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/*
 * Licensed to Elasticsearch under one or more contributor
 * license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright
 * ownership. Elasticsearch 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,
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package org.elasticsearch.search.suggest.phrase;

import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Terms;
import org.apache.lucene.util.BytesRef;
import org.elasticsearch.common.ParseField;
import org.elasticsearch.common.ParsingException;
import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentParser;
import org.elasticsearch.common.xcontent.XContentParser.Token;
import org.elasticsearch.search.suggest.phrase.WordScorer.WordScorerFactory;

import java.io.IOException;
import java.util.Objects;

/**
 * Linear interpolation smoothing model.
 * 

* See N-Gram * Smoothing for details. *

*/ public final class LinearInterpolation extends SmoothingModel { public static final String NAME = "linear"; static final ParseField PARSE_FIELD = new ParseField(NAME); private static final ParseField TRIGRAM_FIELD = new ParseField("trigram_lambda"); private static final ParseField BIGRAM_FIELD = new ParseField("bigram_lambda"); private static final ParseField UNIGRAM_FIELD = new ParseField("unigram_lambda"); private final double trigramLambda; private final double bigramLambda; private final double unigramLambda; /** * Creates a linear interpolation smoothing model. * * Note: the lambdas must sum up to one. * * @param trigramLambda * the trigram lambda * @param bigramLambda * the bigram lambda * @param unigramLambda * the unigram lambda */ public LinearInterpolation(double trigramLambda, double bigramLambda, double unigramLambda) { double sum = trigramLambda + bigramLambda + unigramLambda; if (Math.abs(sum - 1.0) > 0.001) { throw new IllegalArgumentException("linear smoothing lambdas must sum to 1"); } this.trigramLambda = trigramLambda; this.bigramLambda = bigramLambda; this.unigramLambda = unigramLambda; } /** * Read from a stream. */ public LinearInterpolation(StreamInput in) throws IOException { trigramLambda = in.readDouble(); bigramLambda = in.readDouble(); unigramLambda = in.readDouble(); } @Override public void writeTo(StreamOutput out) throws IOException { out.writeDouble(trigramLambda); out.writeDouble(bigramLambda); out.writeDouble(unigramLambda); } public double getTrigramLambda() { return this.trigramLambda; } public double getBigramLambda() { return this.bigramLambda; } public double getUnigramLambda() { return this.unigramLambda; } @Override protected XContentBuilder innerToXContent(XContentBuilder builder, Params params) throws IOException { builder.field(TRIGRAM_FIELD.getPreferredName(), trigramLambda); builder.field(BIGRAM_FIELD.getPreferredName(), bigramLambda); builder.field(UNIGRAM_FIELD.getPreferredName(), unigramLambda); return builder; } @Override public String getWriteableName() { return NAME; } @Override protected boolean doEquals(SmoothingModel other) { final LinearInterpolation otherModel = (LinearInterpolation) other; return Objects.equals(trigramLambda, otherModel.trigramLambda) && Objects.equals(bigramLambda, otherModel.bigramLambda) && Objects.equals(unigramLambda, otherModel.unigramLambda); } @Override protected int doHashCode() { return Objects.hash(trigramLambda, bigramLambda, unigramLambda); } public static LinearInterpolation fromXContent(XContentParser parser) throws IOException { XContentParser.Token token; String fieldName = null; double trigramLambda = 0.0; double bigramLambda = 0.0; double unigramLambda = 0.0; while ((token = parser.nextToken()) != Token.END_OBJECT) { if (token == XContentParser.Token.FIELD_NAME) { fieldName = parser.currentName(); } else if (token.isValue()) { if (TRIGRAM_FIELD.match(fieldName, parser.getDeprecationHandler())) { trigramLambda = parser.doubleValue(); if (trigramLambda < 0) { throw new IllegalArgumentException("trigram_lambda must be positive"); } } else if (BIGRAM_FIELD.match(fieldName, parser.getDeprecationHandler())) { bigramLambda = parser.doubleValue(); if (bigramLambda < 0) { throw new IllegalArgumentException("bigram_lambda must be positive"); } } else if (UNIGRAM_FIELD.match(fieldName, parser.getDeprecationHandler())) { unigramLambda = parser.doubleValue(); if (unigramLambda < 0) { throw new IllegalArgumentException("unigram_lambda must be positive"); } } else { throw new IllegalArgumentException( "suggester[phrase][smoothing][linear] doesn't support field [" + fieldName + "]"); } } else { throw new ParsingException(parser.getTokenLocation(), "[" + NAME + "] unknown token [" + token + "] after [" + fieldName + "]"); } } return new LinearInterpolation(trigramLambda, bigramLambda, unigramLambda); } @Override public WordScorerFactory buildWordScorerFactory() { return (IndexReader reader, Terms terms, String field, double realWordLikelihood, BytesRef separator) -> new LinearInterpolatingScorer(reader, terms, field, realWordLikelihood, separator, trigramLambda, bigramLambda, unigramLambda); } }




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