refactor going well bout to do one final change on new branch

Author: Jammy2211

autoarray/inversion/pixelization/interpolator/delaunay.py

@@ -424,15 +424,7 @@ def delaunay(self) -> "scipy.spatial.Delaunay":
         `MeshException`, which helps exception handling in the `inversion` package.
         """
 
-        if self.preloads is not None:
-
-            skip_areas = self.preloads.skip_areas
-
-        else:
-
-            skip_areas = False
-
-        if not skip_areas:
+        if not self.mesh.skip_areas:
 
             if self._xp.__name__.startswith("jax"):
 

autoarray/inversion/pixelization/mesh/delaunay.py

@@ -37,6 +37,16 @@ def __init__(self, areas_factor: float = 0.5):
         super().__init__()
         self.areas_factor = areas_factor
 
+    @property
+    def skip_areas(self):
+        """
+        Whether to skip barycentric  area calculations and split point computations during Delaunay triangulation.
+        When True, the Delaunay interface returns only the minimal set of outputs (points, simplices, mappings)
+        without computing split_points or splitted_mappings. This optimization is useful for regularization
+        schemes like Matérn kernels that don't require area-based calculations. Default is False.
+        """
+        return False
+
     @property
     def mapper_cls(self):
 

autoarray/inversion/pixelization/mesh/knn.py

@@ -18,6 +18,16 @@ def __init__(
 
         super().__init__()
 
+    @property
+    def skip_areas(self):
+        """
+        Whether to skip barycentric  area calculations and split point computations during Delaunay triangulation.
+        When True, the Delaunay interface returns only the minimal set of outputs (points, simplices, mappings)
+        without computing split_points or splitted_mappings. This optimization is useful for regularization
+        schemes like Matérn kernels that don't require area-based calculations. Default is False.
+        """
+        return False
+
     @property
     def mapper_cls(self):
 

autoarray/preloads.py

@@ -24,7 +24,6 @@ def __init__(
         source_pixel_zeroed_indices: np.ndarray = None,
         image_plane_mesh_grid_list: np.ndarray = None,
         linear_light_profile_blurred_mapping_matrix=None,
-        skip_areas: bool = False,
     ):
         """
         Stores preloaded arrays and matrices used during pixelized linear inversions, improving both performance
@@ -80,11 +79,6 @@ def __init__(
             inversion, with the other component being the pixelization's pixels. These are fixed when the lens light
             is fixed to the maximum likelihood solution, allowing the blurred mapping matrix to be preloaded, but
             the intensity values will still be solved for during the inversion.
-        skip_areas
-            Whether to skip Voronoi area calculations and split point computations during Delaunay triangulation.
-            When True, the Delaunay interface returns only the minimal set of outputs (points, simplices, mappings)
-            without computing split_points or splitted_mappings. This optimization is useful for regularization
-            schemes like Matérn kernels that don't require area-based calculations. Default is False.
         """
         self.mapper_indices = None
         self.source_pixel_zeroed_indices = None
@@ -124,5 +118,3 @@ def __init__(
             self.linear_light_profile_blurred_mapping_matrix = np.array(
                 linear_light_profile_blurred_mapping_matrix
             )
-
-        self.skip_areas = skip_areas