If you're using numpy 2.0 (the development branch), the function numpy.random.choice might do what you're looking for.
-Chris On Mon, Feb 20, 2012 at 8:35 PM, Yaroslav Halchenko <li...@onerussian.com> wrote: > Hi to all Numeric Python experts, > > could not think of a mailing list with better fit to my question which might > have an obvious answer: > > straightforward (naive) Python code to answer my question would be > something like > > import random, itertools > n,p,k=100,50,10 # don't try to run with this numbers! ;) > print random.sample(list(itertools.combinations(range(n), p)), k) > > so the goal is to get k (non-repeating) p-subsets of n, where n and p > prohibitively large to first populate the full set of combinations. > > Thank you in advance ;-) > -- > =------------------------------------------------------------------= > Keep in touch www.onerussian.com > Yaroslav Halchenko www.ohloh.net/accounts/yarikoptic > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
