Merge branch 'master' of git+ssh://github.com/cython/cython

1 files changed, 44 insertions, 0 deletions

diff --git a/docs/examples/tutorial/numpy/convolve_py.py b/docs/examples/tutorial/numpy/convolve_py.py
new file mode 100644
index 000000000..547bae755
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+++ b/docs/examples/tutorial/numpy/convolve_py.py
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+from __future__ import division

+import numpy as np

+

+

+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