Changeset 10402 for branches/Sliding Window GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Views

Timestamp:

01/27/14 14:14:42 (11 years ago)

Author:

bburlacu

Message:

#1837: Added missing license information headers. Added storable constructors and changed properties in SlidingWindowBestSolutionsCollection to return IEnumerables instead of Lists.

File:

• branches/Sliding Window GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Views/3.4/SlidingWindowBestSolutionsCollectionView.cs (modified) (4 diffs)

branches/Sliding Window GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Views/3.4/SlidingWindowBestSolutionsCollectionView.cs

@@ -1 @@
-using System;
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -43 +64 @@
       var dataGridView = (DataGridView)sender;
       var cell = dataGridView.SelectedCells[0];
-      var tree = Content.BestSolutions[cell.RowIndex];
+      var bestSolutions = Content.BestSolutions.ToList();
+      var tree = bestSolutions[cell.RowIndex];
       var model = Content.CreateModel(tree, Content.Interpreter);
       var solution = Content.CreateSolution(model, Content.ProblemData);
@@ -93 +115 @@
 
     private void UpdateQualitiesMap() {
-      var qualitiesMap = new DoubleMatrix(Content.BestSolutions.Count, Content.SlidingWindowPositions.Count + 1);
+      var bestSolutions = Content.BestSolutions.ToList();
+      var swPositions = Content.SlidingWindowPositions.ToList();
+      var qualitiesMap = new DoubleMatrix(bestSolutions.Count, swPositions.Count + 1);
       qualitiesMap.ColumnNames = Content.SlidingWindowPositions.Select(x => x.Start + "-" + x.End).Concat(new List<string> { "Training" });
-      qualitiesMap.RowNames = Enumerable.Range(1, Content.BestSolutions.Count).Select(x => "M" + x);
+      qualitiesMap.RowNames = Enumerable.Range(1, bestSolutions.Count).Select(x => "M" + x);
       double min = 0, max = 0;
 
       for (int i = 0; i < qualitiesMap.Columns - 1; ++i) {
-        var pos = Content.SlidingWindowPositions[i];
+        var pos = swPositions[i];
         var rows = Enumerable.Range(pos.Start, pos.End - pos.Start).ToList();
 
         for (int j = 0; j < qualitiesMap.Rows; ++j) {
-          var tree = Content.BestSolutions[j];
+          var tree = bestSolutions[j];
           var q = CalculateQuality(tree, rows);
           if (min > q) min = q;
@@ -112 +136 @@
       // deal separately with the last column which represents the whole training partition interval
       for (int j = 0; j < qualitiesMap.Rows; ++j) {
-        var tree = Content.BestSolutions[j];
+        var tree = bestSolutions[j];
         var q = CalculateQuality(tree, Content.ProblemData.TrainingIndices);
         if (min > q) min = q;