Travis E. Oliphant wrote: > Brendon Towle wrote: >> I need to simulate scenarios like the following: "You have a deck of >> 3 orange cards, 5 yellow cards, and 2 blue cards. You draw a card, >> replace it, and repeat N times." >> > > Thinking about the problem as drawing sample froms a discrete > distribution defined by the population might help. > > For example, in SciPy you can define your own discrete random variable: > > var = scipy.stats.rv_discrete(name='sample', > values=([0,1,2],[3/10.,5/10.,2/10.])) > > Then > > var.rvs(size=10000) > > would quickly return an array of "draws" > > If you didn't want to install SciPy, but were willing to install NumPy, > then the crux of the algorithm is to generate an entire array of uniform > random variables: numpy.random.rand(count) and then map them through > the inverse cumulative distribution function to generate your samples. > The inverse cumulative distribution function is just a series of steps > whose width depends on the probablity distribution. > > Thus, the population defines the draw boundaries. To make it easy, just > multiply the uniform random number by the total number of cards and then > the boundaries are on the integers of the number of each kind of card. > > Here is an implementation. I find this version to be 2x - 5x faster > depending on how many draws are used. > > > import numpy as N > > def randomDrawing_N(count, population): > probs = [x[0] for x in population] > res = [[0, item[1]] for item in population] > nums = N.random.rand(count) > cprobs = N.cumsum([0]+probs) > nums *= cprobs[-1] > for k, val in enumerate(probs): > res[k][0] += ((nums > cprobs[k]) & (nums < cprobs[k+1])).sum() > return res > > > -Travis Oliphant >
In response to what Travis and Simon wrote - (1) Where the heck can I find a description of scipy's stat functions? Documentation on these seems sparse. (2) How does one set up a good timer for Python as implemented for Windows? (i.e., how can I make API calls to Windows from Python?) Please bear with me, or not; I am /just/ starting off with Python. Thanks, Dave Braden -- http://mail.python.org/mailman/listinfo/python-list
