Import Debian changes 0.6.5~20141030-1

elki (0.6.5~20141030-1) unstable; urgency=medium

  * New upstream beta release
  * Urgency medium: 0.6.0 suffers from a performance issue with duplicates.
  * Repackaged tarball from .jar to .tar.bz2
  * Add dependency on libsvm3-java
  * Enable line numbers for debugging (ant debuglevel)

1 files changed, 0 insertions, 68 deletions

diff --git a/test/de/lmu/ifi/dbs/elki/math/TestSlidingVariance.java b/test/de/lmu/ifi/dbs/elki/math/TestSlidingVariance.java
deleted file mode 100644
index 58824142..00000000
--- a/test/de/lmu/ifi/dbs/elki/math/TestSlidingVariance.java
+++ /dev/null
@@ -1,68 +0,0 @@
-package de.lmu.ifi.dbs.elki.math;
-
-import static org.junit.Assert.assertEquals;
-
-import java.util.Random;
-
-import org.junit.Test;
-
-import de.lmu.ifi.dbs.elki.JUnit4Test;
-
-/**
- * Unit test {@link MeanVariance} with negative weights.
- * 
- * @author Erich Schubert
- */
-public class TestSlidingVariance implements JUnit4Test {
-  /**
-   * Size of test data set.
-   */
-  private static final int SIZE = 100000;
-
-  /**
-   * Sliding window size.
-   */
-  private static final int WINDOWSIZE = 100;
-
-  @Test
-  public void testSlidingWindowVariance() {
-    MeanVariance mv = new MeanVariance();
-    MeanVariance mc = new MeanVariance();
-
-    Random r = new Random(0);
-    double[] data = new double[SIZE];
-    for(int i = 0; i < data.length; i++) {
-      data[i] = r.nextDouble();
-    }
-    // Arrays.sort(data);
-
-    // Pre-roll:
-    for(int i = 0; i < WINDOWSIZE; i++) {
-      mv.put(data[i]);
-    }
-    // Compare to window approach
-    for(int i = WINDOWSIZE; i < data.length; i++) {
-      mv.put(data[i - WINDOWSIZE], -1.); // Remove
-      mv.put(data[i]);
-
-      mc.reset(); // Reset statistics
-      for(int j = i + 1 - WINDOWSIZE; j <= i; j++) {
-        mc.put(data[j]);
-      }
-      // Fully manual statistics, exact two-pass algorithm:
-      double mean = 0.0;
-      for(int j = i + 1 - WINDOWSIZE; j <= i; j++) {
-        mean += data[j];
-      }
-      mean /= WINDOWSIZE;
-      double var = 0.0;
-      for(int j = i + 1 - WINDOWSIZE; j <= i; j++) {
-        double v = data[j] - mean;
-        var += v * v;
-      }
-      var /= (WINDOWSIZE - 1);
-      assertEquals("Variance does not agree at i=" + i, mv.getSampleVariance(), mc.getSampleVariance(), 1e-14);
-      assertEquals("Variance does not agree at i=" + i, mv.getSampleVariance(), var, 1e-14);
-    }
-  }
-}