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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.Cluster;
import org.apache.commons.math3.ml.distance.DistanceMeasure;
import org.apache.commons.math3.ml.distance.EuclideanDistance;
import org.apache.solr.client.solrj.io.Tuple;
import org.apache.commons.math3.ml.clustering.Clusterable;
import org.apache.commons.math3.ml.clustering.DBSCANClusterer;
import org.apache.solr.client.solrj.io.stream.expr.StreamExpression;
import org.apache.solr.client.solrj.io.stream.expr.StreamFactory;
public class DbscanEvaluator extends RecursiveObjectEvaluator implements ManyValueWorker {
protected static final long serialVersionUID = 1L;
public DbscanEvaluator(StreamExpression expression, StreamFactory factory) throws IOException{
super(expression, factory);
}
@Override
@SuppressWarnings({"unchecked"})
public Object doWork(Object... values) throws IOException {
Matrix matrix = null;
double e = 0;
int minPoints = 1;
DistanceMeasure distanceMeasure = new EuclideanDistance();
if(values.length < 3 || values.length > 4) {
throw new IOException("The dbscan scan function requires 3 or 4 parameters.");
}
if(values[0] instanceof Matrix) {
matrix = (Matrix)values[0];
} else {
throw new IOException("The first parameter for dbscan should be the observation matrix.");
}
if(values[1] instanceof Number) {
e = ((Number)values[1]).doubleValue();
} else {
throw new IOException("The second parameter for dbscan should be e.");
}
if(values[2] instanceof Number) {
minPoints = ((Number)values[2]).intValue();
} else {
throw new IOException("The third parameter for dbscan should be minPoints.");
}
if(values.length > 3) {
distanceMeasure = (DistanceMeasure)values[3];
}
@SuppressWarnings({"rawtypes"})
DBSCANClusterer<ClusterPoint> dbscan = new DBSCANClusterer(e, minPoints, distanceMeasure);
List<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];
if(ids != null) {
points.add(new ClusterPoint(ids.get(i), vec));
} else {
points.add(new ClusterPoint(Integer.toString(i), vec));
}
}
@SuppressWarnings({"rawtypes"})
Map fields = new HashMap();
fields.put("e", e);
fields.put("minPoints", minPoints);
fields.put("distance", distanceMeasure.toString());
return new ClusterTuple(fields, dbscan.cluster(points), matrix.getColumnLabels());
}
public static class ClusterPoint implements Clusterable {
private double[] point;
private String id;
public ClusterPoint(String id, double[] point) {
this.id = id;
this.point = point;
}
public double[] getPoint() {
return this.point;
}
public String getId() {
return this.id;
}
}
public static class ClusterTuple extends Tuple {
private List<String> columnLabels;
private List<Cluster<ClusterPoint>> clusters;
public ClusterTuple(@SuppressWarnings({"rawtypes"})Map fields,
List<Cluster<ClusterPoint>> clusters,
List<String> columnLabels) {
super(fields);
this.clusters = clusters;
this.columnLabels = columnLabels;
}
public List<String> getColumnLabels() {
return this.columnLabels;
}
public List<Cluster<ClusterPoint>> getClusters() {
return this.clusters;
}
}
}