1 files changed, 75 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/WeightedDistanceFunction.java b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/WeightedDistanceFunction.java
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+++ b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/WeightedDistanceFunction.java
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+package de.lmu.ifi.dbs.elki.distance.distancefunction;
+/*
+This file is part of ELKI:
+Environment for Developing KDD-Applications Supported by Index-Structures
+
+Copyright (C) 2011
+Ludwig-Maximilians-Universität München
+Lehr- und Forschungseinheit für Datenbanksysteme
+ELKI Development Team
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+This program 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 Affero General Public License for more details.
+
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see <http://www.gnu.org/licenses/>.
+*/
+
+import de.lmu.ifi.dbs.elki.data.NumberVector;
+import de.lmu.ifi.dbs.elki.data.type.VectorFieldTypeInformation;
+import de.lmu.ifi.dbs.elki.math.MathUtil;
+import de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix;
+import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
+
+/**
+ * Provides the Weighted distance for feature vectors.
+ * 
+ * @author Elke Achtert
+ */
+// TODO: Factory with parameterizable weight matrix?
+public class WeightedDistanceFunction extends AbstractVectorDoubleDistanceFunction {
+  /**
+   * The weight matrix.
+   */
+  protected Matrix weightMatrix;
+
+  /**
+   * Provides the Weighted distance for feature vectors.
+   * 
+   * @param weightMatrix weight matrix
+   */
+  public WeightedDistanceFunction(Matrix weightMatrix) {
+    super();
+    this.weightMatrix = weightMatrix;
+    assert (weightMatrix.getColumnDimensionality() == weightMatrix.getRowDimensionality());
+  }
+
+  /**
+   * Provides the Weighted distance for feature vectors.
+   * 
+   * @return the Weighted distance between the given two vectors
+   */
+  @Override
+  public double doubleDistance(NumberVector<?, ?> o1, NumberVector<?, ?> o2) {
+    if(o1.getDimensionality() != o2.getDimensionality()) {
+      throw new IllegalArgumentException("Different dimensionality of FeatureVectors" + "\n  first argument: " + o1.toString() + "\n  second argument: " + o2.toString());
+    }
+
+    Vector o1_minus_o2 = o1.getColumnVector().minus(o2.getColumnVector());
+    double dist = MathUtil.mahalanobisDistance(weightMatrix, o1_minus_o2);
+
+    return dist;
+  }
+
+  @Override
+  public VectorFieldTypeInformation<? super NumberVector<?, ?>> getInputTypeRestriction() {
+    return VectorFieldTypeInformation.get(NumberVector.class, weightMatrix.getColumnDimensionality());
+  }
+}
+\ No newline at end of file