def test_2_old():
import time
start = time.time()
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
# selecting only one session
base_events = base_events[base_events.eegfile == base_events[0].eegfile]
from ptsa.data.readers.TalReader import TalReader
tal_path = '/Users/m/data/eeg/R1060M/tal/R1060M_talLocs_database_bipol.mat'
tal_reader = TalReader(tal_filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
print 'bipolar_pairs=', bipolar_pairs
from ptsa.data.experimental.TimeSeriesEEGReader import TimeSeriesEEGReader
time_series_reader = TimeSeriesEEGReader(events=base_events, start_time=0.0,
end_time=1.6, buffer_time=1.0, keep_buffer=True)
base_eegs = time_series_reader.read(channels=monopolar_channels)
# base_eegs = base_eegs[:, 0:10, :]
# bipolar_pairs = bipolar_pairs[0:10]
wf = MorletWaveletFilter(time_series=base_eegs,
freqs=np.logspace(np.log10(3), np.log10(180), 2),
# freqs=np.array([3.]),
output='power',
# resamplerate=50.0
)
pow_wavelet, phase_wavelet = wf.filter()
print 'total time = ', time.time() - start
res_start = time.time()
# from ptsa.data.filters.ResampleFilter import ResampleFilter
# rsf = ResampleFilter (resamplerate=50.0)
# rsf.set_input(pow_wavelet)
# pow_wavelet = rsf.filter()
print 'resample_time=', time.time() - res_start
return pow_wavelet
def test_2():
import time
start = time.time()
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
# selecting only one session
base_events = base_events[base_events.eegfile == base_events[0].eegfile]
from ptsa.data.readers.TalReader import TalReader
tal_path = '/Users/m/data/eeg/R1060M/tal/R1060M_talLocs_database_bipol.mat'
tal_reader = TalReader(tal_filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
print 'bipolar_pairs=', bipolar_pairs
from ptsa.data.experimental.TimeSeriesEEGReader import TimeSeriesEEGReader
time_series_reader = TimeSeriesEEGReader(events=base_events,
start_time=0.0,
end_time=1.6,
buffer_time=1.0,
keep_buffer=True)
base_eegs = time_series_reader.read(channels=monopolar_channels)
# base_eegs = base_eegs[:, 0:10, :]
# bipolar_pairs = bipolar_pairs[0:10]
wf = MorletWaveletFilter(
time_series=base_eegs,
# bipolar_pairs=bipolar_pairs,
freqs=np.logspace(np.log10(3), np.log10(180), 2),
# freqs=np.array([3.]),
output='power',
# resamplerate=50.0
)
pow_wavelet, phase_wavelet = wf.filter()
print 'total time = ', time.time() - start
return pow_wavelet
def read_base_events(self):
base_e_reader = BaseEventReader(event_file=self.e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
base_ev_order = np.argsort(base_events,
order=('session', 'list', 'mstime'))
base_events = base_events[base_ev_order]
base_events = base_events[self.event_range]
return base_events
def read_base_events(self):
base_e_reader = BaseEventReader(event_file=self.e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
base_ev_order = np.argsort(base_events, order=('session','list','mstime'))
base_events = base_events[base_ev_order]
base_events = base_events[self.event_range]
return base_events
def test_1_old():
import time
start = time.time()
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
# selecting only one session
base_events = base_events[base_events.eegfile == base_events[0].eegfile]
from ptsa.data.readers.TalReader import TalReader
tal_path = '/Users/m/data/eeg/R1060M/tal/R1060M_talLocs_database_bipol.mat'
tal_reader = TalReader(tal_filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
print('bipolar_pairs=', bipolar_pairs)
from ptsa.data.experimental.TimeSeriesSessionEEGReader import TimeSeriesSessionEEGReader
# time_series_reader = TimeSeriesSessionEEGReader(events=base_events, channels = ['002', '003', '004', '005'])
time_series_reader = TimeSeriesSessionEEGReader(
events=base_events, channels=monopolar_channels)
ts_dict = time_series_reader.read()
first_session_data = list(ts_dict.items())[0][1]
print(first_session_data)
wavelet_start = time.time()
wf = MorletWaveletFilterSimple(
time_series=first_session_data,
freqs=np.logspace(np.log10(3), np.log10(180), 2),
# freqs=np.array([3.]),
output='power',
# resamplerate=50.0
)
pow_wavelet, phase_wavelet = wf.filter()
print('wavelet total time = ', time.time() - wavelet_start)
# return pow_wavelet
from ptsa.data.experimental.EventDataChopper import EventDataChopper
edcw = EventDataChopper(events=base_events,
event_duration=1.6,
buffer=1.0,
data_dict={base_events[0].eegfile: pow_wavelet})
chopped_wavelets = edcw.filter()
chopped_wavelets = list(chopped_wavelets.items())[0][
1] # getting first item of return dictionary
print('total time = ', time.time() - start)
#
# from ptsa.data.filters.ResampleFilter import ResampleFilter
# rsf = ResampleFilter (resamplerate=50.0)
# rsf.set_input(chopped_wavelets)
# chopped_wavelets_resampled = rsf.filter()
#
# return chopped_wavelets_resampled
return chopped_wavelets
def test_1_old():
import time
start = time.time()
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
# selecting only one session
base_events = base_events[base_events.eegfile == base_events[0].eegfile]
from ptsa.data.readers.TalReader import TalReader
tal_path = '/Users/m/data/eeg/R1060M/tal/R1060M_talLocs_database_bipol.mat'
tal_reader = TalReader(tal_filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
print 'bipolar_pairs=', bipolar_pairs
from ptsa.data.experimental.TimeSeriesSessionEEGReader import TimeSeriesSessionEEGReader
# time_series_reader = TimeSeriesSessionEEGReader(events=base_events, channels = ['002', '003', '004', '005'])
time_series_reader = TimeSeriesSessionEEGReader(events=base_events, channels=monopolar_channels)
ts_dict = time_series_reader.read()
first_session_data = ts_dict.items()[0][1]
print first_session_data
wavelet_start = time.time()
wf = MorletWaveletFilter(time_series=first_session_data,
freqs=np.logspace(np.log10(3), np.log10(180), 2),
# freqs=np.array([3.]),
output='power',
# resamplerate=50.0
)
pow_wavelet, phase_wavelet = wf.filter()
print 'wavelet total time = ', time.time() - wavelet_start
# return pow_wavelet
from ptsa.data.experimental.EventDataChopper import EventDataChopper
edcw = EventDataChopper(events=base_events, event_duration=1.6, buffer=1.0,
data_dict={base_events[0].eegfile: pow_wavelet})
chopped_wavelets = edcw.filter()
chopped_wavelets = chopped_wavelets.items()[0][1] # getting first item of return dictionary
print 'total time = ', time.time() - start
#
# from ptsa.data.filters.ResampleFilter import ResampleFilter
# rsf = ResampleFilter (resamplerate=50.0)
# rsf.set_input(chopped_wavelets)
# chopped_wavelets_resampled = rsf.filter()
#
# return chopped_wavelets_resampled
return chopped_wavelets
session_eegdata_dict[eegfile_name] = eegdata_xray
return session_eegdata_dict
if __name__ == "__main__":
event_range = range(0, 30, 1)
e_path = "/Users/m/data/events/RAM_FR1/R1060M_events.mat"
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == "WORD"]
from ptsa.data.experimental.TimeSeriesSessionEEGReader import TimeSeriesSessionEEGReader
time_series_reader = TimeSeriesSessionEEGReader(events=base_events, channels=["002", "003", "004", "005"])
# time_series_reader = TimeSeriesSessionEEGReader(events=base_events, event_data_only=True, channels=['002', '003', '004', '005']*20)
ts = time_series_reader.read()
print ts
# #
# # sys.exit()
# print ts
return eventdata_xray
if __name__ == '__main__':
event_range = range(0, 30, 1)
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
from ptsa.data.readers import BaseEventReader
base_e_reader = BaseEventReader(event_file=e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
# sorting names in the order in which they appear in the file
eegfile_names = np.unique(base_events.eegfile)
eeg_file_names_sorter = np.zeros(len(eegfile_names), dtype=np.int)
for i, eegfile_name in enumerate(eegfile_names):
eeg_file_names_sorter[i] = np.where(
base_events.eegfile == eegfile_name)[0][0]
eeg_file_names_sorter = np.argsort(eeg_file_names_sorter)
eegfile_names = eegfile_names[eeg_file_names_sorter]
def run(self):
# PTSA EVENT READER
# e_path = join(self.pipeline.mount_point, 'data/events', self.pipeline.task,self.pipeline.subject+'_events.mat')
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
# e_path = '/Users/m/data/events/RAM_FR1/R1056M_events.mat'
e_reader = PTSAEventReader(event_file=e_path, eliminate_events_with_no_eeg=True)
e_reader.read()
events = e_reader.get_output()
events = events[events.type == 'WORD']
events = events[0:30]
ev_order = np.argsort(events, order=('session','list','mstime'))
events = events[ev_order]
events = Events(events) # necessary workaround for new numpy
print 'events=',events
eegs= events.get_data(channels=['002','003'], start_time=0.0, end_time=1.6,
buffer_time=1.0, eoffset='eegoffset', keep_buffer=False, eoffset_in_time=False,verbose=True)
print eegs
# BASE READER
base_e_reader = BaseEventReader(event_file=e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
base_ev_order = np.argsort(base_events, order=('session','list','mstime'))
base_events = base_events[base_ev_order]
base_events = base_events[0:30]
print 'base_events=',base_events
from ptsa.data.readers.TimeSeriesEEGReader import TimeSeriesEEGReader
time_series_reader = TimeSeriesEEGReader(base_events)
time_series_reader.start_time = 0.0
time_series_reader.end_time = 1.6
time_series_reader.buffer_time = 1.0
time_series_reader.keep_buffer = False
time_series_reader.read(channels=['002','003'])
base_eegs = time_series_reader.get_output()
print
def run(self):
# PTSA EVENT READER
# e_path = join(self.pipeline.mount_point, 'data/events', self.pipeline.task,self.pipeline.subject+'_events.mat')
e_path = '/Users/m/data/events/RAM_FR1/R1060M_events.mat'
# e_path = '/Users/m/data/events/RAM_FR1/R1056M_events.mat'
e_reader = PTSAEventReader(event_file=e_path,
eliminate_events_with_no_eeg=True)
e_reader.read()
events = e_reader.get_output()
events = events[events.type == 'WORD']
events = events[0:30]
ev_order = np.argsort(events, order=('session', 'list', 'mstime'))
events = events[ev_order]
events = Events(events) # necessary workaround for new numpy
print 'events=', events
eegs = events.get_data(channels=['002', '003'],
start_time=0.0,
end_time=1.6,
buffer_time=1.0,
eoffset='eegoffset',
keep_buffer=False,
eoffset_in_time=False,
verbose=True)
print eegs
# BASE READER
base_e_reader = BaseEventReader(event_file=e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_e_reader.read()
base_events = base_e_reader.get_output()
base_events = base_events[base_events.type == 'WORD']
base_ev_order = np.argsort(base_events,
order=('session', 'list', 'mstime'))
base_events = base_events[base_ev_order]
base_events = base_events[0:30]
print 'base_events=', base_events
from ptsa.data.readers.TimeSeriesEEGReader import TimeSeriesEEGReader
time_series_reader = TimeSeriesEEGReader(base_events)
time_series_reader.start_time = 0.0
time_series_reader.end_time = 1.6
time_series_reader.buffer_time = 1.0
time_series_reader.keep_buffer = False
time_series_reader.read(channels=['002', '003'])
base_eegs = time_series_reader.get_output()
print
