1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.Linq;
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4 | using System.Text;
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5 | using System.Threading.Tasks;
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6 | using HeuristicLab.Common;
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7 | using HeuristicLab.Random;
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8 |
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9 | namespace HeuristicLab.Problems.Instances.DataAnalysis {
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10 | public class Feynman3 : FeynmanDescriptor{
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11 | public override string Name { get { return "Feynman I.6.2b f = exp(-((theta-theta1)/sigma)^2/2)/(sqrt(2*pi)*sigma)"; } }
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12 |
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13 | protected override string TargetVariable { get { return "f"; } }
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14 | protected override string[] VariableNames { get { return new string[] { "sigma", "theta", "theta1", "f"}; } }
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15 | protected override string[] AllowedInputVariables { get { return new string[] { "sigma", "theta", "theta1" }; } }
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16 |
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17 | public int Seed { get; private set; }
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18 |
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19 | public Feynman3() : this((int)System.DateTime.Now.Ticks) { }
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20 |
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21 | public Feynman3(int seed) {
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22 | Seed = seed;
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23 | }
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24 |
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25 | protected override List<List<double>> GenerateValues() {
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26 | var rand = new MersenneTwister((uint)Seed);
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27 |
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28 | var data = new List<List<double>>();
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29 | var sigma = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
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30 | var theta = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
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31 | var theta1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 3).ToList();
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32 |
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33 | var f = new List<double>();
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34 |
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35 | data.Add(sigma);
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36 | data.Add(theta);
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37 | data.Add(theta1);
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38 | data.Add(f);
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39 |
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40 |
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41 | for (var i = 0; i < theta.Count; i++) {
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42 | var res = Math.Exp(-(Math.Pow(theta[i] - theta1[i], 2) / sigma[i]) / 2) / (Math.Sqrt(2 * Math.PI) * sigma[i]);
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43 | f.Add(res);
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44 | }
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45 |
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46 |
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47 | return data;
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48 | }
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49 | }
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50 | }
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