public static GeneticIndividual Crossover(GeneticIndividual a, GeneticIndividual b)
{
var ret = new GeneticIndividual(a._recognizer);
for (var i = 0; i < a.Items.Length; i++)
{
ret.Items[i] = GeneticIndividualItem.Crossover(a.Items[i], b.Items[i]);
}
return(ret);
}
public GeneticIndividualItem GenerateRandomItem(int pos)
{
var d = _recognizer.Target.Width / _recognizer.DigitsCount;
var ret = new GeneticIndividualItem(_recognizer,
d * pos + (d - _recognizer.DigitWidth) / 2,
(_recognizer.Target.Height - _recognizer.DigitHeight) / 2
);
ret = GeneticIndividualItem.Mutation(ret);
return(ret);
}
public static GeneticIndividualItem Mutation(GeneticIndividualItem a)
{
var maxDeltaX = 20;
var maxDeltaY = 5;
var dx = Random.Next(maxDeltaX * 2 + 1) - maxDeltaX;
var dy = Random.Next(maxDeltaY * 2 + 1) - maxDeltaY;
return(new GeneticIndividualItem(a._recognizer,
Math.Min(Math.Max(0, a.X + dx), a._recognizer.Target.Width - a._recognizer.DigitWidth),
Math.Min(Math.Max(0, a.Y + dy), a._recognizer.Target.Height - a._recognizer.DigitHeight)
));
}
public static GeneticIndividual Mutation(GeneticIndividual a)
{
var ret = new GeneticIndividual(a._recognizer);
var idx = Random.Next(a._recognizer.DigitsCount);
for (var i = 0; i < a.Items.Length; i++)
{
ret.Items[i] = i == idx
? GeneticIndividualItem.Mutation(a.Items[i])
: a.Items[i];
}
return(ret);
}
public static GeneticIndividualItem Crossover(GeneticIndividualItem a, GeneticIndividualItem b)
{
return(new GeneticIndividualItem(a._recognizer, (a.X + b.X) / 2, (a.Y + b.Y) / 2));
}
