profiling_dict -> run_time_dict

autogalaxy/analysis/analysis.py

@@ -44,7 +44,7 @@ def __init__(self, cosmology: LensingCosmology = Planck15):
         self.cosmology = cosmology
 
     def plane_via_instance_from(
-        self, instance: af.ModelInstance, profiling_dict: Optional[Dict] = None
+        self, instance: af.ModelInstance, run_time_dict: Optional[Dict] = None
     ) -> Plane:
         """
         Create a `Plane` from the galaxies contained in a model instance.
@@ -62,9 +62,9 @@ def plane_via_instance_from(
         if hasattr(instance, "clumps"):
             return Plane(
                 galaxies=instance.galaxies + instance.clumps,
-                profiling_dict=profiling_dict,
+                run_time_dict=run_time_dict,
             )
-        return Plane(galaxies=instance.galaxies, profiling_dict=profiling_dict)
+        return Plane(galaxies=instance.galaxies, run_time_dict=run_time_dict)
 
     @property
     def fit_func(self) -> Callable:
@@ -77,7 +77,7 @@ def profile_log_likelihood_function(
         This function is optionally called throughout a model-fit to profile the log likelihood function.
 
         All function calls inside the `log_likelihood_function` that are decorated with the `profile_func` are timed
-        with their times stored in a dictionary called the `profiling_dict`.
+        with their times stored in a dictionary called the `run_time_dict`.
 
         An `info_dict` is also created which stores information on aspects of the model and dataset that dictate
         run times, so the profiled times can be interpreted with this context.
@@ -99,7 +99,7 @@ def profile_log_likelihood_function(
         Two dictionaries, the profiling dictionary and info dictionary, which contain the profiling times of the
         `log_likelihood_function` and information on the model and dataset used to perform the profiling.
         """
-        profiling_dict = {}
+        run_time_dict = {}
         info_dict = {}
 
         repeats = conf.instance["general"]["profiling"]["repeats"]
@@ -122,9 +122,9 @@ def profile_log_likelihood_function(
 
         fit_time = (time.time() - start) / repeats
 
-        profiling_dict["fit_time"] = fit_time
+        run_time_dict["fit_time"] = fit_time
 
-        fit = self.fit_func(instance=instance, profiling_dict=profiling_dict)
+        fit = self.fit_func(instance=instance, run_time_dict=run_time_dict)
         fit.figure_of_merit
 
         try:
@@ -151,27 +151,27 @@ def profile_log_likelihood_function(
                 ] = fit.inversion.w_tilde.curvature_preload.shape[0]
 
         self.output_profiling_info(
-            paths=paths, profiling_dict=profiling_dict, info_dict=info_dict
+            paths=paths, run_time_dict=run_time_dict, info_dict=info_dict
         )
 
-        return profiling_dict, info_dict
+        return run_time_dict, info_dict
 
     def output_profiling_info(
-        self, paths: Optional[af.DirectoryPaths], profiling_dict: Dict, info_dict: Dict
+        self, paths: Optional[af.DirectoryPaths], run_time_dict: Dict, info_dict: Dict
     ):
         """
         Output the log likelihood function profiling information to hard-disk as a json file.
 
         This function is separate from the `profile_log_likelihood_function` function above such that it can be
         called by children `Analysis` classes that profile additional aspects of the model-fit and therefore add
-        extra information to the `profiling_dict` and `info_dict`.
+        extra information to the `run_time_dict` and `info_dict`.
 
         Parameters
         ----------
         paths
             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.
-        profiling_dict
+        run_time_dict
             A dictionary containing the profiling times of the functions called by the `log_likelihood_function`.
         info_dict
             A dictionary containing information on the model and dataset used to perform the profiling, where these
@@ -183,8 +183,8 @@ def output_profiling_info(
 
         os.makedirs(paths.profile_path, exist_ok=True)
 
-        with open(path.join(paths.profile_path, "profiling_dict.json"), "w+") as f:
-            json.dump(profiling_dict, f, indent=4)
+        with open(path.join(paths.profile_path, "run_time_dict.json"), "w+") as f:
+            json.dump(run_time_dict, f, indent=4)
 
         with open(path.join(paths.profile_path, "info_dict.json"), "w+") as f:
             json.dump(info_dict, f, indent=4)

autogalaxy/imaging/fit_imaging.py

@@ -25,7 +25,7 @@ def __init__(
         settings_pixelization: aa.SettingsPixelization = aa.SettingsPixelization(),
         settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
         preloads: aa.Preloads = Preloads(),
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ):
         """
         Fits an imaging dataset using a `Plane` object.
@@ -65,7 +65,7 @@ def __init__(
         preloads
             Contains preloaded calculations (e.g. linear algebra matrices) which can skip certain calculations in
             the fit.
-        profiling_dict
+        run_time_dict
             A dictionary which if passed to the fit records how long fucntion calls which have the `profile_func`
             decorator take to run.
         """
@@ -75,7 +75,7 @@ def __init__(
 
         super().__init__(
             dataset=dataset,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )
         AbstractFitInversion.__init__(
             self=self, model_obj=plane, settings_inversion=settings_inversion
@@ -145,7 +145,7 @@ def plane_to_inversion(self) -> PlaneToInversion:
             settings_pixelization=self.settings_pixelization,
             settings_inversion=self.settings_inversion,
             preloads=self.preloads,
-            profiling_dict=self.profiling_dict,
+            run_time_dict=self.run_time_dict,
         )
 
     @cached_property
@@ -305,7 +305,7 @@ def refit_with_new_preloads(
         -------
         A new fit which has used new preloads input into this function but the same dataset, plane and other settings.
         """
-        profiling_dict = {} if self.profiling_dict is not None else None
+        run_time_dict = {} if self.run_time_dict is not None else None
 
         settings_inversion = (
             self.settings_inversion
@@ -319,5 +319,5 @@ def refit_with_new_preloads(
             settings_pixelization=self.settings_pixelization,
             settings_inversion=settings_inversion,
             preloads=preloads,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )

autogalaxy/imaging/model/analysis.py

@@ -151,7 +151,7 @@ def fit_imaging_via_instance_from(
         self,
         instance: af.ModelInstance,
         preload_overwrite: Optional[Preloads] = None,
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ) -> FitImaging:
         """
         Given a model instance create a `FitImaging` object.
@@ -166,7 +166,7 @@ def fit_imaging_via_instance_from(
             via a non-linear search).
         preload_overwrite
             If a `Preload` object is input this is used instead of the preloads stored as an attribute in the analysis.
-        profiling_dict
+        run_time_dict
             A dictionary which times functions called to fit the model to data, for profiling.
 
         Returns
@@ -177,20 +177,20 @@ def fit_imaging_via_instance_from(
         instance = self.instance_with_associated_adapt_images_from(instance=instance)
 
         plane = self.plane_via_instance_from(
-            instance=instance, profiling_dict=profiling_dict
+            instance=instance, run_time_dict=run_time_dict
         )
 
         return self.fit_imaging_via_plane_from(
             plane=plane,
             preload_overwrite=preload_overwrite,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )
 
     def fit_imaging_via_plane_from(
         self,
         plane: Plane,
         preload_overwrite: Optional[Preloads] = None,
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ) -> FitImaging:
         """
         Given a `Plane`, which the analysis constructs from a model instance, create a `FitImaging` object.
@@ -204,7 +204,7 @@ def fit_imaging_via_plane_from(
             The plane of galaxies whose model images are used to fit the imaging data.
         preload_overwrite
             If a `Preload` object is input this is used instead of the preloads stored as an attribute in the analysis.
-        profiling_dict
+        run_time_dict
             A dictionary which times functions called to fit the model to data, for profiling.
 
         Returns
@@ -221,7 +221,7 @@ def fit_imaging_via_plane_from(
             settings_pixelization=self.settings_pixelization,
             settings_inversion=self.settings_inversion,
             preloads=preloads,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )
 
     @property
@@ -410,7 +410,7 @@ def profile_log_likelihood_function(
         This function is optionally called throughout a model-fit to profile the log likelihood function.
 
         All function calls inside the `log_likelihood_function` that are decorated with the `profile_func` are timed
-        with their times stored in a dictionary called the `profiling_dict`.
+        with their times stored in a dictionary called the `run_time_dict`.
 
         An `info_dict` is also created which stores information on aspects of the model and dataset that dictate
         run times, so the profiled times can be interpreted with this context.
@@ -432,14 +432,14 @@ def profile_log_likelihood_function(
         Two dictionaries, the profiling dictionary and info dictionary, which contain the profiling times of the
         `log_likelihood_function` and information on the model and dataset used to perform the profiling.
         """
-        profiling_dict, info_dict = super().profile_log_likelihood_function(
+        run_time_dict, info_dict = super().profile_log_likelihood_function(
             instance=instance,
         )
 
         info_dict["psf_shape_2d"] = self.dataset.psf.shape_native
 
         self.output_profiling_info(
-            paths=paths, profiling_dict=profiling_dict, info_dict=info_dict
+            paths=paths, run_time_dict=run_time_dict, info_dict=info_dict
         )
 
-        return profiling_dict, info_dict
+        return run_time_dict, info_dict

autogalaxy/interferometer/fit_interferometer.py

@@ -20,7 +20,7 @@ def __init__(
         settings_pixelization: aa.SettingsPixelization = aa.SettingsPixelization(),
         settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
         preloads: aa.Preloads = Preloads(),
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ):
         """
         Fits an interferometer dataset using a `Plane` object.
@@ -61,7 +61,7 @@ def __init__(
         preloads
             Contains preloaded calculations (e.g. linear algebra matrices) which can skip certain calculations in
             the fit.
-        profiling_dict
+        run_time_dict
             A dictionary which if passed to the fit records how long fucntion calls which have the `profile_func`
             decorator take to run.
         """
@@ -72,7 +72,7 @@ def __init__(
             settings_inversion.use_w_tilde = False
 
         super().__init__(
-            dataset=dataset, use_mask_in_fit=False, profiling_dict=profiling_dict
+            dataset=dataset, use_mask_in_fit=False, run_time_dict=run_time_dict
         )
         AbstractFitInversion.__init__(
             self=self, model_obj=plane, settings_inversion=settings_inversion
@@ -241,10 +241,10 @@ def refit_with_new_preloads(
         -------
         A new fit which has used new preloads input into this function but the same dataset, plane and other settings.
         """
-        if self.profiling_dict is not None:
-            profiling_dict = {}
+        if self.run_time_dict is not None:
+            run_time_dict = {}
         else:
-            profiling_dict = None
+            run_time_dict = None
 
         if settings_inversion is None:
             settings_inversion = self.settings_inversion
@@ -255,5 +255,5 @@ def refit_with_new_preloads(
             settings_pixelization=self.settings_pixelization,
             settings_inversion=settings_inversion,
             preloads=preloads,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )

autogalaxy/interferometer/model/analysis.py

@@ -159,7 +159,7 @@ def log_likelihood_function(self, instance: af.ModelInstance) -> float:
     def fit_interferometer_via_instance_from(
         self,
         instance: af.ModelInstance,
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ) -> FitInterferometer:
         """
         Given a model instance create a `FitInterferometer` object.
@@ -174,7 +174,7 @@ def fit_interferometer_via_instance_from(
             via a non-linear search).
         preload_overwrite
             If a `Preload` object is input this is used instead of the preloads stored as an attribute in the analysis.
-        profiling_dict
+        run_time_dict
             A dictionary which times functions called to fit the model to data, for profiling.
 
         Returns
@@ -185,18 +185,18 @@ def fit_interferometer_via_instance_from(
         instance = self.instance_with_associated_adapt_images_from(instance=instance)
 
         plane = self.plane_via_instance_from(
-            instance=instance, profiling_dict=profiling_dict
+            instance=instance, run_time_dict=run_time_dict
         )
 
         return self.fit_interferometer_via_plane_from(
-            plane=plane, profiling_dict=profiling_dict
+            plane=plane, run_time_dict=run_time_dict
         )
 
     def fit_interferometer_via_plane_from(
         self,
         plane: Plane,
         preload_overwrite: Optional[Preloads] = None,
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ) -> FitInterferometer:
         """
         Given a `Plane`, which the analysis constructs from a model instance, create a `FitInterferometer` object.
@@ -223,7 +223,7 @@ def fit_interferometer_via_plane_from(
             settings_pixelization=self.settings_pixelization,
             settings_inversion=self.settings_inversion,
             preloads=preloads,
-            profiling_dict=profiling_dict,
+            run_time_dict=run_time_dict,
         )
 
     @property
@@ -417,7 +417,7 @@ def profile_log_likelihood_function(
         This function is optionally called throughout a model-fit to profile the log likelihood function.
 
         All function calls inside the `log_likelihood_function` that are decorated with the `profile_func` are timed
-        with their times stored in a dictionary called the `profiling_dict`.
+        with their times stored in a dictionary called the `run_time_dict`.
 
         An `info_dict` is also created which stores information on aspects of the model and dataset that dictate
         run times, so the profiled times can be interpreted with this context.
@@ -439,15 +439,15 @@ def profile_log_likelihood_function(
         Two dictionaries, the profiling dictionary and info dictionary, which contain the profiling times of the
         `log_likelihood_function` and information on the model and dataset used to perform the profiling.
         """
-        profiling_dict, info_dict = super().profile_log_likelihood_function(
+        run_time_dict, info_dict = super().profile_log_likelihood_function(
             instance=instance,
         )
 
         info_dict["number_of_visibilities"] = self.dataset.visibilities.shape[0]
         info_dict["transformer_cls"] = self.dataset.transformer.__class__.__name__
 
         self.output_profiling_info(
-            paths=paths, profiling_dict=profiling_dict, info_dict=info_dict
+            paths=paths, run_time_dict=run_time_dict, info_dict=info_dict
         )
 
-        return profiling_dict, info_dict
+        return run_time_dict, info_dict

autogalaxy/plane/plane.py

@@ -23,7 +23,7 @@ def __init__(
         self,
         galaxies,
         redshift: Optional[float] = None,
-        profiling_dict: Optional[Dict] = None,
+        run_time_dict: Optional[Dict] = None,
     ):
         """
         A plane of galaxies where all galaxies are at the same redshift.
@@ -52,7 +52,7 @@ def __init__(
         self.redshift = redshift
         self.galaxies = galaxies
 
-        self.profiling_dict = profiling_dict
+        self.run_time_dict = run_time_dict
 
     def dict(self) -> Dict:
         plane_dict = super().dict()

autogalaxy/plane/plane_util.py

@@ -209,7 +209,7 @@ def galaxies_in_redshift_ordered_planes_from(galaxies, plane_redshifts):
     return galaxies_in_redshift_ordered_planes
 
 
-def planes_via_galaxies_from(galaxies, profiling_dict=None, plane_cls=Plane):
+def planes_via_galaxies_from(galaxies, run_time_dict=None, plane_cls=Plane):
     plane_redshifts = ordered_plane_redshifts_from(galaxies=galaxies)
 
     galaxies_in_planes = galaxies_in_redshift_ordered_planes_from(
@@ -221,7 +221,7 @@ def planes_via_galaxies_from(galaxies, profiling_dict=None, plane_cls=Plane):
     for plane_index in range(0, len(plane_redshifts)):
         planes.append(
             plane_cls(
-                galaxies=galaxies_in_planes[plane_index], profiling_dict=profiling_dict
+                galaxies=galaxies_in_planes[plane_index], run_time_dict=run_time_dict
             )
         )