variable -> model

Author: rhayes777

test_autoarray/unit/dataset/test_imaging.py

@@ -321,7 +321,7 @@ def test__image_and_exposure_times_range_of_values__background_has_value_9___noi
     def test__image_and_exposure_times_and_background_are_all_ranges_of_values__noise_estimates_correct(
         self
     ):
-        # Use same pattern as above, noting that we are now also using a variable background signal_to_noise_ratio map.
+        # Use same pattern as above, noting that we are now also using a model background signal_to_noise_ratio map.
 
         image = aa.array.manual_2d(array=[[5.0, 3.0], [10.0, 20.0]])
 
@@ -2277,7 +2277,7 @@ def test__simulate_function__turns_exposure_time_and_sky_level_to_arrays(self):
 
         background_sky_map = aa.array.full(fill_value=16.0, shape_2d=image.mask.shape)
 
-        imaging_variable = aa.imaging.simulate(
+        imaging_model = aa.imaging.simulate(
             image=image,
             exposure_time=1.0,
             exposure_time_map=exposure_time_map,
@@ -2309,14 +2309,14 @@ def test__simulate_function__turns_exposure_time_and_sky_level_to_arrays(self):
         )
 
         assert (
-            imaging_variable.exposure_time_map.in_2d
+            imaging_model.exposure_time_map.in_2d
             == imaging_simulated.exposure_time_map.in_2d
         ).all()
-        assert imaging_variable.image.in_2d == pytest.approx(
+        assert imaging_model.image.in_2d == pytest.approx(
             imaging_simulated.image.in_2d, 1e-4
         )
         assert (
-            imaging_variable.background_noise_map.in_2d
+            imaging_model.background_noise_map.in_2d
             == imaging_simulated.background_noise_map.in_2d
         ).all()
 

test_autoarray/unit/util/test_regularization_util.py

@@ -394,7 +394,7 @@ def test__4_b_matrices_size_6x6__weights_all_1s__makes_correct_regularization_ma
             test_regularization_matrix, 1.0e-4
         )
 
-    def test__2_b_matrices_size_4x4_variables_regularization_weights__makes_correct_regularization_matrix(
+    def test__2_b_matrices_size_4x4_models_regularization_weights__makes_correct_regularization_matrix(
         self
     ):
         # Simple case, where we have just one regularization direction, regularizing pixel 0 -> 1 and 1 -> 2.