#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using HeuristicLab.Core;
using HeuristicLab.DataAnalysis;
using HeuristicLab.GP.Interfaces;
namespace HeuristicLab.GP.StructureIdentification {
///
/// Base class for tree evaluators
///
public abstract class TreeEvaluatorBase : ItemBase, ITreeEvaluator {
protected const double EPSILON = 1.0e-7;
protected double maxValue;
protected double minValue;
protected class Instr {
public double d_arg0;
public short i_arg0;
public short i_arg1;
public byte arity;
public byte symbol;
}
protected Instr[] codeArr;
protected int PC;
protected Dataset dataset;
protected int sampleIndex;
public void PrepareForEvaluation(Dataset dataset, int targetVariable, int start, int end, double punishmentFactor, IFunctionTree functionTree) {
this.dataset = dataset;
// calculate upper and lower bounds for the estimated value (mean +/- punishmentFactor * range)
double mean = dataset.GetMean(targetVariable, start, end);
double range = dataset.GetRange(targetVariable, start, end);
maxValue = mean + punishmentFactor * range;
minValue = mean - punishmentFactor * range;
codeArr = new Instr[functionTree.GetSize()];
int i = 0;
foreach (IFunctionTree tree in IteratePrefix(functionTree)) {
codeArr[i++] = TranslateToInstr(tree);
}
}
private IEnumerable IteratePrefix(IFunctionTree functionTree) {
List prefixForm = new List();
prefixForm.Add(functionTree);
foreach (IFunctionTree subTree in functionTree.SubTrees) {
prefixForm.AddRange(IteratePrefix(subTree));
}
return prefixForm;
}
private Instr TranslateToInstr(IFunctionTree tree) {
Instr instr = new Instr();
instr.arity = (byte)tree.SubTrees.Count;
instr.symbol = EvaluatorSymbolTable.MapFunction(tree.Function);
switch (instr.symbol) {
case EvaluatorSymbolTable.DIFFERENTIAL:
case EvaluatorSymbolTable.VARIABLE: {
VariableFunctionTree varTree = (VariableFunctionTree)tree;
instr.i_arg0 = (short)dataset.GetVariableIndex(varTree.VariableName);
instr.d_arg0 = varTree.Weight;
instr.i_arg1 = (short)varTree.SampleOffset;
break;
}
case EvaluatorSymbolTable.CONSTANT: {
ConstantFunctionTree constTree = (ConstantFunctionTree)tree;
instr.d_arg0 = constTree.Value;
break;
}
case EvaluatorSymbolTable.UNKNOWN: {
throw new NotSupportedException("Unknown function symbol: " + instr.symbol);
}
}
return instr;
}
public double Evaluate(int sampleIndex) {
PC = 0;
this.sampleIndex = sampleIndex;
double estimated = EvaluateBakedCode();
if (double.IsNaN(estimated) || double.IsInfinity(estimated)) estimated = maxValue;
else if (estimated < minValue) estimated = minValue;
else if (estimated > maxValue) estimated = maxValue;
return estimated;
}
// skips a whole branch
protected void SkipBakedCode() {
int i = 1;
while (i > 0) {
i += codeArr[PC++].arity;
i--;
}
}
protected abstract double EvaluateBakedCode();
}
}