source: branches/3075_aifeynman_instances/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs @ 17640

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

namespace HeuristicLab.Problems.Instances.DataAnalysis {
  public class Feynman61 : FeynmanDescriptor {
    public override string Name { get { return "Feynman II.11.3 q*Ef/(m*(omega_0**2-omega**2))"; } }

    protected override string TargetVariable { get { return "x"; } }
    protected override string[] VariableNames { get { return new[] {"q", "Ef", "m", "omega_0", "omega", "x"}; } }
    protected override string[] AllowedInputVariables { get { return new[] {"q", "Ef", "m", "omega_0", "omega"}; } }

    public int Seed { get; private set; }

    public Feynman61() : this((int) DateTime.Now.Ticks) { }

    public Feynman61(int seed) {
      Seed = seed;
    }

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

      var data    = new List<List<double>>();
      var q       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
      var Ef      = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
      var m       = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
      var omega_0 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 5).ToList();
      var omega   = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();

      var x = new List<double>();

      data.Add(q);
      data.Add(Ef);
      data.Add(m);
      data.Add(omega_0);
      data.Add(omega);
      data.Add(x);

      for (var i = 0; i < q.Count; i++) {
        var res = q[i] * Ef[i] / (m[i] * (Math.Pow(omega_0[i], 2) - Math.Pow(omega[i], 2)));
        x.Add(res);
      }

      return data;
    }
  }
}