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source: branches/3075_aifeynman_instances/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.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: 3.1 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 Feynman10 : FeynmanDescriptor {
9    private readonly int testSamples;
10    private readonly int trainingSamples;
11
12    public Feynman10() : this((int) DateTime.Now.Ticks, 10000, 10000, null) { }
13
14    public Feynman10(int seed) {
15      Seed            = seed;
16      trainingSamples = 10000;
17      testSamples     = 10000;
18      noiseRatio      = null;
19    }
20
21    public Feynman10(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.12.2 q1*q2*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 ? "F" : "F_noise"; } }
36
37    protected override string[] VariableNames {
38      get { return new[] {"q1", "q2", "epsilon", "r", noiseRatio == null ? "F" : "F_noise"}; }
39    }
40
41    protected override string[] AllowedInputVariables { get { return new[] {"q1", "q2", "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 q2      = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
56      var epsilon = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
57      var r       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
58
59      var F = new List<double>();
60
61      data.Add(q1);
62      data.Add(q2);
63      data.Add(epsilon);
64      data.Add(r);
65      data.Add(F);
66
67      for (var i = 0; i < q1.Count; i++) {
68        var res = q1[i] * q2[i] * r[i] / (4 * Math.PI * epsilon[i] * Math.Pow(r[i], 3));
69        F.Add(res);
70      }
71
72      if (noiseRatio != null) {
73        var F_noise     = new List<double>();
74        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
75        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
76        data.Remove(F);
77        data.Add(F_noise);
78      }
79
80      return data;
81    }
82  }
83}
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