Python write_graph示例

示例#1

文件： workshop_dartmouth_2010.py 项目： amoliu/nipype

"""
... and we can change a parameter and run it again. Only the dependent nodes
are rerun and that too only if the input state has changed.
"""

preproc.inputs.meanfuncmask.frac = 0.5
preproc.run()

"""
Visualizing workflows 1
-----------------------

So what did we run in this precanned workflow
"""

preproc.write_graph()

"""
Datasink
--------

Datasink is a special interface for copying and arranging results.
"""

import nipype.interfaces.io as nio

preproc.inputs.inputspec.func = os.path.abspath('data/s1/f3.nii')
preproc.inputs.inputspec.struct = os.path.abspath('data/s1/struct.nii')
datasink = pe.Node(interface=nio.DataSink(), name='sinker')
preprocess = pe.Workflow(name='preprocout')
preprocess.base_dir = os.path.abspath('.')

示例#2

preproc.run()
"""
... and we can change a parameter and run it again. Only the dependent nodes
are rerun and that too only if the input state has changed.
"""

preproc.inputs.meanfuncmask.frac = 0.5
preproc.run()
"""
Visualizing workflows 1
-----------------------

So what did we run in this precanned workflow
"""

preproc.write_graph()
"""
Datasink
--------

Datasink is a special interface for copying and arranging results.
"""

import nipype.interfaces.io as nio

preproc.inputs.inputspec.func = os.path.abspath('data/s1/f3.nii')
preproc.inputs.inputspec.struct = os.path.abspath('data/s1/struct.nii')
datasink = pe.Node(interface=nio.DataSink(), name='sinker')
preprocess = pe.Workflow(name='preprocout')
preprocess.base_dir = os.path.abspath('.')
preprocess.connect([(preproc, datasink, [('meanfunc2.out_file', 'meanfunc'),