remove many np.array() conversions

Author: Jammy2211

autoarray/fit/fit_interferometer.py

@@ -122,7 +122,7 @@ def noise_normalization(self) -> float:
         [Noise_Term] = sum(log(2*pi*[Noise]**2.0))
         """
         return fit_util.noise_normalization_complex_from(
-            noise_map=self.noise_map,
+            noise_map=self.noise_map.array,
         )
 
     @property

autoarray/geometry/geometry_2d.py

@@ -294,7 +294,7 @@ def grid_pixel_indexes_2d_from(self, grid_scaled_2d: Grid2D) -> Array2D:
         from autoarray.structures.arrays.uniform_2d import Array2D
 
         grid_pixel_indexes_2d = geometry_util.grid_pixel_indexes_2d_slim_from(
-            grid_scaled_2d_slim=np.array(grid_scaled_2d),
+            grid_scaled_2d_slim=grid_scaled_2d,
             shape_native=self.shape_native,
             pixel_scales=self.pixel_scales,
             origin=self.origin,
@@ -320,7 +320,7 @@ def grid_scaled_2d_from(self, grid_pixels_2d: Grid2D) -> Grid2D:
         from autoarray.structures.grids.uniform_2d import Grid2D
 
         grid_scaled_1d = geometry_util.grid_scaled_2d_slim_from(
-            grid_pixels_2d_slim=np.array(grid_pixels_2d),
+            grid_pixels_2d_slim=grid_pixels_2d,
             shape_native=self.shape_native,
             pixel_scales=self.pixel_scales,
             origin=self.origin,

autoarray/inversion/pixelization/image_mesh/kmeans.py

@@ -105,7 +105,7 @@ def image_plane_mesh_grid_from(
             max_iter=5,
         )
 
-        grid = mask.derive_grid.unmasked
+        grid = mask.derive_grid.unmasked.array
 
         try:
             kmeans = kmeans.fit(X=grid, sample_weight=weight_map)

autoarray/mask/derive/grid_2d.py

@@ -112,7 +112,7 @@ def all_false(self) -> Grid2D:
             origin=self.mask.origin,
         )
 
-        return Grid2D(values=np.array(grid_slim), mask=self.mask.derive_mask.all_false)
+        return Grid2D(values=grid_slim, mask=self.mask.derive_mask.all_false)
 
     @property
     def unmasked(self) -> Grid2D:
@@ -163,7 +163,7 @@ def unmasked(self) -> Grid2D:
             pixel_scales=self.mask.pixel_scales,
             origin=self.mask.origin,
         )
-        return Grid2D(values=np.array(grid_2d), mask=self.mask)
+        return Grid2D(values=grid_2d, mask=self.mask)
 
     @property
     def edge(self) -> Grid2D:

autoarray/mask/derive/indexes_2d.py

@@ -112,7 +112,7 @@ def unmasked_slim(self) -> np.ndarray:
             print(derive_indexes_2d.unmasked_slim)
         """
         return mask_2d_util.mask_slim_indexes_from(
-            mask_2d=np.array(self.mask), return_masked_indexes=False
+            mask_2d=self.mask, return_masked_indexes=False
         ).astype("int")
 
     @property
@@ -154,7 +154,7 @@ def masked_slim(self) -> np.ndarray:
             print(derive_indexes_2d.masked_slim)
         """
         return mask_2d_util.mask_slim_indexes_from(
-            mask_2d=np.array(self.mask), return_masked_indexes=True
+            mask_2d=self.mask, return_masked_indexes=True
         ).astype("int")
 
     @property
@@ -202,7 +202,7 @@ def edge_slim(self) -> np.ndarray:
             print(derive_indexes_2d.edge_slim)
         """
         return mask_2d_util.edge_1d_indexes_from(
-            mask_2d=np.array(self.mask).astype("bool")
+            mask_2d=self.mask.astype("bool")
         ).astype("int")
 
     @property
@@ -304,7 +304,7 @@ def border_slim(self) -> np.ndarray:
             print(derive_indexes_2d.border_slim)
         """
         return mask_2d_util.border_slim_indexes_from(
-            mask_2d=np.array(self.mask).astype("bool")
+            mask_2d=self.mask.astype("bool")
         ).astype("int")
 
     @property
@@ -409,5 +409,5 @@ def native_for_slim(self) -> np.ndarray:
             print(derive_indexes_2d.native_for_slim)
         """
         return mask_2d_util.native_index_for_slim_index_2d_from(
-            mask_2d=np.array(self.mask),
+            mask_2d=self.mask,
         ).astype("int")

autoarray/mask/derive/mask_2d.py

@@ -204,7 +204,7 @@ def blurring_from(self, kernel_shape_native: Tuple[int, int]) -> Mask2D:
             raise exc.MaskException("psf_size of exterior region must be odd")
 
         blurring_mask = mask_2d_util.blurring_mask_2d_from(
-            mask_2d=np.array(self.mask),
+            mask_2d=self.mask,
             kernel_shape_native=kernel_shape_native,
         )
 
@@ -325,7 +325,7 @@ def edge_buffed(self) -> Mask2D:
         from autoarray.mask.mask_2d import Mask2D
 
         edge_buffed_mask = mask_2d_util.buffed_mask_2d_from(
-            mask_2d=np.array(self.mask)
+            mask_2d=self.mask
         ).astype("bool")
 
         return Mask2D(

autoarray/mask/mask_1d.py

@@ -153,9 +153,7 @@ def from_fits(
         """
 
         return cls(
-            mask=np.array(
-                array_1d_util.numpy_array_1d_via_fits_from(file_path=file_path, hdu=hdu)
-            ),
+            mask=array_1d_util.numpy_array_1d_via_fits_from(file_path=file_path, hdu=hdu),
             pixel_scales=pixel_scales,
             origin=origin,
         )

autoarray/mask/mask_2d.py

@@ -331,7 +331,7 @@ def circular(
         )
 
         return cls(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
             invert=invert,
@@ -385,7 +385,7 @@ def circular_annular(
         )
 
         return cls(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
             invert=invert,
@@ -442,7 +442,7 @@ def elliptical(
         )
 
         return cls(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
             invert=invert,
@@ -512,7 +512,7 @@ def elliptical_annular(
         )
 
         return cls(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
             invert=invert,
@@ -560,7 +560,7 @@ def from_pixel_coordinates(
         )
 
         return cls(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
             invert=invert,
@@ -598,7 +598,7 @@ def from_fits(
             mask = np.invert(mask.astype("bool"))
 
         mask = Mask2D(
-            mask=np.array(mask),
+            mask=mask,
             pixel_scales=pixel_scales,
             origin=origin,
         )
@@ -680,7 +680,7 @@ def header_dict(self) -> Dict:
     @property
     def mask_centre(self) -> Tuple[float, float]:
         grid = grid_2d_util.grid_2d_slim_via_mask_from(
-            mask_2d=np.array(self),
+            mask_2d=self,
             pixel_scales=self.pixel_scales,
             origin=self.origin,
         )
@@ -697,7 +697,7 @@ def shape_native_masked_pixels(self) -> Tuple[int, int]:
         and 12 False entries going horizontally in the central regions of the mask, then shape_masked_pixels=(15,12).
         """
 
-        where = np.array(np.where(np.invert(self.astype("bool"))))
+        where = np.where(np.invert(self.astype("bool")))
         y0, x0 = np.amin(where, axis=1)
         y1, x1 = np.amax(where, axis=1)
 

autoarray/operators/transformer.py

@@ -140,7 +140,7 @@ def visibilities_from(self, image: Array2D) -> Visibilities:
         else:
             visibilities = transformer_util.visibilities_from(
                 image_1d=image.slim.array,
-                grid_radians=np.array(self.grid),
+                grid_radians=self.grid.array,
                 uv_wavelengths=self.uv_wavelengths,
             )
 
@@ -170,7 +170,7 @@ def image_from(
         """
         image_slim = transformer_util.image_direct_from(
             visibilities=visibilities.in_array,
-            grid_radians=np.array(self.grid.array),
+            grid_radians=self.grid.array,
             uv_wavelengths=self.uv_wavelengths,
         )
 
@@ -210,7 +210,7 @@ def transform_mapping_matrix(self, mapping_matrix: np.ndarray) -> np.ndarray:
 
         return transformer_util.transformed_mapping_matrix_from(
             mapping_matrix=mapping_matrix,
-            grid_radians=np.array(self.grid),
+            grid_radians=self.grid.array,
             uv_wavelengths=self.uv_wavelengths,
         )
 

autoarray/plot/visuals/two_d.py

@@ -56,7 +56,7 @@ def plot_via_plotter(self, plotter, grid_indexes=None, mapper=None, geometry=Non
 
         if self.mask is not None:
             plotter.mask_scatter.scatter_grid(
-                grid=np.array(self.mask.derive_grid.edge.array)
+                grid=self.mask.derive_grid.edge.array
             )
 
         if self.border is not None: