def test_ImageInfo_outputs():
output_map = dict(TE=dict(),
TI=dict(),
TR=dict(),
data_type=dict(),
dimensions=dict(),
file_format=dict(),
info=dict(),
orientation=dict(),
out_file=dict(),
ph_enc_dir=dict(),
vox_sizes=dict(),
)
outputs = ImageInfo.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_ImageInfo_outputs():
output_map = dict(
TE=dict(),
TI=dict(),
TR=dict(),
data_type=dict(),
dimensions=dict(),
file_format=dict(),
info=dict(),
orientation=dict(),
out_file=dict(),
ph_enc_dir=dict(),
vox_sizes=dict(),
)
outputs = ImageInfo.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_ImageInfo_inputs():
input_map = dict(args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='%s',
position=1,
),
subjects_dir=dict(),
terminal_output=dict(nohash=True,
),
)
inputs = ImageInfo.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_ImageInfo_inputs():
input_map = dict(
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='%s',
position=1,
),
subjects_dir=dict(),
terminal_output=dict(nohash=True, ),
)
inputs = ImageInfo.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def create_converter_functional_pipeline(working_dir,
ds_dir,
name='converter_funct'):
# initiate workflow
converter_wf = Workflow(name=name)
converter_wf.base_dir = os.path.join(working_dir, 'LeiCA_resting')
# set fsl output
fsl.FSLCommand.set_default_output_type('NIFTI_GZ')
# I/O NODE
inputnode = Node(
util.IdentityInterface(fields=['epi_dicom', 'out_format']),
name='inputnode')
outputnode = Node(util.IdentityInterface(fields=['epi', 'TR_ms']),
name='outputnode')
niftisink = Node(nio.DataSink(), name='niftisink')
niftisink.inputs.base_directory = os.path.join(ds_dir, 'raw_niftis')
niftisink.inputs.substitutions = [('_TR_id_', 'TR_')]
# convert to nifti
# todo check if geometry bugs attac. use dcm2nii?
converter_epi = Node(DcmStack(embed_meta=True), name='converter_epi')
converter_epi.plugin_args = {'submit_specs': 'request_memory = 2000'}
def reformat_filename_fct(TR_str):
return 'rsfMRI_' + TR_str
reformat_filename = Node(util.Function(input_names=['TR_str'],
output_names=['filename'],
function=reformat_filename_fct),
name='reformat_filename')
converter_wf.connect(inputnode, 'out_format', reformat_filename, 'TR_str')
converter_wf.connect(inputnode, 'epi_dicom', converter_epi, 'dicom_files')
converter_wf.connect(reformat_filename, 'filename', converter_epi,
'out_format')
# reorient to standard orientation
reor_2_std = Node(fsl.Reorient2Std(), name='reor_2_std')
converter_wf.connect(converter_epi, 'out_file', reor_2_std, 'in_file')
converter_wf.connect(reor_2_std, 'out_file', outputnode, 'epi')
# save original niftis
converter_wf.connect(reor_2_std, 'out_file', niftisink, 'rsfMRI')
# GET TR FROM .nii
def check_TR_fct(TR):
print ' '
print 'check_TR_fct checks validity of TR'
print('imported TR is %s' % TR)
print ' '
try:
float(TR)
except ValueError:
isvalid_TR = 0
raise Exception(
'ERROR: TR COULD NOT AUTOMATICALLY BE EXTRACTED FROM EPI.\nEXECUTION STOPPED'
)
else:
isvalid_TR = 1
print 'TR is valid'
if isvalid_TR:
if float(TR <= 0):
raise Exception(
'ERROR: TR NOT VALID (<=0).\nEXECUTION STOPPED')
return float(TR)
get_TR = Node(ImageInfo(), name='get_TR')
converter_wf.connect(reor_2_std, 'out_file', get_TR, 'in_file')
check_TR = Node(util.Function(input_names=['TR'],
output_names=['TR_ms'],
function=check_TR_fct),
name='check_TR')
converter_wf.connect(get_TR, 'TR', check_TR, 'TR')
converter_wf.connect(check_TR, 'TR_ms', outputnode, 'TR_ms')
converter_wf.write_graph(dotfilename=converter_wf.name,
graph2use='flat',
format='pdf')
return converter_wf
