public IGenoType GetGenoType()
{
var genoType = new GenoType();
for (var c = 0; c < EaGeneExpressionParameters.MaximumNumberOfHeadNodes; c++)
{
genoType.GenoTypeNodes.Add(GetFunctionOrTerminalNode());
}
for (var c = 0; c < EaGeneExpressionParameters.MaximumNumberOTailNodes; c++)
{
genoType.GenoTypeNodes.Add(GetTerminalNode());
}
return(genoType);
}
public void CanCrossover()
{
var listLeft = new List <IGenoTypeNode>
{
new SquareRoot(),
new Multiplication(),
new Plus(),
new Minus(),
new FeatureTerminal("a"),
new FeatureTerminal("b"),
new FeatureTerminal("c"),
new FeatureTerminal("d")
};
var listRight = new List <IGenoTypeNode>
{
new Sinus(),
new Multiplication(),
new Division(),
new Minus(),
new FeatureTerminal("a1"),
new FeatureTerminal("b1"),
new FeatureTerminal("c1"),
new FeatureTerminal("d1")
};
var possibleFunctions = new List <IGenoTypeNode>
{
new SquareRoot(),
new Multiplication(),
new Plus(),
new Minus()
};
var possibleTerminals = new List <IGenoTypeNode>
{
new FeatureTerminal("a"),
new FeatureTerminal("b"),
new FeatureTerminal("c"),
new FeatureTerminal("d")
};
var eaGeneExpressionParameters =
new EaGeneExpressionParameters(4, possibleFunctions, possibleTerminals)
{
CrossoverProbability = 1.0
};
IGenoType left = new GeneExpression.GenoType {
GenoTypeNodes = listLeft
};
IGenoType right = new GeneExpression.GenoType {
GenoTypeNodes = listRight
};
var randomGenerator = new UniformRandomGenerator();
var genotypeCrossoverator1 = new GenoTypeCrossoveratorBasic1(randomGenerator, eaGeneExpressionParameters);
var phenoTypeTreeLeft1 = new GeneExpression.PhenoTypeTree(left.GenoTypeNodes);
var phenoTypeTreeRight1 = new GeneExpression.PhenoTypeTree(right.GenoTypeNodes);
genotypeCrossoverator1.PerformCrossover(ref left, ref right);
var phenoTypeTreeLeft2 = new GeneExpression.PhenoTypeTree(left.GenoTypeNodes);
var phenoTypeTreeRight2 = new GeneExpression.PhenoTypeTree(right.GenoTypeNodes);
Assert.NotEqual(phenoTypeTreeLeft1, phenoTypeTreeLeft2);
Assert.NotEqual(phenoTypeTreeRight1, phenoTypeTreeRight2);
}
