On Thu, Aug 5, 2010 at 1:12 PM, Martin Spacek <[email protected]> wrote:
> I want to take an n x m array "a" and index into it using an integer index
> array
> "i" of length n that will pull out the value at the designated column from
> each
> corresponding row of "a".
>
>>>> a = np.arange(10)
>>>> a.shape = 5, 2
>>>> a
> array([[0, 1],
> [2, 3],
> [4, 5],
> [6, 7],
> [8, 9]])
>>>> i = np.array([0, 1, 1, 0, 1])
>
> I want:
>
>>>> b = a.foo(i)
>>>> b
> array([0, 3, 5, 6, 9])
>
> What's foo? I can't get take() to do what I want. I went and wrote my own
> little
> Cython function to do this, but that seems silly (and is also array dtype
> dependent). I've tried reading through the numpy book, and I'm sure this is
> somewhere on the list, but I can't find it. I think it has something to do
> with
> fancy indexing. I should know how to do this by know...
like this ?
>>> a= np.array([[0, 1],
[2, 3],
[4, 5],
[6, 7],
[8, 9]])
>>> i = np.array([0, 1, 1, 0, 1])
>>> a[range(a.shape[0]), i]
array([0, 3, 5, 6, 9])
>>> a[np.arange(a.shape[0]), i]
array([0, 3, 5, 6, 9])
Josef
>
> Cheers,
>
> Martin
>
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