Re: [Numpy-discussion] is there an efficient way to get a random set of subsets/combinations?
Thank you guys for replies! On Mon, 20 Feb 2012, Christopher Jordan-Squire wrote: If you're using numpy 2.0 (the development branch), the function numpy.random.choice might do what you're looking for. yeap -- handy one, although would require manual control over repetitions lazy me was trying to avoid ;) On Tue, 21 Feb 2012, Val Kalatsky wrote: Hi Slava, Mom, is that you? ;-) Since your k is only 10, here is a�quickie: import numpy as np arr = np.arange(n) for i in range(k): � � np.random.shuffle(arr) � � print np.sort(arr[:p]) If your ever get non-unique entries in a set of k=10 for your n and p, consider yourself lucky:) well -- I just thought that there might be an ideal function which in limit would return all combinations if given large enough k for reasonably small (n, p)... but indeed I should just put a logic in place to treat those cases separately. -- =--= 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] is there an efficient way to get a random set of subsets/combinations?
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
Re: [Numpy-discussion] is there an efficient way to get a random set of subsets/combinations?
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
Re: [Numpy-discussion] is there an efficient way to get a random set of subsets/combinations?
Hi Slava, Since your k is only 10, here is a quickie: import numpy as np arr = np.arange(n) for i in range(k): np.random.shuffle(arr) print np.sort(arr[:p]) If your ever get non-unique entries in a set of k=10 for your n and p, consider yourself lucky:) Val On Mon, Feb 20, 2012 at 10:35 PM, Yaroslav Halchenko li...@onerussian.comwrote: 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
