public void OperateTest()
{
double percent = 50.0;
Selection_PercentAboveAverage target = new Selection_PercentAboveAverage(percent);
DoublePoint p1 = new DoublePoint(10);
DoublePoint p2 = new DoublePoint(1);
DoublePoint p3 = new DoublePoint(15);
DoublePoint p4 = new DoublePoint(17);
DoublePoint p5 = new DoublePoint(12);
p1.Value = 2;
p2.Value = 5;
p3.Value = 324;
p4.Value = 4;
p5.Value = 6;
PointSet ps = new PointSet(new HashSet <Point>()
{
p1, p2, p3, p4, p5
});
PointSet ps1 = new PointSet(new HashSet <Point>()
{
p1, p2, p3, p4, p5
});
PointSet actual;
actual = target.Operate(ps);
Assert.IsTrue(actual.Set.Count <= ps1.Set.Count);
}
public void Selection_PercentAboveAverageConstructorTest()
{
double percent = 50.0;
Selection_PercentAboveAverage target = new Selection_PercentAboveAverage(percent);
Assert.AreEqual(target.Type, OperatorType.Both);
}
private void SetDoubleDefaults()
{
double[] p1 = { 0.0, 0.0 };
double[] p2 = { 5.0, 5.0 };
Initialization = new DoubleInitialization_RandomBetweenTwoPoints(
new DoublePoint(p1), new DoublePoint(p2), 10);
SelectionIF S = new Selection_PercentAboveAverage(50);
CrossoverIF C2 = new DoubleCrossover_Random();
MutationIF M = new DoubleMutation_ValuePercent(5.0);
Operations.Add(S);
Operations.Add(C2);
Operations.Add(M);
}
public void OperationsTest()
{
EvaluationIF e = new DoubleEvaluation_Logarithmic();
GeneticAlgorithm target = new GeneticAlgorithm(e);
IList <Operator> expected = new List <Operator>();
SelectionIF S = new Selection_PercentAboveAverage(50);
CrossoverIF C2 = new DoubleCrossover_Random();
MutationIF M = new DoubleMutation_ValuePercent(5.0);
expected.Add(S);
expected.Add(C2);
expected.Add(M);
IList <Operator> actual;
target.Operations = expected;
actual = target.Operations;
Assert.AreEqual(expected, actual);
}
public void GeneticAlgorithmConstructorTest()
{
List <Operator> operators = new List <Operator>();
SelectionIF S = new Selection_PercentAboveAverage(50);
CrossoverIF C2 = new DoubleCrossover_Random();
MutationIF M = new DoubleMutation_ValuePercent(5.0);
operators.Add(S);
operators.Add(C2);
operators.Add(M);
double[] p1 = { 0.0, 0.0 };
double[] p2 = { 5.0, 5.0 };
InitializationIF initialization = new DoubleInitialization_RandomBetweenTwoPoints(
new DoublePoint(p1), new DoublePoint(p2), 10);
EvaluationIF evaluation = new DoubleEvaluation_Trigonometric();
GeneticAlgorithm target = new GeneticAlgorithm(operators, initialization, evaluation);
Assert.IsNotNull(target.Operations);
Assert.IsNotNull(target.Initialization);
Assert.IsNotNull(target.Evaluation);
}