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diff --git a/scripts/cython_example.py b/scripts/cython_example.py
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index 6da48b0b1bb8cc47f67a39d8c66e47da8183bcce..0000000000000000000000000000000000000000
--- a/scripts/cython_example.py
+++ /dev/null
@@ -1,55 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Fri May 03 09:20:51 2013
-
-@author: Jan
-"""
-
-import cython
-import numpy as np
-
-
-n= 100
-A = np.array(range(n**2)).reshape((n,n))
-
-
-def naive_convolve(f, g):
- # f is an image and is indexed by (v, w)
- # g is a filter kernel and is indexed by (s, t),
- # it needs odd dimensions
- # h is the output image and is indexed by (x, y),
- # it is not cropped
- if g.shape[0] % 2 != 1 or g.shape[1] % 2 != 1:
- raise ValueError("Only odd dimensions on filter supported")
- # smid and tmid are number of pixels between the center pixel
- # and the edge, ie for a 5x5 filter they will be 2.
- #
- # The output size is calculated by adding smid, tmid to each
- # side of the dimensions of the input image.
- vmax = f.shape[0]
- wmax = f.shape[1]
- smax = g.shape[0]
- tmax = g.shape[1]
- smid = smax // 2
- tmid = tmax // 2
- xmax = vmax + 2*smid
- ymax = wmax + 2*tmid
- # Allocate result image.
- h = np.zeros([xmax, ymax], dtype=f.dtype)
- # Do convolution
- for x in range(xmax):
- for y in range(ymax):
- # Calculate pixel value for h at (x,y). Sum one component
- # for each pixel (s, t) of the filter g.
- s_from = max(smid - x, -smid)
- s_to = min((xmax - x) - smid, smid + 1)
- t_from = max(tmid - y, -tmid)
- t_to = min((ymax - y) - tmid, tmid + 1)
- value = 0
- for s in range(s_from, s_to):
- for t in range(t_from, t_to):
- v = x - smid + s
- w = y - tmid + t
- value += g[smid - s, tmid - t] * f[v, w]
- h[x, y] = value
- return h
\ No newline at end of file