/*
 * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
 * or more contributor license agreements. Licensed under the "Elastic License
 * 2.0", the "GNU Affero General Public License v3.0 only", and the "Server Side
 * Public License v 1"; you may not use this file except in compliance with, at
 * your election, the "Elastic License 2.0", the "GNU Affero General Public
 * License v3.0 only", or the "Server Side Public License, v 1".
 */

package org.elasticsearch.example.customsigheuristic;

import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.xcontent.ObjectParser;
import org.elasticsearch.xcontent.XContentBuilder;
import org.elasticsearch.search.aggregations.bucket.terms.heuristic.SignificanceHeuristic;

import java.io.IOException;

/**
 * A simple {@linkplain SignificanceHeuristic} used an example of declaring a custom heuristic.
 */
public class SimpleHeuristic extends SignificanceHeuristic {
    public static final String NAME = "simple";
    public static final ObjectParser<SimpleHeuristic, Void> PARSER = new ObjectParser<>(NAME, SimpleHeuristic::new);

    public SimpleHeuristic() {
    }

    /**
     * Read from a stream.
     */
    public SimpleHeuristic(StreamInput in) throws IOException {
        // Nothing to read
    }

    @Override
    public void writeTo(StreamOutput out) throws IOException {
        // Nothing to write
    }

    @Override
    public String getWriteableName() {
        return NAME;
    }

    @Override
    public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
        builder.startObject(NAME).endObject();
        return builder;
    }

    @Override
    public int hashCode() {
        return 1;
    }

    @Override
    public boolean equals(Object obj) {
        if (obj == null) {
            return false;
        }
        if (getClass() != obj.getClass()) {
            return false;
        }
        return true;
    }

    /**
     * @param subsetFreq   The frequency of the term in the selected sample
     * @param subsetSize   The size of the selected sample (typically number of docs)
     * @param supersetFreq The frequency of the term in the superset from which the sample was taken
     * @param supersetSize The size of the superset from which the sample was taken  (typically number of docs)
     * @return a "significance" score
     */
    @Override
    public double getScore(long subsetFreq, long subsetSize, long supersetFreq, long supersetSize) {
        return subsetFreq / subsetSize > supersetFreq / supersetSize ? 2.0 : 1.0;
    }
}