def wbWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpBraintoFMRI', transform='nac2fmri')
    mask = maskNode(name='wholeBrainMask', fileName='wholeBrainMask.nii', low=0.5, high=1.0, flags=['largest'])
    avg = afninodes.maskavenode('AFNI_1D', name='afni3DmaskAve_whole')
    # Pipeline
    wb = pipe.Workflow(name='wb')
    wb.connect([(warp, mask, [('output_image', 'input_file')]),
                (mask, avg,  [('output_file', 'mask')]),
               ])
    return wb
def gmWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpGMtoFMRI', transform='t12fmri')
    mask = maskNode(name='grmMask', fileName='grmMask.nii', low=0.99, high=1.0)
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_grm')
    # Pipeline
    gm = pipe.Workflow(name='gm')
    gm.connect([(warp, mask, [('output_image', 'input_file')]),
                (mask, avg,  [('output_file', 'mask')]),
               ])
    return gm
def wmWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpWMtoFMRI', transform='t12fmri')
    mask = maskNode(name='wmMask', fileName='whiteMatterMask.nii', low=0.99, high=1.0, flags=['erode'])
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_wm')
    # Pipeline
    wm = pipe.Workflow(name='wm')
    wm.connect([(warp, mask, [('output_image', 'input_file')]),
                (mask, avg,  [('output_file', 'mask')]),
               ])
    return wm
def csfWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpCSFtoFMRI', transform='nac2fmri')
    mask = maskNode(name='csfMask', fileName='csfMask.nii', low=3, high=42, flags=['binary'])
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_csf')
    # Pipeline
    csf = pipe.Workflow(name='csf')
    csf.connect([(warp, mask, [('output_image', 'input_file')]),
                 (mask, avg,  [('output_file', 'mask')]),
                ])
    return csf
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def gmWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpGMtoFMRI', transform='t12fmri')
    mask = maskNode(name='grmMask', fileName='grmMask.nii', low=0.99, high=1.0)
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_grm')
    # Pipeline
    gm = pipe.Workflow(name='gm')
    gm.connect([
        (warp, mask, [('output_image', 'input_file')]),
        (mask, avg, [('output_file', 'mask')]),
    ])
    return gm
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def wbWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpBraintoFMRI', transform='nac2fmri')
    mask = maskNode(name='wholeBrainMask',
                    fileName='wholeBrainMask.nii',
                    low=0.5,
                    high=1.0,
                    flags=['largest'])
    avg = afninodes.maskavenode('AFNI_1D', name='afni3DmaskAve_whole')
    # Pipeline
    wb = pipe.Workflow(name='wb')
    wb.connect([
        (warp, mask, [('output_image', 'input_file')]),
        (mask, avg, [('output_file', 'mask')]),
    ])
    return wb
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def wmWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpWMtoFMRI', transform='t12fmri')
    mask = maskNode(name='wmMask',
                    fileName='whiteMatterMask.nii',
                    low=0.99,
                    high=1.0,
                    flags=['erode'])
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_wm')
    # Pipeline
    wm = pipe.Workflow(name='wm')
    wm.connect([
        (warp, mask, [('output_image', 'input_file')]),
        (mask, avg, [('output_file', 'mask')]),
    ])
    return wm
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def csfWorkflow():
    # Nodes
    warp = applyTransformNode(name='warpCSFtoFMRI', transform='nac2fmri')
    mask = maskNode(name='csfMask',
                    fileName='csfMask.nii',
                    low=3,
                    high=42,
                    flags=['binary'])
    avg = afninodes.maskavenode('AFNI_1D', 'afni3DmaskAve_csf')
    # Pipeline
    csf = pipe.Workflow(name='csf')
    csf.connect([
        (warp, mask, [('output_image', 'input_file')]),
        (mask, avg, [('output_file', 'mask')]),
    ])
    return csf