VERBOSE = True
import os
import sys
# import errno # should do some error checking...
# import subprocess
# ENH: install "official" version of stormdb on isis/hyades
path_to_stormdb = '/users/cjb/src/git/cfin-tools/stormdb/stormdb'
sys.path.append(path_to_stormdb)
# change to stormdb.access (mod. __init__.py)
from access import Query
proj_code = 'MINDLAB2015_MR-YoungAddiction'
db = Query(proj_code)
proj_folder = os.path.join('/projects', proj_code)
scratch_folder = os.path.join(proj_folder, 'scratch')
recon_all_bin = '/opt/local/freesurfer-releases/5.3.0/bin/recon-all'
subjects_dir = os.path.join(scratch_folder, 'fs_subjects_dir')
script_dir = proj_folder+'/scripts/MR_scripts'
included_subjects = db.get_subjects()
# included_subjects = included_subjects[3:]
# just test with first one!
# included_subjects = [included_subjects[1]]
for sub in included_subjects:
# this is an example of getting the DICOM files as a list
sequence_name = 't1_mp2rage_sag_p2_iso_UNI_Images'
proc = subprocess.Popen([command], shell=True)
proc.communicate()
return proc.returncode
proj_code = "MINDLAB2013_03-MEG-BlindPerception"
proj_path = "/projects/" + proj_code
analysis_name = "sss"
VERBOSE = True
FAKE = False # NB
n_processes = 3 # Remember that each process is using n_threads cores by default!
n_threads = 2 # 2 threads per process
db = Query(proj_code=proj_code, verbose=True)
## Make copies of the binary, calibration and cross-talk correction files
## Place them e.g. in "proj_path"/misc/maxfilter
# cp /neuro/bin/util/x86_64-pc-linux-gnu/maxfilter-2.2.15 .
mx_cmd = proj_path + "/misc/maxfilter/maxfilter-2.2.15"
# cp /neuro/databases/sss/sss_cal.dat .
cal_db = proj_path + "/misc/maxfilter/sss_cal.dat"
# cp /neuro/databases/ctc/ct_sparse.fif .
ctc_db = proj_path + "/misc/maxfilter/ct_sparse.fif"
mf_params_defaults = {
"input_file": None,
"output_file": None,
"autobad": "on",
import os, sys
import errno # should do some error checking...
import subprocess
# ENH: install "official" version of stormdb on isis/hyades
path_to_stormdb = '/users/cjb/src/git/cfin-tools/stormdb'
sys.path.append(path_to_stormdb)
# change to stormdb.access (mod. __init__.py)
from access import Query
import numpy as np
proj_code = 'MEG_EEG-Training'
db=Query(proj_code)
proj_folder = os.path.join('/projects', proj_code)
scratch_folder = os.path.join(proj_folder, 'scratch')
recon_all_bin = '/opt/local/freesurfer-releases/5.3.0/bin/recon-all'
subjects_dir = os.path.join(scratch_folder, 'fs_subjects_dir')
script_dir = proj_folder+'/scripts/mads_test_scripts'
included_subjects = db.get_subjects()
# just test with first one!
included_subjects = [included_subjects[0]]
for sub in included_subjects:
# this is an example of getting the DICOM files as a list
sequence_name='t1_mprage_3D_sag'
proc = subprocess.Popen([command], shell=True)
proc.communicate()
return proc.returncode
proj_code = 'MINDLAB2013_03-MEG-BlindPerception'
proj_path = '/projects/' + proj_code
analysis_name = 'sss'
VERBOSE = True
FAKE = False # NB
n_processes = 3 # Remember that each process is using n_threads cores by default!
n_threads = 2 # 2 threads per process
db = Query(proj_code=proj_code, verbose=True)
## Make copies of the binary, calibration and cross-talk correction files
## Place them e.g. in "proj_path"/misc/maxfilter
# cp /neuro/bin/util/x86_64-pc-linux-gnu/maxfilter-2.2.15 .
mx_cmd = proj_path + '/misc/maxfilter/maxfilter-2.2.15'
# cp /neuro/databases/sss/sss_cal.dat .
cal_db = proj_path + '/misc/maxfilter/sss_cal.dat'
# cp /neuro/databases/ctc/ct_sparse.fif .
ctc_db = proj_path + '/misc/maxfilter/ct_sparse.fif'
mf_params_defaults = {
'input_file': None,
'output_file': None,
'autobad': 'on',