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# permutations, patterns, and probability

 P: n/a Greetings, I am working on a program to produce patterns. What would like is for it to exhaustively produce all possible permutations of a sequence of items but for each permutation produce variations, and also a sort of stutter based on probability / weighted randomess. Let us say we have tiles of four primary colors: ['Red', 'Blue', 'Green', 'Yellow']. Now we also have 4 alternatives or substitutes for each color ['Maroon', 'Navy_Blue', 'Forest_Green', 'Dark_Brown'] We pick a unique permutation, say: ['Red', 'Blue', 'Yellow', 'Green'] Now I would like to pick the primary colors substitute (say 30% chance for each element) so instead of our plain ['Red', 'Blue', 'Yellow', 'Green'] we might end up with: ['Red', 'Navy_Blue', 'Yellow', 'Forest_Green'] or ['Maroon', 'Navy_Blue', 'Yellow', 'Green'] Whatever... The main point is that sometimes the original color is retained and sometimes the dark color is substituted. Now I want to take this list and sometimes stutter an element so that there is, let us say a 50% chance for each element, that it is stuttered, and it may be repeated 1 (34%), 2(66%), or 3(33%) times. So that we could get: ['Maroon','Maroon','Navy_Blue', 'Yellow','Yellow','Yellow','Yellow', 'Green'] The program would quit when all 24 (in the case of 4 elements) was exhausted. I have code that makes weighted randomness. I have code that makes permutations, but I am having trouble putting this all together... While i work on it though that i might ask for help... I'd like for the code to be reusable and am building a library of functions for patterns. cheers, kevin ### This is not mine, it is from a python book... I believe the Lutz book def permute(list): if not list: # shuffle any sequence return[list] # empty sequence else: res = [] for i in range(len(list)): rest = list[:i] + list[i+1:] # delete current node for x in permute(rest): # permute the others res.append(list[i:i+1] + x) # add node at front return res mport random ### This this is mine, but seems to work anyway hee hee def windex(lst): '''an attempt to make a random.choose() function that makes weighted choices accepts a list of tuples with the item and probability as a pair like: >>> x = [('one', 0.25), ('two', 0.25), ('three', 0.5)] y=windex(x)''' n = random.uniform(0, 1) for item, weight in lst: if n < weight: break n = n - weight return item Jul 18 '05 #1