.. AUTO-GENERATED FILE -- DO NOT EDIT!

.. _example_mri_plot:


Basic (f)MRI plotting
=====================

.. index:: plotting

Estimate basic univariate sensitivity (ANOVA) an plot it overlayed on top
of the anatomical.

We start with basic steps: loading PyMVPA and the example fMRI
dataset, basic preprocessing, estimation of the ANOVA scores and
plotting.

::
  
  from mvpa.suite import *
  
  # load PyMVPA example dataset
  attr = SampleAttributes(os.path.join(pymvpa_dataroot, 'attributes_literal.txt'))
  dataset = NiftiDataset(samples=os.path.join(pymvpa_dataroot, 'bold.nii.gz'),
                         labels=attr.labels,
                         labels_map=True,
                         chunks=attr.chunks,
                         mask=os.path.join(pymvpa_dataroot, 'mask.nii.gz'))
  
  # since we don't have a proper anatomical -- lets overlay on BOLD
  nianat = NiftiImage(dataset.O[0], header=dataset.niftihdr)
  
  # do chunkswise linear detrending on dataset
  detrend(dataset, perchunk=True, model='linear')
  
  # define sensitivity analyzer
  sensana = OneWayAnova(transformer=N.abs)
  sens = sensana(dataset)
  

It might be convinient to pre-define common arguments for multiple calls to
plotMRI

::
  mri_args = {
  	'background' : nianat,              # could be a filename
  	'background_mask' : os.path.join(pymvpa_dataroot, 'mask.nii.gz'),
  	'overlay_mask' : os.path.join(pymvpa_dataroot, 'mask.nii.gz'),
  	'do_stretch_colors' : False,
  	'cmap_bg' : 'gray',
  	'cmap_overlay' : 'autumn', # YlOrRd_r # P.cm.autumn
  	'fig' : None,              # create new figure
      'interactive' : cfg.getboolean('examples', 'interactive', True),
  	}
  
  fig = plotMRI(overlay=dataset.map2Nifti(sens),
                vlim=(0.5, None),
                #vlim_type="symneg_z",
                **mri_args)
  
  

Output of the example analysis:

.. image:: ../pics/ex_plotMRI.*
   :align: center
   :alt: Simple plotting facility for (f)MRI


.. seealso::
  The full source code of this example is included in the PyMVPA source distribution (`doc/examples/mri_plot.py`).
