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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 org.apache.solr.client.solrj.io.eval;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.HashMap;
import org.apache.commons.math3.ml.clustering.KMeansPlusPlusClusterer;
import org.apache.commons.math3.ml.clustering.MultiKMeansPlusPlusClusterer;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpression;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpressionNamedParameter;
import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
public class MultiKmeansEvaluator extends RecursiveObjectEvaluator implements ManyValueWorker {
protected static final long serialVersionUID = 1L;
private int maxIterations = 1000;
public MultiKmeansEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
super(expression, factory);
List<StreamExpressionNamedParameter> namedParams = factory.getNamedOperands(expression);
for(StreamExpressionNamedParameter namedParam : namedParams){
if(namedParam.getName().equals("maxIterations")) {
this.maxIterations = Integer.parseInt(namedParam.getParameter().toString().trim());
} else {
throw new IOException("Unexpected named parameter:"+namedParam.getName());
}
}
}
@Override
@SuppressWarnings({"unchecked"})
public Object doWork(Object... values) throws IOException {
if(values.length != 3) {
throw new IOException("The multiKmeans function expects three parameters; a matrix to cluster, k and number of trials.");
}
Object value1 = values[0];
Object value2 = values[1];
Object value3 = values[2];
Matrix matrix = null;
int k = 0;
int trials=0;
if(value1 instanceof Matrix) {
matrix = (Matrix)value1;
} else {
throw new IOException("The first parameter for multiKmeans should be the observation matrix.");
}
if(value2 instanceof Number) {
k = ((Number)value2).intValue();
} else {
throw new IOException("The second parameter for multiKmeans should be k.");
}
if(value3 instanceof Number) {
trials= ((Number)value3).intValue();
} else {
throw new IOException("The third parameter for multiKmeans should be trials.");
}
@SuppressWarnings({"rawtypes"})
KMeansPlusPlusClusterer<KmeansEvaluator.ClusterPoint> kmeans = new KMeansPlusPlusClusterer(k, maxIterations);
@SuppressWarnings({"rawtypes"})
MultiKMeansPlusPlusClusterer multiKmeans = new MultiKMeansPlusPlusClusterer(kmeans, trials);
List<KmeansEvaluator.ClusterPoint> points = new ArrayList<>();
double[][] data = matrix.getData();
List<String> ids = matrix.getRowLabels();
for(int i=0; i<data.length; i++) {
double[] vec = data[i];
points.add(new KmeansEvaluator.ClusterPoint(ids.get(i), vec));
}
@SuppressWarnings({"rawtypes"})
Map fields = new HashMap();
fields.put("k", k);
fields.put("trials", trials);
fields.put("distance", "euclidean");
fields.put("maxIterations", maxIterations);
return new KmeansEvaluator.ClusterTuple(fields, multiKmeans.cluster(points), matrix.getColumnLabels());
}
}