#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 System.Xml; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.DataAnalysis; using System.Linq; namespace HeuristicLab.Modeling { public abstract class VariableEvaluationImpactCalculator : VariableImpactCalculatorBase { public override string OutputVariableName { get { return "VariableEvaluationImpacts"; } } public override string Description { get { return @"Calculates the impact of all allowed input variables on the model outputs using evaluator supplied as suboperator."; } } private double[,] CombineOutputs(double[] referenceOutputs, double[] newOutputs) { if (referenceOutputs.Length != newOutputs.Length) throw new InvalidProgramException(); double[,] result = new double[referenceOutputs.Length, 2]; for (int i = 0; i < referenceOutputs.Length; i++) { result[i, 0] = referenceOutputs[i]; result[i, 1] = newOutputs[i]; } return result; } protected override double CalculateImpact(double[] referenceValue, double[] newValue) { try { return SimpleMSEEvaluator.Calculate(CombineOutputs(referenceValue, newValue)); } catch (ArgumentException) { return double.PositiveInfinity; } } protected override double[] CalculateValue(IScope scope, Dataset dataset, int targetVariable, int start, int end) { return GetOutputs(scope, dataset, targetVariable, start, end); } protected override double[] PostProcessImpacts(double[] impacts) { double mseSum = impacts.Sum(); if (mseSum.IsAlmost(0.0)) mseSum = 1.0; for (int i = 0; i < impacts.Length; i++) { impacts[i] = impacts[i] / mseSum; } return impacts; } private bool IsAlmost(double x, double y) { return Math.Abs(x - y) < 1.0E-12; } protected abstract double[] GetOutputs(IScope scope, Dataset dataset, int targetVariable, int start, int end); } }