On Mon, Mar 21, 2011 at 10:10 AM, Brent Pedersen <bpede...@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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
