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Merge pull request #198 from jadball/master
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Add scanning 3DXRD example notebooks
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@jadball
jadball authored Jan 16, 2024
2 parents 34c0a95 + a0b39a7 commit 866a259
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232 changes: 232 additions & 0 deletions ImageD11/nbGui/S3DXRD/0_S3DXRD_segment_and_label_single_dset.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "8deabe5b",
"metadata": {},
"source": [
"# Jupyter notebook based on ImageD11 to process scanning 3DXRD data\n",
"# Written by Haixing Fang, Jon Wright and James Ball\n",
"## Date: 16/01/2024"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "851fcab9-7631-439f-885c-438bcefeac84",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# There is a bug with the current version of ImageD11 in the site-wide Jupyter env.\n",
"# This has been fixed here: https://github.com/FABLE-3DXRD/ImageD11/commit/4af88b886b1775585e868f2339a0eb975401468f\n",
"# Until a new release has been made and added to the env, we need to get the latest version of ImageD11 from GitHub\n",
"# Put it in your home directory somewhere\n",
"# USER: Change the path below to point to your local copy of ImageD11:\n",
"\n",
"id11_code_path = \"/home/esrf/james1997a/Code/ImageD11\"\n",
"\n",
"import sys\n",
"\n",
"sys.path.insert(0, id11_code_path)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9b5c1db6-5a32-4294-abef-cfc2150d24de",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# import functions we need\n",
"\n",
"import os, glob, pprint\n",
"\n",
"import ImageD11.sinograms.dataset\n",
"import ImageD11.sinograms.lima_segmenter\n",
"import ImageD11.sinograms.assemble_label\n",
"import ImageD11.sinograms.properties"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f45e3647-2e1b-4a31-b5de-01adbd4d7573",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Check that we're importing ImageD11 from the home directory rather than from the Jupyter kernel\n",
"\n",
"?ImageD11.sinograms.dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0a307437-2d15-4de5-985f-7c7daf68db0c",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# USER: specify your experimental directory\n",
"\n",
"base_dir = \"/home/esrf/james1997a/Data/ihma439/id11/20231211\"\n",
"\n",
"rawdata_path = os.path.join(base_dir, 'RAW_DATA')\n",
"\n",
"!ls -lrt {rawdata_path}"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ad077c4b-39cc-4b90-9637-33c32f12e364",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# USER: pick a sample and a dataset you want to segment\n",
"\n",
"sample = \"FeAu_0p5_tR_nscope\"\n",
"dataset = \"top_700um\"\n",
"\n",
"# USER: specify path to detector mask\n",
"\n",
"mask_path = '/data/id11/nanoscope/Eiger/eiger_mask_E-08-0173_20231127.edf'\n",
"\n",
"processed_data_root_dir = os.path.join(base_dir, 'PROCESSED_DATA/James') # USER: modify this to change the destination folder if desired\n",
"sparse_pixels_dir = os.path.join(processed_data_root_dir, \"SparsePixels_NewMask\") # USER: modify this to change the name of the SparsePixels folder inside processed_data_root_dir\n",
"\n",
"# makes folders if they don't already exist\n",
"\n",
"if not os.path.exists(processed_data_root_dir):\n",
" os.makedir(processed_data_root_dir)\n",
" \n",
"if not os.path.exists(sparse_pixels_dir):\n",
" os.makedirs(sparse_pixels_dir)\n",
"\n",
"# desination of H5 files\n",
"\n",
"dset_path = os.path.join(sparse_pixels_dir, f\"ds_{sample}_{dataset}.h5\" )\n",
"sparse_path = os.path.join(sparse_pixels_dir, f'{sample}_{dataset}_sparse.h5')\n",
"pks_path = os.path.join(sparse_pixels_dir, f'pks_{sample}_{dataset}.h5')\n",
"\n",
"# create ImageD11 dataset object\n",
"\n",
"ds = ImageD11.sinograms.dataset.DataSet(dataroot=rawdata_path,\n",
" analysisroot=sparse_pixels_dir,\n",
" sample=sample,\n",
" dset=dataset)\n",
"ds.import_all()\n",
"ds.save(dset_path)\n",
"\n",
"# create batch file to send to SLURM cluster\n",
"\n",
"sbat = ImageD11.sinograms.lima_segmenter.setup(dset_path, maskfile=mask_path)\n",
"sbat"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4b8bb44d",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# send batch file to SLURM cluster\n",
"\n",
"!sbatch {sbat}"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a057fef3",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# check status of SLURM jobs\n",
"\n",
"!squeue -u $USER"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b56de064-adb9-4d9c-92e8-301d24598f16",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# you must wait until the SLURM jobs have completed before running the next cell!"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5de23264-4c22-43fe-8be6-8cc54039ea2d",
"metadata": {},
"outputs": [],
"source": [
"# label sparse peaks\n",
"\n",
"ImageD11.sinograms.assemble_label.main(dset_path, sparse_path)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ddb029cd-7f66-4c91-abee-5f1723303360",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# generate peaks table\n",
"\n",
"ImageD11.sinograms.properties.main(dset_path, sparse_path, pks_path, options={'algorithm': 'lmlabel', 'wtmax': 70000, 'save_overlaps': False})"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0b6e6575-bb8e-47ac-88e1-0ff5350ab1a5",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (main)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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