def processS():
numCores=int(sys.argv[1])
wfname='resting_preproc'
workflow=pe.Workflow(name=wfname)
anatpreproc=create_anat_preproc()
anatpreproc.inputs.inputspec.anat=os.path.abspath('/home/sharad/Resources/0010052/session_1/anat_1/mprage.nii.gz')
funcpreproc=create_func_preproc()
funcpreproc.inputs.inputspec.rest=os.path.abspath('/home/sharad/Resources/0010052/session_1/rest_1/rest.nii.gz')
funcpreproc.inputs.inputspec.start_idx=0
funcpreproc.inputs.inputspec.stop_idx=175
segpreproc=create_seg_preproc()
segpreproc.inputs.inputspec.PRIOR_CSF = os.path.abspath('/home/sharad/nki_nyu_pipeline/tissuepriors/avg152T1_csf_bin.nii.gz')
segpreproc.inputs.inputspec.PRIOR_WHITE = os.path.abspath('/home/sharad/nki_nyu_pipeline/tissuepriors/avg152T1_white_bin.nii.gz')
segpreproc.inputs.inputspec.standard_res_brain=os.path.abspath('/frodo/shared/RH5_fsl/data/standard/MNI152_T1_3mm_brain.nii.gz')
regpreproc=create_reg_preproc()
regpreproc.inputs.inputspec.standard_res_brain=os.path.abspath('/frodo/shared/RH5_fsl/data/standard/MNI152_T1_3mm_brain.nii.gz')
regpreproc.inputs.inputspec.standard=os.path.abspath('/frodo/shared/RH5_fsl/data/standard/MNI152_T1_3mm.nii.gz')
regpreproc.inputs.inputspec.config_file=os.path.abspath('/frodo/shared/RH5_fsl/etc/flirtsch/T1_2_MNI152_3mm.cnf')
regpreproc.inputs.inputspec.standard_brain_mask_dil=os.path.abspath('/frodo/shared/RH5_fsl/data/standard/MNI152_T1_3mm_brain_mask_dil.nii.gz')
workflow.connect(funcpreproc, 'outputspec.example_func', regpreproc, 'inputspec.example_func')
workflow.connect(anatpreproc, 'outputspec.brain', regpreproc, 'inputspec.brain')
workflow.connect(anatpreproc, 'outputspec.reorient', regpreproc, 'inputspec.reorient')
workflow.connect(funcpreproc, 'outputspec.preprocessed_mask', segpreproc, 'inputspec.preprocessed_mask')
workflow.connect(anatpreproc, 'outputspec.brain', segpreproc, 'inputspec.brain')
workflow.connect(funcpreproc, 'outputspec.example_func', segpreproc, 'inputspec.example_func')
workflow.connect(regpreproc, 'outputspec.highres2example_func_mat', segpreproc, 'inputspec.highres2example_func_mat')
workflow.connect(regpreproc, 'outputspec.stand2highres_warp', segpreproc, 'inputspec.stand2highres_warp')
# workflow.add_nodes([anatpreproc, funcpreproc])
workflow.base_dir='/home/sharad/nki_nyu_pipeline/working_dir'
workflow.run(plugin='MultiProc', plugin_args={'n_procs': numCores})
def get_workflow(wf_name, c):
preproc = None
"""
setup standard file paths
"""
prior_path = os.path.join(c.priorDirectory, c.standardResolution)
PRIOR_CSF = os.path.join(prior_path, 'avg152T1_csf_bin.nii.gz')
PRIOR_GRAY = os.path.join(prior_path, 'avg152T1_gray_bin.nii.gz')
PRIOR_WHITE = os.path.join(prior_path, 'avg152T1_white_bin.nii.gz')
standard_res_brain = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s_brain.nii.gz' % (c.standardResolution))
standard = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s.nii.gz' % (c.standardResolution))
standard_brain_mask_dil = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s_brain_mask_dil.nii.gz' % (c.standardResolution))
config_file = os.path.join(c.FSLDIR,
'etc/flirtsch/T1_2_MNI152_%s.cnf' % (c.standardResolution))
brain_symmetric = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_brain_symmetric.nii.gz')
symm_standard = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_symmetric.nii.gz')
twomm_brain_mask_dil = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_brain_mask_symmetric_dil.nii.gz')
config_file_twomm = os.path.join(c.FSLDIR,
'etc/flirtsch/T1_2_MNI152_2mm.cnf')
identity_matrix = os.path.join(c.FSLDIR,
'etc/flirtsch/ident.mat')
if wf_name.lower() == 'anat':
preproc = create_anat_preproc()
return preproc
if wf_name.lower() == 'func':
preproc = create_func_preproc()
preproc.inputs.inputspec.start_idx = c.startIdx
preproc.inputs.inputspec.stop_idx = c.stopIdx
return preproc
if wf_name.lower() == 'seg':
preproc = create_seg_preproc()
preproc.inputs.inputspec.PRIOR_CSF = PRIOR_CSF
preproc.inputs.inputspec.PRIOR_WHITE = PRIOR_WHITE
preproc.inputs.inputspec.PRIOR_GRAY = PRIOR_GRAY
preproc.inputs.inputspec.standard_res_brain = standard_res_brain
preproc.inputs.csf_threshold.csf_threshold = \
c.cerebralSpinalFluidThreshold
preproc.inputs.wm_threshold.wm_threshold = \
c.whiteMatterThreshold
preproc.inputs.gm_threshold.gm_threshold = \
c.grayMatterThreshold
preproc.get_node('csf_threshold').iterables = ('csf_threshold',
c.cerebralSpinalFluidThreshold)
preproc.get_node('wm_threshold').iterables = ('wm_threshold',
c.whiteMatterThreshold)
preproc.get_node('gm_threshold').iterables = ('gm_threshold',
c.grayMatterThreshold)
return preproc
if wf_name.lower() == 'reg':
preproc = create_reg_preproc()
preproc.inputs.inputspec.standard_res_brain = \
standard_res_brain
preproc.inputs.inputspec.standard = standard
preproc.inputs.inputspec.config_file = config_file
preproc.inputs.inputspec.standard_brain_mask_dil = \
standard_brain_mask_dil
return preproc
if wf_name.lower() == 'alff':
preproc = create_alff_preproc(c)
preproc.inputs.inputspec.standard = standard
preproc.inputs.hp_input.hp = c.highPassFreqALFF
preproc.inputs.lp_input.lp = c.lowPassFreqALFF
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('hp_input').iterables = ('hp',
c.highPassFreqALFF)
preproc.get_node('lp_input').iterables = ('lp',
c.lowPassFreqALFF)
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
return preproc
if wf_name.lower() == 'sca':
preproc = create_sca_preproc(c.correlationSpace)
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'vmhc':
preproc = create_vmhc_preproc(c)
preproc.inputs.inputspec.brain_symmetric = \
brain_symmetric
preproc.inputs.inputspec.symm_standard = \
symm_standard
preproc.inputs.inputspec.twomm_brain_mask_dil = \
twomm_brain_mask_dil
preproc.inputs.inputspec.config_file_twomm = \
config_file_twomm
preproc.inputs.inputspec.standard = \
standard
return preproc
if wf_name.lower() == 'sc':
preproc = create_scrubbing_preproc()
return preproc
if wf_name.lower() == 'pm':
preproc = create_parameters_preproc(c)
preproc.inputs.threshold_input.threshold = c.scrubbingThreshold
preproc.get_node('threshold_input').iterables = ('threshold', c.scrubbingThreshold)
return preproc
if wf_name.lower() == 'select':
preproc = selector_wf()
preproc.inputs.scrubbed_input.scrubbed = c.scrubData
preproc.get_node('scrubbed_input').iterables = \
('scrubbed', c.scrubData)
return preproc
if wf_name.lower() == 'nuisance':
preproc = create_nuisance_preproc()
preproc.inputs.selector_input.selector = c.Corrections
preproc.inputs.nc_input.nc = c.nComponents
preproc.inputs.target_angle_deg_input.target_angle_deg = \
c.targetAngleDeg
preproc.get_node('selector_input').iterables = \
('selector', c.Corrections)
preproc.get_node('nc_input').iterables = \
('nc', c.nComponents)
preproc.get_node('target_angle_deg_input').iterables = \
('target_angle_deg', c.targetAngleDeg)
return preproc
if wf_name.lower() == 'mprage_in_mnioutputs':
preproc = mprage_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'func_in_mnioutputs':
preproc = func_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'freq_filter':
from base_nuisance import bandpass_voxels
import nipype.interfaces.utility as util
preproc = pe.MapNode(util.Function(input_names=['realigned_file',
'sample_period',
'bandpass_freqs'],
output_names=['bandpassed_file'],
function=bandpass_voxels),
name='bandpass_filter',
iterfield=['realigned_file', 'bandpass_freqs', 'sample_period'])
preproc.inputs.bandpass_freqs = c.nuisanceBandpassFreq
#preproc.inputs.sample_period = c.TR
return preproc
if wf_name.lower() == 'ts':
preproc = create_timeseries_preproc(True, True, True, c.runSurfaceRegistraion)
preproc.inputs.inputspec.recon_subjects = c.reconSubjectsDirectory
preproc.inputs.inputspec.standard = standard
preproc.inputs.inputspec.identity_matrix = identity_matrix
preproc.inputs.inputspec.unitTSOutputs = [True, True]
preproc.inputs.inputspec.voxelTSOutputs = [True, True]
preproc.inputs.inputspec.verticesTSOutputs = [True, True]
return preproc
if wf_name.lower() == 'group_analysis':
preproc = create_group_analysis(c.fTest)
preproc.inputs.inputspec.z_threshold = c.zThreshold
preproc.inputs.inputspec.p_threshold = c.pThreshold
preproc.inputs.inputspec.parameters = (c.FSLDIR,
c.MNI)
return preproc
def get_workflow(wf_name, c):
preproc = None
"""
setup standard file paths
"""
prior_path = os.path.join(c.priorDirectory, c.standardResolution)
PRIOR_CSF = os.path.join(prior_path, 'avg152T1_csf_bin.nii.gz')
PRIOR_GRAY = os.path.join(prior_path, 'avg152T1_gray_bin.nii.gz')
PRIOR_WHITE = os.path.join(prior_path, 'avg152T1_white_bin.nii.gz')
standard_res_brain = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s_brain.nii.gz' % (c.standardResolution))
standard = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s.nii.gz' % (c.standardResolution))
standard_brain_mask_dil = '/home2/ssikka/scripts1/templates/MNI152_T1_%s_brain_mask_dil.nii.gz' % (c.standardResolution)
config_file = '/home2/ssikka/scripts1/templates/T1_2_MNI152_%s.cnf' % (c.standardResolution)
brain_symmetric = '/home2/ssikka/scripts1/templates/MNI152_T1_2mm_brain_symmetric.nii.gz'
symm_standard = '/home2/ssikka/scripts1/templates/MNI152_T1_2mm_symmetric.nii.gz'
twomm_brain_mask_dil = '/home2/ssikka/scripts1/templates/MNI152_T1_2mm_brain_mask_symmetric_dil.nii.gz'
config_file_twomm = '/home2/ssikka/scripts1/templates/T1_2_MNI152_2mm.cnf'
identity_matrix = os.path.join(c.FSLDIR,
'etc/flirtsch/ident.mat')
if wf_name.lower() == 'anat':
preproc = create_anat_preproc()
return preproc
if wf_name.lower() == 'func':
preproc = create_func_preproc()
preproc.inputs.inputspec.start_idx = c.startIdx
preproc.inputs.inputspec.stop_idx = c.stopIdx
return preproc
if wf_name.lower() == 'seg':
preproc = create_seg_preproc()
preproc.inputs.inputspec.PRIOR_CSF = PRIOR_CSF
preproc.inputs.inputspec.PRIOR_WHITE = PRIOR_WHITE
preproc.inputs.inputspec.PRIOR_GRAY = PRIOR_GRAY
preproc.inputs.inputspec.standard_res_brain = standard_res_brain
preproc.inputs.csf_threshold.csf_threshold = \
c.cerebralSpinalFluidThreshold
preproc.inputs.wm_threshold.wm_threshold = \
c.whiteMatterThreshold
preproc.inputs.gm_threshold.gm_threshold = \
c.grayMatterThreshold
preproc.get_node('csf_threshold').iterables = ('csf_threshold',
c.cerebralSpinalFluidThreshold)
preproc.get_node('wm_threshold').iterables = ('wm_threshold',
c.whiteMatterThreshold)
preproc.get_node('gm_threshold').iterables = ('gm_threshold',
c.grayMatterThreshold)
return preproc
if wf_name.lower() == 'reg':
preproc = create_reg_preproc()
preproc.inputs.inputspec.standard_res_brain = \
standard_res_brain
preproc.inputs.inputspec.standard = standard
preproc.inputs.inputspec.config_file = config_file
preproc.inputs.inputspec.standard_brain_mask_dil = \
standard_brain_mask_dil
return preproc
if wf_name.lower() == 'alff':
preproc = create_alff_preproc()
preproc.inputs.inputspec.standard = standard
preproc.inputs.hp_input.hp = c.highPassFreqALFF
preproc.inputs.lp_input.lp = c.lowPassFreqALFF
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('hp_input').iterables = ('hp',
c.highPassFreqALFF)
preproc.get_node('lp_input').iterables = ('lp',
c.lowPassFreqALFF)
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
return preproc
if wf_name.lower() == 'sca':
preproc = create_sca_preproc(c.correlationSpace)
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'vmhc':
preproc = create_vmhc_preproc()
preproc.inputs.inputspec.brain_symmetric = \
brain_symmetric
preproc.inputs.inputspec.symm_standard = \
symm_standard
preproc.inputs.inputspec.twomm_brain_mask_dil = \
twomm_brain_mask_dil
preproc.inputs.inputspec.config_file_twomm = \
config_file_twomm
preproc.inputs.inputspec.standard = \
standard
return preproc
if wf_name.lower() == 'sc':
preproc = create_scrubbing_preproc()
preproc.inputs.threshold_input.threshold = c.scrubbingThreshold
preproc.get_node('threshold_input').iterables = ('threshold', c.scrubbingThreshold)
return preproc
if wf_name.lower() == 'select':
preproc = selector_wf()
preproc.inputs.run_scrubbing_input.run_scrubbing = c.scrubData
preproc.get_node('run_scrubbing_input').iterables = \
('run_scrubbing', c.scrubData)
return preproc
if wf_name.lower() == 'nuisance':
preproc = create_nuisance_preproc()
preproc.inputs.selector_input.selector = c.Corrections
preproc.inputs.nc_input.nc = c.nComponents
preproc.inputs.target_angle_deg_input.target_angle_deg = \
c.targetAngleDeg
preproc.get_node('selector_input').iterables = \
('selector', c.Corrections)
preproc.get_node('nc_input').iterables = \
('nc', c.nComponents)
preproc.get_node('target_angle_deg_input').iterables = \
('target_angle_deg', c.targetAngleDeg)
return preproc
if wf_name.lower() == 'mprage_in_mnioutputs':
preproc = mprage_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'func_in_mnioutputs':
preproc = func_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'freq_filter':
from base_nuisance import bandpass_voxels
import nipype.interfaces.utility as util
preproc = pe.MapNode(util.Function(input_names=['realigned_file',
'sample_period',
'bandpass_freqs'],
output_names=['bandpassed_file'],
function=bandpass_voxels),
name='bandpass_filter',
iterfield=['realigned_file', 'bandpass_freqs'])
preproc.inputs.bandpass_freqs = c.nuisanceBandpassFreq
preproc.inputs.sample_period = c.TR
return preproc
if wf_name.lower() == 'ts':
preproc = create_timeseries_preproc(True, True, True, c.runSurfaceRegistraion)
preproc.inputs.inputspec.recon_subjects = c.reconSubjectsDirectory
preproc.inputs.inputspec.standard = standard
preproc.inputs.inputspec.identity_matrix = identity_matrix
preproc.inputs.inputspec.unitTSOutputs = [True, True]
preproc.inputs.inputspec.voxelTSOutputs = [True, True]
preproc.inputs.inputspec.verticesTSOutputs = [True, True]
return preproc
if wf_name.lower() == 'group_analysis':
preproc = create_group_analysis(c.fTest)
preproc.inputs.inputspec.z_threshold = c.zThreshold
preproc.inputs.inputspec.p_threshold = c.pThreshold
preproc.inputs.inputspec.parameters = (c.FSLDIR,
c.MNI)
return preproc
def get_workflow(wf_name, c):
preproc = None
"""
setup standard file paths
"""
prior_path = os.path.join(c.priorDirectory, c.standardResolution)
PRIOR_CSF = os.path.join(prior_path, 'avg152T1_csf_bin.nii.gz')
PRIOR_GRAY = os.path.join(prior_path, 'avg152T1_gray_bin.nii.gz')
PRIOR_WHITE = os.path.join(prior_path, 'avg152T1_white_bin.nii.gz')
standard_res_brain = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s_brain.nii.gz' % (c.standardResolution))
standard = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s.nii.gz' % (c.standardResolution))
standard_brain_mask_dil = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_%s_brain_mask_dil.nii.gz' % (c.standardResolution))
config_file = os.path.join(c.FSLDIR,
'etc/flirtsch/T1_2_MNI152_%s.cnf' % (c.standardResolution))
brain_symmetric = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_brain_symmetric.nii.gz')
symm_standard = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_symmetric.nii.gz')
twomm_brain_mask_dil = os.path.join(c.FSLDIR,
'data/standard/MNI152_T1_2mm_brain_mask_symmetric_dil.nii.gz')
config_file_twomm = os.path.join(c.FSLDIR,
'etc/flirtsch/T1_2_MNI152_2mm.cnf')
identity_matrix = os.path.join(c.FSLDIR,
'etc/flirtsch/ident.mat')
if wf_name.lower() == 'anat':
preproc = create_anat_preproc()
return preproc
if wf_name.lower() == 'func':
preproc = create_func_preproc()
preproc.inputs.inputspec.start_idx = c.startIdx
preproc.inputs.inputspec.stop_idx = c.stopIdx
return preproc
if wf_name.lower() == 'seg':
preproc = create_seg_preproc()
preproc.inputs.inputspec.PRIOR_CSF = PRIOR_CSF
preproc.inputs.inputspec.PRIOR_WHITE = PRIOR_WHITE
preproc.inputs.inputspec.PRIOR_GRAY = PRIOR_GRAY
preproc.inputs.inputspec.standard_res_brain = standard_res_brain
preproc.inputs.csf_threshold.csf_threshold = \
c.cerebralSpinalFluidThreshold
preproc.inputs.wm_threshold.wm_threshold = \
c.whiteMatterThreshold
preproc.inputs.gm_threshold.gm_threshold = \
c.grayMatterThreshold
preproc.get_node('csf_threshold').iterables = ('csf_threshold',
c.cerebralSpinalFluidThreshold)
preproc.get_node('wm_threshold').iterables = ('wm_threshold',
c.whiteMatterThreshold)
preproc.get_node('gm_threshold').iterables = ('gm_threshold',
c.grayMatterThreshold)
return preproc
if wf_name.lower() == 'reg':
preproc = create_reg_preproc()
preproc.inputs.inputspec.standard_res_brain = \
standard_res_brain
preproc.inputs.inputspec.standard = standard
preproc.inputs.inputspec.config_file = config_file
preproc.inputs.inputspec.standard_brain_mask_dil = \
standard_brain_mask_dil
return preproc
if wf_name.lower() == 'alff':
preproc = create_alff_preproc(c)
preproc.inputs.inputspec.standard = standard
preproc.inputs.hp_input.hp = c.highPassFreqALFF
preproc.inputs.lp_input.lp = c.lowPassFreqALFF
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('hp_input').iterables = ('hp',
c.highPassFreqALFF)
preproc.get_node('lp_input').iterables = ('lp',
c.lowPassFreqALFF)
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
return preproc
if wf_name.lower() == 'sca':
preproc = create_sca_preproc(c.correlationSpace)
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'vmhc':
preproc = create_vmhc_preproc(c)
preproc.inputs.inputspec.brain_symmetric = \
brain_symmetric
preproc.inputs.inputspec.symm_standard = \
symm_standard
preproc.inputs.inputspec.twomm_brain_mask_dil = \
twomm_brain_mask_dil
preproc.inputs.inputspec.config_file_twomm = \
config_file_twomm
preproc.inputs.inputspec.standard = \
standard
preproc.inputs.fwhm_input.fwhm = c.fwhm
preproc.get_node('fwhm_input').iterables = ('fwhm',
c.fwhm)
return preproc
if wf_name.lower() == 'sc':
preproc = create_scrubbing_preproc()
return preproc
if wf_name.lower() == 'pm':
preproc = create_parameters_preproc(c)
preproc.inputs.threshold_input.threshold = c.scrubbingThreshold
preproc.get_node('threshold_input').iterables = ('threshold', c.scrubbingThreshold)
return preproc
if wf_name.lower() == 'select':
preproc = selector_wf()
preproc.inputs.scrubbed_input.scrubbed = c.scrubData
preproc.get_node('scrubbed_input').iterables = \
('scrubbed', c.scrubData)
return preproc
if wf_name.lower() == 'nuisance':
preproc = create_nuisance_preproc()
preproc.inputs.selector_input.selector = c.Corrections
preproc.inputs.nc_input.nc = c.nComponents
preproc.inputs.target_angle_deg_input.target_angle_deg = \
c.targetAngleDeg
preproc.get_node('selector_input').iterables = \
('selector', c.Corrections)
preproc.get_node('nc_input').iterables = \
('nc', c.nComponents)
preproc.get_node('target_angle_deg_input').iterables = \
('target_angle_deg', c.targetAngleDeg)
return preproc
if wf_name.lower() == 'mprage_in_mnioutputs':
preproc = mprage_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'func_in_mnioutputs':
preproc = func_in_mnioutputs()
preproc.inputs.inputspec.standard = standard
return preproc
if wf_name.lower() == 'freq_filter':
struct=[['session_id', 'subject_id']])
datasink = pe.Node(nio.DataSink(infields=['container.@subject']),
name='sinker')
datasink.inputs.base_directory = output_path
#datasink.inputs.substitutions = [('session\d_subject_id_', '')]
#st = pe.Node(interface=fsl.SliceTimer(), name='st')
#st.iterables = [('time_repetition', [2.0, 3.0])]
workflow = pe.Workflow(name='wf')
workflow.base_dir = output_path
anatpreproc = create_anat_preproc()
funcpreproc = create_func_preproc()
funcpreproc.inputs.inputspec.start_idx = start_volume
funcpreproc.inputs.inputspec.stop_idx = stop_volume
regpreproc = create_reg_preproc()
regpreproc.inputs.inputspec.standard_res_brain = os.path.abspath(
'/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm_brain.nii.gz')
regpreproc.inputs.inputspec.standard = os.path.abspath(
'/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm.nii.gz')
regpreproc.inputs.inputspec.config_file = os.path.abspath(
'/usr/share/fsl/4.1/etc/flirtsch/T1_2_MNI152_3mm.cnf')
regpreproc.inputs.inputspec.standard_brain_mask_dil = os.path.abspath(
'/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm_brain_mask_dil.nii.gz')
segpreproc = create_seg_preproc()
segpreproc.inputs.inputspec.PRIOR_CSF = os.path.abspath(
datasource.inputs.template_args = dict(func=[['session_id', 'subject_id']],
struct=[['session_id', 'subject_id']])
datasink = pe.Node(nio.DataSink(infields=['container.@subject']), name='sinker')
datasink.inputs.base_directory = output_path
#datasink.inputs.substitutions = [('session\d_subject_id_', '')]
#st = pe.Node(interface=fsl.SliceTimer(), name='st')
#st.iterables = [('time_repetition', [2.0, 3.0])]
workflow = pe.Workflow(name='wf')
workflow.base_dir = output_path
anatpreproc=create_anat_preproc()
funcpreproc=create_func_preproc()
funcpreproc.inputs.inputspec.start_idx=start_volume
funcpreproc.inputs.inputspec.stop_idx=stop_volume
regpreproc=create_reg_preproc()
regpreproc.inputs.inputspec.standard_res_brain=os.path.abspath('/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm_brain.nii.gz')
regpreproc.inputs.inputspec.standard=os.path.abspath('/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm.nii.gz')
regpreproc.inputs.inputspec.config_file=os.path.abspath('/usr/share/fsl/4.1/etc/flirtsch/T1_2_MNI152_3mm.cnf')
regpreproc.inputs.inputspec.standard_brain_mask_dil=os.path.abspath('/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm_brain_mask_dil.nii.gz')
segpreproc=create_seg_preproc()
segpreproc.inputs.inputspec.PRIOR_CSF = os.path.abspath('./tissuepriors/3mm/avg152T1_csf_bin.nii.gz')
segpreproc.inputs.inputspec.PRIOR_WHITE = os.path.abspath('./tissuepriors/3mm/avg152T1_white_bin.nii.gz')
segpreproc.inputs.inputspec.PRIOR_GRAY = os.path.abspath('./tissuepriors/3mm/avg152T1_gray_bin_3mm.nii.gz')
segpreproc.inputs.inputspec.standard_res_brain=os.path.abspath('/usr/share/fsl/4.1/data/standard/MNI152_T1_3mm_brain.nii.gz')