package org.apache.lucene.search;
/*
* 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.
*/
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.apache.lucene.search.similarities.AfterEffect;
import org.apache.lucene.search.similarities.AfterEffectB;
import org.apache.lucene.search.similarities.AfterEffectL;
import org.apache.lucene.search.similarities.BM25Similarity;
import org.apache.lucene.search.similarities.BasicModel;
import org.apache.lucene.search.similarities.BasicModelBE;
import org.apache.lucene.search.similarities.BasicModelD;
import org.apache.lucene.search.similarities.BasicModelG;
import org.apache.lucene.search.similarities.BasicModelIF;
import org.apache.lucene.search.similarities.BasicModelIn;
import org.apache.lucene.search.similarities.BasicModelIne;
import org.apache.lucene.search.similarities.BasicModelP;
import org.apache.lucene.search.similarities.DFRSimilarity;
import org.apache.lucene.search.similarities.DefaultSimilarity;
import org.apache.lucene.search.similarities.Distribution;
import org.apache.lucene.search.similarities.DistributionLL;
import org.apache.lucene.search.similarities.DistributionSPL;
import org.apache.lucene.search.similarities.IBSimilarity;
import org.apache.lucene.search.similarities.LMDirichletSimilarity;
import org.apache.lucene.search.similarities.LMJelinekMercerSimilarity;
import org.apache.lucene.search.similarities.Lambda;
import org.apache.lucene.search.similarities.LambdaDF;
import org.apache.lucene.search.similarities.LambdaTTF;
import org.apache.lucene.search.similarities.Normalization;
import org.apache.lucene.search.similarities.NormalizationH1;
import org.apache.lucene.search.similarities.NormalizationH2;
import org.apache.lucene.search.similarities.NormalizationH3;
import org.apache.lucene.search.similarities.NormalizationZ;
import org.apache.lucene.search.similarities.PerFieldSimilarityWrapper;
import org.apache.lucene.search.similarities.Similarity;
/**
* Similarity implementation that randomizes Similarity implementations
* per-field.
* <p>
* The choices are 'sticky', so the selected algorithm is always used
* for the same field.
*/
public class RandomSimilarityProvider extends PerFieldSimilarityWrapper {
final DefaultSimilarity defaultSim = new DefaultSimilarity();
final List<Similarity> knownSims;
Map<String,Similarity> previousMappings = new HashMap<>();
final int perFieldSeed;
final int coordType; // 0 = no coord, 1 = coord, 2 = crazy coord
final boolean shouldQueryNorm;
public RandomSimilarityProvider(Random random) {
perFieldSeed = random.nextInt();
coordType = random.nextInt(3);
shouldQueryNorm = random.nextBoolean();
knownSims = new ArrayList<>(allSims);
Collections.shuffle(knownSims, random);
}
@Override
public float coord(int overlap, int maxOverlap) {
if (coordType == 0) {
return 1.0f;
} else if (coordType == 1) {
return defaultSim.coord(overlap, maxOverlap);
} else {
return overlap / ((float)maxOverlap + 1);
}
}
@Override
public float queryNorm(float sumOfSquaredWeights) {
if (shouldQueryNorm) {
return defaultSim.queryNorm(sumOfSquaredWeights);
} else {
return 1.0f;
}
}
@Override
public synchronized Similarity get(String field) {
assert field != null;
Similarity sim = previousMappings.get(field);
if (sim == null) {
sim = knownSims.get(Math.max(0, Math.abs(perFieldSeed ^ field.hashCode())) % knownSims.size());
previousMappings.put(field, sim);
}
return sim;
}
// all the similarities that we rotate through
/** The DFR basic models to test. */
static BasicModel[] BASIC_MODELS = {
/* TODO: enable new BasicModelBE(), */ /* TODO: enable new BasicModelD(), */ new BasicModelG(),
new BasicModelIF(), new BasicModelIn(), new BasicModelIne(),
/* TODO: enable new BasicModelP() */
};
/** The DFR aftereffects to test. */
static AfterEffect[] AFTER_EFFECTS = {
new AfterEffectB(), new AfterEffectL(), new AfterEffect.NoAfterEffect()
};
/** The DFR normalizations to test. */
static Normalization[] NORMALIZATIONS = {
new NormalizationH1(), new NormalizationH2(),
new NormalizationH3(), new NormalizationZ()
// TODO: if we enable NoNormalization, we have to deal with
// a couple tests (e.g. TestDocBoost, TestSort) that expect length normalization
// new Normalization.NoNormalization()
};
/** The distributions for IB. */
static Distribution[] DISTRIBUTIONS = {
new DistributionLL(), new DistributionSPL()
};
/** Lambdas for IB. */
static Lambda[] LAMBDAS = {
new LambdaDF(), new LambdaTTF()
};
static List<Similarity> allSims;
static {
allSims = new ArrayList<>();
allSims.add(new DefaultSimilarity());
allSims.add(new BM25Similarity());
for (BasicModel basicModel : BASIC_MODELS) {
for (AfterEffect afterEffect : AFTER_EFFECTS) {
for (Normalization normalization : NORMALIZATIONS) {
allSims.add(new DFRSimilarity(basicModel, afterEffect, normalization));
}
}
}
for (Distribution distribution : DISTRIBUTIONS) {
for (Lambda lambda : LAMBDAS) {
for (Normalization normalization : NORMALIZATIONS) {
allSims.add(new IBSimilarity(distribution, lambda, normalization));
}
}
}
/* TODO: enable Dirichlet
allSims.add(new LMDirichletSimilarity()); */
allSims.add(new LMJelinekMercerSimilarity(0.1f));
allSims.add(new LMJelinekMercerSimilarity(0.7f));
}
@Override
public synchronized String toString() {
final String coordMethod;
if (coordType == 0) {
coordMethod = "no";
} else if (coordType == 1) {
coordMethod = "yes";
} else {
coordMethod = "crazy";
}
return "RandomSimilarityProvider(queryNorm=" + shouldQueryNorm + ",coord=" + coordMethod + "): " + previousMappings.toString();
}
}