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'
mr_study = db.get_studies(sub, modality='MR', unique=True)
# if mr_study is not None:
try:
# This is a 2D list with [series_name, series_number]
series = db.get_series(sub, mr_study[0], 'MR')
# Change this to be more elegant: check whether any item in series
# matches sequence_name
try:
T1_file_names = db.get_files(sub, mr_study[0], 'MR',
series[sequence_name])
input_dicom = T1_file_names[0] # first DICOM file
bash_script = ['#!/usr/bin/env bash']
bash_script.append('#$ -S /bin/bash') # for qsub
# have to explicitly source bashrc (non-login shell)
bash_script.append('source ~/.bashrc')
bash_script.append("export FREESURFER_HOME=/usr/local/freesurfer")
bash_script.append("source $FREESURFER_HOME/SetUpFreeSurfer.sh")
included_subjects = db.get_subjects() # [0:1]
if not FAKE:
pool = multiprocessing.Pool(processes=n_processes)
all_cmds = []
for subj in included_subjects:
output_folder_base = proj_path + "/scratch/maxfilter/" + analysis_name + "/" + subj
check_path_exists(output_folder_base)
for study in db.get_studies(subj, modality="MEG", unique=False):
# make a neuromag-style folder structure!
output_folder = output_folder_base + "/" + study[2:8]
check_path_exists(output_folder)
radius_head = None # only once per study!
for (session, sesnum) in db.get_series(subj, study, modality="MEG"):
# Start with a fresh copy of the defaults
mfp = mf_params_defaults.copy()
session_output_files = []
session_mfp = [] # NB: this is a list!!
session_input_files = db.get_files(subj, study, modality="MEG", series=sesnum)
for ii_raw, raw_fname in enumerate(sorted(session_input_files)):
fnum_raw = "%02d" % ii_raw
mfp["input_file"] = raw_fname
if len(session_input_files) > 1:
output_name_base = output_folder + "/" + session + "-" + fnum_raw
else:
output_name_base = output_folder + "/" + session
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'
mr_study = db.get_studies(sub, modality='MR',unique=True)
if not mr_study is None:
# This is a 2D list with [series_name, series_number]
series = db.get_series(sub, mr_study, 'MR',verbose=False)
#### Change this to be more elegant: check whether any item in series
#### matches sequence_name
for ser in series:
if sequence_name in ser:
T1_file_names = db.get_files(sub, mr_study, 'MR',ser[1])
input_dicom = T1_file_names[0] # first DICOM file
bash_script = ['#!/usr/bin/env bash']
bash_script.append('#$ -S /bin/bash') # for qsub
# have to explicitly source bashrc (non-login shell)
bash_script.append('source ~/.bashrc')
bash_script.append('use mne') # set paths
bash_script.append('export SUBJECTS_DIR='+subjects_dir)
included_subjects = db.get_subjects() # [0:1]
if not FAKE:
pool = multiprocessing.Pool(processes=n_processes)
all_cmds = []
for subj in included_subjects:
output_folder_base = proj_path + '/scratch/maxfilter/' + analysis_name + '/' + subj
check_path_exists(output_folder_base)
for study in db.get_studies(subj, modality='MEG', unique=False):
# make a neuromag-style folder structure!
output_folder = output_folder_base + '/' + study[2:8]
check_path_exists(output_folder)
radius_head = None # only once per study!
for (session, sesnum) in db.get_series(subj, study, modality='MEG'):
# Start with a fresh copy of the defaults
mfp = mf_params_defaults.copy()
session_output_files = []
session_mfp = [] #NB: this is a list!!
session_input_files = db.get_files(subj,
study,
modality='MEG',
series=sesnum)
for ii_raw, raw_fname in enumerate(sorted(session_input_files)):
fnum_raw = "%02d" % ii_raw
mfp['input_file'] = raw_fname
if len(session_input_files) > 1:
