Changeset 18006 for branches/3087_Ceres_Integration/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs
- Timestamp:
- 07/13/21 10:55:09 (3 years ago)
- Location:
- branches/3087_Ceres_Integration
- Files:
-
- 3 edited
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branches/3087_Ceres_Integration
- Property svn:mergeinfo changed
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branches/3087_Ceres_Integration/HeuristicLab.Problems.Instances.DataAnalysis
- Property svn:mergeinfo changed
/trunk/HeuristicLab.Problems.Instances.DataAnalysis (added) merged: 17804-17805,17931,17966-17967,17969,17973-17974
- Property svn:mergeinfo changed
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branches/3087_Ceres_Integration/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs
r17678 r18006 29 29 get { 30 30 return string.Format( 31 "Schwarz 13.132 (Klein-Nishina): pi*alpha**2*h**2/(m**2*c**2)*(omega_0/omega)**2*(omega_0/omega+omega/omega_0-sin(beta)**2) | {0} samples | {1}",32 trainingSamples,noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));31 "Schwarz 13.132 (Klein-Nishina): pi*alpha**2*h**2/(m**2*c**2)*(omega_0/omega)**2*(omega_0/omega+omega/omega_0-sin(beta)**2) | {0}", 32 noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio)); 33 33 } 34 34 } … … 37 37 38 38 protected override string[] VariableNames { 39 get { return n ew[] {"omega", "omega_0", "alpha", "h", "m", "c", "beta", noiseRatio == null ? "A" : "A_noise"}; }39 get { return noiseRatio == null ? new[] { "omega", "omega_0", "alpha", "h", "m", "c", "beta", "A" } : new[] { "omega", "omega_0", "alpha", "h", "m", "c", "beta", "A", "A_noise" }; } 40 40 } 41 41 … … 81 81 } 82 82 83 if (noiseRatio != null) { 84 var A_noise = new List<double>(); 85 var sigma_noise = (double) noiseRatio * A.StandardDeviationPop(); 86 A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise))); 87 data.Remove(A); 88 data.Add(A_noise); 89 } 83 var targetNoise = GetNoisyTarget(A, rand); 84 if (targetNoise != null) data.Add(targetNoise); 90 85 91 86 return data;
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