public void MutationsInAllStochasticMutationTest()
{
var converter = new MathExpressionConverter(MathPrimitiveSets.Default);
var mut = new StochasticMutation <MathProgram>(Operators);
var prog1 = converter.FromPrefixNotation("(* 2 (^ 1 4))");
var allMuts = new HashSet <MathProgram>(mut.GetAllMutations(prog1));
Console.WriteLine(prog1);
foreach (var op in Operators)
{
var prog = op.Mutate(prog1);
Console.WriteLine(prog);
Assert.IsTrue(allMuts.Contains(prog), $"{prog} should be a valid mutation of {prog1}.");
}
}
public static void Main(string[] args)
{
const uint popSize = 200;
const uint maxDepth = 4;
const uint maxGenerations = 2000;
const uint maxElementLength = 20;
const uint maxNoImproveGen = (uint)(maxGenerations * 0.5);
const string solutionExp = "(+ (+ x x) (+ (* 3 (* x x)) 1))";
var variable = new Variable("x");
var primitives = new PrimitiveSet <MathProgram>(
new HashSet <Terminal> {
variable, new Constant(0), new Constant(1), new Constant(3)
},
new HashSet <MathProgram>());
primitives.Add(MathPrimitiveSets.Default);
var fitnessFunction = new FitnessFunction(x => 2 * x + 3 * x * x + 1, variable, 100, -50, 50);
var solution = new MathExpressionConverter(primitives).FromPrefixNotation(solutionExp);
Console.WriteLine("===================================");
Console.WriteLine("Fitness: {0} | {1}", fitnessFunction.Evaluate(solution), solution);
solution.ToGraphvizFile(Path.GetFullPath("."), "solution", GraphvizImageType.Png);
Console.WriteLine("===================================");
var seed = new AdditionFunction(new Constant(1), variable);
var elementGenerator =
new StochasticProgramGenerator <MathProgram, double>(
new List <IProgramGenerator <MathProgram, double> >
{
new GrowProgramGenerator <MathProgram, double>(),
new FullProgramGenerator <MathProgram, double>()
});
var selection = new TournamentSelection <MathProgram>(fitnessFunction, (uint)(popSize * 0.05));
var crossover = new StochasticCrossover <MathProgram>(
new List <ICrossoverOperator <MathProgram> >
{
new SubtreeCrossover <MathProgram, double>(),
new OnePointCrossover <MathProgram, double>(),
new ContextPreservingCrossover <MathProgram, double>(),
new UniformCrossover <MathProgram, double>()
});
var mutation = new StochasticMutation <MathProgram>(
new List <IMutationOperator <MathProgram> >
{
new SubtreeMutation <MathProgram, double>(elementGenerator, primitives, 1),
new PointMutation <MathProgram, double>(primitives),
//new ShrinkMutation(primitives),
new SimplifyMutation(),
new HoistMutation <MathProgram, double>()
});
var pop = new Population <MathProgram, double>(
popSize, primitives, elementGenerator,
fitnessFunction, selection, crossover, mutation, maxDepth, maxElementLength);
pop.Init(new HashSet <MathProgram> {
seed
});
MathProgram best = null;
var numNoImproveGens = -1;
for (var i = 0u; i < maxGenerations && numNoImproveGens < maxNoImproveGen; i++)
{
pop.Step();
var newBest = pop.BestProgram;
if (best == null)
{
best = newBest;
}
var diff = fitnessFunction.Evaluate(newBest) - fitnessFunction.Evaluate(best);
numNoImproveGens = diff.Equals(0) && best.Equals(newBest) ? numNoImproveGens + 1 : 0;
best = newBest;
Print(pop, i, fitnessFunction, diff);
}
best.ToGraphvizFile(Path.GetFullPath("."), "best", GraphvizImageType.Png);
Console.WriteLine("===================================");
Console.WriteLine($"Best: {pop.BestProgram}, fitness: {fitnessFunction.Evaluate(pop.BestProgram):0.000}");
Console.ReadKey();
}
