public void CrossoverWithNullParents()
{
using (var parameters = new ExpressionEvolverGeneticAlgorithmParameters(
a => a))
{
parameters.Crossover(null);
}
}
public void CrossoverWithEmptyParents()
{
using (var parameters = new ExpressionEvolverGeneticAlgorithmParameters(
a => a))
{
parameters.Crossover(new List <Chromosome <Expression <Func <double, double> > > >().AsReadOnly());
}
}
public void CrossoverOnDisposedObject()
{
ExpressionEvolverGeneticAlgorithmParameters parameters = null;
using (parameters = new ExpressionEvolverGeneticAlgorithmParameters(
a => a)) { }
parameters.Crossover(new List <Chromosome <Expression <Func <double, double> > > >().AsReadOnly());
}
public void Crossover()
{
Expression <Func <double, double> > evenExpression = x => x / 2;
Expression <Func <double, double> > oddExpression = x => 3 * x + 1;
var random = Substitute.For <SecureRandom>();
var nextCallCount = 0;
random.Next(Arg.Any <int>()).Returns((_) =>
{
var result = 0;
if (nextCallCount == 0)
{
result = 1;
}
else if (nextCallCount == 1)
{
result = 4;
}
else
{
throw new InvalidOperationException("Too many Next(int) calls.");
}
nextCallCount++;
return(result);
});
using (var parameters = new ExpressionEvolverGeneticAlgorithmParameters(
new RandomObjectGenerator().Generate <ReadOnlyCollection <ExpressionEvolverResult> >(),
random))
{
var children = parameters.Crossover(new List <Chromosome <Expression <Func <double, double> > > > {
new Chromosome <Expression <Func <double, double> > >(evenExpression, 0d),
new Chromosome <Expression <Func <double, double> > >(oddExpression, 0d)
}.AsReadOnly());
Assert.AreEqual(2, children.Count);
Assert.AreEqual("x => 0.5", children[0].ToString());
Assert.AreEqual("x => ((3 * x) + x)", children[1].ToString());
}
}
