Changeset 12629 for trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy

Timestamp:

07/07/15 10:42:10 (9 years ago)

Author:

abeham

Message:

#2367:

• Using alglib's smatrixevd to do eigendecomposition
• Incremented version to 3.4 as results are not exactly reproducible anymore

Location:

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy

Files:

• 3.3/CMAEvolutionStrategy.cs (modified) (2 diffs)
• 3.4 (copied) (copied from trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.3)
• 3.4/CMAOperators/CMAUpdater.cs (modified) (2 diffs)
• 3.4/HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3.csproj (deleted)
• 3.4/HeuristicLab.Algorithms.CMAEvolutionStrategy-3.4.csproj (copied) (copied from trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.3/HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3.csproj) (2 diffs)
• 3.4/Plugin.cs.frame (modified) (1 diff)
• 3.4/Properties/AssemblyInfo.cs.frame (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.3/CMAEvolutionStrategy.cs

@@ -37 +37 @@
 namespace HeuristicLab.Algorithms.CMAEvolutionStrategy {
   [Item("CMA Evolution Strategy", "An evolution strategy based on covariance matrix adaptation.")]
-  [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 210)]
   [StorableClass]
   public sealed class CMAEvolutionStrategy : HeuristicOptimizationEngineAlgorithm, IStorableContent {
@@ -489 +488 @@
           CMAUpdater = CMAUpdaterParameter.ValidValues.First();
         }
-      }
-      finally { cmaesInitializerSync = false; }
+      } finally { cmaesInitializerSync = false; }
     }
     private void UpdateAnalyzers() {

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.4/CMAOperators/CMAUpdater.cs

@@ -238 +238 @@
       } else {
 
-        // set B <- C
-        for (int i = 0; i < N; i++) {
-          for (int j = 0; j < N; j++) {
-            sp.B[i, j] = sp.C[i, j];
-          }
-        }
-        var success = Eigendecomposition(N, sp.B, sp.D);
+        double[] d;
+        double[,] b;
+        var success = alglib.smatrixevd(sp.C, N, 1, true, out d, out b);
+        Array.Copy(d, sp.D, N);
+        for (var i = 0; i < N; i++)
+          for (var j = 0; j < N; j++)
+            sp.B[i, j] = b[i, j];
 
         DegenerateStateParameter.ActualValue = new BoolValue(!success);
@@ -261 +261 @@
       return base.Apply();
     }
-
-    private bool Eigendecomposition(int N, double[,] B, double[] diagD) {
-      bool result = true;
-      // eigendecomposition
-      var offdiag = new double[N];
-      try {
-        tred2(N, B, diagD, offdiag);
-        tql2(N, diagD, offdiag, B);
-      } catch { result = false; }
-
-      return result;
-    } // eigendecomposition
-
-
-    // Symmetric Householder reduction to tridiagonal form, taken from JAMA package.
-    private void tred2(int n, double[,] V, double[] d, double[] e) {
-
-      //  This is derived from the Algol procedures tred2 by
-      //  Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
-      //  Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
-      //  Fortran subroutine in EISPACK.
-
-      for (int j = 0; j < n; j++) {
-        d[j] = V[n - 1, j];
-      }
-
-      // Householder reduction to tridiagonal form.
-
-      for (int i = n - 1; i > 0; i--) {
-
-        // Scale to avoid under/overflow.
-
-        double scale = 0.0;
-        double h = 0.0;
-        for (int k = 0; k < i; k++) {
-          scale = scale + Math.Abs(d[k]);
-        }
-        if (scale == 0.0) {
-          e[i] = d[i - 1];
-          for (int j = 0; j < i; j++) {
-            d[j] = V[i - 1, j];
-            V[i, j] = 0.0;
-            V[j, i] = 0.0;
-          }
-        } else {
-
-          // Generate Householder vector.
-
-          for (int k = 0; k < i; k++) {
-            d[k] /= scale;
-            h += d[k] * d[k];
-          }
-          double f = d[i - 1];
-          double g = Math.Sqrt(h);
-          if (f > 0) {
-            g = -g;
-          }
-          e[i] = scale * g;
-          h = h - f * g;
-          d[i - 1] = f - g;
-          for (int j = 0; j < i; j++) {
-            e[j] = 0.0;
-          }
-
-          // Apply similarity transformation to remaining columns.
-
-          for (int j = 0; j < i; j++) {
-            f = d[j];
-            V[j, i] = f;
-            g = e[j] + V[j, j] * f;
-            for (int k = j + 1; k <= i - 1; k++) {
-              g += V[k, j] * d[k];
-              e[k] += V[k, j] * f;
-            }
-            e[j] = g;
-          }
-          f = 0.0;
-          for (int j = 0; j < i; j++) {
-            e[j] /= h;
-            f += e[j] * d[j];
-          }
-          double hh = f / (h + h);
-          for (int j = 0; j < i; j++) {
-            e[j] -= hh * d[j];
-          }
-          for (int j = 0; j < i; j++) {
-            f = d[j];
-            g = e[j];
-            for (int k = j; k <= i - 1; k++) {
-              V[k, j] -= (f * e[k] + g * d[k]);
-            }
-            d[j] = V[i - 1, j];
-            V[i, j] = 0.0;
-          }
-        }
-        d[i] = h;
-      }
-
-      // Accumulate transformations.
-
-      for (int i = 0; i < n - 1; i++) {
-        V[n - 1, i] = V[i, i];
-        V[i, i] = 1.0;
-        double h = d[i + 1];
-        if (h != 0.0) {
-          for (int k = 0; k <= i; k++) {
-            d[k] = V[k, i + 1] / h;
-          }
-          for (int j = 0; j <= i; j++) {
-            double g = 0.0;
-            for (int k = 0; k <= i; k++) {
-              g += V[k, i + 1] * V[k, j];
-            }
-            for (int k = 0; k <= i; k++) {
-              V[k, j] -= g * d[k];
-            }
-          }
-        }
-        for (int k = 0; k <= i; k++) {
-          V[k, i + 1] = 0.0;
-        }
-      }
-      for (int j = 0; j < n; j++) {
-        d[j] = V[n - 1, j];
-        V[n - 1, j] = 0.0;
-      }
-      V[n - 1, n - 1] = 1.0;
-      e[0] = 0.0;
-    }
-
-    // Symmetric tridiagonal QL algorithm, taken from JAMA package.
-    private void tql2(int n, double[] d, double[] e, double[,] V) {
-
-      //  This is derived from the Algol procedures tql2, by
-      //  Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
-      //  Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
-      //  Fortran subroutine in EISPACK.
-
-      for (int i = 1; i < n; i++) {
-        e[i - 1] = e[i];
-      }
-      e[n - 1] = 0.0;
-
-      double f = 0.0;
-      double tst1 = 0.0;
-      double eps = Math.Pow(2.0, -52.0);
-      for (int l = 0; l < n; l++) {
-
-        // Find small subdiagonal element
-
-        tst1 = Math.Max(tst1, Math.Abs(d[l]) + Math.Abs(e[l]));
-        int m = l;
-        while (m < n) {
-          if (Math.Abs(e[m]) <= eps * tst1) {
-            break;
-          }
-          m++;
-        }
-
-        // If m == l, d[l] is an eigenvalue,
-        // otherwise, iterate.
-
-        if (m > l) {
-          int iter = 0;
-          do {
-            iter = iter + 1;  // (Could check iteration count here.)
-
-            // Compute implicit shift
-
-            double g = d[l];
-            double p = (d[l + 1] - g) / (2.0 * e[l]);
-            double r = hypot(p, 1.0);
-            if (p < 0) {
-              r = -r;
-            }
-            d[l] = e[l] / (p + r);
-            d[l + 1] = e[l] * (p + r);
-            double dl1 = d[l + 1];
-            double h = g - d[l];
-            for (int i = l + 2; i < n; i++) {
-              d[i] -= h;
-            }
-            f = f + h;
-
-            // Implicit QL transformation.
-
-            p = d[m];
-            double c = 1.0;
-            double c2 = c;
-            double c3 = c;
-            double el1 = e[l + 1];
-            double s = 0.0;
-            double s2 = 0.0;
-            for (int i = m - 1; i >= l; i--) {
-              c3 = c2;
-              c2 = c;
-              s2 = s;
-              g = c * e[i];
-              h = c * p;
-              r = hypot(p, e[i]);
-              e[i + 1] = s * r;
-              s = e[i] / r;
-              c = p / r;
-              p = c * d[i] - s * g;
-              d[i + 1] = h + s * (c * g + s * d[i]);
-
-              // Accumulate transformation.
-
-              for (int k = 0; k < n; k++) {
-                h = V[k, i + 1];
-                V[k, i + 1] = s * V[k, i] + c * h;
-                V[k, i] = c * V[k, i] - s * h;
-              }
-            }
-            p = -s * s2 * c3 * el1 * e[l] / dl1;
-            e[l] = s * p;
-            d[l] = c * p;
-
-            // Check for convergence.
-
-          } while (Math.Abs(e[l]) > eps * tst1);
-        }
-        d[l] = d[l] + f;
-        e[l] = 0.0;
-      }
-
-      // Sort eigenvalues and corresponding vectors.
-
-      for (int i = 0; i < n - 1; i++) {
-        int k = i;
-        double p = d[i];
-        for (int j = i + 1; j < n; j++) {
-          if (d[j] < p) { // NH find smallest k>i
-            k = j;
-            p = d[j];
-          }
-        }
-        if (k != i) {
-          d[k] = d[i]; // swap k and i 
-          d[i] = p;
-          for (int j = 0; j < n; j++) {
-            p = V[j, i];
-            V[j, i] = V[j, k];
-            V[j, k] = p;
-          }
-        }
-      }
-    }
-
-    /** sqrt(a^2 + b^2) without under/overflow. **/
-    private double hypot(double a, double b) {
-      double r = 0;
-      if (Math.Abs(a) > Math.Abs(b)) {
-        r = b / a;
-        r = Math.Abs(a) * Math.Sqrt(1 + r * r);
-      } else if (b != 0) {
-        r = a / b;
-        r = Math.Abs(b) * Math.Sqrt(1 + r * r);
-      }
-      return r;
-    }
   }
 }

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.4/HeuristicLab.Algorithms.CMAEvolutionStrategy-3.4.csproj

@@ -6 +6 @@
     <ProductVersion>9.0.30729</ProductVersion>
     <SchemaVersion>2.0</SchemaVersion>
-    <ProjectGuid>{5E516C4F-9935-437F-8B15-ECEF4451744E}</ProjectGuid>
+    <ProjectGuid>{291010E4-2F4E-4D29-A795-753CFF293FDB}</ProjectGuid>
     <OutputType>Library</OutputType>
     <AppDesignerFolder>Properties</AppDesignerFolder>
     <RootNamespace>HeuristicLab.Algorithms.CMAEvolutionStrategy</RootNamespace>
-    <AssemblyName>HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3</AssemblyName>
+    <AssemblyName>HeuristicLab.Algorithms.CMAEvolutionStrategy-3.4</AssemblyName>
     <TargetFrameworkVersion>v4.5</TargetFrameworkVersion>
     <TargetFrameworkProfile>
@@ -99 +99 @@
   </PropertyGroup>
   <ItemGroup>
+    <Reference Include="ALGLIB-3.7.0, Version=3.7.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">
+      <SpecificVersion>False</SpecificVersion>
+      <HintPath>..\..\bin\ALGLIB-3.7.0.dll</HintPath>
+      <Private>False</Private>
+    </Reference>
     <Reference Include="System" />
     <Reference Include="System.Core">

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.4/Plugin.cs.frame

@@ -26 +26 @@
   /// Plugin class for HeuristicLab.Algorithms.EvolutionStrategy plugin.
   /// </summary>
-  [Plugin("HeuristicLab.Algorithms.CMAEvolutionStrategy", "3.3.11.$WCREV$")]
-  [PluginFile("HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3.dll", PluginFileType.Assembly)]
+  [Plugin("HeuristicLab.Algorithms.CMAEvolutionStrategy", "3.4.11.$WCREV$")]
+  [PluginFile("HeuristicLab.Algorithms.CMAEvolutionStrategy-3.4.dll", PluginFileType.Assembly)]
+  [PluginDependency("HeuristicLab.ALGLIB", "3.7")]
   [PluginDependency("HeuristicLab.Analysis", "3.3")]
   [PluginDependency("HeuristicLab.Collections", "3.3")]

trunk/sources/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.4/Properties/AssemblyInfo.cs.frame

@@ -52 +52 @@
 // You can specify all the values or you can default the Revision and Build Numbers 
 // by using the '*' as shown below:
-[assembly: AssemblyVersion("3.3.0.0")]
-[assembly: AssemblyFileVersion("3.3.11.$WCREV$")]
+[assembly: AssemblyVersion("3.4.0.0")]
+[assembly: AssemblyFileVersion("3.4.11.$WCREV$")]