def copypasta(subs=all_sub_args, feat=None):
os.system('rm copypasta.txt')
for sub in subs:
subj = bids_meta(sub)
os.system(
'echo "%s" >> copypasta.txt' %
(os.path.join(subj.feat_dir, subj.fsub + '_' + feat + '.feat')))
def wrangle_first_level_rsa():
mem_weights = {
1: 'mem_baseline_CSp.nii.gz',
2: 'mem_baseline_CSm.nii.gz',
3: 'mem_acquisition_CSp.nii.gz',
4: 'mem_acquisition_CSm.nii.gz',
5: 'mem_extinction_CSp.nii.gz',
6: 'mem_extinction_CSm.nii.gz',
7: 'mem_foil_CSp.nii.gz',
8: 'mem_foil_CSm.nii.gz'
}
for sub in all_sub_args:
subj = bids_meta(sub)
print(sub)
# for phase in ['baseline','acquisition','extinction']:
# csp_cope = os.path.join(subj.model_dir,phase,'rsa_model.feat','stats','cope1.nii.gz')
# csm_cope = os.path.join(subj.model_dir,phase,'rsa_model.feat','stats','cope2.nii.gz')
# os.system('cp %s %s'%(csp_cope,os.path.join(subj.weights,'%s_CSp.nii.gz'%(phase))))
# os.system('cp %s %s'%(csm_cope,os.path.join(subj.weights,'%s_CSm.nii.gz'%(phase))))
for cope in mem_weights:
in_file = os.path.join(subj.model_dir, 'feats',
'memory_rsa_lvl2.gfeat', f'cope{cope}.feat',
'stats', 'cope1.nii.gz')
out_file = os.path.join(subj.weights, mem_weights[cope])
os.system(f'cp {in_file} {out_file}')
def motion_outlier_count():
import os
import re
import matplotlib.pyplot as plt
import seaborn as sns
'''to build the output you need a list of all subjects "all_sub_args"
and a list of all tasks "tasks"
'''
df = pd.DataFrame(index=pd.MultiIndex.from_product([all_sub_args, tasks]))
df['censored'] = 0.
for sub in all_sub_args:
'''
to make this work for CCX, comment out the next line
and change the subj.prep_dir so it is the path to each subject's
fMRIprep directory
'''
subj = bids_meta(sub)
for folder in os.walk(subj.prep_dir):
for file in folder[2]:
if 'confounds' in file and '.tsv' in file:
C = pd.read_csv(os.path.join(subj.prep_dir, folder[0],
file),
sep='\t')
mo = [c for c in C.columns if 'motion_outlier' in c]
task = re.search('task-(.*)_desc', file)[1]
df.loc[(sub, task), 'censored'] = len(mo) / C.shape[0]
sns.boxplot(data=df, y='censored')
sns.swarmplot(data=df, y='censored', color='black')
def __init__(self, sub, mask=None, phases='encode_mem'):
self.subj = bids_meta(sub)
if '_mask' in mask:
self.mask_name = mask[:-5]
else:
self.mask_name = mask
#self.mask = self.load_mask(mask)
#self.data = self.load_clean_data(phases=phases)
#self.extract_timecourse()
# self.interact()
self._autofill_fsf()
def prep_lvl2():
import os
from fg_config import bids_meta, all_sub_args
for sub in all_sub_args:
print(sub)
subj = bids_meta(sub)
# for phase in ['memory_run-01','memory_run-02','memory_run-03']:
for phase in ['baseline', 'acquisition', 'extinction']:
regfolder = os.path.join(
subj.model_dir, phase,
'%s_%s_reg_gPPI.feat' % (subj.fsub, phase), 'reg')
for roi in [
'rh_hpc', 'hc_tail', 'hc_body', 'hc_head', 'amyg_bla',
'amyg_cem'
]:
dest = os.path.join(subj.model_dir, phase, roi, 'source.feat',
'reg')
os.system('cp -r %s %s' % (regfolder, dest))
def wrap_lss_jobs():
for sub in all_sub_args:
subj = bids_meta(sub)
os.system(
'launch -N 1 -n 24 -J lss_%s -s jobs/lss_betas/%s_job.txt -m [email protected] -p normal -r 6:00:00 -A LewPea_MRI_Analysis'
% (sub, subj.fsub))
for i, job in enumerate(os.listdir('jobs/lss_betas')):
if '.txt' in job:
os.system(
'launch -N 1 -n 12 -J lss_%s -s jobs/lss_betas/%s -m [email protected] -p normal -r 09:00:00 -A LewPea_MRI_Analysis'
% (i, job))
for job in ['acquisition', 'extinction', 'baseline']:
os.system(
'launch -N 1 -n 12 -J %s -s jobs/%s_rsa_job.txt -m [email protected] -p normal -r 12:00:00'
)
for job in [1, 2, 3]:
# os.system('launch -N 1 -n 24 -J %s -s jobs/memory_run-0%s_rsa_job.txt -m [email protected] -p normal -r 2:00:00 -A LewPea_MRI_Analysis'%(job,job))
os.system(
f'launch -N 1 -n 24 -J m{job} -s jobs/gPPI/memory-{job}_gPPI_job.txt -m [email protected] -p normal -r 10:00:00 -A LewPea_MRI_Analysis'
)
#submit a bunch of jobs at once
for job in range(28):
os.system(
'launch -N 1 -n 12 -J flss_%s -s jobs/final_lss_job_%s.txt -m [email protected] -p normal -r 12:00:00 -A LewPea_MRI_Analysis'
% (job, job))
#splitting up a bunch of jobs into different job scripts
for i in range(bad.shape[0]):
os.system('echo "%s" >> jobs/final_lss_job_%s.txt' %
(bad[0][i], int(np.floor(i / 12))))
for run in [1, 2, 3]:
for roi in ['dACC', 'mOFC', 'rh_hpc', 'lh_hpc', 'lh_amyg', 'rh_amyg']:
os.system(
'launch -N 1 -n 24 -J %s_%s -s jobs/%s_memory_run-0%s_gPPI_job.txt -m [email protected] -p normal -r 3:00:00 -A LewPea_MRI_Analysis'
% (run, roi, roi, run))
for run in [1, 2]:
os.system(
f'launch -N 2 -n 24 -J localizer-{run} -s jobs/localizer-{run}_job.txt -m [email protected] -p normal -r 1:00:00 -A LewPea_MRI_Analysis'
)
os.system(
'launch -N 2 -n 24 -J localizer_lvl2 -s jobs/localizer_lvl2_job.txt -m [email protected] -p normal -r 1:00:00 -A LewPea_MRI_Analysis'
)
# for roi in ['rh_hpc','hc_tail','hc_body','hc_head','amyg_bla','amyg_cem']:
for roi in ['rh_hpc']:
# os.system('launch -N 1 -n 24 -J %s_lvl2 -s jobs/%s_mem_encode_lvl2_gPPI_job.txt -m [email protected] -p normal -r 00:45:00 -A LewPea_MRI_Analysis'%(roi,roi))
os.system(
'launch -N 1 -n 14 -J %s_lvl3 -s jobs/%s_group_cope_job.txt -m [email protected] -p normal -r 2:00:00 -A LewPea_MRI_Analysis -d 2897228'
% (roi, roi))
os.system(
'launch -N 1 -n 18 -J day1_lvl3 -s jobs/group_day1_gPPI_job.txt -m [email protected] -p normal -r 4:00:00 -A LewPea_MRI_Analysis'
% (roi, roi))
for phase in ['baseline', 'acquisition', 'extinction']:
os.system(
'launch -N 1 -n 6 -J %s_lvl3 -s jobs/%s_group_gPPI_job.txt -m [email protected] -p normal -r 3:00:00 -A LewPea_MRI_Analysis'
% (phase, phase))
#launch -N 2 -n 34 -J sm -s jobs/source_memory_job.txt -m [email protected] -p normal -r 3:00:00 -A LewPea_MRI_Analysis
#launch -N 2 -n 34 -J sm_reg -s jobs/source_memory_reg_job.txt -m [email protected] -p normal -r 0:30:00 -A LewPea_MRI_Analysis -d 3051447
#launch -N 3 -n 30 -J sm_lvl3 -s jobs/source_memory_lvl3_job.txt -m [email protected] -p normal -r 3:00:00 -A LewPea_MRI_Analysis -d 3051447
#launch -N 1 -n 64 -p largemem512GB -J 3dlme -s jobs/3dlme_job.txt -m [email protected] -r 48:00:00 -A LewPea_MRI_Analysis
#launch -N 48 -n 48 -J smooth -s jobs/afni_fwhm_job.txt -m [email protected] -p normal -r 2:00:00 -A LewPea_MRI_Analysis
#launch -N 1 -n 64 -p largemem512GB -J 3dmvm -s jobs/3dMVM_job.txt -m [email protected] -r 48:00:00 -A LewPea_MRI_Analysis
os.system(
f'launch -N 2 -n 48 -J univariate -s jobs/memory_univariate_lvl2_job.txt -m [email protected] -p normal -r 2:00:00 -A LewPea_MRI_Analysis'
)
# for phase in ['baseline','acquisition','extinction','memory_run-01','memory_run-02','memory_run-03']:
for phase in ['memory_run-01', 'memory_run-02', 'memory_run-03']:
# for roi in ['rh_hpc']:
# for roi in ['rACC','sgACC','rh_hpc','lh_hpc','lh_amyg','rh_amyg']:
for roi in ['hc_tail', 'hc_body', 'hc_head', 'amyg_bla', 'amyg_cem']:
# for roi in ['rh_hc_tail','lh_hc_tail','rh_hc_body','lh_hc_body','rh_hc_head','lh_hc_head','rh_amyg_bla','lh_amyg_bla','rh_amyg_cem','lh_amyg_cem']:
# os.system('launch -N 1 -n 24 -J %s_gPPI -s jobs/%s_gPPI_job.txt -m [email protected] -p normal -r 2:00:00 -A LewPea_MRI_Analysis'%(phase,phase))
os.system(
f'launch -N 1 -n 24 -J {roi}_{phase} -s jobs/gPPI/{roi}_{phase}_gPPI_job.txt -m [email protected] -p normal -r 01:30:00 -A LewPea_MRI_Analysis'
)
def autofill_fsf(group=False,
template='',
ses=None,
name=None,
roi=None,
run=None,
subjects=all_sub_args):
if 'template' in template: outstr = re.search('template_(.*)', template)[1]
elif roi is not None:
outstr = roi + '_' + name
else:
outstr = name
if run is not None:
outstr = name
if group:
if roi is not None: replacements = {'ROI': roi}
if ses == 'mem':
for cope in range(1, 15):
replacements['COPEID'] = 'cope%s' % (cope)
outfeat = os.path.join(SCRATCH, 'group_gPPI', roi,
'%s_%s.fsf' % (outstr, cope))
with open(
os.path.join(gPPI_codebase, 'feats',
'%s.fsf' % (template))) as infile:
with open(outfeat, 'w') as outfile:
for line in infile:
for src, target in replacements.items():
line = line.replace(src, target)
outfile.write(line)
#also go ahead and make the job script here
os.system('echo "feat %s" >> jobs/%s_job.txt' %
(outfeat, outstr))
if ses == 1:
for phase in ['baseline', 'acquisition', 'extinction']:
outfeat = os.path.join(SCRATCH, 'group_gPPI', roi,
'%s_%s_%s.fsf' % (roi, phase, name))
replacements['RUNID'] = phase
with open(
os.path.join(gPPI_codebase, 'feats',
'%s.fsf' % (template))) as infile:
with open(outfeat, 'w') as outfile:
for line in infile:
for src, target in replacements.items():
line = line.replace(src, target)
outfile.write(line)
os.system('echo "feat %s" >> jobs/%s_job.txt' %
(outfeat, name))
else:
for sub in subjects:
subj = bids_meta(sub)
replacements = {'SUBID': subj.fsub}
if roi is not None: replacements['ROI'] = roi
if run is not None: replacements['RUNID'] = run
#need to handle the special cases where the TR is longer
if ses == 1 and sub in [105, 106]:
replacements['TR_length'] = '2.23'
else:
replacements['TR_length'] = '2'
outfeat = os.path.join(subj.feat_dir,
'%s_%s.fsf' % (subj.fsub, outstr))
with open(
os.path.join(gPPI_codebase, 'feats',
'%s.fsf' % (template))) as infile:
with open(outfeat, 'w') as outfile:
for line in infile:
for src, target in replacements.items():
line = line.replace(src, target)
outfile.write(line)
#also go ahead and make the job script here
os.system('echo "feat %s" >> jobs/%s_job.txt' % (outfeat, outstr))
def __init__(self, sub):
self.subj = bids_meta(sub)