Slicer3:Execution Model Documentation:Python

A Python interpreter has been integrated into Slicer3. This interpreter may be used to execute Python script plugins. The modules have a few specific requirements to be correctly found and used as plugins. Like the standard executable and shared library plugins, Python plugins need to be self describing. To do this, the script must have a top level variable called XML or provide a toXML procedure. For example:

XML = """<?xml version="1.0" encoding="utf-8"?>
<executable>
  <category>Filtering.Denoising</category>
  ...

def toXML():
  return XML;

Details of the XML format are found in the main Execution Model documentation. Rather than construct a command line to pass into Python, Slicer3 directly calls an Execute procedure. It is assumed that the Execute function expects positional arguments first, and any optional arguments are passed in as keyword arguments. For instance, the GradientAnisotropicDiffusion.py module provides an Execute:

def Execute ( inputVolume, outputVolume, conductance=1.0, timeStep=0.0625, iterations=1 ):
    print "Executing Python Demo Application!"
    Slicer = __import__ ( "Slicer" );
    slicer = Slicer.Slicer()
    in = slicer.MRMLScene.GetNodeByID ( inputVolume );
    out = slicer.MRMLScene.GetNodeByID ( outputVolume );

    filter = slicer.vtkITKGradientAnisotropicDiffusionImageFilter.New()
    filter.SetConductanceParameter ( conductance )
    filter.SetTimeStep ( timeStep )
    filter.SetNumberOfIterations ( iterations )
    filter.SetInput ( in.GetImageData() )
    filter.Update()
    out.SetAndObserveImageData(filter.GetOutput())
    return

The function first constructs a Slicer object by importing the Slicer module. The Slicer object is the main interface into Slicer3 as a whole. The first two arguments, inputVolume and outputVolume are not proper MRMLVolumes, and must be looked up using the Slicer object. The filter is constructed through the Slicer object, and the parameters are set. After the filter is updated, the output image is put using the SetAndObserverImageData method on the output volume.

ToDo

• Progress functionality
• Casting image arguments to proper MRML volume objects before calling Execute