#!/usr/bin/env python

import random

class GA :

    def __init__(self, problem, popsize=100, elitismRate=0.2, 
                 mutationRate=0.05, itersToRun=100) :
        self.problem = problem
        self.popsize = popsize
        self.elitismRate = elitismRate
        self.mutationRate = mutationRate
        self.itersToRun = itersToRun

        self.population = problem.makePopulation(popsize) 

    def run(self) :
        i = 0
        while i < self.itersToRun and not self.problem.solved(self.population) :
            i += 1
            self.problem.evalFitness(self.population)
            keepers = self.ApplyElitism(self.population, 
                                                    self.elitismRate)
            j = len(keepers) 
            newcomers = []
            while j <= self.popsize :
                j += 2
                c1, c2 = self.selectChromosomes(self.population)
                c3, c4  = self.crossover(c1,c2)
                newcomers.extend([c3,c4])
            for c in newcomers :
                if random.random() < self.mutationRate :
                    self.problem.mutate(c)
            self.population = keepers + newcomers
            print "Iteration: %d" % i 
        self.problem.evalFitness(self.population) 
        print "Final results: " 
        print self.population