datajoint_to_nwb.py

#!/usr/bin/env python3
import os

import sys
from datetime import datetime
from dateutil.tz import tzlocal
import pytz
import re
import numpy as np
import pandas as pd
import warnings

from pipeline import (reference, subject, acquisition, stimulation, analysis,
                      intracellular, extracellular, behavior, utilities)
import pynwb
from pynwb import NWBFile, NWBHDF5IO

warnings.filterwarnings('ignore', module='pynwb')

# ============================== SET CONSTANTS ==========================================
# Each NWBFile represent a session, thus for every session in acquisition.Session, we build one NWBFile
default_nwb_output_dir = os.path.join('data', 'NWB 2.0')
institution = 'Janelia Research Campus'
hardware_filter = 'Bandpass filtered 300-6K Hz'
related_publications = 'doi:10.1038/nature22324'
ecephys_fs = 25000

# experiment description and keywords - from the abstract
experiment_description = ''
keywords = ['anterior lateral motor cortex', 'thalamus', 'persistent activity',
            'optogenetic perturbations', 'extracellular electrophysiology', 'intracellular electrophysiology']


def export_to_nwb(session_key, nwb_output_dir=default_nwb_output_dir, save=False, overwrite=True):
    this_session = (acquisition.Session & session_key).fetch1()
    # =============== General ====================
    # -- NWB file - a NWB2.0 file for each session
    nwbfile = NWBFile(
        session_description=this_session['session_note'],
        identifier='_'.join(
            [this_session['subject_id'],
             this_session['session_time'].strftime('%Y-%m-%d_%H-%M-%S')]),
        session_start_time=this_session['session_time'],
        file_create_date=datetime.now(tzlocal()),
        experimenter='; '.join((acquisition.Session.Experimenter
                                & session_key).fetch('experimenter')),
        institution=institution,
        experiment_description=experiment_description,
        related_publications=related_publications,
        keywords=keywords)
    # -- subject
    subj = (subject.Subject & session_key).fetch1()
    nwbfile.subject = pynwb.file.Subject(
        subject_id=this_session['subject_id'],
        description=subj['subject_description'],
        genotype=' x '.join((subject.Subject.Allele
                             & session_key).fetch('allele')),
        sex=subj['sex'],
        species=subj['species'])
    # =============== Intracellular ====================
    cell = ((intracellular.Cell & session_key).fetch1()
            if intracellular.Cell & session_key
            else None)
    if cell:
        # metadata
        cell = (intracellular.Cell & session_key).fetch1()
        whole_cell_device = nwbfile.create_device(name=cell['device_name'])
        ic_electrode = nwbfile.create_ic_electrode(
            name=cell['cell_id'],
            device=whole_cell_device,
            description='N/A',
            filtering='low-pass: 10kHz',
            location='; '.join([f'{k}: {str(v)}'
                                for k, v in (reference.ActionLocation & cell).fetch1().items()]))
        # acquisition - membrane potential
        mp, mp_wo_spike, mp_start_time, mp_fs = (intracellular.MembranePotential & cell).fetch1(
            'membrane_potential', 'membrane_potential_wo_spike',
            'membrane_potential_start_time', 'membrane_potential_sampling_rate')
        nwbfile.add_acquisition(pynwb.icephys.PatchClampSeries(name='PatchClampSeries',
                                                               electrode=ic_electrode,
                                                               unit='mV',
                                                               conversion=1e-3,
                                                               gain=1.0,
                                                               data=mp,
                                                               starting_time=mp_start_time,
                                                               rate=mp_fs))
        # acquisition - current injection
        current_injection, ci_start_time, ci_fs = (intracellular.CurrentInjection & cell).fetch1(
            'current_injection', 'current_injection_start_time', 'current_injection_sampling_rate')
        nwbfile.add_stimulus(pynwb.icephys.CurrentClampStimulusSeries(name='CurrentClampStimulus',
                                                                      electrode=ic_electrode,
                                                                      conversion=1e-9,
                                                                      gain=1.0,
                                                                      data=current_injection,
                                                                      starting_time=ci_start_time,
                                                                      rate=ci_fs))

        # analysis - membrane potential without spike
        mp_rmv_spike = nwbfile.create_processing_module(name='icephys',
                                                        description='Spike removal')
        mp_rmv_spike.add_data_interface(pynwb.icephys.PatchClampSeries(name='icephys',
                                                                       electrode=ic_electrode,
                                                                       unit='mV',
                                                                       conversion=1e-3,
                                                                       gain=1.0,
                                                                       data=mp_wo_spike,
                                                                       starting_time=mp_start_time,
                                                                       rate=mp_fs))

    # =============== Extracellular ====================
    probe_insertion = ((extracellular.ProbeInsertion & session_key).fetch1()
                       if extracellular.ProbeInsertion & session_key
                       else None)
    if probe_insertion:
        probe = nwbfile.create_device(name = probe_insertion['probe_name'])
        electrode_group = nwbfile.create_electrode_group(
            name='; '.join([f'{probe_insertion["probe_name"]}: {str(probe_insertion["channel_counts"])}']),
            description = 'N/A',
            device = probe,
            location = '; '.join([f'{k}: {str(v)}' for k, v in
                                  (reference.ActionLocation & probe_insertion).fetch1().items()]))

        for chn in (reference.Probe.Channel & probe_insertion).fetch(as_dict=True):
            nwbfile.add_electrode(id=chn['channel_id'],
                                  group=electrode_group,
                                  filtering=hardware_filter,
                                  imp=-1.,
                                  x=chn['channel_x_pos'],
                                  y=chn['channel_y_pos'],
                                  z=chn['channel_z_pos'],
                                  location=electrode_group.location)

        # --- unit spike times ---
        nwbfile.add_unit_column(name='sampling_rate', description='Sampling rate of the raw voltage traces (Hz)')
        nwbfile.add_unit_column(name='unit_x', description='x-coordinate of this unit (mm)')
        nwbfile.add_unit_column(name='unit_y', description='y-coordinate of this unit (mm)')
        nwbfile.add_unit_column(name='unit_z', description='z-coordinate of this unit (mm)')
        nwbfile.add_unit_column(name='cell_type', description='cell type (e.g. wide width, narrow width spiking)')

        for unit in (extracellular.UnitSpikeTimes & probe_insertion).fetch(as_dict=True):
            # make an electrode table region (which electrode(s) is this unit coming from)
            nwbfile.add_unit(id=unit['unit_id'],
                             electrodes=(unit['channel_id']
                                         if isinstance(unit['channel_id'], np.ndarray) else [unit['channel_id']]),
                             sampling_rate=ecephys_fs,
                             unit_x=unit['unit_x'],
                             unit_y=unit['unit_y'],
                             unit_z=unit['unit_z'],
                             cell_type=unit['unit_cell_type'],
                             spike_times=unit['spike_times'],
                             waveform_mean=np.mean(unit['spike_waveform'], axis=0),
                             waveform_sd=np.std(unit['spike_waveform'], axis=0))

    # =============== Behavior ====================
    behavior_data = ((behavior.LickTrace & session_key).fetch1()
                     if behavior.LickTrace & session_key
                     else None)
    if behavior_data:
        behav_acq = pynwb.behavior.BehavioralTimeSeries(name='lick_trace')
        nwbfile.add_acquisition(behav_acq)
        [behavior_data.pop(k) for k in behavior.LickTrace.primary_key]
        lt_start_time = behavior_data.pop('lick_trace_start_time')
        lt_fs = behavior_data.pop('lick_trace_sampling_rate')
        for b_k, b_v in behavior_data.items():
            behav_acq.create_timeseries(name=b_k,
                                        unit='a.u.',
                                        conversion=1.0,
                                        data=b_v,
                                        starting_time=lt_start_time,
                                        rate=lt_fs)

    # =============== Photostimulation ====================
    photostim = ((stimulation.PhotoStimulation & session_key).fetch1()
                       if stimulation.PhotoStimulation & session_key
                       else None)
    if photostim:
        photostim_device = (stimulation.PhotoStimDevice & photostim).fetch1()
        stim_device = nwbfile.create_device(name=photostim_device['device_name'])
        stim_site = pynwb.ogen.OptogeneticStimulusSite(
            name='-'.join([photostim['hemisphere'], photostim['brain_region']]),
            device=stim_device,
            excitation_lambda=float(photostim['photo_stim_excitation_lambda']),
            location = '; '.join([f'{k}: {str(v)}' for k, v in
                                  (reference.ActionLocation & photostim).fetch1().items()]),
            description=(stimulation.PhotoStimulationInfo & photostim).fetch1('photo_stim_notes'))
        nwbfile.add_ogen_site(stim_site)

        if photostim['photostim_timeseries'] is not None:
            nwbfile.add_stimulus(pynwb.ogen.OptogeneticSeries(
                name='_'.join(['photostim_on', photostim['photostim_datetime'].strftime('%Y-%m-%d_%H-%M-%S')]),
                site=stim_site,
                resolution = 0.0,
                conversion = 1e-3,
                data = photostim['photostim_timeseries'],
                starting_time = photostim['photostim_start_time'],
                rate = photostim['photostim_sampling_rate']))

    # =============== TrialSet ====================
    # NWB 'trial' (of type dynamic table) by default comes with three mandatory attributes:
    #                                                                       'id', 'start_time' and 'stop_time'.
    # Other trial-related information needs to be added in to the trial-table as additional columns (with column name
    # and column description)
    if acquisition.TrialSet & session_key:
        # Get trial descriptors from TrialSet.Trial and TrialStimInfo
        trial_columns = [{'name': tag.replace('trial_', ''),
                          'description': re.search(
                              f'(?<={tag})(.*)#(.*)',
                              str((acquisition.TrialSet.Trial
                                   * stimulation.TrialPhotoStimInfo).heading)).groups()[-1].strip()}
                         for tag in (acquisition.TrialSet.Trial * stimulation.TrialPhotoStimInfo).heading.names
                         if tag not in (acquisition.TrialSet.Trial
                                        & stimulation.TrialPhotoStimInfo).primary_key + ['start_time', 'stop_time']]

        # Trial Events - discard 'trial_start' and 'trial_stop' as we already have start_time and stop_time
        # also add `_time` suffix to all events
        trial_events = set(((acquisition.TrialSet.EventTime & session_key)
                            - [{'trial_event': 'trial_start'}, {'trial_event': 'trial_stop'}]).fetch('trial_event'))
        event_names = [{'name': e + '_time', 'description': d}
                       for e, d in zip(*(reference.ExperimentalEvent & [{'event': k}
                                                                        for k in trial_events]).fetch('event',
                                                                                                      'description'))]
        # Add new table columns to nwb trial-table for trial-label
        for c in trial_columns + event_names:
            nwbfile.add_trial_column(**c)

        photostim_tag_default = {tag: '' for tag in stimulation.TrialPhotoStimInfo.heading.names
                                 if tag not in stimulation.TrialPhotoStimInfo.primary_key}

        # Add entry to the trial-table
        for trial in (acquisition.TrialSet.Trial & session_key).fetch(as_dict=True):
            events = dict(zip(*(acquisition.TrialSet.EventTime & trial
                                & [{'trial_event': e} for e in trial_events]).fetch('trial_event', 'event_time')))

            trial_tag_value = ({**trial, **events, **(stimulation.TrialPhotoStimInfo & trial).fetch1()}
                               if (stimulation.TrialPhotoStimInfo & trial)
                               else {**trial, **events, **photostim_tag_default})

            # rename 'trial_id' to 'id'
            trial_tag_value['id'] = trial_tag_value['trial_id']
            [trial_tag_value.pop(k) for k in acquisition.TrialSet.Trial.primary_key]

            # Final tweaks: i) add '_time' suffix and ii) remove 'trial_' prefix
            events = {k + '_time': trial_tag_value.pop(k) for k in events}
            trial_attrs = {k.replace('trial_', ''): trial_tag_value.pop(k)
                           for k in [n for n in trial_tag_value if n.startswith('trial_')]}

            nwbfile.add_trial(**trial_tag_value, **events, **trial_attrs)

    # =============== Write NWB 2.0 file ===============
    if save:
        save_file_name = ''.join([nwbfile.identifier, '.nwb'])
        if not os.path.exists(nwb_output_dir):
            os.makedirs(nwb_output_dir)
        if not overwrite and os.path.exists(os.path.join(nwb_output_dir, save_file_name)):
            return nwbfile
        with NWBHDF5IO(os.path.join(nwb_output_dir, save_file_name), mode = 'w') as io:
            io.write(nwbfile)
            print(f'Write NWB 2.0 file: {save_file_name}')

    return nwbfile


# ============================== EXPORT ALL ==========================================

if __name__ == '__main__':
    if len(sys.argv) > 1:
        nwb_outdir = sys.argv[1]
    else:
        nwb_outdir = default_nwb_output_dir

    for skey in acquisition.Session.fetch('KEY'):
        export_to_nwb(skey, nwb_output_dir=nwb_outdir, save=True)