Modifying fitness values after each generation

[João Antunes]

Hello, so I'm new to pyevolve and I'm trying to implement a binary coded rastring minimization GA with roulette wheel selection.
As the roulette only accepts maximization, I have to change the calculated fitness value of the chromossome to maxfitness - fitness.
I'm trying to do this with this function as setcallback:

def calculateRealFitness(ga_engine):

   best = ga_engine.bestIndividual()

   bestfitness = best.getFitnessScore()

   population = ga_engine.getPopulation()

   for i in xrange(10):   #10 is the size of the population in this case

      population[i].fitness = bestfitness - population[i].fitness

   ga_engine.internalPop = population

   return False

Unfortunately, it doesn't change anything. What is wrong with my code? What's the best way to do it?

[Arseniy Terekhin]

I have't touched pyevolve for over two years, but example at http://pyevolve.sourceforge.net/0_6rc1/examples.html#example-3-schaffer-f6-deceptive-function say you CAN minimize:

   # Genetic Algorithm Instance
   ga = GSimpleGA.GSimpleGA(genome)
   ga.selector.set(Selectors.GRouletteWheel)

   ga.setMinimax(Consts.minimaxType["minimize"])

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I remain,
Arseniy Terekhin