def fetch(self, n_subjects=1, preprocess_data=True, convert=True,
url=None, resume=True, force=False, verbose=1):
from openfmri2bids.converter import convert
# Prep the URLs
if not op.exists(op.join(self.data_dir, 'ds052_BIDS')):
url = 'http://openfmri.s3.amazonaws.com/tarballs/ds052_raw.tgz'
opts = {'uncompress': True}
files = [('ds052', url, opts)]
files = self.fetcher.fetch(files, resume=resume, force=force,
verbose=verbose)
# Move around the files to BIDS format.
if convert:
convert(source_dir=op.join(self.data_dir, 'ds052'),
dest_dir=op.join(self.data_dir, 'ds052_BIDS'),
nii_handling='link')
# Loop over subjects to extract files.
anat_files = []
func_files = []
for subj_dir in glob.glob(op.join(self.data_dir,
'ds052_BIDS', 'sub-*')):
anat_files += glob.glob(op.join(subj_dir,
'anatomy', '*_T1w_run*.nii.gz'))
func_files += glob.glob(op.join(subj_dir, 'functional',
'*_task-*_bold*.nii.gz'))
if preprocess_data:
func_files = self.preprocess_files(func_files,
anat_files=anat_files)
# return the data
return dict(func=func_files, anat=anat_files)
def fetch(self,
n_subjects=1,
preprocess_data=True,
url=None,
resume=True,
force=False,
verbose=1):
# Prep the URLs
if not os.path.exists(os.path.join(self.data_dir, 'ds052_BIDS')):
url = 'http://openfmri.s3.amazonaws.com/tarballs/ds052_raw.tgz'
opts = {'uncompress': True}
files = [('ds052', url, opts)]
files = self.fetcher.fetch(files,
resume=resume,
force=force,
verbose=verbose)
# Move around the files to BIDS format.
convert(source_dir=os.path.join(self.data_dir, 'ds052'),
dest_dir=os.path.join(self.data_dir, 'ds052_BIDS'),
nii_handling='link')
# Loop over subjects to extract files.
anat_files = []
func_files = []
for subj_dir in glob.glob(
os.path.join(self.data_dir, 'ds052_BIDS', 'sub-*')):
anat_files += glob.glob(
os.path.join(subj_dir, 'anatomy', '*_T1w_run*.nii.gz'))
func_files += glob.glob(
os.path.join(subj_dir, 'functional', '*_task-*_bold*.nii.gz'))
# if not (i == 2 and anat_file == 'highres002.nii.gz') and not i==11]
if preprocess_data:
func_files = self.preprocess_files(func_files,
anat_files=anat_files)
plt.show()
# return the data
return Bunch(func=func_files, anat=anat_files)
for dataset in datasets:
if isinstance(dataset, dict):
output_ds_dir = output_data_dir + "symlinked/%s/" % \
list(dataset.values())[0][
:-1]
try:
shutil.rmtree(output_ds_dir)
except:
pass
for ses_label, ds in dataset.items():
args = {}
if ds in custom_chngelog_converters:
args["changelog_converter"] = custom_chngelog_converters[ds]
convert(input_data_dir+"%s/"%ds,
output_ds_dir,
ses=ses_label,
nii_handling='link', **args)
else:
output_ds_dir = os.path.join(output_data_dir,
"symlinked/%s/" % dataset)
try:
shutil.rmtree(output_ds_dir)
except:
pass
args = {}
if dataset in custom_chngelog_converters:
args["changelog_converter"] = custom_chngelog_converters[dataset]
convert(os.path.join(input_data_dir, "%s/"%dataset),
output_ds_dir,
nii_handling='link',
**args)
f.write(out_str)
custom_chngelog_converters = {"ds113b": ds113b_converter}
for dataset in datasets:
if isinstance(dataset, dict):
try:
shutil.rmtree("/Volumes/Samsung_T1/bids_examples/symlinked/%s/"%dataset.values()[0][:-1])
except:
pass
for ses_label, ds in dataset.items():
args = {}
if ds in custom_chngelog_converters:
args["changelog_converter"] = custom_chngelog_converters[ds]
convert("/Volumes/Samsung_T1/openfmri/%s/"%ds,
"/Volumes/Samsung_T1/bids_examples/symlinked/%s/"%ds[:-1],
ses=ses_label,
nii_handling='link', **args)
else:
try:
shutil.rmtree("/Volumes/Samsung_T1/bids_examples/symlinked/%s/"%dataset)
except:
pass
args = {}
if dataset in custom_chngelog_converters:
args["changelog_converter"] = custom_chngelog_converters[dataset]
convert("/Volumes/Samsung_T1/openfmri/%s/"%dataset,
"/Volumes/Samsung_T1/bids_examples/symlinked/%s/"%dataset,
nii_handling='link',
**args)
