black

Author: Jammy2211

autolens/analysis/analysis/dataset.py

@@ -26,9 +26,7 @@ class AnalysisDataset(AgAnalysisDataset, AnalysisLens):
     def __init__(
         self,
         dataset,
-        positions_likelihood_list: Optional[
-            List[PositionsLH]
-        ] = None,
+        positions_likelihood_list: Optional[List[PositionsLH]] = None,
         adapt_image_maker: Optional[ag.AdaptImageMaker] = None,
         cosmology: ag.cosmo.LensingCosmology = ag.cosmo.Planck15(),
         settings_inversion: aa.SettingsInversion = None,

autolens/analysis/analysis/lens.py

@@ -21,9 +21,7 @@
 class AnalysisLens:
     def __init__(
         self,
-        positions_likelihood_list: Optional[
-            List[PositionsLH]
-        ] = None,
+        positions_likelihood_list: Optional[List[PositionsLH]] = None,
         cosmology: ag.cosmo.LensingCosmology = ag.cosmo.Planck15(),
     ):
         """

autolens/analysis/positions.py

@@ -105,7 +105,10 @@ def output_positions_info(self, output_path: str, tracer: Tracer):
         with open_(path.join(output_path, "positions.info"), "a+") as f:
 
             positions_fit = SourceMaxSeparation(
-                data=self.positions, noise_map=None, tracer=tracer, plane_redshift=self.plane_redshift
+                data=self.positions,
+                noise_map=None,
+                tracer=tracer,
+                plane_redshift=self.plane_redshift,
             )
 
             distances = positions_fit.data.distances_to_coordinate_from(
@@ -209,8 +212,7 @@ def log_likelihood_penalty_from(self, tracer: Tracer) -> Optional[float]:
         if not positions_fit.max_separation_within_threshold(self.threshold):
 
             log_likelihood_penalty += self.log_likelihood_penalty_factor * (
-                positions_fit.max_separation_of_plane_positions
-                - self.threshold
+                positions_fit.max_separation_of_plane_positions - self.threshold
             )
 
         return log_likelihood_penalty

autolens/analysis/result.py

@@ -54,7 +54,9 @@ def source_plane_centre(self) -> aa.Grid2DIrregular:
         """
         return self.source_plane_light_profile_centre
 
-    def image_plane_multiple_image_positions(self, plane_redshift : Optional[float] = None) -> aa.Grid2DIrregular:
+    def image_plane_multiple_image_positions(
+        self, plane_redshift: Optional[float] = None
+    ) -> aa.Grid2DIrregular:
         """
         Backwards ray-trace the source-plane centres (see above) to the image-plane via the mass model, to determine
         the multiple image position of the source(s) in the image-plane.
@@ -89,7 +91,7 @@ def image_plane_multiple_image_positions(self, plane_redshift : Optional[float]
         return aa.Grid2DIrregular(values=multiple_images)
 
     def image_plane_multiple_image_positions_for_single_image_from(
-        self, plane_redshift : Optional[float] = None, increments: int = 20
+        self, plane_redshift: Optional[float] = None, increments: int = 20
     ) -> aa.Grid2DIrregular:
         """
         If the standard point solver only locates one multiple image, finds one or more additional images, which are
@@ -149,7 +151,7 @@ def image_plane_multiple_image_positions_for_single_image_from(
                 return aa.Grid2DIrregular(values=multiple_images)
 
         logger.info(
-        """
+            """
         Could not find multiple images for maximum likelihood lens model, even after incrementally moving the source
         centre inwards to the centre of the source-plane.
 
@@ -163,7 +165,7 @@ def positions_threshold_from(
         factor=1.0,
         minimum_threshold=None,
         positions: Optional[aa.Grid2DIrregular] = None,
-        plane_redshift : Optional[float] = None,
+        plane_redshift: Optional[float] = None,
     ) -> float:
         """
         Compute a new position threshold from these results corresponding to the image-plane multiple image positions
@@ -176,10 +178,10 @@ def positions_threshold_from(
 
         This is used for non-linear search chaining, specifically updating the position threshold of a new model-fit
         using the maximum likelihood model of a previous search.
-        
+
         The above behaviour assumes a single lens and single source plane, if there are multiple source planes (e.g.
         a double source plane lens) the input `plane_redshift_list` can be used to specify which source planea
-        the position threshold is computed for. 
+        the position threshold is computed for.
 
         Parameters
         ----------
@@ -216,9 +218,7 @@ def positions_threshold_from(
             data=positions, noise_map=None, tracer=tracer, plane_redshift=plane_redshift
         )
 
-        threshold = factor * np.max(
-            positions_fits.max_separation_of_plane_positions
-        )
+        threshold = factor * np.max(positions_fits.max_separation_of_plane_positions)
 
         if minimum_threshold is not None:
             if threshold < minimum_threshold:
@@ -294,10 +294,15 @@ def positions_likelihood_from(
             positions = positions[distances > mass_centre_radial_distance_min]
 
         threshold = self.positions_threshold_from(
-            factor=factor, minimum_threshold=minimum_threshold, positions=positions, plane_redshift=plane_redshift
+            factor=factor,
+            minimum_threshold=minimum_threshold,
+            positions=positions,
+            plane_redshift=plane_redshift,
+        )
+
+        return PositionsLH(
+            positions=positions, threshold=threshold, plane_redshift=plane_redshift
         )
-        
-        return PositionsLH(positions=positions, threshold=threshold, plane_redshift=plane_redshift)
 
 
 class ResultDataset(Result):

autolens/interferometer/model/analysis.py

@@ -28,9 +28,7 @@ class AnalysisInterferometer(AnalysisDataset):
     def __init__(
         self,
         dataset,
-        positions_likelihood_list: Optional[
-            PositionsLH
-        ] = None,
+        positions_likelihood_list: Optional[PositionsLH] = None,
         adapt_image_maker: Optional[ag.AdaptImageMaker] = None,
         cosmology: ag.cosmo.LensingCosmology = ag.cosmo.Planck15(),
         settings_inversion: aa.SettingsInversion = None,

autolens/interferometer/model/visualizer.py

@@ -40,15 +40,12 @@ def visualize_before_fit(
             positions_list = []
 
             for positions_likelihood in analysis.positions_likelihood_list:
-                positions_list.append(
-                    positions_likelihood.positions
-                )
+                positions_list.append(positions_likelihood.positions)
 
             positions = ag.Grid2DIrregular(positions_list)
 
             plotter_interface.image_with_positions(
-                image=analysis.dataset.dirty_image,
-                positions=positions
+                image=analysis.dataset.dirty_image, positions=positions
             )
 
         if analysis.adapt_images is not None:

autolens/lens/tracer.py

@@ -801,7 +801,7 @@ def cls_list_from(self, cls: Type) -> List:
 
         return cls_list
 
-    def plane_index_via_redshift_from(self, redshift : float) -> Optional[int]:
+    def plane_index_via_redshift_from(self, redshift: float) -> Optional[int]:
         """
         Returns the index of a plane at a given redshift.
 

autolens/point/max_separation.py

@@ -42,9 +42,7 @@ def __init__(
         except TypeError:
             plane_index = -1
 
-        self.plane_positions = tracer.traced_grid_2d_list_from(grid=data)[
-            plane_index
-        ]
+        self.plane_positions = tracer.traced_grid_2d_list_from(grid=data)[plane_index]
 
     @property
     def furthest_separations_of_plane_positions(self) -> aa.ArrayIrregular:

test_autolens/analysis/test_positions.py

@@ -17,9 +17,7 @@ def test__check_positions_on_instantiation():
     # Positions input with threshold but positions are length 1.
 
     with pytest.raises(exc.PositionsException):
-        al.PositionsLH(
-            positions=al.Grid2DIrregular([(1.0, 2.0)]), threshold=0.1
-        )
+        al.PositionsLH(positions=al.Grid2DIrregular([(1.0, 2.0)]), threshold=0.1)
 
 
 def test__output_positions_info():

test_autolens/analysis/test_result.py

@@ -253,6 +253,7 @@ def test__positions_likelihood_from(analysis_imaging_7x7):
     assert isinstance(positions_likelihood, al.PositionsLH)
     assert positions_likelihood.threshold == pytest.approx(0.2, 1.0e-4)
 
+
 def test__positions_likelihood_from__mass_centre_radial_distance_min(
     analysis_imaging_7x7,
 ):
@@ -297,7 +298,6 @@ def test__results_include_mask__available_as_property(
     assert (result.mask == masked_imaging_7x7.mask).all()
 
 
-
 def test___image_dict(analysis_imaging_7x7):
     galaxies = af.ModelInstance()
     galaxies.lens = al.Galaxy(redshift=0.5)