public void TestDepth()
{
EncogProgramContext context = new EncogProgramContext();
context.DefineVariable("x");
StandardExtensions.CreateAll(context);
PrgGrowGenerator rnd = new PrgGrowGenerator(context, 2);
EncogProgram prg = (EncogProgram)rnd.Generate(new EncogRandom());
RenderCommonExpression render = new RenderCommonExpression();
}
public void TestCloneVar()
{
EncogProgramContext context = new EncogProgramContext();
context.LoadAllFunctions();
context.DefineVariable("x");
RenderCommonExpression render = new RenderCommonExpression();
EncogProgram prg1 = context.CreateProgram("x*2*3");
EncogProgram prg2 = context.CloneProgram(prg1);
Assert.AreEqual("((x*2)*3)", render.Render(prg1));
Assert.AreEqual("((x*2)*3)", render.Render(prg2));
}
public void TestCloneComplex()
{
EncogProgramContext context = new EncogProgramContext();
context.LoadAllFunctions();
context.DefineVariable("a");
RenderCommonExpression render = new RenderCommonExpression();
EncogProgram prg1 = context.CreateProgram("((a+25)^3/25)-((a*3)^4/250)");
EncogProgram prg2 = context.CloneProgram(prg1);
Assert.AreEqual("((((a+25)^3)/25)-(((a*3)^4)/250))", render.Render(prg1));
Assert.AreEqual("((((a+25)^3)/25)-(((a*3)^4)/250))", render.Render(prg2));
}
public void TestCloneComplex()
{
EncogProgramContext context = new EncogProgramContext();
context.LoadAllFunctions();
context.DefineVariable("a");
RenderCommonExpression render = new RenderCommonExpression();
EncogProgram prg1 = context.CreateProgram("((a+25)^3/25)-((a*3)^4/250)");
EncogProgram prg2 = context.CloneProgram(prg1);
Assert.AreEqual("((((a+25)^3)/25)-(((a*3)^4)/250))", render.Render(prg1));
Assert.AreEqual("((((a+25)^3)/25)-(((a*3)^4)/250))", render.Render(prg2));
}
public void TestCloneVar()
{
EncogProgramContext context = new EncogProgramContext();
context.LoadAllFunctions();
context.DefineVariable("x");
RenderCommonExpression render = new RenderCommonExpression();
EncogProgram prg1 = context.CreateProgram("x*2*3");
EncogProgram prg2 = context.CloneProgram(prg1);
Assert.AreEqual("((x*2)*3)", render.Render(prg1));
Assert.AreEqual("((x*2)*3)", render.Render(prg2));
}
private PrgPopulation Create()
{
EncogProgramContext context = new EncogProgramContext();
context.DefineVariable("x");
StandardExtensions.CreateAll(context);
PrgPopulation pop = new PrgPopulation(context, 10);
EncogProgram prg1 = new EncogProgram(context);
EncogProgram prg2 = new EncogProgram(context);
prg1.CompileExpression("x+1");
prg2.CompileExpression("(x+5)/2");
ISpecies defaultSpecies = pop.CreateSpecies();
defaultSpecies.Add(prg1);
defaultSpecies.Add(prg2);
return pop;
}
/// <summary>
/// Create a feed forward network.
/// </summary>
/// <param name="architecture">The architecture string to use.</param>
/// <param name="input">The input count.</param>
/// <param name="output">The output count.</param>
/// <returns>The feedforward network.</returns>
public IMLMethod Create(String architecture, int input,
int output)
{
if (input <= 0)
{
throw new EncogError("Must have at least one input for EPL.");
}
if (output <= 0)
{
throw new EncogError("Must have at least one output for EPL.");
}
IDictionary<String, String> args = ArchitectureParse.ParseParams(architecture);
var holder = new ParamsHolder(args);
int populationSize = holder.GetInt(
MLMethodFactory.PropertyPopulationSize, false, 1000);
String variables = holder.GetString("vars", false, "x");
String funct = holder.GetString("funct", false, null);
var context = new EncogProgramContext();
string[] tok = variables.Split(',');
foreach (string v in tok)
{
context.DefineVariable(v);
}
if (String.Compare("numeric", funct, StringComparison.OrdinalIgnoreCase) == 0)
{
StandardExtensions.CreateNumericOperators(context);
}
var pop = new PrgPopulation(context, populationSize);
if (context.Functions.Count > 0)
{
(new RampedHalfAndHalf(context, 2, 6)).Generate(new EncogRandom(), pop);
}
return pop;
}
/// <summary>
/// Program entry point.
/// </summary>
/// <param name="app">Holds arguments and other info.</param>
public void Execute(IExampleInterface app)
{
IMLDataSet trainingData = GenerationUtil.GenerateSingleDataRange(
(x) => (3 * Math.Pow(x, 2) + (12 * x) + 4)
, 0, 100, 1);
EncogProgramContext context = new EncogProgramContext();
context.DefineVariable("x");
StandardExtensions.CreateNumericOperators(context);
PrgPopulation pop = new PrgPopulation(context, 1000);
MultiObjectiveFitness score = new MultiObjectiveFitness();
score.AddObjective(1.0, new TrainingSetScore(trainingData));
TrainEA genetic = new TrainEA(pop, score);
genetic.ValidationMode = true;
genetic.CODEC = new PrgCODEC();
genetic.AddOperation(0.5, new SubtreeCrossover());
genetic.AddOperation(0.25, new ConstMutation(context, 0.5, 1.0));
genetic.AddOperation(0.25, new SubtreeMutation(context, 4));
genetic.AddScoreAdjuster(new ComplexityAdjustedScore(10, 20, 10, 20.0));
genetic.Rules.AddRewriteRule(new RewriteConstants());
genetic.Rules.AddRewriteRule(new RewriteAlgebraic());
genetic.Speciation = new PrgSpeciation();
(new RampedHalfAndHalf(context, 1, 6)).Generate(new EncogRandom(), pop);
genetic.ShouldIgnoreExceptions = false;
EncogProgram best = null;
genetic.ThreadCount = 1;
try
{
for (int i = 0; i < 1000; i++)
{
genetic.Iteration();
best = (EncogProgram)genetic.BestGenome;
Console.Out.WriteLine(genetic.IterationNumber + ", Error: "
+ best.Score + ",Best Genome Size:" + best.Size
+ ",Species Count:" + pop.Species.Count + ",best: " + best.DumpAsCommonExpression());
}
//EncogUtility.evaluate(best, trainingData);
Console.Out.WriteLine("Final score:" + best.Score
+ ", effective score:" + best.AdjustedScore);
Console.Out.WriteLine(best.DumpAsCommonExpression());
//pop.dumpMembers(Integer.MAX_VALUE);
//pop.dumpMembers(10);
}
catch (Exception t)
{
Console.Out.WriteLine(t.ToString());
}
finally
{
genetic.FinishTraining();
EncogFramework.Instance.Shutdown();
}
}