added weight floor to mesh adapt

Author: Jammy2211

autoarray/inversion/pixelization/mesh/rectangular.py

@@ -158,7 +158,7 @@ def requires_image_mesh(self):
 
 class RectangularSource(RectangularMagnification):
 
-    def __init__(self, shape: Tuple[int, int] = (3, 3), weight_power: float = 1.0):
+    def __init__(self, shape: Tuple[int, int] = (3, 3), weight_power: float = 1.0, weight_floor : float = 0.0):
         """
         A uniform mesh of rectangular pixels, which without interpolation are paired with a 2D grid of (y,x)
         coordinates.
@@ -190,6 +190,7 @@ def __init__(self, shape: Tuple[int, int] = (3, 3), weight_power: float = 1.0):
         super().__init__(shape=shape)
 
         self.weight_power = weight_power
+        self.weight_floor = weight_floor
 
     def mesh_weight_map_from(self, adapt_data, xp=np) -> np.ndarray:
         """
@@ -205,5 +206,6 @@ def mesh_weight_map_from(self, adapt_data, xp=np) -> np.ndarray:
         mesh_weight_map = xp.asarray(adapt_data.array)
         mesh_weight_map = xp.clip(mesh_weight_map, 1e-12, None)
         mesh_weight_map = mesh_weight_map**self.weight_power
+        mesh_weight_map[mesh_weight_map < self.weight_floor] = self.weight_floor
         mesh_weight_map /= xp.sum(mesh_weight_map)
         return mesh_weight_map

autoarray/operators/transformer.py

@@ -440,11 +440,14 @@ def transform_mapping_matrix(self, mapping_matrix: np.ndarray, xp=np) -> np.ndar
         - Each column of the input mapping matrix is reshaped into the native 2D image grid before transformation.
         - This method repeatedly calls `visibilities_from` for each column, which may be computationally intensive.
         """
-        transformed_mapping_matrix = 0 + 0j * np.zeros(
+        transformed_mapping_matrix = 0 + 0j * xp.zeros(
             (self.uv_wavelengths.shape[0], mapping_matrix.shape[1])
         )
 
         for source_pixel_1d_index in range(mapping_matrix.shape[1]):
+
+            print("hi")
+
             image_2d = array_2d_util.array_2d_native_from(
                 array_2d_slim=mapping_matrix[:, source_pixel_1d_index],
                 mask_2d=self.grid.mask,