fix unit test

Author: Jammy2211

autoarray/inversion/inversion/abstract.py

@@ -791,7 +791,7 @@ def reconstruction_noise_map(self):
 
         The noise-map of the reconstruction is the RMS standard deviation of the noise in every pixel of the
         reconstruction. This definition is identical to the `noise_map` attributes of dataset objects.
-        
+
         It is computed as the square root of the diagonal of the `reconstruction_noise_map_with_covariance` matrix,
         which is the same matrix used to solve for the reconstruction via the linear inversion.
 
@@ -804,7 +804,9 @@ def reconstruction_noise_map(self):
 
     @property
     def reconstruction_noise_map_dict(self) -> Dict[LinearObj, np.ndarray]:
-        return self.source_quantity_dict_from(source_quantity=self.reconstruction_noise_map)
+        return self.source_quantity_dict_from(
+            source_quantity=self.reconstruction_noise_map
+        )
 
     def regularization_weights_from(self, index: int) -> np.ndarray:
         linear_obj = self.linear_obj_list[index]

autoarray/inversion/mock/mock_inversion.py

@@ -59,8 +59,8 @@ def __init__(
         self._mapped_reconstructed_data_dict = mapped_reconstructed_data_dict
         self._mapped_reconstructed_image_dict = mapped_reconstructed_image_dict
 
-        self._errors = reconstruction_noise_map
-        self._errors_dict = reconstruction_noise_map_dict
+        self._reconstruction_noise_map = reconstruction_noise_map
+        self._reconstruction_noise_map_dict = reconstruction_noise_map_dict
 
         self._regularization_term = regularization_term
         self._log_det_curvature_reg_matrix_term = log_det_curvature_reg_matrix_term
@@ -172,15 +172,15 @@ def mapped_reconstructed_image_dict(self):
 
     @property
     def reconstruction_noise_map(self):
-        if self._errors is None:
+        if self._reconstruction_noise_map is None:
             return super().reconstruction_noise_map
-        return self._errors
+        return self._reconstruction_noise_map
 
     @property
     def reconstruction_noise_map_dict(self):
-        if self._errors_dict is None:
+        if self._reconstruction_noise_map_dict is None:
             return super().reconstruction_noise_map_dict
-        return self._errors_dict
+        return self._reconstruction_noise_map_dict
 
     @property
     def regularization_term(self):

autoarray/inversion/plot/inversion_plotters.py

@@ -239,8 +239,12 @@ def figures_2d_of_pixelization(
         if reconstruction_noise_map:
             try:
                 mapper_plotter.plot_source_from(
-                    pixel_values=self.inversion.reconstruction_noise_map_dict[mapper_plotter.mapper],
-                    auto_labels=AutoLabels(title="Noise Map", filename="reconstruction_noise_map"),
+                    pixel_values=self.inversion.reconstruction_noise_map_dict[
+                        mapper_plotter.mapper
+                    ],
+                    auto_labels=AutoLabels(
+                        title="Noise Map", filename="reconstruction_noise_map"
+                    ),
                 )
 
             except TypeError:
@@ -250,7 +254,9 @@ def figures_2d_of_pixelization(
             try:
                 signal_to_noise_values = (
                     self.inversion.reconstruction_dict[mapper_plotter.mapper]
-                    / self.inversion.reconstruction_noise_map_dict[mapper_plotter.mapper]
+                    / self.inversion.reconstruction_noise_map_dict[
+                        mapper_plotter.mapper
+                    ]
                 )
 
                 mapper_plotter.plot_source_from(
@@ -390,7 +396,9 @@ def subplot_of_mapper(
 
         self.set_title(label="Noise-Map (Unzoomed)")
         self.figures_2d_of_pixelization(
-            pixelization_index=mapper_index, reconstruction_noise_map=True, zoom_to_brightest=False
+            pixelization_index=mapper_index,
+            reconstruction_noise_map=True,
+            zoom_to_brightest=False,
         )
 
         self.set_title(label="Regularization Weights (Unzoomed)")

test_autoarray/inversion/inversion/test_abstract.py

@@ -636,7 +636,9 @@ def test__reconstruction_noise_map():
 
     inversion = aa.m.MockInversion(curvature_reg_matrix=curvature_reg_matrix)
 
-    assert inversion.errors_with_covariance == pytest.approx(
-        np.array([[2.5, -1.0, -0.5], [-1.0, 1.0, 0.0], [-0.5, 0.0, 0.5]]), 1.0e-2
+    assert inversion.reconstruction_noise_map_with_covariance[0, 0] == pytest.approx(
+        np.sqrt(2.5), 1.0e-2
+    )
+    assert inversion.reconstruction_noise_map == pytest.approx(
+        np.sqrt(np.array([2.5, 1.0, 0.5])), 1.0e-3
     )
-    assert inversion.reconstruction_noise_map == pytest.approx(np.array([2.5, 1.0, 0.5]), 1.0e-3)