def test_read_block(self):
"""Read data in a certain time range into one block"""
dirname = self.get_filename_path('Cheetah_v5.6.3/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# There are two segments due to gap in recording
self.assertEqual(len(block.segments), 2)
for seg in block.segments:
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 2. * pq.kHz)
self.assertEqual(len(seg.spiketrains), 8)
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 8)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[0],
block.segments[0].spiketrains[0].shape[0])
# this is tetrode data, containing 32 samples per waveform
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[1], 4)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[-1], 32)
self.assertGreater(len(block.segments[0].events), 0)
self.assertEqual(len(block.channel_indexes[-1].units[0].spiketrains), 2)
block = nio.read_block(load_waveforms=True, units_group_mode='all-in-one')
self.assertEqual(len(block.channel_indexes[-1].units), 8)
block = nio.read_block(load_waveforms=True, units_group_mode='split-all')
self.assertEqual(len(block.channel_indexes[-1].units), 1) # 1 units by ChannelIndex
def test_read_block(self):
"""Read data in a certain time range into one block"""
dirname = self.get_filename_path('Cheetah_v5.5.1/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
self.assertEqual(len(block.segments), 2)
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32. * pq.kHz)
self.assertEqual(len(seg.spiketrains), 2)
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 2)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[0],
block.segments[0].spiketrains[0].shape[0])
self.assertGreater(len(block.segments[0].events), 0)
self.assertEqual(len(block.channel_indexes[-1].units[0].spiketrains), 2) # 2 segment
block = nio.read_block(load_waveforms=True, units_group_mode='all-in-one')
self.assertEqual(len(block.channel_indexes[-1].units), 2) # 2 units
block = nio.read_block(load_waveforms=True, units_group_mode='split-all')
self.assertEqual(len(block.channel_indexes[-1].units), 1) # 1 units by ChannelIndex
def test_read_block(self):
dirname = self.get_filename_path('Cheetah_v5.7.4/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 5)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32 * pq.kHz)
self.assertEqual(len(seg.spiketrains), 0) # no nse files available
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 0)
self.assertGreater(len(block.segments[0].events), 0)
block = nio.read_block(signal_group_mode='split-all')
self.assertEqual(len(block.channel_indexes), 5)
block = nio.read_block(signal_group_mode='group-by-same-units')
self.assertEqual(len(block.channel_indexes), 1)
def test_read_segment(self):
dirname = self.get_filename_path('Cheetah_v5.7.4/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
seg = nio.read_segment(time_slice=None)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 5)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32*pq.kHz)
self.assertEqual(len(seg.spiketrains), 0)
# Testing different parameter combinations
seg = nio.read_segment(lazy=True)
self.assertEqual(len(seg.analogsignals[0]), 0)
self.assertEqual(len(seg.spiketrains), 0)
seg = nio.read_segment(cascade=False)
self.assertEqual(len(seg.analogsignals), 0)
self.assertEqual(len(seg.spiketrains), 0)
seg = nio.read_segment(load_waveforms=True)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(len(seg.spiketrains), 0)
self.assertTrue(len(seg.events) > 0)
def test_gap_handling_v563(self):
dirname = self.get_filename_path('Cheetah_v5.6.3/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# known gap values
n_gaps = 1
# so 2 segments, 2 anasigs by Channelindex, 2 SpikeTrain by Units
self.assertEqual(len(block.segments), n_gaps + 1)
self.assertEqual(len(block.channel_indexes[0].analogsignals), n_gaps + 1)
self.assertEqual(len(block.channel_indexes[-1].units[0].spiketrains), n_gaps + 1)
def test_ncs(self):
for session in self.files_to_test[1:2]: # in the long run this should include all files
dirname = self.get_filename_path(session)
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
for anasig_id, anasig in enumerate(block.segments[0].analogsignals):
chid = anasig.channel_index.annotations['channel_id'][anasig_id]
filename = nio.ncs_filenames[chid][:-3] + 'txt'
filename = filename.replace('original_data', 'plain_data')
plain_data = np.loadtxt(filename)[:, 5:].flatten() # first columns are meta info
overlap = 512 * 500
gain_factor_0 = plain_data[0] / anasig.magnitude[0, 0]
np.testing.assert_allclose(plain_data[:overlap],
anasig.magnitude[:overlap, 0] * gain_factor_0,
rtol=0.01)
def compare_old_and_new_neuralynxio():
base = '/tmp/files_for_testing_neo/neuralynx/'
dirname = base+'Cheetah_v5.5.1/original_data/'
#~ dirname = base+'Cheetah_v5.7.4/original_data/'
t0 = time.perf_counter()
newreader = NewNeuralynxIO(dirname)
t1 = time.perf_counter()
bl1 = newreader.read_block(load_waveforms=True)
t2 = time.perf_counter()
print('newreader header', t1-t0, 's')
print('newreader data', t2-t1, 's')
print('newreader toal', t2-t0, 's')
for seg in bl1.segments:
print('seg', seg.index)
for anasig in seg.analogsignals:
print(' AnalogSignal', anasig.name, anasig.shape, anasig.t_start)
for st in seg.spiketrains:
print(' SpikeTrain', st.name, st.shape, st.waveforms.shape, st[:5])
for ev in seg.events:
print(' Event', ev.name, ev.times.shape)
print('*'*10)
t0 = time.perf_counter()
oldreader = OldNeuralynxIO(sessiondir=dirname, use_cache='never')
t1 = time.perf_counter()
bl2 = oldreader.read_block(waveforms=True, events=True)
t2 = time.perf_counter()
print('oldreader header', t1-t0, 's')
print('oldreader data', t2-t1, 's')
print('oldreader toal', t2-t0, 's')
for seg in bl2.segments:
print('seg', seg.index)
for anasig in seg.analogsignals:
print(' AnalogSignal', anasig.name, anasig.shape, anasig.t_start)
for st in seg.spiketrains:
print(' SpikeTrain', st.name, st.shape, st.waveforms.shape, st[:5])
for ev in seg.events:
print(' Event', ev.name, ev.times.shape)
print('*' * 10)
compare_neo_content(bl1, bl2)
def test_read_segment(self):
dirname = self.get_filename_path('Cheetah_v5.5.1/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
# read first segment entirely
seg = nio.read_segment(seg_index=0, time_slice=None)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32 * pq.kHz)
self.assertEqual(len(seg.spiketrains), 2)
# Testing different parameter combinations
seg = nio.read_segment(seg_index=0, load_waveforms=True)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(len(seg.spiketrains), 2)
self.assertTrue(len(seg.spiketrains[0].waveforms) > 0)
self.assertTrue(len(seg.events) > 0)
def test_read_block(self):
"""Read data in a certain time range into one block"""
dirname = self.get_filename_path('Cheetah_v5.5.1/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
self.assertEqual(len(block.segments), 2)
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32. * pq.kHz)
self.assertEqual(len(seg.spiketrains), 2)
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 2)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[0],
block.segments[0].spiketrains[0].shape[0])
self.assertGreater(len(block.segments[0].events), 0)
self.assertEqual(len(block.channel_indexes[-1].units[0].spiketrains),
2) # 2 segment
block = nio.read_block(load_waveforms=True,
units_group_mode='all-in-one')
self.assertEqual(len(block.channel_indexes[-1].units), 2) # 2 units
block = nio.read_block(load_waveforms=True,
units_group_mode='split-all')
self.assertEqual(len(block.channel_indexes[-1].units),
1) # 1 units by ChannelIndex
def test_read_block(self):
dirname = self.get_filename_path('Cheetah_v5.7.4/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 5)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32 * pq.kHz)
self.assertEqual(len(seg.spiketrains), 0) # no nse files available
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 0)
self.assertGreater(len(block.segments[0].events), 0)
block = nio.read_block(signal_group_mode='split-all')
self.assertEqual(len(block.channel_indexes), 5)
block = nio.read_block(signal_group_mode='group-by-same-units')
self.assertEqual(len(block.channel_indexes), 1)
def test_keep_original_spike_times(self):
for session in self.files_to_test:
dirname = self.get_filename_path(session)
nio = NeuralynxIO(dirname=dirname, keep_original_times=True)
block = nio.read_block()
for st in block.segments[0].spiketrains:
filename = st.file_origin.replace('original_data', 'plain_data')
if '.nse' in st.file_origin:
filename = filename.replace('.nse', '.txt')
times_column = 0
plain_data = np.loadtxt(filename)[:, times_column]
elif '.ntt' in st.file_origin:
filename = filename.replace('.ntt', '.txt')
times_column = 2
plain_data = np.loadtxt(filename)[:, times_column]
# ntt files contain 4 rows per spike time
plain_data = plain_data[::4]
times = st.rescale(pq.microsecond).magnitude
overlap = min(len(plain_data), len(times))
np.testing.assert_allclose(plain_data[:overlap], times[:overlap], rtol=1e-10)
def test_ncs(self):
for session in self.files_to_test[
1:2]: # in the long run this should include all files
dirname = self.get_filename_path(session)
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
for anasig_id, anasig in enumerate(
block.segments[0].analogsignals):
chid = anasig.channel_index.channel_ids[anasig_id]
chname = anasig.channel_index.channel_names[anasig_id].decode(
'UTF-8') # need to decode, unless keyerror
chuid = (chname, chid)
filename = nio.ncs_filenames[chuid][:-3] + 'txt'
filename = filename.replace('original_data', 'plain_data')
plain_data = np.loadtxt(
filename)[:, 5:].flatten() # first columns are meta info
overlap = 512 * 500
gain_factor_0 = plain_data[0] / anasig.magnitude[0, 0]
np.testing.assert_allclose(plain_data[:overlap],
anasig.magnitude[:overlap, 0] *
gain_factor_0,
rtol=0.01)
def test_read_block(self):
"""Read data in a certain time range into one block"""
dirname = self.get_local_path('neuralynx/Cheetah_v5.5.1/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
self.assertEqual(len(block.segments), 2)
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32. * pq.kHz)
self.assertEqual(len(seg.spiketrains), 2)
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 2)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[0],
block.segments[0].spiketrains[0].shape[0])
self.assertGreater(len(block.segments[0].events), 0)
def test_read_segment(self):
dirname = self.get_filename_path('Cheetah_v5.7.4/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
seg = nio.read_segment(time_slice=None)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 5)
self.assertEqual(seg.analogsignals[0].sampling_rate, 32 * pq.kHz)
self.assertEqual(len(seg.spiketrains), 0)
# Testing different parameter combinations
seg = nio.read_segment(lazy=True)
self.assertEqual(len(seg.analogsignals[0]), 0)
self.assertEqual(len(seg.spiketrains), 0)
seg = nio.read_segment(load_waveforms=True)
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(len(seg.spiketrains), 0)
self.assertTrue(len(seg.events) > 0)
def test_read_block(self):
"""Read data in a certain time range into one block"""
dirname = self.get_filename_path('Cheetah_v5.6.3/original_data')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# There are two segments due to gap in recording
self.assertEqual(len(block.segments), 2)
for seg in block.segments:
self.assertEqual(len(seg.analogsignals), 1)
self.assertEqual(seg.analogsignals[0].shape[-1], 2)
self.assertEqual(seg.analogsignals[0].sampling_rate, 2. * pq.kHz)
self.assertEqual(len(seg.spiketrains), 8)
# Testing different parameter combinations
block = nio.read_block(lazy=True)
self.assertEqual(len(block.segments[0].analogsignals[0]), 0)
self.assertEqual(len(block.segments[0].spiketrains[0]), 0)
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].analogsignals), 1)
self.assertEqual(len(block.segments[0].spiketrains), 8)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[0],
block.segments[0].spiketrains[0].shape[0])
# this is tetrode data, containing 32 samples per waveform
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[1],
4)
self.assertEqual(block.segments[0].spiketrains[0].waveforms.shape[-1],
32)
self.assertGreater(len(block.segments[0].events), 0)
self.assertEqual(len(block.channel_indexes[-1].units[0].spiketrains),
2)
block = nio.read_block(load_waveforms=True,
units_group_mode='all-in-one')
self.assertEqual(len(block.channel_indexes[-1].units), 8)
block = nio.read_block(load_waveforms=True,
units_group_mode='split-all')
self.assertEqual(len(block.channel_indexes[-1].units),
1) # 1 units by ChannelIndex
def test_read_block(self):
dirname = self.get_local_path('neuralynx/Pegasus_v2.1.1')
nio = NeuralynxIO(dirname=dirname, use_cache=False)
block = nio.read_block()
# Everything put in one segment
seg = block.segments[0]
self.assertEqual(len(seg.analogsignals), 0) # no ncs file available
self.assertGreater(len(block.segments[0].events),
1) # single nev file available
self.assertEqual(len(seg.spiketrains), 0) # no nse files available
# Testing different parameter combinations
block = nio.read_block(load_waveforms=True)
self.assertEqual(len(block.segments[0].spiketrains), 0)
self.assertGreater(len(block.segments[0].events), 1)
block = nio.read_block(signal_group_mode='split-all')
block = nio.read_block(signal_group_mode='group-by-same-units')
def test_exclude_filename(self):
dname = self.get_local_path('neuralynx/Cheetah_v5.7.4/original_data/')
# exclude a single file
nio = NeuralynxIO(dirname=dname,
exclude_filename='CSC1.ncs',
use_cache=False)
block = nio.read_block()
self.assertTrue(len(block.segments[0].analogsignals) > 0)
self.assertTrue((len(block.segments[0].spiketrains)) >= 0)
self.assertTrue((len(block.segments[0].events)) >= 0)
self.assertTrue((len(block.segments[0].epochs)) == 0)
# exclude all ncs files from session
exclude_files = [f'CSC{i}.ncs' for i in range(6)]
nio = NeuralynxIO(dirname=dname,
exclude_filename=exclude_files,
use_cache=False)
block = nio.read_block()
self.assertTrue(len(block.segments[0].analogsignals) == 0)
self.assertTrue((len(block.segments[0].spiketrains)) >= 0)
self.assertTrue((len(block.segments[0].events)) >= 0)
self.assertTrue((len(block.segments[0].epochs)) == 0)
def test_header_read(self):
dirname = '/tmp/ncsTestData/Cheetah_v5.3.1_digital'
nio = NeuralynxIO(dirname=dirname, use_cache=False)
