/*
* UPGMATree.java
*
* Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard
*
* This file is part of BEAST.
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership and licensing.
*
* BEAST is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* BEAST 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 Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with BEAST; if not, write to the
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
* Boston, MA 02110-1301 USA
*/
package dr.evolution.tree;
import dr.evolution.distance.DistanceMatrix;
/**
* constructs a UPGMA tree from pairwise distances
*
* @version $Id: UPGMATree.java,v 1.14 2005/05/24 20:25:57 rambaut Exp $
*
* @author Andrew Rambaut
* @author Alexei Drummond
*/
public class UPGMATree extends ClusteringTree {
/**
* constructor UPGMA tree
*
* @param distanceMatrix distance matrix
*/
public UPGMATree(DistanceMatrix distanceMatrix) {
super(distanceMatrix, 2);
}
//
// Protected and Private stuff
//
protected void findNextPair() {
besti = 0;
bestj = 1;
double dmin = getDist(0, 1);
for (int i = 0; i < numClusters-1; i++) {
for (int j = i+1; j < numClusters; j++) {
if (getDist(i, j) < dmin) {
dmin = getDist(i, j);
besti = i;
bestj = j;
}
}
}
abi = alias[besti];
abj = alias[bestj];
}
protected double newNodeHeight() {
return getDist(besti, bestj) / 2.0;
}
/**
* compute updated distance between the new cluster (i,j)
* to any other cluster k
*/
protected double updatedDistance(int i, int j, int k)
{
int ai = alias[i];
int aj = alias[j];
double tipSum = (double) (tipCount[ai] + tipCount[aj]);
return (((double)tipCount[ai]) / tipSum) * getDist(k, i) +
(((double)tipCount[aj]) / tipSum) * getDist(k, j);
}
}