def test_wavelets_with_event_data_chopper(self):
wf_session = MorletWaveletFilter(
time_series=self.session_eegs[:, :, :self.session_eegs.shape[2] / 4],
freqs=np.logspace(np.log10(3), np.log10(180), 8),
output='power',
frequency_dim_pos=0,
verbose=True
)
pow_wavelet_session, phase_wavelet_session = wf_session.filter()
sedc = DataChopper(events=self.base_events, session_data=pow_wavelet_session, start_time=self.start_time,
end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session_pow_wavelet = sedc.filter()
# removing buffer
chopped_session_pow_wavelet = chopped_session_pow_wavelet[:, :, :, 500:-500]
wf = MorletWaveletFilter(time_series=self.base_eegs,
freqs=np.logspace(np.log10(3), np.log10(180), 8),
output='power',
frequency_dim_pos=0,
verbose=True
)
pow_wavelet, phase_wavelet = wf.filter()
pow_wavelet = pow_wavelet[:, :, :, 500:-500]
assert_array_almost_equal(
(chopped_session_pow_wavelet.data - pow_wavelet.data) / pow_wavelet.data,
np.zeros_like(pow_wavelet),
decimal=5
)
def test_wavelets_with_event_data_chopper(self):
wf_session = MorletWaveletFilter(
time_series=self.session_eegs[:, :, :self.session_eegs.shape[2] / 4],
freqs=np.logspace(np.log10(3), np.log10(180), 8),
output='power',
frequency_dim_pos=0,
verbose=True
)
pow_wavelet_session, phase_wavelet_session = wf_session.filter()
sedc = DataChopper(events=self.base_events, session_data=pow_wavelet_session, start_time=self.start_time,
end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session_pow_wavelet = sedc.filter()
# removing buffer
chopped_session_pow_wavelet = chopped_session_pow_wavelet[:, :, :, 500:-500]
wf = MorletWaveletFilter(time_series=self.base_eegs,
freqs=np.logspace(np.log10(3), np.log10(180), 8),
output='power',
frequency_dim_pos=0,
verbose=True
)
pow_wavelet, phase_wavelet = wf.filter()
pow_wavelet = pow_wavelet[:, :, :, 500:-500]
assert_array_almost_equal(
(chopped_session_pow_wavelet.data - pow_wavelet.data) / pow_wavelet.data,
np.zeros_like(pow_wavelet),
decimal=5
)
def test_event_data_chopper(self):
dataroot = self.base_events[0].eegfile
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
sedc = DataChopper(events=self.base_events, session_data=session_eegs,
start_time=self.start_time, end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session = sedc.filter()
assert_array_equal(chopped_session, self.base_eegs)
sedc = DataChopper(start_offsets=self.base_events.eegoffset, session_data=session_eegs,
start_time=self.start_time, end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session = sedc.filter()
assert_array_equal(chopped_session, self.base_eegs)
def test_event_data_chopper(self):
dataroot=self.base_events[0].eegfile
from ptsa.data.readers import EEGReader
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
sedc = DataChopper(events=self.base_events, session_data=session_eegs, start_time=0.0, end_time=1.6, buffer_time=1.0)
chopped_session = sedc.filter()
sedc_so = DataChopper(start_offsets=self.base_events.eegoffset, session_data=session_eegs, start_time=0.0, end_time=1.6, buffer_time=1.0)
chopped_session_so = sedc_so.filter()
assert_array_equal(chopped_session,chopped_session_so)
def test_monopolar_to_bipolar_filter_and_data_chopper(self):
dataroot = self.base_events[0].eegfile
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
m2b = MonopolarToBipolarMapper(time_series=session_eegs, bipolar_pairs=self.bipolar_pairs)
bp_session_eegs = m2b.filter()
sedc = DataChopper(events=self.base_events, session_data=bp_session_eegs, start_time=self.start_time,
end_time=self.end_time, buffer_time=self.buffer_time)
bp_session_eegs_chopped = sedc.filter()
m2b = MonopolarToBipolarMapper(time_series=self.base_eegs, bipolar_pairs=self.bipolar_pairs)
bp_base_eegs = m2b.filter()
assert_array_equal(bp_session_eegs_chopped, bp_base_eegs)
def test_monopolar_to_bipolar_filter_and_data_chopper(self):
dataroot = self.base_events[0].eegfile
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
m2b = MonopolarToBipolarMapper(time_series=session_eegs, bipolar_pairs=self.bipolar_pairs)
bp_session_eegs = m2b.filter()
sedc = DataChopper(events=self.base_events, session_data=bp_session_eegs, start_time=self.start_time,
end_time=self.end_time, buffer_time=self.buffer_time)
bp_session_eegs_chopped = sedc.filter()
m2b = MonopolarToBipolarMapper(time_series=self.base_eegs, bipolar_pairs=self.bipolar_pairs)
bp_base_eegs = m2b.filter()
assert_array_equal(bp_session_eegs_chopped, bp_base_eegs)
def test_event_data_chopper(self):
dataroot=self.base_events[0].eegfile
from ptsa.data.readers import EEGReader
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
sedc = DataChopper(events=self.base_events, session_data=session_eegs, start_time=0.0, end_time=1.6, buffer_time=1.0)
chopped_session = sedc.filter()
sedc_so = DataChopper(start_offsets=self.base_events.eegoffset, session_data=session_eegs, start_time=0.0, end_time=1.6, buffer_time=1.0)
chopped_session_so = sedc_so.filter()
assert_array_equal(chopped_session,chopped_session_so)
def test_event_data_chopper(self):
dataroot = self.base_events[0].eegfile
session_reader = EEGReader(session_dataroot=dataroot, channels=self.monopolar_channels)
session_eegs = session_reader.read()
sedc = DataChopper(events=self.base_events, session_data=session_eegs,
start_time=self.start_time, end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session = sedc.filter()
assert_array_equal(chopped_session, self.base_eegs)
sedc = DataChopper(start_offsets=self.base_events.eegoffset, session_data=session_eegs,
start_time=self.start_time, end_time=self.end_time, buffer_time=self.buffer_time)
chopped_session = sedc.filter()
assert_array_equal(chopped_session, self.base_eegs)
def chop_time_series(time_series, start_offsets):
dc = DataChopper(start_offsets=start_offsets, session_data=time_series, start_time=start_time, end_time=end_time)
chopped_time_series = dc.filter()
return chopped_time_series
