def test_kilosort_extractor(self):
path1 = self.test_dir + '/ks'
se.KiloSortSortingExtractor.write_sorting(self.SX, path1)
SX_ks = se.KiloSortSortingExtractor(path1)
check_sorting_return_types(SX_ks)
check_sortings_equal(self.SX, SX_ks)
check_dumping(SX_ks)
def get_result_from_folder(output_folder):
output_folder = Path(output_folder)
with (output_folder / 'spikeinterface_params.json').open('r') as f:
sorter_params = json.load(f)['sorter_params']
sorting = se.KiloSortSortingExtractor(
folder_path=output_folder,
keep_good_only=sorter_params['keep_good_only'])
return sorting
def get_result_from_folder(output_folder):
sorting = se.KiloSortSortingExtractor(folder_path=output_folder)
return sorting
def test_kilosort_extractor(self):
path1 = self.test_dir + '/firings_true'
se.KiloSortSortingExtractor.writeSorting(self.SX, path1)
SX_ks = se.KiloSortSortingExtractor(path1)
self._check_sorting_return_types(SX_ks)
self._check_sortings_equal(self.SX, SX_ks)
def kilosort(recording,
kilosort_path=None,
npy_matlab_path=None,
output_folder=None,
useGPU=False,
probe_file=None,
file_name=None,
spike_thresh=4,
electrode_dimensions=None):
if kilosort_path is None:
kilosort_path = os.getenv('KILOSORT_PATH', None)
if npy_matlab_path is None:
npy_matlab_path = os.getenv('NPY_MATLAB_PATH', None)
if not os.path.isfile(join(kilosort_path, 'preprocessData.m')) \
or not os.path.isfile(join(npy_matlab_path, 'readNPY.m')):
raise ModuleNotFoundError(
"\nTo use KiloSort, install KiloSort and npy-matlab from sources: \n\n"
"\ngit clone https://github.com/cortex-lab/KiloSort\n"
"\ngit clone https://github.com/kwikteam/npy-matlab\n"
"and provide the installation path with the 'kilosort_path' and "
"'npy_matlab_path' arguments or by setting the KILOSORT_PATH and NPY_MATLAB_PATH"
"environment variables.\n+n"
"\nMore information on KiloSort at: "
"\nhttps://github.com/cortex-lab/KiloSort")
source_dir = os.path.dirname(os.path.realpath(__file__))
if output_folder is None:
output_folder = os.path.abspath('kilosort')
else:
output_folder = os.path.abspath(join(output_folder, 'kilosort'))
if not os.path.isdir(output_folder):
os.makedirs(output_folder)
kilosort_path = os.path.abspath(kilosort_path)
npy_matlab_path = os.path.abspath(npy_matlab_path)
if probe_file is not None:
se.loadProbeFile(recording, probe_file)
# save binary file
if file_name is None:
file_name = 'recording'
elif file_name.endswith('.dat'):
file_name = file_name[file_name.find('.dat')]
se.writeBinaryDatFormat(recording,
join(output_folder, file_name),
dtype='int16')
# set up kilosort config files and run kilosort on data
with open(join(source_dir, 'kilosort_master.txt'), 'r') as f:
kilosort_master = f.readlines()
with open(join(source_dir, 'kilosort_config.txt'), 'r') as f:
kilosort_config = f.readlines()
with open(join(source_dir, 'kilosort_channelmap.txt'), 'r') as f:
kilosort_channelmap = f.readlines()
nchan = recording.getNumChannels()
dat_file = file_name + '.dat'
kilo_thresh = spike_thresh
Nfilt = (nchan // 32) * 32 * 8
if Nfilt == 0:
Nfilt = nchan * 8
nsamples = 128 * 1024 + 64
if useGPU:
ug = 1
else:
ug = 0
abs_channel = os.path.abspath(join(output_folder, 'kilosort_channelmap.m'))
abs_config = os.path.abspath(join(output_folder, 'kilosort_config.m'))
kilosort_master = ''.join(kilosort_master).format(ug, kilosort_path,
npy_matlab_path,
output_folder,
abs_channel, abs_config)
kilosort_config = ''.join(kilosort_config).format(
nchan, nchan, recording.getSamplingFrequency(), dat_file, Nfilt,
nsamples, kilo_thresh)
if 'location' in recording.getChannelPropertyNames():
positions = np.array([
recording.getChannelProperty(chan, 'location')
for chan in range(nchan)
])
if electrode_dimensions is None:
kilosort_channelmap = ''.join(kilosort_channelmap).format(
nchan, list(positions[:, 0]), list(positions[:, 1]),
'ones(1, Nchannels)', recording.getSamplingFrequency())
elif len(electrode_dimensions) == 2:
kilosort_channelmap = ''.join(kilosort_channelmap).format(
nchan, list(positions[:, electrode_dimensions[0]]),
list(positions[:, electrode_dimensions[1]]),
'ones(1, Nchannels)', recording.getSamplingFrequency())
else:
raise Exception("Electrode dimension should bi a list of len 2")
else:
raise Exception(
"'location' information is needed. Provide a probe information with a 'probe_file'"
)
for fname, value in zip(
['kilosort_master.m', 'kilosort_config.m', 'kilosort_channelmap.m'],
[kilosort_master, kilosort_config, kilosort_channelmap]):
with open(join(output_folder, fname), 'w') as f:
f.writelines(value)
# start sorting with kilosort
print('Running KiloSort')
t_start_proc = time.time()
cmd = 'matlab -nosplash -nodisplay -r "run {}; quit;"'.format(
join(output_folder, 'kilosort_master.m'))
print(cmd)
call_command(cmd)
# retcode = run_command_and_print_output(cmd)
# if retcode != 0:
# raise Exception('KiloSort returned a non-zero exit code')
print('Elapsed time: ', time.time() - t_start_proc)
sorting = se.KiloSortSortingExtractor(join(output_folder))
return sorting
def _kilosort(recording,
output_folder=None,
kilosort_path=None,
npy_matlab_path=None,
useGPU=False,
probe_file=None,
file_name=None,
detect_threshold=4,
electrode_dimensions=None):
if kilosort_path is None or kilosort_path == 'None':
klp = os.getenv('KILOSORT_PATH')
if klp.startswith('"'):
klp = klp[1:-1]
kilosort_path = Path(klp)
if npy_matlab_path is None or npy_matlab_path == 'None':
npp = os.getenv('NPY_MATLAB_PATH')
if npp.startswith('"'):
npp = npp[1:-1]
npy_matlab_path = Path(npp)
if not (Path(kilosort_path) / 'preprocessData.m').is_file() \
or not (Path(npy_matlab_path) / 'npy-matlab' / 'readNPY.m').is_file():
raise ModuleNotFoundError(
"\nTo use KiloSort, install KiloSort and npy-matlab from sources: \n\n"
"\ngit clone https://github.com/cortex-lab/KiloSort\n"
"\ngit clone https://github.com/kwikteam/npy-matlab\n"
"and provide the installation path with the 'kilosort_path' and "
"'npy_matlab_path' arguments or by setting the KILOSORT_PATH and NPY_MATLAB_PATH"
"environment variables.\n+n"
"\nMore information on KiloSort at: "
"\nhttps://github.com/cortex-lab/KiloSort")
source_dir = Path(__file__).parent
if output_folder is None:
output_folder = Path('kilosort')
else:
output_folder = Path(output_folder)
if not output_folder.is_dir():
output_folder.mkdir()
output_folder = output_folder.absolute()
if probe_file is not None:
recording = se.loadProbeFile(recording, probe_file)
# save binary file
if file_name is None:
file_name = Path('recording')
elif file_name.suffix == '.dat':
file_name = file_name.stem
se.writeBinaryDatFormat(recording,
output_folder / file_name,
dtype='int16')
# set up kilosort config files and run kilosort on data
with (source_dir / 'kilosort_master.txt').open('r') as f:
kilosort_master = f.readlines()
with (source_dir / 'kilosort_config.txt').open('r') as f:
kilosort_config = f.readlines()
with (source_dir / 'kilosort_channelmap.txt').open('r') as f:
kilosort_channelmap = f.readlines()
nchan = recording.getNumChannels()
dat_file = (output_folder / (file_name.name + '.dat')).absolute()
kilo_thresh = detect_threshold
Nfilt = (nchan // 32) * 32 * 8
if Nfilt == 0:
Nfilt = nchan * 8
nsamples = 128 * 1024 + 64
if useGPU:
ug = 1
else:
ug = 0
abs_channel = (output_folder / 'kilosort_channelmap.m').absolute()
abs_config = (output_folder / 'kilosort_config.m').absolute()
kilosort_path = kilosort_path.absolute()
npy_matlab_path = npy_matlab_path.absolute() / 'npy-matlab'
kilosort_master = ''.join(kilosort_master).format(ug, kilosort_path,
npy_matlab_path,
output_folder,
abs_channel, abs_config)
kilosort_config = ''.join(kilosort_config).format(
nchan, nchan, recording.getSamplingFrequency(), dat_file, Nfilt,
nsamples, kilo_thresh)
if 'location' in recording.getChannelPropertyNames():
positions = np.array([
recording.getChannelProperty(chan, 'location')
for chan in recording.getChannelIds()
])
if electrode_dimensions is None:
kilosort_channelmap = ''.join(kilosort_channelmap).format(
nchan, list(positions[:, 0]), list(positions[:, 1]),
'ones(1, Nchannels)', recording.getSamplingFrequency())
elif len(electrode_dimensions) == 2:
kilosort_channelmap = ''.join(kilosort_channelmap).format(
nchan, list(positions[:, electrode_dimensions[0]]),
list(positions[:, electrode_dimensions[1]]),
'ones(1, Nchannels)', recording.getSamplingFrequency())
else:
raise Exception("Electrode dimension should bi a list of len 2")
else:
raise Exception(
"'location' information is needed. Provide a probe information with a 'probe_file'"
)
for fname, value in zip(
['kilosort_master.m', 'kilosort_config.m', 'kilosort_channelmap.m'],
[kilosort_master, kilosort_config, kilosort_channelmap]):
with (output_folder / fname).open('w') as f:
f.writelines(value)
# start sorting with kilosort
print('Running KiloSort')
cmd = "matlab -nosplash -nodisplay -r 'run {}; quit;'".format(
output_folder / 'kilosort_master.m')
print(cmd)
if sys.platform == "win":
cmd_list = [
'matlab', '-nosplash', '-nodisplay', '-wait', '-r',
'run {}; quit;'.format(output_folder / 'kilosort_master.m')
]
else:
cmd_list = [
'matlab', '-nosplash', '-nodisplay', '-r',
'run {}; quit;'.format(output_folder / 'kilosort_master.m')
]
retcode = _run_command_and_print_output_split(cmd_list)
if not (output_folder / 'spike_times.npy').is_file():
raise Exception('KiloSort did not run successfully')
sorting = se.KiloSortSortingExtractor(output_folder)
return sorting
