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Kirill Smelkov
cython
Commits
422151fc
Commit
422151fc
authored
Jun 15, 2018
by
gabrieldemarmiesse
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Moved a first code snippet from numpy.rst to examples to enable testing.
parent
ff577a2b
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45 additions
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44 deletions
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-44
docs/examples/tutorial/numpy/convolve_py.py
docs/examples/tutorial/numpy/convolve_py.py
+44
-0
docs/src/tutorial/numpy.rst
docs/src/tutorial/numpy.rst
+1
-44
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docs/examples/tutorial/numpy/convolve_py.py
0 → 100644
View file @
422151fc
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
docs/src/tutorial/numpy.rst
View file @
422151fc
...
...
@@ -21,50 +21,7 @@ valid Python and valid Cython code. I'll refer to it as both
:file:`convolve_py.py` for the Python version and :file:`convolve1.pyx` for
the Cython version -- Cython uses ".pyx" as its file suffix.
.. code-block:: python
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
.. literalinclude:: ../../examples/tutorial/numpy/convolve_py.py
This should be compiled to produce :file:`yourmod.so` (for Linux systems). We
run a Python session to test both the Python version (imported from
...
...
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