#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 System.Text; using HeuristicLab.Core; using System.Diagnostics; using HeuristicLab.Data; using HeuristicLab.Constraints; using HeuristicLab.DataAnalysis; namespace HeuristicLab.Functions { public class Variable : FunctionBase { public static readonly string WEIGHT = "Weight"; public static readonly string OFFSET = "SampleOffset"; public static readonly string INDEX = "Variable"; public override string Description { get { return @"Variable reads a value from a dataset, multiplies that value with a given factor and returns the result. The variable 'SampleOffset' can be used to read a value from previous or following rows. The index of the row that is actually read is SampleIndex+SampleOffset)."; } } public Variable() : base() { AddVariableInfo(new VariableInfo(INDEX, "Index of the variable in the dataset representing this feature", typeof(ConstrainedIntData), VariableKind.None)); GetVariableInfo(INDEX).Local = true; AddVariableInfo(new VariableInfo(WEIGHT, "Weight is multiplied to the feature value", typeof(ConstrainedDoubleData), VariableKind.None)); GetVariableInfo(WEIGHT).Local = true; AddVariableInfo(new VariableInfo(OFFSET, "SampleOffset is added to the sample index", typeof(ConstrainedIntData), VariableKind.None)); GetVariableInfo(OFFSET).Local = true; ConstrainedDoubleData weight = new ConstrainedDoubleData(); // initialize a totally arbitrary range for the weight = [-20.0, 20.0] weight.AddConstraint(new DoubleBoundedConstraint(-20.0, 20.0)); AddVariable(new HeuristicLab.Core.Variable(WEIGHT, weight)); ConstrainedIntData variable = new ConstrainedIntData(); AddVariable(new HeuristicLab.Core.Variable(INDEX, variable)); ConstrainedIntData sampleOffset = new ConstrainedIntData(); // initialize a totally arbitrary default range for sampleoffset = [-10, 10] sampleOffset.AddConstraint(new IntBoundedConstraint(0, 0)); AddVariable(new HeuristicLab.Core.Variable(OFFSET, sampleOffset)); // variable can't have suboperators AddConstraint(new NumberOfSubOperatorsConstraint(0, 0)); } // variable can be evaluated directly // evaluation reads local variables weight, index, offset from function-tree and returns the variable-value * weight public override double Evaluate(Dataset dataset, int sampleIndex, IFunctionTree tree) { double w = ((ConstrainedDoubleData)tree.GetLocalVariable(WEIGHT).Value).Data; int v = ((ConstrainedIntData)tree.GetLocalVariable(INDEX).Value).Data; int offset = ((ConstrainedIntData)tree.GetLocalVariable(OFFSET).Value).Data; if(sampleIndex + offset < 0 || sampleIndex + offset >= dataset.Rows) return double.NaN; return w * dataset.GetValue(sampleIndex + offset, v); } // can't apply a variable public override double Apply(Dataset dataset, int sampleIndex, double[] args) { throw new NotSupportedException(); } public override void Accept(IFunctionVisitor visitor) { visitor.Visit(this); } } }