source: branches/3075_aifeynman_instances/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs @ 17638

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using HeuristicLab.Common;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.Instances.DataAnalysis {
  public class Feynman7 : FeynmanDescriptor{
 public override string Name { get { return "Feynman I.11.19 A = x1*y1+x2*y2+x3*y3"; } }

 protected override string TargetVariable { get { return "A"; } }
    protected override string[] VariableNames { get { return new string[] { "x1", "x2", "x3", "y1", "y2", "y3", "A"}; } }
    protected override string[] AllowedInputVariables { get { return new string[] {"x1", "x2", "x3", "y1", "y2", "y3"}; } }
    protected override int TrainingPartitionStart { get { return 0; } }
    protected override int TrainingPartitionEnd { get { return 80; } }
    protected override int TestPartitionStart { get { return 80; } }
    protected override int TestPartitionEnd { get { return 100; } }
    public int Seed { get; private set; }

    public Feynman7() : this((int)System.DateTime.Now.Ticks) { }

    public Feynman7(int seed) {
      Seed = seed;
    }

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

      var data = new List<List<double>>();
      var x1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var x2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var x3 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var y1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var y2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();
      var y3 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 5).ToList();

      var A = new List<double>();

      data.Add(x1);
      data.Add(x2);
      data.Add(x3);
      data.Add(y1);
      data.Add(y2);
      data.Add(y3);
      data.Add(A);

      for (var i = 0; i < x1.Count; i++) {
        var res = x1[i] * y1[i] + x2[i] * y2[i] + x3[i] * y3[i];
        A.Add(res);
      }


      return data;
    }
  }
}