def createAxonaData_for_NWBfile(OpenEphysDataPath, spike_name='first_available', channel_map=None,
subfolder='AxonaData', eegChans=None, pixels_per_metre=None,
show_output=False, clustering_name=None):
# Construct path for AxonaData and get experiment info
AxonaDataPath = os.path.join(os.path.dirname(OpenEphysDataPath), subfolder)
experiment_info = getExperimentInfo(OpenEphysDataPath)
# Get channel_map for this dataset
if channel_map is None:
if NWBio.check_if_settings_available(OpenEphysDataPath,'/General/channel_map/'):
channel_map = NWBio.load_settings(OpenEphysDataPath,'/General/channel_map/')
else:
raise ValueError('Channel map could not be generated. Enter channels to process.')
# Get position data for this recording
data_time_edges = NWBio.get_processed_tracking_data_timestamp_edges(OpenEphysDataPath)
if NWBio.check_if_processed_position_data_available(OpenEphysDataPath):
posdata = NWBio.load_processed_tracking_data(OpenEphysDataPath)
else:
posdata = None
# Create AxonaData separately for each recording area
for area in channel_map.keys():
# Load spike data
tetrode_nrs = hfunct.get_tetrode_nrs(channel_map[area]['list'])
print('Loading spikes for tetrodes nr: ' + ', '.join(map(str, tetrode_nrs)))
if spike_name == 'first_available':
spike_data = get_first_available_spike_data(OpenEphysDataPath, tetrode_nrs,
use_idx_keep=True, use_badChan=True,
clustering_name=clustering_name)
else:
spike_data = NWBio.load_spikes(OpenEphysDataPath, tetrode_nrs=tetrode_nrs,
spike_name=spike_name, use_idx_keep=True,
use_badChan=True, clustering_name=clustering_name)
# Load eeg data
if eegChans is None:
eegData = None
else:
eegChansInArea_Bool = [x in channel_map[area]['list'] for x in eegChans]
if any(eegChansInArea_Bool):
eegChansInArea = [x for (x,y) in zip(eegChans, eegChansInArea_Bool) if y]
print('Loading LFP data for channels: ' + ', '.join(map(str, eegChansInArea)))
eegData = load_eegData(OpenEphysDataPath, eegChansInArea)
else:
eegData = None
createAxonaData(AxonaDataPath, spike_data, data_time_edges, posdata=posdata,
experiment_info=experiment_info, axona_file_name=area,
eegData=eegData, pixels_per_metre=pixels_per_metre,
show_output=show_output)
def createAxonaData_for_multiple_NWBfiles(OpenEphysDataPaths, AxonaDataPath,
spike_name='first_available', channel_map=None,
eegChans=None, pixels_per_metre=None,
show_output=False, clustering_name=None):
# Get experiment info
if len(OpenEphysDataPaths) > 1:
print('Using experiment_info from first recording only.')
experiment_info = getExperimentInfo(OpenEphysDataPaths[0])
# Get channel_map for this dataset
if channel_map is None:
if len(OpenEphysDataPaths) > 1:
print('Using channel_map from first recording only.')
if NWBio.check_if_settings_available(OpenEphysDataPaths[0],'/General/channel_map/'):
channel_map = NWBio.load_settings(OpenEphysDataPaths[0],'/General/channel_map/')
else:
raise ValueError('Channel map could not be generated. Enter channels to process.')
# Compute start and end times of each segment of the recording
data_time_edges = []
for OpenEphysDataPath in OpenEphysDataPaths:
data_time_edges.append(NWBio.get_processed_tracking_data_timestamp_edges(OpenEphysDataPath))
recording_edges = []
recording_duration = 0
for dte in data_time_edges:
end_of_this_recording = recording_duration + (dte[1] - dte[0])
recording_edges.append([recording_duration, end_of_this_recording])
recording_duration = end_of_this_recording
combined_data_time_edges = [recording_edges[0][0], recording_edges[-1][1]]
# Get position data for these recordings
print('Loading position data.')
posdata = []
for OpenEphysDataPath in OpenEphysDataPaths:
if NWBio.check_if_processed_position_data_available(OpenEphysDataPath):
posdata.append(NWBio.load_processed_tracking_data(OpenEphysDataPath))
else:
posdata.append(None)
if any([x is None for x in posdata]):
posdata = None
else:
posdata = concatenate_posdata_across_recordings(posdata, data_time_edges,
recording_edges)
# Create AxonaData separately for each recording area
for area in channel_map.keys():
# Load spike data
tetrode_nrs = hfunct.get_tetrode_nrs(channel_map[area]['list'])
print('Loading spikes for tetrodes nr: ' + ', '.join(map(str, tetrode_nrs)))
spike_data = []
for OpenEphysDataPath in OpenEphysDataPaths:
if spike_name == 'first_available':
spike_data.append(get_first_available_spike_data(OpenEphysDataPath, tetrode_nrs,
use_idx_keep=True, use_badChan=True))
else:
print([hfunct.time_string(), 'DEBUG: loading spikes of tet ', tetrode_nrs, ' from ', OpenEphysDataPath])
spike_data.append(NWBio.load_spikes(OpenEphysDataPath, tetrode_nrs=tetrode_nrs,
spike_name=spike_name, use_idx_keep=True,
use_badChan=True, clustering_name=clustering_name))
spike_data = concatenate_spike_data_across_recordings(spike_data, data_time_edges,
recording_edges)
# Load eeg data
if eegChans is None:
eegData = None
else:
eegChansInArea_Bool = [x in channel_map[area]['list'] for x in eegChans]
if any(eegChansInArea_Bool):
eegChansInArea = [x for (x,y) in zip(eegChans, eegChansInArea_Bool) if y]
print('Loading LFP data for channels: ' + ', '.join(map(str, eegChansInArea)))
eegData = []
for OpenEphysDataPath in OpenEphysDataPaths:
print([hfunct.time_string(), 'DEBUG: loading eegData for ', OpenEphysDataPath])
eegData.append(load_eegData(OpenEphysDataPath, eegChansInArea))
print([hfunct.time_string(), 'DEBUG: concatenating eeg data'])
eegData = concatenate_eegData_across_recordings(eegData, data_time_edges,
recording_edges)
else:
eegData = None
createAxonaData(AxonaDataPath, spike_data, combined_data_time_edges,
posdata=posdata, experiment_info=experiment_info,
axona_file_name=area, eegData=eegData,
pixels_per_metre=pixels_per_metre, show_output=show_output)
with open(os.path.join(AxonaDataPath, 'recording_edges'), 'w') as file:
for edges, OpenEphysDataPath in zip(recording_edges, OpenEphysDataPaths):
file.write(str(edges) + ' path: ' + OpenEphysDataPath + '\n')