Max wrote: > In GAs, you operate on a Population of solutions. Each Individual from > the Population is a potential solution to the problem you're > optimizing, and Individuals have what's called a chromosome - a > specification of what it contains. For example, common chromosomes are > bit strings, lists of ints/floats, permutations...etc. I'm stuck on > how to implement the different chromosomes. I have a Population class, > which is going to contain a list of Individuals. Each individual will > be of a certain chromosome. I envision the chromosomes as subclasses > of an abstract Individual class, perhaps all in the same module. I'm > just having trouble envisioning how this would be coded at the > population level. Presumably, when a population is created, a > parameter to its __init__ would be the chromosome type, but I don't > know how to take that in Python and use it to specify a certain class. > I'm not sure I'm following you here. So a "chromosome" is bit of functionality, right? So basically it is a function. So my advice would be to write these functions and store it to the "indivuals"-list like so:
class Population(object): def __init__(self, *individuals): self.individuals = list(individuals) Then you can say: p = Population(indiv1, indiv2, indiv3) for individual in p.individual: individual(whatever_your_problem) (Don't know if this is the way GA's are supposed to work) You can also create callable classes (that is, classes that implement the __call__ method), and use instances of these as the individuals. For example you can create a Permutation class that returns a permutation (defined in it's __init__()) when it's __call__ method is called. (Am I making sense?) This is just generic advice, maybe this helps and maybe it doesn't at all. :) > I'm doing something similar with my crossover methods, by specifying > them as functions in a module called Crossover, importing that, and > defining > > crossover_function = getattr(Crossover, "%s_crossover" % xover) > > Where xover is a parameter defining the type of crossover to be used. > I'm hoping there's some similar trick to accomplish what I want to do > with chromosomes - or maybe I'm going about this completely the wrong > way, trying to get Python to do something it's not made for. Any help/ > feedback would be wonderful. > This isn't too bad, but for such things dictionaries are your Go-To datatype. Just have a dictionary of xover-functions handy and call the thusly: crossover_function = Crossover.function[xover] > Thanks, > Max Martin If that helps :) regards /W -- http://mail.python.org/mailman/listinfo/python-list