Changeset 7759 for branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/ValueGenerator.cs

Timestamp:

04/24/12 16:37:40 (12 years ago)

Author:

sforsten

Message:

#1784:

• deleted ClassificationData and RegressionData. RegressionProblemData and ClassificationProblemData are used instead
• deleted not needed Transformer
• ValueGenerator is now a static class and yield return is used return IEnumerable

File:

• branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/ValueGenerator.cs (modified) (1 diff)

branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/ValueGenerator.cs

@@ -26 +26 @@
 using HeuristicLab.Random;
 namespace HeuristicLab.Problems.Instances.Regression {
-  public class ValueGenerator {
-    protected static FastRandom rand = new FastRandom();
+  public static class ValueGenerator {
+    private static FastRandom rand = new FastRandom();
 
     public static IEnumerable<double> GenerateSteps(double start, double end, double stepWidth) {
-      return Enumerable.Range(0, (int)Math.Round(((end - start) / stepWidth) + 1))
-                                      .Select(i => (start + i * stepWidth));
+      int steps = (int)Math.Round(((end - start) / stepWidth) + 1);
+      for (int i = 0; i < steps; i++)
+        yield return start + i * stepWidth;
     }
 
     public static IEnumerable<double> GenerateUniformDistributedValues(int amount, double start, double end) {
-      List<double> values = new List<double>();
-      for (int i = 0; i < amount; i++) {
-        values.Add(rand.NextDouble() * (end - start) + start);
-      }
-      return values;
+      for (int i = 0; i < amount; i++)
+        yield return rand.NextDouble() * (end - start) + start;
     }
 
     public static IEnumerable<double> GenerateNormalDistributedValues(int amount, double mu, double sigma) {
-      List<double> values = new List<double>();
-      for (int i = 0; i < amount; i++) {
-        values.Add(NormalDistributedRandom.NextDouble(rand, mu, sigma));
-      }
-      return values;
+      for (int i = 0; i < amount; i++)
+        yield return NormalDistributedRandom.NextDouble(rand, mu, sigma);
     }