def test1(self):
"""Create clu and fet files based on spiketrains in a block.
Checks that
Files are created
Converted to samples correctly
Missing sampling rate are taken from IO reader default
Spiketrains without cluster info are assigned to cluster 0
Spiketrains across segments are concatenated
"""
block = neo.Block()
segment = neo.Segment()
segment2 = neo.Segment()
block.segments.append(segment)
block.segments.append(segment2)
# Fake spiketrain 1
st1 = neo.SpikeTrain(times=[.002, .004, .006], units='s', t_stop=1.)
st1.annotations['cluster'] = 0
st1.annotations['group'] = 0
wff = np.array([[11.3, 0.2], [-0.3, 12.3], [3.0, -2.5]])
st1.annotations['waveform_features'] = wff
segment.spiketrains.append(st1)
# Create empty directory for writing
if not os.path.exists(self.dirname):
os.mkdir(self.dirname)
delete_test_session(self.dirname)
# Create writer
kio = KlustaKwikIO(filename=os.path.join(self.dirname, 'base2'),
sampling_rate=1000.)
kio.write_block(block)
# Check files were created
for fn in ['.fet.0', '.clu.0']:
self.assertTrue(
os.path.exists(os.path.join(self.dirname, 'base2' + fn)))
# Check files contain correct content
fi = file(os.path.join(self.dirname, 'base2.fet.0'))
# first line is nbFeatures
self.assertEqual(fi.readline(), '2\n')
# Now check waveforms and times are same
data = fi.readlines()
new_wff = []
new_times = []
for line in data:
line_split = line.split()
new_wff.append([float(val) for val in line_split[:-1]])
new_times.append(int(line_split[-1]))
self.assertEqual(new_times, [2, 4, 6])
assert_arrays_almost_equal(wff, np.array(new_wff), .00001)
# Clusters on group 0
data = file(os.path.join(self.dirname, 'base2.clu.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, 0, 0, 0])
# Now read the features and test same
block = kio.read_block()
train = block.segments[0].spiketrains[0]
assert_arrays_almost_equal(wff, train.annotations['waveform_features'],
.00001)
# Empty out test session again
delete_test_session(self.dirname)
def test1(self):
"""Create clu and fet files based on spiketrains in a block.
Checks that
Files are created
Converted to samples correctly
Missing sampling rate are taken from IO reader default
Spiketrains without cluster info are assigned to cluster 0
Spiketrains across segments are concatenated
"""
block = neo.Block()
segment = neo.Segment()
segment2 = neo.Segment()
block.segments.append(segment)
block.segments.append(segment2)
# Fake spiketrain 1
st1 = neo.SpikeTrain(times=[.002, .004, .006], units='s', t_stop=1.)
st1.annotations['cluster'] = 0
st1.annotations['group'] = 0
wff = np.array([
[11.3, 0.2],
[-0.3, 12.3],
[3.0, -2.5]])
st1.annotations['waveform_features'] = wff
segment.spiketrains.append(st1)
# Create empty directory for writing
if not os.path.exists(self.dirname):
os.mkdir(self.dirname)
delete_test_session(self.dirname)
# Create writer
kio = KlustaKwikIO(filename=os.path.join(self.dirname, 'base2'),
sampling_rate=1000.)
kio.write_block(block)
# Check files were created
for fn in ['.fet.0', '.clu.0']:
self.assertTrue(os.path.exists(os.path.join(self.dirname,
'base2' + fn)))
# Check files contain correct content
fi = file(os.path.join(self.dirname, 'base2.fet.0'))
# first line is nbFeatures
self.assertEqual(fi.readline(), '2\n')
# Now check waveforms and times are same
data = fi.readlines()
new_wff = []
new_times = []
for line in data:
line_split = line.split()
new_wff.append([float(val) for val in line_split[:-1]])
new_times.append(int(line_split[-1]))
self.assertEqual(new_times, [2, 4, 6])
assert_arrays_almost_equal(wff, np.array(new_wff), .00001)
# Clusters on group 0
data = file(os.path.join(self.dirname, 'base2.clu.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, 0, 0, 0])
# Now read the features and test same
block = kio.read_block()
assert_arrays_almost_equal(wff,
block.segments[0].spiketrains[0].annotations['waveform_features'],
.00001)
# Empty out test session again
delete_test_session(self.dirname)
def test1(self):
"""Create clu and fet files based on spiketrains in a block.
Checks that
Files are created
Converted to samples correctly
Missing sampling rate are taken from IO reader default
Spiketrains without cluster info are assigned to cluster 0
Spiketrains across segments are concatenated
"""
block = neo.Block()
segment = neo.Segment()
segment2 = neo.Segment()
block.segments.append(segment)
block.segments.append(segment2)
# Fake spiketrain 1, will be sorted
st1 = neo.SpikeTrain(times=[.002, .004, .006], units='s', t_stop=1.)
st1.annotations['cluster'] = 0
st1.annotations['group'] = 0
segment.spiketrains.append(st1)
# Fake spiketrain 1B, on another segment. No group specified,
# default is 0.
st1B = neo.SpikeTrain(times=[.106], units='s', t_stop=1.)
st1B.annotations['cluster'] = 0
segment2.spiketrains.append(st1B)
# Fake spiketrain 2 on same group, no sampling rate specified
st2 = neo.SpikeTrain(times=[.001, .003, .011], units='s', t_stop=1.)
st2.annotations['cluster'] = 1
st2.annotations['group'] = 0
segment.spiketrains.append(st2)
# Fake spiketrain 3 on new group, with different sampling rate
st3 = neo.SpikeTrain(times=[.05, .09, .10], units='s', t_stop=1.)
st3.annotations['cluster'] = -1
st3.annotations['group'] = 1
segment.spiketrains.append(st3)
# Fake spiketrain 4 on new group, without cluster info
st4 = neo.SpikeTrain(times=[.005, .009], units='s', t_stop=1.)
st4.annotations['group'] = 2
segment.spiketrains.append(st4)
# Create empty directory for writing
delete_test_session()
# Create writer with default sampling rate
kio = KlustaKwikIO(filename=os.path.join(self.dirname, 'base1'),
sampling_rate=1000.)
kio.write_block(block)
# Check files were created
for fn in ['.fet.0', '.fet.1', '.clu.0', '.clu.1']:
self.assertTrue(
os.path.exists(os.path.join(self.dirname, 'base1' + fn)))
# Check files contain correct content
# Spike times on group 0
data = file(os.path.join(self.dirname, 'base1.fet.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 2, 4, 6, 1, 3, 11, 106])
# Clusters on group 0
data = file(os.path.join(self.dirname, 'base1.clu.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [2, 0, 0, 0, 1, 1, 1, 0])
# Spike times on group 1
data = file(os.path.join(self.dirname, 'base1.fet.1')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 50, 90, 100])
# Clusters on group 1
data = file(os.path.join(self.dirname, 'base1.clu.1')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, -1, -1, -1])
# Spike times on group 2
data = file(os.path.join(self.dirname, 'base1.fet.2')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 5, 9])
# Clusters on group 2
data = file(os.path.join(self.dirname, 'base1.clu.2')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, 0, 0])
# Empty out test session again
delete_test_session()
def test1(self):
"""Create clu and fet files based on spiketrains in a block.
Checks that
Files are created
Converted to samples correctly
Missing sampling rate are taken from IO reader default
Spiketrains without cluster info are assigned to cluster 0
Spiketrains across segments are concatenated
"""
block = neo.Block()
segment = neo.Segment()
segment2 = neo.Segment()
block.segments.append(segment)
block.segments.append(segment2)
# Fake spiketrain 1, will be sorted
st1 = neo.SpikeTrain(times=[.002, .004, .006], units='s', t_stop=1.)
st1.annotations['cluster'] = 0
st1.annotations['group'] = 0
segment.spiketrains.append(st1)
# Fake spiketrain 1B, on another segment. No group specified,
# default is 0.
st1B = neo.SpikeTrain(times=[.106], units='s', t_stop=1.)
st1B.annotations['cluster'] = 0
segment2.spiketrains.append(st1B)
# Fake spiketrain 2 on same group, no sampling rate specified
st2 = neo.SpikeTrain(times=[.001, .003, .011], units='s', t_stop=1.)
st2.annotations['cluster'] = 1
st2.annotations['group'] = 0
segment.spiketrains.append(st2)
# Fake spiketrain 3 on new group, with different sampling rate
st3 = neo.SpikeTrain(times=[.05, .09, .10], units='s', t_stop=1.)
st3.annotations['cluster'] = -1
st3.annotations['group'] = 1
segment.spiketrains.append(st3)
# Fake spiketrain 4 on new group, without cluster info
st4 = neo.SpikeTrain(times=[.005, .009], units='s', t_stop=1.)
st4.annotations['group'] = 2
segment.spiketrains.append(st4)
# Create empty directory for writing
delete_test_session()
# Create writer with default sampling rate
kio = KlustaKwikIO(filename=os.path.join(self.dirname, 'base1'),
sampling_rate=1000.)
kio.write_block(block)
# Check files were created
for fn in ['.fet.0', '.fet.1', '.clu.0', '.clu.1']:
self.assertTrue(os.path.exists(os.path.join(self.dirname,
'base1' + fn)))
# Check files contain correct content
# Spike times on group 0
data = file(os.path.join(self.dirname, 'base1.fet.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 2, 4, 6, 1, 3, 11, 106])
# Clusters on group 0
data = file(os.path.join(self.dirname, 'base1.clu.0')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [2, 0, 0, 0, 1, 1, 1, 0])
# Spike times on group 1
data = file(os.path.join(self.dirname, 'base1.fet.1')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 50, 90, 100])
# Clusters on group 1
data = file(os.path.join(self.dirname, 'base1.clu.1')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, -1, -1, -1])
# Spike times on group 2
data = file(os.path.join(self.dirname, 'base1.fet.2')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [0, 5, 9])
# Clusters on group 2
data = file(os.path.join(self.dirname, 'base1.clu.2')).readlines()
data = [int(d) for d in data]
self.assertEqual(data, [1, 0, 0])
# Empty out test session again
delete_test_session()
