Feature/iterate refactor

autolens/__init__.py

@@ -1,10 +1,9 @@
 from autoconf.dictable import from_dict, from_json, output_to_json, to_dict
 from autoarray import preprocess
 from autoarray.dataset.imaging.w_tilde import WTildeImaging
-from autoarray.dataset.imaging.dataset import Imaging, SettingsImaging
+from autoarray.dataset.imaging.dataset import Imaging
 from autoarray.dataset.interferometer.dataset import (
     Interferometer,
-    SettingsInterferometer,
 )
 from autoarray.mask.mask_1d import Mask1D
 from autoarray.mask.mask_2d import Mask2D
@@ -34,9 +33,9 @@
 from autoarray.structures.arrays.irregular import ArrayIrregular
 from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.uniform_2d import Grid2D
-from autoarray.structures.grids.iterate_2d import Grid2DIterate
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.irregular_2d import Grid2DIrregularUniform
+from autoarray.structures.grids.over_sample.iterate import OverSampleIterate
 from autoarray.structures.mesh.rectangular_2d import Mesh2DRectangular
 from autoarray.structures.mesh.voronoi_2d import Mesh2DVoronoi
 from autoarray.structures.mesh.delaunay_2d import Mesh2DDelaunay
@@ -47,7 +46,8 @@
 from autoarray.structures.visibilities import VisibilitiesNoiseMap
 
 from autogalaxy import cosmology as cosmo
-from autogalaxy.analysis.adapt_images import AdaptImages
+from autogalaxy.analysis.adapt_images.adapt_images import AdaptImages
+from autogalaxy.analysis.adapt_images.adapt_image_maker import AdaptImageMaker
 from autogalaxy.gui.clicker import Clicker
 from autogalaxy.gui.scribbler import Scribbler
 from autogalaxy.galaxy.galaxy import Galaxy
@@ -57,7 +57,6 @@
 from autogalaxy.analysis.clump_model import ClumpModelDisabled
 
 from autogalaxy.quantity.dataset_quantity import DatasetQuantity
-from autogalaxy.quantity.dataset_quantity import SettingsQuantity
 from autogalaxy.profiles.geometry_profiles import EllProfile
 from autogalaxy.profiles import (
     point_sources as ps,

autolens/aggregator/fit_imaging.py

@@ -15,7 +15,6 @@
 def _fit_imaging_from(
     fit: af.Fit,
     instance: Optional[af.ModelInstance] = None,
-    settings_dataset: aa.SettingsImaging = None,
     settings_inversion: aa.SettingsInversion = None,
     use_preloaded_grid: bool = True,
 ) -> List[FitImaging]:
@@ -37,7 +36,7 @@ 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 a pixelization of inversion can be overwritten by inputting a `settings_dataset` object, for example
+    The settings of an inversion can be overwritten by inputting a `settings_inversion` object, for example
     if you want to use a grid with a different inversion solver.
 
     Parameters
@@ -47,8 +46,6 @@ 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_dataset
-        Optionally overwrite the `SettingsImaging` of the `Imaging` object that is created from the fit.
     settings_inversion
         Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
     use_preloaded_grid
@@ -57,7 +54,7 @@ def _fit_imaging_from(
         as the fit.
     """
 
-    dataset_list = _imaging_from(fit=fit, settings_dataset=settings_dataset)
+    dataset_list = _imaging_from(fit=fit)
 
     tracer_list = _tracer_from(fit=fit, instance=instance)
 
@@ -98,7 +95,6 @@ class FitImagingAgg(af.AggBase):
     def __init__(
         self,
         aggregator: af.Aggregator,
-        settings_dataset: Optional[aa.SettingsImaging] = None,
         settings_inversion: Optional[aa.SettingsInversion] = None,
         use_preloaded_grid: bool = True,
     ):
@@ -132,8 +128,6 @@ def __init__(
         ----------
         aggregator
             A `PyAutoFit` aggregator object which can load the results of model-fits.
-        settings_dataset
-            Optionally overwrite the `SettingsImaging` of the `Imaging` object that is created from the fit.
         settings_inversion
             Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
         use_preloaded_grid
@@ -143,7 +137,6 @@ def __init__(
         """
         super().__init__(aggregator=aggregator)
 
-        self.settings_dataset = settings_dataset
         self.settings_inversion = settings_inversion
         self.use_preloaded_grid = use_preloaded_grid
 
@@ -166,7 +159,6 @@ def object_via_gen_from(
         return _fit_imaging_from(
             fit=fit,
             instance=instance,
-            settings_dataset=self.settings_dataset,
             settings_inversion=self.settings_inversion,
             use_preloaded_grid=self.use_preloaded_grid,
         )

autolens/aggregator/fit_interferometer.py

@@ -16,7 +16,6 @@ def _fit_interferometer_from(
     fit: af.Fit,
     instance: Optional[af.ModelInstance] = None,
     real_space_mask: Optional[aa.Mask2D] = None,
-    settings_dataset: aa.SettingsInterferometer = None,
     settings_inversion: aa.SettingsInversion = None,
     use_preloaded_grid: bool = True,
 ) -> List[FitInterferometer]:
@@ -39,7 +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 a pixelization of inversion can be overwritten by inputting a `settings_dataset` object, for
+    The settings of an inversion can be overwritten by inputting a `settings_inversion` object, for
     example if you want to use a grid with a different inversion solver.
 
     Parameters
@@ -49,8 +48,6 @@ 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_dataset
-        Optionally overwrite the `SettingsInterferometer` of the `Interferometer` object that is created from the fit.
     settings_inversion
         Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
     use_preloaded_grid
@@ -61,7 +58,6 @@ def _fit_interferometer_from(
     dataset_list = _interferometer_from(
         fit=fit,
         real_space_mask=real_space_mask,
-        settings_dataset=settings_dataset,
     )
     tracer_list = _tracer_from(fit=fit, instance=instance)
 
@@ -102,7 +98,6 @@ class FitInterferometerAgg(af.AggBase):
     def __init__(
         self,
         aggregator: af.Aggregator,
-        settings_dataset: Optional[aa.SettingsInterferometer] = None,
         settings_inversion: Optional[aa.SettingsInversion] = None,
         use_preloaded_grid: bool = True,
         real_space_mask: Optional[aa.Mask2D] = None,
@@ -133,8 +128,6 @@ def __init__(
         ----------
         aggregator
             A `PyAutoFit` aggregator object which can load the results of model-fits.
-        settings_dataset
-            Optionally overwrite the `SettingsInterferometer` of the `Interferometer` object that is created from the fit.
         settings_inversion
             Optionally overwrite the `SettingsInversion` of the `Inversion` object that is created from the fit.
         use_preloaded_grid
@@ -144,7 +137,6 @@ def __init__(
         """
         super().__init__(aggregator=aggregator)
 
-        self.settings_dataset = settings_dataset
         self.settings_inversion = settings_inversion
         self.use_preloaded_grid = use_preloaded_grid
         self.real_space_mask = real_space_mask
@@ -168,7 +160,6 @@ def object_via_gen_from(
         return _fit_interferometer_from(
             fit=fit,
             instance=instance,
-            settings_dataset=self.settings_dataset,
             settings_inversion=self.settings_inversion,
             use_preloaded_grid=self.use_preloaded_grid,
         )

autolens/aggregator/subhalo.py

@@ -10,7 +10,6 @@ class SubhaloAgg:
     def __init__(
         self,
         aggregator_grid_search: af.GridSearchAggregator,
-        settings_dataset: Optional[aa.SettingsImaging] = None,
         settings_inversion: Optional[aa.SettingsInversion] = None,
         use_preloaded_grid: bool = True,
     ):
@@ -20,7 +19,6 @@ def __init__(
         """
 
         self.aggregator_grid_search = aggregator_grid_search
-        self.settings_dataset = settings_dataset
         self.settings_inversion = settings_inversion
         self.use_preloaded_grid = use_preloaded_grid
 

autolens/analysis/analysis.py

@@ -1,11 +1,7 @@
-import dill
 import os
-import json
 import logging
 import numpy as np
-from os import path
-from scipy.stats import norm
-from typing import Dict, Optional, List, Union
+from typing import Dict, Optional, Union
 
 from autoconf import conf
 from autoconf.dictable import to_dict, output_to_json
@@ -14,14 +10,13 @@
 import autoarray as aa
 import autogalaxy as ag
 
-from autogalaxy.analysis.analysis import AnalysisDataset as AgAnalysisDataset
+from autogalaxy.analysis.analysis.dataset import AnalysisDataset as AgAnalysisDataset
 
 from autolens.analysis.result import ResultDataset
 from autolens.analysis.maker import FitMaker
 from autolens.analysis.preloads import Preloads
 from autolens.analysis.positions import PositionsLHResample
 from autolens.analysis.positions import PositionsLHPenalty
-from autolens.analysis.visualizer import Visualizer
 from autolens.lens.tracer import Tracer
 
 from autolens.lens import tracer_util
@@ -33,7 +28,7 @@
 logger.setLevel(level="INFO")
 
 
-class AnalysisLensing:
+class AnalysisLens:
     def __init__(
         self,
         positions_likelihood: Optional[
@@ -139,14 +134,14 @@ def log_likelihood_positions_overwrite_from(
                 raise exc.FitException from e
 
 
-class AnalysisDataset(AgAnalysisDataset, AnalysisLensing):
+class AnalysisDataset(AgAnalysisDataset, AnalysisLens):
     def __init__(
         self,
         dataset,
         positions_likelihood: Optional[
             Union[PositionsLHResample, PositionsLHPenalty]
         ] = None,
-        adapt_images: Optional[ag.AdaptImages] = None,
+        adapt_image_maker: Optional[ag.AdaptImageMaker] = None,
         cosmology: ag.cosmo.LensingCosmology = ag.cosmo.Planck15(),
         settings_inversion: aa.SettingsInversion = None,
         raise_inversion_positions_likelihood_exception: bool = True,
@@ -185,12 +180,12 @@ def __init__(
 
         super().__init__(
             dataset=dataset,
-            adapt_images=adapt_images,
+            adapt_image_maker=adapt_image_maker,
             cosmology=cosmology,
             settings_inversion=settings_inversion,
         )
 
-        AnalysisLensing.__init__(
+        AnalysisLens.__init__(
             self=self,
             positions_likelihood=positions_likelihood,
             cosmology=cosmology,