Free cookie consent management tool by TermsFeed Policy Generator

source: branches/3106_AnalyticContinuedFractionsRegression/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs @ 17970

Last change on this file since 17970 was 17970, checked in by gkronber, 3 years ago

#3106 merged r17856:17969 from trunk to branch

File size: 3.6 KB
Line 
1using System;
2using System.Collections.Generic;
3using System.Linq;
4using HeuristicLab.Common;
5using HeuristicLab.Random;
6
7namespace HeuristicLab.Problems.Instances.DataAnalysis {
8  public class FeynmanBonus13 : FeynmanDescriptor {
9    private readonly int testSamples;
10    private readonly int trainingSamples;
11
12    public FeynmanBonus13() : this((int) DateTime.Now.Ticks, 10000, 10000, null) { }
13
14    public FeynmanBonus13(int seed) {
15      Seed            = seed;
16      trainingSamples = 10000;
17      testSamples     = 10000;
18      noiseRatio      = null;
19    }
20
21    public FeynmanBonus13(int seed, int trainingSamples, int testSamples, double? noiseRatio) {
22      Seed                 = seed;
23      this.trainingSamples = trainingSamples;
24      this.testSamples     = testSamples;
25      this.noiseRatio      = noiseRatio;
26    }
27
28    public override string Name {
29      get {
30        return string.Format(
31          "Goldstein 12.80: 1/(2*m)*(p**2+m**2*omega**2*x**2*(1+alpha*x/y)) | {0}",
32          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
33      }
34    }
35
36    protected override string TargetVariable { get { return noiseRatio == null ? "E_n" : "E_n_noise"; } }
37
38    protected override string[] VariableNames {
39      get { return new[] {"m", "omega", "p", "y", "x", "alpha", noiseRatio == null ? "E_n" : "E_n_noise"}; }
40    }
41
42    protected override string[] AllowedInputVariables { get { return new[] {"m", "omega", "p", "y", "x", "alpha"}; } }
43
44    public int Seed { get; private set; }
45
46    protected override int TrainingPartitionStart { get { return 0; } }
47    protected override int TrainingPartitionEnd { get { return trainingSamples; } }
48    protected override int TestPartitionStart { get { return trainingSamples; } }
49    protected override int TestPartitionEnd { get { return trainingSamples + testSamples; } }
50
51    protected override List<List<double>> GenerateValues() {
52      var rand = new MersenneTwister((uint) Seed);
53
54      var data  = new List<List<double>>();
55      var m     = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
56      var omega = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
57      var p     = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
58      var y     = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
59      var x     = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
60      var alpha = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
61
62      var E_n = new List<double>();
63
64      data.Add(m);
65      data.Add(omega);
66      data.Add(p);
67      data.Add(y);
68      data.Add(x);
69      data.Add(alpha);
70      data.Add(E_n);
71
72      for (var i = 0; i < m.Count; i++) {
73        var res = 1.0 / (2 * m[i]) * (Math.Pow(p[i], 2) +
74                                      Math.Pow(m[i], 2) * Math.Pow(omega[i], 2) * Math.Pow(x[i], 2) *
75                                      (1 + alpha[i] * x[i] / y[i]));
76        E_n.Add(res);
77      }
78
79      if (noiseRatio != null) {
80        var E_n_noise   = new List<double>();
81        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
82        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
83        data.Remove(E_n);
84        data.Add(E_n_noise);
85      }
86
87      return data;
88    }
89  }
90}
Note: See TracBrowser for help on using the repository browser.