Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs	(revision 17966)
@@ -63,5 +63,5 @@
         var f_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
-        f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        f_noise.AddRange(f.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
         data.Add(f_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var Ef_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
-        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
         data.Add(Ef_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var j_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * j.StandardDeviationPop();
-        j_noise.AddRange(j.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        j_noise.AddRange(j.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(j);
         data.Add(j_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var K_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * K.StandardDeviationPop();
-        K_noise.AddRange(K.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        K_noise.AddRange(K.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(K);
         data.Add(K_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var U_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
-        U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        U_noise.AddRange(U.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
         data.Add(U_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var U_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
-        U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        U_noise.AddRange(U.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
         data.Add(U_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var U_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
-        U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        U_noise.AddRange(U.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
         data.Add(U_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs	(revision 17966)
@@ -10,18 +10,18 @@
     private readonly int trainingSamples;
 
-    public Feynman17() : this((int) DateTime.Now.Ticks, 10000, 10000, null) { }
+    public Feynman17() : this((int)DateTime.Now.Ticks, 10000, 10000, null) { }
 
     public Feynman17(int seed) {
-      Seed            = seed;
+      Seed = seed;
       trainingSamples = 10000;
-      testSamples     = 10000;
-      noiseRatio      = null;
+      testSamples = 10000;
+      noiseRatio = null;
     }
 
     public Feynman17(int seed, int trainingSamples, int testSamples, double? noiseRatio) {
-      Seed                 = seed;
+      Seed = seed;
       this.trainingSamples = trainingSamples;
-      this.testSamples     = testSamples;
-      this.noiseRatio      = noiseRatio;
+      this.testSamples = testSamples;
+      this.noiseRatio = noiseRatio;
     }
 
@@ -29,5 +29,5 @@
       get {
         return string.Format("I.15.3x (x-u*t)/sqrt(1-u**2/c**2) | {0}",
-          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}", noiseRatio));
       }
     }
@@ -36,8 +36,8 @@
 
     protected override string[] VariableNames {
-      get { return new[] {"x", "u", "c", "t", noiseRatio == null ? "x1" : "x1_noise"}; }
+      get { return new[] { "x", "u", "c", "t", noiseRatio == null ? "x1" : "x1_noise" }; }
     }
 
-    protected override string[] AllowedInputVariables { get { return new[] {"x", "u", "c", "t"}; } }
+    protected override string[] AllowedInputVariables { get { return new[] { "x", "u", "c", "t" }; } }
 
     public int Seed { get; private set; }
@@ -49,11 +49,11 @@
 
     protected override List<List<double>> GenerateValues() {
-      var rand = new MersenneTwister((uint) Seed);
+      var rand = new MersenneTwister((uint)Seed);
 
       var data = new List<List<double>>();
-      var x    = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5, 10).ToList();
-      var u    = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
-      var c    = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 20).ToList();
-      var t    = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
+      var x = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5, 10).ToList();
+      var u = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
+      var c = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 3, 20).ToList();
+      var t = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1, 2).ToList();
 
       var x1 = new List<double>();
@@ -71,7 +71,7 @@
 
       if (noiseRatio != null) {
-        var x1_noise    = new List<double>();
-        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x1.StandardDeviationPop();
-        x1_noise.AddRange(x1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        var x1_noise = new List<double>();
+        var sigma_noise = (double)Math.Sqrt(noiseRatio.Value) * x1.StandardDeviationPop();
+        x1_noise.AddRange(x1.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x1);
         data.Add(x1_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var t1_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * t1.StandardDeviationPop();
-        t1_noise.AddRange(t1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        t1_noise.AddRange(t1.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(t1);
         data.Add(t1_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var p_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * p.StandardDeviationPop();
-        p_noise.AddRange(p.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        p_noise.AddRange(p.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(p);
         data.Add(p_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var f_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
-        f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        f_noise.AddRange(f.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
         data.Add(f_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var v1_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v1.StandardDeviationPop();
-        v1_noise.AddRange(v1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        v1_noise.AddRange(v1.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v1);
         data.Add(v1_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var r_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
-        r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        r_noise.AddRange(r.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
         data.Add(r_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var tau_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * tau.StandardDeviationPop();
-        tau_noise.AddRange(tau.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        tau_noise.AddRange(tau.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(tau);
         data.Add(tau_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var L_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L.StandardDeviationPop();
-        L_noise.AddRange(L.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        L_noise.AddRange(L.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L);
         data.Add(L_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var theta1_noise = new List<double>();
         var sigma_noise  = (double) Math.Sqrt(noiseRatio.Value) * theta1.StandardDeviationPop();
-        theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta1);
         data.Add(theta1_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var foc_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * foc.StandardDeviationPop();
-        foc_noise.AddRange(foc.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        foc_noise.AddRange(foc.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(foc);
         data.Add(foc_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var k_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
-        k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        k_noise.AddRange(k.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
         data.Add(k_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs	(revision 17966)
@@ -74,5 +74,5 @@
         var x_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
-        x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        x_noise.AddRange(x.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
         data.Add(x_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs	(revision 17966)
@@ -72,5 +72,5 @@
         var f_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
-        f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        f_noise.AddRange(f.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
         data.Add(f_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var Int_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Int.StandardDeviationPop();
-        Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Int);
         data.Add(Int_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var theta_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * theta.StandardDeviationPop();
-        theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta);
         data.Add(theta_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var Pwr_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
-        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
         data.Add(Pwr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs	(revision 17966)
@@ -81,5 +81,5 @@
         var Pwr_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
-        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
         data.Add(Pwr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var omega_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
-        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
         data.Add(omega_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var omega_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
-        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
         data.Add(omega_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var omega_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
-        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
         data.Add(omega_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var Int_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Int.StandardDeviationPop();
-        Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Int);
         data.Add(Int_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var r_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
-        r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        r_noise.AddRange(r.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
         data.Add(r_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var d_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * d.StandardDeviationPop();
-        d_noise.AddRange(d.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        d_noise.AddRange(d.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(d);
         data.Add(d_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var pr_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * pr.StandardDeviationPop();
-        pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(pr);
         data.Add(pr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var n_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
-        n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        n_noise.AddRange(n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
         data.Add(n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs	(revision 17966)
@@ -78,5 +78,5 @@
         var L_rad_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L_rad.StandardDeviationPop();
-        L_rad_noise.AddRange(L_rad.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        L_rad_noise.AddRange(L_rad.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L_rad);
         data.Add(L_rad_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var v_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
-        v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        v_noise.AddRange(v.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
         data.Add(v_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var D_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * D.StandardDeviationPop();
-        D_noise.AddRange(D.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        D_noise.AddRange(D.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(D);
         data.Add(D_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var kappa_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * kappa.StandardDeviationPop();
-        kappa_noise.AddRange(kappa.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        kappa_noise.AddRange(kappa.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(kappa);
         data.Add(kappa_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var c_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * c.StandardDeviationPop();
-        c_noise.AddRange(c.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        c_noise.AddRange(c.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(c);
         data.Add(c_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs	(revision 17966)
@@ -86,5 +86,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var x_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
-        x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        x_noise.AddRange(x.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
         data.Add(x_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var Pwr_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
-        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
         data.Add(Pwr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var flux_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * flux.StandardDeviationPop();
-        flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(flux);
         data.Add(flux_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs	(revision 17966)
@@ -78,5 +78,5 @@
         var Ef_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
-        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
         data.Add(Ef_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs	(revision 17966)
@@ -74,5 +74,5 @@
         var Ef_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
-        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
         data.Add(Ef_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var E_den_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_den.StandardDeviationPop();
-        E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_den);
         data.Add(E_den_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var m_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * m.StandardDeviationPop();
-        m_noise.AddRange(m.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        m_noise.AddRange(m.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(m);
         data.Add(m_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var Ef_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
-        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
         data.Add(Ef_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var x_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
-        x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        x_noise.AddRange(x.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
         data.Add(x_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var n_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
-        n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        n_noise.AddRange(n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
         data.Add(n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var Pol_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pol.StandardDeviationPop();
-        Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pol);
         data.Add(Pol_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var Pol_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pol.StandardDeviationPop();
-        Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pol);
         data.Add(Pol_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var theta_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * theta.StandardDeviationPop();
-        theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta);
         data.Add(theta_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var B_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * B.StandardDeviationPop();
-        B_noise.AddRange(B.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        B_noise.AddRange(B.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(B);
         data.Add(B_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var rho_c_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * rho_c.StandardDeviationPop();
-        rho_c_noise.AddRange(rho_c.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        rho_c_noise.AddRange(rho_c.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(rho_c);
         data.Add(rho_c_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var j_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * j.StandardDeviationPop();
-        j_noise.AddRange(j.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        j_noise.AddRange(j.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(j);
         data.Add(j_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var A_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
-        A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        A_noise.AddRange(A.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
         data.Add(A_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var k_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
-        k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        k_noise.AddRange(k.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
         data.Add(k_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var flux_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * flux.StandardDeviationPop();
-        flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(flux);
         data.Add(flux_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var E_den_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_den.StandardDeviationPop();
-        E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_den);
         data.Add(E_den_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var I_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
-        I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        I_noise.AddRange(I.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
         data.Add(I_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var mom_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mom.StandardDeviationPop();
-        mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mom);
         data.Add(mom_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var omega_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
-        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
         data.Add(omega_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var mom_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mom.StandardDeviationPop();
-        mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mom);
         data.Add(mom_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var n_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
-        n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        n_noise.AddRange(n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
         data.Add(n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var M_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * M.StandardDeviationPop();
-        M_noise.AddRange(M.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        M_noise.AddRange(M.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(M);
         data.Add(M_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs	(revision 17966)
@@ -85,5 +85,5 @@
         var f_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
-        f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        f_noise.AddRange(f.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
         data.Add(f_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs	(revision 17966)
@@ -69,5 +69,5 @@
         var mu_S_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mu_S.StandardDeviationPop();
-        mu_S_noise.AddRange(mu_S.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        mu_S_noise.AddRange(mu_S.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mu_S);
         data.Add(mu_S_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var n_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
-        n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        n_noise.AddRange(n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
         data.Add(n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs	(revision 17966)
@@ -74,5 +74,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var omega_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
-        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
         data.Add(omega_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var prob_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * prob.StandardDeviationPop();
-        prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(prob);
         data.Add(prob_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs	(revision 17966)
@@ -82,5 +82,5 @@
         var prob_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * prob.StandardDeviationPop();
-        prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(prob);
         data.Add(prob_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs	(revision 17966)
@@ -65,5 +65,5 @@
         var L_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L.StandardDeviationPop();
-        L_noise.AddRange(L.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        L_noise.AddRange(L.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L);
         data.Add(L_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var v_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
-        v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        v_noise.AddRange(v.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
         data.Add(v_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var I_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
-        I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        I_noise.AddRange(I.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
         data.Add(I_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var m_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * m.StandardDeviationPop();
-        m_noise.AddRange(m.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        m_noise.AddRange(m.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(m);
         data.Add(m_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var k_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
-        k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        k_noise.AddRange(k.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
         data.Add(k_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs	(revision 17966)
@@ -71,5 +71,5 @@
         var f_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
-        f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        f_noise.AddRange(f.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
         data.Add(f_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs	(revision 17966)
@@ -83,5 +83,5 @@
         var A_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
-        A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        A_noise.AddRange(A.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
         data.Add(A_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs	(revision 17966)
@@ -73,5 +73,5 @@
         var t_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * t.StandardDeviationPop();
-        t_noise.AddRange(t.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        t_noise.AddRange(t.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(t);
         data.Add(t_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs	(revision 17966)
@@ -85,5 +85,5 @@
         var alpha_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * alpha.StandardDeviationPop();
-        alpha_noise.AddRange(alpha.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        alpha_noise.AddRange(alpha.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(alpha);
         data.Add(alpha_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs	(revision 17966)
@@ -79,5 +79,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs	(revision 17966)
@@ -80,5 +80,5 @@
         var E_n_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
-        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
         data.Add(E_n_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs	(revision 17966)
@@ -78,5 +78,5 @@
         var F_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
-        F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        F_noise.AddRange(F.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
         data.Add(F_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var Volt_noise  = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
-        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
         data.Add(Volt_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var omega_0_noise = new List<double>();
         var sigma_noise   = (double) Math.Sqrt(noiseRatio.Value) * omega_0.StandardDeviationPop();
-        omega_0_noise.AddRange(omega_0.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        omega_0_noise.AddRange(omega_0.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega_0);
         data.Add(omega_0_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var rho_0_noise = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * rho_0.StandardDeviationPop();
-        rho_0_noise.AddRange(rho_0.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        rho_0_noise.AddRange(rho_0.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(rho_0);
         data.Add(rho_0_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs	(revision 17966)
@@ -79,5 +79,5 @@
         var pr_noise    = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * pr.StandardDeviationPop();
-        pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(pr);
         data.Add(pr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var H_G_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * H_G.StandardDeviationPop();
-        H_G_noise.AddRange(H_G.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        H_G_noise.AddRange(H_G.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(H_G);
         data.Add(H_G_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs	(revision 17966)
@@ -84,5 +84,5 @@
         var A_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
-        A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        A_noise.AddRange(A.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
         data.Add(A_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs	(revision 17966)
@@ -74,5 +74,5 @@
         var K_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * K.StandardDeviationPop();
-        K_noise.AddRange(K.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        K_noise.AddRange(K.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(K);
         data.Add(K_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs	(revision 17966)
@@ -77,5 +77,5 @@
         var Pwr_noise   = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
-        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
         data.Add(Pwr_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs	(revision 17966)
@@ -72,5 +72,5 @@
         var theta1_noise = new List<double>();
         var sigma_noise  = (double) Math.Sqrt(noiseRatio.Value) * theta1.StandardDeviationPop();
-        theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta1);
         data.Add(theta1_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs	(revision 17966)
@@ -76,5 +76,5 @@
         var I_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
-        I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        I_noise.AddRange(I.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
         data.Add(I_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs	(revision 17966)
@@ -75,5 +75,5 @@
         var v_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
-        v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        v_noise.AddRange(v.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
         data.Add(v_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs	(revision 17966)
@@ -82,5 +82,5 @@
         var k_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
-        k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        k_noise.AddRange(k.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
         data.Add(k_noise);
Index: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs
===================================================================
--- trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs	(revision 17931)
+++ trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs	(revision 17966)
@@ -74,5 +74,5 @@
         var r_noise     = new List<double>();
         var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
-        r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
+        r_noise.AddRange(r.Select(md => md + NormalDistributedRandomPolar.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
         data.Add(r_noise);
