/*
* 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.search.function.distance;
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.queries.function.FunctionValues;
import org.apache.lucene.queries.function.ValueSource;
import org.apache.lucene.queries.function.docvalues.DoubleDocValues;
import org.apache.lucene.queries.function.valuesource.MultiValueSource;
import org.apache.lucene.search.IndexSearcher;
import org.apache.solr.common.SolrException;
import java.io.IOException;
import java.util.Map;
/**
* Calculate the p-norm for a Vector. See http://en.wikipedia.org/wiki/Lp_space
* <p>
* Common cases:
* <ul>
* <li>0 = Sparseness calculation</li>
* <li>1 = Manhattan distance</li>
* <li>2 = Euclidean distance</li>
* <li>Integer.MAX_VALUE = infinite norm</li>
* </ul>
*
* @see SquaredEuclideanFunction for the special case
*/
public class VectorDistanceFunction extends ValueSource {
protected MultiValueSource source1, source2;
protected float power;
protected float oneOverPower;
public VectorDistanceFunction(float power, MultiValueSource source1, MultiValueSource source2) {
if ((source1.dimension() != source2.dimension())) {
throw new SolrException(SolrException.ErrorCode.BAD_REQUEST, "Illegal number of sources");
}
this.power = power;
this.oneOverPower = 1 / power;
this.source1 = source1;
this.source2 = source2;
}
protected String name() {
return "dist";
}
/**
* Calculate the distance
*
* @param doc The current doc
* @param dv1 The values from the first MultiValueSource
* @param dv2 The values from the second MultiValueSource
* @return The distance
*/
protected double distance(int doc, FunctionValues dv1, FunctionValues dv2) throws IOException {
//Handle some special cases:
double[] vals1 = new double[source1.dimension()];
double[] vals2 = new double[source1.dimension()];
dv1.doubleVal(doc, vals1);
dv2.doubleVal(doc, vals2);
return vectorDistance(vals1, vals2, power, oneOverPower);
}
/**
* Calculate the p-norm (i.e. length) between two vectors.
* <p>
* See <a href="http://en.wikipedia.org/wiki/Lp_space">Lp space</a>
*
* @param vec1 The first vector
* @param vec2 The second vector
* @param power The power (2 for cartesian distance, 1 for manhattan, etc.)
* @return The length.
*
* @see #vectorDistance(double[], double[], double, double)
*
*/
public static double vectorDistance(double[] vec1, double[] vec2, double power) {
//only calc oneOverPower if it's needed
double oneOverPower = (power == 0 || power == 1.0 || power == 2.0) ? Double.NaN : 1.0 / power;
return vectorDistance(vec1, vec2, power, oneOverPower);
}
/**
* Calculate the p-norm (i.e. length) between two vectors.
*
* @param vec1 The first vector
* @param vec2 The second vector
* @param power The power (2 for cartesian distance, 1 for manhattan, etc.)
* @param oneOverPower If you've pre-calculated oneOverPower and cached it, use this method to save
* one division operation over {@link #vectorDistance(double[], double[], double)}.
* @return The length.
*/
public static double vectorDistance(double[] vec1, double[] vec2, double power, double oneOverPower) {
double result = 0;
if (power == 0) {
for (int i = 0; i < vec1.length; i++) {
result += vec1[i] - vec2[i] == 0 ? 0 : 1;
}
} else if (power == 1.0) { // Manhattan
for (int i = 0; i < vec1.length; i++) {
result += Math.abs(vec1[i] - vec2[i]);
}
} else if (power == 2.0) { // Cartesian
result = Math.sqrt(distSquaredCartesian(vec1, vec2));
} else if (power == Integer.MAX_VALUE || Double.isInfinite(power)) {//infinite norm?
for (int i = 0; i < vec1.length; i++) {
result = Math.max(result, Math.max(vec1[i], vec2[i]));
}
} else {
for (int i = 0; i < vec1.length; i++) {
result += Math.pow(vec1[i] - vec2[i], power);
}
result = Math.pow(result, oneOverPower);
}
return result;
}
/**
* The square of the cartesian Distance. Not really a distance, but useful if all that matters is
* comparing the result to another one.
*
* @param vec1 The first point
* @param vec2 The second point
* @return The squared cartesian distance
*/
public static double distSquaredCartesian(double[] vec1, double[] vec2) {
double result = 0;
for (int i = 0; i < vec1.length; i++) {
double v = vec1[i] - vec2[i];
result += v * v;
}
return result;
}
@Override
public FunctionValues getValues(Map context, LeafReaderContext readerContext) throws IOException {
final FunctionValues vals1 = source1.getValues(context, readerContext);
final FunctionValues vals2 = source2.getValues(context, readerContext);
return new DoubleDocValues(this) {
@Override
public double doubleVal(int doc) throws IOException {
return distance(doc, vals1, vals2);
}
@Override
public String toString(int doc) throws IOException {
StringBuilder sb = new StringBuilder();
sb.append(name()).append('(').append(power).append(',');
boolean firstTime = true;
sb.append(vals1.toString(doc)).append(',');
sb.append(vals2.toString(doc));
sb.append(')');
return sb.toString();
}
};
}
@Override
public void createWeight(Map context, IndexSearcher searcher) throws IOException {
source1.createWeight(context, searcher);
source2.createWeight(context, searcher);
}
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (!(o instanceof VectorDistanceFunction)) return false;
VectorDistanceFunction that = (VectorDistanceFunction) o;
if (Float.compare(that.power, power) != 0) return false;
if (!source1.equals(that.source1)) return false;
if (!source2.equals(that.source2)) return false;
return true;
}
@Override
public int hashCode() {
int result = source1.hashCode();
result = 31 * result + source2.hashCode();
result = 31 * result + Float.floatToRawIntBits(power);
return result;
}
@Override
public String description() {
StringBuilder sb = new StringBuilder();
sb.append(name()).append('(').append(power).append(',');
sb.append(source1).append(',');
sb.append(source2);
sb.append(')');
return sb.toString();
}
}