remove force edge pixels to zero

Author: Jammy2211

autoarray/inversion/inversion/abstract.py

@@ -327,9 +327,6 @@ def regularization_matrix(self) -> Optional[np.ndarray]:
         For multiple mappers, the regularization matrix is computed as the block diagonal of each individual mapper.
         The scipy function `block_diag` has an overhead associated with it and if there is only one mapper and
         regularization it is bypassed.
-
-        If the `settings.force_edge_pixels_to_zeros` is `True`, the edge pixels of each mapper in the inversion
-        are regularized so high their value is forced to zero.
         """
         if self._xp.__name__.startswith("jax"):
             from jax.scipy.linalg import block_diag
@@ -425,10 +422,7 @@ def reconstruction(self) -> np.ndarray:
         """
         if self.settings.use_positive_only_solver:
 
-            if (
-                self.preloads.source_pixel_zeroed_indices is not None
-                and self.settings.force_edge_pixels_to_zeros
-            ):
+            if self.preloads.source_pixel_zeroed_indices is not None:
 
                 # ids of values which are not zeroed and therefore kept in soluiton, which is computed in preloads.
                 ids_to_keep = self.preloads.source_pixel_zeroed_indices_to_keep

autoarray/inversion/inversion/settings.py

@@ -13,7 +13,6 @@ def __init__(
         use_positive_only_solver: Optional[bool] = None,
         positive_only_uses_p_initial: Optional[bool] = None,
         use_border_relocator: Optional[bool] = None,
-        force_edge_pixels_to_zeros: bool = True,
         no_regularization_add_to_curvature_diag_value: float = None,
         use_w_tilde_numpy: bool = False,
         use_source_loop: bool = False,
@@ -52,7 +51,6 @@ def __init__(
         self._use_positive_only_solver = use_positive_only_solver
         self._positive_only_uses_p_initial = positive_only_uses_p_initial
         self._use_border_relocator = use_border_relocator
-        self.force_edge_pixels_to_zeros = force_edge_pixels_to_zeros
         self._no_regularization_add_to_curvature_diag_value = (
             no_regularization_add_to_curvature_diag_value
         )

test_autoarray/inversion/inversion/test_factory.py

@@ -281,7 +281,6 @@ def test__inversion_imaging__via_linear_obj_func_and_mapper__force_edge_pixels_t
         linear_obj_list=[linear_obj, delaunay_mapper_9_3x3],
         settings=aa.SettingsInversion(
             no_regularization_add_to_curvature_diag_value=False,
-            force_edge_pixels_to_zeros=True,
         ),
     )
 
@@ -295,7 +294,6 @@ def test__inversion_imaging__via_linear_obj_func_and_mapper__force_edge_pixels_t
         settings=aa.SettingsInversion(
             use_positive_only_solver=True,
             no_regularization_add_to_curvature_diag_value=False,
-            force_edge_pixels_to_zeros=True,
         ),
     )
 
@@ -362,7 +360,6 @@ def test__inversion_imaging__linear_obj_func_and_non_func_give_same_terms(
         linear_obj_list=[linear_obj, rectangular_mapper_7x7_3x3],
         settings=aa.SettingsInversion(
             use_positive_only_solver=True,
-            force_edge_pixels_to_zeros=False,
         ),
     )
 
@@ -377,7 +374,6 @@ def test__inversion_imaging__linear_obj_func_and_non_func_give_same_terms(
         linear_obj_list=[rectangular_mapper_7x7_3x3],
         settings=aa.SettingsInversion(
             use_positive_only_solver=True,
-            force_edge_pixels_to_zeros=False,
         ),
     )
 

test_autoarray/inversion/inversion/test_settings_dict.py

@@ -15,7 +15,6 @@ def make_settings_dict():
         "arguments": {
             "use_positive_only_solver": False,
             "positive_only_uses_p_initial": False,
-            "force_edge_pixels_to_zeros": True,
             "no_regularization_add_to_curvature_diag_value": 1e-08,
             "use_w_tilde_numpy": False,
             "use_source_loop": False,