diff --git a/autogalaxy/__init__.py b/autogalaxy/__init__.py
index 65a00fab6..6f677c9a7 100644
--- a/autogalaxy/__init__.py
+++ b/autogalaxy/__init__.py
@@ -10,22 +10,17 @@
 from autoarray.dataset.imaging.dataset import Imaging  # noqa
 from autoarray.dataset.interferometer.dataset import Interferometer  # noqa
 from autoarray.dataset.dataset_model import DatasetModel
-from autoarray.inversion.pixelization import mesh  # noqa
+from autoarray.inversion.mesh import mesh  # noqa
 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.inversion.mesh import image_mesh
+from autoarray.inversion.mappers.abstract import Mapper  # 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.mesh.image_mesh.abstract import AbstractImageMesh
+from autoarray.inversion.mesh.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.inversion.pixelization import Pixelization  # noqa
+from autoarray.inversion.mesh.border_relocator import BorderRelocator
 from autoarray.preloads import Preloads
 from autoarray.preloads import mapper_indices_from
 from autoarray.mask.mask_1d import Mask1D  # noqa
@@ -43,11 +38,12 @@
 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.structures.mesh.rectangular_2d import Mesh2DRectangular  # noqa
-from autoarray.structures.mesh.rectangular_2d_uniform import (
-    Mesh2DRectangularUniform,
+from autoarray.inversion.mesh.interpolator.rectangular import (
+    InterpolatorRectangular,
+)  # noqa
+from autoarray.inversion.mesh.interpolator.delaunay import (
+    InterpolatorDelaunay,
 )  # noqa
-from autoarray.structures.mesh.delaunay_2d 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
@@ -55,6 +51,9 @@
 from autoarray.structures.arrays.kernel_2d import Kernel2D  # noqa
 from autoarray.structures.visibilities import Visibilities  # noqa
 from autoarray.structures.visibilities import VisibilitiesNoiseMap  # noqa
+from autoarray.inversion.mesh.mesh_geometry.rectangular import (
+    rectangular_edge_pixel_list_from,
+)
 
 from .analysis import model_util
 from .analysis.adapt_images.adapt_images import AdaptImages
diff --git a/autogalaxy/abstract_fit.py b/autogalaxy/abstract_fit.py
index 5f7223592..a478a8dc5 100644
--- a/autogalaxy/abstract_fit.py
+++ b/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
         -------
diff --git a/autogalaxy/aggregator/ellipse/fit_ellipse.py b/autogalaxy/aggregator/ellipse/fit_ellipse.py
index 3773bb914..7f1ca263c 100644
--- a/autogalaxy/aggregator/ellipse/fit_ellipse.py
+++ b/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
diff --git a/autogalaxy/aggregator/imaging/fit_imaging.py b/autogalaxy/aggregator/imaging/fit_imaging.py
index ef22525a3..aac0dc26b 100644
--- a/autogalaxy/aggregator/imaging/fit_imaging.py
+++ b/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,
         )
diff --git a/autogalaxy/aggregator/interferometer/fit_interferometer.py b/autogalaxy/aggregator/interferometer/fit_interferometer.py
index 4f4034c4b..69885be52 100644
--- a/autogalaxy/aggregator/interferometer/fit_interferometer.py
+++ b/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,
         )
diff --git a/autogalaxy/analysis/analysis/dataset.py b/autogalaxy/analysis/analysis/dataset.py
index f2ad68159..ee9843c2c 100644
--- a/autogalaxy/analysis/analysis/dataset.py
+++ b/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",
diff --git a/autogalaxy/analysis/plotter_interface.py b/autogalaxy/analysis/plotter_interface.py
index ff6fdbe4b..f825b2091 100644
--- a/autogalaxy/analysis/plotter_interface.py
+++ b/autogalaxy/analysis/plotter_interface.py
@@ -214,7 +214,7 @@ def should_plot(name):
         )
 
         if should_plot("subplot_inversion"):
-            mapper_list = inversion.cls_list_from(cls=aa.AbstractMapper)
+            mapper_list = inversion.cls_list_from(cls=aa.Mapper)
 
             for i in range(len(mapper_list)):
                 suffix = "" if len(mapper_list) == 1 else f"_{i}"
@@ -224,11 +224,11 @@ def should_plot(name):
                 )
 
         if should_plot("csv_reconstruction"):
-            mapper_list = inversion.cls_list_from(cls=aa.AbstractMapper)
+            mapper_list = inversion.cls_list_from(cls=aa.Mapper)
 
             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]
 
diff --git a/autogalaxy/config/priors/mass/dark/cnfw_mcr_scatter.yaml b/autogalaxy/config/priors/mass/dark/cnfw_mcr_scatter.yaml
index 907ca18aa..5cd63266a 100644
--- a/autogalaxy/config/priors/mass/dark/cnfw_mcr_scatter.yaml
+++ b/autogalaxy/config/priors/mass/dark/cnfw_mcr_scatter.yaml
@@ -59,7 +59,7 @@ cNFWMCRScatterLudlowSph:
     limits:
       lower: 0.0
       upper: inf
-  scatter:
+  scatter_sigma:
     type: Gaussian
     mean: 0.0
     sigma: 3.0
diff --git a/autogalaxy/config/priors/mass/dark/nfw_mcr_scatter.yaml b/autogalaxy/config/priors/mass/dark/nfw_mcr_scatter.yaml
index d01feb8ff..01cd31a1e 100644
--- a/autogalaxy/config/priors/mass/dark/nfw_mcr_scatter.yaml
+++ b/autogalaxy/config/priors/mass/dark/nfw_mcr_scatter.yaml
@@ -49,7 +49,7 @@ NFWMCRScatterLudlowSph:
     limits:
       lower: 0.0
       upper: inf
-  scatter:
+  scatter_sigma:
     type: Gaussian
     mean: 0.0
     sigma: 3.0
diff --git a/autogalaxy/config/priors/mass/dark/nfw_truncated_mcr.yaml b/autogalaxy/config/priors/mass/dark/nfw_truncated_mcr.yaml
index 13c1a813f..2eb3bb70d 100644
--- a/autogalaxy/config/priors/mass/dark/nfw_truncated_mcr.yaml
+++ b/autogalaxy/config/priors/mass/dark/nfw_truncated_mcr.yaml
@@ -151,7 +151,7 @@ NFWTruncatedMCRScatterLudlowSph:
     limits:
       lower: 0.0
       upper: inf
-  scatter:
+  scatter_sigma:
     type: Gaussian
     mean: 0.0
     sigma: 3.0
diff --git a/autogalaxy/config/priors/regularization/matern_adapt_kernel_rho.yaml b/autogalaxy/config/priors/regularization/matern_adapt_kernel_rho.yaml
deleted file mode 100644
index 105ec87a1..000000000
--- a/autogalaxy/config/priors/regularization/matern_adapt_kernel_rho.yaml
+++ /dev/null
@@ -1,41 +0,0 @@
-MaternAdaptKernelRho:
-  coefficient:
-    type: LogUniform
-    lower_limit: 1.0e-06
-    upper_limit: 1000000.0
-    width_modifier:
-      type: Relative
-      value: 0.5
-    limits:
-      lower: 0.0
-      upper: inf
-  scale:
-    type: LogUniform
-    lower_limit: 1.0e-06
-    upper_limit: 1000000.0
-    width_modifier:
-      type: Relative
-      value: 0.2
-    limits:
-      lower: 0.0
-      upper: inf
-  nu:
-    type: Uniform
-    lower_limit: 0.5
-    upper_limit: 5.5
-    width_modifier:
-      type: Relative
-      value: 0.2
-    limits:
-      lower: 0.0
-      upper: inf
-  rho:
-    type: Uniform
-    lower_limit: 1.0e-06
-    upper_limit: 1000000.0
-    width_modifier:
-      type: Relative
-      value: 0.2
-    limits:
-      lower: 0.0
-      upper: inf
\ No newline at end of file
diff --git a/autogalaxy/convert.py b/autogalaxy/convert.py
index fa0b12b91..641b12623 100644
--- a/autogalaxy/convert.py
+++ b/autogalaxy/convert.py
@@ -28,7 +28,6 @@ def ell_comps_from(axis_ratio: float, angle: float, xp=np) -> Tuple[float, float
     return (ellip_y, ellip_x)
 
 
-
 def axis_ratio_and_angle_from(
     ell_comps: Tuple[float, float], xp=np
 ) -> Tuple[float, float]:
@@ -61,7 +60,10 @@ def axis_ratio_and_angle_from(
     ell_comps
         The elliptical components of the light or mass profile which are converted to an angle.
     """
-    angle = 0.5 * xp.arctan2(ell_comps[0], xp.where((ell_comps[0] == 0) & (ell_comps[1] == 0), 1.0, ell_comps[1]))
+    angle = 0.5 * xp.arctan2(
+        ell_comps[0],
+        xp.where((ell_comps[0] == 0) & (ell_comps[1] == 0), 1.0, ell_comps[1]),
+    )
     angle *= 180.0 / xp.pi
 
     angle = xp.where(angle < -45, angle + 180, angle)
@@ -198,7 +200,12 @@ def shear_magnitude_and_angle_from(
     gamma_2
         The gamma 2 component of the shear.
     """
-    angle = 0.5 * xp.arctan2(gamma_2, xp.where((gamma_1 == 0) & (gamma_2 == 0), 1.0, gamma_1)) * 180.0 / xp.pi
+    angle = (
+        0.5
+        * xp.arctan2(gamma_2, xp.where((gamma_1 == 0) & (gamma_2 == 0), 1.0, gamma_1))
+        * 180.0
+        / xp.pi
+    )
     magnitude = xp.sqrt(gamma_1**2 + gamma_2**2)
 
     angle = xp.where(angle < 0, angle + 180.0, angle)
@@ -298,14 +305,19 @@ def multipole_k_m_and_phi_m_from(
     -------
     The normalization and angle parameters of the multipole.
     """
-    phi_m = xp.arctan2(
-        multipole_comps[0],
-        xp.where(
-            (multipole_comps[0] == 0) & (multipole_comps[1] == 0),
-            1.0,
-            multipole_comps[1],
-        ),
-    ) * 180.0 / xp.pi / float(m)
+    phi_m = (
+        xp.arctan2(
+            multipole_comps[0],
+            xp.where(
+                (multipole_comps[0] == 0) & (multipole_comps[1] == 0),
+                1.0,
+                multipole_comps[1],
+            ),
+        )
+        * 180.0
+        / xp.pi
+        / float(m)
+    )
 
     k_m = xp.sqrt(multipole_comps[1] ** 2 + multipole_comps[0] ** 2)
 
diff --git a/autogalaxy/galaxy/to_inversion.py b/autogalaxy/galaxy/to_inversion.py
index 82a0087c7..927ed4ef4 100644
--- a/autogalaxy/galaxy/to_inversion.py
+++ b/autogalaxy/galaxy/to_inversion.py
@@ -6,7 +6,6 @@
 
 import autoarray as aa
 
-from autoarray.inversion.pixelization.mappers.factory import mapper_from
 from autoarray.inversion.inversion.factory import inversion_from
 from autogalaxy.analysis.adapt_images.adapt_images import AdaptImages
 from autogalaxy.profiles.light.linear import (
@@ -23,7 +22,7 @@ def __init__(
         self,
         dataset: Optional[Union[aa.Imaging, aa.Interferometer, aa.DatasetInterface]],
         adapt_images: Optional[AdaptImages] = None,
-        settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
+        settings: aa.Settings = None,
         preloads: aa.Preloads = None,
         xp=np,
     ):
@@ -57,7 +56,7 @@ def __init__(
         adapt_images
             Images which certain pixelizations use to adapt their properties to the dataset, for example congregating
             the pixelization's pixels to the brightest regions of the image.
-        settings_inversion
+        settings
             The settings of the inversion, which controls how the linear algebra calculation is performed.
         """
         if dataset is not None:
@@ -76,7 +75,7 @@ def __init__(
 
         self.adapt_images = adapt_images
 
-        self.settings_inversion = settings_inversion
+        self.settings = settings or aa.Settings()
 
         self.preloads = preloads
 
@@ -135,9 +134,9 @@ def border_relocator(self) -> Optional[aa.BorderRelocator]:
 
         A full description of the border relocator is given in the `BorderRelocator` class in PyAutoArray.
 
-        Border relocation is only used if the `use_border_relocator` attribute is True in the `SettingsInversion` object.
+        Border relocation is only used if the `use_border_relocator` attribute is True in the `Settings` object.
         """
-        if self.settings_inversion.use_border_relocator:
+        if self.settings.use_border_relocator:
             return self.dataset.grids.border_relocator
 
     def cls_light_profile_func_list_galaxy_dict_from(
@@ -158,7 +157,7 @@ def mapper_galaxy_dict(self):
     @cached_property
     def linear_obj_galaxy_dict(
         self,
-    ) -> Dict[Union[LightProfileLinearObjFuncList, aa.AbstractMapper], Galaxy]:
+    ) -> Dict[Union[LightProfileLinearObjFuncList, aa.Mapper], Galaxy]:
         """
         Returns a dictionary associating every linear object (e.g. a linear light profile or mapper) with the galaxy
         it belongs to.
@@ -202,7 +201,7 @@ def __init__(
         dataset: Optional[Union[aa.Imaging, aa.Interferometer, aa.DatasetInterface]],
         galaxies: List[Galaxy],
         adapt_images: Optional[AdaptImages] = None,
-        settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
+        settings: aa.Settings = None,
         preloads: aa.Preloads = None,
         xp=np,
     ):
@@ -237,7 +236,7 @@ def __init__(
         adapt_images
             Images which certain pixelizations use to adapt their properties to the dataset, for example congregating
             the pixelization's pixels to the brightest regions of the image.
-        settings_inversion
+        settings
             The settings of the inversion, which controls how the linear algebra calculation is performed.
         """
         self.galaxies = Galaxies(galaxies)
@@ -245,7 +244,7 @@ def __init__(
         super().__init__(
             dataset=dataset,
             adapt_images=adapt_images,
-            settings_inversion=settings_inversion,
+            settings=settings,
             preloads=preloads,
             xp=xp,
         )
@@ -323,7 +322,7 @@ def cls_light_profile_func_list_galaxy_dict_from(
                             psf=self.dataset.psf,
                             light_profile_list=light_profile_list,
                             regularization=light_profile.regularization,
-                            settings=self.settings_inversion,
+                            settings=self.settings,
                             xp=self._xp,
                         )
 
@@ -430,7 +429,7 @@ def mapper_from(
         source_plane_data_grid: aa.Grid2D,
         adapt_galaxy_image: aa.Array2D,
         image_plane_mesh_grid: Optional[aa.Grid2DIrregular] = None,
-    ) -> aa.AbstractMapper:
+    ) -> aa.Mapper:
         """
         Returns a `Mapper` object from the attributes required to create one, which are extracted and computed
         from the dataset and galaxies.
@@ -473,27 +472,26 @@ def mapper_from(
         -------
         A `Mapper` object which maps the dataset's data to the pixelization's mesh.
         """
-        mapper_grids = mesh.mapper_grids_from(
-            mask=self.dataset.mask,
+        interpolator = mesh.interpolator_from(
             border_relocator=self.border_relocator,
             source_plane_data_grid=source_plane_data_grid,
             source_plane_mesh_grid=source_plane_mesh_grid,
-            image_plane_mesh_grid=image_plane_mesh_grid,
             adapt_data=adapt_galaxy_image,
             preloads=self.preloads,
             xp=self._xp,
         )
 
-        return mapper_from(
-            mapper_grids=mapper_grids,
+        return aa.Mapper(
+            interpolator=interpolator,
+            image_plane_mesh_grid=image_plane_mesh_grid,
             regularization=regularization,
-            settings=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
 
     @cached_property
-    def mapper_galaxy_dict(self) -> Dict[aa.AbstractMapper, Galaxy]:
+    def mapper_galaxy_dict(self) -> Dict[aa.Mapper, Galaxy]:
         """
         Returns a dictionary associating each `Mapper` object with the galaxy it belongs to.
 
@@ -570,7 +568,7 @@ def inversion(self) -> aa.AbstractInversion:
         inversion = inversion_from(
             dataset=self.dataset,
             linear_obj_list=self.linear_obj_list,
-            settings=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
diff --git a/autogalaxy/imaging/fit_imaging.py b/autogalaxy/imaging/fit_imaging.py
index e4ea1bce7..997c723fc 100644
--- a/autogalaxy/imaging/fit_imaging.py
+++ b/autogalaxy/imaging/fit_imaging.py
@@ -24,7 +24,7 @@ def __init__(
         galaxies: List[Galaxy],
         dataset_model: Optional[aa.DatasetModel] = None,
         adapt_images: Optional[AdaptImages] = None,
-        settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
+        settings: aa.Settings = None,
         preloads: aa.Preloads = None,
         xp=np,
     ):
@@ -63,7 +63,7 @@ def __init__(
         adapt_images
             Contains the adapt-images which are used to make a pixelization's mesh and regularization adapt to the
             reconstructed galaxy's morphology.
-        settings_inversion
+        settings
             Settings controlling how an inversion is fitted for example which linear algebra formalism is used.
         """
 
@@ -77,12 +77,12 @@ def __init__(
         AbstractFitInversion.__init__(
             self=self,
             model_obj=self.galaxies,
-            settings_inversion=settings_inversion,
+            settings=settings,
             xp=xp,
         )
 
         self.adapt_images = adapt_images
-        self.settings_inversion = settings_inversion
+        self.settings = settings or aa.Settings()
 
         self.preloads = preloads
 
@@ -131,7 +131,7 @@ def galaxies_to_inversion(self) -> GalaxiesToInversion:
             dataset=dataset,
             galaxies=self.galaxies,
             adapt_images=self.adapt_images,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
diff --git a/autogalaxy/imaging/model/analysis.py b/autogalaxy/imaging/model/analysis.py
index 2d1e6fabd..b95ef3f5b 100644
--- a/autogalaxy/imaging/model/analysis.py
+++ b/autogalaxy/imaging/model/analysis.py
@@ -21,7 +21,7 @@ def __init__(
         dataset: aa.Imaging,
         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,
@@ -50,7 +50,7 @@ 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 for example which linear algebra formalism is used.
         title_prefix
             A string that is added before the title of all figures output by visualization, for example to
@@ -60,7 +60,7 @@ def __init__(
             dataset=dataset,
             adapt_images=adapt_images,
             cosmology=cosmology,
-            settings_inversion=settings_inversion,
+            settings=settings,
             preloads=preloads,
             title_prefix=title_prefix,
             use_jax=use_jax,
@@ -143,7 +143,7 @@ def fit_from(self, instance: af.ModelInstance) -> FitImaging:
             galaxies=galaxies,
             dataset_model=dataset_model,
             adapt_images=adapt_images,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
diff --git a/autogalaxy/interferometer/fit_interferometer.py b/autogalaxy/interferometer/fit_interferometer.py
index 72b4e0f05..e64ef0a74 100644
--- a/autogalaxy/interferometer/fit_interferometer.py
+++ b/autogalaxy/interferometer/fit_interferometer.py
@@ -19,7 +19,7 @@ def __init__(
         galaxies: List[Galaxy],
         dataset_model: Optional[aa.DatasetModel] = None,
         adapt_images: Optional[AdaptImages] = None,
-        settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
+        settings: aa.Settings = None,
         preloads: aa.Preloads = None,
         xp=np,
     ):
@@ -59,7 +59,7 @@ def __init__(
         adapt_images
             Contains the adapt-images which are used to make a pixelization's mesh and regularization adapt to the
             reconstructed galaxy's morphology.
-        settings_inversion
+        settings
             Settings controlling how an inversion is fitted for example which linear algebra formalism is used.
         """
 
@@ -71,12 +71,12 @@ def __init__(
         AbstractFitInversion.__init__(
             self=self,
             model_obj=self.galaxies,
-            settings_inversion=settings_inversion,
+            settings=settings,
             xp=xp,
         )
 
         self.adapt_images = adapt_images
-        self.settings_inversion = settings_inversion
+        self.settings = settings or aa.Settings()
 
         self.preloads = preloads
 
@@ -111,7 +111,7 @@ def galaxies_to_inversion(self) -> GalaxiesToInversion:
             dataset=dataset,
             galaxies=self.galaxies,
             adapt_images=self.adapt_images,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
diff --git a/autogalaxy/interferometer/model/analysis.py b/autogalaxy/interferometer/model/analysis.py
index 010ffae83..61571ee33 100644
--- a/autogalaxy/interferometer/model/analysis.py
+++ b/autogalaxy/interferometer/model/analysis.py
@@ -28,7 +28,7 @@ def __init__(
         dataset: 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,
@@ -57,7 +57,7 @@ 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, for example which linear algebra formalism is used.
         title_prefix
             A string that is added before the title of all figures output by visualization, for example to
@@ -67,7 +67,7 @@ def __init__(
             dataset=dataset,
             adapt_images=adapt_images,
             cosmology=cosmology,
-            settings_inversion=settings_inversion,
+            settings=settings,
             preloads=preloads,
             title_prefix=title_prefix,
             use_jax=use_jax,
@@ -145,7 +145,7 @@ def fit_from(self, instance: af.ModelInstance) -> FitInterferometer:
             dataset=self.dataset,
             galaxies=galaxies,
             adapt_images=adapt_images,
-            settings_inversion=self.settings_inversion,
+            settings=self.settings,
             preloads=self.preloads,
             xp=self._xp,
         )
diff --git a/autogalaxy/profiles/geometry_profiles.py b/autogalaxy/profiles/geometry_profiles.py
index 920247bdf..963ed955d 100644
--- a/autogalaxy/profiles/geometry_profiles.py
+++ b/autogalaxy/profiles/geometry_profiles.py
@@ -106,7 +106,9 @@ def _cartesian_grid_via_radial_from(
         """
         grid_angles = xp.arctan2(grid.array[:, 0], grid.array[:, 1])
 
-        cos_theta, sin_theta = self.angle_to_profile_grid_from(grid_angles=grid_angles, xp=xp, **kwargs)
+        cos_theta, sin_theta = self.angle_to_profile_grid_from(
+            grid_angles=grid_angles, xp=xp, **kwargs
+        )
 
         return xp.multiply(radius[:, None], xp.vstack((sin_theta, cos_theta)).T)
 
diff --git a/autogalaxy/profiles/light/linear/abstract.py b/autogalaxy/profiles/light/linear/abstract.py
index 5bb3f4c01..26eccf333 100644
--- a/autogalaxy/profiles/light/linear/abstract.py
+++ b/autogalaxy/profiles/light/linear/abstract.py
@@ -145,7 +145,7 @@ def __init__(
         psf: Optional[aa.Kernel2D],
         light_profile_list: List[LightProfileLinear],
         regularization=Optional[aa.reg.Regularization],
-        settings=aa.SettingsInversion(),
+        settings=aa.Settings(),
         xp=np,
     ):
         """
diff --git a/autogalaxy/profiles/mass/dark/cnfw.py b/autogalaxy/profiles/mass/dark/cnfw.py
index 1dd868b22..5037038d7 100644
--- a/autogalaxy/profiles/mass/dark/cnfw.py
+++ b/autogalaxy/profiles/mass/dark/cnfw.py
@@ -164,4 +164,4 @@ def potential_2d_from(self, grid: aa.type.Grid2DLike, xp=np, **kwargs):
         Lensing potential for the cored NFW profile.
         This is not yet implemented for `cNFWSph`.
         """
-        return xp.zeros(shape=grid.shape[0])
\ No newline at end of file
+        return xp.zeros(shape=grid.shape[0])
diff --git a/autogalaxy/profiles/mass/dark/cnfw_mcr_scatter.py b/autogalaxy/profiles/mass/dark/cnfw_mcr_scatter.py
index 14b1a75f3..84122ebb7 100644
--- a/autogalaxy/profiles/mass/dark/cnfw_mcr_scatter.py
+++ b/autogalaxy/profiles/mass/dark/cnfw_mcr_scatter.py
@@ -39,4 +39,4 @@ def __init__(
             kappa_s=kappa_s,
             scale_radius=scale_radius,
             core_radius=core_radius,
-        )
\ No newline at end of file
+        )
diff --git a/autogalaxy/profiles/mass/dark/nfw.py b/autogalaxy/profiles/mass/dark/nfw.py
index 01e8c8c30..69c089a5d 100644
--- a/autogalaxy/profiles/mass/dark/nfw.py
+++ b/autogalaxy/profiles/mass/dark/nfw.py
@@ -48,7 +48,7 @@ def deflections_yx_2d_from(self, grid: aa.type.Grid2DLike, xp=np, **kwargs):
     @aa.grid_dec.to_vector_yx
     @aa.grid_dec.transform
     def deflections_2d_via_analytic_from(
-            self, grid: aa.type.Grid2DLike, xp=np, **kwargs
+        self, grid: aa.type.Grid2DLike, xp=np, **kwargs
     ):
         """
         Analytic calculation deflection angles from Heyrovský & Karamazov 2024 via Eq. 30 & 31
@@ -70,28 +70,37 @@ def deflections_2d_via_analytic_from(
         x1 = grid.array[:, 1] / self.scale_radius
         x2 = grid.array[:, 0] / self.scale_radius
 
-        r2 = x1 ** 2 + x2 ** 2
+        r2 = x1**2 + x2**2
 
         # Avoid nans
 
         mask = r2 > 1e-24
 
-        prefactor = xp.where(mask, 4 * self.kappa_s * xp.sqrt(1 - e_hk24 ** 2) / (
-                ((x1 - e_hk24) ** 2 + x2 ** 2) * ((x1 + e_hk24) ** 2 + x2 ** 2)
-        ), 0.0)
+        prefactor = xp.where(
+            mask,
+            4
+            * self.kappa_s
+            * xp.sqrt(1 - e_hk24**2)
+            / (((x1 - e_hk24) ** 2 + x2**2) * ((x1 + e_hk24) ** 2 + x2**2)),
+            0.0,
+        )
 
         f1 = xp.where(mask, nfw_hk24_util.small_f_1(x1, x2, e_hk24, xp=xp), 0.0)
         f2 = xp.where(mask, nfw_hk24_util.small_f_2(x1, x2, e_hk24, xp=xp), 0.0)
         f3 = xp.where(mask, nfw_hk24_util.small_f_3(x1, x2, e_hk24, xp=xp), 0.0)
 
-        deflection_x = (x1 * ((x1**2 - e_hk24**2) * (1 - e_hk24**2) + x2**2 * (1 + e_hk24**2)) * f1
-                        + x1 * (x1**2 + x2**2 - e_hk24**2) * f2
-                        - x2 * (x1**2 + x2**2 + e_hk24**2) * f3)
+        deflection_x = (
+            x1 * ((x1**2 - e_hk24**2) * (1 - e_hk24**2) + x2**2 * (1 + e_hk24**2)) * f1
+            + x1 * (x1**2 + x2**2 - e_hk24**2) * f2
+            - x2 * (x1**2 + x2**2 + e_hk24**2) * f3
+        )
         deflection_x *= prefactor
 
-        deflection_y = (x2 * (x1**2 * (1 - 2 * e_hk24**2) + x2**2 + e_hk24**2) * f1
-                        + x2 * (x1**2 + x2**2 + e_hk24**2) * f2
-                        + x1 * (x1**2 + x2**2 - e_hk24**2) * f3)
+        deflection_y = (
+            x2 * (x1**2 * (1 - 2 * e_hk24**2) + x2**2 + e_hk24**2) * f1
+            + x2 * (x1**2 + x2**2 + e_hk24**2) * f2
+            + x1 * (x1**2 + x2**2 - e_hk24**2) * f3
+        )
         deflection_y *= prefactor
 
         return self.rotated_grid_from_reference_frame_from(
@@ -199,9 +208,7 @@ def convergence_2d_via_cse_from(self, grid: aa.type.Grid2DLike, xp=np, **kwargs)
     def convergence_func(self, grid_radius: float) -> float:
         grid_radius = (1.0 / self.scale_radius) * grid_radius.array + 0j
         return np.real(
-            2.0
-            * self.kappa_s
-            * np.array(self.coord_func_g(grid_radius=grid_radius))
+            2.0 * self.kappa_s * np.array(self.coord_func_g(grid_radius=grid_radius))
         )
 
     @aa.over_sample
@@ -340,7 +347,9 @@ def shear_yx_2d_from(self, grid: aa.type.Grid2DLike, xp=np, **kwargs):
 
         # Calculate shear from nfw_HK24.py
 
-        g1, g2 = nfw_hk24_util.g1_g2_from(x1=x1, x2=x2, e=e_hk24, k_s=self.kappa_s, xp=xp)
+        g1, g2 = nfw_hk24_util.g1_g2_from(
+            x1=x1, x2=x2, e=e_hk24, k_s=self.kappa_s, xp=xp
+        )
 
         # Rotation for shear
 
diff --git a/autogalaxy/profiles/mass/dark/nfw_hk24_util.py b/autogalaxy/profiles/mass/dark/nfw_hk24_util.py
index 667240baa..b75921bd6 100644
--- a/autogalaxy/profiles/mass/dark/nfw_hk24_util.py
+++ b/autogalaxy/profiles/mass/dark/nfw_hk24_util.py
@@ -42,12 +42,12 @@ def capital_F_from(chi, xp=np):
     less = chi < 1 - eps
     greater = chi > 1 + eps
 
-    root_min_arg = xp.where(less, 1 - chi ** 2, 0.0)
+    root_min_arg = xp.where(less, 1 - chi**2, 0.0)
     root_min = xp.sqrt(root_min_arg)
     root_min_safe = xp.where(less, root_min, 1.0)
     F_less = xp.where(less, xp.arctanh(root_min) / root_min_safe, 0.0)
 
-    root_plus_arg = xp.where(greater, chi ** 2 - 1, 0.0)
+    root_plus_arg = xp.where(greater, chi**2 - 1, 0.0)
     root_plus = xp.sqrt(root_plus_arg)
     root_plus_safe = xp.where(greater, root_plus, 1.0)
     F_greater = xp.where(greater, xp.arctan(root_plus) / root_plus_safe, 0.0)
@@ -73,7 +73,7 @@ def kappa_from(k_s, a, xp=np):
     Convergence as a function of a
     """
     F = capital_F_from(a, xp=xp)
-    kappa = xp.where(xp.abs(a - 1) < 1e-12, 2/3 * k_s, 2 * k_s * (1 - F) / (a**2 - 1))
+    kappa = xp.where(xp.abs(a - 1) < 1e-12, 2 / 3 * k_s, 2 * k_s * (1 - F) / (a**2 - 1))
     return kappa
 
 
diff --git a/autogalaxy/util/__init__.py b/autogalaxy/util/__init__.py
index 07b85cd91..32b7b7fa1 100644
--- a/autogalaxy/util/__init__.py
+++ b/autogalaxy/util/__init__.py
@@ -8,8 +8,7 @@
 from autoarray.structures.grids import grid_2d_util as grid_2d
 from autoarray.structures.grids import sparse_2d_util as sparse
 from autoarray.fit import fit_util as fit
-from autoarray.inversion.pixelization.mesh import mesh_util as mesh
-from autoarray.inversion.pixelization.mappers import mapper_util as mapper
+from autoarray.inversion.mappers import mapper_util as mapper
 from autoarray.inversion.regularization import regularization_util as regularization
 from autoarray.inversion.inversion import inversion_util as inversion
 from autoarray.inversion.inversion.imaging import (
diff --git a/docs/api/pixelization.rst b/docs/api/pixelization.rst
index a34e73960..89be6265d 100644
--- a/docs/api/pixelization.rst
+++ b/docs/api/pixelization.rst
@@ -78,7 +78,7 @@ Settings
    :template: custom-class-template.rst
    :recursive:
 
-   SettingsInversion
+   Settings
 
 Mapper
 ------
diff --git a/test_autogalaxy/config/general.yaml b/test_autogalaxy/config/general.yaml
index c67a01ed9..4643a809f 100644
--- a/test_autogalaxy/config/general.yaml
+++ b/test_autogalaxy/config/general.yaml
@@ -8,7 +8,6 @@ inversion:
   check_reconstruction: false       # If True, the inversion's reconstruction is checked to ensure the solution of a meshs's mapper is not an invalid solution where the values are all the same.
   use_positive_only_solver: false    # If True, inversion's use a positive-only linear algebra solver by default, which is slower but prevents unphysical negative values in the reconstructed solutuion.
   no_regularization_add_to_curvature_diag_value: 1.0e-8 # The default value added to the curvature matrix's diagonal when regularization is not applied to a linear object, which prevents inversion's failing due to the matrix being singular.
-  positive_only_uses_p_initial: false  # If True, the positive-only solver of an inversion's uses an initial guess of the reconstructed data's values as which values should be positive, speeding up the solver.
   use_border_relocator: false          # If True, by default a pixelization's border is used to relocate all pixels outside its border to the border.
 updates:
   iterations_per_quick_update: 1e99 # Non-linear search iterations between every quick update, which just displays the maximum likelihood model fit.
diff --git a/test_autogalaxy/galaxy/test_galaxies.py b/test_autogalaxy/galaxy/test_galaxies.py
index ea16d74ab..119655458 100644
--- a/test_autogalaxy/galaxy/test_galaxies.py
+++ b/test_autogalaxy/galaxy/test_galaxies.py
@@ -4,7 +4,7 @@
 
 import autogalaxy as ag
 
-from autoarray.inversion.pixelization.mesh.abstract import AbstractMesh
+from autoarray.inversion.mesh.mesh.abstract import AbstractMesh
 from autoarray.inversion.regularization.abstract import AbstractRegularization
 
 from autogalaxy.galaxy.galaxies import plane_image_from
diff --git a/test_autogalaxy/interferometer/test_fit_interferometer.py b/test_autogalaxy/interferometer/test_fit_interferometer.py
index 4dcb55648..e10d07529 100644
--- a/test_autogalaxy/interferometer/test_fit_interferometer.py
+++ b/test_autogalaxy/interferometer/test_fit_interferometer.py
@@ -146,9 +146,10 @@ def test___galaxy_image_dict(interferometer_7):
     assert fit.galaxy_image_dict[g0_linear][4] == pytest.approx(0.9876689631, 1.0e-4)
 
     # Pixelization + Regularizaiton only
+    mesh = ag.mesh.RectangularUniform(shape=(3, 3))
 
     pixelization = ag.Pixelization(
-        mesh=ag.mesh.RectangularUniform(shape=(3, 3)),
+        mesh=mesh,
         regularization=ag.reg.Constant(coefficient=1.0),
     )
 
@@ -158,19 +159,17 @@ def test___galaxy_image_dict(interferometer_7):
     fit = ag.FitInterferometer(
         dataset=interferometer_7,
         galaxies=[g0, galaxy_pix_0],
-        settings_inversion=ag.SettingsInversion(use_border_relocator=True),
+        settings=ag.Settings(use_border_relocator=True),
     )
 
-    mapper_grids = pixelization.mesh.mapper_grids_from(
-        mask=interferometer_7.real_space_mask,
+    interpolator = mesh.interpolator_from(
         source_plane_data_grid=interferometer_7.grids.lp,
         border_relocator=interferometer_7.grids.border_relocator,
         source_plane_mesh_grid=None,
     )
 
     mapper = ag.Mapper(
-        mapper_grids=mapper_grids,
-        border_relocator=interferometer_7.grids.border_relocator,
+        interpolator=interpolator,
         regularization=pixelization.regularization,
     )
 
@@ -263,8 +262,10 @@ def test___galaxy_model_visibilities_dict(interferometer_7):
 
     # Pixelization + Regularizaiton only
 
+    mesh = ag.mesh.RectangularUniform(shape=(3, 3))
+
     pixelization = ag.Pixelization(
-        mesh=ag.mesh.RectangularUniform(shape=(3, 3)),
+        mesh=mesh,
         regularization=ag.reg.Constant(coefficient=1.0),
     )
 
@@ -274,19 +275,17 @@ def test___galaxy_model_visibilities_dict(interferometer_7):
     fit = ag.FitInterferometer(
         dataset=interferometer_7,
         galaxies=[g0, galaxy_pix_0],
-        settings_inversion=ag.SettingsInversion(use_border_relocator=True),
+        settings=ag.Settings(use_border_relocator=True),
     )
 
-    mapper_grids = pixelization.mesh.mapper_grids_from(
-        mask=interferometer_7.real_space_mask,
+    interpolator = mesh.interpolator_from(
         source_plane_data_grid=interferometer_7.grids.lp,
         border_relocator=interferometer_7.grids.border_relocator,
         source_plane_mesh_grid=None,
     )
 
     mapper = ag.Mapper(
-        mapper_grids=mapper_grids,
-        border_relocator=interferometer_7.grids.border_relocator,
+        interpolator=interpolator,
         regularization=pixelization.regularization,
     )
 
diff --git a/test_autogalaxy/interferometer/test_simulate_and_fit_interferometer.py b/test_autogalaxy/interferometer/test_simulate_and_fit_interferometer.py
index d4b178cc4..c8e1752b3 100644
--- a/test_autogalaxy/interferometer/test_simulate_and_fit_interferometer.py
+++ b/test_autogalaxy/interferometer/test_simulate_and_fit_interferometer.py
@@ -186,9 +186,7 @@ def test__linear_light_profiles_agree_with_standard_light_profiles():
     fit_linear = ag.FitInterferometer(
         dataset=dataset,
         galaxies=[galaxy_linear],
-        settings_inversion=ag.SettingsInversion(
-            no_regularization_add_to_curvature_diag_value=False
-        ),
+        settings=ag.Settings(no_regularization_add_to_curvature_diag_value=False),
     )
 
     assert fit_linear.inversion.reconstruction == pytest.approx(
diff --git a/test_autogalaxy/profiles/mass/dark/test_nfw.py b/test_autogalaxy/profiles/mass/dark/test_nfw.py
index 2fc4d4a06..fc1a16bb5 100644
--- a/test_autogalaxy/profiles/mass/dark/test_nfw.py
+++ b/test_autogalaxy/profiles/mass/dark/test_nfw.py
@@ -5,6 +5,7 @@
 
 grid = ag.Grid2DIrregular([[1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [2.0, 4.0]])
 
+
 def test__deflections_via_analytical_from():
 
     nfw = ag.mp.NFW(
diff --git a/test_autogalaxy/test_regression.py b/test_autogalaxy/test_regression.py
index 9017db4b0..d83e8a43d 100644
--- a/test_autogalaxy/test_regression.py
+++ b/test_autogalaxy/test_regression.py
@@ -8,10 +8,8 @@
 
 
 class FitInversion(AbstractFitInversion):
-    def __init__(
-        self, model_obj, settings_inversion: aa.SettingsInversion, light_profiles
-    ):
-        super().__init__(model_obj=model_obj, settings_inversion=settings_inversion)
+    def __init__(self, model_obj, settings: aa.Settings, light_profiles):
+        super().__init__(model_obj=model_obj, settings=settings)
         self.light_profiles = light_profiles
 
     @property
@@ -41,7 +39,7 @@ def test_no_modify_state(light_profile):
     fit_inversion = FitInversion(
         model_obj=model_obj,
         light_profiles=[light_profile],
-        settings_inversion=aa.SettingsInversion(),
+        settings=aa.Settings(),
     )
     result = fit_inversion.model_obj_linear_light_profiles_to_light_profiles