add epoch for sub-session times

src/cai_lab_to_nwb/zaki_2024/zaki_2024_convert_week_session.py

@@ -1,12 +1,21 @@
 """Primary script to run to convert an entire session for of data using the NWBConverter."""
 
 import time
+import uuid
+from copy import deepcopy
 from natsort import natsorted
 from pathlib import Path
 from typing import Union
 import os
+import pandas as pd
+
+from pynwb import NWBFile
+from pynwb.epoch import TimeIntervals
 from neuroconv.utils import load_dict_from_file, dict_deep_update
+from neuroconv.tools.nwb_helpers import configure_and_write_nwbfile
 
+from utils import get_session_slicing_time_range
+from interfaces.miniscope_imaging_interface import get_miniscope_folder_path
 from zaki_2024_nwbconverter import Zaki2024NWBConverter
 
 
@@ -47,7 +56,7 @@ def session_to_nwb(
     else:
         print(f"No .edf file found in {edf_folder_path}")
 
-    # Add Cross session cell registration
+        # Add Cross session cell registration
     main_folder = data_dir_path / f"/Ca_EEG_Calcium/{subject_id}/SpatialFootprints"
     file_paths = []
     for folder in os.listdir(main_folder):
@@ -60,28 +69,69 @@ def session_to_nwb(
     source_data.update(dict(CellRegistration=dict(file_paths=file_paths)))
     conversion_options.update(dict(CellRegistration=dict(stub_test=stub_test, subject_id=subject_id)))
 
-    converter = Zaki2024NWBConverter(source_data=source_data)
-
-    # Add datetime to conversion
-    metadata = converter.get_metadata()
-
     from mne.io import read_raw_edf
 
     edf_reader = read_raw_edf(input_fname=edf_file_paths[0], verbose=verbose)
     session_start_time = edf_reader.info["meas_date"]
-    metadata["NWBFile"]["session_start_time"] = session_start_time
 
-    # Update default metadata with the editable in the corresponding yaml file
     editable_metadata_path = Path(__file__).parent / "zaki_2024_metadata.yaml"
     editable_metadata = load_dict_from_file(editable_metadata_path)
-    metadata = dict_deep_update(metadata, editable_metadata)
+    nwbfile_kwargs = deepcopy(editable_metadata["NWBFile"])
+
+    nwbfile_kwargs.update(
+        dict(
+            session_id=f"{subject_id}_week_session",
+            identifier=str(uuid.uuid4()),
+            session_start_time=session_start_time,
+        )
+    )
+
+    nwbfile = NWBFile(**nwbfile_kwargs)
+
+    # Add epochs table to store time range of conditioning and offline sessions
+    sessions_summary_file = data_dir_path / f"Ca_EEG_Experiment/{subject_id}/{subject_id}_SessionTimes.csv"
+    sessions_summary_df = pd.read_csv(sessions_summary_file)
+
+    # Add columns to TimeIntervals
+    nwbfile.add_epoch_column(name="session_ids", description="ID of the session")
 
+    for task, date_str, time_str in zip(
+        sessions_summary_df["Session"], sessions_summary_df["Date"], sessions_summary_df["Time"]
+    ):
+        session_id = subject_id + "_" + task
+        if "Offline" in session_id:
+            offline_day = session_id.split("Session")[0]
+            experiment_dir_path = (
+                data_dir_path / "Ca_EEG_Experiment" / subject_id / (subject_id + "_Offline") / offline_day
+            )
+        else:
+            experiment_dir_path = (
+                data_dir_path / "Ca_EEG_Experiment" / subject_id / (subject_id + "_Sessions") / session_id
+            )
+        folder_path = experiment_dir_path / date_str / time_str
+        miniscope_folder_path = get_miniscope_folder_path(folder_path)
+        miniscope_metadata_json = folder_path / "metaData.json"
+        assert miniscope_metadata_json.exists(), f"General metadata json not found in {folder_path}"
+        timestamps_file_path = miniscope_folder_path / "timeStamps.csv"
+        assert timestamps_file_path.exists(), f"Miniscope timestamps file not found in {miniscope_folder_path}"
+        start_datetime_timestamp, stop_datetime_timestamp = get_session_slicing_time_range(
+            miniscope_metadata_json=miniscope_metadata_json, timestamps_file_path=timestamps_file_path
+        )
+        start_time = start_datetime_timestamp - session_start_time.replace(tzinfo=None)
+        stop_time = stop_datetime_timestamp - session_start_time.replace(tzinfo=None)
+        nwbfile.add_epoch(
+            start_time=start_time.total_seconds(), stop_time=stop_time.total_seconds(), session_ids=session_id
+        )
+
+    converter = Zaki2024NWBConverter(source_data=source_data)
+
+    # Add datetime to conversion
+    metadata = converter.get_metadata()
     metadata["Subject"]["subject_id"] = subject_id
 
     # Run conversion
-    converter.run_conversion(
-        metadata=metadata, nwbfile_path=nwbfile_path, conversion_options=conversion_options, overwrite=True
-    )
+    converter.add_to_nwbfile(metadata=metadata, nwbfile=nwbfile, conversion_options=conversion_options)
+    configure_and_write_nwbfile(nwbfile=nwbfile, backend="hdf5", output_filepath=nwbfile_path)
 
     if verbose:
         stop_time = time.time()

src/cai_lab_to_nwb/zaki_2024/zaki_2024_nwbconverter.py

@@ -1,10 +1,7 @@
 """Primary NWBConverter class for this dataset."""
 
 from neuroconv import NWBConverter
-from pynwb import NWBFile
 from neuroconv.datainterfaces import VideoInterface
-from typing import Optional
-from pathlib import Path
 
 from interfaces import (
     MinianSegmentationInterface,