boa.aggregators.ConfidenceIntervalAggregator.java Source code

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Here is the source code for boa.aggregators.ConfidenceIntervalAggregator.java

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/*
 * Copyright 2014, Hridesh Rajan, Robert Dyer, 
 *                 and Iowa State University of Science and Technology
 *
 * Licensed 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 boa.aggregators;

import java.io.IOException;
import java.util.TreeMap;
import java.util.SortedMap;

import org.apache.commons.math.MathException;
import org.apache.commons.math.distribution.TDistributionImpl;
import org.apache.commons.math.stat.descriptive.SummaryStatistics;

import boa.io.EmitKey;

/**
 * A Boa aggregator to calculate a confidence interval of the values in a dataset.
 * 
 * @author rdyer
 */
@AggregatorSpec(name = "confidence", formalParameters = { "float" }, type = "int")
public class ConfidenceIntervalAggregator extends Aggregator {
    private SortedMap<Long, Long> map;
    private double n;

    /**
     * Construct a {@link ConfidenceIntervalAggregator}.
     */
    public ConfidenceIntervalAggregator() {
        this(5);
    }

    /**
     * Construct a {@link ConfidenceIntervalAggregator}.
     * 
     * @param n
     *            A double representing the significance
     */
    public ConfidenceIntervalAggregator(final double n) {
        this.n = n;
    }

    /** {@inheritDoc} */
    @Override
    public void start(final EmitKey key) {
        super.start(key);

        map = new TreeMap<Long, Long>();
    }

    /** {@inheritDoc} */
    @Override
    public void aggregate(final String data, final String metadata) throws IOException, InterruptedException {
        for (final String s : data.split(";")) {
            final int idx = s.indexOf(":");
            if (idx > 0) {
                final long item = Long.valueOf(s.substring(0, idx));
                final long count = Long.valueOf(s.substring(idx + 1));
                for (int i = 0; i < count; i++)
                    aggregate(item, metadata);
            } else
                aggregate(Long.valueOf(s), metadata);
        }
    }

    /** {@inheritDoc} */
    @Override
    public void aggregate(final long data, final String metadata) {
        if (map.containsKey(data))
            map.put(data, map.get(data) + 1L);
        else
            map.put(data, 1L);
    }

    /** {@inheritDoc} */
    @Override
    public void aggregate(final double data, final String metadata) {
        this.aggregate(Double.valueOf(data).longValue(), metadata);
    }

    /** {@inheritDoc} */
    @Override
    public void finish() throws IOException, InterruptedException {
        if (this.isCombining()) {
            String s = "";
            for (final Long key : map.keySet())
                s += key + ":" + map.get(key) + ";";
            this.collect(s, null);
            return;
        }

        try {
            final SummaryStatistics summaryStatistics = new SummaryStatistics();

            for (final Long key : map.keySet())
                for (int i = 0; i < map.get(key); i++)
                    summaryStatistics.addValue(key);

            final double a = new TDistributionImpl(summaryStatistics.getN() - 1)
                    .inverseCumulativeProbability(1.0 - n / 200.0);

            this.collect(a * summaryStatistics.getStandardDeviation() / Math.sqrt(summaryStatistics.getN()));
        } catch (final MathException e) {
        }
    }
}