1 files changed, 59 insertions, 30 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/minkowski/WeightedSquaredEuclideanDistanceFunction.java b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/minkowski/WeightedSquaredEuclideanDistanceFunction.java
index 4e361c10..a238ba1d 100644
--- a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/minkowski/WeightedSquaredEuclideanDistanceFunction.java
+++ b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/minkowski/WeightedSquaredEuclideanDistanceFunction.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski;
  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
@@ -27,15 +27,20 @@ import java.util.Arrays;
 
 import de.lmu.ifi.dbs.elki.data.NumberVector;
 import de.lmu.ifi.dbs.elki.data.spatial.SpatialComparable;
-import de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialDoubleDistanceNorm;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialNorm;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.WeightedNumberVectorDistanceFunction;
+import de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleListParameter;
 
 /**
- * Provides the squared Euclidean distance for FeatureVectors. This results in
- * the same rankings, but saves computing the square root as often.
+ * Squared Euclidean distance for {@link NumberVector}s. This results in the
+ * same rankings as Euclidean distance, but saves computing the square root.
  * 
  * @author Arthur Zimek
  */
-public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDoubleDistanceNorm {
+public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialNorm implements WeightedNumberVectorDistanceFunction<NumberVector> {
   /**
    * Weight array
    */
@@ -44,24 +49,18 @@ public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDou
   /**
    * Constructor.
    * 
-   * @param weights
+   * @param weights Weight vector
    */
   public WeightedSquaredEuclideanDistanceFunction(double[] weights) {
     super();
     this.weights = weights;
   }
 
-  /**
-   * Provides the squared Euclidean distance between the given two vectors.
-   * 
-   * @return the squared Euclidean distance between the given two vectors as raw
-   *         double value
-   */
   @Override
-  public double doubleDistance(NumberVector<?> v1, NumberVector<?> v2) {
+  public double distance(NumberVector v1, NumberVector v2) {
     final int dim = dimensionality(v1, v2, weights.length);
     double agg = 0.;
-    for (int d = 0; d < dim; d++) {
+    for(int d = 0; d < dim; d++) {
       final double delta = (v1.doubleValue(d) - v2.doubleValue(d));
       agg += delta * delta * weights[d];
     }
@@ -69,10 +68,10 @@ public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDou
   }
 
   @Override
-  public double doubleNorm(NumberVector<?> obj) {
+  public double norm(NumberVector obj) {
     final int dim = obj.getDimensionality();
     double agg = 0.;
-    for (int d = 0; d < dim; d++) {
+    for(int d = 0; d < dim; d++) {
       final double delta = obj.doubleValue(dim);
       agg += delta * delta * weights[d];
     }
@@ -80,23 +79,25 @@ public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDou
   }
 
   @Override
-  public double doubleMinDist(SpatialComparable mbr1, SpatialComparable mbr2) {
+  public double minDist(SpatialComparable mbr1, SpatialComparable mbr2) {
     // Optimization for the simplest case
-    if (mbr1 instanceof NumberVector) {
-      if (mbr2 instanceof NumberVector) {
-        return doubleDistance((NumberVector<?>) mbr1, (NumberVector<?>) mbr2);
+    if(mbr1 instanceof NumberVector) {
+      if(mbr2 instanceof NumberVector) {
+        return distance((NumberVector) mbr1, (NumberVector) mbr2);
       }
     }
     // TODO: optimize for more simpler cases: obj vs. rect?
     final int dim = dimensionality(mbr1, mbr2, weights.length);
     double agg = 0;
-    for (int d = 0; d < dim; d++) {
+    for(int d = 0; d < dim; d++) {
       final double diff;
-      if (mbr1.getMax(d) < mbr2.getMin(d)) {
+      if(mbr1.getMax(d) < mbr2.getMin(d)) {
         diff = mbr2.getMin(d) - mbr1.getMax(d);
-      } else if (mbr1.getMin(d) > mbr2.getMax(d)) {
+      }
+      else if(mbr1.getMin(d) > mbr2.getMax(d)) {
         diff = mbr1.getMin(d) - mbr2.getMax(d);
-      } else { // The mbrs intersect!
+      }
+      else { // The mbrs intersect!
         continue;
       }
       agg += diff * diff * weights[d];
@@ -111,16 +112,16 @@ public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDou
 
   @Override
   public boolean equals(Object obj) {
-    if (this == obj) {
+    if(this == obj) {
       return true;
     }
-    if (obj == null) {
+    if(obj == null) {
       return false;
     }
-    if (!(obj instanceof WeightedSquaredEuclideanDistanceFunction)) {
-      if (obj.getClass().equals(SquaredEuclideanDistanceFunction.class)) {
-        for (double d : weights) {
-          if (d != 1.0) {
+    if(!(obj instanceof WeightedSquaredEuclideanDistanceFunction)) {
+      if(obj.getClass().equals(SquaredEuclideanDistanceFunction.class)) {
+        for(double d : weights) {
+          if(d != 1.0) {
             return false;
           }
         }
@@ -131,4 +132,32 @@ public class WeightedSquaredEuclideanDistanceFunction extends AbstractSpatialDou
     WeightedSquaredEuclideanDistanceFunction other = (WeightedSquaredEuclideanDistanceFunction) obj;
     return Arrays.equals(this.weights, other.weights);
   }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractParameterizer {
+    /**
+     * Weight array
+     */
+    protected double[] weights;
+
+    @Override
+    protected void makeOptions(Parameterization config) {
+      super.makeOptions(config);
+      DoubleListParameter weightsP = new DoubleListParameter(WEIGHTS_ID);
+      if(config.grab(weightsP)) {
+        weights = ArrayLikeUtil.toPrimitiveDoubleArray(weightsP.getValue());
+      }
+    }
+
+    @Override
+    protected WeightedSquaredEuclideanDistanceFunction makeInstance() {
+      return new WeightedSquaredEuclideanDistanceFunction(weights);
+    }
+  }
 }