refactor removing Masked objects

autocti/__init__.py

@@ -7,14 +7,13 @@
 from autoarray.instruments import euclid
 from autoarray.instruments import acs
 from autoarray.dataset import preprocess
+from autoarray.dataset.imaging import Imaging
 
 from autocti.structures.lines import Line
 from autocti.structures.lines import LineCollection
 
 from .mask.mask import Mask2D
 from .mask.mask import SettingsMask
-from .dataset.imaging import Imaging
-from .dataset.imaging import MaskedImaging
 from .dataset.warm_pixels import find_warm_pixels
 from . import charge_injection as ci
 from .analysis.analysis import AnalysisCIImaging

autocti/analysis/analysis.py

@@ -144,7 +144,7 @@ def fit_from_instance_and_ci_imaging(
         )
 
         return ci_fit.CIFitImaging(
-            masked_ci_imaging=ci_imaging,
+            ci_imaging=ci_imaging,
             ci_post_cti=ci_post_cti,
             hyper_noise_scalars=hyper_noise_scalars,
         )
@@ -241,7 +241,7 @@ def pipe_cti(ci_data_masked, instance, clocker, hyper_noise_scalars):
     )
 
     fit = ci_fit.CIFitImaging(
-        masked_ci_imaging=ci_data_masked,
+        ci_imaging=ci_data_masked,
         ci_post_cti=ci_post_cti,
         hyper_noise_scalars=hyper_noise_scalars,
     )

autocti/analysis/visualizer.py

@@ -47,7 +47,7 @@ def should_plot(name):
             imaging=ci_imaging, mat_plot_2d=mat_plot_2d, include_2d=self.include_2d
         )
 
-        ci_imaging_plotter.figures(
+        ci_imaging_plotter.figures_2d(
             image=should_plot("data"),
             noise_map=should_plot("noise_map"),
             inverse_noise_map=should_plot("inverse_noise_map"),
@@ -94,7 +94,7 @@ def should_plot(name):
             fit=fit, mat_plot_2d=mat_plot_2d, include_2d=self.include_2d
         )
 
-        ci_fit_plotter.figures(
+        ci_fit_plotter.figures_2d(
             image=should_plot("data"),
             noise_map=should_plot("noise_map"),
             signal_to_noise_map=should_plot("signal_to_noise_map"),
@@ -109,7 +109,7 @@ def should_plot(name):
 
             if should_plot("all_at_end_png"):
 
-                ci_fit_plotter.figures(
+                ci_fit_plotter.figures_2d(
                     image=True,
                     noise_map=True,
                     signal_to_noise_map=True,
@@ -183,17 +183,17 @@ def should_plot(name):
 
         if should_plot("subplot_residual_maps"):
             multi_plotter.subplot_of_figure(
-                func_name="figures", figure_name="residual_map"
+                func_name="figures_2d", figure_name="residual_map"
             )
 
         if should_plot("subplot_normalized_residual_maps"):
             multi_plotter.subplot_of_figure(
-                func_name="figures", figure_name="normalized_residual_map"
+                func_name="figures_2d", figure_name="normalized_residual_map"
             )
 
         if should_plot("subplot_chi_squared_maps"):
             multi_plotter.subplot_of_figure(
-                func_name="figures", figure_name="chi_squared_map"
+                func_name="figures_2d", figure_name="chi_squared_map"
             )
 
     def visualize_multiple_ci_fits_subplots_1d_lines(self, fits, line_region):
@@ -241,7 +241,7 @@ def visualize_fit_in_fits(self, fit):
             fit=fit, mat_plot_2d=mat_plot_2d, include_2d=self.include_2d
         )
 
-        ci_fit_plotter.figures(
+        ci_fit_plotter.figures_2d(
             image=True,
             noise_map=True,
             signal_to_noise_map=True,

autocti/charge_injection/__init__.py

@@ -7,8 +7,8 @@
 from .ci_hyper import CIHyperNoiseScalar
 from .ci_hyper import CIHyperNoiseCollection
 from .ci_imaging import CIImaging
-from .ci_imaging import SettingsMaskedCIImaging
-from .ci_imaging import MaskedCIImaging
+from .ci_imaging import SettingsCIImaging
+from .ci_imaging import CIImaging
 from .ci_imaging import SimulatorCIImaging
 from .ci_mask import SettingsCIMask
 from .ci_mask import CIMask2D

autocti/charge_injection/ci_fit.py

@@ -6,17 +6,14 @@
 
 class CIFitImaging(fit.FitImaging):
     def __init__(
-        self,
-        masked_ci_imaging: ci_imaging.MaskedCIImaging,
-        ci_post_cti,
-        hyper_noise_scalars=None,
+        self, ci_imaging: ci_imaging.CIImaging, ci_post_cti, hyper_noise_scalars=None
     ):
         """Fit a charge injection ci_data-set with a model cti image, also scalng the noises within a Bayesian
         framework.
 
         Parameters
         -----------
-        masked_ci_imaging
+        ci_imaging
             The charge injection image that is fitted.
         cti_params : arctic_params.ArcticParams
             The cti model parameters which describe how CTI during clocking.
@@ -26,22 +23,22 @@ def __init__(
             The ci_hyper-parameter(s) which the noise_scaling_maps_list is multiplied by to scale the noise-map.
         """
 
-        self.ci_masked_data = masked_ci_imaging
+        self.ci_masked_data = ci_imaging
         self.hyper_noise_scalars = hyper_noise_scalars
 
         if hyper_noise_scalars is not None and len(hyper_noise_scalars) > 0:
 
-            self.noise_scaling_maps = masked_ci_imaging.noise_scaling_maps
+            self.noise_scaling_maps = ci_imaging.noise_scaling_maps
 
             noise_map = hyper_noise_map_from_noise_map_and_noise_scalings(
                 hyper_noise_scalars=hyper_noise_scalars,
-                noise_scaling_maps=masked_ci_imaging.noise_scaling_maps,
-                noise_map=masked_ci_imaging.noise_map,
+                noise_scaling_maps=ci_imaging.noise_scaling_maps,
+                noise_map=ci_imaging.noise_map,
             )
 
-            masked_ci_imaging = masked_ci_imaging.modify_noise_map(noise_map=noise_map)
+            ci_imaging = ci_imaging.modify_noise_map(noise_map=noise_map)
 
-        super().__init__(imaging=masked_ci_imaging, model_image=ci_post_cti)
+        super().__init__(imaging=ci_imaging, model_image=ci_post_cti)
 
     @property
     def masked_ci_imaging(self):