/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
package smile.clustering.linkage;
/**
* Weighted Pair Group Method using Centroids (also known as median linkage).
* The distance between two clusters is the Euclidean distance between their
* weighted centroids. Only valid for Euclidean distance based proximity matrix.
*
* @author Haifeng Li
*/
public class WPGMCLinkage extends Linkage {
/**
* Constructor.
* @param proximity the proximity matrix to store the distance measure of
* dissimilarity. To save space, we only need the lower half of matrix.
*/
public WPGMCLinkage(double[][] proximity) {
this.proximity = proximity;
for (int i = 0; i < proximity.length; i++) {
for (int j = 0; j < i; j++)
proximity[i][j] *= proximity[i][j];
}
}
@Override
public String toString() {
return "WPGMC linkage";
}
@Override
public void merge(int i, int j) {
for (int k = 0; k < i; k++) {
proximity[i][k] = (proximity[i][k] + proximity[j][k]) / 2 - proximity[j][i] / 4;
}
for (int k = i+1; k < j; k++) {
proximity[k][i] = (proximity[k][i] + proximity[j][k]) / 2 - proximity[j][i] / 4;
}
for (int k = j+1; k < proximity.length; k++) {
proximity[k][i] = (proximity[k][i] + proximity[k][j]) / 2 - proximity[j][i] / 4;
}
}
}