86 řádky
3,1 KiB
Java
86 řádky
3,1 KiB
Java
/*
|
|
* Copyright (C) 2011-2016 clueminer.org
|
|
*
|
|
* This program 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.
|
|
*
|
|
* 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 General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU General Public License
|
|
* along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
*/
|
|
package org.clueminer.clustering.benchmark;
|
|
|
|
import org.clueminer.clustering.TreeDiff;
|
|
import org.clueminer.clustering.api.AgglomerativeClustering;
|
|
import org.clueminer.clustering.api.AlgParams;
|
|
import org.clueminer.clustering.api.Clustering;
|
|
import org.clueminer.clustering.api.ClusteringAlgorithm;
|
|
import org.clueminer.clustering.api.ClusteringType;
|
|
import org.clueminer.clustering.api.HierarchicalResult;
|
|
import org.clueminer.dataset.api.Dataset;
|
|
import org.clueminer.dataset.api.Instance;
|
|
import org.clueminer.exec.ClusteringExecutorCached;
|
|
import org.clueminer.utils.Props;
|
|
import org.slf4j.Logger;
|
|
import org.slf4j.LoggerFactory;
|
|
|
|
/**
|
|
*
|
|
* @author Tomas Barton
|
|
* @param <E>
|
|
*/
|
|
public class Container<E extends Instance> implements Runnable {
|
|
|
|
private HierarchicalResult result;
|
|
private Clustering clustering;
|
|
private final Dataset<E> dataset;
|
|
private Props params;
|
|
private static final Logger LOG = LoggerFactory.getLogger(Container.class);
|
|
private ClusteringExecutorCached executor;
|
|
|
|
public Container(ClusteringAlgorithm algorithm, Dataset<E> dataset) {
|
|
this.executor = new ClusteringExecutorCached();
|
|
executor.setAlgorithm(algorithm);
|
|
this.dataset = dataset;
|
|
this.params = new Props();
|
|
}
|
|
|
|
public Container(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props params) {
|
|
this.executor = new ClusteringExecutorCached();
|
|
executor.setAlgorithm(algorithm);
|
|
this.dataset = dataset;
|
|
this.params = params;
|
|
}
|
|
|
|
public HierarchicalResult hierarchical(AgglomerativeClustering algorithm, Dataset<E> dataset, Props params) {
|
|
params.put(AlgParams.CLUSTERING_TYPE, ClusteringType.ROWS_CLUSTERING);
|
|
return algorithm.hierarchy(dataset, params);
|
|
}
|
|
|
|
@Override
|
|
public void run() {
|
|
if (executor.getAlgorithm() instanceof AgglomerativeClustering) {
|
|
this.result = executor.hclustRows(dataset, params);
|
|
} else {
|
|
this.clustering = executor.clusterRows(dataset, params);
|
|
}
|
|
}
|
|
|
|
public Clustering cluster(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props params) {
|
|
return executor.clusterRows(dataset, params);
|
|
}
|
|
|
|
public boolean equals(Container other) {
|
|
if (this.result == null || other.result == null) {
|
|
throw new RuntimeException("got null result. this = " + result + " other = " + other);
|
|
}
|
|
return TreeDiff.compare(this.result, other.result);
|
|
}
|
|
|
|
}
|