rename variable

Author: Yngve S. Kristiansen

src/semeio/workflows/ahm_analysis/ahmanalysis.py

@@ -236,9 +236,9 @@ def _replace(s: str) -> str:
         )
         # loop over keys and calculate the KS matrix,
         # conditioning one parameter at the time.
-        updated_combinations = deepcopy(combinations)
-        for group_name, obs_group in combinations.items():
-            print("Processing:", group_name)
+        obs_group_to_observations = deepcopy(combinations)
+        for obs_group, observations in combinations.items():
+            print("Processing:", obs_group)
 
             #  Use localization to evaluate change of parameters for each observation
             # The order of the context managers is important, as we want to create a new
@@ -261,7 +261,7 @@ def _replace(s: str) -> str:
                     update_log = _run_ministep(
                         prior_storage=prior_ensemble,
                         target_storage=target_ensemble,
-                        obs_group=obs_group,
+                        observations=observations,
                         data_parameters=field_parameters + gen_kw_names,
                         observation_settings=observation_settings,
                         es_settings=es_settings,
@@ -270,29 +270,29 @@ def _replace(s: str) -> str:
                     # Get the active vs total observation info
                     df_update_log = make_update_log_df(update_log)
                 except ErtAnalysisError:
-                    logger.error(f"Analysis failed for: {obs_group}")
-                    del updated_combinations[group_name]
+                    logger.error(f"Analysis failed for: {observations}")
+                    del obs_group_to_observations[obs_group]
                     continue
                 # Get the updated scalar parameter distributions
                 target_ensemble.load_all_gen_kw_data().to_csv(
-                    ahmanalysis_reports_dir / f"{group_name}.csv"
+                    ahmanalysis_reports_dir / f"{obs_group}.csv"
                 )
 
-                active_obs.at["ratio", group_name] = (
+                active_obs.at["ratio", obs_group] = (
                     str(count_active_observations(df_update_log))
                     + " active/"
                     + str(len(df_update_log.index))
                 )
                 # Get misfit values
-                misfitval[group_name] = [
+                misfitval[obs_group] = [
                     calc_observationsgroup_misfit(
-                        group_name,
+                        obs_group,
                         df_update_log,
                         LibresFacade.load_all_misfit_data(prior_ensemble),
                     )
                 ]
                 # Calculate Ks matrix for scalar parameters
-                kolmogorov_smirnov_data[group_name] = kolmogorov_smirnov_data[
+                kolmogorov_smirnov_data[obs_group] = kolmogorov_smirnov_data[
                     "Parameters"
                 ].map(
                     calc_kolmogorov_smirnov(
@@ -344,7 +344,7 @@ def make_update_log_df(update_log: SmootherSnapshot) -> pd.DataFrame:
 def _run_ministep(
     prior_storage: Ensemble,
     target_storage: Ensemble,
-    obs_group: Iterable[str],
+    observations: Iterable[str],
     data_parameters: Iterable[str],
     observation_settings: ObservationSettings,
     es_settings: ESSettings,
@@ -355,7 +355,7 @@ def _run_ministep(
     return smoother_update(
         prior_storage=prior_storage,
         posterior_storage=target_storage,
-        observations=obs_group,
+        observations=observations,
         parameters=data_parameters,
         update_settings=copy.deepcopy(observation_settings),
         es_settings=es_settings,

tests/workflows/ahm_analysis/test_ahm_analysis.py

@@ -28,7 +28,7 @@ def test_make_update_log_df(snake_oil_config, snapshot):
         log = _run_ministep(
             prior_storage=prior_ens,
             target_storage=posterior_ens,
-            obs_group=sorted(prior_ens.experiment.observation_keys),
+            observations=sorted(prior_ens.experiment.observation_keys),
             data_parameters=sorted(prior_ens.experiment.parameter_configuration.keys()),
             observation_settings=snake_oil_config.analysis_config.observation_settings,
             es_settings=snake_oil_config.analysis_config.es_settings,