On 2009-02-17 14:36, Nick Matzke wrote:
Looks like "compress" is the right numpy function, but it took forever
for me to find it...
x = array([[1,2,3], [4,5,6], [7,8,9]], dtype=float)
compress([1,2], x, axis=1)
result:
array([[ 1., 2.],
[ 4., 5.],
[ 7., 8.]])
No, that's actually not correct. compress() takes a boolean mask, not integer
indices. It just happens to be the case that compress() implicitly appends
Falses to the end if the lengths don't match. Also, numpy indices are 0-indexed
just like most Python sequences.
If you need to specify integer indices, you need this:
In [4]: x[:,[0,1]]
Out[4]:
array([[ 1., 2.],
[ 4., 5.],
[ 7., 8.]])
If you have more numpy questions, you should ask on the numpy mailing list.
http://www.scipy.org/Mailing_Lists
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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