def test_1():
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(filename=e_path,
eliminate_events_with_no_eeg=True,
use_ptsa_events_class=False)
base_events = base_e_reader.read()
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(filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
dataroot = base_events[0].eegfile
from ptsa.data.readers import EEGReader
session_reader = EEGReader(session_dataroot=dataroot,
channels=monopolar_channels)
session_eegs = session_reader.read()
wavelet_start = time.time()
wf = MorletWaveletFilterSimple(
time_series=session_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('wavelet total time = ', time.time() - wavelet_start)
# return pow_wavelet
from ptsa.data.filters import EventDataChopper
sedc = EventDataChopper(events=base_events,
session_data=pow_wavelet,
start_time=0.0,
end_time=1.6,
buffer_time=1.0)
chopped_wavelets = sedc.filter()
print('total time = ', time.time() - start)
return chopped_wavelets
def test_1():
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(filename=e_path, eliminate_events_with_no_eeg=True, use_ptsa_events_class=False)
base_events = base_e_reader.read()
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(filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
bipolar_pairs = tal_reader.get_bipolar_pairs()
dataroot = base_events[0].eegfile
from ptsa.data.readers import EEGReader
session_reader = EEGReader(session_dataroot=dataroot, channels=monopolar_channels)
session_eegs = session_reader.read()
wavelet_start = time.time()
wf = MorletWaveletFilterSimple(
time_series=session_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 "wavelet total time = ", time.time() - wavelet_start
# return pow_wavelet
from ptsa.data.filters import EventDataChopper
sedc = EventDataChopper(events=base_events, session_data=pow_wavelet, start_time=0.0, end_time=1.6, buffer_time=1.0)
chopped_wavelets = sedc.filter()
print "total time = ", time.time() - start
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 = 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
tal_path = '/Users/m/data/eeg/R1060M/tal/R1060M_talLocs_database_bipol.mat'
tal_reader = TalReader(filename=tal_path)
monopolar_channels = tal_reader.get_monopolar_channels()
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()
print ts_dict
from ptsa.data.experimental.EventDataChopper import EventDataChopper
edc = EventDataChopper(events=base_events, event_duration=1.6, buffer=1.0, data_dict=ts_dict)
ev_data_dict = edc.filter()
print ev_data_dict
# from ptsa.data.filters.EventDataChopper import EventDataChopper
#
# edc = EventDataChopper(events=base_events, event_duration=1.6,buffer=1.0,session_data_dict=ts_dict)
# ev_data_dict = edc.filter()
# print ev_data_dict
# wavelets
freqs = np.logspace(np.log10(3), np.log10(180), 12)
for session_file, ev_data in ev_data_dict.items():
break
