fix all inversion unit tests

Author: Jammy2211

autoarray/inversion/inversion/inversion_util.py

@@ -61,9 +61,42 @@ def curvature_matrix_with_added_to_diag_from(
     curvature_matrix
         The curvature matrix which is being constructed in order to solve a linear system of equations.
     """
-    return curvature_matrix.at[
-        no_regularization_index_list, no_regularization_index_list
-    ].add(value)
+    try:
+        return curvature_matrix.at[
+            no_regularization_index_list, no_regularization_index_list
+        ].add(value)
+    except AttributeError:
+        return curvature_matrix_with_added_to_diag_from_numba(
+            curvature_matrix=curvature_matrix,
+            value=value,
+            no_regularization_index_list=no_regularization_index_list,
+        )
+
+@numba_util.jit()
+def curvature_matrix_with_added_to_diag_from_numba(
+        curvature_matrix: np.ndarray,
+        value: float,
+        no_regularization_index_list: Optional[List] = None,
+) -> np.ndarray:
+    """
+    It is common for the `curvature_matrix` computed to not be positive-definite, leading for the inversion
+    via `np.linalg.solve` to fail and raise a `LinAlgError`.
+
+    In many circumstances, adding a small numerical value of `1.0e-8` to the diagonal of the `curvature_matrix`
+    makes it positive definite, such that the inversion is performed without raising an error.
+
+    This function adds this numerical value to the diagonal of the curvature matrix.
+
+    Parameters
+    ----------
+    curvature_matrix
+        The curvature matrix which is being constructed in order to solve a linear system of equations.
+    """
+
+    for i in no_regularization_index_list:
+        curvature_matrix[i, i] += value
+
+    return curvature_matrix
 
 
 def curvature_matrix_mirrored_from(

test_autoarray/inversion/inversion/interferometer/test_inversion_interferometer_util.py

@@ -272,8 +272,8 @@ def test__identical_inversion_values_for_two_methods():
         == inversion_mapping_matrices.regularization_matrix
     ).all()
 
-    assert inversion_w_tilde.data_vector.array == pytest.approx(
-        inversion_mapping_matrices.data_vector.array, 1.0e-8
+    assert inversion_w_tilde.data_vector == pytest.approx(
+        inversion_mapping_matrices.data_vector, 1.0e-8
     )
     assert inversion_w_tilde.curvature_matrix == pytest.approx(
         inversion_mapping_matrices.curvature_matrix, 1.0e-8
@@ -285,8 +285,8 @@ def test__identical_inversion_values_for_two_methods():
     assert inversion_w_tilde.reconstruction == pytest.approx(
         inversion_mapping_matrices.reconstruction, abs=1.0e-1
     )
-    assert inversion_w_tilde.mapped_reconstructed_image == pytest.approx(
-        inversion_mapping_matrices.mapped_reconstructed_image, abs=1.0e-1
+    assert inversion_w_tilde.mapped_reconstructed_image.array == pytest.approx(
+        inversion_mapping_matrices.mapped_reconstructed_image.array, abs=1.0e-1
     )
     assert inversion_w_tilde.mapped_reconstructed_data == pytest.approx(
         inversion_mapping_matrices.mapped_reconstructed_data, abs=1.0e-1