/// <summary>
/// Fitness function calculating
/// </summary>
/// <param name="generation"></param>
/// <param name="unsafeMode"></param>
/// <returns></returns>
private List <FitnessFunction> CalculateFitnessFunctionValues(List <List <double> > generation, bool unsafeMode)
{
// Creating real neural networks by weights lists:
List <NeuralNetworkGeneticAlg> networksList = generation.Select(t => new NeuralNetworkGeneticAlg(t, NetworkStructure)).ToList();
// Calculating values:
List <FitnessFunction> fitnessFuncValues = new List <FitnessFunction>();
Parallel.For(0, networksList.Count, i =>
{
FitnessFunction fitnessFunction = new FitnessFunction
{
ChromosomeIndex = i
};
fitnessFunction.CalculateValue(networksList[i], InputDatasets, OutputDatasets, unsafeMode);
lock (_sync)
{
fitnessFuncValues.Add(fitnessFunction);
}
});
return(fitnessFuncValues);
}
