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
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'] base_ev_order = np.argsort(base_events, order=('session','list','mstime')) base_events = base_events[base_ev_order] base_events = base_events[event_range] ##################### from ptsa.data.experimental.TimeSeriesSessionEEGReader import TimeSeriesSessionEEGReader time_series_session_reader = TimeSeriesSessionEEGReader(events=base_events, channels=np.array(['003', '004', '005'])) ts_dict = time_series_session_reader.read() print ts_dict ts=ts_dict.items()[0][1] resample_filter_rounded = ResampleFilter(time_series=ts, resamplerate=50.0,round_to_original_timepoints=True) # resample_filter_rounded = ResampleFilter(time_series=ts, resamplerate=50.0) base_eegs_resampled_rounded = resample_filter_rounded.filter() ###################################### 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)
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 # # for eegfile_name, eeg_session_data in ts.items(): # base_events_0 = base_events[base_events.eegfile == eegfile_name] # break # # print base_events_0
base_e_reader = BaseEventReader(filename=e_path, eliminate_events_with_no_eeg=True) base_events = base_e_reader.read() base_events = base_events[base_events.type == 'WORD'] 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() 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()
use_ptsa_events_class=False) base_events = base_e_reader.read() 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[event_range] ##################### from ptsa.data.experimental.TimeSeriesSessionEEGReader import TimeSeriesSessionEEGReader time_series_session_reader = TimeSeriesSessionEEGReader( events=base_events, channels=np.array(['003', '004', '005'])) ts_dict = time_series_session_reader.read() print ts_dict ts = ts_dict.items()[0][1] resample_filter_rounded = ResampleFilter(time_series=ts, resamplerate=50.0, round_to_original_timepoints=True) # resample_filter_rounded = ResampleFilter(time_series=ts, resamplerate=50.0) base_eegs_resampled_rounded = resample_filter_rounded.filter() ###################################### from ptsa.data.experimental.TimeSeriesEEGReader import TimeSeriesEEGReader