def _run_from_folder(cls, output_folder, params, verbose):
recording = load_extractor(output_folder / 'spikeinterface_recording.json')
assert isinstance(recording, BinaryRecordingExtractor)
assert recording.get_num_segments() == 1
dat_path = recording._kwargs['file_paths'][0]
print('dat_path', dat_path)
num_chans = recording.get_num_channels()
locations = recording.get_channel_locations()
print(locations)
print(type(locations))
# ks_probe is not probeinterface Probe at all
ks_probe = Bunch()
ks_probe.NchanTOT = num_chans
ks_probe.chanMap = np.arange(num_chans)
ks_probe.kcoords = np.ones(num_chans)
ks_probe.xc = locations[:, 0]
ks_probe.yc = locations[:, 1]
run(
dat_path,
params=params,
probe=ks_probe,
dir_path=output_folder,
n_channels=num_chans,
dtype=recording.get_dtype(),
sample_rate=recording.get_sampling_frequency(),
)
def import_matlab_chanmap(chanmap_matfile):
'''Load a MATLAB channel map file.
Parameters
----------
chanmap_matfile (str): MATLAB file containing probe information
Returns
-------
probe (pykilosort.Bunch):
Object containing probe information
'''
# read MAT file and extract relevant info
mat = loadmat(chanmap_matfile)
chanmap_zeroidx = mat['chanMap'].squeeze().astype(np.int64) - 1 # 0-indexed
xcoords = mat['xcoords'].squeeze().astype(np.float32)
ycoords = mat['ycoords'].squeeze().astype(np.float32)
# Create `probe` object
probe = Bunch()
probe.chanMap = chanmap_zeroidx
probe.xc = xcoords
probe.yc = ycoords
probe.NchanTOT = len(chanmap_zeroidx)
return probe
def run_spike_sorting_ibl(bin_file):
_logger = logging.getLogger("pykilosort")
START_TIME = datetime.datetime.now()
out_dir = Path("/datadisk/Data/spike_sorting/datasets").joinpath(
'_'.join(list(bin_file.parts[-6:-3]) + [bin_file.parts[-2]]))
out_dir.mkdir(exist_ok=True, parents=True)
add_default_handler(level='DEBUG')
add_default_handler(
level='DEBUG',
filename=out_dir.joinpath(f"{START_TIME.isoformat()}_kilosort.log"))
files_chmap = Path(
"/home/olivier/Documents/MATLAB/Kilosort2/configFiles/neuropixPhase3A_kilosortChanMap.mat"
)
matdata = Bunch(scipy.io.loadmat(files_chmap))
probe = Bunch()
probe.NchanTOT = 385
# WARNING: indexing mismatch with MATLAB hence the -1
probe.chanMap = (matdata.chanMap - 1).squeeze()
probe.xc = matdata.xcoords.squeeze()
probe.yc = matdata.ycoords.squeeze()
probe.kcoords = probe.yc * 0 + 1
try:
_logger.info(f"Starting KS, output in {out_dir}")
run(bin_file,
probe=probe,
dir_path=out_dir,
n_channels=385,
dtype=np.int16,
sample_rate=3e4)
except Exception as e:
_logger.exception("Error in the main loop")
[_logger.removeHandler(h) for h in _logger.handlers]
from pykilosort import Bunch, add_default_handler, run
from spikeextractors.extractors import bindatrecordingextractor as dat
from spikeforest2_utils import AutoRecordingExtractor, AutoSortingExtractor
dat_path = Path("test/test.bin").absolute()
dir_path = dat_path.parent
ka.set_config(fr="default_readonly")
recording_path = "sha1dir://c0879a26f92e4c876cd608ca79192a84d4382868.manual_franklab/tetrode_600s/sorter1_1"
recording = AutoRecordingExtractor(recording_path, download=True)
recording.write_to_binary_dat_format(str(dat_path))
n_channels = len(recording.get_channel_ids())
probe = Bunch()
probe.NchanTOT = n_channels
probe.chanMap = np.array(range(0, n_channels))
probe.kcoords = np.ones(n_channels)
probe.xc = recording.get_channel_locations()[:, 0]
probe.yc = recording.get_channel_locations()[:, 1]
add_default_handler(level="DEBUG")
params = {"nfilt_factor": 8, "AUCsplit": 0.85, "nskip": 5}
run(
dat_path,
params=params,
probe=probe,
dir_path=dir_path,
n_channels=probe.NchanTOT,
dtype=np.int16,
if not dat_path.is_file():
create_test_directory(test_dir)
dir_path = dat_path.parent
# Use spikeinterface to get a consistent interface to the recording
recording = dat.BinDatRecordingExtractor(dat_path,
sampling_frequency=3e4,
numchan=64,
dtype='int16')
n_channels = len(recording.get_channel_ids())
# Load the config into pykilosort2.
# This should be automatic in the future.
probe = Bunch()
probe.NchanTOT = n_channels
probe.chanMap = np.load(dir_path.as_posix() +
'/chanMap.npy').flatten().astype(int)
probe.kcoords = np.ones(n_channels)
probe.xc = np.load(dir_path.as_posix() + '/xc.npy').flatten()
probe.yc = np.load(dir_path.as_posix() + '/yc.npy').flatten()
add_default_handler(level="DEBUG")
#params = {
# "nfilt_factor": 8,
# "AUCsplit": 0.85,
# "nskip": 5
#}
params = None #{}
def run_example():