Import Upstream version 0.6.0

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diff --git a/src/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/RadialBasisFunctionKernelFunction.java b/src/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/RadialBasisFunctionKernelFunction.java
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+++ b/src/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/RadialBasisFunctionKernelFunction.java
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+package de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2013
+ 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.distance.distancefunction.AbstractVectorDoubleDistanceFunction;
+import de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorDoubleSimilarityFunction;
+import de.lmu.ifi.dbs.elki.utilities.Alias;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter;
+
+/**
+ * Provides the Gaussian radial basis function kernel (RBF Kernel).
+ * 
+ * @author Erich Schubert
+ */
+@Alias({ "rbf" })
+public class RadialBasisFunctionKernelFunction extends AbstractVectorDoubleSimilarityFunction {
+  /**
+   * Scaling factor gamma. (= - 1/(2sigma^2))
+   */
+  private final double gamma;
+
+  /**
+   * Constructor.
+   * 
+   * @param sigma Scaling parameter sigma
+   */
+  public RadialBasisFunctionKernelFunction(double sigma) {
+    super();
+    this.gamma = -.5 / (sigma * sigma);
+  }
+
+  @Override
+  public double doubleSimilarity(NumberVector<?> o1, NumberVector<?> o2) {
+    final int dim = AbstractVectorDoubleDistanceFunction.dimensionality(o1, o2);
+    double sim = 0.;
+    for(int i = 0; i < dim; i++) {
+      final double v = o1.doubleValue(i) - o2.doubleValue(i);
+      sim += v * v;
+    }
+    return Math.exp(gamma * sim);
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractParameterizer {
+    /**
+     * Sigma parameter: standard deviation.
+     */
+    public static final OptionID SIGMA_ID = new OptionID("kernel.rbf.sigma", "Standard deviation of the Gaussian RBF kernel.");
+
+    /**
+     * Sigma parameter
+     */
+    protected double sigma = 1.;
+
+    @Override
+    protected void makeOptions(Parameterization config) {
+      super.makeOptions(config);
+      final DoubleParameter sigmaP = new DoubleParameter(SIGMA_ID, 1.);
+      sigmaP.addConstraint(CommonConstraints.GREATER_THAN_ZERO_DOUBLE);
+      if(config.grab(sigmaP)) {
+        sigma = sigmaP.doubleValue();
+      }
+    }
+
+    @Override
+    protected RadialBasisFunctionKernelFunction makeInstance() {
+      return new RadialBasisFunctionKernelFunction(sigma);
+    }
+  }
+}