source: branches/3075_aifeynman_instances/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs @ 17639

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.Instances.DataAnalysis {
  public class Feynman39 : FeynmanDescriptor {
    public override string Name { get { return "Feynman I.38.12 4*pi*epsilon*(h/(2*pi))**2/(m*q**2)"; } }

    protected override string TargetVariable { get { return "r"; } }
    protected override string[] VariableNames { get { return new[] {"m", "q", "h", "epsilon", "r"}; } }
    protected override string[] AllowedInputVariables { get { return new[] {"m", "q", "h", "epsilon"}; } }

    public int Seed { get; private set; }

    public Feynman39() : this((int) DateTime.Now.Ticks) { }

    public Feynman39(int seed) {
      Seed = seed;
    }

    protected override List<List<double>> GenerateValues() {
      var rand = new MersenneTwister((uint) Seed);

      var data    = new List<List<double>>();
      var m       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var q       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var h       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var epsilon = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();

      var r = new List<double>();

      data.Add(m);
      data.Add(q);
      data.Add(h);
      data.Add(epsilon);
      data.Add(r);

      for (var i = 0; i < m.Count; i++) {
        var res = 4 * Math.PI * epsilon[i] * Math.Pow((h[i] / (2 * Math.PI)), 2) / (m[i] * Math.Pow(q[i], 2));
        r.Add(res);
      }

      return data;
    }
  }
}