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diff --git a/src/de/lmu/ifi/dbs/elki/math/statistics/dependence/SlopeInversionDependenceMeasure.java b/src/de/lmu/ifi/dbs/elki/math/statistics/dependence/SlopeInversionDependenceMeasure.java
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+package de.lmu.ifi.dbs.elki.math.statistics.dependence;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2014
+ 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.utilities.datastructures.arraylike.NumberArrayAdapter;
+import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+
+/**
+ * Arrange dimensions based on the entropy of the slope spectrum.
+ * 
+ * Reference:
+ * <p>
+ * Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:<br />
+ * Interactive Data Mining with 3D-Parallel-Coordinate-Trees.<br />
+ * Proceedings of the 2013 ACM International Conference on Management of Data
+ * (SIGMOD), New York City, NY, 2013.
+ * </p>
+ *
+ * TODO: shouldn't this be normalized by the single-dimension entropies or so?
+ * 
+ * @author Erich Schubert
+ * @author Robert Rödler
+ */
+@Reference(authors = "Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek", //
+title = "Interactive Data Mining with 3D-Parallel-Coordinate-Trees", //
+booktitle = "Proc. of the 2013 ACM International Conference on Management of Data (SIGMOD)", //
+url = "http://dx.doi.org/10.1145/2463676.2463696")
+public class SlopeInversionDependenceMeasure extends SlopeDependenceMeasure {
+  /**
+   * Static instance.
+   */
+  public static final SlopeInversionDependenceMeasure STATIC = new SlopeInversionDependenceMeasure();
+
+  /**
+   * Constructor. Use static instance instead!
+   */
+  protected SlopeInversionDependenceMeasure() {
+    super();
+  }
+
+  @Override
+  public <A, B> double dependence(NumberArrayAdapter<?, A> adapter1, A data1, NumberArrayAdapter<?, B> adapter2, B data2) {
+    final int len = size(adapter1, data1, adapter2, data2);
+
+    // Get attribute value range:
+    final double off1, scale1, off2, scale2;
+    {
+      double mi = adapter1.getDouble(data1, 0), ma = mi;
+      for(int i = 1; i < len; ++i) {
+        double v = adapter1.getDouble(data1, i);
+        if(v < mi) {
+          mi = v;
+        }
+        else if(v > ma) {
+          ma = v;
+        }
+      }
+      off1 = mi;
+      scale1 = (ma > mi) ? (1. / (ma - mi)) : 1.;
+      // Second data
+      mi = adapter2.getDouble(data2, 0);
+      ma = mi;
+      for(int i = 1; i < len; ++i) {
+        double v = adapter2.getDouble(data2, i);
+        if(v < mi) {
+          mi = v;
+        }
+        else if(v > ma) {
+          ma = v;
+        }
+      }
+      off2 = mi;
+      scale2 = (ma > mi) ? (1. / (ma - mi)) : 1.;
+    }
+
+    // Collect angular histograms.
+    // Note, we only fill half of the matrix
+    int[] angles = new int[PRECISION];
+    int[] angleI = new int[PRECISION];
+
+    // Scratch buffer
+    for(int i = 0; i < len; i++) {
+      double x = adapter1.getDouble(data1, i), y = adapter2.getDouble(data2, i);
+      x = (x - off1) * scale1;
+      y = (y - off2) * scale2;
+      {
+        final double delta = x - y + 1;
+        int div = (int) Math.round(delta * RESCALE);
+        // TODO: do we really need this check?
+        div = (div < 0) ? 0 : (div >= PRECISION) ? PRECISION - 1 : div;
+        angles[div] += 1;
+      }
+      {
+        final double delta = x + y;
+        int div = (int) Math.round(delta * RESCALE);
+        // TODO: do we really need this check?
+        div = (div < 0) ? 0 : (div >= PRECISION) ? PRECISION - 1 : div;
+        angleI[div] += 1;
+      }
+    }
+
+    // Compute entropy:
+    double entropy = 0., entropyI = 0.;
+    for(int l = 0; l < PRECISION; l++) {
+      if(angles[l] > 0) {
+        final double p = angles[l] / (double) len;
+        entropy += p * Math.log(p);
+      }
+      if(angleI[l] > 0) {
+        final double p = angleI[l] / (double) len;
+        entropyI += p * Math.log(p);
+      }
+    }
+    if(entropy >= entropyI) {
+      return 1 + entropy / LOG_PRECISION;
+    }
+    else {
+      return 1 + entropyI / LOG_PRECISION;
+    }
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   *
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractParameterizer {
+    @Override
+    protected SlopeInversionDependenceMeasure makeInstance() {
+      return STATIC;
+    }
+  }
+}