Feature/unconvolved images

autogalaxy/abstract_fit.py

@@ -117,7 +117,8 @@ def linear_light_profile_intensity_dict(
         return linear_light_profile_intensity_dict
 
     def galaxy_linear_obj_data_dict_from(
-        self, use_image: bool = False
+        self,
+        use_operated: bool = True,
     ) -> Dict[Galaxy, aa.Array2D]:
         """
         Returns a dictionary mapping every galaxy containing a linear
@@ -129,16 +130,17 @@ def galaxy_linear_obj_data_dict_from(
         This is used to create the overall `galaxy_model_image_dict`, which maps every galaxy to its
         overall `model_data` (e.g. including the `model_data` of orindary light profiles too).
 
-        If `use_image=False`, the `reconstructed_data` of the inversion (e.g. an image for dataset data,
+        If `use_operated=False`, the `reconstructed_data` of the inversion (e.g. an image for dataset data,
         visibilities for  interferometer data) is input in the dictionary.
 
-        if `use_image=True`, the `reconstructed_image` of the inversion (e.g. the image for dataset data, the
+        if `use_operated=True`, the `reconstructed_operated_data` of the inversion (e.g. the image for dataset data, the
         real-space image for interferometer data) is input in the dictionary.
 
         Parameters
         ----------
-        use_image
-            Whether to put the reconstructed data or images in the dictionary.
+        use_operated
+            Whether to use the operated (e.g PSF convolved) images of the linear objects in the dictionary, or
+            the unoperated images.
 
         Returns
         -------
@@ -156,13 +158,12 @@ def galaxy_linear_obj_data_dict_from(
             except KeyError:
                 continue
 
-            if not use_image:
-                mapped_reconstructed = self.inversion.mapped_reconstructed_data_dict[
-                    linear_obj
-                ]
-
+            if use_operated:
+                mapped_reconstructed = (
+                    self.inversion.mapped_reconstructed_operated_data_dict[linear_obj]
+                )
             else:
-                mapped_reconstructed = self.inversion.mapped_reconstructed_image_dict[
+                mapped_reconstructed = self.inversion.mapped_reconstructed_data_dict[
                     linear_obj
                 ]
 

autogalaxy/config/visualize/plots.yaml

@@ -11,7 +11,7 @@
 # These can be disabled to save on hard-disk space but will lead to certain database functionality being disabled.
 
 subplot_format: [png]                      # Output format of all subplots, can be png, pdf or both (e.g. [png, pdf])
-fits_are_zoomed: true                      # If true, output .fits files are zoomed in on the center of the unmasked region image, saving hard-disk space.
+fits_are_zoomed: false                     # If true, output .fits files are zoomed in on the center of the unmasked region image, saving hard-disk space.
 
 dataset:                                   # Settings for plots of all datasets (e.g. ImagingPlotter, InterferometerPlotter).
   subplot_dataset: true                    # Plot subplot containing all dataset quantities (e.g. the data, noise-map, etc.)?
@@ -23,7 +23,8 @@ fit:                                       # Settings for plots of all fits (e.g
   subplot_of_galaxies: false               # Plot subplot of the model-image, subtracted image and other quantities of each galaxy?
   subplot_galaxy_images: false             # Plot subplot of the image of each galaxy in the model?
   fits_fit: false                          # Output a .fits file containing the fit model data, residual map, normalized residual map and chi-squared?
-  fits_model_galaxy_images : false         # Output a .fits file containing the model images of every galaxy?
+  fits_galaxy_images : false               # Output a .fits file containing the images (e.g. without PSF convolution) of every galaxy?
+  fits_model_galaxy_images : false         # Output a .fits file containing the model images (e.g. with PSF convolution) of every galaxy?
 
 fit_imaging: {}                            # Settings for plots of fits to imaging datasets (e.g. FitImagingPlotter).
 

autogalaxy/imaging/fit_imaging.py

@@ -161,10 +161,37 @@ def model_data(self) -> aa.Array2D:
         """
 
         if self.perform_inversion:
-            return self.blurred_image + self.inversion.mapped_reconstructed_data
+            return (
+                self.blurred_image + self.inversion.mapped_reconstructed_operated_data
+            )
 
         return self.blurred_image
 
+    @property
+    def galaxy_image_dict(self) -> Dict[Galaxy, np.ndarray]:
+        """
+        A dictionary which associates every galaxy in the fit with its image before operation (e.g. no PSF convolution
+        or NUFFT performed).
+
+        This image is the image of the sum of:
+
+        - The images of all ordinary light profiles summed before any operation is performed on them.
+        - The images of all linear objects (e.g. linear light profiles / pixelizations), where the images are solved
+          for first via the inversion.
+
+        This dictionary is used to output to .fits file the galaxy images.
+        """
+
+        galaxy_image_2d_dict = self.galaxies.galaxy_image_2d_dict_from(
+            grid=self.grids.lp,
+        )
+
+        galaxy_linear_obj_image_dict = self.galaxy_linear_obj_data_dict_from(
+            use_operated=False,
+        )
+
+        return {**galaxy_image_2d_dict, **galaxy_linear_obj_image_dict}
+
     @property
     def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         """
@@ -187,7 +214,7 @@ def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         )
 
         galaxy_linear_obj_image_dict = self.galaxy_linear_obj_data_dict_from(
-            use_image=True
+            use_operated=True,
         )
 
         return {**galaxy_blurred_image_2d_dict, **galaxy_linear_obj_image_dict}

autogalaxy/imaging/model/plotter_interface.py

@@ -60,6 +60,22 @@ def fits_to_fits(
 
         hdu_list.writeto(image_path / "fit.fits", overwrite=True)
 
+    if should_plot("fits_galaxy_images"):
+        number_plots = len(fit.galaxy_image_dict.keys()) + 1
+
+        image_list = [image.native_for_fits for image in fit.galaxy_image_dict.values()]
+
+        hdu_list = hdu_list_for_output_from(
+            values_list=[image_list[0].mask.astype("float")] + image_list,
+            ext_name_list=[
+                "mask",
+            ]
+            + [f"galaxy_{i}" for i in range(number_plots)],
+            header_dict=fit.mask.header_dict,
+        )
+
+        hdu_list.writeto(image_path / "galaxy_images.fits", overwrite=True)
+
     if should_plot("fits_model_galaxy_images"):
         number_plots = len(fit.galaxy_model_image_dict.keys()) + 1
 

autogalaxy/interferometer/fit_interferometer.py

@@ -139,12 +139,15 @@ def model_data(self) -> aa.Visibilities:
         """
 
         if self.perform_inversion:
-            return self.profile_visibilities + self.inversion.mapped_reconstructed_data
+            return (
+                self.profile_visibilities
+                + self.inversion.mapped_reconstructed_operated_data
+            )
 
         return self.profile_visibilities
 
     @property
-    def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
+    def galaxy_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         """
         A dictionary which associates every galaxy with its `image`.
 
@@ -157,15 +160,13 @@ def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         For modeling, this dictionary is used to set up the `adapt_images` that adapt certain pixelizations to the
         data being fitted.
         """
-        galaxy_model_image_dict = self.galaxies.galaxy_image_2d_dict_from(
-            grid=self.grids.lp
-        )
+        galaxy_image_dict = self.galaxies.galaxy_image_2d_dict_from(grid=self.grids.lp)
 
         galaxy_linear_obj_image_dict = self.galaxy_linear_obj_data_dict_from(
-            use_image=True
+            use_operated=False
         )
 
-        return {**galaxy_model_image_dict, **galaxy_linear_obj_image_dict}
+        return {**galaxy_image_dict, **galaxy_linear_obj_image_dict}
 
     @property
     def galaxy_model_visibilities_dict(self) -> Dict[Galaxy, np.ndarray]:
@@ -186,7 +187,7 @@ def galaxy_model_visibilities_dict(self) -> Dict[Galaxy, np.ndarray]:
         )
 
         galaxy_linear_obj_data_dict = self.galaxy_linear_obj_data_dict_from(
-            use_image=False
+            use_operated=True
         )
 
         return {**galaxy_model_visibilities_dict, **galaxy_linear_obj_data_dict}

autogalaxy/interferometer/model/plotter_interface.py

@@ -35,20 +35,18 @@ def fits_to_fits(
         The fit to output to a .fits file.
     """
 
-    if should_plot("fits_model_galaxy_images"):
+    if should_plot("fits_galaxy_images"):
 
-        image_list = [
-            image.native_for_fits for image in fit.galaxy_model_image_dict.values()
-        ]
+        image_list = [image.native_for_fits for image in fit.galaxy_image_dict.values()]
 
         hdu_list = hdu_list_for_output_from(
             values_list=[image_list[0].mask.astype("float")] + image_list,
             ext_name_list=["mask"]
-            + [f"galaxy_{i}" for i in range(len(fit.galaxy_model_image_dict.values()))],
+            + [f"galaxy_{i}" for i in range(len(fit.galaxy_image_dict.values()))],
             header_dict=fit.dataset.real_space_mask.header_dict,
         )
 
-        hdu_list.writeto(image_path / "model_galaxy_images.fits", overwrite=True)
+        hdu_list.writeto(image_path / "galaxy_images.fits", overwrite=True)
 
     if should_plot("fits_dirty_images"):
 

autogalaxy/interferometer/plot/fit_interferometer_plotters.py

@@ -179,7 +179,7 @@ def subplot_fit_real_space(self):
             mapper_index = 0
 
             self.inversion_plotter.figures_2d_of_pixelization(
-                pixelization_index=mapper_index, reconstructed_image=True
+                pixelization_index=mapper_index, reconstructed_operated_data=True
             )
             self.inversion_plotter.figures_2d_of_pixelization(
                 pixelization_index=mapper_index, reconstruction=True

test_autogalaxy/config/visualize.yaml

@@ -331,13 +331,15 @@ mat_wrap_2d:
       marker: .
       s: 17
 plots:
+  fits_are_zoomed: true
   dataset:
     subplot_dataset: true
   fit:
     subplot_fit: true
     subplot_of_galaxies: false
     fits_fit: true                          # Output a .fits file containing the fit model data, residual map, normalized residual map and chi-squared?
-    fits_model_galaxy_images : true         # Output a .fits file containing the model images of every galaxy?
+    fits_galaxy_images : true                # Output a .fits file containing the images (e.g. without PSF convolution) of every galaxy?
+    fits_model_galaxy_images : true          # Output a .fits file containing the model images (e.g. with PSF convolution) of every galaxy?
   fit_imaging: {}
   fit_interferometer:
     fits_dirty_images: true                 # output dirty_images.fits showing the dirty image, noise-map, model-data, resiual-map, normalized residual map and chi-squared map?

test_autogalaxy/galaxy/test_to_inversion.py

@@ -180,7 +180,7 @@ def test__inversion_imaging_from(grid_2d_7x7, masked_imaging_7x7):
 
     inversion = to_inversion.inversion
 
-    assert inversion.mapped_reconstructed_image == pytest.approx(
+    assert inversion.mapped_reconstructed_operated_data == pytest.approx(
         masked_imaging_7x7.data, 1.0e-2
     )
 
@@ -215,7 +215,7 @@ def test__inversion_interferometer_from(grid_2d_7x7, interferometer_7):
 
     inversion = to_inversion.inversion
 
-    assert inversion.mapped_reconstructed_data.real == pytest.approx(
+    assert inversion.mapped_reconstructed_operated_data.real == pytest.approx(
         interferometer_7.data.real, 1.0e-2
     )
 

test_autogalaxy/imaging/test_fit_imaging.py

@@ -234,6 +234,73 @@ def test__fit__model_dataset__grid_offset__handles_special_behaviour(
     assert fit.figure_of_merit == pytest.approx(-22.914118686169, 1.0e-4)
 
 
+def test__galaxy_image_dict(masked_imaging_7x7):
+    # Normal Light Profiles Only
+
+    g0 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(intensity=1.0))
+    g1 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(intensity=2.0))
+    g2 = ag.Galaxy(
+        redshift=0.5,
+        light_profile_0=ag.lp.Sersic(intensity=1.0),
+        light_profile_1=ag.lp.Sersic(intensity=2.0),
+    )
+    g3 = ag.Galaxy(redshift=0.5)
+
+    fit = ag.FitImaging(dataset=masked_imaging_7x7, galaxies=[g0, g1, g2, g3])
+
+    g0_image_2d = g0.image_2d_from(
+        grid=masked_imaging_7x7.grids.lp,
+    )
+
+    g1_image_2d = g1.image_2d_from(
+        grid=masked_imaging_7x7.grids.lp,
+    )
+
+    assert fit.galaxy_image_dict[g0] == pytest.approx(g0_image_2d.array, 1.0e-4)
+    assert fit.galaxy_image_dict[g1] == pytest.approx(g1_image_2d.array, 1.0e-4)
+    assert fit.galaxy_image_dict[g2] == pytest.approx(
+        g0_image_2d.array + g1_image_2d.array, 1.0e-4
+    )
+    assert (fit.galaxy_image_dict[g3].slim == np.zeros(9)).all()
+
+    # Linear Light PRofiles + Pixelization + Regularizaiton
+
+    g0 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(intensity=1.0, centre=(0.05, 0.05)))
+    g1_linear = ag.Galaxy(redshift=0.5, bulge=ag.lp_linear.Sersic(centre=(0.05, 0.05)))
+
+    pixelization = ag.Pixelization(
+        mesh=ag.mesh.RectangularUniform(shape=(3, 3)),
+        regularization=ag.reg.Constant(coefficient=1.0),
+    )
+
+    galaxy_pix_0 = ag.Galaxy(redshift=0.5, pixelization=pixelization)
+    galaxy_pix_1 = ag.Galaxy(redshift=0.5, pixelization=pixelization)
+
+    masked_imaging_7x7.data[0] = 3.0
+
+    fit = ag.FitImaging(
+        dataset=masked_imaging_7x7,
+        galaxies=[g0, g1_linear, g3, galaxy_pix_0, galaxy_pix_1],
+    )
+
+    assert (fit.galaxy_image_dict[g3] == np.zeros(9)).all()
+
+    assert fit.galaxy_image_dict[g0][4] == pytest.approx(23.944378406, 1.0e-4)
+    assert fit.galaxy_image_dict[g1_linear][4] == pytest.approx(-28.1424200, 1.0e-4)
+    assert fit.galaxy_image_dict[galaxy_pix_0][4] == pytest.approx(1.107972830, 1.0e-4)
+    assert fit.galaxy_image_dict[galaxy_pix_1][4] == pytest.approx(1.1079728213, 1.0e-4)
+
+    mapped_reconstructed_data = (
+        fit.galaxy_image_dict[g1_linear]
+        + fit.galaxy_image_dict[galaxy_pix_0]
+        + fit.galaxy_image_dict[galaxy_pix_1]
+    )
+
+    assert mapped_reconstructed_data == pytest.approx(
+        fit.inversion.mapped_reconstructed_data.array, 1.0e-4
+    )
+
+
 def test__galaxy_model_image_dict(masked_imaging_7x7):
     # Normal Light Profiles Only
 
@@ -309,7 +376,7 @@ def test__galaxy_model_image_dict(masked_imaging_7x7):
 
     assert fit.galaxy_model_image_dict[g1][4] == pytest.approx(1.25795063, 1.0e-4)
     assert fit.galaxy_model_image_dict[g1].native.array == pytest.approx(
-        fit.inversion.mapped_reconstructed_image.native.array, 1.0e-4
+        fit.inversion.mapped_reconstructed_operated_data.native.array, 1.0e-4
     )
 
     assert fit.model_data.native.array == pytest.approx(
@@ -349,19 +416,19 @@ def test__galaxy_model_image_dict(masked_imaging_7x7):
         1.10780906, 1.0e-4
     )
 
-    mapped_reconstructed_image = (
+    mapped_reconstructed_operated_data = (
         fit.galaxy_model_image_dict[g1_linear]
         + fit.galaxy_model_image_dict[galaxy_pix_0]
         + fit.galaxy_model_image_dict[galaxy_pix_1]
     )
 
-    assert mapped_reconstructed_image == pytest.approx(
-        fit.inversion.mapped_reconstructed_image.array, 1.0e-4
+    assert mapped_reconstructed_operated_data == pytest.approx(
+        fit.inversion.mapped_reconstructed_operated_data.array, 1.0e-4
     )
 
     assert fit.model_data == pytest.approx(
         fit.galaxy_model_image_dict[g0].array
-        + fit.inversion.mapped_reconstructed_image.array,
+        + fit.inversion.mapped_reconstructed_operated_data.array,
         1.0e-4,
     )