smile.clustering.linkage.UPGMALinkage Maven / Gradle / Ivy
/*
* Copyright (c) 2010-2021 Haifeng Li. All rights reserved.
*
* Smile is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Smile 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with Smile. If not, see .
*/
package smile.clustering.linkage;
import smile.math.distance.Distance;
/**
* Unweighted Pair Group Method with Arithmetic mean (also known as average linkage).
* The distance between two clusters is the mean distance between all possible
* pairs of nodes in the two clusters.
*
* In bioinformatics, UPGMA is used for the creation of phenetic trees
* (phenograms). UPGMA assumes a constant rate of evolution (molecular
* clock hypothesis), and is not a well-regarded method for inferring
* relationships unless this assumption has been tested and justified
* for the data set being used.
*
* @author Haifeng Li
*/
public class UPGMALinkage extends Linkage {
/**
* The number of samples in each cluster.
*/
private int[] n;
/**
* Constructor.
* @param proximity the proximity matrix. Only the lower half will
* be referred.
*/
public UPGMALinkage(double[][] proximity) {
super(proximity);
init();
}
/**
* Constructor. Initialize the linkage with the lower triangular proximity matrix.
* @param size the data size.
* @param proximity the column-wise linearized proximity matrix that stores
* only the lower half. The length of proximity should be
* size * (size+1) / 2.
* To save space, Linkage will use this argument directly
* without copy. The elements may be modified.
*/
public UPGMALinkage(int size, float[] proximity) {
super(size, proximity);
init();
}
/** Initialize sample size. */
private void init() {
n = new int[size];
for (int i = 0; i < size; i++) {
n[i] = 1;
}
}
/**
* Computes the proximity and the linkage.
*
* @param data the data points.
* @return the linkage.
*/
public static UPGMALinkage of(double[][] data) {
return new UPGMALinkage(data.length, proximity(data));
}
/**
* Computes the proximity and the linkage.
*
* @param data the data points.
* @param distance the distance function.
* @param the data type of points.
* @return the linkage.
*/
public static UPGMALinkage of(T[] data, Distance distance) {
return new UPGMALinkage(data.length, proximity(data, distance));
}
@Override
public String toString() {
return "UPGMA linkage";
}
@Override
public void merge(int i, int j) {
float sum = n[i] + n[j];
for (int k = 0; k < i; k++) {
proximity[index(i, k)] = d(i, k) * n[i] / sum + d(j, k) * n[j] / sum;
}
for (int k = i+1; k < size; k++) {
proximity[index(k, i)] = d(k, i) * n[i] / sum + d(j, k) * n[j] / sum;
}
n[i] += n[j];
}
}