refactor complete

Author: Jammy2211

autogalaxy/__init__.py

@@ -14,17 +14,13 @@
 from autoarray.inversion import regularization as reg  # noqa
 from autoarray.inversion.pixelization import image_mesh
 from autoarray.inversion.pixelization.mappers.abstract import AbstractMapper  # noqa
-from autoarray.inversion.inversion.settings import SettingsInversion  # noqa
+from autoarray.settings import Settings  # noqa
 from autoarray.inversion.inversion.factory import inversion_from as Inversion  # noqa
 from autoarray.inversion.pixelization.image_mesh.abstract import AbstractImageMesh
 from autoarray.inversion.pixelization.mesh.abstract import AbstractMesh
 from autoarray.inversion.regularization.abstract import AbstractRegularization
 from autoarray.inversion.pixelization.pixelization import Pixelization  # noqa
 from autoarray.inversion.pixelization.mappers.abstract import AbstractMapper
-from autoarray.inversion.pixelization.mappers.mapper_grids import MapperGrids  # noqa
-from autoarray.inversion.pixelization.mappers.factory import (
-    mapper_from as Mapper,
-)  # noqa
 from autoarray.inversion.pixelization.border_relocator import BorderRelocator
 from autoarray.preloads import Preloads
 from autoarray.preloads import mapper_indices_from
@@ -43,8 +39,8 @@
 from autoarray.structures.grids.uniform_2d import Grid2D  # noqa
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular  # noqa
 from autoarray.operators.over_sampling.over_sampler import OverSampler  # noqa
-from autoarray.inversion.pixelization.mesh_grid.rectangular_2d import Mesh2DRectangular  # noqa
-from autoarray.inversion.pixelization.mesh_grid.delaunay_2d import Mesh2DDelaunay  # noqa
+from autoarray.inversion.pixelization.mesh_grid.rectangular import Mesh2DRectangular  # noqa
+from autoarray.inversion.pixelization.mesh_grid.delaunay import Mesh2DDelaunay  # noqa
 from autoarray.structures.vectors.uniform import VectorYX2D  # noqa
 from autoarray.structures.vectors.irregular import VectorYX2DIrregular  # noqa
 from autoarray.layout.region import Region1D  # noqa

autogalaxy/abstract_fit.py

@@ -15,7 +15,7 @@
 
 
 class AbstractFitInversion:
-    def __init__(self, model_obj, settings_inversion: aa.SettingsInversion, xp=np):
+    def __init__(self, model_obj, settings: aa.Settings, xp=np):
         """
         An abstract fit object which fits to datasets (e.g. imaging, interferometer) inherit from.
 
@@ -28,11 +28,11 @@ def __init__(self, model_obj, settings_inversion: aa.SettingsInversion, xp=np):
             The object which contains the model components (e.g. light profiles, galaxies, etc) which are used to
             create the model-data that fits the data. In PyAutoGalaxy this is a list of galaxies and PyAutoLens
             it is a `Tracer`.
-        settings_inversion
+        settings
             Settings controlling how an inversion is fitted for example which linear algebra formalism is used.
         """
         self.model_obj = model_obj
-        self.settings_inversion = settings_inversion
+        self.settings = settings or aa.Settings()
         self.use_jax = xp is not np
 
     @property
@@ -75,7 +75,7 @@ def perform_inversion(self) -> bool:
     def sparse_operator(self) -> Optional[aa.ImagingSparseOperator]:
         """
         Only call the `sparse_operator` property of a dataset used to perform efficient linear algebra calculations if
-        the SettingsInversion()` object has `use_sparse_operator=True`, to avoid unnecessary computation.
+        the Settings()` object has `use_sparse_operator=True`, to avoid unnecessary computation.
 
         Returns
         -------

autogalaxy/aggregator/ellipse/fit_ellipse.py

@@ -33,7 +33,7 @@ def _fit_ellipse_from(
     is instead used to load lists of the data, noise-map, PSF and mask and combine them into a list of
     `FitEllipse` objects.
 
-    The settings of an inversion can be overwritten by inputting a `settings_inversion` object, for example
+    The settings of an inversion can be overwritten by inputting a `settings` object, for example
     if you want to use a grid with a different inversion solver.
 
     Parameters

autogalaxy/aggregator/imaging/fit_imaging.py

@@ -16,7 +16,7 @@
 def _fit_imaging_from(
     fit: af.Fit,
     instance: Optional[af.ModelInstance] = None,
-    settings_inversion: aa.SettingsInversion = None,
+    settings: aa.Settings = None,
 ) -> List[FitImaging]:
     """
     Returns a list of `FitImaging` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
@@ -26,7 +26,7 @@ def _fit_imaging_from(
 
     - The imaging data, noise-map, PSF and settings as .fits files (e.g. `dataset/data.fits`).
     - The mask used to mask the `Imaging` data structure in the fit (`dataset.fits[hdu=0]`).
-    - The settings of inversions used by the fit (`dataset/settings_inversion.json`).
+    - The settings of inversions used by the fit (`dataset/settings.json`).
 
     Each individual attribute can be loaded from the database via the `fit.value()` method.
 
@@ -37,7 +37,7 @@ def _fit_imaging_from(
     is instead used to load lists of the data, noise-map, PSF and mask and combine them into a list of
     `FitImaging` objects.
 
-    The settings of an inversion can be overwritten by inputting a `settings_inversion` object, for example
+    The settings of an inversion can be overwritten by inputting a `settings` object, for example
     if you want to use a grid with a different inversion solver.
 
     Parameters
@@ -48,8 +48,8 @@ def _fit_imaging_from(
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
-    settings_inversion
-        Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+    settings
+        Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
     """
 
     from autogalaxy.imaging.fit_imaging import FitImaging
@@ -62,7 +62,7 @@ def _fit_imaging_from(
 
     adapt_images_list = agg_util.adapt_images_from(fit=fit)
 
-    settings_inversion = settings_inversion or fit.value(name="settings_inversion")
+    settings = settings or fit.value(name="settings")
 
     fit_dataset_list = []
 
@@ -79,7 +79,7 @@ def _fit_imaging_from(
                 galaxies=galaxies,
                 dataset_model=dataset_model,
                 adapt_images=adapt_images,
-                settings_inversion=settings_inversion,
+                settings=settings,
             )
         )
 
@@ -90,7 +90,7 @@ class FitImagingAgg(af.AggBase):
     def __init__(
         self,
         aggregator: af.Aggregator,
-        settings_inversion: Optional[aa.SettingsInversion] = None,
+        settings: Optional[aa.Settings] = None,
     ):
         """
             Interfaces with an `PyAutoFit` aggregator object to create instances of `FitImaging` objects from the results
@@ -101,7 +101,7 @@ def __init__(
 
             - The imaging data, noise-map, PSF and settings as .fits files (e.g. `dataset/data.fits`).
             - The mask used to mask the `Imaging` data structure in the fit (`dataset.fits[hdu=0]`).
-            - The settings of inversions used by the fit (`dataset/settings_inversion.json`).
+            - The settings of inversions used by the fit (`dataset/settings.json`).
 
             The `aggregator` contains the path to each of these files, and they can be loaded individually. This class
             can load them all at once and create an `FitImaging` object via the `_fit_imaging_from` method.
@@ -123,19 +123,19 @@ def __init__(
             ----------
             aggregator
                 A `PyAutoFit` aggregator object which can load the results of model-fits.
-            settings_inversion
-                Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+            settings
+                Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
 
         Parameters
         ----------
         aggregator
             A `PyAutoFit` aggregator object which can load the results of model-fits.
-        settings_inversion
-            Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+        settings
+            Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
         """
         super().__init__(aggregator=aggregator)
 
-        self.settings_inversion = settings_inversion
+        self.settings = settings
 
     def object_via_gen_from(
         self, fit, instance: Optional[af.ModelInstance] = None
@@ -157,5 +157,5 @@ def object_via_gen_from(
         return _fit_imaging_from(
             fit=fit,
             instance=instance,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
         )

autogalaxy/aggregator/interferometer/fit_interferometer.py

@@ -16,7 +16,7 @@
 def _fit_interferometer_from(
     fit: af.Fit,
     instance: Optional[af.ModelInstance] = None,
-    settings_inversion: aa.SettingsInversion = None,
+    settings: aa.Settings = None,
 ) -> List[FitInterferometer]:
     """
     Returns a list of `FitInterferometer` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
@@ -26,7 +26,7 @@ def _fit_interferometer_from(
 
     - The interferometer data, noise-map, uv-wavelengths and settings as .fits files (e.g. `dataset/data.fits`).
     - The real space mask defining the grid of the interferometer for the FFT (`dataset/real_space_mask.fits`).
-    - The settings of inversions used by the fit (`dataset/settings_inversion.json`).
+    - The settings of inversions used by the fit (`dataset/settings.json`).
 
     Each individual attribute can be loaded from the database via the `fit.value()` method.
 
@@ -38,7 +38,7 @@ def _fit_interferometer_from(
     method is instead used to load lists of the data, noise-map, PSF and mask and combine them into a list of
     `FitInterferometer` objects.
 
-    The settings of an inversion can be overwritten by inputting a `settings_inversion` object, for
+    The settings of an inversion can be overwritten by inputting a `settings` object, for
     example if you want to use a grid with a different inversion solver.
 
     Parameters
@@ -49,8 +49,8 @@ def _fit_interferometer_from(
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
-    settings_inversion
-        Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+    settings
+        Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
     """
     from autogalaxy.interferometer.fit_interferometer import FitInterferometer
 
@@ -64,7 +64,7 @@ def _fit_interferometer_from(
 
     adapt_images_list = agg_util.adapt_images_from(fit=fit)
 
-    settings_inversion = settings_inversion or fit.value(name="settings_inversion")
+    settings = settings or fit.value(name="settings")
 
     fit_dataset_list = []
 
@@ -81,7 +81,7 @@ def _fit_interferometer_from(
                 galaxies=galaxies,
                 dataset_model=dataset_model,
                 adapt_images=adapt_images,
-                settings_inversion=settings_inversion,
+                settings=settings,
             )
         )
 
@@ -92,7 +92,7 @@ class FitInterferometerAgg(af.AggBase):
     def __init__(
         self,
         aggregator: af.Aggregator,
-        settings_inversion: Optional[aa.SettingsInversion] = None,
+        settings: Optional[aa.Settings] = None,
     ):
         """
         Interfaces with an `PyAutoFit` aggregator object to create instances of `FitInterferometer` objects from the
@@ -103,7 +103,7 @@ def __init__(
 
         - The interferometer data, noise-map, uv-wavelengths and settings as .fits files (e.g. `dataset/data.fits`).
         - The real space mask defining the grid of the interferometer for the FFT (`dataset/real_space_mask.fits`).
-        - The settings of inversions used by the fit (`dataset/settings_inversion.json`).
+        - The settings of inversions used by the fit (`dataset/settings.json`).
 
         The `aggregator` contains the path to each of these files, and they can be loaded individually. This class
         can load them all at once and create an `FitInterferometer` object via the `_fit_interferometer_from` method.
@@ -125,19 +125,19 @@ def __init__(
         ----------
         aggregator
             A `PyAutoFit` aggregator object which can load the results of model-fits.
-        settings_inversion
-            Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+        settings
+            Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
 
         Parameters
         ----------
         aggregator
             A `PyAutoFit` aggregator object which can load the results of model-fits.
-        settings_inversion
-            Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
+        settings
+            Optionally overwrite the `Settings` of the `Inversion` object that is created from the fit.
         """
         super().__init__(aggregator=aggregator)
 
-        self.settings_inversion = settings_inversion
+        self.settings = settings
 
     def object_via_gen_from(
         self, fit, instance: Optional[af.ModelInstance] = None
@@ -159,5 +159,5 @@ def object_via_gen_from(
         return _fit_interferometer_from(
             fit=fit,
             instance=instance,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
         )

autogalaxy/analysis/analysis/dataset.py

@@ -23,7 +23,7 @@ def __init__(
         dataset: Union[aa.Imaging, aa.Interferometer],
         adapt_images: Optional[AdaptImages] = None,
         cosmology: LensingCosmology = None,
-        settings_inversion: aa.SettingsInversion = None,
+        settings: aa.Settings = None,
         preloads: aa.Preloads = None,
         title_prefix: str = None,
         use_jax: bool = True,
@@ -45,7 +45,7 @@ def __init__(
             used by certain classes for adapting the analysis to the properties of the dataset.
         cosmology
             The Cosmology assumed for this analysis.
-        settings_inversion
+        settings
             Settings controlling how an inversion is fitted during the model-fit, for example which linear algebra
             formalism is used.
         title_prefix
@@ -62,7 +62,7 @@ def __init__(
         self.dataset = dataset
         self.adapt_images = adapt_images
 
-        self.settings_inversion = settings_inversion or aa.SettingsInversion()
+        self.settings = settings or aa.Settings()
 
         self.title_prefix = title_prefix
 
@@ -138,8 +138,8 @@ def save_attributes(self, paths: af.DirectoryPaths):
             visualization, and the pickled objects used by the aggregator output by this function.
         """
         paths.save_json(
-            name="settings_inversion",
-            object_dict=to_dict(self.settings_inversion),
+            name="settings",
+            object_dict=to_dict(self.settings),
         )
         paths.save_json(
             name="cosmology",

autogalaxy/analysis/plotter_interface.py

@@ -227,8 +227,8 @@ def should_plot(name):
             mapper_list = inversion.cls_list_from(cls=aa.AbstractMapper)
 
             for i, mapper in enumerate(mapper_list):
-                y = mapper.mapper_grids.source_plane_mesh_grid[:, 0]
-                x = mapper.mapper_grids.source_plane_mesh_grid[:, 1]
+                y = mapper.source_plane_mesh_grid[:, 0]
+                x = mapper.source_plane_mesh_grid[:, 1]
                 reconstruction = inversion.reconstruction_dict[mapper]
                 noise_map = inversion.reconstruction_noise_map_dict[mapper]