remove disable_fft_pad and imaigng plotter sends psf.kernel to plot

Author: Jammy2211

autoarray/dataset/imaging/simulator.py

@@ -192,13 +192,12 @@ def via_image_from(
             psf=self.psf,
             noise_map=noise_map,
             check_noise_map=False,
-            disable_fft_pad=True,
         )
 
         if over_sample_size is not None:
 
             dataset = dataset.apply_over_sampling(
-                over_sample_size_lp=over_sample_size.native, disable_fft_pad=True
+                over_sample_size_lp=over_sample_size.native,
             )
 
         return dataset

autoarray/dataset/plot/imaging_plotters.py

@@ -93,7 +93,7 @@ def figures_2d(
 
         if psf:
             self.mat_plot_2d.plot_array(
-                array=self.dataset.psf,
+                array=self.dataset.psf.kernel,
                 visuals_2d=self.visuals_2d,
                 auto_labels=AutoLabels(
                     title=title_str or f"Point Spread Function",

test_autoarray/dataset/imaging/test_dataset.py

@@ -173,7 +173,7 @@ def test__output_to_fits(imaging_7x7, test_data_path):
 
 
 def test__apply_mask(imaging_7x7, mask_2d_7x7, psf_3x3):
-    masked_imaging_7x7 = imaging_7x7.apply_mask(mask=mask_2d_7x7, disable_fft_pad=True)
+    masked_imaging_7x7 = imaging_7x7.apply_mask(mask=mask_2d_7x7)
 
     assert (masked_imaging_7x7.data.slim == np.ones(9)).all()
 
@@ -310,5 +310,5 @@ def test__psf_not_odd_x_odd_kernel__raises_error():
         psf = aa.Convolver(kernel=kernel)
 
         dataset = aa.Imaging(
-            data=image, noise_map=noise_map, psf=psf, disable_fft_pad=True
+            data=image, noise_map=noise_map, psf=psf,
         )

test_autoarray/fit/test_fit_dataset.py

@@ -66,7 +66,7 @@ def test__figure_of_merit__with_noise_covariance_matrix_in_dataset(
 
 def test__grid_offset_via_data_model(imaging_7x7, mask_2d_7x7, model_image_7x7):
 
-    masked_imaging_7x7 = imaging_7x7.apply_mask(mask=mask_2d_7x7, disable_fft_pad=True)
+    masked_imaging_7x7 = imaging_7x7.apply_mask(mask=mask_2d_7x7)
 
     fit = aa.m.MockFitImaging(
         dataset=masked_imaging_7x7,

test_autoarray/inversion/inversion/imaging/test_inversion_imaging_util.py

@@ -192,11 +192,11 @@ def test__data_vector_via_weighted_data_two_methods_agree():
     noise_map = np.random.uniform(size=mask.shape_native)
     noise_map = aa.Array2D(values=noise_map, mask=mask)
 
-    kernel = aa.Convolver.from_gaussian(
+    convolver = aa.Convolver.from_gaussian(
         shape_native=(7, 7), pixel_scales=mask.pixel_scales, sigma=1.0, normalize=True
     )
 
-    psf = kernel
+    psf = convolver
 
     mesh = aa.mesh.RectangularUniform(shape=(20, 20))
 
@@ -239,7 +239,7 @@ def test__data_vector_via_weighted_data_two_methods_agree():
 
         psf_weighted_data = aa.util.inversion_imaging.psf_weighted_data_from(
             weight_map_native=weight_map.native.array,
-            kernel_native=kernel.native.array,
+            kernel_native=convolver.kernel.native.array,
             native_index_for_slim_index=mask.derive_indexes.native_for_slim.astype(
                 "int"
             ),