def get_unit_waveforms(file_dir, unit, required_descrip=None):
if isinstance(unit, int):
un = 'unit%03i' % unit
else:
un = unit
unit = parse_unit_number(un)
h5_file = get_h5_filename(file_dir)
clustering_params = params.load_params('clustering_params', file_dir)
fs = clustering_params['sampling_rate']
with tables.open_file(h5_file, 'r') as hf5:
waveforms = hf5.root.sorted_units[un].waveforms[:]
descriptor = hf5.root.unit_descriptor[unit]
if required_descrip is not None:
if descriptor != required_descrip:
return None, descriptor, fs
return waveforms, descriptor, fs * 10
def get_raw_unit_waveforms(rec_dir,
unit_name,
electrode_mapping=None,
clustering_params=None,
shell=True,
required_descrip=None):
'''Returns the waveforms of a single unit extracting them directly from the
raw data files.
Parameters
----------
rec_dir : str
unit_name : str or int
electrode_mapping : pd.DataFrame (optional)
if raw data is not in hf5 this is used to get the raw data from the
original dat files
if not provided program will try to grab this from the h5 file
clustering_params : dict (optional)
requires fields 'spike_snapshot' and 'bandpass_params'
if not provided these will be queried from the json file written in the
rec_dir or from the defaults if no params are in rec_dir
shell : bool (optional)
True to CLI (default in ssh). False for GUI. Only relevant if multiple
h5 files in rec_dir
required_descrip : tuple (optional)
required unit description. Returns None instead of raw trace if unit
does not match required_descrip
Returns
-------
raw_trace, unit_descriptor, sampling_rate
np.array, tuple, float
'''
if isinstance(unit_name, int):
unit_num = unit_name
unit_name = 'unit%03i' % unit_num
else:
unit_num = parse_unit_number(unit_name)
if electrode_mapping is None:
electrode_mapping = get_electrode_mapping(rec_dir)
if clustering_params is None:
clustering_params = params.load_params('clustering_params', rec_dir)
snapshot = clustering_params['spike_snapshot']
snapshot = [
snapshot['Time before spike (ms)'], snapshot['Time after spike (ms)']
]
bandpass = clustering_params['bandpass_params']
bandpass = [bandpass['Lower freq cutoff'], bandpass['Upper freq cutoff']]
fs = clustering_params['sampling_rate']
if fs is None:
raise ValueError('clustering_params.json does not exist')
# Get spike times for unit
h5_file = get_h5_filename(rec_dir, shell=shell)
with tables.open_file(h5_file, 'r') as hf5:
spike_times = hf5.root.sorted_units[unit_name]['times'][:]
descriptor = hf5.root.unit_descriptor[unit_num]
if required_descrip is not None:
if descriptor != required_descrip:
return None, descriptor, fs
print('Getting raw waveforms for %s %s' %
(os.path.basename(rec_dir), unit_name))
electrode = descriptor['electrode_number']
raw_el = get_raw_trace(rec_dir, electrode, electrode_mapping)
if electrode_mapping is None and raw_el is None:
raise FileNotFoundError('Raw data not found in h5 file and'
' electrode_mapping not found')
if raw_el is None:
raise FileNotFoundError('Raw data not found')
slices_dj, new_fs = clust.get_waveforms(raw_el,
spike_times,
sampling_rate=fs,
snapshot=snapshot,
bandpass=bandpass)
return slices_dj, descriptor, new_fs