text: #! /usr/bin/env python
  """
  demonstration of bayseian inference between two mvn's
  aka "covariance intersection" 
  
  .. plot:: ./examples/blend.py main
  """
  
  import pylab
  
  
  
  from mvn import Mvn
  
  def main():
      """
      demonstrate the `covariance intersection algorithm
      <http://en.wikipedia.org/wiki/Kalman_filter#Update>`_ 
      """
      pylab.figure(1, figsize=(5,5))
      
      red  = Mvn.rand(shape=2)    
      blue = Mvn.rand(shape=2)
      
      magenta = red & blue
      
      red.plot(    facecolor = 'r')
      blue.plot(   facecolor = 'b')
      magenta.plot(facecolor = 'm')   
      
      pylab.xlabel('Magenta = Red & Blue')    
      pylab.show()
  
  if __name__ == '__main__':
      main()
  