old_contents: import unittest, os, scipy, glob, sets
  import numpy as N
  from neuroimaging.image import Image, interpolation
  from neuroimaging.visualization import viewer, slices
  from neuroimaging.visualization import arrayview
  from neuroimaging.reference import slices as rslices
  import pylab
  
  class VisualizationTest(unittest.TestCase):
  
      def setUp(self):
          url = 'http://kff.stanford.edu/~jtaylo/BrainSTAT/rho.img'
          self.img = Image(url)
  
      def test_view(self):
          view = viewer.BoxViewer(self.img, z_pix=80.)
          view.draw()
          pylab.show()
  
      def test_transversal_slice(self):
          self.interpolator = interpolation.ImageInterpolator(self.img)
          min = float(self.img.readall().min())
          max = float(self.img.readall().max())
          _slice = slices.transversal(self.img, z=0.,
            xlim=[-20,20.], ylim=[0,40.])
          x = slices.PylabDataSlice(self.interpolator, _slice, vmax=max, vmin=min,
            colormap='spectral', interpolation='nearest')
          x.width = 0.8; x.height = 0.8
          pylab.figure(figsize=(3,3))
          x.getaxes()
          pylab.imshow(x.RGBA(), origin=x.origin)
          pylab.show()
        
      def test_transversal_slice2(self):
          x = slices.PylabTransversal(self.img, y=3., xlim=[-49.,35.])
          x.width = 0.8; x.height = 0.8
          pylab.figure(figsize=(3,3))
          x.getaxes()
          pylab.imshow(x.RGBA(), origin=x.origin)
          pylab.show()
  
      def test_arrayview(self):
          from neuroimaging.visualization import arrayview
          arrayview.arrayview(self.img.buffer)
  
  def suite():
      return unittest.makeSuite(VisualizationTest)
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: import unittest, os, scipy, glob, sets
  import numpy as N
  from neuroimaging.tests.data import repository
  from neuroimaging.image import Image, interpolation
  from neuroimaging.visualization import viewer, slices
  from neuroimaging.visualization import arrayview
  from neuroimaging.reference import slices as rslices
  import pylab
  
  class VisualizationTest(unittest.TestCase):
  
      def setUp(self):
          self.img = Image(repository.filename("rho.img"))
  
      def test_view(self):
          view = viewer.BoxViewer(self.img, z_pix=80.)
          view.draw()
          pylab.show()
  
      def test_transversal_slice(self):
          self.interpolator = interpolation.ImageInterpolator(self.img)
          min = float(self.img.readall().min())
          max = float(self.img.readall().max())
          _slice = slices.transversal(self.img, z=0.,
            xlim=[-20,20.], ylim=[0,40.])
          x = slices.PylabDataSlice(self.interpolator, _slice, vmax=max, vmin=min,
            colormap='spectral', interpolation='nearest')
          x.width = 0.8; x.height = 0.8
          pylab.figure(figsize=(3,3))
          x.getaxes()
          pylab.imshow(x.RGBA(), origin=x.origin)
          pylab.show()
        
      def test_transversal_slice2(self):
          x = slices.PylabTransversal(self.img, y=3., xlim=[-49.,35.])
          x.width = 0.8; x.height = 0.8
          pylab.figure(figsize=(3,3))
          x.getaxes()
          pylab.imshow(x.RGBA(), origin=x.origin)
          pylab.show()
  
      def test_arrayview(self):
          from neuroimaging.visualization import arrayview
          arrayview.arrayview(self.img.buffer)
  
  def suite():
      return unittest.makeSuite(VisualizationTest)
  
  
  if __name__ == '__main__':
      unittest.main()
  
subject: migrate to use test data repository so test can be run offline