Tidy up observed storm impacts

src/analysis/observed_storm_impacts.py

@@ -22,6 +22,13 @@ def return_first_or_nan(l):
 
 
 def volume_change(df_profiles, df_profile_features, zone):
+    """
+    Calculates how much the volume change there is between prestrom and post storm profiles.
+    :param df_profiles:
+    :param df_profile_features:
+    :param zone: Either 'swash' or 'dune_face'
+    :return:
+    """
     logger.info('Calculating change in beach volume in {} zone'.format(zone))
 
     df_vol_changes = pd.DataFrame(index=df_profile_features.index)
@@ -96,27 +103,19 @@ def beach_volume(x, z, x_min=np.NINF, x_max=np.inf):
         return simps(z_masked, x_masked)
 
 
-def impacts_from_profiles(df_profiles, df_profile_features):
-    # Impacts should be per site, so use the profile_features as the base index.
-    df_observed_impacts = pd.DataFrame(index=df_profile_features.index)
-
-    # Swash zone volume change
-    prestorm_swash_vol, poststorm_swash_vol = volume_change(df_profiles, df_profile_features, zone='swash')
-
-    # Dune volume change
-
-    # If no dune volume change, then swash zone
-
-    #
-    pass
-
-
 def storm_regime(df_observed_impacts):
+    """
+    Returns the dataframe with an additional column of storm impacts based on the Storm Impact Scale. Refer to
+    Sallenger (2000) for details.
+    :param df_observed_impacts:
+    :return:
+    """
     logger.info('Getting observed storm regimes')
-    df_observed_impacts.loc[df_observed_impacts.swash_vol_change < 3,'storm_regime'] = 'swash'
+    df_observed_impacts.loc[df_observed_impacts.swash_vol_change < 3, 'storm_regime'] = 'swash'
     df_observed_impacts.loc[df_observed_impacts.dune_face_vol_change > 3, 'storm_regime'] = 'collision'
     return df_observed_impacts
 
+
 if __name__ == '__main__':
     logger.info('Importing existing data')
     data_folder = './data/interim'
@@ -129,10 +128,10 @@ if __name__ == '__main__':
     logger.info('Getting pre/post storm volumes')
     df_swash_vol_changes = volume_change(df_profiles, df_profile_features, zone='swash')
     df_dune_face_vol_changes = volume_change(df_profiles, df_profile_features, zone='dune_face')
-    df_observed_impacts = df_observed_impacts.join([df_swash_vol_changes, df_dune_face_vol_changes ])
+    df_observed_impacts = df_observed_impacts.join([df_swash_vol_changes, df_dune_face_vol_changes])
 
-    # TODO Classify regime based on volume changes
+    # Classify regime based on volume changes
     df_observed_impacts = storm_regime(df_observed_impacts)
 
-    # TODO Save dataframe to csv
+    # Save dataframe to csv
     df_observed_impacts.to_csv(os.path.join(data_folder, 'impacts_observed.csv'))