Merge pull request #389 from Jammy2211/feature/psf_convolution_refactor

Feature/psf convolution refactor

Author: Jammy2211

autolens/__init__.py

@@ -24,6 +24,7 @@
 from autoarray.inversion.inversion.factory import inversion_from as Inversion
 from autoarray.inversion.mappers.abstract import Mapper
 from autoarray.inversion.mesh.border_relocator import BorderRelocator
+from autoarray.operators.convolver import Convolver
 from autoarray.operators.transformer import TransformerDFT
 from autoarray.operators.transformer import TransformerNUFFT
 from autoarray.preloads import Preloads
@@ -45,7 +46,6 @@
 from autoarray.structures.triangles.shape import Polygon
 from autoarray.structures.vectors.uniform import VectorYX2D
 from autoarray.structures.vectors.irregular import VectorYX2DIrregular
-from autoarray.structures.arrays.kernel_2d import Kernel2D
 from autoarray.structures.visibilities import Visibilities
 from autoarray.structures.visibilities import VisibilitiesNoiseMap
 from autoarray.inversion.mesh.mesh_geometry.rectangular import (

autolens/imaging/simulator.py

@@ -43,7 +43,7 @@ def via_tracer_from(self, tracer : Tracer, grid : aa.type.Grid2DLike, xp=np) ->
         )
 
         image = tracer.padded_image_2d_from(
-            grid=grid, psf_shape_2d=self.psf.shape_native, xp=xp
+            grid=grid, psf_shape_2d=self.psf.kernel.shape_native, xp=xp
         )
 
         over_sample_size = grid.over_sample_size.resized_from(
@@ -53,7 +53,7 @@ def via_tracer_from(self, tracer : Tracer, grid : aa.type.Grid2DLike, xp=np) ->
         dataset = self.via_image_from(image=image, over_sample_size=over_sample_size, xp=xp)
 
         return dataset.trimmed_after_convolution_from(
-            kernel_shape=self.psf.shape_native
+            kernel_shape=self.psf.kernel.shape_native
         )
 
     def via_galaxies_from(self, galaxies : List[ag.Galaxy], grid : aa.type.Grid2DLike) -> aa.Imaging:
@@ -166,10 +166,10 @@ def via_source_image_from(self, tracer : Tracer, grid : aa.type.Grid2DLike, sour
         )
 
         padded_image = image.padded_before_convolution_from(
-            kernel_shape=self.psf.shape_native
+            kernel_shape=self.psf.kernel.shape_native
         )
         dataset = self.via_image_from(image=padded_image)
 
         return dataset.trimmed_after_convolution_from(
-            kernel_shape=self.psf.shape_native
+            kernel_shape=self.psf.kernel.shape_native
         )

autolens/lens/tracer.py

@@ -1159,7 +1159,7 @@ def set_snr_of_snr_light_profiles(
         grid: aa.type.Grid2DLike,
         exposure_time: float,
         background_sky_level: float = 0.0,
-        psf: Optional[aa.Kernel2D] = None,
+        psf: Optional[aa.Convolver] = None,
     ):
         """
         Iterate over every `LightProfileSNR` in the tracer and set their `intensity` values to values which give

test_autolens/imaging/test_simulate_and_fit_imaging.py

@@ -11,7 +11,7 @@ def test__perfect_fit__chi_squared_0():
 
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2, over_sample_size=1)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -85,7 +85,7 @@ def test__simulate_imaging_data_and_fit__known_likelihood():
 
     grid = al.Grid2D.uniform(shape_native=(31, 31), pixel_scales=0.2)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -127,7 +127,7 @@ def test__simulate_imaging_data_and_fit__linear_light_profiles_agree_with_standa
 
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2, over_sample_size=1)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -235,7 +235,7 @@ def test__simulate_imaging_data_and_fit__linear_light_profiles_and_pixelization(
 
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2, over_sample_size=1)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -357,7 +357,7 @@ def test__simulate_imaging_data_and_fit__linear_light_profiles_and_pixelization_
 
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2, over_sample_size=2)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -489,7 +489,7 @@ def test__simulate_imaging_data_and_fit__linear_light_profiles_and_pixelization_
 
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2, over_sample_size=2)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -645,7 +645,7 @@ def test__simulate_imaging_data_and_fit__complex_fit_compare_mapping_matrix_spar
 
     grid = al.Grid2D.uniform(shape_native=(21, 21), pixel_scales=0.1)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 
@@ -748,7 +748,7 @@ def test__fit_figure_of_merit__mge_mass_model(masked_imaging_7x7, masked_imaging
     grid = al.Grid2D.uniform(shape_native=(11, 11), pixel_scales=0.2,
                              over_sample_size=8)
 
-    psf = al.Kernel2D.from_gaussian(
+    psf = al.Convolver.from_gaussian(
         shape_native=(3, 3), pixel_scales=0.2, sigma=0.75, normalize=True
     )
 

test_autolens/lens/test_tracer.py

@@ -457,7 +457,8 @@ def test__light_profile_snr__signal_to_noise_via_simulator_correct():
         ]
     )
 
-    psf = al.Kernel2D.no_mask(values=[[1.0]], pixel_scales=1.0)
+    kernel = al.Array2D.no_mask(values=[[1.0]], pixel_scales=1.0)
+    psf = al.Convolver(kernel=kernel)
 
     simulator = al.SimulatorImaging(
         psf=psf,