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
