remove print statements

Author: Jammy2211

test_autoarray/inversion/inversion/test_abstract.py

@@ -235,8 +235,6 @@ def test__curvature_reg_matrix_reduced():
         linear_obj_list=linear_obj_list, curvature_reg_matrix=curvature_reg_matrix
     )
 
-    print(inversion.curvature_reg_matrix_reduced)
-
     assert (
         inversion.curvature_reg_matrix_reduced == np.array([[1.0, 2.0], [4.0, 5.0]])
     ).all()

test_autoarray/inversion/inversion/test_factory.py

@@ -389,15 +389,6 @@ def test__inversion_imaging__linear_obj_func_with_sparse_operator(
     assert inversion_mapping.data_vector == pytest.approx(
         inversion_sparse_operator.data_vector, 1.0e-4
     )
-<<<<<<< HEAD
-    print(inversion_mapping.curvature_matrix[0,2])
-    print(inversion_mapping.curvature_matrix[0,3])
-    print(inversion_w_tilde.curvature_matrix[0,2])
-    print(inversion_w_tilde.curvature_matrix[0,3])
-    ffff
-=======
-
->>>>>>> a655bb9e4603df17c8ff7f8d20459bb36fa03c5a
     assert inversion_mapping.curvature_matrix == pytest.approx(
         inversion_sparse_operator.curvature_matrix, 1.0e-4
     )

test_autoarray/inversion/regularizations/test_regularization_util.py

@@ -238,9 +238,6 @@ def test__weighted_regularization_matrix_from():
         neighbors=neighbors,
     )
 
-    print(regularization_matrix)
-    print(test_regularization_matrix)
-
     assert regularization_matrix == pytest.approx(test_regularization_matrix, 1.0e-4)
 
     # Here, we define the neighbors first here and make the B matrices based on them.
@@ -272,9 +269,6 @@ def test__weighted_regularization_matrix_from():
         neighbors=neighbors,
     )
 
-    print(regularization_matrix)
-    print(test_regularization_matrix)
-
     assert regularization_matrix == pytest.approx(test_regularization_matrix, 1.0e-4)
 
     b_matrix_1 = np.array([[-1, 1, 0, 0], [0, -1, 1, 0], [0, 0, -1, 1], [1, 0, 0, -1]])