#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.Collections.Generic;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.GP.Interfaces;
using HeuristicLab.GP;
using HeuristicLab.Modeling;
using System;
using System.Xml;
using HeuristicLab.DataAnalysis;
using System.Linq;
namespace HeuristicLab.GP.StructureIdentification {
public class Predictor : PredictorBase {
public Predictor() : base() { } // for persistence
public Predictor(ITreeEvaluator evaluator, IGeneticProgrammingModel tree, double lowerPredictionLimit, double upperPredictionLimit)
: base(lowerPredictionLimit, upperPredictionLimit) {
this.treeEvaluator = evaluator;
this.functionTree = tree;
}
private ITreeEvaluator treeEvaluator;
public ITreeEvaluator TreeEvaluator {
get { return (ITreeEvaluator)this.treeEvaluator.Clone(); }
}
private IGeneticProgrammingModel functionTree;
public IGeneticProgrammingModel FunctionTree {
get { return functionTree; }
set { this.functionTree = value; }
}
public override IEnumerable Predict(Dataset input, int start, int end) {
if (input == null) throw new ArgumentNullException();
if (start < 0 || end <= start) throw new ArgumentException("start must be larger than zero and strictly smaller than end");
if (end > input.Rows) throw new ArgumentOutOfRangeException("number of rows in input is smaller then end");
treeEvaluator.UpperEvaluationLimit = UpperPredictionLimit;
treeEvaluator.LowerEvaluationLimit = LowerPredictionLimit;
return treeEvaluator.Evaluate(input, functionTree.FunctionTree, Enumerable.Range(start, end - start));
}
public override IEnumerable GetInputVariables() {
HashSet inputVariables = new HashSet();
foreach (IFunctionTree ft in FunctionTreeIterator.IteratePrefix(functionTree.FunctionTree)) {
VariableFunctionTree varFunTree = ft as VariableFunctionTree;
if (varFunTree != null) {
inputVariables.Add(varFunTree.VariableName);
}
}
return inputVariables;
}
public override IView CreateView() {
return new PredictorView(this);
}
public override object Clone(IDictionary clonedObjects) {
Predictor clone = (Predictor)base.Clone(clonedObjects);
clone.treeEvaluator = (ITreeEvaluator)Auxiliary.Clone(treeEvaluator, clonedObjects);
clone.functionTree = (IGeneticProgrammingModel)Auxiliary.Clone(functionTree, clonedObjects);
return clone;
}
public override System.Xml.XmlNode GetXmlNode(string name, System.Xml.XmlDocument document, IDictionary persistedObjects) {
XmlNode node = base.GetXmlNode(name, document, persistedObjects);
node.AppendChild(PersistenceManager.Persist("Evaluator", treeEvaluator, document, persistedObjects));
node.AppendChild(PersistenceManager.Persist("FunctionTree", functionTree, document, persistedObjects));
return node;
}
public override void Populate(System.Xml.XmlNode node, IDictionary restoredObjects) {
base.Populate(node, restoredObjects);
treeEvaluator = (ITreeEvaluator)PersistenceManager.Restore(node.SelectSingleNode("Evaluator"), restoredObjects);
functionTree = (IGeneticProgrammingModel)PersistenceManager.Restore(node.SelectSingleNode("FunctionTree"), restoredObjects);
}
}
}