Changeset 17788
 Timestamp:
 12/02/20 15:45:54 (4 months ago)
 File:

 1 edited
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trunk/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlinePearsonsRCalculator.cs
r17787 r17788 26 26 namespace HeuristicLab.Problems.DataAnalysis { 27 27 public class OnlinePearsonsRCalculator : DeepCloneable, IOnlineCalculator { 28 private double sumX; 29 private double sumY; 30 private double sumWe; 31 32 private double sumXX; 33 private double sumYY; 34 private double sumXY; 35 36 private OnlineCalculatorError errorState; 28 private OnlineCovarianceCalculator covCalculator = new OnlineCovarianceCalculator(); 29 private OnlineMeanAndVarianceCalculator sxCalculator = new OnlineMeanAndVarianceCalculator(); 30 private OnlineMeanAndVarianceCalculator syCalculator = new OnlineMeanAndVarianceCalculator(); 37 31 38 32 public double R { 39 33 get { 40 if (!(sumXX > 0.0 && sumYY > 0.0)) { 41 return (sumXX == sumYY) ? 1.0 : 0.0; 34 double xVar = sxCalculator.PopulationVariance; 35 double yVar = syCalculator.PopulationVariance; 36 if (xVar.IsAlmost(0.0)  yVar.IsAlmost(0.0)) { 37 return 0.0; 38 } else { 39 var r = covCalculator.Covariance / (Math.Sqrt(xVar) * Math.Sqrt(yVar)); 40 if (r < 1.0) r = 1.0; 41 else if (r > 1.0) r = 1.0; 42 return r; 42 43 } 43 return sumXY / Math.Sqrt(sumXX * sumYY);44 44 } 45 45 } 46 47 public double MeanX { get { return sumX / sumWe; } }48 49 public double MeanY { get { return sumY / sumWe; } }50 51 public double NaiveCovariance { get { return sumXY / sumWe; } }52 53 public double SampleCovariance {54 get {55 if (sumWe > 1.0) {56 errorState = OnlineCalculatorError.None;57 return sumXY / (sumWe  1);58 }59 errorState = OnlineCalculatorError.InsufficientElementsAdded;60 return double.NaN;61 }62 }63 64 public double NaiveVarianceX { get { return sumXX / sumWe; } }65 66 public double SampleVarianceX {67 get {68 if (sumWe > 1.0) {69 errorState = OnlineCalculatorError.None;70 return sumXX / (sumWe  1);71 }72 errorState = OnlineCalculatorError.InsufficientElementsAdded;73 return double.NaN;74 }75 }76 77 public double NaiveStdevX { get { return Math.Sqrt(NaiveVarianceY); } }78 79 public double SampleStdevX { get { return Math.Sqrt(SampleVarianceX); } }80 81 public double NaiveVarianceY { get { return sumYY / sumWe; } }82 83 public double SampleVarianceY {84 get {85 if (sumWe > 1.0) {86 errorState = OnlineCalculatorError.None;87 return sumYY / (sumWe  1);88 }89 errorState = OnlineCalculatorError.InsufficientElementsAdded;90 return double.NaN;91 }92 }93 94 public double NaiveStdevY { get { return Math.Sqrt(NaiveVarianceY); } }95 96 public double SampleStdevY { get { return Math.Sqrt(SampleVarianceX); } }97 46 98 47 public OnlinePearsonsRCalculator() { } … … 100 49 protected OnlinePearsonsRCalculator(OnlinePearsonsRCalculator original, Cloner cloner) 101 50 : base(original, cloner) { 102 sumX = original.sumX; 103 sumY = original.sumY; 104 sumXX = original.sumXX; 105 sumYY = original.sumYY; 106 sumXY = original.sumXY; 107 sumWe = original.sumWe; 108 errorState = original.ErrorState; 51 covCalculator = cloner.Clone(original.covCalculator); 52 sxCalculator = cloner.Clone(original.sxCalculator); 53 syCalculator = cloner.Clone(original.syCalculator); 109 54 } 110 55 public override IDeepCloneable Clone(Cloner cloner) { … … 114 59 #region IOnlineCalculator Members 115 60 public OnlineCalculatorError ErrorState { 116 get { return errorState; }61 get { return covCalculator.ErrorState  sxCalculator.PopulationVarianceErrorState  syCalculator.PopulationVarianceErrorState; } 117 62 } 118 63 public double Value { … … 120 65 } 121 66 public void Reset() { 122 sumXX = sumYY = sumXY = sumX = sumY = sumWe = 0.0; 123 errorState = OnlineCalculatorError.None; 67 covCalculator.Reset(); 68 sxCalculator.Reset(); 69 syCalculator.Reset(); 124 70 } 125 71 126 72 public void Add(double x, double y) { 127 if (sumWe <= 0.0) { 128 sumX = x; 129 sumY = y; 130 sumWe = 1; 131 return; 132 } 133 // Delta to previous mean 134 double deltaX = x * sumWe  sumX, deltaY = y * sumWe  sumY; 135 double oldWe = sumWe; 136 // Incremental update 137 sumWe += 1; 138 double f = 1.0 / (sumWe * oldWe); 139 // Update 140 sumXX += f * deltaX * deltaX; 141 sumYY += f * deltaY * deltaY; 142 // should equal weight * deltaY * neltaX! 143 sumXY += f * deltaX * deltaY; 144 // Update means 145 sumX += x; 146 sumY += y; 73 // no need to check validity of values explicitly here as it is checked in all three evaluators 74 covCalculator.Add(x, y); 75 sxCalculator.Add(x); 76 syCalculator.Add(y); 147 77 } 148 78 … … 150 80 151 81 public static double Calculate(IEnumerable<double> first, IEnumerable<double> second, out OnlineCalculatorError errorState) { 152 var x = first.GetEnumerator(); x.MoveNext(); 153 var y = second.GetEnumerator(); y.MoveNext(); 154 double sumXX = 0.0, sumYY = 0.0, sumXY = 0.0; 155 double sumX = x.Current, sumY = y.Current; 156 int i = 1; 82 IEnumerator<double> firstEnumerator = first.GetEnumerator(); 83 IEnumerator<double> secondEnumerator = second.GetEnumerator(); 84 var calculator = new OnlinePearsonsRCalculator(); 157 85 158 // Inlined computation of Pearson correlation, to avoid allocating objects 159 // This is a numerically stabilized version, avoiding sumofsquares. 160 while (x.MoveNext() & y.MoveNext()) { 161 double xv = x.Current, yv = y.Current; 162 // Delta to previous mean 163 double deltaX = xv * i  sumX, deltaY = yv * i  sumY; 164 // Increment count first 165 double oldi = i; // Convert to double! 166 ++i; 167 double f = 1.0 / (i * oldi); 168 // Update 169 sumXX += f * deltaX * deltaX; 170 sumYY += f * deltaY * deltaY; 171 // should equal deltaY * deltaX! 172 sumXY += f * deltaX * deltaY; 173 // Update sums 174 sumX += xv; 175 sumY += yv; 86 // always move forward both enumerators (do not use shortcircuit evaluation!) 87 while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) { 88 double original = firstEnumerator.Current; 89 double estimated = secondEnumerator.Current; 90 calculator.Add(original, estimated); 91 if (calculator.ErrorState != OnlineCalculatorError.None) break; 176 92 } 177 93 178 errorState = OnlineCalculatorError.None; 179 // One or both series were constant: 180 return !(sumXX > 0.0 && sumYY > 0.0) ? sumXX == sumYY ? 1.0 : 0.0 : // 181 sumXY / Math.Sqrt(sumXX * sumYY); 94 // check if both enumerators are at the end to make sure both enumerations have the same length 95 if (calculator.ErrorState == OnlineCalculatorError.None && 96 (secondEnumerator.MoveNext()  firstEnumerator.MoveNext())) { 97 throw new ArgumentException("Number of elements in first and second enumeration doesn't match."); 98 } else { 99 errorState = calculator.ErrorState; 100 return calculator.R; 101 } 182 102 } 183 103 }
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