def extract_rolling_median(self, seriesname="raw", window_size=128): """Extracts a rolling median for the specified series""" print "Extracting rolling median: name=%s window_size=%d" % (seriesname, window_size) new_feature_name = seriesname + "_rolling_median_" + str(window_size) self.series[new_feature_name] = rolling_windows.downsampled_rolling_median( self.series[seriesname], window_size=window_size )
except ImportError: print "Please create a dev_settings.py. Example: dev_settings.py.example" data = pd.read_table( join(SAVE_URL, 'raw', '20101214163931.a.rawwave_label.csv')) grouped = data.groupby(('taskid')) taskids = grouped.size().keys() ret = grouped.mean() # add new columns, to populate below ret['rolling_median'] = None ret['rolling_PSD'] = None for taskid in taskids: eeg_signal = grouped.get_group(taskid)[' Value'] # TODO remove space from name ret.set_value( taskid, 'rolling_median', rolling_windows.downsampled_rolling_median(eeg_signal, window_size=128)) window_size = 512 if len(eeg_signal) >= window_size: ret.set_value( taskid, 'rolling_PSD', rolling_windows.rolling_power_ratio(eeg_signal, window_size=512)) outfilename = 'features.pickle' ret.save(outfilename) print 'saved features as pickle in file "%s"' % outfilename
try: # Import config params from dev_settings import * except ImportError: print "Please create a dev_settings.py. Example: dev_settings.py.example" data = pd.read_table(join(SAVE_URL,'raw','20101214163931.a.rawwave_label.csv')) grouped = data.groupby(('taskid')) taskids = grouped.size().keys() ret = grouped.mean() # add new columns, to populate below ret['rolling_median'] = None ret['rolling_PSD'] = None for taskid in taskids: eeg_signal = grouped.get_group(taskid)[' Value'] # TODO remove space from name ret.set_value(taskid, 'rolling_median', rolling_windows.downsampled_rolling_median(eeg_signal, window_size=128)) window_size = 512 if len(eeg_signal) >= window_size: ret.set_value(taskid, 'rolling_PSD', rolling_windows.rolling_power_ratio(eeg_signal, window_size=512)) outfilename = 'features.pickle' ret.save(outfilename) print 'saved features as pickle in file "%s"' % outfilename