dilate-naive-square.py

def dilate_naive(x, k):
  m,n = x.shape
  y = np.empty_like(x)
  for i in xrange(m):
    for j in xrange(n):
      currmax = x[i,j]
      for ii in xrange(max(0, i-k/2), min(m, i+k/2+1)):
        for jj in xrange(max(0, j-k/2), min(n, j+k/2+1)):
          elt = x[ii,jj]
          if elt > currmax:
            currmax = elt
      y[i,j] = currmax
  return y