Python Genetic Algorithm

[Steven Clark]

Why not make chromosome itself a class?

class BasicChromosome(object):
    def __init__(self, data):
        self.data = data

    def crossover(self):
        [stuff here]

You can subclass this as needed, altering the crossover method as necessary.

...perhaps I didn't understand your question.
-Steven

On Jan 27, 2008 6:35 PM, Wildemar Wildenburger
<lasses_weil at klapptsowieso.net> wrote:
> 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
>
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