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diff --git a/elki/src/test/java/de/lmu/ifi/dbs/elki/distance/distancefunction/correlation/SquaredPearsonCorrelationDistanceFunctionTest.java b/elki/src/test/java/de/lmu/ifi/dbs/elki/distance/distancefunction/correlation/SquaredPearsonCorrelationDistanceFunctionTest.java
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+++ b/elki/src/test/java/de/lmu/ifi/dbs/elki/distance/distancefunction/correlation/SquaredPearsonCorrelationDistanceFunctionTest.java
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+package de.lmu.ifi.dbs.elki.distance.distancefunction.correlation;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2015
+ 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 static org.junit.Assert.assertEquals;
+
+import org.junit.Test;
+
+import de.lmu.ifi.dbs.elki.JUnit4Test;
+import de.lmu.ifi.dbs.elki.data.DoubleVector;
+
+/**
+ * Unit test for squared Pearson correlation distance.
+ * 
+ * @author Erich Schubert
+ * @since 0.4.0
+ */
+public class SquaredPearsonCorrelationDistanceFunctionTest implements JUnit4Test {
+  /** Test set */
+  final static DoubleVector[] TESTS = PearsonCorrelationDistanceFunctionTest.TESTS;
+
+  /** Note, these are not yet adjusted */
+  final static double[][] SCORES = PearsonCorrelationDistanceFunctionTest.SCORES;
+
+  @Test
+  public void testSquaredPearson() {
+    SquaredPearsonCorrelationDistanceFunction f = SquaredPearsonCorrelationDistanceFunction.STATIC;
+    for(int i = 0; i < TESTS.length; i++) {
+      for(int j = 0; j < TESTS.length; j++) {
+        final double dist = f.distance(TESTS[i], TESTS[j]);
+        final double r = 1. - SCORES[i][j];
+        assertEquals("Distance does not agree: " + TESTS[i] + " <-> " + TESTS[j], 1. - r * r, dist, 1e-15);
+      }
+    }
+  }
+}