def open_klusters_oneshank(filename):
filenames = find_filenames(filename)
fileindex = find_index(filename)
# Open small Klusters files.
data = {}
metadata = read_xml(filenames['xml'], fileindex)
data['clu'] = read_clusters(filenames['clu'])
# Read .aclu data.
if 'aclu' in filenames and os.path.exists(filenames['aclu']):
data['aclu'] = read_clusters(filenames['aclu'])
else:
data['aclu'] = data['clu']
# Read .acluinfo data.
if 'acluinfo' in filenames and os.path.exists(filenames['acluinfo']):
data['acluinfo'] = read_cluster_info(filenames['acluinfo'])
# If the ACLUINFO does not exist, try CLUINFO (older file extension)
elif 'cluinfo' in filenames and os.path.exists(filenames['cluinfo']):
data['acluinfo'] = read_cluster_info(filenames['cluinfo'])
else:
data['acluinfo'] = default_cluster_info(np.unique(data['aclu']))
# Read group info.
if 'groupinfo' in filenames and os.path.exists(filenames['groupinfo']):
data['groupinfo'] = read_group_info(filenames['groupinfo'])
else:
data['groupinfo'] = default_group_info()
# Find out the number of columns in the .fet file.
with open(filenames['fet'], 'r') as f:
f.readline()
# Get the number of non-empty columns in the .fet file.
data['fetcol'] = len(
[col for col in f.readline().split(' ') if col.strip() != ''])
metadata['nspikes'] = len(data['clu'])
data['fileindex'] = fileindex
# Open big Klusters files.
data['fet'] = MemMappedText(filenames['fet'], np.int64, skiprows=1)
if 'spk' in filenames and os.path.exists(filenames['spk'] or ''):
data['spk'] = MemMappedBinary(filenames['spk'],
np.int16,
rowsize=metadata['nchannels'] *
metadata['nsamples'])
if 'uspk' in filenames and os.path.exists(filenames['uspk'] or ''):
data['uspk'] = MemMappedBinary(filenames['uspk'],
np.int16,
rowsize=metadata['nchannels'] *
metadata['nsamples'])
if 'mask' in filenames and os.path.exists(filenames['mask'] or ''):
data['mask'] = MemMappedText(filenames['mask'], np.float32, skiprows=1)
# data['metadata'] = metadata
data.update(metadata)
return data
def open_klusters_oneshank(filename):
filenames = find_filenames(filename)
fileindex = find_index(filename)
# Open small Klusters files.
data = {}
metadata = read_xml(filenames['xml'], fileindex)
data['clu'] = read_clusters(filenames['clu'])
# Read .aclu data.
if 'aclu' in filenames and os.path.exists(filenames['aclu']):
data['aclu'] = read_clusters(filenames['aclu'])
else:
data['aclu'] = data['clu']
# Read .acluinfo data.
if 'acluinfo' in filenames and os.path.exists(filenames['acluinfo']):
data['acluinfo'] = read_cluster_info(filenames['acluinfo'])
# If the ACLUINFO does not exist, try CLUINFO (older file extension)
elif 'cluinfo' in filenames and os.path.exists(filenames['cluinfo']):
data['acluinfo'] = read_cluster_info(filenames['cluinfo'])
else:
data['acluinfo'] = default_cluster_info(np.unique(data['aclu']))
# Read group info.
if 'groupinfo' in filenames and os.path.exists(filenames['groupinfo']):
data['groupinfo'] = read_group_info(filenames['groupinfo'])
else:
data['groupinfo'] = default_group_info()
# Find out the number of columns in the .fet file.
with open(filenames['fet'], 'r') as f:
f.readline()
# Get the number of non-empty columns in the .fet file.
data['fetcol'] = len([col for col in f.readline().split(' ') if col.strip() != ''])
metadata['nspikes'] = len(data['clu'])
data['fileindex'] = fileindex
# Open big Klusters files.
data['fet'] = MemMappedText(filenames['fet'], np.int64, skiprows=1)
if 'spk' in filenames and os.path.exists(filenames['spk'] or ''):
data['spk'] = MemMappedBinary(filenames['spk'], np.int16,
rowsize=metadata['nchannels'] * metadata['nsamples'])
if 'uspk' in filenames and os.path.exists(filenames['uspk'] or ''):
data['uspk'] = MemMappedBinary(filenames['uspk'], np.int16,
rowsize=metadata['nchannels'] * metadata['nsamples'])
if 'mask' in filenames and os.path.exists(filenames['mask'] or ''):
data['mask'] = MemMappedText(filenames['mask'], np.float32, skiprows=1)
# data['metadata'] = metadata
data.update(metadata)
return data
def read_group_info(self):
try:
self.group_info = read_group_info(self.filename_groupinfo)
info("Successfully loaded {0:s}".format(self.filename_groupinfo))
except IOError:
info("The GROUPINFO file is missing, generating a default one.")
self.group_info = default_group_info()
# Convert to Pandas.
self.group_colors = self.group_info['color'].astype(np.int32)
self.group_names = self.group_info['name']
def read_group_info(self):
try:
self.group_info = read_group_info(self.filename_groupinfo)
info("Successfully loaded {0:s}".format(self.filename_groupinfo))
except IOError:
info("The GROUPINFO file is missing, generating a default one.")
self.group_info = default_group_info()
# Convert to Pandas.
self.group_colors = self.group_info['color'].astype(np.int32)
self.group_names = self.group_info['name']