def __init__(self,
dirname,
use_cache=False,
cache_path='same_as_resource',
keep_original_times=False):
"""
Initialise IO instance
Parameters
----------
dirname : str
Directory containing data files
use_cache : bool, optional
Cache results of initial file scans for faster loading in subsequent runs.
Default: False
cache_path : str, optional
Folder path to use for cache files.
Default: 'same_as_resource'
keep_original_times : bool
Preserve original time stamps as in data files. By default datasets are
shifted to begin at t_start = 0*pq.second.
Default: False
"""
NeuralynxRawIO.__init__(self,
dirname=dirname,
use_cache=use_cache,
cache_path=cache_path,
keep_original_times=keep_original_times)
BaseFromRaw.__init__(self, dirname)
def test_single_file_mode(self):
"""
Tests reading of single files.
"""
# test single analog signal channel
fname = self.get_filename_path('Cheetah_v5.6.3/original_data/CSC1.ncs')
rawio = NeuralynxRawIO(filename=fname)
rawio.parse_header()
self.assertEqual(rawio._nb_segment, 2)
self.assertEqual(len(rawio.ncs_filenames), 1)
self.assertEqual(len(rawio.nev_filenames), 0)
sigHdrs = rawio.header['signal_channels']
self.assertEqual(sigHdrs.size, 1)
self.assertEqual(sigHdrs[0][0], 'CSC1')
self.assertEqual(sigHdrs[0][1], '58')
self.assertEqual(len(rawio.header['spike_channels']), 0)
self.assertEqual(len(rawio.header['event_channels']), 0)
# test one single electrode channel
fname = self.get_filename_path(
'Cheetah_v5.5.1/original_data/STet3a.nse')
rawio = NeuralynxRawIO(filename=fname)
rawio.parse_header()
self.assertEqual(rawio._nb_segment, 1)
self.assertEqual(len(rawio.ncs_filenames), 0)
self.assertEqual(len(rawio.nev_filenames), 0)
seHdrs = rawio.header['spike_channels']
self.assertEqual(len(seHdrs), 1)
self.assertEqual(seHdrs[0][0], 'chSTet3a#8#0')
self.assertEqual(seHdrs[0][1], '0')
self.assertEqual(len(rawio.header['signal_channels']), 0)
self.assertEqual(len(rawio.header['event_channels']), 0)
def test_exclude_filenames(self):
# exclude single ncs file from session
dname = self.get_local_path('neuralynx/Cheetah_v5.6.3/original_data/')
rawio = NeuralynxRawIO(dirname=dname, exclude_filename='CSC2.ncs')
rawio.parse_header()
self.assertEqual(rawio._nb_segment, 2)
self.assertEqual(len(rawio.ncs_filenames), 1)
self.assertEqual(len(rawio.nev_filenames), 1)
sigHdrs = rawio.header['signal_channels']
self.assertEqual(sigHdrs.size, 1)
self.assertEqual(sigHdrs[0][0], 'CSC1')
self.assertEqual(sigHdrs[0][1], '58')
self.assertEqual(len(rawio.header['spike_channels']), 8)
self.assertEqual(len(rawio.header['event_channels']), 2)
# exclude multiple files from session
rawio = NeuralynxRawIO(dirname=dname,
exclude_filename=['Events.nev', 'CSC2.ncs'])
rawio.parse_header()
self.assertEqual(rawio._nb_segment, 2)
self.assertEqual(len(rawio.ncs_filenames), 1)
self.assertEqual(len(rawio.nev_filenames), 0)
sigHdrs = rawio.header['signal_channels']
self.assertEqual(sigHdrs.size, 1)
self.assertEqual(sigHdrs[0][0], 'CSC1')
self.assertEqual(sigHdrs[0][1], '58')
self.assertEqual(len(rawio.header['spike_channels']), 8)
self.assertEqual(len(rawio.header['event_channels']), 0)
def __init__(self,
dirname='',
filename='',
use_cache=False,
cache_path='same_as_resource',
exclude_filename=None,
keep_original_times=False):
"""
Initialise IO instance
Parameters
----------
dirname : str
Directory containing data files
use_cache : bool, optional
Cache results of initial file scans for faster loading in subsequent runs.
Default: False
cache_path : str, optional
Folder path to use for cache files.
Default: 'same_as_resource'
exclude_filename: str or list
Filename or list of filenames to be excluded. Expects base filenames without
directory path.
keep_original_times : bool
Preserve original time stamps as in data files. By default datasets are
shifted to begin at t_start = 0*pq.second.
Default: False
"""
NeuralynxRawIO.__init__(self,
dirname=dirname,
filename=filename,
use_cache=use_cache,
cache_path=cache_path,
exclude_filename=exclude_filename,
keep_original_times=keep_original_times)
if self.rawmode == 'one-file':
BaseFromRaw.__init__(self, filename)
elif self.rawmode == 'one-dir':
BaseFromRaw.__init__(self, dirname)
def test_scan_ncs_files(self):
# Test BML style of Ncs files, similar to PRE4 but with fractional frequency
# in the header and fractional microsPerSamp, which is then rounded as appropriate
# in each record.
rawio = NeuralynxRawIO(self.get_filename_path('BML/original_data'))
rawio.parse_header()
# test values here from direct inspection of .ncs files
self.assertEqual(rawio._nb_segment, 1)
self.assertListEqual(rawio._timestamp_limits, [(0, 192000)])
self.assertEqual(rawio._sigs_length[0], 4608)
self.assertEqual(rawio._sigs_t_start[0], 0)
self.assertEqual(rawio._sigs_t_stop[0], 0.192)
self.assertEqual(len(rawio._sigs_memmaps), 1)
# Test Cheetah 4.0.2, which is PRE4 type with frequency in header and
# no microsPerSamp. Number of microseconds per sample in file is inverse of
# sampling frequency in header trucated to microseconds.
rawio = NeuralynxRawIO(
self.get_filename_path('Cheetah_v4.0.2/original_data'))
rawio.parse_header()
# test values here from direct inspection of .ncs files
self.assertEqual(rawio._nb_segment, 1)
self.assertListEqual(rawio._timestamp_limits, [(266982936, 267162136)])
self.assertEqual(rawio._sigs_length[0], 5120)
self.assertEqual(rawio._sigs_t_start[0], 266.982936)
self.assertEqual(rawio._sigs_t_stop[0], 267.162136)
self.assertEqual(len(rawio._sigs_memmaps), 1)
# Test Cheetah 5.5.1, which is DigitalLynxSX and has two blocks of records
# with a fairly large gap.
rawio = NeuralynxRawIO(
self.get_filename_path('Cheetah_v5.5.1/original_data'))
rawio.parse_header()
# test values here from direct inspection of .ncs files
self.assertEqual(rawio._nb_segment, 2)
self.assertListEqual(rawio._timestamp_limits,
[(26122557633, 26162525633),
(26366360633, 26379704633)])
self.assertListEqual(rawio._sigs_length, [1278976, 427008])
self.assertListEqual(rawio._sigs_t_stop, [26162.525633, 26379.704633])
self.assertListEqual(rawio._sigs_t_start, [26122.557633, 26366.360633])
self.assertEqual(len(rawio._sigs_memmaps),
2) # check only that there are 2 memmaps
# Test Cheetah 6.3.2, the incomplete_blocks test. This is a DigitalLynxSX with
# three blocks of records. Gaps are on the order of 60 microseconds or so.
rawio = NeuralynxRawIO(
self.get_filename_path('Cheetah_v6.3.2/incomplete_blocks'))
rawio.parse_header()
# test values here from direct inspection of .ncs file, except for 3rd block
# t_stop, which is extended due to events past the last block of ncs records.
self.assertEqual(rawio._nb_segment, 3)
self.assertListEqual(rawio._timestamp_limits,
[(8408806811, 8427831990),
(8427832053, 8487768498),
(8487768561, 8515816549)])
self.assertListEqual(rawio._sigs_length, [608806, 1917967, 897536])
self.assertListEqual(rawio._sigs_t_stop,
[8427.831990, 8487.768498, 8515.816549])
self.assertListEqual(rawio._sigs_t_start,
[8408.806811, 8427.832053, 8487.768561])
self.assertEqual(len(rawio._sigs_memmaps),
3) # check only that there are 3 memmaps