remove redunant methods from mapping

Author: Jammy2211

autoarray/inversion/inversion/imaging/abstract.py

@@ -1,8 +1,6 @@
 import numpy as np
 from typing import Dict, List, Union, Type
 
-from autoconf import cached_property
-
 from autoarray.dataset.imaging.dataset import Imaging
 from autoarray.inversion.inversion.dataset_interface import DatasetInterface
 from autoarray.inversion.linear_obj.func_list import AbstractLinearObjFuncList
@@ -97,6 +95,7 @@ def operated_mapping_matrix_list(self) -> List[np.ndarray]:
                 self.psf.convolved_mapping_matrix_from(
                     mapping_matrix=linear_obj.mapping_matrix,
                     mask=self.mask,
+                    use_mixed_precision=self.settings.use_mixed_precision,
                     xp=self._xp,
                 )
                 if linear_obj.operated_mapping_matrix_override is None
@@ -138,7 +137,6 @@ def linear_func_operated_mapping_matrix_dict(self) -> Dict:
             if linear_func.operated_mapping_matrix_override is not None:
                 operated_mapping_matrix = linear_func.operated_mapping_matrix_override
             else:
-                vvv
                 operated_mapping_matrix = self.psf.convolved_mapping_matrix_from(
                     mapping_matrix=linear_func.mapping_matrix,
                     mask=self.mask,
@@ -203,7 +201,7 @@ def data_linear_func_matrix_dict(self):
 
         return data_linear_func_matrix_dict
 
-    @cached_property
+    @property
     def mapper_operated_mapping_matrix_dict(self) -> Dict:
         """
         The `operated_mapping_matrix` of a `Mapper` object describes the mappings between the observed data's values

autoarray/inversion/inversion/imaging/mapping.py

@@ -53,47 +53,6 @@ def __init__(
             xp=xp,
         )
 
-    @property
-    def _data_vector_mapper(self) -> np.ndarray:
-        """
-        Returns the `data_vector` of all mappers, a 1D vector whose values are solved for by the simultaneous
-        linear equations constructed by this object. The object is described in full in the method `data_vector`.
-
-        This method is used to compute part of the `data_vector` if there are also linear function list objects
-        in the inversion, and is separated into a separate method to enable preloading of the mapper `data_vector`.
-        """
-
-        if not self.has(cls=AbstractMapper):
-            return
-
-        data_vector = np.zeros(self.total_params)
-
-        mapper_list = self.cls_list_from(cls=AbstractMapper)
-        mapper_param_range_list = self.param_range_list_from(cls=AbstractMapper)
-
-        for i in range(len(mapper_list)):
-            mapper = mapper_list[i]
-            param_range = mapper_param_range_list[i]
-
-            operated_mapping_matrix = self.psf.convolved_mapping_matrix_from(
-                mapping_matrix=mapper.mapping_matrix,
-                mask=self.mask,
-                use_mixed_precision=self.settings.use_mixed_precision,
-                xp=self._xp
-            )
-
-            data_vector_mapper = (
-                inversion_imaging_util.data_vector_via_blurred_mapping_matrix_from(
-                    blurred_mapping_matrix=operated_mapping_matrix,
-                    image=self.data,
-                    noise_map=self.noise_map,
-                )
-            )
-
-            data_vector[param_range[0] : param_range[1],] = data_vector_mapper
-
-        return data_vector
-
     @cached_property
     def data_vector(self) -> np.ndarray:
         """
@@ -114,56 +73,6 @@ def data_vector(self) -> np.ndarray:
             noise_map=self.noise_map.array,
         )
 
-    @property
-    def _curvature_matrix_mapper_diag(self) -> Optional[np.ndarray]:
-        """
-        Returns the diagonal regions of the `curvature_matrix`, a 2D matrix which uses the mappings between the data
-        and the linear objects to construct the simultaneous linear equations. The object is described in full in
-        the method `curvature_matrix`.
-
-        This method computes the diagonal entries of all mapper objects in the `curvature_matrix`. It is separate from
-        other calculations to enable preloading of this calculation.
-        """
-
-        if not self.has(cls=AbstractMapper):
-            return None
-
-        curvature_matrix = np.zeros((self.total_params, self.total_params))
-
-        mapper_list = self.cls_list_from(cls=AbstractMapper)
-        mapper_param_range_list = self.param_range_list_from(cls=AbstractMapper)
-
-        for i in range(len(mapper_list)):
-            mapper_i = mapper_list[i]
-            mapper_param_range_i = mapper_param_range_list[i]
-
-            operated_mapping_matrix = self.psf.convolved_mapping_matrix_from(
-                mapping_matrix=mapper_i.mapping_matrix,
-                mask=self.mask,
-                use_mixed_precision=self.settings.use_mixed_precision,
-                xp=self._xp
-            )
-
-            diag = inversion_util.curvature_matrix_via_mapping_matrix_from(
-                mapping_matrix=operated_mapping_matrix,
-                noise_map=self.noise_map,
-                settings=self.settings,
-                add_to_curvature_diag=True,
-                no_regularization_index_list=self.no_regularization_index_list,
-                xp=self._xp,
-            )
-
-            curvature_matrix[
-                mapper_param_range_i[0] : mapper_param_range_i[1],
-                mapper_param_range_i[0] : mapper_param_range_i[1],
-            ] = diag
-
-        curvature_matrix = inversion_util.curvature_matrix_mirrored_from(
-            curvature_matrix=curvature_matrix, xp=self._xp
-        )
-
-        return curvature_matrix
-
     @cached_property
     def curvature_matrix(self):
         """

autoarray/inversion/inversion/settings.py

@@ -48,6 +48,7 @@ def __init__(
             For an interferometer inversion using the linear operators method, sets the maximum number of iterations
             of the solver (this input does nothing for dataset data and other interferometer methods).
         """
+        self.use_mixed_precision = use_mixed_precision
         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

test_autoarray/inversion/inversion/test_factory.py

@@ -290,9 +290,6 @@ def test__inversion_imaging__compare_mapping_and_sparse_operator_values(
         settings=aa.SettingsInversion(),
     )
 
-    assert inversion_sparse_operator._curvature_matrix_mapper_diag == pytest.approx(
-        inversion_mapping._curvature_matrix_mapper_diag, 1.0e-4
-    )
     assert inversion_sparse_operator.reconstruction == pytest.approx(
         inversion_mapping.reconstruction, 1.0e-4
     )