os.makedirs(pth)
except OSError as exc:
if exc.errno == errno.EEXIST and os.path.isdir(pth):
pass
else:
raise
###############################################################################
# Setup paths and prepare raw data
proj_code = 'MINDLAB2013_01-MEG-AttentionEmotionVisualTracking'
VERBOSE=True
SAVE=False # NB
db = Query(proj_code=proj_code,verbose=True)
subjects = db.get_subjects()
example_subject = subjects[1][1:] #007
print "Using {:s} as example".format(example_subject)
proj_folder = '/projects/' + proj_code
misc_folder = proj_folder + '/misc'
scratch_folder = proj_folder + '/scratch'
raw_data_folder = scratch_folder + '/tsss_initial/' + \
example_subject
img_folder = raw_data_folder + '/img'
mkdir_p(img_folder)
raw_fname = raw_data_folder + '/VS_1a_1_tsss_mc.fif'
###############################################################################
def test_get_studies():
studies = Query(proj_name).get_studies(test_subject_name)
assert_equal(len(studies), len(study_modalities))
assert_equal(studies[study_name_tuple[0]], study_name_tuple[1])
def test_filter_series():
series = Query(proj_name).filter_series(series_name,
subjects=test_subject_name)
assert_equal(len(series), 1)
assert_equal(int(series[0]['serieno']), series_number)
CLOBBER = False
FAKE = False
VERBOSE = True
# ENH: install "official" version of stormdb on isis/hyades
path_to_stormdb = "/usr/local/common/meeg-cfin/stormdb"
# path_to_stormdb = "/volatile/mje/meeg-cfin/stormdb"
sys.path.append(path_to_stormdb)
from stormdb.access import Query
# path to submit_to_isis
cmd = "/usr/local/common/meeg-cfin/configurations/bin/submit_to_isis"
proj_code = "MINDLAB2015_MEG-CorticalAlphaAttention"
db = Query(proj_code)
proj_folder = os.path.join("/projects", proj_code)
scratch_folder = os.path.join(proj_folder, "scratch/")
fs_subjects_dir = os.path.join(scratch_folder, "fs_subjects_dir/")
subjects_dir = os.path.join(scratch_folder, "fs_subjects_dir")
script_dir = proj_folder + "/scripts/"
included_subjects = db.get_subjects()
# just test with first one!
sub_new = []
#
for sub in [included_subjects[5]]:
if not os.path.isfile(fs_subjects_dir + "%s/%s_t1.nii.gz" % (sub[:4], sub[:4])):
# this is an example of getting the DICOM files as a list
def test_get_subjects():
subs = Query(proj_name).get_subjects()
assert_true(isinstance(subs, list))
assert_equal(subs[0], test_subject_name) # 0001 is excluded in DB!
st_buflen=30,
st_corr=0.95,
movecomp=True,
# cal=cal,
# ctc=ctc,
mx_args='',
maxfilter_bin='maxfilter',
force=True
)
# path to submit_to_isis
cmd = "/usr/local/common/meeg-cfin/configurations/bin/submit_to_isis"
proj_code = "MINDLAB2015_MEG-CorticalAlphaAttention"
db = Query(proj_code)
proj_folder = os.path.join('/projects', proj_code)
scratch_folder = os.path.join(proj_folder, 'scratch/maxfiltered_data/')
subjects_dir = os.path.join(scratch_folder, 'fs_subjects_dir')
script_dir = proj_folder + '/scripts/'
included_subjects = db.get_subjects()
# just test with first one!
included_subjects = included_subjects[-3:]
for sub in included_subjects:
# this is an example of getting the DICOM files as a list
# sequence_name='t1_mprage_3D_sag'
MEG_study = db.get_studies(sub, modality='MEG')
if len(MEG_study) > 0:
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)
autobad='off', # or use xscan first
st=True, # use tSSS
st_buflen=30, # parameter set in beg. of notebook
st_corr=95, # parameter set in beg. of notebook
movecomp=True,
trans=None, # compensate to mean initial head position (saved to file),
# or use None for initial head position
logfile=None, # we replace this in each loop
hp=None, # head positions, replace in each loop
n_threads=4 # number of parallel threads to run on
)
# path to submit_to_isis
proj_code = "MINDLAB2011_24-MEG-readiness"
db = Query(proj_code)
proj_folder = os.path.join('/projects', proj_code)
script_dir = proj_folder + '/scripts/RP_scripts'
conditions = {"classic": "2", "plan": "4", "interupt": "3"}
included_subjects = db.get_subjects()
# just test with first one!
included_subjects = included_subjects[7]
for sub in [included_subjects]:
MEG_study = db.get_studies(sub, modality='MEG')
for condition in conditions:
in_name = db.get_files(sub, MEG_study[0], 'MEG',
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,
autobad="on",
st=True,
st_buflen=30,
st_corr=0.95,
movecomp=True,
cal=cal,
ctc=ctc,
mx_args='',
maxfilter_bin='maxfilter',
force=True)
# path to submit_to_isis
cmd = "/usr/local/common/meeg-cfin/configurations/bin/submit_to_isis"
proj_code = "MINDLAB2011_24-MEG-readiness"
db = Query(proj_code)
proj_folder = os.path.join('/projects', proj_code)
script_dir = proj_folder + '/scripts/'
conditions = {"classic": "2", "plan": "4", "interupt": "3"}
included_subjects = db.get_subjects()
# just test with first one!
included_subjects = included_subjects[6:]
for sub in included_subjects:
MEG_study = db.get_studies(sub, modality='MEG')
for condition in conditions:
in_name = db.get_files(sub, MEG_study[0], 'MEG', conditions[condition])
