[Numpy-discussion] moving window product
Brent Pedersen
bpederse@gmail....
Mon Mar 21 12:34:01 CDT 2011
On Mon, Mar 21, 2011 at 11:19 AM, Keith Goodman <kwgoodman@gmail.com> wrote:
> On Mon, Mar 21, 2011 at 10:10 AM, Brent Pedersen <bpederse@gmail.com> wrote:
>> hi, is there a way to take the product along a 1-d array in a moving
>> window? -- similar to convolve, with product in place of sum?
>> currently, i'm column_stacking the array with offsets of itself into
>> window_size columns and then taking the product at axis 1.
>> like::
>>
>> w = np.column_stack(a[i:-window_size+i] for i in range(0, window_size))
>> window_product = np.product(w, axis=1)
>>
>> but then there are the edge effects/array size issues--like those
>> handled in np.convolve.
>> it there something in numpy/scipy that addresses this. or that does
>> the column_stacking with an offset?
>
> The Bottleneck package has a fast moving window sum (bn.move_sum and
> bn.move_nansum). You could use that along with
>
>>> a = np.random.rand(5)
>>> a.prod()
> 0.015877866878931741
>>> np.exp(np.log(a).sum())
> 0.015877866878931751
>
> Or you could use strides or scipy.ndimage as in
> https://github.com/kwgoodman/bottleneck/blob/master/bottleneck/slow/move.py
>
ah yes, of course. thank you.
def moving_product(a, window_size, mode="same"):
return np.exp(np.convolve(np.log(a), np.ones(window_size), mode))
i'll have a closer look at your strided version in bottleneck as well.
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