- Timestamp:
- 03/22/10 22:58:43 (15 years ago)
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-
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trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/SumSquaresEvaluator.cs
r3161 r3187 1 1 #region License Information 2 2 /* HeuristicLab 3 * Copyright (C) 2002-20 08Heuristic and Evolutionary Algorithms Laboratory (HEAL)3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL) 4 4 * 5 5 * This file is part of HeuristicLab. … … 21 21 22 22 using System; 23 using System.Collections.Generic; 24 using System.Text; 23 using HeuristicLab.Core; 24 using HeuristicLab.Data; 25 using HeuristicLab.Encodings.RealVectorEncoding; 26 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 25 27 26 namespace HeuristicLab. TestFunctions {28 namespace HeuristicLab.Problems.TestFunctions { 27 29 /// <summary> 28 30 /// Sum Squares Function<br/> … … 30 32 /// Optimum: 0.0 at (0.0, 0.0, ..., 0.0) 31 33 /// </summary> 32 public class SumSquaresEvaluator : TestFunctionEvaluatorBase { 33 /// <inheritdoc select="summary"/> 34 public override string Description { 35 get { return 36 @"Sum Squares Function 37 38 Domain: [-10.0 , 10.0]^n 39 Optimum: 0.0 at (0.0, 0.0, ..., 0.0)"; 40 } 34 [Item("SumSquaresEvaluator", "Evaluates the sum squares function on a given point. The optimum of this function is 0 at the origin.")] 35 [StorableClass] 36 public class SumSquaresEvaluator : SingleObjectiveTestFunctionProblemEvaluator { 37 /// <summary> 38 /// Returns false as the Rosenbrock function is a minimization problem. 39 /// </summary> 40 public override bool Maximization { 41 get { return false; } 42 } 43 /// <summary> 44 /// Gets the optimum function value (0). 45 /// </summary> 46 public override double BestKnownQuality { 47 get { return 0; } 48 } 49 /// <summary> 50 /// Gets the lower and upper bound of the function. 51 /// </summary> 52 public override DoubleMatrix Bounds { 53 get { return new DoubleMatrix(new double[,] { { -10, 10 } }); } 54 } 55 /// <summary> 56 /// Gets the minimum problem size (1). 57 /// </summary> 58 public override int MinimumProblemSize { 59 get { return 1; } 60 } 61 /// <summary> 62 /// Gets the (theoretical) maximum problem size (2^31 - 1). 63 /// </summary> 64 public override int MaximumProblemSize { 65 get { return int.MaxValue; } 41 66 } 42 67 … … 46 71 /// <param name="point">N-dimensional point for which the test function should be evaluated.</param> 47 72 /// <returns>The result value of the Sum Squares function at the given point.</returns> 48 public static double Apply( double[]point) {73 public static double Apply(RealVector point) { 49 74 double result = 0; 50 75 for (int i = 0; i < point.Length; i++) { … … 60 85 /// <param name="point">N-dimensional point for which the test function should be evaluated.</param> 61 86 /// <returns>The result value of the Sum Squares function at the given point.</returns> 62 protected override double EvaluateFunction( double[]point) {87 protected override double EvaluateFunction(RealVector point) { 63 88 return Apply(point); 64 89 }
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