fix test imaging

Author: Jammy2211

autoarray/dataset/imaging/dataset.py

@@ -204,9 +204,9 @@ def w_tilde(self):
             indexes,
             lengths,
         ) = inversion_imaging_util.w_tilde_curvature_preload_imaging_from(
-            noise_map_native=np.array(self.noise_map.native),
-            kernel_native=np.array(self.psf.native),
-            native_index_for_slim_index=self.mask.derive_indexes.native_for_slim,
+            noise_map_native=np.array(self.noise_map.native.array).astype("float64"),
+            kernel_native=np.array(self.psf.native.array).astype("float64"),
+            native_index_for_slim_index=np.array(self.mask.derive_indexes.native_for_slim).astype("int"),
         )
 
         return WTildeImaging(
@@ -409,20 +409,20 @@ def apply_noise_scaling(
         """
 
         if signal_to_noise_value is None:
-            noise_map = self.noise_map.native
-            noise_map[mask == False] = noise_value
+            noise_map = np.array(self.noise_map.native.array)
+            noise_map[mask.array == False] = noise_value
         else:
             noise_map = np.where(
                 mask == False,
-                np.median(self.data.native[mask.derive_mask.edge == False])
+                np.median(self.data.native.array[mask.derive_mask.edge == False])
                 / signal_to_noise_value,
-                self.noise_map.native,
+                self.noise_map.native.array,
             )
 
         if should_zero_data:
-            data = np.where(np.invert(mask), 0.0, self.data.native)
+            data = np.where(np.invert(mask.array), 0.0, self.data.native.array)
         else:
-            data = self.data.native
+            data = self.data.native.array
 
         data_unmasked = Array2D.no_mask(
             values=data,

test_autoarray/dataset/imaging/test_dataset.py

@@ -139,7 +139,7 @@ def test__apply_mask(imaging_7x7, mask_2d_7x7, psf_3x3):
         == 2.0 * np.ones((7, 7)) * np.invert(mask_2d_7x7)
     ).all()
 
-    assert (masked_imaging_7x7.psf.slim == (1.0 / 3.0) * psf_3x3.slim).all()
+    assert masked_imaging_7x7.psf.slim == pytest.approx((1.0 / 3.0) * psf_3x3.slim, 1.0e-4)
 
     assert type(masked_imaging_7x7.psf) == aa.Kernel2D
     assert masked_imaging_7x7.w_tilde.curvature_preload.shape == (35,)
@@ -244,4 +244,9 @@ def test__noise_map_unmasked_has_zeros_or_negative__raises_exception():
 def test__psf_not_odd_x_odd_kernel__raises_error():
 
     with pytest.raises(exc.KernelException):
-        aa.Kernel2D.no_mask(values=[[0.0, 1.0], [1.0, 2.0]], pixel_scales=1.0)
+        image = aa.Array2D.ones(shape_native=(3, 3), pixel_scales=1.0)
+        noise_map = aa.Array2D.ones(shape_native=(3, 3), pixel_scales=1.0)
+        psf = aa.Kernel2D.no_mask(values=[[0.0, 1.0], [1.0, 2.0]], pixel_scales=1.0)
+
+        dataset = aa.Imaging(data=image, noise_map=noise_map, psf=psf, pad_for_psf=False)
+

test_autoarray/dataset/imaging/test_simulator.py

@@ -70,7 +70,7 @@ def test__via_image_from__psf_off__noise_off_value_is_noise_value(
         == np.array([[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0]])
     ).all()
 
-    assert np.allclose(dataset.noise_map.native, 0.2 * np.ones((3, 3)))
+    assert np.allclose(dataset.noise_map.native.array, 0.2 * np.ones((3, 3)))
 
 
 def test__via_image_from__psf_off__background_sky_on(image_central_delta_3x3):