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base.py
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import sys
import e_afni
import os
import commands
import nipype.pipeline.engine as pe
import nipype.algorithms.rapidart as ra
import nipype.interfaces.afni as afni
import nipype.interfaces.fsl as fsl
import nipype.interfaces.io as nio
import nipype.interfaces.utility as util
from utils import *
def create_filter(high_pass_filter_bool, low_pass_filter_bool):
preproc = pe.Workflow(name='frequency_filter')
inputNode = pe.Node(util.IdentityInterface(fields=['in_file']),
name='inputspec')
inputnode_hp = pe.Node(util.IdentityInterface(fields=['hp']),
name='hp_input')
inputnode_lp = pe.Node(util.IdentityInterface(fields=['lp']),
name='lp_input')
outputNode = pe.Node(util.IdentityInterface(fields=['rest_res_filt']),
name='outputspec')
filter = pe.MapNode(interface=afni.Fourier(),
name='func_filter',
iterfield=['in_file'])
filter.inputs.other = '-retrend'
preproc.connect(inputNode, 'in_file',
filter, 'in_file')
if(high_pass_filter_bool):
preproc.connect(inputnode_hp, 'hp',
filter, 'highpass')
if(low_pass_filter_bool):
preproc.connect(inputnode_lp, 'lp',
filter, 'lowpass')
preproc.connect(filter, 'out_file',
outputNode, 'rest_res_filt')
return preproc
def create_fmri_mni():
preproc = pe.Workflow(name='fmri_mnioutputs')
inputNode = pe.Node(util.IdentityInterface(fields=['reference_file',
'warp_file',
'premat',
'in_file']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['out_file']),
name='outputspec')
apply_warp = pe.MapNode(interface=fsl.ApplyWarp(),
name='apply_warp',
iterfield=['in_file', 'premat'])
preproc.connect(inputNode, 'in_file',
apply_warp, 'in_file')
preproc.connect(inputNode, 'warp_file',
apply_warp, 'field_file')
preproc.connect(inputNode, 'reference_file',
apply_warp, 'ref_file')
preproc.connect(inputNode, 'premat',
apply_warp, 'premat')
preproc.connect(apply_warp, 'out_file',
outputNode, 'out_file')
return preproc
def create_Tone_mni():
preproc = pe.Workflow(name='Tone_mnioutputs')
inputNode = pe.Node(util.IdentityInterface(fields=['reference_file',
'warp_file',
'in_file']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['out_file']),
name='outputspec')
apply_warp = pe.MapNode(interface=fsl.ApplyWarp(),
name='apply_warp',
iterfield=['in_file'])
preproc.connect(inputNode, 'in_file',
apply_warp, 'in_file')
preproc.connect(inputNode, 'warp_file',
apply_warp, 'field_file')
preproc.connect(inputNode, 'reference_file',
apply_warp, 'ref_file')
preproc.connect(apply_warp, 'out_file',
outputNode, 'out_file')
return preproc
def mprage_in_mnioutputs():
preproc = pe.Workflow(name='mprage_in_mnioutputs')
inputNode = pe.Node(util.IdentityInterface(fields=['reorient',
'brain',
'mixeltype',
'probability_maps',
'partial_volume_map',
'partial_volume_files',
'highres2standard_warp',
'standard']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['reorient_mni',
'brain_mni',
'mixeltype_mni',
'probability_maps_mni',
'partial_volume_map_mni',
'partial_volume_files_mni'
]),
name='outputspec')
r_mni = create_Tone_mni()
b_mni = r_mni.clone('brain_mni')
m_mni = r_mni.clone('mixeltype_mni')
p_maps_mni = r_mni.clone('probability_maps_in_mni')
pv_map_mni = r_mni.clone('partial_volume_map_mni')
pv_files_mni = r_mni.clone('partial_volume_files_mni')
preproc.connect(inputNode, 'reorient',
r_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
r_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
r_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'brain',
b_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
b_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
b_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'mixeltype',
m_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
m_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
m_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'probability_maps',
p_maps_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
p_maps_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
p_maps_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'partial_volume_map',
pv_map_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
pv_map_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
pv_map_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'partial_volume_files',
pv_files_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'standard',
pv_files_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'highres2standard_warp',
pv_files_mni, 'inputspec.warp_file')
preproc.connect(r_mni, 'outputspec.out_file',
outputNode, 'reorient_mni')
preproc.connect(b_mni, 'outputspec.out_file',
outputNode, 'brain_mni')
preproc.connect(m_mni, 'outputspec.out_file',
outputNode, 'mixeltype_mni')
preproc.connect(p_maps_mni, 'outputspec.out_file',
outputNode, 'probability_maps_mni')
preproc.connect(pv_map_mni, 'outputspec.out_file',
outputNode, 'partial_volume_map_mni')
preproc.connect(pv_files_mni, 'outputspec.out_file',
outputNode, 'partial_volume_files_mni')
return preproc
def func_in_mnioutputs():
preproc = pe.Workflow(name='func_in_mnioutputs')
inputNode = pe.Node(util.IdentityInterface(fields=['residual_file',
'highres2standard_warp',
'premat',
'standard',
'preprocessed_mask']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['residual_file_mni',
'preprocessed_mask_mni'
]),
name='outputspec')
residual_mni = create_fmri_mni()
pm_mni = residual_mni.clone('pm_mni')
preproc.connect(inputNode, 'residual_file',
residual_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'highres2standard_warp',
residual_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'standard',
residual_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'premat',
residual_mni, 'inputspec.premat')
preproc.connect(inputNode, 'preprocessed_mask',
pm_mni, 'inputspec.in_file')
preproc.connect(inputNode, 'highres2standard_warp',
pm_mni, 'inputspec.warp_file')
preproc.connect(inputNode, 'standard',
pm_mni, 'inputspec.reference_file')
preproc.connect(inputNode, 'premat',
pm_mni, 'inputspec.premat')
preproc.connect(residual_mni, 'outputspec.out_file',
outputNode, 'residual_file_mni')
preproc.connect(pm_mni, 'outputspec.out_file',
outputNode, 'preprocessed_mask_mni')
return preproc
def create_anat_preproc():
preproc = pe.Workflow(name='anatpreproc')
#Node or Node ?
inputNode = pe.Node(util.IdentityInterface(fields=['anat']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['refit',
'reorient',
'skullstrip',
'brain']),
name='outputspec')
anat_refit = pe.Node(interface=e_afni.Threedrefit(),
name='anat_refit')
anat_refit.inputs.deoblique = True
anat_reorient = pe.Node(interface=afni.Resample(),
name='anat_reorient')
anat_reorient.inputs.orientation = 'RPI'
anat_skullstrip = pe.Node(interface=afni.SkullStrip(),
name='anat_skullstrip')
anat_skullstrip.inputs.options = '-o_ply'
anat_calc = pe.Node(interface=e_afni.Threedcalc(),
name='anat_calc')
anat_calc.inputs.expr = '\'a*step(b)\''
preproc.connect(inputNode, 'anat',
anat_refit, 'in_file')
preproc.connect(anat_refit, 'out_file',
anat_reorient, 'in_file')
preproc.connect(anat_reorient, 'out_file',
anat_skullstrip, 'in_file')
preproc.connect(anat_skullstrip, 'out_file',
anat_calc, 'infile_b')
preproc.connect(anat_reorient, 'out_file',
anat_calc, 'infile_a')
preproc.connect(anat_refit, 'out_file',
outputNode, 'refit')
preproc.connect(anat_reorient, 'out_file',
outputNode, 'reorient')
preproc.connect(anat_skullstrip, 'out_file',
outputNode, 'skullstrip')
preproc.connect(anat_calc, 'out_file',
outputNode, 'brain')
return preproc
def create_func_preproc():
preproc = pe.Workflow(name='funcpreproc')
inputNode = pe.Node(util.IdentityInterface(fields=['rest',
'start_idx',
'stop_idx']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['drop_tr',
'refit',
'reorient',
'reorient_mean',
'motion_correct',
'motion_correct_ref',
'movement_parameters',
'max_displacement',
'mask',
'skullstrip',
'example_func',
'preprocessed',
'preprocessed_mask']),
name='outputspec')
func_idx = pe.MapNode(util.Function(input_names=['in_files', 'stop_idx', 'start_idx'],
output_names=['stopidx', 'startidx'],
function=get_idx), name='func_idx',
iterfield=['in_files'])
func_calc = pe.MapNode(interface=e_afni.Threedcalc(),
name='func_calc',
iterfield=['infile_a', 'stop_idx', 'start_idx'])
func_calc.inputs.expr = '\'a\''
func_refit = pe.MapNode(interface=e_afni.Threedrefit(),
name='func_refit',
iterfield=['in_file'])
func_refit.inputs.deoblique = True
func_reorient = pe.MapNode(interface=afni.Resample(),
name='func_reorient',
iterfield=['in_file'])
func_reorient.inputs.orientation = 'RPI'
func_tstat = pe.MapNode(interface=afni.TStat(),
name='func_tstat',
iterfield=['in_file'])
func_tstat.inputs.options = '-mean'
func_tstat_1 = func_tstat.clone('func_tstat_1')
func_volreg = pe.MapNode(interface=e_afni.Threedvolreg(),
name='func_volreg',
iterfield=['in_file', 'basefile'])
func_volreg.inputs.other = '-Fourier -twopass'
func_volreg.inputs.zpad = '4'
func_volreg_1 = func_volreg.clone('func_volreg_1')
func_automask = pe.MapNode(interface=e_afni.ThreedAutomask(),
name='func_automask',
iterfield=['in_file'])
func_automask.inputs.dilate = 1
func_calcR = pe.MapNode(interface=e_afni.Threedcalc(),
name='func_calcR',
iterfield=['infile_a', 'infile_b'])
func_calcR.inputs.expr = '\'a*b\''
func_mean = pe.MapNode(interface=afni.TStat(),
name='func_mean',
iterfield=['in_file'])
func_mean.inputs.options = '-mean'
func_scale = pe.MapNode(interface=fsl.ImageMaths(),
name='func_scale',
iterfield=['in_file'])
func_scale.inputs.op_string = '-ing 10000'
func_scale.inputs.out_data_type = 'float'
func_mask = pe.MapNode(interface=fsl.ImageMaths(),
name='func_mask',
iterfield=['in_file'])
func_mask.inputs.op_string = '-Tmin -bin'
func_mask.inputs.out_data_type = 'char'
preproc.connect(inputNode, 'rest',
func_idx, 'in_files')
preproc.connect(inputNode, 'start_idx',
func_idx, 'start_idx')
preproc.connect(inputNode, 'stop_idx',
func_idx, 'stop_idx')
preproc.connect(inputNode, 'rest',
func_calc, 'infile_a')
preproc.connect(func_idx, 'startidx',
func_calc, 'start_idx')
preproc.connect(func_idx, 'stopidx',
func_calc, 'stop_idx')
preproc.connect(func_calc, 'out_file',
func_refit, 'in_file')
preproc.connect(func_refit, 'out_file',
func_reorient, 'in_file')
preproc.connect(func_reorient, 'out_file',
func_tstat, 'in_file')
preproc.connect(func_reorient, 'out_file',
func_volreg, 'in_file')
preproc.connect(func_tstat, 'out_file',
func_volreg, 'basefile')
preproc.connect(func_volreg, 'out_file',
func_tstat_1, 'in_file')
preproc.connect(func_reorient, 'out_file',
func_volreg_1, 'in_file')
preproc.connect(func_tstat_1, 'out_file',
func_volreg_1, 'basefile')
preproc.connect(func_volreg_1, 'out_file',
func_automask, 'in_file')
preproc.connect(func_volreg_1, 'out_file',
func_calcR, 'infile_a')
preproc.connect(func_automask, 'out_file',
func_calcR, 'infile_b')
preproc.connect(func_calcR, 'out_file',
func_mean, 'in_file')
preproc.connect(func_calcR, 'out_file',
func_scale, 'in_file')
preproc.connect(func_scale, 'out_file',
func_mask, 'in_file')
preproc.connect(func_calc, 'out_file',
outputNode, 'drop_tr')
preproc.connect(func_refit, 'out_file',
outputNode, 'refit')
preproc.connect(func_reorient, 'out_file',
outputNode, 'reorient')
preproc.connect(func_tstat_1, 'out_file',
outputNode, 'motion_correct_ref')
preproc.connect(func_volreg_1, 'out_file',
outputNode, 'motion_correct')
preproc.connect(func_volreg_1, 'md1d_file',
outputNode, 'max_displacement')
preproc.connect(func_volreg_1, 'oned_file',
outputNode, 'movement_parameters')
preproc.connect(func_automask, 'out_file',
outputNode, 'mask')
preproc.connect(func_calcR, 'out_file',
outputNode, 'skullstrip')
preproc.connect(func_mean, 'out_file',
outputNode, 'example_func')
preproc.connect(func_scale, 'out_file',
outputNode, 'preprocessed')
preproc.connect(func_mask, 'out_file',
outputNode, 'preprocessed_mask')
return preproc
def create_reg_preproc():
preproc = pe.Workflow(name='regpreproc')
inputNode = pe.Node(util.IdentityInterface(fields=['example_func',
'brain',
'standard_res_brain',
'reorient',
'standard',
'standard_brain_mask_dil',
'config_file']),
name='inputspec')
outputNode = pe.Node(util.IdentityInterface(fields=['example_func2highres',
'example_func2highres_mat',
'highres2example_func_mat',
'highres2standard',
'highres2standard_mat',
'standard2highres_mat',
'highres2standard_warp',
'highres2standard_NL',
'highres2standard_jac',
'stand2highres_warp',
'example_func2standard_NL']),
name='outputspec')
reg_flirt = pe.MapNode(interface=fsl.FLIRT(),
name='reg_flirt',
iterfield=['in_file'])
reg_flirt.inputs.cost = 'corratio'
reg_flirt.inputs.dof = 6
reg_flirt.inputs.interp = 'nearestneighbour'
# Create mat file for conversion from subject's anatomical to functional
reg_xfm1 = pe.MapNode(interface=fsl.ConvertXFM(),
name='reg_xfm1',
iterfield=['in_file'])
reg_xfm1.inputs.invert_xfm = True
## T1->STANDARD
## NOTE THAT THIS IS Linear registration,
## you may want to use FNIRT (non-linear)
reg_flirt1 = pe.Node(interface=fsl.FLIRT(),
name='reg_flirt1')
reg_flirt1.inputs.cost = 'corratio'
reg_flirt1.inputs.cost_func = 'corratio'
reg_flirt1.inputs.dof = 12
reg_flirt1.inputs.interp = 'nearestneighbour'
## Create mat file for conversion from standard to high res
reg_xfm2 = pe.Node(interface=fsl.ConvertXFM(),
name='reg_xfm2')
reg_xfm2.inputs.invert_xfm = True
reg_inw = pe.Node(interface=e_afni.InvWarp(),
name='reg_inw')
## T1->STANDARD NONLINEAR
# Perform nonlinear registration (higres to standard)
reg_fnt = pe.Node(interface=fsl.FNIRT(),
name='reg_fnt')
reg_fnt.inputs.fieldcoeff_file = True
reg_fnt.inputs.jacobian_file = True
reg_fnt.inputs.warp_resolution = (10, 10, 10)
## Apply nonlinear registration (func to standard)
reg_warp = pe.MapNode(interface=fsl.ApplyWarp(),
name='reg_warp',
iterfield=['in_file',
'premat'
])
preproc.connect(inputNode, 'example_func',
reg_flirt, 'in_file')
preproc.connect(inputNode, 'brain',
reg_flirt, 'reference')
preproc.connect(reg_flirt, 'out_matrix_file',
reg_xfm1, 'in_file')
preproc.connect(inputNode, 'brain',
reg_flirt1, 'in_file')
preproc.connect(inputNode, 'standard_res_brain',
reg_flirt1, 'reference')
preproc.connect(reg_flirt1, 'out_matrix_file',
reg_xfm2, 'in_file')
preproc.connect(inputNode, 'reorient',
reg_fnt, 'in_file')
preproc.connect(reg_flirt1, 'out_matrix_file',
reg_fnt, 'affine_file')
preproc.connect(inputNode, 'standard',
reg_fnt, 'ref_file')
preproc.connect(inputNode, 'standard_brain_mask_dil',
reg_fnt, 'refmask_file')
preproc.connect(inputNode, 'config_file',
reg_fnt, 'config_file')
preproc.connect(reg_fnt, 'fieldcoeff_file',
reg_inw, 'in_file')
preproc.connect(inputNode, 'brain',
reg_inw, 'ref_file')
preproc.connect(inputNode, 'example_func',
reg_warp, 'in_file')
preproc.connect(inputNode, 'standard',
reg_warp, 'ref_file')
preproc.connect(reg_fnt, 'fieldcoeff_file',
reg_warp, 'field_file')
preproc.connect(reg_flirt, 'out_matrix_file',
reg_warp, 'premat')
preproc.connect(reg_flirt, 'out_file',
outputNode, 'example_func2highres')
preproc.connect(reg_flirt, 'out_matrix_file',
outputNode, 'example_func2highres_mat')
preproc.connect(reg_xfm1, 'out_file',
outputNode, 'highres2example_func_mat')
preproc.connect(reg_warp, 'out_file',
outputNode, 'example_func2standard_NL')
preproc.connect(reg_flirt1, 'out_file',
outputNode, 'highres2standard')
preproc.connect(reg_flirt1, 'out_matrix_file',
outputNode, 'highres2standard_mat')
preproc.connect(reg_inw, 'out_file',
outputNode, 'stand2highres_warp')
preproc.connect(reg_fnt, 'jacobian_file',
outputNode, 'highres2standard_jac')
preproc.connect(reg_fnt, 'fieldcoeff_file',
outputNode, 'highres2standard_warp')
preproc.connect(reg_fnt, 'warped_file',
outputNode, 'highres2standard_NL')
return preproc
def create_seg_preproc():
preproc = pe.Workflow(name='segpreproc')
inputNode = pe.Node(util.IdentityInterface(fields=['preprocessed_mask',
'brain',
'standard_res_brain',
'example_func',
'highres2example_func_mat',
'stand2highres_warp',
'PRIOR_CSF',
'PRIOR_GRAY',
'PRIOR_WHITE']),
name='inputspec')
inputnode_csf_threshold = pe.Node(util.IdentityInterface(
fields=['csf_threshold']),
name='csf_threshold')
inputnode_wm_threshold = pe.Node(util.IdentityInterface(
fields=['wm_threshold']),
name='wm_threshold')
inputnode_gm_threshold = pe.Node(util.IdentityInterface(
fields=['gm_threshold']),
name='gm_threshold')
outputNode = pe.Node(util.IdentityInterface(fields=['csf_t12func',
'csf_mni2func',
'csf_combo',
'csf_bin',
'csf_mask',
'gm_t12func',
'gm_mni2func',
'gm_combo',
'gm_bin',
'gm_mask',
'global_mask',
'wm_t12func',
'wm_mni2func',
'wm_combo',
'wm_bin',
'probability_maps',
'mixeltype',
'partial_volume_map',
'partial_volume_files',
'wm_mask']),
name='outputspec')
def form_threshold_string(threshold):
return '-thr %f -bin ' % (threshold)
seg_segment = pe.Node(interface=fsl.FAST(),
name='seg_segment')
seg_segment.inputs.img_type = 1
seg_segment.inputs.segments = True
seg_segment.inputs.probability_maps = True
seg_segment.inputs.out_basename = 'segment'
seg_copy = pe.MapNode(interface=afni.Copy(),
name='seg_copy',
iterfield=['in_file'])
seg_flirt = pe.MapNode(interface=fsl.FLIRT(),
name='seg_flirt',
iterfield=['reference',
'in_matrix_file'])
seg_flirt.inputs.apply_xfm = True
seg_warp = pe.MapNode(interface=fsl.ApplyWarp(),
name='seg_warp',
iterfield=['ref_file',
'postmat'])
seg_warp.inputs.interp = 'nn'
seg_warp1 = seg_warp.clone('seg_warp1')
seg_smooth1 = pe.MapNode(interface=fsl.MultiImageMaths(),
name='seg_smooth1',
iterfield=['in_file',
'operand_files'])
seg_str1 = '-mas %s '
seg_smooth1.inputs.op_string = seg_str1
seg_thresh = pe.MapNode(interface=fsl.ImageMaths(),
name='seg_thresh',
iterfield=['in_file'])
seg_mask = pe.MapNode(interface=fsl.MultiImageMaths(),
name='seg_mask',
iterfield=['in_file',
'operand_files'])
seg_str1 = '-mas %s '
seg_mask.inputs.op_string = seg_str1
seg_prior1 = pe.MapNode(interface=fsl.MultiImageMaths(),
name='seg_prior1',
iterfield=['in_file',
'operand_files'])
seg_str1 = '-mas %s '
seg_prior1.inputs.op_string = seg_str1
seg_thresh1 = pe.MapNode(interface=fsl.ImageMaths(),
name='seg_thresh1',
iterfield=['in_file'])
#seg_str1 = '-thr 0.66 -bin '
#seg_thresh1.inputs.op_string = seg_str1
seg_flirt3 = pe.MapNode(interface=fsl.FLIRT(),
name='seg_flirt3',
iterfield=['reference',
'in_matrix_file'])
seg_flirt3.inputs.apply_xfm = True
seg_mask1 = seg_mask.clone('seg_mask1')
seg_flirt4 = seg_flirt3.clone('seg_flirt4')
seg_thresh2 = seg_thresh.clone('seg_thresh2')
#seg_thresh2.inputs.op_string = '-thr 0.2 -bin '
seg_warp2 = seg_warp1.clone('seg_warp2')
seg_prior2 = seg_prior1.clone('seg_prior2')
seg_mask2 = seg_mask.clone('seg_mask2')
preproc.connect(inputNode, 'brain',
seg_segment, 'in_files')
preproc.connect(seg_segment, ('probability_maps', pick_wm_0),
seg_flirt, 'in_file')
preproc.connect(inputNode, 'example_func',
seg_flirt, 'reference')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_flirt, 'in_matrix_file')
preproc.connect(inputNode, 'example_func',
seg_warp, 'ref_file')
preproc.connect(inputNode, 'stand2highres_warp',
seg_warp, 'field_file')
preproc.connect(inputNode, 'PRIOR_CSF',
seg_warp, 'in_file')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_warp, 'postmat')
preproc.connect(seg_flirt, 'out_file',
seg_smooth1, 'in_file')
preproc.connect(seg_warp, 'out_file',
seg_smooth1, 'operand_files')
preproc.connect(seg_smooth1, 'out_file',
seg_thresh, 'in_file')
preproc.connect(inputnode_csf_threshold,
('csf_threshold', form_threshold_string),
seg_thresh, 'op_string')
preproc.connect(seg_thresh, 'out_file',
seg_mask, 'in_file')
preproc.connect(inputNode, 'preprocessed_mask',
seg_copy, 'in_file')
preproc.connect(seg_copy, 'out_file',
seg_mask, 'operand_files')
preproc.connect(seg_segment,
('probability_maps', pick_wm_2),
seg_flirt3, 'in_file')
preproc.connect(inputNode, 'example_func',
seg_flirt3, 'reference')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_flirt3, 'in_matrix_file')
preproc.connect(inputNode, 'example_func',
seg_warp1, 'ref_file')
preproc.connect(inputNode, 'stand2highres_warp',
seg_warp1, 'field_file')
preproc.connect(inputNode, 'PRIOR_WHITE',
seg_warp1, 'in_file')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_warp1, 'postmat')
preproc.connect(seg_flirt3, 'out_file',
seg_prior1, 'in_file')
preproc.connect(seg_warp1, 'out_file',
seg_prior1, 'operand_files')
preproc.connect(seg_prior1, 'out_file',
seg_thresh1, 'in_file')
preproc.connect(inputnode_wm_threshold,
('wm_threshold', form_threshold_string),
seg_thresh1, 'op_string')
preproc.connect(seg_thresh1, 'out_file',
seg_mask1, 'in_file')
preproc.connect(seg_copy, 'out_file',
seg_mask1, 'operand_files')
##gray matter mask
preproc.connect(seg_segment,
('probability_maps', pick_wm_1),
seg_flirt4, 'in_file')
preproc.connect(inputNode, 'example_func',
seg_flirt4, 'reference')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_flirt4, 'in_matrix_file')
preproc.connect(inputNode, 'example_func',
seg_warp2, 'ref_file')
preproc.connect(inputNode, 'stand2highres_warp',
seg_warp2, 'field_file')
preproc.connect(inputNode, 'PRIOR_GRAY',
seg_warp2, 'in_file')
preproc.connect(inputNode, 'highres2example_func_mat',
seg_warp2, 'postmat')
preproc.connect(seg_flirt4, 'out_file',
seg_prior2, 'in_file')
preproc.connect(seg_warp2, 'out_file',
seg_prior2, 'operand_files')
preproc.connect(seg_prior2, 'out_file',
seg_thresh2, 'in_file')
preproc.connect(inputnode_gm_threshold,
('gm_threshold', form_threshold_string),
seg_thresh2, 'op_string')
preproc.connect(seg_thresh2, 'out_file',
seg_mask2, 'in_file')
preproc.connect(seg_copy, 'out_file',
seg_mask2, 'operand_files')
preproc.connect(seg_segment, 'probability_maps',
outputNode, 'probability_maps')
preproc.connect(seg_segment, 'mixeltype',
outputNode, 'mixeltype')
preproc.connect(seg_segment, 'partial_volume_files',
outputNode, 'partial_volume_files')
preproc.connect(seg_segment, 'partial_volume_map',
outputNode, 'partial_volume_map')
preproc.connect(seg_flirt, 'out_file',
outputNode, 'csf_t12func')
preproc.connect(seg_warp, 'out_file',
outputNode, 'csf_mni2func')
preproc.connect(seg_smooth1, 'out_file',
outputNode, 'csf_combo')
preproc.connect(seg_thresh, 'out_file',
outputNode, 'csf_bin')
preproc.connect(seg_mask, 'out_file',
outputNode, 'csf_mask')
preproc.connect(seg_copy, 'out_file',
outputNode, 'global_mask')
preproc.connect(seg_flirt3, 'out_file',
outputNode, 'wm_t12func')
preproc.connect(seg_warp1, 'out_file',
outputNode, 'wm_mni2func')
preproc.connect(seg_prior1, 'out_file',
outputNode, 'wm_combo')
preproc.connect(seg_thresh1, 'out_file',
outputNode, 'wm_bin')
preproc.connect(seg_mask1, 'out_file',
outputNode, 'wm_mask')
preproc.connect(seg_flirt4, 'out_file',
outputNode, 'gm_t12func')
preproc.connect(seg_warp2, 'out_file',
outputNode, 'gm_mni2func')
preproc.connect(seg_prior2, 'out_file',
outputNode, 'gm_combo')
preproc.connect(seg_thresh2, 'out_file',
outputNode, 'gm_bin')
preproc.connect(seg_mask2, 'out_file',
outputNode, 'gm_mask')
return preproc
def create_parameters_preproc(c):
sc = pe.Workflow(name='param_preproc')
inputNode = pe.Node(util.IdentityInterface(fields=['subject_id',
'session_id',
'rest',
'movement_parameters',
'max_displacement'
]),
name='inputspec')
inputnode_threshold = pe.Node(util.IdentityInterface(fields=['threshold']),
name='threshold_input')
outputNode = pe.Node(util.IdentityInterface(fields=['mean_deriv_sq_1D',
'mean_raw_sq_1D',
'temp_deriv_brik_file',
'temp_deriv_head_file',
'temp_deriv_sq_brik_file',
'temp_deriv_sq_head_file',
'raw_sq_brik_file',
'raw_sq_head_file',
'mask_brik_file',
'mask_head_file',
'FD_1D',
'sqrt_mean_deriv_sq_1D',
'sqrt_mean_raw_sq_1D',
'frames_ex_1D',
'frames_in_1D',
'power_params',
'motion_params',
'ftof_percent_change_1D']),
name='outputspec')
NVOLS = pe.Node(util.Function(input_names=['in_files', 'stopIdx', 'startIdx'],
output_names=['nvols'],
function=getImgNVols),
name='NVOLS')
NVOLS.inputs.stopIdx = c.stopIdx
NVOLS.inputs.startIdx = c.startIdx
last = pe.MapNode(util.Function(input_names=['nvols', 'stopIdx', 'startIdx'],
output_names=['last_volume'],
function=last_vol),
name='last',
iterfield=['nvols'])
last.inputs.stopIdx = c.stopIdx
last.inputs.startIdx = c.startIdx
last_minus_one = pe.MapNode(util.Function(input_names=['nvols', 'stopIdx', 'startIdx'],
output_names=['last_vol_minus_one'],
function=TRendminus1),
name='last_minus_one',
iterfield=['nvols'])
last_minus_one.inputs.startIdx = c.startIdx
last_minus_one.inputs.stopIdx = c.stopIdx
sc_createSC = pe.MapNode(util.Function(input_names=['in_file'],
output_names=['out_file'],
function=createSC),
name='sc_createSC',
iterfield=["in_file"])
sc_FramesEx = pe.MapNode(util.Function(input_names=['in_file', 'threshold'],
output_names=['out_file'],
function=setFramesEx),
name='sc_FramesEx',
iterfield=["in_file"])
sc_FramesIN = pe.MapNode(util.Function(input_names=['in_file', 'threshold', 'exclude_list'],
output_names=['out_file'],
function=setFramesIN),
name='sc_FramesIN',
iterfield=["in_file", "exclude_list"])
sc_FtoFPercentChange = pe.MapNode(util.Function(input_names=['infile_a', 'infile_b'],
output_names=['out_file'],
function=setFtoFPercentChange),
name='sc_FtoFPercentChange',
iterfield=["infile_a", "infile_b"])
sc_SqrtMeanDeriv = pe.MapNode(util.Function(input_names=['in_file'], output_names=['out_file'],
function=setSqrtMeanDeriv),
name='sc_SqrtMeanDeriv',
iterfield=["in_file"])
sc_SqrtMeanRaw = pe.MapNode(util.Function(input_names=['in_file'],
output_names=['out_file'],
function=setSqrtMeanRaw),
name='sc_SqrtMeanRaw',
iterfield=["in_file"])
sc_calc1 = pe.MapNode(interface=e_afni.Threedcalc(),
name='sc_calc1',
iterfield=["infile_a", "stop_idx", "infile_b", "stop_idx2"])
sc_calc1.inputs.start_idx = 4
sc_calc1.inputs.start_idx2 = 3
sc_calc1.inputs.expr = '\'(a-b)\''
sc_calc1.inputs.out_file = 'temp_deriv'
sc_calc2 = pe.MapNode(interface=e_afni.Threedcalc(),
name='sc_calc2',
iterfield=["infile_a"])
sc_calc2.inputs.expr = '\'a*a\''
sc_calc2.inputs.out_file = 'temp_deriv_sq'
sc_calc3 = pe.MapNode(interface=e_afni.Threedcalc(),
name='sc_calc3',
iterfield=["infile_a", "stop_idx"])
sc_calc3.inputs.start_idx = 3
sc_calc3.inputs.expr = '\'a*a\''
sc_calc3.inputs.out_file = 'raw_sq'
sc_automask = pe.MapNode(interface=e_afni.ThreedAutomask(),
name='sc_automask',
iterfield=["in_file"])
sc_automask.inputs.dilate = 1
sc_automask.inputs.genbrickhead = True
sc_automask.inputs.out_file = './mask'
sc_3dROIstats_1 = pe.MapNode(interface=e_afni.ThreedROIstats(),
name='sc_3dROIstats_1',
iterfield=["in_file", "mask"])
sc_3dROIstats_1.inputs.quiet = True
sc_3dROIstats_2 = pe.MapNode(interface=e_afni.ThreedROIstats(),
name='sc_3dROIstats_2',
iterfield=["in_file", "mask"])
sc_3dROIstats_2.inputs.quiet = True
sc_MotionParameters = pe.MapNode(util.Function(input_names=["subject_id","session_id", "rest", "movement_parameters",
"max_displacement"],
output_names=['out_file'],
function=generateMotionParameters),
name='sc_MotionParameters',
iterfield=["rest",
"movement_parameters",
"max_displacement"])
sc_PowerParameters = pe.MapNode(util.Function(input_names=["rest", "FD_1D", "threshold",
"ftof_percent", "sqrt_mean_raw"],
output_names=['out_file'],
function=generatePowerParams),
name='sc_PowerParameters',
iterfield=["rest", "FD_1D",
"ftof_percent",
"sqrt_mean_raw"])
sc.connect(inputNode, 'rest', NVOLS, 'in_files')
sc.connect(inputNode, 'rest', sc_calc1, 'infile_a')
sc.connect(inputNode, 'rest', sc_calc1, 'infile_b')
sc.connect(NVOLS, 'nvols', last, 'nvols')