[SciPy-user] stupid array tricks
Stéfan van der Walt
stefan@sun.ac...
Sat Feb 7 11:36:46 CST 2009
2009/2/7 Karl Young <karl.young@ucsf.edu>:
> I have three objects, 1) an array containing an "image" (could be any
> dimension), 2) a mask for the image (of the same dimensions as the
> image), and 3) a "template" which is just a list of offset coordinates
> from any point in the image.
You can create a strided view of the image, so that the values around
each position where the filter can be applied becomes a row.
Thereafter, using the indexing tricks shown at
http://mentat.za.net/numpy/numpy_advanced_slides/
index the view to produce the templated values at each position.
Say your template has length n, then you'd have:
template of shape (1, n)
rows = np.arange(m)[:, None] with shape (m, 1)
When using template and rows in a fancy indexing operating, you should
get an output of shape (m, n).
Here is a simplified example:
# Strided view of your image
In [25]: data
Out[25]:
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]])
In [26]: rows
Out[26]:
array([[0],
[1],
[2],
[3]])
In [27]: rows.shape
Out[27]: (4, 1)
In [28]: template
Out[28]: array([[0, 2]])
In [29]: template.shape
Out[29]: (1, 2)
In [30]: data[rows, template]
Out[30]:
array([[ 0, 2],
[ 3, 5],
[ 6, 8],
[ 9, 11]])
Hope that helps!
Cheers
Stéfan
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