if crop_plot_time is not None:
epochs.crop(*crop_plot_time)
epochs.plot_image(pick, fig=imgfig)
# mnefig[0].get_axes()[1].set_title('')
stats = dict()
stats['mean'] = np.mean(delays)
stats['std'] = np.std(delays)
stats['median'] = np.median(delays)
stats['q10'] = np.percentile(delays, 10.)
stats['q90'] = np.percentile(delays, 90.)
stats['max_amp'] = np.max(epochs._data[:, pick, :]) # ovr epochs & times
stats['min_amp'] = np.min(epochs._data[:, pick, :]) # ovr epochs & times
return (delays, stats)
if __name__ == '__main__':
from stormdb.access import Query
proj_name = 'MEG_service'
subj_id = '0032'
qy = Query(proj_name)
series = qy.filter_series('audvis*', subjects=subj_id)
cur_series = series[0]
delays = extract_delays(cur_series,
stim_chan='STI101',
misc_chan='MISC001',
trig_codes=[2],
plot_figures=True)
from stormdb.access import Query
from stormdb.process import Maxfilter
from os.path import join
from os import makedirs
proj_name = 'MINDLAB2018_MEG-SF-Integration-Images'
mf_out_path = join('/projects', proj_name, 'scratch', 'maxfiltered')
log_out_path = join('/projects', proj_name, 'scratch', 'maxfiltered', 'logs')
makedirs(log_out_path, exist_ok=True)
qy = Query(proj_name)
mf = Maxfilter(proj_name)
# Get all series (regardless of subject) named '*SFtuned*' (note wildcards)
series = qy.filter_series(description='*SFtuned*')
# Restrict to specific subjects
# series = qy.filter_series(description='*SFtuned*', subjects=['0007', '0012'])
# Restrict to specific modality
# series = qy.filter_series(description='*mprage*', modalities='MR')
for ses in series:
# MEG acquistions will be split into 2GB chunks if long
for fifname in ses['files']:
in_fname = join(ses['path'], fifname)
outbase = splitext(fifname)[0]
out_fname = join(mf_out_path, outbase + '_tsss.fif')
log_fname = join(log_out_path, outbase + '_tsss.log')
# see maxfilter manual for options
mf.build_cmd(in_fname, out_fname, logfile=log_fname,
