Flow. Use intermediate iceblocks.csv file for more convenient viewing/editing.

cfatools/processor/flow.py

@@ -238,7 +238,7 @@ def get_bubble_density_from_conduct(dataset: DatasetReader):
     return compump_df
 
 
-def get_datasets_data(dataset: DatasetReader)\
+def get_datasets_data(dataset: DatasetReader, retrieve_iceblocks_from_processed_csv: bool = True)\
         -> typing.Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame]:
     """Get the dataframes useful for flow analysis
 
@@ -246,6 +246,10 @@ def get_datasets_data(dataset: DatasetReader)\
     ----------
     dataset: DatasetReader
         Dataset whose data should be retrieved.
+    retrieve_iceblocks_from_processed_csv: bool, optional
+        If `True`, the information about the iceblock sequence will be read from a processed file
+        (`processed/iceblocks.csv`; if it exists, otherwise it will be created). If `False`, the information will be
+        re-processed from `yyyymmdd_[dataset_name]_ICBKCTRL_instant.log` file. Default is `True`.
 
     Returns
     -------
@@ -257,8 +261,13 @@ def get_datasets_data(dataset: DatasetReader)\
     encoder_df = encoder_df.drop(columns="speed_avg")
 
     # Iceblock
+    iceblock_filename = os.path.join(dataset.dataset_path, "processed", "iceblocks.csv")
+    if retrieve_iceblocks_from_processed_csv and os.path.exists(iceblock_filename):
+        iceblock_df = pd.read_csv(iceblock_filename, parse_dates=["datetime_start", "datetime_end", "datetime_stacked"])
+    else:
         iceblock_df = dataset.get_timeseries("ICBKCTRL_instant")
         iceblock_df = iceblock.get_clean_iceblock_df(iceblock_df)
+        iceblock_df.to_csv(iceblock_filename, index=False, date_format="%Y-%m-%dT%H:%M:%SZ")
 
     # Conductivity
     conduct_df = dataset.get_timeseries("CONDUCTI_periodic")