Python create_tessellation_flow Examples

Example #1

File: tessellation_tutorial.py Project: sebastientourbier/nipype_lts5

lookup_file = op.join(fs_dir, 'FreeSurferColorLUT.txt')
subjects_dir = op.join(fs_dir, 'subjects/')
output_dir = './tessellate_tutorial'
"""
Inputs
======

Create the tessellation workflow and set inputs
Here we will choose Gifti (gii) as the output format, because
we want to able to view the surface in ConnectomeViewer.

In you intend to view the meshes in gmsh or Blender, you should change
the workflow creation to use stereolithographic (stl) format.
"""

tessflow = create_tessellation_flow(name='tessflow', out_format='gii')
tessflow.inputs.inputspec.subject_id = 'fsaverage'
tessflow.inputs.inputspec.subjects_dir = subjects_dir
tessflow.inputs.inputspec.lookup_file = lookup_file
"""
We also create a conditional node to package the surfaces for ConnectomeViewer.
Simply set cff to "False" to ignore this step.
"""

cff = True
if cff:
    cff = pe.Node(interface=cmtk.CFFConverter(), name='cff')
    cff.inputs.out_file = 'Meshes.cff'
"""
Outputs
=======

Example #2

File: dmri_connectivity_advanced.py Project: ChadCumba/nipype

giftiLabels = pe.Node(interface=util.Merge(2), name="GiftiLabels")
niftiVolumes = pe.Node(interface=util.Merge(3), name="NiftiVolumes")
fiberDataArrays = pe.Node(interface=util.Merge(4), name="FiberDataArrays")
gpickledNetworks = pe.Node(interface=util.Merge(2), name="NetworkFiles")

"""
We also create a workflow to calculate several network metrics on our resulting file, and another CFF converter
which will be used to package these networks into a single file.
"""

networkx = create_networkx_pipeline(name='networkx')
cmats_to_csv = create_cmats_to_csv_pipeline(name='cmats_to_csv')
NxStatsCFFConverter = pe.Node(interface=cmtk.CFFConverter(), name="NxStatsCFFConverter")
NxStatsCFFConverter.inputs.script_files = op.abspath(inspect.getfile(inspect.currentframe()))

tessflow = create_tessellation_flow(name='tessflow', out_format='gii')
tessflow.inputs.inputspec.lookup_file = lookup_file

"""
Connecting the workflow
=======================
Here we connect our processing pipeline.

Connecting the inputs, FreeSurfer nodes, and conversions
--------------------------------------------------------
"""

mapping = pe.Workflow(name='mapping')

"""
First, we connect the input node to the FreeSurfer input nodes.

Example #3

File: tessellation_tutorial.py Project: FNNDSC/nipype

Set the default directory and lookup table (LUT) paths
"""

fs_dir = os.environ['FREESURFER_HOME']
lookup_file = op.join(fs_dir,'FreeSurferColorLUT.txt')
subjects_dir = op.join(fs_dir, 'subjects/')
output_dir = './tessellate_tutorial'

"""
Inputs
======

Create the tessellation workflow and set inputs
"""

tessflow = create_tessellation_flow(name='tessflow')
tessflow.inputs.inputspec.subject_id = 'fsaverage'
tessflow.inputs.inputspec.subjects_dir = subjects_dir
tessflow.inputs.inputspec.lookup_file = lookup_file

"""
Outputs
=======

Create a datasink to organize the smoothed meshes
Using regular-expression substitutions we can remove the extraneous folders generated by the mapnode.
"""

datasink = pe.Node(interface=nio.DataSink(), name="datasink")
datasink.inputs.base_directory = 'meshes'
datasink.inputs.regexp_substitutions = [('_smoother[\d]*/', '')]

Example #4

File: dmri_connectivity_advanced.py Project: forgit/nipype

giftiLabels = pe.Node(interface=util.Merge(2), name="GiftiLabels")
niftiVolumes = pe.Node(interface=util.Merge(3), name="NiftiVolumes")
fiberDataArrays = pe.Node(interface=util.Merge(4), name="FiberDataArrays")
gpickledNetworks = pe.Node(interface=util.Merge(2), name="NetworkFiles")

"""
We also create a workflow to calculate several network metrics on our resulting file, and another CFF converter
which will be used to package these networks into a single file.
"""

networkx = create_networkx_pipeline(name="networkx")
cmats_to_csv = create_cmats_to_csv_pipeline(name="cmats_to_csv")
NxStatsCFFConverter = pe.Node(interface=cmtk.CFFConverter(), name="NxStatsCFFConverter")
NxStatsCFFConverter.inputs.script_files = op.abspath(inspect.getfile(inspect.currentframe()))

tessflow = create_tessellation_flow(name="tessflow", out_format="gii")
tessflow.inputs.inputspec.lookup_file = lookup_file

"""
Connecting the workflow
=======================
Here we connect our processing pipeline.

Connecting the inputs, FreeSurfer nodes, and conversions
--------------------------------------------------------
"""

mapping = pe.Workflow(name="mapping")

"""
First, we connect the input node to the FreeSurfer input nodes.

Example #5

File: tessellation_tutorial.py Project: connectthefuture/nipype

Set the default directory and lookup table (LUT) paths
"""

fs_dir = os.environ['FREESURFER_HOME']
lookup_file = op.join(fs_dir, 'FreeSurferColorLUT.txt')
subjects_dir = op.join(fs_dir, 'subjects/')
output_dir = './tessellate_tutorial'
"""
Inputs
======

Create the tessellation workflow and set inputs
"""

tessflow = create_tessellation_flow(name='tessflow')
tessflow.inputs.inputspec.subject_id = 'fsaverage'
tessflow.inputs.inputspec.subjects_dir = subjects_dir
tessflow.inputs.inputspec.lookup_file = lookup_file
"""
Outputs
=======

Create a datasink to organize the smoothed meshes
Using regular-expression substitutions we can remove the extraneous folders generated by the mapnode.
"""

datasink = pe.Node(interface=nio.DataSink(), name="datasink")
datasink.inputs.base_directory = 'meshes'
datasink.inputs.regexp_substitutions = [('_smoother[\d]*/', '')]
"""