Import Upstream version 0.7.0

1 files changed, 53 insertions, 0 deletions

diff --git a/elki/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/ErfcWeight.java b/elki/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/ErfcWeight.java
new file mode 100644
index 00000000..b7bc1c67
--- /dev/null
+++ b/elki/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/ErfcWeight.java
@@ -0,0 +1,53 @@
+package de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions;
+
+/*
+ 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 de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution;
+
+/**
+ * Gaussian Error Function Weight function, scaled such that the result it 0.1
+ * at distance == max
+ * 
+ * erfc(1.1630871536766736 * distance / max)
+ * 
+ * The value of 1.1630871536766736 is erfcinv(0.1), to achieve the intended
+ * scaling.
+ * 
+ * @author Erich Schubert
+ */
+public final class ErfcWeight implements WeightFunction {
+  /**
+   * Get Erfc Weight, using distance / max. stddev is ignored.
+   */
+  @Override
+  public double getWeight(double distance, double max, double stddev) {
+    if(max <= 0) {
+      return 1.0;
+    }
+    double relativedistance = distance / max;
+    // the scaling was picked such that getWeight(a,a,0) is 0.1
+    // since erfc(1.1630871536766736) == 1.0
+    return NormalDistribution.erfc(1.1630871536766736 * relativedistance);
+  }
+}