Hi Wolfgang, I think you are looking for reduceat( ), in particular add.reduceat()
-- srean On Thu, May 31, 2012 at 12:36 AM, Wolfgang Kerzendorf <wkerzend...@gmail.com> wrote: > Dear all, > > I have an ndarray which consists of many arrays stacked behind each other > (only conceptually, in truth it's a normal 1d float64 array). > I have a second array which tells me the start of the individual data sets in > the 1d float64 array and another one which tells me the length. > Example: > > data_array = (conceptually) [[1,2], [1,2,3,4], [1,2,3]] = in reality > [1,2,1,2,3,4,1,2,3, dtype=float64] > start_pointer = [0, 2, 6] > length_data = [2, 4, 3] > > I now want to normalize each of the individual data sets. I wrote a simple > for loop over the start_pointer and length data grabbed the data and > normalized it and wrote it back to the big array. That's slow. Is there an > elegant numpy way to do that? Do I have to go the cython way? _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
