fix numpy interface to vertex areas

Author: Jammy2211

autoarray/structures/mesh/triangulation_2d.py

@@ -1,5 +1,5 @@
 import numpy as np
-
+import scipy.spatial
 from typing import List, Union, Tuple
 
 from autoconf import cached_property
@@ -12,8 +12,7 @@
 from autoarray.structures.grids import grid_2d_util
 
 
-import numpy as np
-import scipy.spatial
+
 
 
 def scipy_delaunay_padded(points_np, max_simplices):
@@ -146,7 +145,10 @@ def vertex_areas_from_delaunay(points, simplices, xp=np):
     vertex_area = xp.zeros(n_pts)
 
     # Scatter-add: NumPy and JAX both support this API!
-    vertex_area = vertex_area.at[scatter_idx].add(scatter_vals)
+    if xp.__name__.startswith("jax"):
+        vertex_area = vertex_area.at[scatter_idx].add(scatter_vals)
+    else:
+        np.add.at(vertex_area, scatter_idx, scatter_vals)
 
     return vertex_area
 
@@ -289,6 +291,7 @@ def delaunay(self) -> "scipy.spatial.Delaunay":
         to compute the Voronoi mesh are ill posed. These exceptions are caught and combined into a single
         `MeshException`, which helps exception handling in the `inversion` package.
         """
+
         mesh_grid = self._xp.stack([self.array[:, 0], self.array[:, 1]]).T
 
         if self._xp.__name__.startswith("jax"):

test_autoarray/structures/mesh/test_delaunay.py

@@ -3,6 +3,7 @@
 
 import autoarray as aa
 
+from autoarray.structures.mesh.triangulation_2d import vertex_areas_from_delaunay
 
 def test__edge_pixel_list():
     grid = np.array(
@@ -58,3 +59,4 @@ def test__interpolated_array_from():
     assert interpolated_array.native == pytest.approx(
         np.array([[1.0, 1.907216], [1.0, 1.0], [1.0, 1.0]]), 1.0e-4
     )
+