public static ResultStruct GenerateResult(float[] distances)
{
ResultStruct result = new ResultStruct();
result.min = distances.Min();
result.max = distances.Max();
result.avg = distances.Average();
float sumOfSquaresOfDifferences = distances.Select(val => (val - result.avg) * (val - result.avg)).Sum();
result.std = Convert.ToSingle(Math.Sqrt(sumOfSquaresOfDifferences / distances.Length));
return(result);
}
private void Start(int crossoverSelection, float mutationPossibility)
{
ResultStruct[] results = new ResultStruct[iteration];
for (int i = 0; i < iteration; i++)
{
GeneticAlgorithm.Evolution(ref currentPopulation, ref currentDistances, crossoverSelection, mutationPossibility);
results[i] = ResultHelper.GenerateResult(currentDistances);
}
RefreshPicBox(currentPopulation[0]);
EvolutionFrm eFrm = new EvolutionFrm();
eFrm.CreateChart(results);
eFrm.ShowDialog();
RefreshList();
}
