Merge branch 'feature/workflow_extend'

Author: Jammy2211

autolens/analysis/analysis/dataset.py

@@ -122,6 +122,8 @@ def modify_before_fit(self, paths: af.DirectoryPaths, model: af.Collection):
 
         self.raise_exceptions(model=model)
 
+        return self
+
     def raise_exceptions(self, model):
         has_pix = model.has_model(cls=(aa.Pixelization,)) or model.has_instance(
             cls=(aa.Pixelization,)

autolens/analysis/analysis/lens.py

@@ -120,8 +120,10 @@ def log_likelihood_penalty_from(
 
         if self.positions_likelihood_list is not None:
 
-            try:
-                for positions_likelihood in self.positions_likelihood_list:
+            for positions_likelihood in self.positions_likelihood_list:
+
+                if positions_likelihood is not None:
+
                     log_likelihood_penalty = (
                         positions_likelihood.log_likelihood_penalty_from(
                             instance=instance, analysis=self, xp=xp
@@ -130,8 +132,6 @@ def log_likelihood_penalty_from(
 
                     log_likelihood_penalty += log_likelihood_penalty
 
-                return log_likelihood_penalty
-            except (ValueError, np.linalg.LinAlgError) as e:
-                raise exc.FitException from e
+            return log_likelihood_penalty
 
         return log_likelihood_penalty

autolens/imaging/model/analysis.py

@@ -18,33 +18,6 @@ class AnalysisImaging(AnalysisDataset):
     Result = ResultImaging
     Visualizer = VisualizerImaging
 
-    def modify_before_fit(self, paths: af.DirectoryPaths, model: af.Collection):
-        """
-        This function is called immediately before the non-linear search begins and performs final tasks and checks 
-        before it begins.
-
-        This function:
-
-        - Checks that the adapt-dataset is consistent with previous adapt-datasets if the model-fit is being
-          resumed from a previous run.
-
-        - Checks the model and raises exceptions if certain critieria are not met.
-
-        Once inherited from it also visualizes objects which do not change throughout the model fit like the dataset.
-
-        Parameters
-        ----------
-        paths
-            The 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.
-        model
-            The model object, which includes model components representing the galaxies that are fitted to
-            the imaging data.
-        """
-        super().modify_before_fit(paths=paths, model=model)
-
-        return self
-
     def log_likelihood_function(self, instance: af.ModelInstance) -> float:
         """
         Given an instance of the model, where the model parameters are set via a non-linear search, fit the model

autolens/interferometer/model/analysis.py

@@ -90,28 +90,6 @@ def __init__(
     def interferometer(self):
         return self.dataset
 
-    def modify_before_fit(self, paths: af.DirectoryPaths, model: af.Collection):
-        """
-        This function is called immediately before the non-linear search begins and performs final tasks and checks
-        before it begins.
-
-        This function checks that the adapt-dataset is consistent with previous adapt-datasets if the model-fit is
-        being resumed from a previous run, and it visualizes objects which do not change throughout the model fit
-        like the dataset.
-
-        Parameters
-        ----------
-        paths
-            The 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.
-        model
-            The model object, which includes model components representing the galaxies that are fitted to
-            the imaging data.
-        """
-        super().modify_before_fit(paths=paths, model=model)
-
-        return self
-
     def log_likelihood_function(self, instance):
         """
         Given an instance of the model, where the model parameters are set via a non-linear search, fit the model

test_autolens/aggregator/conftest.py

@@ -46,6 +46,7 @@ def aggregator_from(database_file, analysis, model, samples):
     search.paths = af.DirectoryPaths(path_prefix=database_file)
     search.fit(model=model, analysis=analysis)
 
+    analysis.modify_before_fit(paths=search.paths, model=model)
     analysis.visualize_before_fit(paths=search.paths, model=model)
 
     database_file = path.join(conf.instance.output_path, f"{database_file}.sqlite")