import numpy

def dist(size):
   """
   title::
      dist

   description::
      This method will create a rectangular array (numpy.ndarray) in which 
      each element represents the distance from the upper left position -or- 
      in which each element is proportional to its frequency.  This method 
      is modeled directly after the IDL DIST function.

   attributes::
      size
         a scalar or 2-element tuple/list representing the square dimension
         or the (rows, columns) of the array to be producedi, respectively.

   author::
      Carl Salvaggio

   copyright::
      Copyright (C) 2014, Rochester Institute of Technology

   license::
      GPL

   version::
      1.0.0

   disclaimer::
      This source code is provided "as is" and without warranties as to 
      performance or merchantability. The author and/or distributors of 
      this source code may have made statements about this source code. 
      Any such statements do not constitute warranties and shall not be 
      relied on by the user in deciding whether to use this source code.
      
      This source code is provided without any express or implied warranties 
      whatsoever. Because of the diversity of conditions and hardware under 
      which this source code may be used, no warranty of fitness for a 
      particular purpose is offered. The user is advised to test the source 
      code thoroughly before relying on it. The user must assume the entire 
      risk of using the source code.
   """

   (rows, columns) = size if isinstance(size, (list, tuple)) else (size, size)

   x = numpy.arange(columns, dtype=numpy.float32)
   x = numpy.where(x < (columns-x), x**2, (columns-x)**2)
   a = numpy.zeros((rows, columns), dtype=numpy.float32)
   for i in range(rows/2+1):
      y = numpy.sqrt(x + i**2)
      a[i,:] = y
      if i != 0:
         a[rows-i,:] = y

   return a


if __name__ == '__main__':
   r = 5
   c = 3
   distanceArray = dist((r, c))
   print 'Distance array ...'
   print distanceArray
   print ''
   print 'Distance array (centered) ...'
   print numpy.roll(numpy.roll(distanceArray, r/2, axis=0), c/2, axis=1)

   s = 3
   distanceArray = dist(s)
   print 'Distance array ...'
   print distanceArray
   print ''
   print 'Distance array (centered) ...'
   print numpy.roll(numpy.roll(distanceArray, s/2, axis=0), s/2, axis=1)