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 Feynman5 : FeynmanDescriptor{
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11 | public override string Name { get { return "Feynman I.9.18 F = G*m1*m2/((x2-x1)^2+(y2-y1)^2+(z2-z1)^2)"; } }
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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[] { "m1", "m2", "G", "x1", "x2", "y1", "y2", "z1", "z2", "F"}; } }
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15 | protected override string[] AllowedInputVariables { get { return new string[] {"m1", "m2", "G", "x1", "x2", "y1", "y2", "z1", "z2"}; } }
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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 Feynman5() : this((int)System.DateTime.Now.Ticks) { }
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20 |
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21 | public Feynman5(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 m1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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30 | var m2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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31 | var G = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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32 | var x1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 4).ToList();
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33 | var x2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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34 | var y1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 4).ToList();
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35 | var y2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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36 | var z1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 4).ToList();
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37 | var z2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
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38 |
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39 | var F = new List<double>();
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40 |
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41 | data.Add(m1);
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42 | data.Add(m2);
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43 | data.Add(G);
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44 | data.Add(x1);
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45 | data.Add(x2);
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46 | data.Add(y1);
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47 | data.Add(y2);
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48 | data.Add(z1);
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49 | data.Add(z2);
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50 | data.Add(F);
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51 |
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52 | for (var i = 0; i < x1.Count; i++) {
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53 | var res = G[i] * m1[i] * m2[i] / (Math.Pow(x2[i] - x1[i], 2) + Math.Pow(y2[i] - y1[i], 2) + Math.Pow(z2[i] - z1[i], 2));
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54 | F.Add(res);
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55 | }
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56 |
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57 |
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58 | return data;
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59 | }
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60 | }
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61 | }
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