fix inversion plotters

Author: Jammy2211

autoarray/inversion/inversion/imaging/w_tilde.py

@@ -521,14 +521,14 @@ def mapped_reconstructed_data_dict(self) -> Dict[LinearObj, Array2D]:
                     reconstruction=reconstruction,
                 )
 
+                mapped_reconstructed_image = self.psf.convolve_image_no_blurring(
+                    image=mapped_reconstructed_image, mask=self.mask
+                ).array
+
                 mapped_reconstructed_image = Array2D(
-                    values=mapped_reconstructed_image, mask=self.mask
+                    values=np.array(mapped_reconstructed_image), mask=self.mask
                 )
 
-                mapped_reconstructed_image = np.array(self.psf.convolve_image_no_blurring(
-                    image=mapped_reconstructed_image, mask=self.mask
-                ).array)
-
             else:
                 operated_mapping_matrix = self.linear_func_operated_mapping_matrix_dict[
                     linear_obj

autoarray/inversion/pixelization/mappers/mapper_grids.py

@@ -72,6 +72,7 @@ def image_plane_data_grid(self):
 
     @property
     def mesh_pixels_per_image_pixels(self):
+
         mesh_pixels_per_image_pixels = grid_2d_util.grid_pixels_in_mask_pixels_from(
             grid=np.array(self.image_plane_mesh_grid),
             shape_native=self.mask.shape_native,

autoarray/operators/contour.py

@@ -101,9 +101,6 @@ def hull(
         hull_x = grid_convex[hull_vertices, 0]
         hull_y = grid_convex[hull_vertices, 1]
 
-        grid_hull = jnp.zeros((len(hull_vertices), 2))
-
-        grid_hull[:, 1] = hull_x
-        grid_hull[:, 0] = hull_y
+        grid_hull = jnp.stack((hull_y, hull_x), axis=-1)
 
         return grid_hull

autoarray/plot/wrap/two_d/grid_scatter.py

@@ -55,7 +55,7 @@ def scatter_grid(self, grid: Union[np.ndarray, Grid2D]):
             config_dict["c"] = config_dict["c"][0]
 
         try:
-            plt.scatter(y=grid[:, 0], x=grid[:, 1], **config_dict)
+            plt.scatter(y=grid.array[:, 0], x=grid.array[:, 1], **config_dict)
         except (IndexError, TypeError):
             return self.scatter_grid_list(grid_list=grid)
 

autoarray/structures/grids/grid_2d_util.py

@@ -801,7 +801,6 @@ def compute_polygon_area(points):
     return 0.5 * np.abs(np.dot(x, np.roll(y, 1)) - np.dot(y, np.roll(x, 1)))
 
 
-@numba_util.jit()
 def grid_pixels_in_mask_pixels_from(
     grid, shape_native, pixel_scales, origin
 ) -> np.ndarray:
@@ -832,10 +831,11 @@ def grid_pixels_in_mask_pixels_from(
 
     mesh_pixels_per_image_pixel = np.zeros(shape=shape_native)
 
-    for i in range(grid_pixel_centres.shape[0]):
-        y = grid_pixel_centres[i, 0]
-        x = grid_pixel_centres[i, 1]
+    # Assuming grid_pixel_centres is a 2D array where each row contains (y, x) indices.
+    y_indices = grid_pixel_centres[:, 0]
+    x_indices = grid_pixel_centres[:, 1]
 
-        mesh_pixels_per_image_pixel[y, x] += 1
+    # Use np.add.at to increment the specific indices in a safe and efficient manner
+    np.add.at(mesh_pixels_per_image_pixel, (y_indices, x_indices), 1)
 
-    return mesh_pixels_per_image_pixel
+    return mesh_pixels_per_image_pixel