Revert "Main to JAX"

autogalaxy/__init__.py

@@ -4,7 +4,6 @@
 from autoarray.dataset.interferometer.dataset import Interferometer  # noqa
 from autoarray.dataset.dataset_model import DatasetModel
 from autoarray.dataset.over_sampling import OverSamplingDataset
-from autoarray.inversion.inversion.mapper_valued import MapperValued
 from autoarray.inversion.pixelization import mesh  # noqa
 from autoarray.inversion import regularization as reg  # noqa
 from autoarray.inversion.pixelization import image_mesh
@@ -109,6 +108,8 @@
 from .gui.clicker import Clicker
 from .gui.scribbler import Scribbler
 
+from .analysis.clump_model import ClumpModel
+
 from autoconf import conf
 
 conf.instance.register(__file__)

autogalaxy/aggregator/ellipse/fit_ellipse.py

@@ -60,6 +60,7 @@ def _fit_ellipse_from(
     for dataset, ellipse_list, multipole_lists in zip(
         dataset_list, ellipse_list_list, multipole_list_list
     ):
+
         for ellipse, multipole_list in zip(ellipse_list, multipole_lists):
             fit_dataset_list.append(
                 FitEllipse(

autogalaxy/aggregator/galaxies.py

@@ -41,14 +41,14 @@ def _galaxies_from(fit: af.Fit, instance: af.ModelInstance) -> List[Galaxy]:
     if instance is not None:
         galaxies = instance.galaxies
 
-        if hasattr(instance, "extra_galaxies"):
-            galaxies = galaxies + fit.instance.extra_galaxies
+        if hasattr(instance, "clumps"):
+            galaxies = galaxies + fit.instance.clumps
 
     else:
         galaxies = fit.instance.galaxies
 
-        if hasattr(fit.instance, "extra_galaxies"):
-            galaxies = galaxies + fit.instance.extra_galaxies
+        if hasattr(fit.instance, "clumps"):
+            galaxies = galaxies + fit.instance.clumps
 
     if fit.children is not None:
         if len(fit.children) > 0:

autogalaxy/analysis/analysis/analysis.py

@@ -42,8 +42,8 @@ def galaxies_via_instance_from(
         """
         Create a list of galaxies from a model instance, which is used to fit the dataset.
 
-        The instance may only contain galaxies, in which case this function is redundant. However, if extra galaxies
-        are included, the instance will contain both galaxies and extra galaxies, and they should be added to create
+        The instance may only contain galaxies, in which case this function is redundant. However, if the clumns
+        API is being used, the instance will contain both galaxies and clumps, and they should be added to create
         the single list of galaxies used to fit the dataset.
 
         Parameters
@@ -56,12 +56,11 @@ def galaxies_via_instance_from(
         -------
         A list of galaxies that is used to then fit the dataset.
         """
-        if hasattr(instance, "extra_galaxies"):
-            if getattr(instance, "extra_galaxies", None) is not None:
-                return Galaxies(
-                    galaxies=instance.galaxies + instance.extra_galaxies,
-                    run_time_dict=run_time_dict
-                )
+        if hasattr(instance, "clumps"):
+            return Galaxies(
+                galaxies=instance.galaxies + instance.clumps,
+                run_time_dict=run_time_dict,
+            )
 
         return Galaxies(galaxies=instance.galaxies, run_time_dict=run_time_dict)
 
@@ -148,7 +147,7 @@ def profile_log_likelihood_function(
             An instance of the model that is being fitted to the data by this analysis (whose parameters have been set
             via a non-linear search).
         paths
-            The paths object which manages all paths, e.g. where the non-linear search outputs are stored,
+            The PyAutoFit paths object which manages all paths, e.g. where the non-linear search outputs are stored,
             visualization and the pickled objects used by the aggregator output by this function.
 
         Returns
@@ -239,7 +238,7 @@ def output_profiling_info(
         Parameters
         ----------
         paths
-            The paths object which manages all paths, e.g. where the non-linear search outputs are stored,
+            The PyAutoFit paths object which manages all paths, e.g. where the non-linear search outputs are stored,
             visualization and the pickled objects used by the aggregator output by this function.
         run_time_dict
             A dictionary containing the profiling times of the functions called by the `log_likelihood_function`.

autogalaxy/analysis/analysis/dataset.py

@@ -90,7 +90,7 @@ def save_attributes(self, paths: af.DirectoryPaths):
         Parameters
         ----------
         paths
-            The paths object which manages all paths, e.g. where the non-linear search outputs are stored,
+            The PyAutoFit paths object which manages all paths, e.g. where the non-linear search outputs are stored,
             visualization, and the pickled objects used by the aggregator output by this function.
         """
         paths.save_fits(
@@ -145,7 +145,7 @@ def save_results(self, paths: af.DirectoryPaths, result: ResultDataset):
         Parameters
         ----------
         paths
-            The paths object which manages all paths, e.g. where the non-linear search outputs are stored,
+            The PyAutoFit paths object which manages all paths, e.g. where the non-linear search outputs are stored,
             visualization and the pickled objects used by the aggregator output by this function.
         result
             The result of a model fit, including the non-linear search, samples and maximum likelihood tracer.

autogalaxy/analysis/chaining_util.py

@@ -166,90 +166,77 @@ def source_from(
     return source_custom_model_from(result=result, source_is_model=True)
 
 
-def extra_galaxies_from(
+def clumps_from(
     result: Result,
     light_as_model: bool = False,
     mass_as_model: bool = False,
     free_centre: bool = False,
 ) -> af.Collection:
     """
-    The extra galaxies API models the light and / or mass of additional galaxies surrouding the main galaxy or
-    strong lens system.
+    The clump API models the light and / or mass of additional galaxies surrouding the main galaxy or strong lens
+    system.
 
-    This function performs model composition of extra galaxies for fits using the search chaining API. It makes it
-    possible to pass the extra galaxy parameters from a previous search to a new search, such that the new extra
-    galaxies are either treated as an instance or model component.
+    This function performs model composition of clumps for fits using the search chaining API. It makes it possible to
+    pass the clump parameters from a previous search to a new search, such that the new clumps are either treated
+    as an instance or model component.
 
     This function currently requires that mass profiles are `IsothermalSph` objects and that light profiles are
     `Sersic` objects. This will be generalised in the future.
 
     Parameters
     ----------
     result
-        The result, which includes extra galaxies, of the previous search, which via prior passing are used to create
-        the new extra galaxy model.
+        The result, which includes clumps, of the previous search, which via prior passing are used to create the new
+        clump model.
     light_as_model
-        If `True`, the extra_galaxy light is passed as a model component, else it is a fixed instance.
+        If `True`, the clump light is passed as a model component, else it is a fixed instance.
     mass_as_model
-        If `True`, the extra_galaxy mass is passed as a model component, else it is a fixed instance.
+        If `True`, the clump mass is passed as a model component, else it is a fixed instance.
     free_centre
         If `True`, the requested mass and/or light model centres are passed as a model, else they are fixed.
 
     Returns
     -------
     af.Collection
-        A collection of extra galaxy `Galaxy` objects, where each is either an instance or model component.
+        A collection of clump `Galaxy` objects, where each clump is either an instance or model component.
     """
     # ideal API:
 
-    # extra_galaxies = result.instance.extra_galaxies.as_model((LightProfile, mp.MassProfile,), fixed="centre", prior_pass=True)
-
-    if result.instance.extra_galaxies is None:
-        return None
+    # clumps = result.instance.clumps.as_model((LightProfile, mp.MassProfile,), fixed="centre", prior_pass=True)
 
     if mass_as_model:
-        extra_galaxies = result.instance.extra_galaxies.as_model((MassProfile,))
-
-        for extra_galaxy_index in range(len(result.instance.extra_galaxies)):
-            if hasattr(result.instance.extra_galaxies[extra_galaxy_index], "mass"):
-                extra_galaxies[
-                    extra_galaxy_index
-                ].mass.centre = result.instance.extra_galaxies[
-                    extra_galaxy_index
+        clumps = result.instance.clumps.as_model((MassProfile,))
+
+        for clump_index in range(len(result.instance.clumps)):
+            if hasattr(result.instance.clumps[clump_index], "mass"):
+                clumps[clump_index].mass.centre = result.instance.clumps[
+                    clump_index
                 ].mass.centre
-                extra_galaxies[
-                    extra_galaxy_index
-                ].mass.einstein_radius = result.model.extra_galaxies[
-                    extra_galaxy_index
+                clumps[clump_index].mass.einstein_radius = result.model.clumps[
+                    clump_index
                 ].mass.einstein_radius
                 if free_centre:
-                    extra_galaxies[
-                        extra_galaxy_index
-                    ].mass.centre = result.model.extra_galaxies[
-                        extra_galaxy_index
+                    clumps[clump_index].mass.centre = result.model.clumps[
+                        clump_index
                     ].mass.centre
 
     elif light_as_model:
-        extra_galaxies = result.instance.extra_galaxies.as_model((LightProfile,))
-
-        for extra_galaxy_index in range(len(result.instance.extra_galaxies)):
-            if extra_galaxies[extra_galaxy_index].bulge is not None:
-                extra_galaxies[
-                    extra_galaxy_index
-                ].bulge.centre = result.instance.extra_galaxies[
-                    extra_galaxy_index
-                ].bulge.centre
+        clumps = result.instance.clumps.as_model((LightProfile,))
+
+        for clump_index in range(len(result.instance.clumps)):
+            if clumps[clump_index].light is not None:
+                clumps[clump_index].light.centre = result.instance.clumps[
+                    clump_index
+                ].light.centre
                 if free_centre:
-                    extra_galaxies[
-                        extra_galaxy_index
-                    ].bulge.centre = result.model.extra_galaxies[
-                        extra_galaxy_index
-                    ].bulge.centre
+                    clumps[clump_index].light.centre = result.model.clumps[
+                        clump_index
+                    ].light.centre
 
     else:
-        extra_galaxies = result.instance.extra_galaxies.as_model(())
+        clumps = result.instance.clumps.as_model(())
 
-    return extra_galaxies
+    return clumps
 
 
 def lp_chain_tracer_from(light_result, settings_search):