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source: stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RippleFunction.cs @ 16819

Last change on this file since 16819 was 15584, checked in by swagner, 7 years ago

#2640: Updated year of copyrights in license headers on stable

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Random;
26
27namespace HeuristicLab.Problems.Instances.DataAnalysis {
28  public class RippleFunction : ArtificialRegressionDataDescriptor {
29
30    public override string Name { get { return "Vladislavleva-7 F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))"; } }
31    public override string Description {
32      get {
33        return "Paper: Order of Nonlinearity as a Complexity Measure for Models Generated by Symbolic Regression via Pareto Genetic Programming " + Environment.NewLine
34        + "Authors: Ekaterina J. Vladislavleva, Member, IEEE, Guido F. Smits, Member, IEEE, and Dick den Hertog" + Environment.NewLine
35        + "Function: F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))" + Environment.NewLine
36        + "Training Data: 300 points X1, X2 = Rand(0.05, 6.05)" + Environment.NewLine
37        + "Test Data: 1000 points X1, X2 = Rand(-0.25, 6.35)" + Environment.NewLine
38        + "Function Set: +, -, *, /, square, e^x, e^-x, sin(x), cos(x), x^eps, x + eps, x + eps";
39      }
40    }
41    protected override string TargetVariable { get { return "Y"; } }
42    protected override string[] VariableNames { get { return new string[] { "X1", "X2", "Y" }; } }
43    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } }
44    protected override int TrainingPartitionStart { get { return 0; } }
45    protected override int TrainingPartitionEnd { get { return 300; } }
46    protected override int TestPartitionStart { get { return 300; } }
47    protected override int TestPartitionEnd { get { return 300 + 1000; } }
48    public int Seed { get; private set; }
49
50    public RippleFunction() : this((int)DateTime.Now.Ticks) { }
51
52    public RippleFunction(int seed) : base() {
53      Seed = seed;
54    }
55    protected override List<List<double>> GenerateValues() {
56      List<List<double>> data = new List<List<double>>();
57      var rand = new MersenneTwister((uint)Seed);
58      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
59        data.Add(ValueGenerator.GenerateUniformDistributedValues(rand.Next(), 300, 0.05, 6.05).ToList());
60      }
61
62      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
63        data[i].AddRange(ValueGenerator.GenerateUniformDistributedValues(rand.Next(), 1000, -0.25, 6.35));
64      }
65
66      double x1, x2;
67      List<double> results = new List<double>();
68      for (int i = 0; i < data[0].Count; i++) {
69        x1 = data[0][i];
70        x2 = data[1][i];
71        results.Add((x1 - 3) * (x2 - 3) + 2 * Math.Sin((x1 - 4) * (x2 - 4)));
72      }
73      data.Add(results);
74
75      return data;
76    }
77  }
78}
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