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? Cheers Wolfgang _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
