Java tutorial
/* * 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 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."); } KMeansPlusPlusClusterer<KmeansEvaluator.ClusterPoint> kmeans = new KMeansPlusPlusClusterer(k, maxIterations); 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)); } 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()); } }