class_docstr: Generates Spherical Function PICo Calibration Data.
  
  SFPICOCalibData creates synthetic data for use with SFLUTGen. The
  synthetic data is generated using a mixture of gaussians, in the
  same way datasynth generates data.  Each voxel of data models a
  slightly different fibre configuration (varying FA and fibre-
  crossings) and undergoes a random rotation to help account for any
  directional bias in the chosen acquisition scheme.  A second file,
  which stores information about the datafile, is generated along with
  the datafile.
  
  Examples
  --------
  To create a calibration dataset using the default settings
  
  >>> import nipype.interfaces.camino as cam
  >>> calib = cam.SFPICOCalibData()
  >>> calib.inputs.scheme_file = 'A.scheme'
  >>> calib.inputs.snr = 20
  >>> calib.inputs.info_file = 'PICO_calib.info'
  >>> calib.run()           # doctest: +SKIP
  
  The default settings create a large dataset (249,231 voxels), of
  which 3401 voxels contain a single fibre population per voxel and
  the rest of the voxels contain two fibre-populations. The amount of
  data produced can be varied by specifying the ranges and steps of
  the parameters for both the one and two fibre datasets used.
  
  To create a custom calibration dataset
  
  >>> import nipype.interfaces.camino as cam
  >>> calib = cam.SFPICOCalibData()
  >>> calib.inputs.scheme_file = 'A.scheme'
  >>> calib.inputs.snr = 20
  >>> calib.inputs.info_file = 'PICO_calib.info'
  >>> calib.inputs.twodtfarange = [0.3, 0.9]
  >>> calib.inputs.twodtfastep = 0.02
  >>> calib.inputs.twodtanglerange = [0, 0.785]
  >>> calib.inputs.twodtanglestep = 0.03925
  >>> calib.inputs.twodtmixmax = 0.8
  >>> calib.inputs.twodtmixstep = 0.1
  >>> calib.run()              # doctest: +SKIP
  
  This would provide 76,313 voxels of synthetic data, where 3401 voxels
  simulate the one fibre cases and 72,912 voxels simulate the various
  two fibre cases. However, care should be taken to ensure that enough
  data is generated for calculating the LUT.      # doctest: +SKIP
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code: def _list_outputs(self):
      outputs = self.output_spec().get()
      outputs["PICOCalib"] = os.path.abspath(self._gen_outfilename())
      outputs["calib_info"] = os.path.abspath(self.inputs.info_file)
      return outputs
  
file_path: nipype/nipype/interfaces/camino/calib.py
imports: import os
  from ...utils.filemanip import split_filename
  from ..base import traits, TraitedSpec, File, StdOutCommandLine, StdOutCommandLineInputSpec
label_desc: Use image node_id 1 for calling the SFPICOCalibData obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs