org.apache.solr.client.solrj.io.eval.KnnEvaluator.java Source code

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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.TreeSet;

import org.apache.commons.math3.ml.distance.CanberraDistance;
import org.apache.commons.math3.ml.distance.DistanceMeasure;
import org.apache.commons.math3.ml.distance.EarthMoversDistance;
import org.apache.commons.math3.ml.distance.EuclideanDistance;
import org.apache.commons.math3.ml.distance.ManhattanDistance;
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 KnnEvaluator extends RecursiveObjectEvaluator implements ManyValueWorker {
    protected static final long serialVersionUID = 1L;

    private DistanceMeasure distanceMeasure;

    public KnnEvaluator(StreamExpression expression, StreamFactory factory) throws IOException {
        super(expression, factory);

        DistanceEvaluator.DistanceType type = null;
        List<StreamExpressionNamedParameter> namedParams = factory.getNamedOperands(expression);
        if (namedParams.size() > 0) {
            if (namedParams.size() > 1) {
                throw new IOException("distance function expects only one named parameter 'distance'.");
            }

            StreamExpressionNamedParameter namedParameter = namedParams.get(0);
            String name = namedParameter.getName();
            if (!name.equalsIgnoreCase("distance")) {
                throw new IOException("distance function expects only one named parameter 'distance'.");
            }

            String typeParam = namedParameter.getParameter().toString().trim();
            type = DistanceEvaluator.DistanceType.valueOf(typeParam);
        } else {
            type = DistanceEvaluator.DistanceType.euclidean;
        }

        if (type.equals(DistanceEvaluator.DistanceType.euclidean)) {
            distanceMeasure = new EuclideanDistance();
        } else if (type.equals(DistanceEvaluator.DistanceType.manhattan)) {
            distanceMeasure = new ManhattanDistance();
        } else if (type.equals(DistanceEvaluator.DistanceType.canberra)) {
            distanceMeasure = new CanberraDistance();
        } else if (type.equals(DistanceEvaluator.DistanceType.earthMovers)) {
            distanceMeasure = new EarthMoversDistance();
        }

    }

    @Override
    public Object doWork(Object... values) throws IOException {

        if (values.length < 3) {
            throw new IOException("knn expects three parameters a Matrix, numeric array and k");
        }

        Matrix matrix = null;
        double[] vec = null;
        int k = 0;

        if (values[0] instanceof Matrix) {
            matrix = (Matrix) values[0];
        } else {
            throw new IOException("The first parameter for knn should be a matrix.");
        }

        if (values[1] instanceof List) {
            List<Number> nums = (List<Number>) values[1];
            vec = new double[nums.size()];
            for (int i = 0; i < nums.size(); i++) {
                vec[i] = nums.get(i).doubleValue();
            }
        } else {
            throw new IOException("The second parameter for knn should be a numeric array.");
        }

        if (values[2] instanceof Number) {
            k = ((Number) values[2]).intValue();
        } else {
            throw new IOException("The third parameter for knn should be k.");
        }

        double[][] data = matrix.getData();

        TreeSet<Neighbor> neighbors = new TreeSet();
        for (int i = 0; i < data.length; i++) {
            double distance = distanceMeasure.compute(vec, data[i]);
            neighbors.add(new Neighbor(i, distance));
            if (neighbors.size() > k) {
                neighbors.pollLast();
            }
        }

        double[][] out = new double[neighbors.size()][];
        List<String> rowLabels = matrix.getRowLabels();
        List<String> newRowLabels = new ArrayList();
        List<Number> distances = new ArrayList();
        int i = -1;

        while (neighbors.size() > 0) {
            Neighbor neighbor = neighbors.pollFirst();
            int rowIndex = neighbor.getRow();

            if (rowLabels != null) {
                newRowLabels.add(rowLabels.get(rowIndex));
            }

            out[++i] = data[rowIndex];
            distances.add(neighbor.getDistance());
        }

        Matrix knn = new Matrix(out);

        if (rowLabels != null) {
            knn.setRowLabels(newRowLabels);
        }

        knn.setColumnLabels(matrix.getColumnLabels());
        knn.setAttribute("distances", distances);
        return knn;
    }

    public static class Neighbor implements Comparable<Neighbor> {

        private Double distance;
        private int row;

        public Neighbor(int row, double distance) {
            this.distance = distance;
            this.row = row;
        }

        public int getRow() {
            return this.row;
        }

        public Double getDistance() {
            return distance;
        }

        public int compareTo(Neighbor neighbor) {
            return this.distance.compareTo(neighbor.getDistance());
        }
    }

}