add behavioral data

src/fox_lab_to_nwb/behavior.py

@@ -0,0 +1,107 @@
+from pathlib import Path
+from typing import Optional
+
+from neuroconv import BaseDataInterface
+from pydantic import FilePath
+from pynwb import NWBFile
+from pynwb import TimeSeries
+from pymatreader import read_mat
+
+
+class BehaviorInterface(BaseDataInterface):
+    def __init__(self, file_path: FilePath):
+        self.file_path = Path(file_path)
+
+    def add_to_nwbfile(
+        self,
+        nwbfile: NWBFile,
+        metadata: Optional[dict] = None,
+    ) -> None:
+
+        mat = read_mat(self.file_path)
+        rec_struct = mat["rec"]
+        daq_struct = rec_struct["daq"]
+
+        timestamps = daq_struct["tstamps"]
+
+        # Extracted from the matlab manually
+        # neither scipy or pymatreader can read string characters from the .mat file
+        channel_names = [
+            "CamSync",
+            "CamTrigger",
+            "OptoTrigger",
+            "LWingBeatAmp",
+            "RWingBeatAmp",
+            "WingBeatFreq",
+            "LHutchen",
+            "RHutchen",
+            "PTrigger",
+        ]
+
+        # TODO: figure how how to store this
+        # Synchronization signals
+        cam_sync = daq_struct["data"][:, 0]
+        cam_trigger = daq_struct["data"][:, 1]
+        opto_trigger = daq_struct["data"][:, 2]
+        ptrigger = daq_struct["data"][:, 8]
+
+        # Behavior signals
+        left_wing_beat_amplitude = daq_struct["data"][:, 3]
+        right_wing_beat_amplitude = daq_struct["data"][:, 4]
+        wing_beat_frequency = daq_struct["data"][:, 5]
+
+        unit = "tbd"
+        description = "tbd"
+        left_wing_beat_amplitude_time_series = TimeSeries(
+            name="LeftWingBeatAmplitudeTimeSeries",
+            data=left_wing_beat_amplitude,
+            unit=unit,
+            timestamps=timestamps,
+            description=description,
+        )
+
+        description = "tbd"
+        right_wing_beat_amplitude_time_series = TimeSeries(
+            name="RightWingBeatAmplitudeTimeSeries",
+            data=right_wing_beat_amplitude,
+            unit=unit,
+            timestamps=timestamps,
+            description=description,
+        )
+
+        description = "tbd"
+        unit = "Hz"  # TODO: Figure this out, the values in the plot are around 3 but should be higher for flies
+        wing_beat_frequency_time_series = TimeSeries(
+            name="WingBeatFrequencyTimeSeries",
+            data=wing_beat_frequency,
+            unit=unit,
+            timestamps=timestamps,
+            description=description,
+        )
+
+        nwbfile.add_acquisition(left_wing_beat_amplitude_time_series)
+        nwbfile.add_acquisition(right_wing_beat_amplitude_time_series)
+        nwbfile.add_acquisition(wing_beat_frequency_time_series)
+
+        # TODO: Ask Ben if this nesting makes sense? probably not
+        # time_series = [left_wing_beat_amplitude_time_series, right_wing_beat_amplitude_time_series, wing_beat_frequency_time_series]
+        # behavioral_time_series_container = BehavioralTimeSeries(name="BehavioralTimeSeries", time_series=time_series)
+        # nwbfile.add_acquisition(behavioral_time_series_container)
+
+        # Not clear what are those signals, haltere?
+        lhutchen = daq_struct["data"][:, 6]
+        rhutchen = daq_struct["data"][:, 7]
+
+        unit = "tbd"
+        description = "tbd"
+        lhutchen_time_series = TimeSeries(
+            name="LHutchenTimeSeries", data=lhutchen, unit=unit, timestamps=timestamps, description=description
+        )
+
+        description = "tbd"
+        rhutchen_time_series = TimeSeries(
+            name="RHutchenTimeSeries", data=rhutchen, unit=unit, timestamps=timestamps, description=description
+        )
+
+        nwbfile.add_acquisition(lhutchen_time_series)
+        nwbfile.add_acquisition(rhutchen_time_series)

src/fox_lab_to_nwb/conversion.py

@@ -0,0 +1,73 @@
+from pathlib import Path
+import time
+from datetime import datetime 
+from typing import Optional
+from zoneinfo import ZoneInfo
+from neuroconv.utils import dict_deep_update, load_dict_from_file
+
+from neuroconv import ConverterPipe
+from fox_lab_to_nwb.behavior import BehaviorInterface
+
+
+def run_trial_conversion(trial_data_folder: Path, output_dir_path: Optional[Path] = None, verbose: bool = True):
+
+    if verbose:
+        start_time = time.time()
+
+    if output_dir_path is None:
+        output_dir_path = Path.home() / "conversion_nwb"
+
+    # session_id = f"{subject}_{session_date}_{session_time}"
+    session_id = "session"
+    nwbfile_path = output_dir_path / f"{session_id}.nwb"
+
+    file_path = trial_data_folder / "Tshx18D07_240124_115923_f3_r1.fly2"
+    assert file_path.exists(), f"File {file_path} does not exist"
+    interface = BehaviorInterface(file_path=file_path)
+
+    converter = ConverterPipe(data_interfaces={"behavior": interface})
+
+
+    # Add datetime to conversion
+    metadata = converter.get_metadata()
+    session_start_time = datetime.now().astimezone(ZoneInfo("America/New_York"))
+    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 / "metadata.yaml"
+    editable_metadata = load_dict_from_file(editable_metadata_path)
+    metadata = dict_deep_update(metadata, editable_metadata)
+
+    subject_metadata = metadata["Subject"]
+    subject = "subject"
+    subject_metadata["subject_id"] = f"{subject}"
+
+    # Run conversion, this adds the basic data to the NWBFile
+    conversion_options = {}
+    converter.run_conversion(
+        metadata=metadata,
+        nwbfile_path=nwbfile_path,
+        conversion_options=conversion_options,
+        overwrite=True,
+    )
+
+    if verbose:
+        stop_time = time.time()
+        conversion_time_seconds = stop_time - start_time
+        if conversion_time_seconds <= 60 * 3:
+            print(f"Conversion took {conversion_time_seconds:.2f} seconds")
+        elif conversion_time_seconds <= 60 * 60:
+            print(f"Conversion took {conversion_time_seconds / 60:.2f} minutes")
+        else:
+            print(f"Conversion took {conversion_time_seconds / 60 / 60:.2f} hours")
+
+
+if __name__ == "__main__":
+
+    verbose = True
+    data_path = Path("/home/heberto/cohen_project/Sample data/Fox Lab")
+    assert data_path.exists(), f"Folder {data_path} does not exist"
+    trial_data_folder = data_path / "Tshx18D07_240124_115923_f3_r1"
+    assert trial_data_folder.exists(), f"Folder {trial_data_folder} does not exist"
+
+    run_trial_conversion(trial_data_folder=trial_data_folder, verbose=verbose)

src/fox_lab_to_nwb/conversion_notes.md

@@ -29,10 +29,11 @@ Channel names:
 - LWingBeatAmp
 - RWingBeatAmp
 - WingBeatFreq
-- LHutchen
+- LHutchen  # What does Hutchen mean? Could be halteres?
 - RHutchen
 - PTrigger
 
+These can't be extracted with pyton from matlab because they are strings. Are they always the same order?
 
 ## Cameras 
 ### Fastec

src/fox_lab_to_nwb/metadata.yaml

@@ -0,0 +1,20 @@
+NWBFile:
+  keywords:
+    - Fly
+    - Wingbeat
+    - Behavior
+  related_publications:
+    - https://doi.org/great_publication or link to APA or MLA citation of the publication
+  session_description:
+    A rich text description of the experiment. Can also just be the abstract of the publication.
+  experiment_description: 'Task: Rapid serial visual presentation (RSVP).'
+  institution:  Case Western Reserve University
+  lab: Fox
+  experimenter:
+    - Streets, Amy
+    - Lea, Kriss
+  surgery: TBD
+Subject:
+  sex: M
+  species: Drosophila melanogaster  # TODO: Figure this one out
+  description: fly