz"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTSJACOBIAN_METADATA", - "AntsjacobianOutputs", - "antsjacobian", -] diff --git a/python/src/niwrap/ants/antsuse_deformation_field_to_get_affine_transform.py b/python/src/niwrap/ants/antsuse_deformation_field_to_get_affine_transform.py deleted file mode 100644 index a34592f99..000000000 --- a/python/src/niwrap/ants/antsuse_deformation_field_to_get_affine_transform.py +++ /dev/null @@ -1,81 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTSUSE_DEFORMATION_FIELD_TO_GET_AFFINE_TRANSFORM_METADATA = Metadata( - id="a114d5c9bfbab1242b558e6ff3e44480841f6e38.boutiques", - name="ANTSUseDeformationFieldToGetAffineTransform", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsuseDeformationFieldToGetAffineTransformOutputs(typing.NamedTuple): - """ - Output object returned when calling `antsuse_deformation_field_to_get_affine_transform(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - out_affine_txt: OutputPathType - """The output is the affine transformation matrix file.""" - - -def antsuse_deformation_field_to_get_affine_transform( - deformation_field: InputPathType, - load_ratio: float, - transform_type: typing.Literal["rigid", "affine"], - output_affine: str, - mask: InputPathType | None = None, - runner: Runner | None = None, -) -> AntsuseDeformationFieldToGetAffineTransformOutputs: - """ - Extracts an affine transform from a deformation field. The input deformation - field is expected to be in the same physical space as the images you want to - transform. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - deformation_field: The input deformation field in NIfTI format (e.g.,\ - zzzWarp.nii.gz). - load_ratio: Ratio of points to be loaded from deformation field to save\ - memory (ex: 0.01). - transform_type: Type of transform to be extracted. Can be 'rigid' or\ - 'affine'. - output_affine: The output file where the affine transform will be saved\ - (e.g., OutAffine.txt). - mask: Optional mask file defining the region from which points will be\ - selected. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsuseDeformationFieldToGetAffineTransformOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTSUSE_DEFORMATION_FIELD_TO_GET_AFFINE_TRANSFORM_METADATA) - cargs = [] - cargs.append("ANTSUseDeformationFieldToGetAffineTransform") - cargs.append(execution.input_file(deformation_field)) - cargs.append(str(load_ratio)) - cargs.append(transform_type) - cargs.append(output_affine) - if mask is not None: - cargs.append(execution.input_file(mask)) - ret = AntsuseDeformationFieldToGetAffineTransformOutputs( - root=execution.output_file("."), - out_affine_txt=execution.output_file(output_affine), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTSUSE_DEFORMATION_FIELD_TO_GET_AFFINE_TRANSFORM_METADATA", - "AntsuseDeformationFieldToGetAffineTransformOutputs", - "antsuse_deformation_field_to_get_affine_transform", -] diff --git a/python/src/niwrap/ants/antsuse_landmark_images_to_get_affine_transform.py b/python/src/niwrap/ants/antsuse_landmark_images_to_get_affine_transform.py deleted file mode 100644 index 0c1fc84a2..000000000 --- a/python/src/niwrap/ants/antsuse_landmark_images_to_get_affine_transform.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTSUSE_LANDMARK_IMAGES_TO_GET_AFFINE_TRANSFORM_METADATA = Metadata( - id="c11dd7c0d9840d40017d52a654120cd6141ec439.boutiques", - name="ANTSUseLandmarkImagesToGetAffineTransform", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsuseLandmarkImagesToGetAffineTransformOutputs(typing.NamedTuple): - """ - Output object returned when calling `antsuse_landmark_images_to_get_affine_transform(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - affine_transform_matrix: OutputPathType - """The output is the affine transformation matrix file.""" - - -def antsuse_landmark_images_to_get_affine_transform( - fixed_image: InputPathType, - moving_image: InputPathType, - transform_type: typing.Literal["rigid", "affine"], - output_affine: str, - runner: Runner | None = None, -) -> AntsuseLandmarkImagesToGetAffineTransformOutputs: - """ - This tool computes an affine transform (rigid or affine) from labeled landmark - images. It requires input images to be N-ary, in the same physical space as the - images you want to register, and to have the same landmark points defined within - them. Landmarks are defined from the center of mass of the labels in the input - images. ITK-snap can be used to generate the label images. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - fixed_image: The fixed image containing labeled landmarks (N-ary\ - image). - moving_image: The moving image containing labeled landmarks (N-ary\ - image). - transform_type: Type of transform to compute: 'rigid' or 'affine'. - output_affine: The output file for the affine transform matrix (e.g.,\ - OutAffine.txt). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsuseLandmarkImagesToGetAffineTransformOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTSUSE_LANDMARK_IMAGES_TO_GET_AFFINE_TRANSFORM_METADATA) - cargs = [] - cargs.append("ANTSUseLandmarkImagesToGetAffineTransform") - cargs.append(execution.input_file(fixed_image)) - cargs.append(execution.input_file(moving_image)) - cargs.append(transform_type) - cargs.append(output_affine) - ret = AntsuseLandmarkImagesToGetAffineTransformOutputs( - root=execution.output_file("."), - affine_transform_matrix=execution.output_file(output_affine), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTSUSE_LANDMARK_IMAGES_TO_GET_AFFINE_TRANSFORM_METADATA", - "AntsuseLandmarkImagesToGetAffineTransformOutputs", - "antsuse_landmark_images_to_get_affine_transform", -] diff --git a/python/src/niwrap/ants/antsuse_landmark_images_to_get_bspline_displacement_field.py b/python/src/niwrap/ants/antsuse_landmark_images_to_get_bspline_displacement_field.py deleted file mode 100644 index 812706118..000000000 --- a/python/src/niwrap/ants/antsuse_landmark_images_to_get_bspline_displacement_field.py +++ /dev/null @@ -1,97 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ANTSUSE_LANDMARK_IMAGES_TO_GET_BSPLINE_DISPLACEMENT_FIELD_METADATA = Metadata( - id="7af4a9a784989ddd8ff76f3225c25b7355e86a75.boutiques", - name="ANTSUseLandmarkImagesToGetBSplineDisplacementField", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AntsuseLandmarkImagesToGetBsplineDisplacementFieldOutputs(typing.NamedTuple): - """ - Output object returned when calling `antsuse_landmark_images_to_get_bspline_displacement_field(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - displacement_field: OutputPathType - """The resultant displacement field for the registration process.""" - - -def antsuse_landmark_images_to_get_bspline_displacement_field( - fixed_image_with_labeled_landmarks: InputPathType, - moving_image_with_labeled_landmarks: InputPathType, - output_displacement_field: str, - mesh_size: str, - number_of_levels: int, - order: int | None = 3, - enforce_stationary_boundaries: int | None = 1, - landmark_weights: InputPathType | None = None, - runner: Runner | None = None, -) -> AntsuseLandmarkImagesToGetBsplineDisplacementFieldOutputs: - """ - We expect the input images to be (1) N-ary (2) in the same physical space as the - images you want to register and (3) to have the same landmark points defined - within them. Landmarks will be defined from the center of mass of the labels in - the input images. You can use ITK-snap to generate the label images. The - optional landmarks weights are read from a text file where each row is either: - "label,labelWeight" or "labelWeight". If the latter format is used, the label - weights are assumed to be arranged in ascending order by label. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - fixed_image_with_labeled_landmarks: The fixed image with labeled\ - landmarks. - moving_image_with_labeled_landmarks: The moving image with labeled\ - landmarks. - output_displacement_field: The output displacement field file. - mesh_size: The mesh size specified as meshSize[0]xmeshSize[1]x... - number_of_levels: The number of levels in the B-spline hierarchy. - order: The order of the B-spline (default is 3). - enforce_stationary_boundaries: Whether to enforce stationary boundaries\ - (default is 1). - landmark_weights: Optional text file containing landmark weights. Each\ - row is either "label,labelWeight" or "labelWeight". If the latter\ - format is used, the weights are assumed to be arranged in ascending\ - order by label. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AntsuseLandmarkImagesToGetBsplineDisplacementFieldOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ANTSUSE_LANDMARK_IMAGES_TO_GET_BSPLINE_DISPLACEMENT_FIELD_METADATA) - cargs = [] - cargs.append("ANTSUseLandmarkImagesToGetBSplineDisplacementField") - cargs.append(execution.input_file(fixed_image_with_labeled_landmarks)) - cargs.append(execution.input_file(moving_image_with_labeled_landmarks)) - cargs.append(output_displacement_field) - cargs.append(mesh_size) - cargs.append(str(number_of_levels)) - if order is not None: - cargs.append(str(order)) - if enforce_stationary_boundaries is not None: - cargs.append(str(enforce_stationary_boundaries)) - if landmark_weights is not None: - cargs.append(execution.input_file(landmark_weights)) - ret = AntsuseLandmarkImagesToGetBsplineDisplacementFieldOutputs( - root=execution.output_file("."), - displacement_field=execution.output_file(output_displacement_field), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ANTSUSE_LANDMARK_IMAGES_TO_GET_BSPLINE_DISPLACEMENT_FIELD_METADATA", - "AntsuseLandmarkImagesToGetBsplineDisplacementFieldOutputs", - "antsuse_landmark_images_to_get_bspline_displacement_field", -] diff --git a/python/src/niwrap/ants/atropos.py b/python/src/niwrap/ants/atropos.py deleted file mode 100644 index 4d04e5656..000000000 --- a/python/src/niwrap/ants/atropos.py +++ /dev/null @@ -1,215 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -ATROPOS_METADATA = Metadata( - id="4530aeaa8993b5f6c6337cb784311667ed8f0bbf.boutiques", - name="Atropos", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class AtroposOutputs(typing.NamedTuple): - """ - Output object returned when calling `atropos(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - classified_image: OutputPathType - """The output labeled image with assigned labels for each voxel in the - masked region.""" - posterior_probability_images: OutputPathType - """Output posterior probability images in specified format.""" - - -def atropos( - intensity_image: str, - initialization: str, - mask_image: InputPathType, - convergence: str, - likelihood_model: str, - output: str, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - bspline: str | None = None, - partial_volume_label_set: str | None = None, - use_partial_volume_likelihoods: typing.Literal[0, 1] | None = None, - posterior_formulation: str | None = None, - mrf: str | None = None, - icm: str | None = None, - use_random_seed: typing.Literal[0, 1] | None = None, - minimize_memory_usage: typing.Literal[0, 1] | None = None, - winsorize_outliers: str | None = None, - use_euclidean_distance: typing.Literal[0, 1] | None = None, - label_propagation: str | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> AtroposOutputs: - """ - Atropos is a finite mixture modeling (FMM) segmentation approach that allows for - prior constraints including a prior label image, prior probability images, - and/or an MRF prior to enforce spatial smoothing of the labels. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - intensity_image: One or more scalar images is specified for\ - segmentation. For scenarios with no prior information, the first scalar\ - image is used to order labelings by intensity. The optional adaptive\ - smoothing weight is applicable with prior images, specified between\ - [0,1]. - initialization: Initialize the FMM parameters. options include Random,\ - Otsu, KMeans, PriorProbabilityImages, and PriorLabelImage. - mask_image: The required image mask defines the region to be labeled by\ - Atropos. - convergence: Determine convergence based on mean maximum posterior\ - probability over region of interest. - likelihood_model: Specify parametric or non-parametric likelihood\ - model. Options include Gaussian, HistogramParzenWindows,\ - ManifoldParzenWindows, among others. - output: Output labeled image and optionally posterior probability\ - images. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, Atropos tries to infer\ - the dimensionality from the first input image. - bspline: Parameters for B-Spline. Adaptive smoothing is applied to\ - intensity images if smoothing weights > 0. - partial_volume_label_set: Model mixtures of classes within single\ - voxels. Specify labels for each partial volume class. - use_partial_volume_likelihoods: Whether to use partial volume\ - likelihoods. A value of 1 considers the partial volume class separate\ - from tissue classes. - posterior_formulation: Specify posterior probability formulation.\ - Options are Socrates, Plato, Aristotle, or Sigmoid. - mrf: Markov Random Field parameters to enforce spatial constraints on\ - segmentation. - icm: ICM (Iterated Conditional Modes) parameters for asynchronous\ - updating. - use_random_seed: Initialize with a random seed or a constant seed\ - number. - minimize_memory_usage: Minimize memory usage by calculating images on\ - the fly and storing only non-negligible pixel values. - winsorize_outliers: Options to remove effects of outliers in\ - calculations using methods like BoxPlot or GrubbsRosner. - use_euclidean_distance: Propagate labels throughout the mask using a\ - distance transform. - label_propagation: Control propagation of each prior label by specified\ - lambda and boundary probability. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `AtroposOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(ATROPOS_METADATA) - cargs = [] - cargs.append("Atropos") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - cargs.extend([ - "-a", - intensity_image - ]) - if bspline is not None: - cargs.extend([ - "-b", - bspline - ]) - cargs.extend([ - "-i", - initialization - ]) - if partial_volume_label_set is not None: - cargs.extend([ - "-s", - partial_volume_label_set - ]) - if use_partial_volume_likelihoods is not None: - cargs.extend([ - "--use-partial-volume-likelihoods", - str(use_partial_volume_likelihoods) - ]) - if posterior_formulation is not None: - cargs.extend([ - "-p", - posterior_formulation - ]) - cargs.extend([ - "-x", - execution.input_file(mask_image) - ]) - cargs.extend([ - "-c", - convergence - ]) - cargs.extend([ - "-k", - likelihood_model - ]) - if mrf is not None: - cargs.extend([ - "-m", - mrf - ]) - if icm is not None: - cargs.extend([ - "-g", - icm - ]) - if use_random_seed is not None: - cargs.extend([ - "-r", - str(use_random_seed) - ]) - cargs.extend([ - "-o", - output - ]) - if minimize_memory_usage is not None: - cargs.extend([ - "-u", - str(minimize_memory_usage) - ]) - if winsorize_outliers is not None: - cargs.extend([ - "-w", - winsorize_outliers - ]) - if use_euclidean_distance is not None: - cargs.extend([ - "-e", - str(use_euclidean_distance) - ]) - if label_propagation is not None: - cargs.extend([ - "-l", - label_propagation - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = AtroposOutputs( - root=execution.output_file("."), - classified_image=execution.output_file(output + "_classified.nii.gz"), - posterior_probability_images=execution.output_file("[POSTERIOR_PROBABILITY_IMAGE_FILE_NAME_FORMAT]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "ATROPOS_METADATA", - "AtroposOutputs", - "atropos", -] diff --git a/python/src/niwrap/ants/convert_scalar_image_to_rgb.py b/python/src/niwrap/ants/convert_scalar_image_to_rgb.py deleted file mode 100644 index 6c305143b..000000000 --- a/python/src/niwrap/ants/convert_scalar_image_to_rgb.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_SCALAR_IMAGE_TO_RGB_METADATA = Metadata( - id="bd90be2304f55e5624a9a746b1b00f9df35ab8d6.boutiques", - name="ConvertScalarImageToRGB", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ConvertScalarImageToRgbOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_scalar_image_to_rgb(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_rgb_image: OutputPathType - """The resulting RGB image after conversion.""" - - -def convert_scalar_image_to_rgb( - image_dimension: int, - input_image: InputPathType, - output_image: InputPathType, - mask: InputPathType, - colormap: typing.Literal["grey", "red", "green", "blue", "copper", "jet", "hsv", "spring", "summer", "autumn", "winter", "hot", "cool", "overunder", "custom"], - custom_colormap_file: InputPathType | None = None, - minimum_input: float | None = None, - maximum_input: float | None = None, - minimum_rgb_output: int | None = 0, - maximum_rgb_output: int | None = 255, - vtk_lookup_table: str | None = None, - runner: Runner | None = None, -) -> ConvertScalarImageToRgbOutputs: - """ - Converts a scalar image to an RGB image using specified parameters. Supports - multiple colormap options and customization. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the image (e.g., 2D or 3D). - input_image: The input scalar image to be converted to RGB. - output_image: The output RGB image file. - mask: The mask image to apply during conversion. - colormap: The colormap to use for RGB conversion. - custom_colormap_file: The file specifying the custom colormap (only\ - used if colormap is 'custom'). - minimum_input: The minimum input value for scaling. - maximum_input: The maximum input value for scaling. - minimum_rgb_output: The minimum output value for the RGB image.\ - Defaults to 0. - maximum_rgb_output: The maximum output value for the RGB image.\ - Defaults to 255. - vtk_lookup_table: The VTK lookup table to apply for additional\ - customization. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertScalarImageToRgbOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_SCALAR_IMAGE_TO_RGB_METADATA) - cargs = [] - cargs.append("ConvertScalarImageToRGB") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - cargs.append(execution.input_file(output_image)) - cargs.append(execution.input_file(mask)) - cargs.append(colormap) - if custom_colormap_file is not None: - cargs.append(execution.input_file(custom_colormap_file)) - if minimum_input is not None: - cargs.append(str(minimum_input)) - if maximum_input is not None: - cargs.append(str(maximum_input)) - if minimum_rgb_output is not None: - cargs.append(str(minimum_rgb_output)) - if maximum_rgb_output is not None: - cargs.append(str(maximum_rgb_output)) - if vtk_lookup_table is not None: - cargs.append(vtk_lookup_table) - ret = ConvertScalarImageToRgbOutputs( - root=execution.output_file("."), - output_rgb_image=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_SCALAR_IMAGE_TO_RGB_METADATA", - "ConvertScalarImageToRgbOutputs", - "convert_scalar_image_to_rgb", -] diff --git a/python/src/niwrap/ants/convert_to_jpg.py b/python/src/niwrap/ants/convert_to_jpg.py deleted file mode 100644 index 4fb82c1d2..000000000 --- a/python/src/niwrap/ants/convert_to_jpg.py +++ /dev/null @@ -1,64 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_TO_JPG_METADATA = Metadata( - id="31b6355945c3546a7d864a64fbe9afa58d72247b.boutiques", - name="ConvertToJpg", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ConvertToJpgOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_to_jpg(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_jpg: OutputPathType - """The converted JPG image.""" - - -def convert_to_jpg( - infile: InputPathType, - outfile: str, - runner: Runner | None = None, -) -> ConvertToJpgOutputs: - """ - A tool to convert NIfTI images to JPG format. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - infile: The input file in NIfTI format. - outfile: The output file in JPG format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertToJpgOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_TO_JPG_METADATA) - cargs = [] - cargs.append("ConvertToJpg") - cargs.append(execution.input_file(infile)) - cargs.append(outfile) - ret = ConvertToJpgOutputs( - root=execution.output_file("."), - output_jpg=execution.output_file(outfile), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_TO_JPG_METADATA", - "ConvertToJpgOutputs", - "convert_to_jpg", -] diff --git a/python/src/niwrap/ants/convert_transform_file.py b/python/src/niwrap/ants/convert_transform_file.py deleted file mode 100644 index bba3bdc69..000000000 --- a/python/src/niwrap/ants/convert_transform_file.py +++ /dev/null @@ -1,68 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CONVERT_TRANSFORM_FILE_METADATA = Metadata( - id="224c137774aff43d94d1fecb5c8b4a19ae81816c.boutiques", - name="ConvertTransformFile", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ConvertTransformFileOutputs(typing.NamedTuple): - """ - Output object returned when calling `convert_transform_file(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def convert_transform_file( - dimensions: int, - input_transform_file: InputPathType, - output_transform_file: str, - runner: Runner | None = None, -) -> ConvertTransformFileOutputs: - """ - Utility to read in a transform file (presumed to be in binary format) and output - it in various formats. Default output is legacy human-readable text format. - Without any options, the output filename extension must be .txt or .tfm to - signify a text-formatted transform file. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimensions: Dimensionality of the transform file. - input_transform_file: Path to the input transform file. - output_transform_file: Path for the output transform file. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ConvertTransformFileOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CONVERT_TRANSFORM_FILE_METADATA) - cargs = [] - cargs.append("ConvertTransformFile") - cargs.append(str(dimensions)) - cargs.append(execution.input_file(input_transform_file)) - cargs.append(output_transform_file) - cargs.append("[OPTIONS]") - ret = ConvertTransformFileOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CONVERT_TRANSFORM_FILE_METADATA", - "ConvertTransformFileOutputs", - "convert_transform_file", -] diff --git a/python/src/niwrap/ants/create_displacement_field.py b/python/src/niwrap/ants/create_displacement_field.py deleted file mode 100644 index d83fe8b8f..000000000 --- a/python/src/niwrap/ants/create_displacement_field.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CREATE_DISPLACEMENT_FIELD_METADATA = Metadata( - id="802911687fe6024ba5b40503dd2ac46f0ca9b56b.boutiques", - name="CreateDisplacementField", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class CreateDisplacementFieldOutputs(typing.NamedTuple): - """ - Output object returned when calling `create_displacement_field(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_displacement_field: OutputPathType - """The generated itkImage of itkVector pixels representing the displacement - field.""" - - -def create_displacement_field( - image_dimension: int, - enforce_zero_boundary_flag: typing.Literal[0, 1], - component_images: list[InputPathType], - output_image: InputPathType, - runner: Runner | None = None, -) -> CreateDisplacementFieldOutputs: - """ - Create an itkImage of itkVector pixels (NOT an itkVectorImage), using each - scalar input component image for each vector component. An itkImage of - itkVectors is the standard type for displacement fields in ITK. All component - images (up to 8) are assumed to have the same size, offset, origin, and spacing. - The 'EnforceZeroBoundaryFlag' option will create zero-valued vectors along the - borders when enabled (pass 1), and is recommended for better displacement field - behavior. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimension of the image, typically 2 or 3. - enforce_zero_boundary_flag: Create zero-valued vectors along the\ - borders when enabled (pass 1), recommended for better displacement\ - field behavior. - component_images: Input component images, each used for a vector\ - component. All component images must have the same size, offset,\ - origin, and spacing. - output_image: The output displacement field image with itkVector\ - pixels. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CreateDisplacementFieldOutputs`). - """ - if not (1 <= len(component_images) <= 8): - raise ValueError(f"Length of 'component_images' must be between 1 and 8 but was {len(component_images)}") - runner = runner or get_global_runner() - execution = runner.start_execution(CREATE_DISPLACEMENT_FIELD_METADATA) - cargs = [] - cargs.append("CreateDisplacementField") - cargs.append(str(image_dimension)) - cargs.append(str(enforce_zero_boundary_flag)) - cargs.extend([execution.input_file(f) for f in component_images]) - cargs.append(execution.input_file(output_image)) - ret = CreateDisplacementFieldOutputs( - root=execution.output_file("."), - output_displacement_field=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CREATE_DISPLACEMENT_FIELD_METADATA", - "CreateDisplacementFieldOutputs", - "create_displacement_field", -] diff --git a/python/src/niwrap/ants/create_dticohort.py b/python/src/niwrap/ants/create_dticohort.py deleted file mode 100644 index bd59525d5..000000000 --- a/python/src/niwrap/ants/create_dticohort.py +++ /dev/null @@ -1,134 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CREATE_DTICOHORT_METADATA = Metadata( - id="b6d3b7b7d3095a9db5e406c42360be21bbfd0ce5.boutiques", - name="CreateDTICohort", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class CreateDticohortOutputs(typing.NamedTuple): - """ - Output object returned when calling `create_dticohort(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_directory: OutputPathType - """The directory where the output data will be stored.""" - filename_series: OutputPathType - """Root name for the series of output files.""" - - -def create_dticohort( - dti_atlas: InputPathType, - dwi_parameters: str, - output: str, - image_dimensionality: typing.Literal[2, 3] | None = None, - label_mask_image: str | None = None, - noise_sigma: float | None = None, - pathology: str | None = None, - registered_population: InputPathType | None = None, - runner: Runner | None = None, -) -> CreateDticohortOutputs: - """ - CreateDTICohort implements the work of Van Hecke et al. to create simulated DTI - data sets. The only difference is that all registrations (both for the input - population and for the output population) are assumed to take place outside of - this program. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dti_atlas: A diffusion tensor atlas image is required input for\ - creating the cohort. - dwi_parameters: This option specifies the parameters of the output\ - diffusion-weighted images, including the directions and b-values.\ - Directions can be specified using a direction file or scheme file. - output: The output consists of a set of diffusion-weighted images for\ - each subject. Control and experimental subject numbers can be\ - specified. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - label_mask_image: A mask image can be specified which determines the\ - region(s) to which the simulated pathology operations are applied. If\ - no mask is specified one is created by thresholding the atlas FA map at\ - 0.2 unless a lower threshold is specified. - noise_sigma: This parameter characterizes the Rician noise in the\ - original DWI images. Default value is 18. - pathology: The user can specify the simulated pathology in a given area\ - using a label mask. Pathology is simulated by changing the eigenvalues.\ - One can specify the number of voxels affected in each region or the\ - proportion of voxels affected. Change is specified as a proportion of\ - the current eigenvalues. - registered_population: To introduce inter-subject variability, a\ - registered DTI population to the DTI atlas is required. This is modeled\ - by PCA decomposition. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CreateDticohortOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CREATE_DTICOHORT_METADATA) - cargs = [] - cargs.append("CreateDTICohort") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - cargs.extend([ - "--dti-atlas", - execution.input_file(dti_atlas) - ]) - if label_mask_image is not None: - cargs.extend([ - "--label-mask-image", - label_mask_image - ]) - if noise_sigma is not None: - cargs.extend([ - "--noise-sigma", - str(noise_sigma) - ]) - if pathology is not None: - cargs.extend([ - "--pathology", - pathology - ]) - cargs.extend([ - "--dwi-parameters", - dwi_parameters - ]) - if registered_population is not None: - cargs.extend([ - "--registered-population", - execution.input_file(registered_population) - ]) - cargs.extend([ - "--output", - output - ]) - ret = CreateDticohortOutputs( - root=execution.output_file("."), - output_directory=execution.output_file("[OUTPUT_DIRECTORY]"), - filename_series=execution.output_file("[OUTPUT_DIRECTORY]/[FILENAME_SERIES_ROOT_NAME]_*.nii"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CREATE_DTICOHORT_METADATA", - "CreateDticohortOutputs", - "create_dticohort", -] diff --git a/python/src/niwrap/ants/create_tiled_mosaic.py b/python/src/niwrap/ants/create_tiled_mosaic.py deleted file mode 100644 index 24f9eb3e6..000000000 --- a/python/src/niwrap/ants/create_tiled_mosaic.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CREATE_TILED_MOSAIC_METADATA = Metadata( - id="62ba9b499dd56904d0e9344bc41632c426e55fc9.boutiques", - name="CreateTiledMosaic", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class CreateTiledMosaicOutputs(typing.NamedTuple): - """ - Output object returned when calling `create_tiled_mosaic(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - tiled_mosaic_image: OutputPathType - """The output is the tiled mosaic image.""" - - -def create_tiled_mosaic( - input_image: InputPathType, - output: InputPathType, - rgb_image: InputPathType | None = None, - mask_image: InputPathType | None = None, - alpha: float | None = None, - functional_overlay: str | None = None, - tile_geometry: str | None = None, - direction: typing.Literal["0", "1", "2", "x", "y", "z"] | None = None, - pad_or_crop: str | None = None, - slices: str | None = None, - flip_slice: str | None = None, - permute_axes: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> CreateTiledMosaicOutputs: - """ - Render a 3-D image volume with optional Rgb overlay. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: Main input is a 3-D grayscale image. - output: The output is the tiled mosaic image. The format must support\ - the specific data type: floating point images without RGB overlays, Rgb\ - images with intensities scaled to [0,255] if overlays are present. - rgb_image: An optional Rgb image can be added as an overlay. It must\ - have the same image geometry as the input grayscale image. - mask_image: Specifies the ROI of the RGB voxels used. - alpha: If an Rgb image is provided, render the overlay using the\ - specified alpha parameter. - functional_overlay: A functional overlay can be specified using both\ - and rgb image and a mask specifying where that rgb image should be\ - applied. Both images must have the same image geometry as the input\ - image. Optionally, an alpha parameter can be specified. - tile_geometry: The tile geometry specifies the number of rows and\ - columns in the output image. For example, specifying '5x10' renders 5\ - rows by 10 columns of slices. - direction: Specifies the direction of the slices. Can be based on image\ - storage in memory or aligned physical space. Defaults to z-direction if\ - unspecified. - pad_or_crop: Specify padding or cropping with a voxel-width boundary\ - for each slice. Padding uses a specified constant value. Cropping pads\ - with negative voxel-widths. - slices: Control over which slices to render. Specify slices directly or\ - incrementally with optional start and end slices. - flip_slice: Flip individual slice images horizontally and/or\ - vertically. - permute_axes: Permute (or swap) the axes of the individual slice\ - images. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CreateTiledMosaicOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CREATE_TILED_MOSAIC_METADATA) - cargs = [] - cargs.append("CreateTiledMosaic") - cargs.extend([ - "-i", - execution.input_file(input_image) - ]) - if rgb_image is not None: - cargs.extend([ - "-r", - execution.input_file(rgb_image) - ]) - if mask_image is not None: - cargs.extend([ - "-x", - execution.input_file(mask_image) - ]) - if alpha is not None: - cargs.extend([ - "-a", - str(alpha) - ]) - if functional_overlay is not None: - cargs.extend([ - "-e", - functional_overlay - ]) - cargs.extend([ - "-o", - execution.input_file(output) - ]) - if tile_geometry is not None: - cargs.extend([ - "-t", - tile_geometry - ]) - if direction is not None: - cargs.extend([ - "-d", - direction - ]) - if pad_or_crop is not None: - cargs.extend([ - "-p", - pad_or_crop - ]) - if slices is not None: - cargs.extend([ - "-s", - slices - ]) - if flip_slice is not None: - cargs.extend([ - "-f", - flip_slice - ]) - if permute_axes is not None: - cargs.extend([ - "-g", - str(permute_axes) - ]) - ret = CreateTiledMosaicOutputs( - root=execution.output_file("."), - tiled_mosaic_image=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CREATE_TILED_MOSAIC_METADATA", - "CreateTiledMosaicOutputs", - "create_tiled_mosaic", -] diff --git a/python/src/niwrap/ants/create_warped_grid_image.py b/python/src/niwrap/ants/create_warped_grid_image.py deleted file mode 100644 index 183f8b0c1..000000000 --- a/python/src/niwrap/ants/create_warped_grid_image.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -CREATE_WARPED_GRID_IMAGE_METADATA = Metadata( - id="43b75b2bbf1de43489ea85a551208078dcde662b.boutiques", - name="CreateWarpedGridImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class CreateWarpedGridImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `create_warped_grid_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - warped_grid_image: OutputPathType - """The resultant warped grid image.""" - - -def create_warped_grid_image( - image_dimension: int, - deformation_field: InputPathType, - output_image: str, - directions: str | None = None, - grid_spacing: str | None = None, - grid_sigma: str | None = None, - runner: Runner | None = None, -) -> CreateWarpedGridImageOutputs: - """ - Create a warped grid image based on the specified deformation field. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input image. - deformation_field: File containing the deformation field to be applied. - output_image: The filename of the output warped grid image. - directions: Directions for the grid warping, e.g., '1x0x0'. - grid_spacing: Spacing of the grid, e.g., '10x10x10'. - grid_sigma: Sigma value for the grid smoothing, e.g., '1x1x1'. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `CreateWarpedGridImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(CREATE_WARPED_GRID_IMAGE_METADATA) - cargs = [] - cargs.append("CreateWarpedGridImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(deformation_field)) - cargs.append(output_image) - if directions is not None: - cargs.append(directions) - if grid_spacing is not None: - cargs.append(grid_spacing) - if grid_sigma is not None: - cargs.append(grid_sigma) - ret = CreateWarpedGridImageOutputs( - root=execution.output_file("."), - warped_grid_image=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "CREATE_WARPED_GRID_IMAGE_METADATA", - "CreateWarpedGridImageOutputs", - "create_warped_grid_image", -] diff --git a/python/src/niwrap/ants/denoise_image.py b/python/src/niwrap/ants/denoise_image.py deleted file mode 100644 index 94c9b24ff..000000000 --- a/python/src/niwrap/ants/denoise_image.py +++ /dev/null @@ -1,135 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -DENOISE_IMAGE_METADATA = Metadata( - id="9cd7501fd7ace5efdaa42362d19437b6007309ac.boutiques", - name="DenoiseImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class DenoiseImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `denoise_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_image: OutputPathType - """The noise corrected version of the input image.""" - noise_image: OutputPathType - """Estimated noise image.""" - - -def denoise_image( - input_image: InputPathType, - corrected_image_path: str, - noise_image_path: str, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - noise_model: typing.Literal["Gaussian", "Rician"] | None = None, - shrink_factor: int | None = None, - mask_image: InputPathType | None = None, - patch_radius: str | None = None, - search_radius: str | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> DenoiseImageOutputs: - """ - Denoise an image using a spatially adaptive filter originally described in J. V. - Manjon, P. Coupe, Luis Marti-Bonmati, D. L. Collins, and M. Robles. Adaptive - Non-Local Means Denoising of MR Images With Spatially Varying Noise Levels, - Journal of Magnetic Resonance Imaging, 31:192-203, June 2010. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: -i, --input-image inputImageFilename. A scalar image is\ - expected as input for noise correction. - corrected_image_path: The noise corrected version of the input image. - noise_image_path: Estimated noise image. - image_dimensionality: -d, --image-dimensionality 2/3/4. This option\ - forces the image to be treated as a specified-dimensional image. If not\ - specified, the program tries to infer the dimensionality from the input\ - image. - noise_model: -n, --noise-model Rician/(Gaussian). Employ a Rician or\ - Gaussian noise model. - shrink_factor: -s, --shrink-factor (1)/2/3/... Running noise correction\ - on large images can be time consuming. To lessen computation time, the\ - input image can be resampled. The shrink factor, specified as a single\ - integer, describes this resampling. Shrink factor = 1 is the default. - mask_image: -x, --mask-image maskImageFilename. If a mask image is\ - specified, denoising is only performed in the mask region. - patch_radius: -p, --patch-radius 1x1x1. Patch radius. Default is 1x1x1. - search_radius: -r, --search-radius 2x2x2. Search radius. Default is\ - 2x2x2. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `DenoiseImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(DENOISE_IMAGE_METADATA) - cargs = [] - cargs.append("DenoiseImage") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - if noise_model is not None: - cargs.extend([ - "--noise-model", - noise_model - ]) - if shrink_factor is not None: - cargs.extend([ - "--shrink-factor", - str(shrink_factor) - ]) - if mask_image is not None: - cargs.extend([ - "--mask-image", - execution.input_file(mask_image) - ]) - if patch_radius is not None: - cargs.extend([ - "--patch-radius", - patch_radius - ]) - if search_radius is not None: - cargs.extend([ - "--search-radius", - search_radius - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - cargs.extend([ - "--input-image", - execution.input_file(input_image) - ]) - cargs.append("--output") - cargs.append("[" + corrected_image_path + "," + noise_image_path + "]") - ret = DenoiseImageOutputs( - root=execution.output_file("."), - corrected_image=execution.output_file(corrected_image_path), - noise_image=execution.output_file(noise_image_path), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "DENOISE_IMAGE_METADATA", - "DenoiseImageOutputs", - "denoise_image", -] diff --git a/python/src/niwrap/ants/extract_region_from_image.py b/python/src/niwrap/ants/extract_region_from_image.py deleted file mode 100644 index ced2800ab..000000000 --- a/python/src/niwrap/ants/extract_region_from_image.py +++ /dev/null @@ -1,174 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -EXTRACT_REGION_FROM_IMAGE_METADATA = Metadata( - id="ae946f4d1bb246c4c0e1a26e1d18d3d6f5ce930d.boutiques", - name="ExtractRegionFromImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class ExtractRegionFromImageRegionMinMaxIndex: - min_index: str - """Minimum index to define the starting point of the region.""" - max_index: str - """Maximum index to define the endpoint of the region.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(self.min_index) - cargs.append(self.max_index) - return cargs - - -@dataclasses.dataclass -class ExtractRegionFromImageRegionLabel: - label: str - """Label value to extract the region corresponding to the specified - label.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(self.label) - return cargs - - -@dataclasses.dataclass -class ExtractRegionFromImageRegionDomainImage: - domain_image: InputPathType - """Image defining the domain from which to extract the region.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(execution.input_file(self.domain_image)) - return cargs - - -@dataclasses.dataclass -class ExtractRegionFromImageRegionLabelWithImage: - label: str - """Label value used for the region extraction.""" - label_image: InputPathType - """Image containing label information.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(self.label) - cargs.append(execution.input_file(self.label_image)) - cargs.append("1") - return cargs - - -class ExtractRegionFromImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `extract_region_from_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType - """File containing the extracted region.""" - - -def extract_region_from_image( - image_dimension: int, - input_image: InputPathType, - output_image: str, - region_specification: typing.Union[ExtractRegionFromImageRegionMinMaxIndex, ExtractRegionFromImageRegionLabel, ExtractRegionFromImageRegionDomainImage, ExtractRegionFromImageRegionLabelWithImage], - runner: Runner | None = None, -) -> ExtractRegionFromImageOutputs: - """ - ExtractRegionFromImage can be used to extract a specific region from a given - image. The region can be specified via indices, label, or another domain image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the image. - input_image: Path to the input image from which the region will be\ - extracted. - output_image: Path to the output image where the extracted region will\ - be saved. - region_specification: Specify the region to extract using indices,\ - label, domain image, or label with label image. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ExtractRegionFromImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(EXTRACT_REGION_FROM_IMAGE_METADATA) - cargs = [] - cargs.append("ExtractRegionFromImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - cargs.append(output_image) - cargs.extend(region_specification.run(execution)) - ret = ExtractRegionFromImageOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "EXTRACT_REGION_FROM_IMAGE_METADATA", - "ExtractRegionFromImageOutputs", - "ExtractRegionFromImageRegionDomainImage", - "ExtractRegionFromImageRegionLabel", - "ExtractRegionFromImageRegionLabelWithImage", - "ExtractRegionFromImageRegionMinMaxIndex", - "extract_region_from_image", -] diff --git a/python/src/niwrap/ants/extract_region_from_image_by_mask.py b/python/src/niwrap/ants/extract_region_from_image_by_mask.py deleted file mode 100644 index e590b778e..000000000 --- a/python/src/niwrap/ants/extract_region_from_image_by_mask.py +++ /dev/null @@ -1,78 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -EXTRACT_REGION_FROM_IMAGE_BY_MASK_METADATA = Metadata( - id="aec2f60db8048987a495410600ad2f857750da61.boutiques", - name="ExtractRegionFromImageByMask", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ExtractRegionFromImageByMaskOutputs(typing.NamedTuple): - """ - Output object returned when calling `extract_region_from_image_by_mask(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def extract_region_from_image_by_mask( - image_dimension: int, - input_image: InputPathType, - output_image: InputPathType, - label_mask_image: InputPathType, - label: int | None = 1, - pad_radius: int | None = 0, - runner: Runner | None = None, -) -> ExtractRegionFromImageByMaskOutputs: - """ - Extract a sub-region from an image using the bounding box from a label image, - with an optional padding radius. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimension of the input image. - input_image: The input image from which a region will be extracted. - output_image: The output image containing the extracted region. - label_mask_image: The label mask image used to extract the bounding\ - box. - label: The label value used to extract the sub-region. - pad_radius: Optional padding radius to be added around the bounding\ - box. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ExtractRegionFromImageByMaskOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(EXTRACT_REGION_FROM_IMAGE_BY_MASK_METADATA) - cargs = [] - cargs.append("ExtractRegionFromImageByMask") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - cargs.append(execution.input_file(output_image)) - cargs.append(execution.input_file(label_mask_image)) - if label is not None: - cargs.append(str(label)) - if pad_radius is not None: - cargs.append(str(pad_radius)) - ret = ExtractRegionFromImageByMaskOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "EXTRACT_REGION_FROM_IMAGE_BY_MASK_METADATA", - "ExtractRegionFromImageByMaskOutputs", - "extract_region_from_image_by_mask", -] diff --git a/python/src/niwrap/ants/i_math.py b/python/src/niwrap/ants/i_math.py deleted file mode 100644 index cc544a5b0..000000000 --- a/python/src/niwrap/ants/i_math.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -I_MATH_METADATA = Metadata( - id="58ac5a6e6eaabd0c15c3cb9cd300ac49330f2a22.boutiques", - name="iMath", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class IMathOutputs(typing.NamedTuple): - """ - Output object returned when calling `i_math(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - resulting_image: OutputPathType - """The output image resulting from the operation.""" - - -def i_math( - image_dimension: typing.Literal[2, 3, 4], - output_image: str, - operations: str, - image1: InputPathType, - image2: InputPathType | None = None, - runner: Runner | None = None, -) -> IMathOutputs: - """ - iMath is a tool for performing various image mathematical operations on medical - images, specifically supporting operations on 2D, 3D, and 4D data. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimensionality of the image, either 2, 3, or 4. - output_image: Path for the output image file. - operations: Operations to be performed along with parameters, e.g.,\ - GetLargestComponent, MC for Closing, etc. - image1: First input image file. - image2: Second input image file, if required by operation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `IMathOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(I_MATH_METADATA) - cargs = [] - cargs.append("iMath") - cargs.append(str(image_dimension)) - cargs.append(output_image) - cargs.append(operations) - cargs.append(execution.input_file(image1)) - if image2 is not None: - cargs.append(execution.input_file(image2)) - ret = IMathOutputs( - root=execution.output_file("."), - resulting_image=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMathOutputs", - "I_MATH_METADATA", - "i_math", -] diff --git a/python/src/niwrap/ants/image_intensity_statistics.py b/python/src/niwrap/ants/image_intensity_statistics.py deleted file mode 100644 index b1718b013..000000000 --- a/python/src/niwrap/ants/image_intensity_statistics.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAGE_INTENSITY_STATISTICS_METADATA = Metadata( - id="ba7ab9e8e494076bff274459f3f86dfd1563d5d9.boutiques", - name="ImageIntensityStatistics", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ImageIntensityStatisticsOutputs(typing.NamedTuple): - """ - Output object returned when calling `image_intensity_statistics(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - intensity_statistics: OutputPathType - """The output file containing intensity statistics.""" - - -def image_intensity_statistics( - image_dimension: int, - input_image: InputPathType, - label_image: InputPathType | None = None, - runner: Runner | None = None, -) -> ImageIntensityStatisticsOutputs: - """ - This tool computes intensity statistics of an input image, optionally given a - label image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the image (e.g., 2D, 3D). - input_image: The input image for which intensity statistics will be\ - computed. - label_image: An optional label image which defines regions of interest. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImageIntensityStatisticsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAGE_INTENSITY_STATISTICS_METADATA) - cargs = [] - cargs.append("ImageIntensityStatistics") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - if label_image is not None: - cargs.append(execution.input_file(label_image)) - ret = ImageIntensityStatisticsOutputs( - root=execution.output_file("."), - intensity_statistics=execution.output_file("intensity_statistics.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAGE_INTENSITY_STATISTICS_METADATA", - "ImageIntensityStatisticsOutputs", - "image_intensity_statistics", -] diff --git a/python/src/niwrap/ants/image_math.py b/python/src/niwrap/ants/image_math.py deleted file mode 100644 index e8853b7b7..000000000 --- a/python/src/niwrap/ants/image_math.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAGE_MATH_METADATA = Metadata( - id="2c72bece75928eecfab8863dce2bbf80261ecbe6.boutiques", - name="ImageMath", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ImageMathOutputs(typing.NamedTuple): - """ - Output object returned when calling `image_math(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """The resulting image after processing.""" - - -def image_math( - image_dimension: typing.Literal[2, 3, 4], - output_image: InputPathType, - image1: InputPathType, - image2: InputPathType | None = None, - runner: Runner | None = None, -) -> ImageMathOutputs: - """ - A versatile tool for performing various mathematical and manipulation operations - on images. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the image. Use 2 or 3 for\ - spatial images, and 4 for 4D images like time-series data. - output_image: The output image file resulting from the operations. - image1: The first input image for the operation. - image2: The second input image for the operation, if required. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImageMathOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAGE_MATH_METADATA) - cargs = [] - cargs.append("ImageMath") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(output_image)) - cargs.append("[operations") - cargs.append("and") - cargs.append("inputs]") - cargs.append(execution.input_file(image1)) - if image2 is not None: - cargs.append(execution.input_file(image2)) - ret = ImageMathOutputs( - root=execution.output_file("."), - output_image=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAGE_MATH_METADATA", - "ImageMathOutputs", - "image_math", -] diff --git a/python/src/niwrap/ants/image_set_statistics.py b/python/src/niwrap/ants/image_set_statistics.py deleted file mode 100644 index d5b16b910..000000000 --- a/python/src/niwrap/ants/image_set_statistics.py +++ /dev/null @@ -1,102 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -IMAGE_SET_STATISTICS_METADATA = Metadata( - id="9329b484e2f67dba69c548b9b9a373ea2a072aa8.boutiques", - name="ImageSetStatistics", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ImageSetStatisticsOutputs(typing.NamedTuple): - """ - Output object returned when calling `image_set_statistics(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - computed_statistics_image: OutputPathType - """The output image containing the computed statistics.""" - - -def image_set_statistics( - image_dimension: int, - controls_list: InputPathType, - output_image: str, - which_stat: typing.Literal[0, 1, 2, 3, 4, 5, 6, 7], - roi: InputPathType | None = None, - imagelist2: InputPathType | None = None, - runner: Runner | None = None, -) -> ImageSetStatisticsOutputs: - """ - ImageSetStatistics computes statistics from a set of images. The whichstat - option defines the type of statistic to compute, ranging from median to - similarity-weighted metrics. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the images to be processed by\ - ImageSetStatistics. - controls_list: Text file containing the list of control images. - output_image: The output image file where the computed statistics are\ - stored. - which_stat: Choice of statistic to compute: 0 for median, 1 for max\ - probability appearance, 2 for weighted mean appearance, 3 for trimmed\ - mean, 4 for max value, 5 for similarity-weighted (requires imagelist2),\ - 6 for best local match label, 7 for max value from ROI. - roi: Region of interest image file, optional depending on the whichstat\ - option. - imagelist2: List of similarity images used for similarity-weighted\ - statistics. Required if whichstat equals 5 or 6. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ImageSetStatisticsOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(IMAGE_SET_STATISTICS_METADATA) - cargs = [] - cargs.append("ImageSetStatistics") - cargs.append(str(image_dimension)) - cargs.extend([ - "[CONTROLS_LIST]", - execution.input_file(controls_list) - ]) - cargs.extend([ - "[OUTPUT_IMAGE]", - output_image - ]) - cargs.extend([ - "[WHICH_STAT]", - str(which_stat) - ]) - if roi is not None: - cargs.extend([ - "[ROI]", - execution.input_file(roi) - ]) - if imagelist2 is not None: - cargs.extend([ - "[IMAGELIST2]", - execution.input_file(imagelist2) - ]) - ret = ImageSetStatisticsOutputs( - root=execution.output_file("."), - computed_statistics_image=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "IMAGE_SET_STATISTICS_METADATA", - "ImageSetStatisticsOutputs", - "image_set_statistics", -] diff --git a/python/src/niwrap/ants/kelly_kapowski.py b/python/src/niwrap/ants/kelly_kapowski.py deleted file mode 100644 index a3f002e72..000000000 --- a/python/src/niwrap/ants/kelly_kapowski.py +++ /dev/null @@ -1,212 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -KELLY_KAPOWSKI_METADATA = Metadata( - id="8cf867e1228b8566e73919051e43b36f34a80495.boutiques", - name="KellyKapowski", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class KellyKapowskiOutputs(typing.NamedTuple): - """ - Output object returned when calling `kelly_kapowski(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - thickness_map: OutputPathType - """The output is the thickness map defined in the segmented gray matter.""" - - -def kelly_kapowski( - output: str, - image_dimensionality: typing.Literal[2, 3] | None = None, - segmentation_image: InputPathType | None = None, - gray_matter_probability_image: InputPathType | None = None, - white_matter_probability_image: InputPathType | None = None, - convergence: str | None = None, - thickness_prior_estimate: float | None = None, - thickness_prior_image: InputPathType | None = None, - gradient_step: float | None = None, - smoothing_variance: float | None = None, - smoothing_velocity_field_parameter: str | None = None, - use_bspline_smoothing: typing.Literal[0, 1] | None = None, - use_masked_smoothing: typing.Literal[0, 1] | None = None, - time_points: str | None = None, - restrict_deformation: typing.Literal[0, 1] | None = None, - number_of_integration_points: int | None = None, - maximum_number_of_invert_displacement_field_iterations: int | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> KellyKapowskiOutputs: - """ - DiReCT is a registration based estimate of cortical thickness. It was published - in S. R. Das, B. B. Avants, M. Grossman, and J. C. Gee, Registration based - cortical thickness measurement, Neuroimage 2009, 45:867--879. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - output: The output consists of a thickness map defined in the segmented\ - gray matter. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, DiReCT tries to infer\ - the dimensionality from the input image. - segmentation_image: A segmentation image must be supplied labeling the\ - gray and white matters. Default values = 2 and 3, respectively. - gray_matter_probability_image: In addition to the segmentation image, a\ - gray matter probability image can be used. If no such image is\ - supplied, one is created using the segmentation image and a variance of\ - 1.0 mm. - white_matter_probability_image: In addition to the segmentation image,\ - a white matter probability image can be used. If no such image is\ - supplied, one is created using the segmentation image and a variance of\ - 1.0 mm. - convergence: Convergence is determined by fitting a line to the\ - normalized energy profile of the last N iterations (where N is\ - specified by the window size) and determining the slope which is then\ - compared with the convergence threshold. - thickness_prior_estimate: Provides a prior constraint on the final\ - thickness measurement. Default = 10 mm. - thickness_prior_image: An image containing spatially varying prior\ - thickness values. - gradient_step: Gradient step size for the optimization. Default =\ - 0.025. - smoothing_variance: Defines the Gaussian smoothing of the hit and total\ - images. Default = 1.0 mm. - smoothing_velocity_field_parameter: Defines the Gaussian smoothing of\ - the velocity field (default = 1.5 voxels). If the b-spline smoothing\ - option is chosen, then this defines the isotropic mesh spacing for the\ - smoothing spline (default = 15 mm). - use_bspline_smoothing: Sets the option for B-spline smoothing of the\ - velocity field. Default = false. - use_masked_smoothing: Sets the option for masked-based smoothing of the\ - velocity field. Default = false. - time_points: Time points for irregularly spaced time samples and\ - time-variance with which to compute distance metric. - restrict_deformation: Restrict the last dimension's deformation. Meant\ - for use with multiple time points. Default = false. - number_of_integration_points: Number of compositions of the\ - diffeomorphism per iteration. Default = 10. - maximum_number_of_invert_displacement_field_iterations: Maximum number\ - of iterations for estimating the invert displacement field. Default =\ - 20. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `KellyKapowskiOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(KELLY_KAPOWSKI_METADATA) - cargs = [] - cargs.append("KellyKapowski") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - if segmentation_image is not None: - cargs.extend([ - "--segmentation-image", - execution.input_file(segmentation_image) - ]) - if gray_matter_probability_image is not None: - cargs.extend([ - "--gray-matter-probability-image", - execution.input_file(gray_matter_probability_image) - ]) - if white_matter_probability_image is not None: - cargs.extend([ - "--white-matter-probability-image", - execution.input_file(white_matter_probability_image) - ]) - if convergence is not None: - cargs.extend([ - "--convergence", - convergence - ]) - if thickness_prior_estimate is not None: - cargs.extend([ - "--thickness-prior-estimate", - str(thickness_prior_estimate) - ]) - if thickness_prior_image is not None: - cargs.extend([ - "--thickness-prior-image", - execution.input_file(thickness_prior_image) - ]) - if gradient_step is not None: - cargs.extend([ - "--gradient-step", - str(gradient_step) - ]) - if smoothing_variance is not None: - cargs.extend([ - "--smoothing-variance", - str(smoothing_variance) - ]) - if smoothing_velocity_field_parameter is not None: - cargs.extend([ - "--smoothing-velocity-field-parameter", - smoothing_velocity_field_parameter - ]) - if use_bspline_smoothing is not None: - cargs.extend([ - "--use-bspline-smoothing", - str(use_bspline_smoothing) - ]) - if use_masked_smoothing is not None: - cargs.extend([ - "--use-masked-smoothing", - str(use_masked_smoothing) - ]) - if time_points is not None: - cargs.extend([ - "--time-points", - time_points - ]) - if restrict_deformation is not None: - cargs.extend([ - "--restrict-deformation", - str(restrict_deformation) - ]) - if number_of_integration_points is not None: - cargs.extend([ - "--number-of-integration-points", - str(number_of_integration_points) - ]) - if maximum_number_of_invert_displacement_field_iterations is not None: - cargs.extend([ - "--maximum-number-of-invert-displacement-field-iterations", - str(maximum_number_of_invert_displacement_field_iterations) - ]) - cargs.extend([ - "--output", - output - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = KellyKapowskiOutputs( - root=execution.output_file("."), - thickness_map=execution.output_file(output), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "KELLY_KAPOWSKI_METADATA", - "KellyKapowskiOutputs", - "kelly_kapowski", -] diff --git a/python/src/niwrap/ants/label_geometry_measures.py b/python/src/niwrap/ants/label_geometry_measures.py deleted file mode 100644 index 2367a6ebf..000000000 --- a/python/src/niwrap/ants/label_geometry_measures.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -LABEL_GEOMETRY_MEASURES_METADATA = Metadata( - id="e7ce3202e62bc39e7b15a1562ae20a5cef322440.boutiques", - name="LabelGeometryMeasures", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class LabelGeometryMeasuresOutputs(typing.NamedTuple): - """ - Output object returned when calling `label_geometry_measures(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_csv: OutputPathType | None - """The CSV file containing the geometry measures.""" - - -def label_geometry_measures( - image_dimension: int, - label_image: InputPathType, - intensity_image: str | None = None, - csv_file: InputPathType | None = None, - runner: Runner | None = None, -) -> LabelGeometryMeasuresOutputs: - """ - This tool computes various geometry measures on a label image, optionally using - an intensity image, and outputs the results to a CSV file. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input images (e.g., 2 for\ - 2D, 3 for 3D). - label_image: The label image on which geometry measures are computed. - intensity_image: An optional intensity image for computing\ - intensity-weighted measures. Use "none" or "na" if not provided. - csv_file: The output file where the geometry measures are written in\ - CSV format. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `LabelGeometryMeasuresOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(LABEL_GEOMETRY_MEASURES_METADATA) - cargs = [] - cargs.append("LabelGeometryMeasures") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(label_image)) - if intensity_image is not None: - cargs.append(intensity_image) - if csv_file is not None: - cargs.append(execution.input_file(csv_file)) - ret = LabelGeometryMeasuresOutputs( - root=execution.output_file("."), - output_csv=execution.output_file(pathlib.Path(csv_file).name) if (csv_file is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "LABEL_GEOMETRY_MEASURES_METADATA", - "LabelGeometryMeasuresOutputs", - "label_geometry_measures", -] diff --git a/python/src/niwrap/ants/lesion_filling.py b/python/src/niwrap/ants/lesion_filling.py deleted file mode 100644 index 6b352ce24..000000000 --- a/python/src/niwrap/ants/lesion_filling.py +++ /dev/null @@ -1,70 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -LESION_FILLING_METADATA = Metadata( - id="e67424ecd9a0c5e13dd9b069bccb2e63e4348726.boutiques", - name="LesionFilling", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class LesionFillingOutputs(typing.NamedTuple): - """ - Output object returned when calling `lesion_filling(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - lesion_filled_output: OutputPathType - """Output image with filled lesions.""" - - -def lesion_filling( - image_dimension: int, - t1_image: InputPathType, - lesion_mask: InputPathType, - output_lesion_filled: str, - runner: Runner | None = None, -) -> LesionFillingOutputs: - """ - A tool for filling lesions in T1 images using a mask. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimensionality of the image (e.g., 2, 3). - t1_image: Path to the T1 image file. - lesion_mask: Path to the lesion mask image file. - output_lesion_filled: Path for the output file with lesions filled. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `LesionFillingOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(LESION_FILLING_METADATA) - cargs = [] - cargs.append("LesionFilling") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(t1_image)) - cargs.append(execution.input_file(lesion_mask)) - cargs.append(output_lesion_filled) - ret = LesionFillingOutputs( - root=execution.output_file("."), - lesion_filled_output=execution.output_file(output_lesion_filled), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "LESION_FILLING_METADATA", - "LesionFillingOutputs", - "lesion_filling", -] diff --git a/python/src/niwrap/ants/multiply_images.py b/python/src/niwrap/ants/multiply_images.py deleted file mode 100644 index 855a66450..000000000 --- a/python/src/niwrap/ants/multiply_images.py +++ /dev/null @@ -1,79 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -MULTIPLY_IMAGES_METADATA = Metadata( - id="c6da8ec5d4fa8b085a1135287a18f750b9fc74b7.boutiques", - name="MultiplyImages", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class MultiplyImagesOutputs(typing.NamedTuple): - """ - Output object returned when calling `multiply_images(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_product_image_outfile: OutputPathType - """Average image file.""" - - -def multiply_images( - dimension: typing.Literal[3, 2], - first_input: InputPathType, - output_product_image: InputPathType, - second_input_2: float | None = None, - num_threads: int | None = 1, - runner: Runner | None = None, -) -> MultiplyImagesOutputs: - """ - Multiply 2 images; 2nd image file may also be floating point numerical value, - and program will act accordingly -- i.e. read as a number. Program handles - vector and tensor images as well. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimension: 3 or 2. Image dimension (2 or 3). - first_input: Image 1. - output_product_image: Outputfname.nii.gz: the name of the resulting\ - image. - second_input_2: file or string or a float. Image 2 or multiplication\ - weight. - num_threads: Number of itk threads to use. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `MultiplyImagesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(MULTIPLY_IMAGES_METADATA) - cargs = [] - cargs.append("MultiplyImages") - cargs.append(str(dimension)) - cargs.append(execution.input_file(first_input)) - if second_input_2 is not None: - cargs.append(str(second_input_2)) - cargs.append(execution.input_file(output_product_image)) - if num_threads is not None: - cargs.append(str(num_threads)) - ret = MultiplyImagesOutputs( - root=execution.output_file("."), - output_product_image_outfile=execution.output_file(pathlib.Path(output_product_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "MULTIPLY_IMAGES_METADATA", - "MultiplyImagesOutputs", - "multiply_images", -] diff --git a/python/src/niwrap/ants/n3_bias_field_correction.py b/python/src/niwrap/ants/n3_bias_field_correction.py deleted file mode 100644 index 90589e1f1..000000000 --- a/python/src/niwrap/ants/n3_bias_field_correction.py +++ /dev/null @@ -1,156 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -N3_BIAS_FIELD_CORRECTION_METADATA = Metadata( - id="12e6ca015aa736902ad4369af67b842768a91549.boutiques", - name="N3BiasFieldCorrection", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class N3BiasFieldCorrectionOutputs(typing.NamedTuple): - """ - Output object returned when calling `n3_bias_field_correction(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_image: OutputPathType - """The bias-corrected version of the input image.""" - bias_field: OutputPathType - """The estimated bias field, if specified in the output.""" - - -def n3_bias_field_correction( - input_image: InputPathType, - output: str, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - mask_image: InputPathType | None = None, - rescale_intensities: typing.Literal[0, 1] | None = None, - weight_image: InputPathType | None = None, - shrink_factor: int | None = None, - convergence: str | None = None, - bspline_fitting: str | None = None, - histogram_sharpening: str | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> N3BiasFieldCorrectionOutputs: - """ - This N3 is a variant of the popular N3 (nonparametric nonuniform normalization) - retrospective bias correction algorithm. Based on the assumption that the - corruption of the low frequency bias field can be modeled as a convolution of - the intensity histogram by a Gaussian, the basic algorithmic protocol is to - iterate between deconvolving the intensity histogram by a Gaussian, remapping - the intensities, and then spatially smoothing this result by a B-spline modeling - of the bias field itself. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: A scalar image is expected as input for bias correction.\ - Since N3 log transforms the intensities, negative values or values\ - close to zero should be processed prior to correction. - output: The bias-corrected version of the input image and optionally\ - the estimated bias field. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, N3 tries to infer the\ - dimensionality from the input image. - mask_image: If a mask image is specified, the final bias correction is\ - only performed in the mask region. If a mask image is not specified,\ - the entire image region will be used as the mask region. Note: this\ - differs from the original N3 implementation. - rescale_intensities: This option rescales the intensity range within\ - the user-specified mask to the original [min, max] range. - weight_image: The weight image allows the user to perform a relative\ - weighting of specific voxels during the B-spline fitting. - shrink_factor: Shrink factor to resample the input image. Commonly used\ - values are <= 4. - convergence: Describes the convergence criteria with default value as\ - [50,0.0]. - bspline_fitting: Describes the parameters for B-Spline fitting.\ - Defaults are [splineDistance,4,3]. - histogram_sharpening: Describes histogram sharpening parameters;\ - defaults are [0.15,0.01,200]. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `N3BiasFieldCorrectionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(N3_BIAS_FIELD_CORRECTION_METADATA) - cargs = [] - cargs.append("N3BiasFieldCorrection") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - cargs.extend([ - "--input-image", - execution.input_file(input_image) - ]) - if mask_image is not None: - cargs.extend([ - "--mask-image", - execution.input_file(mask_image) - ]) - if rescale_intensities is not None: - cargs.extend([ - "--rescale-intensities", - str(rescale_intensities) - ]) - if weight_image is not None: - cargs.extend([ - "--weight-image", - execution.input_file(weight_image) - ]) - if shrink_factor is not None: - cargs.extend([ - "--shrink-factor", - str(shrink_factor) - ]) - if convergence is not None: - cargs.extend([ - "--convergence", - convergence - ]) - if bspline_fitting is not None: - cargs.extend([ - "--bspline-fitting", - bspline_fitting - ]) - if histogram_sharpening is not None: - cargs.extend([ - "--histogram-sharpening", - histogram_sharpening - ]) - cargs.extend([ - "--output", - output - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - ret = N3BiasFieldCorrectionOutputs( - root=execution.output_file("."), - corrected_image=execution.output_file(output), - bias_field=execution.output_file("[BIS_FIELD]"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "N3BiasFieldCorrectionOutputs", - "N3_BIAS_FIELD_CORRECTION_METADATA", - "n3_bias_field_correction", -] diff --git a/python/src/niwrap/ants/n4_bias_field_correction.py b/python/src/niwrap/ants/n4_bias_field_correction.py deleted file mode 100644 index fafb8bf1a..000000000 --- a/python/src/niwrap/ants/n4_bias_field_correction.py +++ /dev/null @@ -1,301 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -N4_BIAS_FIELD_CORRECTION_METADATA = Metadata( - id="58505f193fc8a195b3b5d96b9ba5a60657a77e6d.boutiques", - name="N4BiasFieldCorrection", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class N4BiasFieldCorrectionConvergence: - """ - -c, --convergence - [,]. Convergence - is determined by calculating the coefficient of variation between subsequent - iterations. When this value is less than the specified threshold from the - previous iteration or the maximum number of iterations is exceeded the - program terminates. Multiple resolutions can be specified by using 'x' - between the number of iterations at each resolution, e.g. 100x50x50. - """ - convergence: list[int] - convergence_threshold: float | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.convergence_threshold is not None: - cargs.append("[" + "x".join(map(str, self.convergence)) + "," + str(self.convergence_threshold) + "]") - return cargs - - -@dataclasses.dataclass -class N4BiasFieldCorrectionBsplineFitting: - """ - -b, --bspline-fitting [splineDistance,]. These options - describe the b-spline fitting parameters. The initial b-spline mesh at the - coarsest resolution is specified either as the number of elements in each - dimension, e.g. 2x2x3 for 3-D images, or it can be specified as a single - scalar parameter which describes the isotropic sizing of the mesh elements. - The latter option is typically preferred. For each subsequent level, the - spline distance decreases in half, or equivalently, the number of mesh - elements doubles Cubic splines (order = 3) are typically used. The default - setting is to employ a single mesh element over the entire domain, i.e., -b - [1x1x1,3]. - """ - spline_distance: list[float] - spline_order: int | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.spline_order is not None: - cargs.append("[" + "x".join(map(str, self.spline_distance)) + "," + str(self.spline_order) + "]") - return cargs - - -@dataclasses.dataclass -class N4BiasFieldCorrectionHistogramSharpening: - """ - -t, --histogram-sharpening - [,,]. These options - describe the histogram sharpening parameters, i.e. the deconvolution step - parameters described in the original N3 algorithm. The default values have - been shown to work fairly well. - """ - fwhm: float | None = None - wiener_noise: float | None = None - number_of_histogram_bins: int | None = None - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.fwhm is not None or self.wiener_noise is not None or self.number_of_histogram_bins is not None: - cargs.append("[" + (str(self.fwhm) if self.fwhm is not None else "") + "," + (str(self.wiener_noise) if self.wiener_noise is not None else "") + "," + (str(self.number_of_histogram_bins) if self.number_of_histogram_bins is not None else "") + "]") - return cargs - - -class N4BiasFieldCorrectionOutputs(typing.NamedTuple): - """ - Output object returned when calling `n4_bias_field_correction(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - corrected_image: OutputPathType - """The bias corrected version of the input image.""" - bias_field: OutputPathType | None - """Estimated bias field image.""" - - -def n4_bias_field_correction( - input_image: InputPathType, - corrected_image_path: str, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - shrink_factor: int | None = None, - mask_image: InputPathType | None = None, - rescale_intensities: typing.Literal[0, 1] | None = None, - weight_image: InputPathType | None = None, - convergence: N4BiasFieldCorrectionConvergence | None = None, - bspline_fitting: N4BiasFieldCorrectionBsplineFitting | None = None, - histogram_sharpening: N4BiasFieldCorrectionHistogramSharpening | None = None, - verbose: typing.Literal[0, 1] | None = None, - bias_field_path: str | None = None, - runner: Runner | None = None, -) -> N4BiasFieldCorrectionOutputs: - """ - N4 is a variant of the popular N3 (nonparameteric nonuniform normalization) - retrospective bias correction algorithm. Based on the assumption that the - corruption of the low frequency bias field can be modeled as a convolution of - the intensity histogram by a Gaussian, the basic algorithmic protocol is to - iterate between deconvolving the intensity histogram by a Gaussian, remapping - the intensities, and then spatially smoothing this result by a B-spline modeling - of the bias field itself. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: -i, --input-image inputImageFilename. A scalar image is\ - expected as input for bias correction. Since N4 log transforms the\ - intensities, negative values or values close to zero should be\ - processed prior to correction. - corrected_image_path: The bias corrected version of the input image. - image_dimensionality: -d, --image-dimensionality 2/3/4. This option\ - forces the image to be treated as a specified-dimensional image. If not\ - specified, N4 tries to infer the dimensionality from the input image. - shrink_factor: -s, --shrink-factor 1/2/3/(4)/... Running N4 on large\ - images can be time consuming. To lessen computation time, the input\ - image can be resampled. The shrink factor, specified as a single\ - integer, describes this resampling. Shrink factors <= 4 are commonly\ - used. Note that the shrink factor is only applied to the first two or\ - three dimensions which we assume are spatial. - mask_image: -x, --mask-image maskImageFilename. If a mask image is\ - specified, the final bias correction is only performed in the mask\ - region. If a weight image is not specified, only intensity values\ - inside the masked region are used during the execution of the\ - algorithm. If a weight image is specified, only the non-zero weights\ - are used in the execution of the algorithm although the mask region\ - defines where bias correction is performed in the final output.\ - Otherwise bias correction occurs over the entire image domain. See also\ - the option description for the weight image. If a mask image is *not*\ - specified then the entire image region will be used as the mask region.\ - Note that this is different than the N3 implementation which uses the\ - results of Otsu thresholding to define a mask. However, this leads to\ - unknown anatomical regions being included and excluded during the bias\ - correction. - rescale_intensities: -r, --rescale-intensities 0/(1). At each\ - iteration, a new intensity mapping is calculated and applied but there\ - is nothing which constrains the new intensity range to be within\ - certain values. The result is that the range can "drift" from the\ - original at each iteration. This option rescales to the [min,max] range\ - of the original image intensities within the user-specified mask. A\ - mask is required to perform rescaling. - weight_image: -w, --weight-image weightImageFilename. The weight image\ - allows the user to perform a relative weighting of specific voxels\ - during the B-spline fitting. For example, some studies have shown that\ - N3 performed on white matter segmentations improves performance. If one\ - has a spatial probability map of the white matter, one can use this map\ - to weight the b-spline fitting towards those voxels which are more\ - probabilistically classified as white matter. See also the option\ - description for the mask image. - convergence: -c, --convergence\ - [,].\ - Convergence is determined by calculating the coefficient of variation\ - between subsequent iterations. When this value is less than the\ - specified threshold from the previous iteration or the maximum number\ - of iterations is exceeded the program terminates. Multiple resolutions\ - can be specified by using 'x' between the number of iterations at each\ - resolution, e.g. 100x50x50. - bspline_fitting: -b, --bspline-fitting\ - [splineDistance,]. These options describe the b-spline\ - fitting parameters. The initial b-spline mesh at the coarsest\ - resolution is specified either as the number of elements in each\ - dimension, e.g. 2x2x3 for 3-D images, or it can be specified as a\ - single scalar parameter which describes the isotropic sizing of the\ - mesh elements. The latter option is typically preferred. For each\ - subsequent level, the spline distance decreases in half, or\ - equivalently, the number of mesh elements doubles Cubic splines (order\ - = 3) are typically used. The default setting is to employ a single mesh\ - element over the entire domain, i.e., -b [1x1x1,3]. - histogram_sharpening: -t, --histogram-sharpening\ - [,,]. These\ - options describe the histogram sharpening parameters, i.e. the\ - deconvolution step parameters described in the original N3 algorithm.\ - The default values have been shown to work fairly well. - verbose: Verbose output. - bias_field_path: Estimated bias field image. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `N4BiasFieldCorrectionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(N4_BIAS_FIELD_CORRECTION_METADATA) - cargs = [] - cargs.append("N4BiasFieldCorrection") - if image_dimensionality is not None: - cargs.extend([ - "--image-dimensionality", - str(image_dimensionality) - ]) - if shrink_factor is not None: - cargs.extend([ - "--shrink-factor", - str(shrink_factor) - ]) - if mask_image is not None: - cargs.extend([ - "--mask-image", - execution.input_file(mask_image) - ]) - if rescale_intensities is not None: - cargs.extend([ - "--rescale-intensities", - str(rescale_intensities) - ]) - if weight_image is not None: - cargs.extend([ - "--weight-image", - execution.input_file(weight_image) - ]) - if convergence is not None: - cargs.extend([ - "--convergence", - *convergence.run(execution) - ]) - if bspline_fitting is not None: - cargs.extend([ - "--bspline-fitting", - *bspline_fitting.run(execution) - ]) - if histogram_sharpening is not None: - cargs.extend([ - "--histogram-sharpening", - *histogram_sharpening.run(execution) - ]) - if verbose is not None: - cargs.extend([ - "--verbose", - str(verbose) - ]) - cargs.extend([ - "--input-image", - execution.input_file(input_image) - ]) - cargs.append("--output") - if bias_field_path is not None: - cargs.append("[" + corrected_image_path + "," + bias_field_path + "]") - ret = N4BiasFieldCorrectionOutputs( - root=execution.output_file("."), - corrected_image=execution.output_file(corrected_image_path), - bias_field=execution.output_file(bias_field_path) if (bias_field_path is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "N4BiasFieldCorrectionBsplineFitting", - "N4BiasFieldCorrectionConvergence", - "N4BiasFieldCorrectionHistogramSharpening", - "N4BiasFieldCorrectionOutputs", - "N4_BIAS_FIELD_CORRECTION_METADATA", - "n4_bias_field_correction", -] diff --git a/python/src/niwrap/ants/non_local_super_resolution.py b/python/src/niwrap/ants/non_local_super_resolution.py deleted file mode 100644 index 8be241276..000000000 --- a/python/src/niwrap/ants/non_local_super_resolution.py +++ /dev/null @@ -1,148 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -NON_LOCAL_SUPER_RESOLUTION_METADATA = Metadata( - id="6ff1af6734242879ff8b30bf0db9b599017faa19.boutiques", - name="NonLocalSuperResolution", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class NonLocalSuperResolutionOutputs(typing.NamedTuple): - """ - Output object returned when calling `non_local_super_resolution(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - superresoluted_output: OutputPathType - """The superresoluted output image.""" - - -def non_local_super_resolution( - input_image: InputPathType, - output: InputPathType, - image_dimensionality: typing.Literal[2, 3, 4] | None = None, - interpolated_image: InputPathType | None = None, - reference_image: InputPathType | None = None, - patch_radius: typing.Literal["1", "1x1x1"] | None = None, - search_radius: typing.Literal["3", "3x3x3"] | None = None, - intensity_difference_sigma: float | None = 1.0, - patch_similarity_sigma: float | None = 1.0, - scale_levels: str | None = "32x16x8x2x1", - interpolation: typing.Literal["Linear", "NearestNeighbor", "Gaussian", "BSpline", "CosineWindowedSinc", "WelchWindowedSinc", "HammingWindowedSinc", "LanczosWindowedSinc"] | None = None, - verbose: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> NonLocalSuperResolutionOutputs: - """ - Non-local super resolution described in the papers by JV Manjon et al., focusing - on MRI superresolution using self-similarity and image priors. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - input_image: A low-resolution input image to be superresoluted. - output: The output consists of the noise corrected version of the input\ - image. Optionally, one can also output the estimated noise image. - image_dimensionality: This option forces the image to be treated as a\ - specified-dimensional image. If not specified, the program tries to\ - infer the dimensionality from the input image. - interpolated_image: An interpolated version of the low-resolution image\ - (such as B-spline). Specify either this option or a high-resolution\ - multi-modal counterpart (cf the -k option). - reference_image: A high-resolution reference multi-modal image. Assumed\ - to be in the same space as the low-resolution input image. Specify\ - either this option or an interpolated version (cf the -j option). - patch_radius: Patch radius. Default = 1x1x1. - search_radius: Search radius. Default = 3x3x3. - intensity_difference_sigma: Intensity difference sigma. Default = 1.0. - patch_similarity_sigma: Patch similarity sigma. Default = 1.0. - scale_levels: Scale levels. Default = 32x16x8x2x1. - interpolation: Several interpolation options are available in ITK. - verbose: Verbose output. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `NonLocalSuperResolutionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(NON_LOCAL_SUPER_RESOLUTION_METADATA) - cargs = [] - cargs.append("NonLocalSuperResolution") - if image_dimensionality is not None: - cargs.extend([ - "-d", - str(image_dimensionality) - ]) - cargs.extend([ - "-i", - execution.input_file(input_image) - ]) - if interpolated_image is not None: - cargs.extend([ - "-j", - execution.input_file(interpolated_image) - ]) - if reference_image is not None: - cargs.extend([ - "-k", - execution.input_file(reference_image) - ]) - if patch_radius is not None: - cargs.extend([ - "-p", - patch_radius - ]) - if search_radius is not None: - cargs.extend([ - "-r", - search_radius - ]) - if intensity_difference_sigma is not None: - cargs.extend([ - "-g", - str(intensity_difference_sigma) - ]) - if patch_similarity_sigma is not None: - cargs.extend([ - "-t", - str(patch_similarity_sigma) - ]) - if scale_levels is not None: - cargs.extend([ - "-s", - scale_levels - ]) - if interpolation is not None: - cargs.extend([ - "-n", - interpolation - ]) - cargs.extend([ - "-o", - execution.input_file(output) - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - ret = NonLocalSuperResolutionOutputs( - root=execution.output_file("."), - superresoluted_output=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "NON_LOCAL_SUPER_RESOLUTION_METADATA", - "NonLocalSuperResolutionOutputs", - "non_local_super_resolution", -] diff --git a/python/src/niwrap/ants/paste_image_into_image.py b/python/src/niwrap/ants/paste_image_into_image.py deleted file mode 100644 index 1249b5529..000000000 --- a/python/src/niwrap/ants/paste_image_into_image.py +++ /dev/null @@ -1,92 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PASTE_IMAGE_INTO_IMAGE_METADATA = Metadata( - id="473380596b87ce0da9928dabd1961225e23dd0a4.boutiques", - name="PasteImageIntoImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class PasteImageIntoImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `paste_image_into_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType - """The final output image with the input image pasted onto the canvas.""" - - -def paste_image_into_image( - image_dimension: int, - input_canvas_image: InputPathType, - input_image: InputPathType, - output_image: InputPathType, - start_index: str, - background_label: int | None = 0, - paint_over_non_background_voxels: typing.Literal[0, 1, 2] | None = 0, - conflict_label: int | None = -1, - runner: Runner | None = None, -) -> PasteImageIntoImageOutputs: - """ - Paste the input image into the input canvas image. Depending on parameters, it - can replace or merge existing voxel values. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Specify the dimension of the images. - input_canvas_image: The canvas image on which the input image will be\ - pasted. - input_image: The image to be pasted onto the canvas. - output_image: The resulting image after pasting. - start_index: The starting index where the input image will be pasted on\ - the canvas. - background_label: The label value considered as background. - paint_over_non_background_voxels: Defines behavior when the input image\ - voxel is non-background and the corresponding canvas voxel is\ - background: 0 - leave as is, 1 - replace with input voxel value, 2 -\ - replace with conflict label. - conflict_label: The label value used for conflicting non-background\ - voxels if 'paintOverNonBackgroundVoxels' is set to 2. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PasteImageIntoImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PASTE_IMAGE_INTO_IMAGE_METADATA) - cargs = [] - cargs.append("PasteImageIntoImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_canvas_image)) - cargs.append(execution.input_file(input_image)) - cargs.append(execution.input_file(output_image)) - cargs.append(start_index) - if background_label is not None: - cargs.append(str(background_label)) - if paint_over_non_background_voxels is not None: - cargs.append(str(paint_over_non_background_voxels)) - if conflict_label is not None: - cargs.append(str(conflict_label)) - ret = PasteImageIntoImageOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PASTE_IMAGE_INTO_IMAGE_METADATA", - "PasteImageIntoImageOutputs", - "paste_image_into_image", -] diff --git a/python/src/niwrap/ants/print_header.py b/python/src/niwrap/ants/print_header.py deleted file mode 100644 index 1718d6d91..000000000 --- a/python/src/niwrap/ants/print_header.py +++ /dev/null @@ -1,67 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -PRINT_HEADER_METADATA = Metadata( - id="514e4dbae6f3b5a425925fca62d2ade89ff0b0c2.boutiques", - name="PrintHeader", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class PrintHeaderOutputs(typing.NamedTuple): - """ - Output object returned when calling `print_header(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output: OutputPathType - """The printed header information from the specified image.""" - - -def print_header( - image: InputPathType, - what_information: typing.Literal[0, 1, 2, 3, 4] | None = None, - runner: Runner | None = None, -) -> PrintHeaderOutputs: - """ - A utility to print header information from an image file. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image: The image file to extract header information from. Supported\ - extension: .ext. - what_information: Specify the type of information to print: 0 for\ - origin, 1 for spacing, 2 for size, 3 for index, 4 for direction. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `PrintHeaderOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(PRINT_HEADER_METADATA) - cargs = [] - cargs.append("PrintHeader") - cargs.append(execution.input_file(image)) - if what_information is not None: - cargs.append(str(what_information)) - ret = PrintHeaderOutputs( - root=execution.output_file("."), - output=execution.output_file("header_info.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "PRINT_HEADER_METADATA", - "PrintHeaderOutputs", - "print_header", -] diff --git a/python/src/niwrap/ants/rebase_tensor_image.py b/python/src/niwrap/ants/rebase_tensor_image.py deleted file mode 100644 index 0888dce3a..000000000 --- a/python/src/niwrap/ants/rebase_tensor_image.py +++ /dev/null @@ -1,75 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -REBASE_TENSOR_IMAGE_METADATA = Metadata( - id="cb7dc4431e44610b96f7d5021a64651fd63ad535.boutiques", - name="RebaseTensorImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class RebaseTensorImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `rebase_tensor_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - rebased_image: OutputPathType - """The rebased tensor image.""" - - -def rebase_tensor_image( - dimension: int, - infile: InputPathType, - outfile: InputPathType, - method: typing.Literal["PHYSICAL", "LOCAL"], - reference: InputPathType | None = None, - runner: Runner | None = None, -) -> RebaseTensorImageOutputs: - """ - Rebase Tensor Image using specified dimensionality and method. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimension: The dimensionality of the input image. - infile: The input image file. - outfile: The output image file. - method: Method of rebasing the tensor image. - reference: Reference image file (required if PHYSICAL or LOCAL method\ - is chosen). - runner: Command runner. - Returns: - NamedTuple of outputs (described in `RebaseTensorImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(REBASE_TENSOR_IMAGE_METADATA) - cargs = [] - cargs.append("RebaseTensorImage") - cargs.append(str(dimension)) - cargs.append(execution.input_file(infile)) - cargs.append(execution.input_file(outfile)) - cargs.append(method) - if reference is not None: - cargs.append(execution.input_file(reference)) - ret = RebaseTensorImageOutputs( - root=execution.output_file("."), - rebased_image=execution.output_file(pathlib.Path(outfile).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "REBASE_TENSOR_IMAGE_METADATA", - "RebaseTensorImageOutputs", - "rebase_tensor_image", -] diff --git a/python/src/niwrap/ants/resample_image.py b/python/src/niwrap/ants/resample_image.py deleted file mode 100644 index 0cbb14fab..000000000 --- a/python/src/niwrap/ants/resample_image.py +++ /dev/null @@ -1,83 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -RESAMPLE_IMAGE_METADATA = Metadata( - id="09cbfa81905a40fb69e7164887ae36302a83bb75.boutiques", - name="ResampleImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ResampleImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `resample_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - resampled_output_image: OutputPathType - """The resultant image after resampling.""" - - -def resample_image( - image_dimension: int, - input_image: InputPathType, - output_image: InputPathType, - size_spacing: str, - interpolate_type: typing.Literal["0", "1", "2", "3", "4"] | None = None, - pixeltype: typing.Literal["0", "1", "2", "3", "4", "5", "6", "7"] | None = None, - runner: Runner | None = None, -) -> ResampleImageOutputs: - """ - ResampleImage is a tool used to resample images to specified sizes and spacings, - using various interpolation methods and pixel types. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimension of the image to be resampled. - input_image: The image file to be resampled. - output_image: The output image file after resampling. - size_spacing: Resampling size and spacing specification, e.g., 'MxNxO'. - interpolate_type: Specifies the interpolation type. 0: linear\ - (default), 1: nearest-neighbor, 2: gaussian, 3: windowedSinc, 4:\ - B-Spline. - pixeltype: Specifies the pixel type of the output image. 0: char, 1:\ - unsigned char, 2: short, 3: unsigned short, 4: int, 5: unsigned int, 6:\ - float (default), 7: double. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ResampleImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(RESAMPLE_IMAGE_METADATA) - cargs = [] - cargs.append("ResampleImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - cargs.append(execution.input_file(output_image)) - cargs.append(size_spacing) - if interpolate_type is not None: - cargs.append(interpolate_type) - if pixeltype is not None: - cargs.append(pixeltype) - ret = ResampleImageOutputs( - root=execution.output_file("."), - resampled_output_image=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "RESAMPLE_IMAGE_METADATA", - "ResampleImageOutputs", - "resample_image", -] diff --git a/python/src/niwrap/ants/sccan.py b/python/src/niwrap/ants/sccan.py deleted file mode 100644 index 354366094..000000000 --- a/python/src/niwrap/ants/sccan.py +++ /dev/null @@ -1,257 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SCCAN_METADATA = Metadata( - id="71a35247d8acdc6b81550ffbec697f0dc7665a22.boutiques", - name="sccan", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SccanOutputs(typing.NamedTuple): - """ - Output object returned when calling `sccan(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - - -def sccan( - output: str | None = None, - n_permutations: int | None = None, - smoother: int | None = None, - row_sparseness: int | None = None, - iterations: int | None = None, - n_eigenvectors: int | None = None, - robustify: int | None = None, - covering: int | None = None, - uselong: int | None = None, - l1: float | None = None, - pclusterthresh: float | None = None, - qclusterthresh: float | None = None, - ridge_cca: float | None = None, - initialization: str | None = None, - initialization2: str | None = None, - mask: InputPathType | None = None, - mask2: InputPathType | None = None, - partial_scca_option: str | None = None, - prior_weight: float | None = None, - get_small: float | None = None, - verbose: float | None = None, - imageset_to_matrix: str | None = None, - timeseriesimage_to_matrix: str | None = None, - vector_to_image: str | None = None, - imageset_to_projections: str | None = None, - scca: str | None = None, - svd: str | None = None, - runner: Runner | None = None, -) -> SccanOutputs: - """ - A tool for sparse statistical analysis on images : scca, pscca (with options), - mscca. Can also convert an imagelist/mask pair to a binary matrix image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - output: Output dependent on which option is called. - n_permutations: Number of permutations to use in scca. - smoother: Smoothing function for variates. - row_sparseness: Row sparseness - if (+) then keep values (+) otherwise\ - allow +/- values --- always L1. - iterations: Max iterations for scca optimization (min 20). - n_eigenvectors: Number of eigenvectors to compute in scca/spca. - robustify: Rank-based scca. - covering: Try to make the decomposition cover the whole domain, if\ - possible. - uselong: Use longitudinal formulation (> 0) or not (<= 0). - l1: Use l1 (> 0) or l0 (< 0) penalty, also sets gradient step size. - pclusterthresh: Cluster threshold on view P. - qclusterthresh: Cluster threshold on view Q. - ridge_cca: Ridge cca. - initialization: Initialization file list for Eigenanatomy - must also\ - pass mask option. - initialization2: Initialization file list for SCCAN-Eigenanatomy - must\ - also pass mask option. - mask: Mask file for Eigenanatomy initialization. - mask2: Mask file for Eigenanatomy initialization 2. - partial_scca_option: Choices for pscca: PQ, PminusRQ, PQminusR,\ - PminusRQminusR. - prior_weight: Scalar value weight on prior between 0 (prior is weak)\ - and 1 (prior is strong). Only engaged if initialization is used. - get_small: Find smallest eigenvectors. - verbose: Set whether output is verbose. - imageset_to_matrix: Takes a list of image files names (one per line)\ - and converts it to a 2D matrix/image in binary or csv format. - timeseriesimage_to_matrix: Takes a timeseries (4D) image and converts\ - it to a 2D matrix csv format. - vector_to_image: Converts the 1st column vector in a csv file back to\ - an image. - imageset_to_projections: Takes a list of image and projection files\ - names and writes them to a csv file. - scca: Matrix-based scca operations for 2 and 3 views. - svd: A sparse SVD implementation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SccanOutputs`). - """ - if iterations is not None and not (20 <= iterations): - raise ValueError(f"'iterations' must be greater than 20 <= x but was {iterations}") - runner = runner or get_global_runner() - execution = runner.start_execution(SCCAN_METADATA) - cargs = [] - cargs.append("sccan") - if output is not None: - cargs.extend([ - "-o", - output - ]) - if n_permutations is not None: - cargs.extend([ - "-p", - str(n_permutations) - ]) - if smoother is not None: - cargs.extend([ - "-s", - str(smoother) - ]) - if row_sparseness is not None: - cargs.extend([ - "-z", - str(row_sparseness) - ]) - if iterations is not None: - cargs.extend([ - "-i", - str(iterations) - ]) - if n_eigenvectors is not None: - cargs.extend([ - "-n", - str(n_eigenvectors) - ]) - if robustify is not None: - cargs.extend([ - "-r", - str(robustify) - ]) - if covering is not None: - cargs.extend([ - "-c", - str(covering) - ]) - if uselong is not None: - cargs.extend([ - "-g", - str(uselong) - ]) - if l1 is not None: - cargs.extend([ - "-l", - str(l1) - ]) - if pclusterthresh is not None: - cargs.extend([ - "--PClusterThresh", - str(pclusterthresh) - ]) - if qclusterthresh is not None: - cargs.extend([ - "--QClusterThresh", - str(qclusterthresh) - ]) - if ridge_cca is not None: - cargs.extend([ - "-e", - str(ridge_cca) - ]) - if initialization is not None: - cargs.extend([ - "--initialization", - initialization - ]) - if initialization2 is not None: - cargs.extend([ - "--initialization2", - initialization2 - ]) - if mask is not None: - cargs.extend([ - "--mask", - execution.input_file(mask) - ]) - if mask2 is not None: - cargs.extend([ - "--mask2", - execution.input_file(mask2) - ]) - if partial_scca_option is not None: - cargs.extend([ - "--partial-scca-option", - partial_scca_option - ]) - if prior_weight is not None: - cargs.extend([ - "--prior-weight", - str(prior_weight) - ]) - if get_small is not None: - cargs.extend([ - "--get-small", - str(get_small) - ]) - if verbose is not None: - cargs.extend([ - "-v", - str(verbose) - ]) - if imageset_to_matrix is not None: - cargs.extend([ - "--imageset-to-matrix", - imageset_to_matrix - ]) - if timeseriesimage_to_matrix is not None: - cargs.extend([ - "--timeseriesimage-to-matrix", - timeseriesimage_to_matrix - ]) - if vector_to_image is not None: - cargs.extend([ - "--vector-to-image", - vector_to_image - ]) - if imageset_to_projections is not None: - cargs.extend([ - "--imageset-to-projections", - imageset_to_projections - ]) - if scca is not None: - cargs.extend([ - "--scca", - scca - ]) - if svd is not None: - cargs.extend([ - "--svd", - svd - ]) - ret = SccanOutputs( - root=execution.output_file("."), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SCCAN_METADATA", - "SccanOutputs", - "sccan", -] diff --git a/python/src/niwrap/ants/set_spacing.py b/python/src/niwrap/ants/set_spacing.py deleted file mode 100644 index 9983177e0..000000000 --- a/python/src/niwrap/ants/set_spacing.py +++ /dev/null @@ -1,71 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SET_SPACING_METADATA = Metadata( - id="b77674b8a0a6a1121f61d0814da8fcf1ba54b3f8.boutiques", - name="SetSpacing", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SetSpacingOutputs(typing.NamedTuple): - """ - Output object returned when calling `set_spacing(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """The output image with the specified spacing.""" - - -def set_spacing( - dimension: int, - input_file: InputPathType, - output_file: InputPathType, - spacing: list[float], - runner: Runner | None = None, -) -> SetSpacingOutputs: - """ - A tool to set the spacing of an image in each dimension. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - dimension: The dimensionality of the image (e.g., 2 or 3). - input_file: The input image file in HDR format. - output_file: The output image file in NII format. - spacing: Spacing values for each dimension. Requires SpacingX,\ - SpacingY, and optionally SpacingZ. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SetSpacingOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SET_SPACING_METADATA) - cargs = [] - cargs.append("SetSpacing") - cargs.append(str(dimension)) - cargs.append(execution.input_file(input_file)) - cargs.append(execution.input_file(output_file)) - cargs.extend(map(str, spacing)) - ret = SetSpacingOutputs( - root=execution.output_file("."), - output_image=execution.output_file(pathlib.Path(output_file).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SET_SPACING_METADATA", - "SetSpacingOutputs", - "set_spacing", -] diff --git a/python/src/niwrap/ants/simple_syn_registration.py b/python/src/niwrap/ants/simple_syn_registration.py deleted file mode 100644 index ade005623..000000000 --- a/python/src/niwrap/ants/simple_syn_registration.py +++ /dev/null @@ -1,73 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SIMPLE_SYN_REGISTRATION_METADATA = Metadata( - id="8bdec8bc3a221887858c098adc61e63838dc3139.boutiques", - name="simpleSynRegistration", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SimpleSynRegistrationOutputs(typing.NamedTuple): - """ - Output object returned when calling `simple_syn_registration(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - registered_image: OutputPathType - """The output registered image.""" - transform_matrix: OutputPathType - """The output transformation matrix.""" - - -def simple_syn_registration( - fixed_image: InputPathType, - moving_image: InputPathType, - initial_transform: str, - output_prefix: str, - runner: Runner | None = None, -) -> SimpleSynRegistrationOutputs: - """ - A simple SyN registration tool. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - fixed_image: The fixed image for registration. - moving_image: The moving image to be registered. - initial_transform: The initial transform for registration. - output_prefix: Prefix for the output file name without any extension. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SimpleSynRegistrationOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SIMPLE_SYN_REGISTRATION_METADATA) - cargs = [] - cargs.append("simpleSynRegistration") - cargs.append(execution.input_file(fixed_image) + ",") - cargs.append(execution.input_file(moving_image) + ",") - cargs.append(initial_transform + ",") - cargs.append(output_prefix) - ret = SimpleSynRegistrationOutputs( - root=execution.output_file("."), - registered_image=execution.output_file(output_prefix + "Registered.nii.gz"), - transform_matrix=execution.output_file(output_prefix + "Transform.mat"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SIMPLE_SYN_REGISTRATION_METADATA", - "SimpleSynRegistrationOutputs", - "simple_syn_registration", -] diff --git a/python/src/niwrap/ants/simulate_displacement_field.py b/python/src/niwrap/ants/simulate_displacement_field.py deleted file mode 100644 index 291b5227e..000000000 --- a/python/src/niwrap/ants/simulate_displacement_field.py +++ /dev/null @@ -1,143 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SIMULATE_DISPLACEMENT_FIELD_METADATA = Metadata( - id="b4b4d74766ee9ec6eddb1c050e1dc66d6fc3cd4d.boutiques", - name="SimulateDisplacementField", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class SimulateDisplacementFieldBsplineOptions: - number_of_fitting_levels: int | None = 4 - """Number of fitting levels for BSpline.""" - number_of_control_points: int | None = 4 - """Number of control points for BSpline.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.number_of_fitting_levels is not None: - cargs.append(str(self.number_of_fitting_levels)) - if self.number_of_control_points is not None: - cargs.append(str(self.number_of_control_points)) - return cargs - - -@dataclasses.dataclass -class SimulateDisplacementFieldExponentialOptions: - smoothing_standard_deviation: float | None = 4 - """Smoothing standard deviation for Exponential.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - if self.smoothing_standard_deviation is not None: - cargs.append(str(self.smoothing_standard_deviation)) - return cargs - - -class SimulateDisplacementFieldOutputs(typing.NamedTuple): - """ - Output object returned when calling `simulate_displacement_field(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_displacement_field: OutputPathType - """The simulated displacement field.""" - - -def simulate_displacement_field( - image_dimension: int, - displacement_field_type: typing.Literal["BSpline", "Exponential"], - domain_image: InputPathType, - output_field: InputPathType, - number_of_random_points: int | None = 1000, - standard_deviation_displacement_field: float | None = 10, - enforce_stationary_boundary: int | None = 1, - displacement_specific_options: typing.Union[SimulateDisplacementFieldBsplineOptions, SimulateDisplacementFieldExponentialOptions] | None = None, - runner: Runner | None = None, -) -> SimulateDisplacementFieldOutputs: - """ - Simulate displacement fields using various methods such as BSpline or - Exponential. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimensionality of the image. - displacement_field_type: Type of displacement field to simulate. - domain_image: Image defining the domain for the displacement field. - output_field: Path to save the output displacement field. - number_of_random_points: Number of random points to use in the\ - simulation. - standard_deviation_displacement_field: Standard deviation for the\ - displacement field. - enforce_stationary_boundary: Boolean flag indicating whether to enforce\ - stationary boundary. - displacement_specific_options: Options specific to the type of\ - displacement field simulation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SimulateDisplacementFieldOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SIMULATE_DISPLACEMENT_FIELD_METADATA) - cargs = [] - cargs.append("SimulateDisplacementField") - cargs.append(str(image_dimension)) - cargs.append(displacement_field_type) - cargs.append(execution.input_file(domain_image)) - cargs.append(execution.input_file(output_field)) - if number_of_random_points is not None: - cargs.append(str(number_of_random_points)) - if standard_deviation_displacement_field is not None: - cargs.append(str(standard_deviation_displacement_field)) - if enforce_stationary_boundary is not None: - cargs.append(str(enforce_stationary_boundary)) - if displacement_specific_options is not None: - cargs.extend(displacement_specific_options.run(execution)) - ret = SimulateDisplacementFieldOutputs( - root=execution.output_file("."), - output_displacement_field=execution.output_file(pathlib.Path(output_field).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SIMULATE_DISPLACEMENT_FIELD_METADATA", - "SimulateDisplacementFieldBsplineOptions", - "SimulateDisplacementFieldExponentialOptions", - "SimulateDisplacementFieldOutputs", - "simulate_displacement_field", -] diff --git a/python/src/niwrap/ants/smooth_displacement_field.py b/python/src/niwrap/ants/smooth_displacement_field.py deleted file mode 100644 index e14b515b4..000000000 --- a/python/src/niwrap/ants/smooth_displacement_field.py +++ /dev/null @@ -1,95 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SMOOTH_DISPLACEMENT_FIELD_METADATA = Metadata( - id="74242e4a08e876a4821008fd823b0b832ab0e019.boutiques", - name="SmoothDisplacementField", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SmoothDisplacementFieldOutputs(typing.NamedTuple): - """ - Output object returned when calling `smooth_displacement_field(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - smoothed_field: OutputPathType - """The output file containing the smoothed displacement field.""" - confidence_image_out: OutputPathType | None - """The output file containing confidence information from the smoothing - process.""" - - -def smooth_displacement_field( - image_dimension: int, - input_field: InputPathType, - output_field: InputPathType, - variance_or_mesh_size_base_level: float, - number_of_levels: int | None = 1, - spline_order: int | None = 3, - estimate_inverse: typing.Literal[0, 1] | None = 0, - confidence_image: InputPathType | None = None, - runner: Runner | None = None, -) -> SmoothDisplacementFieldOutputs: - """ - SmoothDisplacementField applies smoothing to a displacement field over a - specified number of levels with optional parameters for spline order, inverse - estimation, and confidence image output. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input displacement field. - input_field: The input displacement field file. - output_field: The output file for the smoothed displacement field. - variance_or_mesh_size_base_level: The variance for Gaussian smoothing\ - or mesh size at the base level for B-spline smoothing. - number_of_levels: The number of levels for multi-resolution smoothing. - spline_order: The order of the spline for B-spline smoothing. - estimate_inverse: Estimate the inverse of the displacement field if set\ - to 1. - confidence_image: Optional confidence image output of the smoothing\ - process. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SmoothDisplacementFieldOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SMOOTH_DISPLACEMENT_FIELD_METADATA) - cargs = [] - cargs.append("SmoothDisplacementField") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_field)) - cargs.append(execution.input_file(output_field)) - cargs.append(str(variance_or_mesh_size_base_level)) - if number_of_levels is not None: - cargs.append(str(number_of_levels)) - if spline_order is not None: - cargs.append(str(spline_order)) - if estimate_inverse is not None: - cargs.append(str(estimate_inverse)) - if confidence_image is not None: - cargs.append(execution.input_file(confidence_image)) - ret = SmoothDisplacementFieldOutputs( - root=execution.output_file("."), - smoothed_field=execution.output_file(pathlib.Path(output_field).name), - confidence_image_out=execution.output_file(pathlib.Path(confidence_image).name) if (confidence_image is not None) else None, - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SMOOTH_DISPLACEMENT_FIELD_METADATA", - "SmoothDisplacementFieldOutputs", - "smooth_displacement_field", -] diff --git a/python/src/niwrap/ants/smooth_image.py b/python/src/niwrap/ants/smooth_image.py deleted file mode 100644 index c008636b7..000000000 --- a/python/src/niwrap/ants/smooth_image.py +++ /dev/null @@ -1,82 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SMOOTH_IMAGE_METADATA = Metadata( - id="c743ecca2407454064c39d3994944e2822b5560a.boutiques", - name="SmoothImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SmoothImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `smooth_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - smoothed_image: OutputPathType - """The output smoothed image file.""" - - -def smooth_image( - image_dimension: int, - image_ext: InputPathType, - smoothing_sigma: str, - out_image_ext: str, - sigma_units: typing.Literal[0, 1] | None = None, - median_filter: typing.Literal[0, 1] | None = None, - runner: Runner | None = None, -) -> SmoothImageOutputs: - """ - SmoothImage allows smoothing of images with adjustable sigma values, offering - optional median filtering functionality. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Specifies the dimensionality of the image. - image_ext: The input image file to be smoothed. - smoothing_sigma: The sigma value for smoothing. A separate sigma may be\ - specified for each dimension, e.g., '1.5x1x2'. - out_image_ext: The output smoothed image file. - sigma_units: Determines if sigma is in spacing units (1) or not (0).\ - Default is 0. - median_filter: Whether to use median filter. Default is 0. If using\ - median filter, sigma represents the radius in voxels. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SmoothImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SMOOTH_IMAGE_METADATA) - cargs = [] - cargs.append("SmoothImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(image_ext)) - cargs.append(smoothing_sigma) - cargs.append(out_image_ext) - if sigma_units is not None: - cargs.append(str(sigma_units)) - if median_filter is not None: - cargs.append(str(median_filter)) - ret = SmoothImageOutputs( - root=execution.output_file("."), - smoothed_image=execution.output_file(out_image_ext), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SMOOTH_IMAGE_METADATA", - "SmoothImageOutputs", - "smooth_image", -] diff --git a/python/src/niwrap/ants/super_resolution.py b/python/src/niwrap/ants/super_resolution.py deleted file mode 100644 index 2bc37e3e4..000000000 --- a/python/src/niwrap/ants/super_resolution.py +++ /dev/null @@ -1,86 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SUPER_RESOLUTION_METADATA = Metadata( - id="971ff863d798c743fcbcf153281a68f737955b2e.boutiques", - name="SuperResolution", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SuperResolutionOutputs(typing.NamedTuple): - """ - Output object returned when calling `super_resolution(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - super_resolved_image: OutputPathType - """The output super-resolved image file.""" - - -def super_resolution( - image_dimension: int, - output_image: InputPathType, - domain_image: InputPathType, - gradient_sigma: float, - mesh_size: float, - number_of_levels: int, - input_image_files: list[InputPathType], - runner: Runner | None = None, -) -> SuperResolutionOutputs: - """ - The SuperResolution tool enhances the spatial resolution of input images. The - 'gradientSigma' parameter is used in calculating the gradient magnitude of the - input images for weighting the voxel points during fitting. If a negative - 'gradient' sigma is specified then no weighting is used. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Specifies the dimensionality of the input images\ - (e.g., 2 for 2D images, 3 for 3D images). - output_image: The file path for the output super-resolved image. - domain_image: The domain image is used as the template space for the\ - alignment of input images. - gradient_sigma: The sigma used for calculating the gradient magnitude\ - of input images. If negative, no weighting is applied. - mesh_size: The size of the mesh used in fitting. - number_of_levels: The number of resolution levels to process. - input_image_files: List of paths to input images to be processed for\ - super resolution. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SuperResolutionOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SUPER_RESOLUTION_METADATA) - cargs = [] - cargs.append("SuperResolution") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(output_image)) - cargs.append(execution.input_file(domain_image)) - cargs.append(str(gradient_sigma)) - cargs.append(str(mesh_size)) - cargs.append(str(number_of_levels)) - cargs.extend([execution.input_file(f) for f in input_image_files]) - ret = SuperResolutionOutputs( - root=execution.output_file("."), - super_resolved_image=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SUPER_RESOLUTION_METADATA", - "SuperResolutionOutputs", - "super_resolution", -] diff --git a/python/src/niwrap/ants/surface_based_smoothing.py b/python/src/niwrap/ants/surface_based_smoothing.py deleted file mode 100644 index e702eacc7..000000000 --- a/python/src/niwrap/ants/surface_based_smoothing.py +++ /dev/null @@ -1,76 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURFACE_BASED_SMOOTHING_METADATA = Metadata( - id="0f212837e6cfdb7d79585c7f58fe041aca5a9ef1.boutiques", - name="SurfaceBasedSmoothing", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SurfaceBasedSmoothingOutputs(typing.NamedTuple): - """ - Output object returned when calling `surface_based_smoothing(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - smoothed_output: OutputPathType - """The output smoothed image.""" - - -def surface_based_smoothing( - image_to_smooth: InputPathType, - sigma: float, - surface_image: InputPathType, - outname: str, - num_repeats: int | None = None, - runner: Runner | None = None, -) -> SurfaceBasedSmoothingOutputs: - """ - Surface-based smoothing applied to ImageToSmooth using a geodesic neighbourhood - defined by sigma and the surface image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_to_smooth: The image that needs to be smoothed. - sigma: Geodesic neighborhood radius. - surface_image: Assumes a label == 1 that defines the surface. - outname: The name of the output file. - num_repeats: Number of times the geodesic neighborhood is applied\ - repeatedly. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfaceBasedSmoothingOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURFACE_BASED_SMOOTHING_METADATA) - cargs = [] - cargs.append("SurfaceBasedSmoothing") - cargs.append(execution.input_file(image_to_smooth)) - cargs.append(str(sigma)) - cargs.append(execution.input_file(surface_image)) - cargs.append(outname) - if num_repeats is not None: - cargs.append(str(num_repeats)) - ret = SurfaceBasedSmoothingOutputs( - root=execution.output_file("."), - smoothed_output=execution.output_file(outname), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURFACE_BASED_SMOOTHING_METADATA", - "SurfaceBasedSmoothingOutputs", - "surface_based_smoothing", -] diff --git a/python/src/niwrap/ants/surface_curvature.py b/python/src/niwrap/ants/surface_curvature.py deleted file mode 100644 index 6984a499c..000000000 --- a/python/src/niwrap/ants/surface_curvature.py +++ /dev/null @@ -1,72 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -SURFACE_CURVATURE_METADATA = Metadata( - id="f51ecb142f0e101ca04c2a1dc64c730be65cd0a3.boutiques", - name="SurfaceCurvature", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class SurfaceCurvatureOutputs(typing.NamedTuple): - """ - Output object returned when calling `surface_curvature(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """The processed image file.""" - - -def surface_curvature( - filename_in: InputPathType, - filename_out: InputPathType, - sigma: float, - option: float, - runner: Runner | None = None, -) -> SurfaceCurvatureOutputs: - """ - The Shape Operator for Differential Analysis of Images. It can operate on binary - or gray scale images with various modes to see different effects. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - filename_in: The input image file in .nii format. - filename_out: The output image file in .nii format. - sigma: The sigma value for analysis. - option: The operation mode: 0 for mean curvature, 5 for surface\ - characterization, 6 for Gaussian curvature, and 7 for surface area. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `SurfaceCurvatureOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(SURFACE_CURVATURE_METADATA) - cargs = [] - cargs.append("SurfaceCurvature") - cargs.append(execution.input_file(filename_in)) - cargs.append(execution.input_file(filename_out)) - cargs.append(str(sigma)) - cargs.append(str(option)) - ret = SurfaceCurvatureOutputs( - root=execution.output_file("."), - output_image=execution.output_file(pathlib.Path(filename_out).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "SURFACE_CURVATURE_METADATA", - "SurfaceCurvatureOutputs", - "surface_curvature", -] diff --git a/python/src/niwrap/ants/texture_cooccurrence_features.py b/python/src/niwrap/ants/texture_cooccurrence_features.py deleted file mode 100644 index 4077be51a..000000000 --- a/python/src/niwrap/ants/texture_cooccurrence_features.py +++ /dev/null @@ -1,84 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TEXTURE_COOCCURRENCE_FEATURES_METADATA = Metadata( - id="91591f77263330ed7a5bfa1c36e1edb089c3c166.boutiques", - name="TextureCooccurrenceFeatures", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class TextureCooccurrenceFeaturesOutputs(typing.NamedTuple): - """ - Output object returned when calling `texture_cooccurrence_features(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - features_output: OutputPathType - """The output file containing the calculated texture co-occurrence - features.""" - - -def texture_cooccurrence_features( - image_dimension: int, - input_image: InputPathType, - number_of_bins_per_axis: int | None = 256, - mask_image: InputPathType | None = None, - mask_label: int | None = 1, - runner: Runner | None = None, -) -> TextureCooccurrenceFeaturesOutputs: - """ - Calculates texture co-occurrence features such as Energy, Entropy, Inverse - Difference Moment, Inertia, Cluster Shade, and Cluster Prominence from an input - image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input image, e.g., 2 for 2D\ - images, 3 for 3D images. - input_image: The input image file for which texture co-occurrence\ - features will be calculated. - number_of_bins_per_axis: The number of bins per axis to be used in the\ - histogram for texture calculation. Defaults to 256. - mask_image: Optional mask image to specify the regions of interest in\ - the input image for which features will be calculated. - mask_label: Label value in the mask image to specify which region to\ - process. Defaults to 1. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TextureCooccurrenceFeaturesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TEXTURE_COOCCURRENCE_FEATURES_METADATA) - cargs = [] - cargs.append("TextureCooccurrenceFeatures") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - if number_of_bins_per_axis is not None: - cargs.append(str(number_of_bins_per_axis)) - if mask_image is not None: - cargs.append(execution.input_file(mask_image)) - if mask_label is not None: - cargs.append(str(mask_label)) - ret = TextureCooccurrenceFeaturesOutputs( - root=execution.output_file("."), - features_output=execution.output_file(pathlib.Path(input_image).name + "_features.txt"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TEXTURE_COOCCURRENCE_FEATURES_METADATA", - "TextureCooccurrenceFeaturesOutputs", - "texture_cooccurrence_features", -] diff --git a/python/src/niwrap/ants/texture_run_length_features.py b/python/src/niwrap/ants/texture_run_length_features.py deleted file mode 100644 index 21ae5b292..000000000 --- a/python/src/niwrap/ants/texture_run_length_features.py +++ /dev/null @@ -1,103 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TEXTURE_RUN_LENGTH_FEATURES_METADATA = Metadata( - id="99c3089b305255bec7d6249a4c2fc94894071c52.boutiques", - name="TextureRunLengthFeatures", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class TextureRunLengthFeaturesOutputs(typing.NamedTuple): - """ - Output object returned when calling `texture_run_length_features(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - short_run_emphasis: OutputPathType - """Output feature: Short Run Emphasis.""" - long_run_emphasis: OutputPathType - """Output feature: Long Run Emphasis.""" - grey_level_nonuniformity: OutputPathType - """Output feature: Grey Level Nonuniformity.""" - run_length_nonuniformity: OutputPathType - """Output feature: Run Length Nonuniformity.""" - low_grey_level_run_emphasis: OutputPathType - """Output feature: Low Grey Level Run Emphasis.""" - high_grey_level_run_emphasis: OutputPathType - """Output feature: High Grey Level Run Emphasis.""" - short_run_low_grey_level_emphasis: OutputPathType - """Output feature: Short Run Low Grey Level Emphasis.""" - short_run_high_grey_level_emphasis: OutputPathType - """Output feature: Short Run High Grey Level Emphasis.""" - long_run_low_grey_level_emphasis: OutputPathType - """Output feature: Long Run Low Grey Level Emphasis.""" - long_run_high_grey_level_emphasis: OutputPathType - """Output feature: Long Run High Grey Level Emphasis.""" - - -def texture_run_length_features( - image_dimension: int, - input_image: InputPathType, - number_of_bins_per_axis: int | None = 256, - mask_image: InputPathType | None = None, - mask_label: int | None = 1, - runner: Runner | None = None, -) -> TextureRunLengthFeaturesOutputs: - """ - A tool to calculate texture run length features on an input image. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input image. - input_image: The path to the input image file. - number_of_bins_per_axis: The number of bins per axis for the histogram. - mask_image: The path to the mask image file. - mask_label: The label value in the mask image to be used. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TextureRunLengthFeaturesOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TEXTURE_RUN_LENGTH_FEATURES_METADATA) - cargs = [] - cargs.append("TextureRunLengthFeatures") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(input_image)) - if number_of_bins_per_axis is not None: - cargs.append(str(number_of_bins_per_axis)) - if mask_image is not None: - cargs.append(execution.input_file(mask_image)) - if mask_label is not None: - cargs.append(str(mask_label)) - ret = TextureRunLengthFeaturesOutputs( - root=execution.output_file("."), - short_run_emphasis=execution.output_file("short_run_emphasis.csv"), - long_run_emphasis=execution.output_file("long_run_emphasis.csv"), - grey_level_nonuniformity=execution.output_file("grey_level_nonuniformity.csv"), - run_length_nonuniformity=execution.output_file("run_length_nonuniformity.csv"), - low_grey_level_run_emphasis=execution.output_file("low_grey_level_run_emphasis.csv"), - high_grey_level_run_emphasis=execution.output_file("high_grey_level_run_emphasis.csv"), - short_run_low_grey_level_emphasis=execution.output_file("short_run_low_grey_level_emphasis.csv"), - short_run_high_grey_level_emphasis=execution.output_file("short_run_high_grey_level_emphasis.csv"), - long_run_low_grey_level_emphasis=execution.output_file("long_run_low_grey_level_emphasis.csv"), - long_run_high_grey_level_emphasis=execution.output_file("long_run_high_grey_level_emphasis.csv"), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TEXTURE_RUN_LENGTH_FEATURES_METADATA", - "TextureRunLengthFeaturesOutputs", - "texture_run_length_features", -] diff --git a/python/src/niwrap/ants/threshold_image.py b/python/src/niwrap/ants/threshold_image.py deleted file mode 100644 index b17c2c490..000000000 --- a/python/src/niwrap/ants/threshold_image.py +++ /dev/null @@ -1,99 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -THRESHOLD_IMAGE_METADATA = Metadata( - id="21280b87f93b4982f5b7173d35c9223a6b16962d.boutiques", - name="ThresholdImage", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class ThresholdImageOutputs(typing.NamedTuple): - """ - Output object returned when calling `threshold_image(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image: OutputPathType - """The resulting image after thresholding.""" - - -def threshold_image( - image_dimension: int, - image_in: InputPathType, - out_image: InputPathType, - threshlo: float | None = None, - threshhi: float | None = None, - inside_value: float | None = None, - outside_value: float | None = None, - otsu_number_of_thresholds: float | None = None, - kmeans_number_of_thresholds: float | None = None, - mask_image: InputPathType | None = None, - runner: Runner | None = None, -) -> ThresholdImageOutputs: - """ - Image thresholding utility that applies different thresholding techniques to an - input image. It can use fixed thresholds, Otsu method, or K-means for - thresholding. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimension of the input image. - image_in: The input image file to be thresholded. - out_image: The output image file after thresholding. - threshlo: The lower threshold value for fixed thresholding. - threshhi: The upper threshold value for fixed thresholding. - inside_value: The pixel value to be used inside the threshold range. - outside_value: The pixel value to be used outside the threshold range. - otsu_number_of_thresholds: Number of thresholds to use when applying\ - the Otsu method. - kmeans_number_of_thresholds: Number of thresholds to use when applying\ - the K-means method. - mask_image: Optional mask image for the thresholding operation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `ThresholdImageOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(THRESHOLD_IMAGE_METADATA) - cargs = [] - cargs.append("ThresholdImage") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(image_in)) - cargs.append(execution.input_file(out_image)) - if threshlo is not None: - cargs.append(str(threshlo)) - if threshhi is not None: - cargs.append(str(threshhi)) - if inside_value is not None: - cargs.append(str(inside_value)) - if outside_value is not None: - cargs.append(str(outside_value)) - if otsu_number_of_thresholds is not None: - cargs.append(str(otsu_number_of_thresholds)) - if kmeans_number_of_thresholds is not None: - cargs.append(str(kmeans_number_of_thresholds)) - if mask_image is not None: - cargs.append(execution.input_file(mask_image)) - ret = ThresholdImageOutputs( - root=execution.output_file("."), - output_image=execution.output_file(pathlib.Path(out_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "THRESHOLD_IMAGE_METADATA", - "ThresholdImageOutputs", - "threshold_image", -] diff --git a/python/src/niwrap/ants/tile_images.py b/python/src/niwrap/ants/tile_images.py deleted file mode 100644 index 3eeb1e889..000000000 --- a/python/src/niwrap/ants/tile_images.py +++ /dev/null @@ -1,77 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TILE_IMAGES_METADATA = Metadata( - id="8a5ab10347c4822ca1b9a1ace149a5ab531d4186.boutiques", - name="TileImages", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class TileImagesOutputs(typing.NamedTuple): - """ - Output object returned when calling `tile_images(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - tiled_image: OutputPathType - """The final tiled output image.""" - - -def tile_images( - image_dimension: int, - output_image: InputPathType, - layout: str, - input_images: list[InputPathType], - runner: Runner | None = None, -) -> TileImagesOutputs: - """ - TileImages allows assembling images into a multi-dimensional array, producing a - single output image. The input images must have a dimension less than or equal - to the specified output image dimension. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimensionality of the output image. - output_image: The path for the output tiled image. - layout: Defines the structure of the tiled output image. The layout\ - dictates the number and arrangement of input images in the output\ - image. - input_images: Input images to be tiled into the output image. The\ - number of input images should match the layout specification. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TileImagesOutputs`). - """ - if not (1 <= len(input_images)): - raise ValueError(f"Length of 'input_images' must be greater than 1 but was {len(input_images)}") - runner = runner or get_global_runner() - execution = runner.start_execution(TILE_IMAGES_METADATA) - cargs = [] - cargs.append("TileImages") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(output_image)) - cargs.append(layout) - cargs.extend([execution.input_file(f) for f in input_images]) - ret = TileImagesOutputs( - root=execution.output_file("."), - tiled_image=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TILE_IMAGES_METADATA", - "TileImagesOutputs", - "tile_images", -] diff --git a/python/src/niwrap/ants/time_sccan.py b/python/src/niwrap/ants/time_sccan.py deleted file mode 100644 index 22a90ea1d..000000000 --- a/python/src/niwrap/ants/time_sccan.py +++ /dev/null @@ -1,238 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -TIME_SCCAN_METADATA = Metadata( - id="c29edfffbdbeee9e02e8801bed3cb5f939e9ea50.boutiques", - name="TimeSCCAN", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -@dataclasses.dataclass -class TimeSccanTimeseriesimageToMatrix: - """ - Takes a timeseries (4D) image and converts it to a 2D matrix csv format as - output. If the mask has multiple labels (more than one), then the average - time series in each label will be computed and put in the csv. - """ - timeseries_image: InputPathType - mask_image: InputPathType - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append(execution.input_file(self.timeseries_image) + execution.input_file(self.mask_image)) - return cargs - - -@dataclasses.dataclass -class TimeSccanNetworkScca: - time_matrix: InputPathType - label_matrix: InputPathType - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("scca[" + execution.input_file(self.time_matrix) + "," + execution.input_file(self.label_matrix) + "]") - return cargs - - -@dataclasses.dataclass -class TimeSccanNetworkRegionAveraging: - time_matrix: InputPathType - label_matrix: InputPathType - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.append("region-averaging[" + execution.input_file(self.time_matrix) + "," + execution.input_file(self.label_matrix) + "]") - return cargs - - -class TimeSccanOutputs(typing.NamedTuple): - """ - Output object returned when calling `time_sccan(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - correlation_matrix: OutputPathType - """The output is the 2D correlation matrix.""" - - -def time_sccan( - output: InputPathType, - number_consecutive_labels: int | None = 0, - minimum_region_size: int | None = 1, - iterations: int | None = 20, - sparsity: float | None = 0.1, - n_eigenvectors: int | None = 2, - robustify: int | None = 0, - l1: float | None = 0, - cluster_thresh: int | None = 1, - ridge_cca: int | None = 0, - partial_scca_option: typing.Literal["PQ", "PminusRQ", "PQminusR", "PminusRQminusR"] | None = None, - timeseriesimage_to_matrix: TimeSccanTimeseriesimageToMatrix | None = None, - labelsimage_to_matrix: InputPathType | None = None, - network: typing.Union[TimeSccanNetworkScca, TimeSccanNetworkRegionAveraging] | None = None, - runner: Runner | None = None, -) -> TimeSccanOutputs: - """ - A tool for sparse statistical analysis on connectivity within a subject. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - output: Output is a 2D correlation matrix. - number_consecutive_labels: Number of consecutive labels in data. - minimum_region_size: Minimum size of a region: regions below this size\ - are given a 0.0 connectivity value. - iterations: Number of iterations. - sparsity: Sparsity - a float from (0,1] indicating what fraction of the\ - data to use. - n_eigenvectors: Number of permutations to use in scca. - robustify: Rank-based scca. - l1: Use l1 ( > 0 ) or l0 ( < 0 ) penalty, also sets gradient step size\ - e.g. -l 0.5 ( L1 ) , -l -0.5 (L0) will set 0.5 grad descent step for\ - either penalty. - cluster_thresh: Cluster threshold on view P. - ridge_cca: Number of permutations to use in scca. - partial_scca_option: Choices for partial SCCA: PQ, PminusRQ, PQminusR,\ - PminusRQminusR. - timeseriesimage_to_matrix: Takes a timeseries (4D) image and converts\ - it to a 2D matrix csv format as output. If the mask has multiple labels\ - (more than one), then the average time series in each label will be\ - computed and put in the csv. - labelsimage_to_matrix: Takes a labeled (3D) image and converts it to a\ - 2D matrix csv format as output. - network: Build the network connectivity matrix. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `TimeSccanOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(TIME_SCCAN_METADATA) - cargs = [] - cargs.append("TimeSCCAN") - cargs.extend([ - "--output", - execution.input_file(output) - ]) - if number_consecutive_labels is not None: - cargs.extend([ - "-l", - str(number_consecutive_labels) - ]) - if minimum_region_size is not None: - cargs.extend([ - "-R", - str(minimum_region_size) - ]) - if iterations is not None: - cargs.extend([ - "-i", - str(iterations) - ]) - if sparsity is not None: - cargs.extend([ - "-s", - str(sparsity) - ]) - if n_eigenvectors is not None: - cargs.extend([ - "-n", - str(n_eigenvectors) - ]) - if robustify is not None: - cargs.extend([ - "-r", - str(robustify) - ]) - if l1 is not None: - cargs.extend([ - "-l", - str(l1) - ]) - if cluster_thresh is not None: - cargs.extend([ - "--ClusterThresh", - str(cluster_thresh) - ]) - if ridge_cca is not None: - cargs.extend([ - "-e", - str(ridge_cca) - ]) - if partial_scca_option is not None: - cargs.extend([ - "--partial-scca-option", - partial_scca_option - ]) - if timeseriesimage_to_matrix is not None: - cargs.extend([ - "--timeseriesimage-to-matrix", - *timeseriesimage_to_matrix.run(execution) - ]) - if labelsimage_to_matrix is not None: - cargs.extend([ - "--labelsimage-to-matrix", - execution.input_file(labelsimage_to_matrix) - ]) - if network is not None: - cargs.extend([ - "--network", - *network.run(execution) - ]) - ret = TimeSccanOutputs( - root=execution.output_file("."), - correlation_matrix=execution.output_file(pathlib.Path(output).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "TIME_SCCAN_METADATA", - "TimeSccanNetworkRegionAveraging", - "TimeSccanNetworkScca", - "TimeSccanOutputs", - "TimeSccanTimeseriesimageToMatrix", - "time_sccan", -] diff --git a/python/src/niwrap/ants/warp_tensor_image_multi_transform.py b/python/src/niwrap/ants/warp_tensor_image_multi_transform.py deleted file mode 100644 index b62cdca1b..000000000 --- a/python/src/niwrap/ants/warp_tensor_image_multi_transform.py +++ /dev/null @@ -1,96 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -WARP_TENSOR_IMAGE_MULTI_TRANSFORM_METADATA = Metadata( - id="14d19d5d0cd63cddc6a5dbd0cf982ba44c0b6d8b.boutiques", - name="WarpTensorImageMultiTransform", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class WarpTensorImageMultiTransformOutputs(typing.NamedTuple): - """ - Output object returned when calling `warp_tensor_image_multi_transform(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_file: OutputPathType - """The resultant transformed output image.""" - - -def warp_tensor_image_multi_transform( - image_dimension: int, - moving_image: InputPathType, - output_image: str, - transforms: list[str], - reference_image: InputPathType | None = None, - tightest_bounding_box: bool = False, - reslice_by_header: bool = False, - use_nearest_neighbor: bool = False, - runner: Runner | None = None, -) -> WarpTensorImageMultiTransformOutputs: - """ - WarpImageMultiTransform is used to apply transformations including affine and - deformation fields to an image, supporting various interpolation techniques, - image header reslicing, and compatibility with ANTS-generated transformations. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: Dimensionality of the image (e.g., 2D or 3D). - moving_image: The moving image that will be transformed. - output_image: Path for saving the transformed output image. - transforms: List of transformations to apply, which can include\ - deformation fields or affine transforms. - reference_image: Reference image for reslicing or defining the\ - transformation domain. - tightest_bounding_box: Compute the tightest bounding box using all\ - affine transformations. - reslice_by_header: Use the orientation matrix and origin encoded in the\ - image file header for reslicing. - use_nearest_neighbor: Use Nearest Neighbor Interpolator for the\ - transformation. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `WarpTensorImageMultiTransformOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(WARP_TENSOR_IMAGE_MULTI_TRANSFORM_METADATA) - cargs = [] - cargs.append("WarpImageMultiTransform") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(moving_image)) - cargs.append(output_image) - if reference_image is not None: - cargs.extend([ - "-R", - execution.input_file(reference_image) - ]) - if tightest_bounding_box: - cargs.append("--tightest-bounding-box") - if reslice_by_header: - cargs.append("--reslice-by-header") - if use_nearest_neighbor: - cargs.append("--use-NN") - cargs.extend(transforms) - ret = WarpTensorImageMultiTransformOutputs( - root=execution.output_file("."), - output_image_file=execution.output_file(output_image), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "WARP_TENSOR_IMAGE_MULTI_TRANSFORM_METADATA", - "WarpTensorImageMultiTransformOutputs", - "warp_tensor_image_multi_transform", -] diff --git a/python/src/niwrap/ants/warp_time_series_image_multi_transform.py b/python/src/niwrap/ants/warp_time_series_image_multi_transform.py deleted file mode 100644 index 80097cad6..000000000 --- a/python/src/niwrap/ants/warp_time_series_image_multi_transform.py +++ /dev/null @@ -1,88 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -WARP_TIME_SERIES_IMAGE_MULTI_TRANSFORM_METADATA = Metadata( - id="4bc360e4981268f29e28fda77231c303fd363337.boutiques", - name="WarpTimeSeriesImageMultiTransform", - package="ants", - container_image_tag="antsx/ants:v2.5.3", -) - - -class WarpTimeSeriesImageMultiTransformOutputs(typing.NamedTuple): - """ - Output object returned when calling `warp_time_series_image_multi_transform(...)`. - """ - root: OutputPathType - """Output root folder. This is the root folder for all outputs.""" - output_image_result: OutputPathType - """The transformed image that is saved as output.""" - - -def warp_time_series_image_multi_transform( - image_dimension: typing.Literal[3, 4], - moving_image: InputPathType, - output_image: InputPathType, - reference_image: InputPathType, - transforms: list[str], - interpolation: typing.Literal["NearestNeighbor", "BSpline"] | None = None, - runner: Runner | None = None, -) -> WarpTimeSeriesImageMultiTransformOutputs: - """ - WarpTimeSeriesImageMultiTransform is a tool used to apply a series of - transformations to a time series image, either forward or reverse, using affine - transforms and warps. - - Author: ANTs Developers - - URL: https://github.com/ANTsX/ANTs - - Args: - image_dimension: The dimensionality of the input images (3D or 4D). - moving_image: The image to which the transformation will be applied. It\ - can be a 3D image with vector voxels or a 4D image with scalar voxels. - output_image: The output image after transformation. It is resampled\ - based on the reference image domain. - reference_image: The reference image that defines the space into which\ - the input image will be warped. - transforms: A list of transformation files, such as affine\ - transformation matrices and warps, applied in sequence. - interpolation: Specifies the type of interpolation to use: Nearest\ - Neighbor or 3rd order B-Spline. - runner: Command runner. - Returns: - NamedTuple of outputs (described in `WarpTimeSeriesImageMultiTransformOutputs`). - """ - runner = runner or get_global_runner() - execution = runner.start_execution(WARP_TIME_SERIES_IMAGE_MULTI_TRANSFORM_METADATA) - cargs = [] - cargs.append("WarpTimeSeriesImageMultiTransform") - cargs.append(str(image_dimension)) - cargs.append(execution.input_file(moving_image)) - cargs.append(execution.input_file(output_image)) - cargs.append("-R") - cargs.extend([ - "-R", - execution.input_file(reference_image) - ]) - cargs.extend(transforms) - if interpolation is not None: - cargs.append(interpolation) - ret = WarpTimeSeriesImageMultiTransformOutputs( - root=execution.output_file("."), - output_image_result=execution.output_file(pathlib.Path(output_image).name), - ) - execution.run(cargs) - return ret - - -__all__ = [ - "WARP_TIME_SERIES_IMAGE_MULTI_TRANSFORM_METADATA", - "WarpTimeSeriesImageMultiTransformOutputs", - "warp_time_series_image_multi_transform", -] diff --git a/python/src/niwrap/c3d/__init__.py b/python/src/niwrap/c3d/__init__.py deleted file mode 100644 index 1091e1163..000000000 --- a/python/src/niwrap/c3d/__init__.py +++ /dev/null @@ -1,23 +0,0 @@ -""" -Convert3D - -Convert3D (unix name c3d) is a command-line image processing tool that offers -complementary features to ITK-SNAP. Originally developed to convert between -various 3D image formats, the tool has become more of a Swiss army knife for -medical image processing. In addition to many standard filters and resampling -commands, c3d offers tools specialized for multilabel images (such as -segmentation images output by ITK-SNAP) and multicomponent images (such as RGB -images read by SNAP). Through the use of reverse polish notation on the command -line, c3d allows many image processing tasks to be combined in small -command-line mini-programs. This saves on the need to save intermediate image -files, saving disk space and network bandwidth. We use c3d extensively to run -studies with thousands of 3D images, and are continually adding commands and -features to the tool. - -URL: http://www.itksnap.org/pmwiki/pmwiki.php?n=Convert3D.Convert3D -""" -# This file was auto generated by Styx. -# Do not edit this file directly. - -from .c3d import * -from .c3d_affine_tool import * diff --git a/python/src/niwrap/c3d/c3d.py b/python/src/niwrap/c3d/c3d.py deleted file mode 100644 index 0da219e2e..000000000 --- a/python/src/niwrap/c3d/c3d.py +++ /dev/null @@ -1,9021 +0,0 @@ -# This file was auto generated by Styx. -# Do not edit this file directly. - -import typing -import pathlib -from styxdefs import * -import dataclasses - -C3D_METADATA = Metadata( - id="2fd805b886703d905dbdaa3b379abc89e94dfe54.boutiques", - name="c3d", - package="c3d", - container_image_tag="pyushkevich/itksnap:v3.8.2", -) - - -@dataclasses.dataclass -class C3dAccum: - """ - -accum, -endaccum: Accumulate operations over all images - - Syntax: `-accum command-list -endaccum` - - Apply a binary operation (such as addition or multiplication) to all the - images on the stack in a cumulative fashion. The command(s) will be applied - to the last and second-to-last images on the stack, then to the result of - this operation and the third-to-last image on the stack and so on. Below is - the example of using the command to add multiple images. - - c3d image*.nii -accum -add -endaccum -o sum.nii. - """ - accum: str - """-accum, -endaccum: Accumulate operations over all images - - Syntax: `-accum command-list -endaccum` - - Apply a binary operation (such as addition or multiplication) to all the - images on the stack in a cumulative fashion. The command(s) will be applied - to the last and second-to-last images on the stack, then to the result of - this operation and the third-to-last image on the stack and so on. Below is - the example of using the command to add multiple images. - - c3d image*.nii -accum -add -endaccum -o sum.nii""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-accum", - self.accum - ]) - return cargs - - -@dataclasses.dataclass -class C3dAcos: - """ - No description found. - """ - acos: str - """No description found.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-acos", - self.acos - ]) - return cargs - - -@dataclasses.dataclass -class C3dAdd: - """ - -add: Voxelwise image addition - - Syntax: `-add` - - Adds the last two images on the stack, and places the sum at the end of the - stack. - - # Add two images: x = a + b - c3d a.img b.img -add -o x.img - - # Add three images, x = (a + b) + c in the first example, x = a + (b + c) in - the second - c3d a.img b.img -add c.img -add -o x.img - c3d a.img b.img c.img -add -add -o x.img - - # Subtract two images, using -scale command: x = a - b - c3d a.img b.img -scale -1 -add -o x.img. - """ - add: str - """-add: Voxelwise image addition - - Syntax: `-add` - - Adds the last two images on the stack, and places the sum at the end of the - stack. - - # Add two images: x = a + b - c3d a.img b.img -add -o x.img - - # Add three images, x = (a + b) + c in the first example, x = a + (b + c) in - the second - c3d a.img b.img -add c.img -add -o x.img - c3d a.img b.img c.img -add -add -o x.img - - # Subtract two images, using -scale command: x = a - b - c3d a.img b.img -scale -1 -add -o x.img""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-add", - self.add - ]) - return cargs - - -@dataclasses.dataclass -class C3dAlignLandmarks: - """ - -alm, -align-landmarks: Align images based on landmark matching - - Syntax: `-alm dof outfile` - - Performs rigid or affine alignment between to sets of landmark images. A - landmark image is an image where for every intensity value, the centroid of - all voxels with that intensity represents a landmark. Landmarks can be - created using the paintbrush tool in ITK-SNAP (they can be spheres, cubes, - etc). The first image on the stack is the target/fixed/reference image, and - the second is the moving image. The parameters are the degrees of freedom, - which is a number (6 for rigid, 7 for rigid+scale, 12 for affine) and the - output matrix file. In this example, we have images **fixed.nii* and - **moving.nii** with corresponding landmark images. We use landmarks to align - the moving image to the fixed: - - c3d fixed_landmarks.nii moving_landmarks.nii -alm 6 rigid.mat - c3d fixed.nii moving.nii -reslice-matrix rigid.mat -o - moving_resliced_to_fixed.nii. - """ - align_landmarks: str - """-alm, -align-landmarks: Align images based on landmark matching - - Syntax: `-alm dof outfile` - - Performs rigid or affine alignment between to sets of landmark images. A - landmark image is an image where for every intensity value, the centroid of - all voxels with that intensity represents a landmark. Landmarks can be - created using the paintbrush tool in ITK-SNAP (they can be spheres, cubes, - etc). The first image on the stack is the target/fixed/reference image, and - the second is the moving image. The parameters are the degrees of freedom, - which is a number (6 for rigid, 7 for rigid+scale, 12 for affine) and the - output matrix file. In this example, we have images **fixed.nii* and - **moving.nii** with corresponding landmark images. We use landmarks to align - the moving image to the fixed: - - c3d fixed_landmarks.nii moving_landmarks.nii -alm 6 rigid.mat - c3d fixed.nii moving.nii -reslice-matrix rigid.mat -o - moving_resliced_to_fixed.nii""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-align-landmarks", - self.align_landmarks - ]) - return cargs - - -@dataclasses.dataclass -class C3dAnisotropicDiffusion: - """ - -add: Voxelwise image addition - - Syntax: `-add` - - Adds the last two images on the stack, and places the sum at the end of the - stack. - - # Add two images: x = a + b - c3d a.img b.img -add -o x.img - - # Add three images, x = (a + b) + c in the first example, x = a + (b + c) in - the second - c3d a.img b.img -add c.img -add -o x.img - c3d a.img b.img c.img -add -add -o x.img - - # Subtract two images, using -scale command: x = a - b - c3d a.img b.img -scale -1 -add -o x.img. - """ - anisotropic_diffusion: str - """-add: Voxelwise image addition - - Syntax: `-add` - - Adds the last two images on the stack, and places the sum at the end of the - stack. - - # Add two images: x = a + b - c3d a.img b.img -add -o x.img - - # Add three images, x = (a + b) + c in the first example, x = a + (b + c) in - the second - c3d a.img b.img -add c.img -add -o x.img - c3d a.img b.img c.img -add -add -o x.img - - # Subtract two images, using -scale command: x = a - b - c3d a.img b.img -scale -1 -add -o x.img""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-anisotropic-diffusion", - self.anisotropic_diffusion - ]) - return cargs - - -@dataclasses.dataclass -class C3dAntialias: - """ - No description found. - """ - antialias: str - """No description found.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-antialias", - self.antialias - ]) - return cargs - - -@dataclasses.dataclass -class C3dSet: - """ - -as: Assign image at the end of the stack to a variable - - Syntax: `-as var` - - Associates the image currently at the end of the stack with variable name - 'var'. This allows you to retrieve the image later on the command line using - the **-push** command. The **-as** and **-push** commands are useful when - you need to use a certain image more than once during a convert3d operation. - For example, if you want to compute the distance transform of a binary image - and mask it so that the values outside of the binary image region have value - 0, you would use the following command: - - c3d binary.img -as A -sdt -push A -times -o masked_distance.img. - """ - set_: str - """-as: Assign image at the end of the stack to a variable - - Syntax: `-as var` - - Associates the image currently at the end of the stack with variable name - 'var'. This allows you to retrieve the image later on the command line using - the **-push** command. The **-as** and **-push** commands are useful when - you need to use a certain image more than once during a convert3d operation. - For example, if you want to compute the distance transform of a binary image - and mask it so that the values outside of the binary image region have value - 0, you would use the following command: - - c3d binary.img -as A -sdt -push A -times -o masked_distance.img""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-as", - self.set_ - ]) - return cargs - - -@dataclasses.dataclass -class C3dAsin: - """ - No description found. - """ - asin: str - """No description found.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-asin", - self.asin - ]) - return cargs - - -@dataclasses.dataclass -class C3dAtan2: - """ - -atan2: Voxelwise angle from sine and cosine - - Syntax: `-atan2` - - Computes the angle in radians from images containing sine and cosine. This - is a voxel-wise operation. It requires two images on the stack (sine - followed by cosine): - - c3d sin_theta.nii.gz cos_theta.nii.gz -atan2 -o theta.nii.gz. - """ - atan2: str - """-atan2: Voxelwise angle from sine and cosine - - Syntax: `-atan2` - - Computes the angle in radians from images containing sine and cosine. This - is a voxel-wise operation. It requires two images on the stack (sine - followed by cosine): - - c3d sin_theta.nii.gz cos_theta.nii.gz -atan2 -o theta.nii.gz""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-atan2", - self.atan2 - ]) - return cargs - - -@dataclasses.dataclass -class C3dBackground: - """ - -background: Specify background intensity - - Syntax: `-background ` - - Sets the background intensity for interpolation and other operations where - some default background value is needed. Default is 0. - """ - background: str - """-background: Specify background intensity - - Syntax: `-background ` - - Sets the background intensity for interpolation and other operations where - some default background value is needed. Default is 0.""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-background", - self.background - ]) - return cargs - - -@dataclasses.dataclass -class C3dN4BiasCorrection: - """ - -biascorr: Automatic MRI bias field correction - - Syntax: `-biascorr` - - Performs automatic bias field correction for MRI images. This feature uses - the [N3 implementation in ITK by Dr. Tustison][4], based on the N3 algorithm - by Sled et al. - - c3d mri.nii.gz -biascorr -o mricorr.nii.gz. - """ - n4_bias_correction: str - """-biascorr: Automatic MRI bias field correction - - Syntax: `-biascorr` - - Performs automatic bias field correction for MRI images. This feature uses - the [N3 implementation in ITK by Dr. Tustison][4], based on the N3 algorithm - by Sled et al. - - c3d mri.nii.gz -biascorr -o mricorr.nii.gz""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-biascorr", - self.n4_bias_correction - ]) - return cargs - - -@dataclasses.dataclass -class C3dBinarize: - """ - -binarize: Convert image to binary - - Syntax: `-binarize` - - Converts an image to binary by mapping all background values (the background - is 0 by default and can be changed by the option **-background**) to 0 and - all non-background values to 1. The **-binarize** command is shorthand for - the **-threshold** command. - - c3d test.img -binarize -o binary.img - c3d -background 10 -binarize -o binary.img - c3d test.img -threshold 10 10 0 1 // equivalent to above command. - """ - binarize: str - """-binarize: Convert image to binary - - Syntax: `-binarize` - - Converts an image to binary by mapping all background values (the background - is 0 by default and can be changed by the option **-background**) to 0 and - all non-background values to 1. The **-binarize** command is shorthand for - the **-threshold** command. - - c3d test.img -binarize -o binary.img - c3d -background 10 -binarize -o binary.img - c3d test.img -threshold 10 10 0 1 // equivalent to above command""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-binarize", - self.binarize - ]) - return cargs - - -@dataclasses.dataclass -class C3dCanny: - """ - -canny: Canny edge detector - - Syntax: `-canny ` - - Performs edge detection on the last image on the stack using the Canny - filter. The parameters are a vector of standard deviations defining the - scale of the edges detected and lower and upper thresholds for edge - selection. See documentation on the [ITK Canny Filter][14]. - """ - canny: str - """-canny: Canny edge detector - - Syntax: `-canny ` - - Performs edge detection on the last image on the stack using the Canny - filter. The parameters are a vector of standard deviations defining the - scale of the edges detected and lower and upper thresholds for edge - selection. See documentation on the [ITK Canny Filter][14].""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-canny", - self.canny - ]) - return cargs - - -@dataclasses.dataclass -class C3dCeil: - """ - -ceil: Round up image intensities - - Syntax: `-ceil ` - - Each image intensity is replaced by the smallest integer larger or equal to - it - - c3d input.img -ceil -o output.img. - """ - ceil: str - """-ceil: Round up image intensities - - Syntax: `-ceil ` - - Each image intensity is replaced by the smallest integer larger or equal to - it - - c3d input.img -ceil -o output.img""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-ceil", - self.ceil - ]) - return cargs - - -@dataclasses.dataclass -class C3dCentroid: - """ - -centroid: Report centroid of foreground voxels - - Syntax: `-centroid` - - Reports the centroid, in physical coordinates, of all foreground voxels in - the image. - - c3d binaryimage.img -centroid // centroid of all non-0 voxels - c3d grayimage.img -thresh 1000 7000 1 0 -centroid 1 // centroid of all - voxels in range 1000-7000 - c3d labelimage.img -thresh 5 5 1 0 -centroid // centroid of all voxels with - label 5 - c3d labelimage.img -split -foreach -centroid -endfor // centroids of all - labels (including 0). - """ - centroid: str - """-centroid: Report centroid of foreground voxels - - Syntax: `-centroid` - - Reports the centroid, in physical coordinates, of all foreground voxels in - the image. - - c3d binaryimage.img -centroid // centroid of all non-0 voxels - c3d grayimage.img -thresh 1000 7000 1 0 -centroid 1 // centroid of all - voxels in range 1000-7000 - c3d labelimage.img -thresh 5 5 1 0 -centroid // centroid of all voxels with - label 5 - c3d labelimage.img -split -foreach -centroid -endfor // centroids of all - labels (including 0)""" - - def run( - self, - execution: Execution, - ) -> list[str]: - """ - Build command line arguments. This method is called by the main command. - - Args: - execution: The execution object. - Returns: - Command line arguments - """ - cargs = [] - cargs.extend([ - "-centroid", - self.centroid - ]) - return cargs - - -@dataclasses.dataclass -class C3dCentroidMark: - """ - -centroid-mark: Mark the centroid of foreground voxels - - Syntax: `-centroid-mark