On 20Jun2010 12:44, Stefan Behnel <stefan...@behnel.de> wrote: | southof40, 20.06.2010 12:19: | >I have list of of N Vehicle objects - the only possible vehicles are | >cars, bikes, trucks. | > | >I want to select an object from the list with a probability of : cars | >0.7, bikes 0.3, trucks 0.1. | > | >I've currently implemented this by creating another list in which each | >car object from the original list appears 7 times, each bike 3 times | >and each truck once. I then pick at random from that list. | > | >This works but seems very clunky to me. | | Why? It's a very simple, generic, easy to understand and fast | solution to the problem.
Only 3 out of 4, if you want to be precise in your selections. Supposing he wants probabilities 0.7432, 0.3765, 0.1087654 ? The required list needs to be Very Long to achieve an accurate representation, and thus Very Slow to construct/populate. A faster approach is to make a list represention the sum of the proportions as one counts along the choices, thus 0.7, 1.0, 1.1 in the example given (0.7, 0.7+0.3, 0.7+0.3+0.1). Then choose a value in the range 0.0 to the total (1.1) using the pseudo-random function of your choice, such as that in the random module. Then binary search the list for the matching item. The list scales linearly as the number of choices, not exponentially with the precision of the proportions. The search is logarithmic with the number of choices. Beyond a very small number of choices the former will dominate. Cheers, -- Cameron Simpson <c...@zip.com.au> DoD#743 http://www.cskk.ezoshosting.com/cs/ ... you could spend *all day* customizing the title bar. Believe me. I speak from experience. - Matt Welsh -- http://mail.python.org/mailman/listinfo/python-list
