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source: branches/3075_aifeynman_instances/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs @ 17671

Last change on this file since 17671 was 17671, checked in by gkronber, 4 years ago

#3075: Removed "Feynman" prefix from all instances

File size: 2.9 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 Feynman11 : FeynmanDescriptor {
9    private readonly int testSamples;
10    private readonly int trainingSamples;
11
12    public Feynman11() : this((int) DateTime.Now.Ticks, 10000, 10000, null) { }
13
14    public Feynman11(int seed) {
15      Seed            = seed;
16      trainingSamples = 10000;
17      testSamples     = 10000;
18      noiseRatio      = null;
19    }
20
21    public Feynman11(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("I.12.4 q1*r/(4*pi*epsilon*r**3) | {0} samples | noise ({1})", trainingSamples,
31          noiseRatio == null ? "no noise" : noiseRatio.ToString());
32      }
33    }
34
35    protected override string TargetVariable { get { return noiseRatio == null ? "Ef" : "Ef_noise"; } }
36
37    protected override string[] VariableNames {
38      get { return new[] {"q1", "epsilon", "r", noiseRatio == null ? "Ef" : "Ef_noise"}; }
39    }
40
41    protected override string[] AllowedInputVariables { get { return new[] {"q1", "epsilon", "r"}; } }
42
43    public int Seed { get; private set; }
44
45    protected override int TrainingPartitionStart { get { return 0; } }
46    protected override int TrainingPartitionEnd { get { return trainingSamples; } }
47    protected override int TestPartitionStart { get { return trainingSamples; } }
48    protected override int TestPartitionEnd { get { return trainingSamples + testSamples; } }
49
50    protected override List<List<double>> GenerateValues() {
51      var rand = new MersenneTwister((uint) Seed);
52
53      var data    = new List<List<double>>();
54      var q1      = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
55      var epsilon = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
56      var r       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
57
58      var Ef = new List<double>();
59
60      data.Add(q1);
61      data.Add(epsilon);
62      data.Add(r);
63      data.Add(Ef);
64
65      for (var i = 0; i < q1.Count; i++) {
66        var res = q1[i] * r[i] / (4 * Math.PI * epsilon[i] * Math.Pow(r[i], 3));
67        Ef.Add(res);
68      }
69
70      if (noiseRatio != null) {
71        var Ef_noise    = new List<double>();
72        var sigma_noise = (double) noiseRatio * Ef.StandardDeviationPop();
73        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
74        data.Remove(Ef);
75        data.Add(Ef_noise);
76      }
77
78      return data;
79    }
80  }
81}
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