[Numpy-discussion] Reductions with nditer working only with the last axis

[Han Genuit]

On Thu, Sep 27, 2012 at 6:08 PM, Sergio Pascual <sergio.pasra at gmail.com> wrote:
> Hello, I'm trying to understand how to work with nditer to do a
> reduction, in my case converting a 3d array into a 2d array.
>
> I followed the help here
> http://docs.scipy.org/doc/numpy/reference/arrays.nditer.html and
> managed to create a function that applies reduction over the last axis
> of the input. With this function
>
> def nditer_sum(data, red_axes):
>     it = numpy.nditer([data, None],
>                 flags=['reduce_ok', 'external_loop'],
>                 op_flags=[['readonly'], ['readwrite', 'allocate']],
>                 op_axes=[None, red_axes])
>     it.operands[1][...] = 0
>
>     for x, y in it:
>         y[...] = x.sum()
>
>     return it.operands[1]
>
> I can get something equivalent to data.sum(axis=2)
>
>>>> data = numpy.arange(2*3*4).reshape((2,3,4))
>>>> nditer_sum(data, [0, 1, -1])
> [[ 6 22 38]
>  [54 70 86]]
>>>> data.sum(axis=2)
> [[ 6 22 38]
>  [54 70 86]]
>
> So to get something equivalent to data.sum(axis=0) I though that it
> was enough to change  the argument red_axes to [-1, 0,1]
> But the result is quite different.
>
>>>> data = numpy.arange(2*3*4).reshape((2,3,4))
>>>> data.sum(axis=0)
> [[12 14 16 18]
>  [20 22 24 26]
>  [28 30 32 34]]
>>>> nditer_sum(data, [-1, 0, 1])
> [[210 210 210 210]
>  [210 210 210 210]
>  [210 210 210 210]]
>
> In the for loop inside nditer_sum (for x,y in it:), the iterator is
> looping 2 times and giving an array of length 12 each time, instead of
> looping 12 times and giving an array of length 2 each time. I have
> read the numpy documentation several times and googled about this to
> no avail.
>
> Does anybody have an example of a reduction in the first axis of an
> array using nditer? Is this a bug?
>
>
> Regards, Sergio
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The example from the link it shows how to do a reduction with y[...]
+= x. If you would replace x.sum() by += x, then it works.

>>> nditer_sum(data, [-1,0,1])
array([[12, 14, 16, 18],
       [20, 22, 24, 26],
       [28, 30, 32, 34]])
>>> data.sum(axis=0)
array([[12, 14, 16, 18],
       [20, 22, 24, 26],
       [28, 30, 32, 34]])

>>> nditer_sum(data, [0,-1,1])
array([[12, 15, 18, 21],
       [48, 51, 54, 57]])
>>> data.sum(axis=1)
array([[12, 15, 18, 21],
       [48, 51, 54, 57]])

I think that is because sum() already reduces all axis by default.

Regards,
Han