After restructuring the project layout tree

scripts/cython_example.py

-# -*- 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
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