Changeset 10086 for branches/HeuristicLab.Problems.GPDL/Examples/symbreg HEAL.txt

Timestamp:

10/27/13 20:17:17 (10 years ago)

Author:

gkronber

Message:

#2026 worked on random search solver (now all examples are working)

File:

• branches/HeuristicLab.Problems.GPDL/Examples/symbreg HEAL.txt (modified) (5 diffs)

branches/HeuristicLab.Problems.GPDL/Examples/symbreg HEAL.txt

@@ -5 +5 @@
   double[] y;
   string[] variableNames;
+  int[] rows;
   Dictionary<string,int> nameToCol;
   
@@ -19 +20 @@
 
   double RSquared(IEnumerable<double> xs, IEnumerable<double> ys) {
-     HeuristicLab.Problems.DataAnalysis.OnlineCalculatorError error;
-     var r2 = HeuristicLab.Problems.DataAnalysis.OnlinePearsonsRSquaredCalculator.Calculate(xs, ys, out error);
-     if(error == HeuristicLab.Problems.DataAnalysis.OnlineCalculatorError.None) return r2;
-     else return 0.0;
-  }
+    // calculate Pearson's correlation in one pass over xs and ys
+    double sumx = 0.0;
+    double sumy = 0.0;
+    double sumxSq = 0.0;
+    double sumySq = 0.0;
+    double sumxy = 0.0;
+    int n = 0;
+    var xEnum = xs.GetEnumerator();
+    var yEnum = ys.GetEnumerator();
+    while(xEnum.MoveNext() & yEnum.MoveNext()) {
+      sumx += xEnum.Current;
+      sumy += yEnum.Current;
+      sumxSq += xEnum.Current * xEnum.Current;
+      sumySq += yEnum.Current * yEnum.Current;
+      sumxy += xEnum.Current * yEnum.Current;
+      n++;
+    }
+    System.Diagnostics.Debug.Assert(!(xEnum.MoveNext() | yEnum.MoveNext()));
+
+    double num;
+    double den;
+    double r = 0.0;
+    num = sumxy - ( ( sumx * sumy ) / n );
+    den = Math.Sqrt( ( sumxSq - ( sumx*sumx ) / n ) *
+                     ( sumySq - ( sumy*sumy ) / n ) );
+    if(den > 0){
+      r = num / den;
+    }
+    return r*r;
+  } 
 >>
 
@@ -33 +59 @@
   x = new double[n, 10];
   y = new double[n];
-  for(int row = 0; row < 500; row++) {
+  for(int row = 0; row < n; row++) {
     for(int col = 0; col < 10; col++) {
       x[row, col] = rand.NextDouble() * 2.0 - 1.0;
@@ -43 +69 @@
              x[row, 2] * x[row, 5] + x[row, 9];
   }
+
+  rows = System.Linq.Enumerable.Range(0, n).ToArray();
 >>
 
@@ -90 +118 @@
   .
 
-MAXIMIZE                                                   /* could also use the keyword MINIMIZE here */
+MAXIMIZE
   << 
-    var rows = System.Linq.Enumerable.Range(0, x.GetLength(0));
     var predicted = rows.Select(r => {
       double result;