Changeset 14236 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour

Timestamp:

08/05/16 11:58:52 (8 years ago)

Author:

gkronber

Message:

#2653: added synchronization in NearestNeighbourModel and made some related changes to GradientBoostedTreesModelSurrogate

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs

@@ -200 +200 @@
           x[column] = inputData[row, column];
         }
-        int actNeighbours = alglib.nearestneighbor.kdtreequeryknn(kdTree, x, k, false);
-        alglib.nearestneighbor.kdtreequeryresultsdistances(kdTree, ref dists);
-        alglib.nearestneighbor.kdtreequeryresultsxy(kdTree, ref neighbours); // gkronber: this call changes the kdTree data structure
+        int numNeighbours;
+        lock (kdTree) { // gkronber: the following calls change the kdTree data structure
+          numNeighbours = alglib.nearestneighbor.kdtreequeryknn(kdTree, x, k, false);
+          alglib.nearestneighbor.kdtreequeryresultsdistances(kdTree, ref dists);
+          alglib.nearestneighbor.kdtreequeryresultsxy(kdTree, ref neighbours);
+        }
 
         double distanceWeightedValue = 0.0;
         double distsSum = 0.0;
-        for (int i = 0; i < actNeighbours; i++) {
+        for (int i = 0; i < numNeighbours; i++) {
           distanceWeightedValue += neighbours[i, columns] / dists[i];
           distsSum += 1.0 / dists[i];
@@ -233 +236 @@
           x[column] = inputData[row, column];
         }
-        int actNeighbours = alglib.nearestneighbor.kdtreequeryknn(kdTree, x, k, false);
-        alglib.nearestneighbor.kdtreequeryresultsdistances(kdTree, ref dists);
-        alglib.nearestneighbor.kdtreequeryresultsxy(kdTree, ref neighbours);
-
+        int numNeighbours;
+        lock (kdTree) {
+          // gkronber: the following calls change the kdTree data structure
+          numNeighbours = alglib.nearestneighbor.kdtreequeryknn(kdTree, x, k, false);
+          alglib.nearestneighbor.kdtreequeryresultsdistances(kdTree, ref dists);
+          alglib.nearestneighbor.kdtreequeryresultsxy(kdTree, ref neighbours);
+        }
         Array.Clear(y, 0, y.Length);
-        for (int i = 0; i < actNeighbours; i++) {
+        for (int i = 0; i < numNeighbours; i++) {
           int classValue = (int)Math.Round(neighbours[i, columns]);
           y[classValue]++;