1 files changed, 34 insertions, 32 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/index/preprocessed/localpca/KNNQueryFilteredPCAIndex.java b/src/de/lmu/ifi/dbs/elki/index/preprocessed/localpca/KNNQueryFilteredPCAIndex.java
index 89c10bf2..49197bda 100644
--- a/src/de/lmu/ifi/dbs/elki/index/preprocessed/localpca/KNNQueryFilteredPCAIndex.java
+++ b/src/de/lmu/ifi/dbs/elki/index/preprocessed/localpca/KNNQueryFilteredPCAIndex.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.index.preprocessed.localpca;
  This file is part of ELKI:
  Environment for Developing KDD-Applications Supported by Index-Structures
 
- Copyright (C) 2013
+ Copyright (C) 2014
  Ludwig-Maximilians-Universität München
  Lehr- und Forschungseinheit für Datenbanksysteme
  ELKI Development Team
@@ -26,12 +26,11 @@ package de.lmu.ifi.dbs.elki.index.preprocessed.localpca;
 import de.lmu.ifi.dbs.elki.data.NumberVector;
 import de.lmu.ifi.dbs.elki.database.QueryUtil;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDRef;
-import de.lmu.ifi.dbs.elki.database.ids.distance.KNNList;
+import de.lmu.ifi.dbs.elki.database.ids.KNNList;
 import de.lmu.ifi.dbs.elki.database.query.knn.KNNQuery;
 import de.lmu.ifi.dbs.elki.database.relation.Relation;
 import de.lmu.ifi.dbs.elki.database.relation.RelationUtil;
 import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
-import de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance;
 import de.lmu.ifi.dbs.elki.logging.Logging;
 import de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner;
 import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
@@ -53,10 +52,9 @@ import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.IntParameter;
  * 
  * @param <NV> Vector type
  */
-// TODO: loosen DoubleDistance restriction.
 @Title("Knn Query Based Local PCA Preprocessor")
 @Description("Materializes the local PCA and the locally weighted matrix of objects of a database. The PCA is based on k nearest neighbor queries.")
-public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends AbstractFilteredPCAIndex<NV> {
+public class KNNQueryFilteredPCAIndex<NV extends NumberVector> extends AbstractFilteredPCAIndex<NV> {
   /**
    * Logger.
    */
@@ -65,10 +63,10 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
   /**
    * The kNN query instance we use.
    */
-  private final KNNQuery<NV, DoubleDistance> knnQuery;
+  private final KNNQuery<NV> knnQuery;
 
   /**
-   * Query k.
+   * Number of neighbors to query.
    */
   private final int k;
 
@@ -80,7 +78,7 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
    * @param knnQuery KNN Query to use
    * @param k k value
    */
-  public KNNQueryFilteredPCAIndex(Relation<NV> relation, PCAFilteredRunner<NV> pca, KNNQuery<NV, DoubleDistance> knnQuery, int k) {
+  public KNNQueryFilteredPCAIndex(Relation<NV> relation, PCAFilteredRunner pca, KNNQuery<NV> knnQuery, int k) {
     super(relation, pca);
     this.knnQuery = knnQuery;
     this.k = k;
@@ -92,7 +90,7 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
   }
 
   @Override
-  protected KNNList<DoubleDistance> objectsForPCA(DBIDRef id) {
+  protected KNNList objectsForPCA(DBIDRef id) {
     return knnQuery.getKNNForDBID(id, k);
   }
 
@@ -125,25 +123,11 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
    * @apiviz.landmark
    * @apiviz.uses KNNQueryFilteredPCAIndex oneway - - «create»
    */
-  public static class Factory<V extends NumberVector<?>> extends AbstractFilteredPCAIndex.Factory<V, KNNQueryFilteredPCAIndex<V>> {
+  public static class Factory<V extends NumberVector> extends AbstractFilteredPCAIndex.Factory<V, KNNQueryFilteredPCAIndex<V>> {
     /**
-     * Optional parameter to specify the number of nearest neighbors considered
-     * in the PCA, must be an integer greater than 0. If this parameter is not
-     * set, k is set to three times of the dimensionality of the database
-     * objects.
-     * <p>
-     * Key: {@code -localpca.k}
-     * </p>
-     * <p>
-     * Default value: three times of the dimensionality of the database objects
-     * </p>
+     * Number of neighbors to query.
      */
-    public static final OptionID K_ID = new OptionID("localpca.k", "The number of nearest neighbors considered in the PCA. " + "If this parameter is not set, k ist set to three " + "times of the dimensionality of the database objects.");
-
-    /**
-     * Holds the value of {@link #K_ID}.
-     */
-    private Integer k = null;
+    private int k;
 
     /**
      * Constructor.
@@ -152,7 +136,7 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
      * @param pca PCA class
      * @param k k
      */
-    public Factory(DistanceFunction<V, DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, Integer k) {
+    public Factory(DistanceFunction<V> pcaDistanceFunction, PCAFilteredRunner pca, int k) {
       super(pcaDistanceFunction, pca);
       this.k = k;
     }
@@ -160,7 +144,7 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
     @Override
     public KNNQueryFilteredPCAIndex<V> instantiate(Relation<V> relation) {
       // TODO: set bulk flag, once the parent class supports bulk.
-      KNNQuery<V, DoubleDistance> knnquery = QueryUtil.getKNNQuery(relation, pcaDistanceFunction, k);
+      KNNQuery<V> knnquery = QueryUtil.getKNNQuery(relation, pcaDistanceFunction, k);
       return new KNNQueryFilteredPCAIndex<>(relation, pca, knnquery, k);
     }
 
@@ -171,16 +155,34 @@ public class KNNQueryFilteredPCAIndex<NV extends NumberVector<?>> extends Abstra
      * 
      * @apiviz.exclude
      */
-    public static class Parameterizer<NV extends NumberVector<?>> extends AbstractFilteredPCAIndex.Factory.Parameterizer<NV, KNNQueryFilteredPCAIndex<NV>> {
+    public static class Parameterizer<NV extends NumberVector> extends AbstractFilteredPCAIndex.Factory.Parameterizer<NV, KNNQueryFilteredPCAIndex<NV>> {
+      /**
+       * Optional parameter to specify the number of nearest neighbors
+       * considered in the PCA, must be an integer greater than 0. If this
+       * parameter is not set, k is set to three times of the dimensionality of
+       * the database objects.
+       * <p>
+       * Key: {@code -localpca.k}
+       * </p>
+       * <p>
+       * Default value: three times of the dimensionality of the database
+       * objects
+       * </p>
+       */
+      public static final OptionID K_ID = new OptionID("localpca.k", "The number of nearest neighbors considered in the PCA. " + "If this parameter is not set, k ist set to three " + "times of the dimensionality of the database objects.");
+
+      /**
+       * Number of neighbors to query.
+       */
       protected int k = 0;
 
       @Override
       protected void makeOptions(Parameterization config) {
         super.makeOptions(config);
-        final IntParameter kP = new IntParameter(K_ID);
-        kP.addConstraint(CommonConstraints.GREATER_EQUAL_ONE_INT);
+        final IntParameter kP = new IntParameter(K_ID) //
+        .addConstraint(CommonConstraints.GREATER_THAN_ONE_INT);
         if(config.grab(kP)) {
-          k = kP.getValue();
+          k = kP.intValue();
         }
       }