def main_wrap():
"""Wrap function call in main."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'tcat_tcorrelate'))
logfile.info('Started 18.tcat_tcorrelate_z_transform.py')
subj_list = ['VREA']
__, clip, __ = tc.get_timings(logfile)
segments = set(c.split('_')[0] for c in clip)
for subject in subj_list:
os.chdir(os.path.join(os.environ['decor'], subject, '6mmblur_results'))
for m in ['AV', 'A', 'V', 'lowlev']:
get_condition_mean(logfile, segments, m, subject,
'6mmblur_tcorr_out_spearman')
tr.setnames_call_funcs(logfile, subject, m,
'6mmblur_tcorr_out_spearman_v2')
for funcseg in ['abouthalf', 'twothirds']:
segments = set(c.split('_')[0] for c in clip)
sub_segments = tc.subsettter(segments, funcseg)
for m in ['AV', 'A', 'V', 'lowlev']:
get_condition_mean(logfile, sub_segments, m, subject,
'6mmblur_tcorr_out_spearman_%s' % funcseg)
tr.setnames_call_funcs(logfile, subject, m,
'6mmblur_tcorr_out_spearman_%s_v2' %
funcseg)
def main():
"""Execute afni_anova."""
subjectlist = [s for s in range(1, 20)]
subjectlist.remove(3)
subjectlist.remove(11)
workdir = os.path.join(os.environ['avp'], 'nii/group_effects_trad')
logfile = setup_log(os.path.join(workdir, 'do_anova_grouptrad'))
logfile.info('Doing main call')
outname = os.path.join(workdir, 'anova2_grouptrad')
afni_anova(logfile, subjectlist, outname)
def main():
"""Wrap the methods to do both main call."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'transform_corr'))
logfile.info('Started 9.transform_corr.py')
subj_list = ['RSDE', 'VREA']
for subject in subj_list:
os.chdir(os.path.join(os.environ['decor'], subject, '6mmblur_results'))
for m in ['AV', 'A', 'V', 'lowlev']:
tcorr_suf = '6mmblur_tcorr_out_spearman'
setnames_call_funcs(logfile, subject, m, tcorr_suf)
def main(subjectlist, anatlist):
"""Wrap methods in main call."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'fsl_anat'))
logfile.info('started 4.fsl_anat.py')
for subject in subjectlist:
os.chdir(os.path.join(os.environ['decor'], subject))
for mprage in anatlist:
anat = '{}.{}.gert_reco'.format(subject, mprage)
fsla = FslAnat(anat)
fsla.afni_to_nifti(logfile)
fsla.fslanat(logfile)
def main():
"""Set names to call vol2surf_mni."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'project_to_surf'))
os.chdir(os.path.join(os.environ['decor'], 'randomise_repmeas'))
pndiff = '1.0'
# No clusters survive tstat4 so do only the first 3
for i in range(1, 4):
for h in ['lh', 'rh']:
parnt = os.path.join(os.environ['decor'], 'randomise_repmeas',
'%s_clustere_corrp_tstat%d_thr005fwe05' %
('repmeas_randomise_out_n5000', i))
vol_to_surf_mni(logfile, h, '%s.nii.gz' % parnt, pndiff,
'%s_%s_pn%s_MNI_N27.1D' % (parnt, h, pndiff))
def main():
"""Wrap funciton calls to main."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'anova'))
logfile.info('Started 17.anova.py')
conditions_list = ['AV', 'A', 'V', 'lowlev']
subjects_list = ['NNPT', 'SSGO', 'LSRS', 'SEKI',
'LNSE', 'JNWL', 'PMBI', 'LNDR',
'GOPR', 'DAHL', 'RSDE', 'VREA']
anova_afni(logfile, subjects_list, conditions_list)
for seg in ['twothirds', 'abouthalf']:
anova_afni(logfile, subjects_list, conditions_list, seg)
def main():
"""Call methods to get randomise."""
randomise_dir = os.path.join(os.environ['decor'], 'randomise_repmeas')
conditions = ['AV', 'A', 'V', 'lowlev']
subjects = ['NNPT', 'SSGO', 'LSRS', 'SEKI',
'LNSE', 'JNWL', 'PMBI', 'LNDR',
'GOPR', 'DAHL', 'RSDE', 'VREA']
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'do_randomise'))
setup_randomise(logfile, randomise_dir, subjects, conditions)
os.chdir(randomise_dir)
logfile.info('Now in working directory: %s', os.getcwd())
nreps = 5000
fsl_randomise(logfile, nreps,
os.path.join(randomise_dir, 'repmeas_4Dfile'),
os.path.join(randomise_dir,
'repmeas_randomise_out_main2tailp005_n%d' % nreps))
def main():
"""Do methods above via this wrapper."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'tcat_tcorrelate'))
logfile.info('Started 8.tcat_tcorrelate.py')
subj_list = ['RSDE', 'VREA']
# Below is for full time series.
__, clip, __ = get_timings(logfile)
segments = set(c.split('_')[0] for c in clip)
tcorr_suf = '6mmblur_tcorr_out_spearman'
for subject in subj_list:
tcorr_main(logfile, subject, segments, tcorr_suf)
# Below is for subset of time series.
# When run either 'twothirds' or 'abouthalf'.
"""
def main():
"""Wrap funciton call."""
randomise_dir = os.path.join(os.environ['decor'], 'randomise_repmeas')
conditions = ['AV', 'A', 'V', 'lowlev']
subjects = ['NNPT', 'SSGO', 'LSRS', 'SEKI',
'LNSE', 'JNWL', 'PMBI', 'LNDR',
'GOPR', 'DAHL', 'RSDE', 'VREA']
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'indivcond_randomise'))
nreps = 10
os.chdir(randomise_dir)
logfile.info('Now in working directory: %s', os.getcwd())
make_condition_file(logfile, randomise_dir, conditions, subjects)
for cond in conditions:
indiv_t_randomise(logfile, nreps,
os.path.join(randomise_dir, '%s_4Dfile' % cond),
os.path.join(randomise_dir,
'%s_out_2tailp005_n%d' % (cond, nreps)))
def main():
"""Wrap funciton calls to main."""
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'epi_reg'))
logfile.info('Started 10.epi_reg.py')
subj_list = ['NNPT']
for subject in subj_list:
basedir = os.path.join(os.environ['decor'], subject)
os.chdir(os.path.join(basedir, '6mmblur_results'))
print os.getcwd()
outpref = 'epi2anat_%s_sess1_6mmblur_meanepi_mprage2' % subject
# converttoNIFTI(logfile, '%s_sess1_6mmblur_meanepi+orig' % subject)
# epi_reg(logfile, '%s_sess1_6mmblur_meanepi.nii.gz' % subject,
# os.path.join(basedir, '%s.mprage2.gert_reco.anat' % subject,
# 'T1_biascorr.nii.gz'),
# os.path.join(basedir, '%s.mprage2.gert_reco.anat' % subject,
# 'T1_biascorr_brain.nii.gz'),
# outpref)
for modal in ['AV', 'A', 'V', 'lowlev']:
# below runs full time series segment
out_flirt = 'highres_flirted_MNI2mm_%s_%s_6mmblur_v2__Z' % \
(subject, modal)
apply_transforms(logfile, subject,
'%s_%s_6mmblur_tcorr_out_spearman_v2_mean_Z.nii.gz'
% (modal, subject),
out_flirt,
'%s.nii.gz' % out_flirt,
'highres_fnirted_MNI2mm_%s_%s_6mmblur_v2_Z'
% (subject, modal),
'%s.mat' % outpref)
# below runs shorter time series segments
for seg in ['twothirds', 'abouthalf']:
out_flirt = 'highres_flirted_MNI2mm_%s_%s_%s_6mmblur_v2__Z' % \
(subject, modal, seg)
apply_transforms(logfile, subject,
'%s_%s_6mmblur_tcorr_out_spearman_%s_v2_mean_Z.nii.gz'
% (modal, subject, seg),
out_flirt,
'%s.nii.gz' % out_flirt,
'highres_fnirted_MNI2mm_%s_%s_%s_6mmblur_v2_Z'
% (subject, modal, seg),
'%s.mat' % outpref)
def main():
"""Wrap method to execute in main.
high/high - mean(high/low, low/high)
mean(high/low, low/high) - low/low
"""
subj_list = [s for s in range(1, 20)]
subj_list.remove(3)
subj_list.remove(11)
logfile = setup_log(os.path.join(os.environ['avp'], 'logs',
'do_regularity_gradient_grptest'))
logfile.info('Doing regularity_gradient_grptest.')
logfile.info('Doing 3dMEMA.')
for lvl in ['high', 'low']:
mema_out = os.path.join(os.environ['avp'], 'nii',
'regularity_gradient',
'{}_grad_flt2_msk_mema'.format(lvl))
mema(logfile, lvl, subj_list, mema_out)
def main():
"""Wrap all the methods to execute."""
subject_list = ['RSDE', 'VREA']
subjectstim_dict = build_subject_dict(subject_list)
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'align_epis'))
logfile.info('started 5.align_epis.py')
for subject in subject_list:
resultsdir = os.path.join(os.environ['decor'], subject,
'6mmblur_results')
dir_check(resultsdir)
os.chdir(resultsdir)
print(os.getcwd())
do_avg_mean_epis(logfile, subjectstim_dict, subject)
align_epis(logfile, subject)
for run in subjectstim_dict[subject]['sess2']:
allineate(logfile, subject, run)
for run in subjectstim_dict[subject]['sess1']:
copyn(logfile, subject, run)
def main():
"""Call methods for thresholding and clustering."""
lname = 'thresh_cluster_twocond_contr_conj'
logfile = setup_log(os.path.join(os.environ['decor'], 'logs', lname))
logfile.info('Do threshold and cluster.')
os.chdir(os.path.join(os.environ['decor'], 'randomise_twocond_contr_conj'))
pref = 'out_1tailp001_n5000'
for ctype in ['clustere', 'clusterm', 'tfce']:
for pref in ['AVvA_randomise_out_n5000_p005',
'AVvV_randomise_out_n5000_p005']:
for i in range(1, 3):
fsl_maths(logfile,
'{}_{}_corrp_tstat{}'.format(pref, ctype, i),
'{}_tstat{}.nii.gz'.format(pref, i),
'{}_{}_corrp_tstat{}_fwe05'.format(pref, ctype, i))
cluster(logfile,
'{}_{}_corrp_tstat{}_fwe05.nii.gz'.format(pref, ctype, i),
'{}_{}_corrp_tstat{}_fwe05_cluster_index'.format(pref, ctype, i),
'{}_{}_corrp_tstat{}_fwe05lmax.txt'.format(pref, ctype, i),
'{}_{}_corrp_tstat{}_fwe05omean'.format(pref, ctype, i),
'{}_{}_corrp_tstat{}_fwe05cluster_size'.format(pref, ctype, i))
def main():
"""Call methods to get randomise."""
randomise_dir = os.path.join(os.environ['decor'],
'randomise_twocond_contr_conj')
subjects = ['NNPT', 'SSGO', 'LSRS', 'SEKI',
'LNSE', 'JNWL', 'PMBI', 'LNDR',
'GOPR', 'DAHL', 'RSDE', 'VREA']
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'do_randomise_twocond_contr_conj'))
os.chdir(randomise_dir)
nreps = 5000
mergefsl(logfile, make_file_list(subjects, ['AV', 'A']), 'AVvA_4Dfile')
fsl_randomise(logfile, nreps,
os.path.join(randomise_dir, 'AVvA_4Dfile'),
os.path.join(randomise_dir,
'AVvA_randomise_out_n%d_p005' % nreps))
mergefsl(logfile, make_file_list(subjects, ['AV', 'V']), 'AVvV_4Dfile')
fsl_randomise(logfile, nreps,
os.path.join(randomise_dir, 'AVvV_4Dfile'),
os.path.join(randomise_dir,
'AVvV_randomise_out_n%d_p005' % nreps))
from pdfminer.pdfpage import PDFPage
from lib.parse_helpers import parse_timecard_line_v2, timecard2dict, date_find
from lib.parse_helpers import weekly_mapping
from lib.parse_helpers import reform_produce
from lib.parse_helpers import handle_buffer_entries
from lib.regex_helper import filter_junk, clean_line_intake
from lib.settings import key_page
from lib.settings import last_timecard
#read?
import lib.settings
from setlog import setup_log
logger = setup_log()
def extract_text_from_pdf(pdf_path):
resource_manager = PDFResourceManager()
fake_file_handle = io.StringIO()
converter = TextConverter(resource_manager, fake_file_handle)
page_interpreter = PDFPageInterpreter(resource_manager, converter)
with open(pdf_path, 'rb') as fh:
for page in PDFPage.get_pages(fh, caching=True,
check_extractable=True):
page_interpreter.process_page(page)
text = fake_file_handle.getvalue()
run, subj, subj, run))
proc = Popen(cmdargs, stdout=PIPE, stderr=STDOUT)
log.info(proc.stdout.read())
def splicer_localizer(subj, run):
"""Splice localizer series."""
stdf = open('stdout_files/stdout_from_Tcat_{}.txt'.format(run), 'w')
cmdargs = split('3dTcat -prefix {}.{}.TRIM \
raw.{}.{}.gert_reco+orig.BRIK[14-405]'.format(
run, subj, subj, run))
Popen(cmdargs, stdout=stdf, stderr=STDOUT)
stdf.close()
if __name__ == "__main__":
SCRUNS = ['SC{}'.format(i) for i in range(1, 7)]
AVRUNS = ['AV1.1', 'AV1.2', 'AV2.1', 'AV2.2', 'AV3.1', 'AV3.2']
RUNIDS = SCRUNS + AVRUNS
SUBJECTLIST = ['RSDE', 'VREA']
logfile = setup_log(os.path.join(os.environ['decor'], 'logs/splicer'))
logfile.info('started splicer.py')
for ss in SUBJECTLIST:
subjectdir = os.path.join(os.environ['decor'], ss)
os.chdir(subjectdir)
for rr in RUNIDS:
splicer(logfile, ss, rr)
splicer_rest(logfile, ss, 'Rest')
stimdict = {}
for subj in subjectlist:
seriesorder = pd.Series(df.loc[df.SSname == subj, 'stim_name'])
subidx = list(seriesorder.iloc[[0, 6]])
subjitem = {subj: {subidx[0]: list(seriesorder.iloc[:6]),
subidx[1]: list(seriesorder.iloc[6:]),
'Rest': ['Rest']}}
stimdict.update(subjitem)
return stimdict
if __name__ == '__main__':
SUBJECTLIST = ['RSDE', 'VREA']
STIMDICT = build_subject_dict(SUBJECTLIST)
logfile = setup_log(os.path.join(os.environ['decor'], 'logs',
'afproc_withblur'))
logfile.info('started 3.afproc_withblur.py')
for subject in SUBJECTLIST:
print('setting work dir: ')
os.chdir(os.path.join(os.environ['decor'], subject))
print(os.getcwd())
for ref in STIMDICT[subject]:
for runident in STIMDICT[subject][ref]:
subjrun = '{}.{}.6mmblur'.format(subject, runident)
afniproc(subject, runident, subjrun, ref)
run_afniproc(logfile, subjrun) # this is separate
