public void IndexOfSerialEqualBinary(int size)
{
var probabilities = Array(size, new Random(12));
Arithmetics.Normalize(probabilities);
ProbabilitySelector.Incremental(probabilities);
Assert.Equal(
ProbabilitySelector.IndexOfSerial(probabilities, 0.5),
ProbabilitySelector.IndexOfBinary(probabilities, 0.5)
);
}
public override double[] Probabilities(Population <TGene, TAllele> population, int count)
{
var fitness = new double[population.Count];
// Copy the fitness values to probabilities arrays.
fitness[0] = population[0].GetFitness().ToDouble(null);
var min = fitness[0];
var max = fitness[0];
for (var i = 1; i < fitness.Length; ++i)
{
fitness[i] = population[i].GetFitness().ToDouble(null);
if (fitness[i] < min)
{
min = fitness[i];
}
else if (fitness[i] > max)
{
max = fitness[i];
}
}
var diff = max - min;
if (ProbabilitySelector.Eq(diff, 0.0))
{
// Set equal probabilities if diff (almost) zero.
//Array.Fill(fitness, 1.0 / fitness.Length);
for (int index = 0; index < fitness.Length; index++)
{
fitness[index] = 1.0 / fitness.Length;
}
}
else
{
// Scale fitness values to avoid overflow.
for (var i = fitness.Length; --i >= 0;)
{
fitness[i] = (fitness[i] - min) / diff;
}
// Apply the "Boltzmann" function.
for (var i = fitness.Length; --i >= 0;)
{
fitness[i] = Math.Exp(_b * fitness[i]);
}
}
return(Arithmetics.Normalize(fitness));
}