001/*-------------------------------------------------------------------------+
002|                                                                          |
003| Copyright 2005-2011 The ConQAT Project                                   |
004|                                                                          |
005| Licensed under the Apache License, Version 2.0 (the "License");          |
006| you may not use this file except in compliance with the License.         |
007| You may obtain a copy of the License at                                  |
008|                                                                          |
009|    http://www.apache.org/licenses/LICENSE-2.0                            |
010|                                                                          |
011| Unless required by applicable law or agreed to in writing, software      |
012| distributed under the License is distributed on an "AS IS" BASIS,        |
013| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
014| See the License for the specific language governing permissions and      |
015| limitations under the License.                                           |
016+-------------------------------------------------------------------------*/
017package org.conqat.lib.commons.math;
018
019import java.util.Collection;
020
021/**
022 * Calculates the variance with a two-pass algorithm. Implementation is highly
023 * similar to the one used in Apache Commons.
024 */
025public class VarianceAggregator implements IAggregator {
026
027        /**
028         * If true, sample variance is calculated, population variance otherwise.
029         */
030        private final boolean sample;
031
032        /**
033         * Constructor.
034         * 
035         * @param sample
036         *            if true sample variance is calculated, population variance
037         *            otherwise.
038         */
039        public VarianceAggregator(boolean sample) {
040                this.sample = sample;
041        }
042
043        /**
044         * Aggregates by finding the average value
045         * 
046         * @return {@link Double#NaN} for empty input collection
047         */
048        @Override
049        public double aggregate(Collection<? extends Number> values) {
050                if (values.isEmpty()) {
051                        return Double.NaN;
052                }
053                return calcVariance(values, MathUtils.mean(values));
054        }
055
056        /**
057         * Calculate variance. The implementation is based on the algorithm
058         * described at
059         * http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
060         */
061        private double calcVariance(Collection<? extends Number> values, double mean) {
062
063                if (values.size() == 1) {
064                        return 0;
065                }
066
067                double totalDeviationSquared = 0.0;
068                double totalDeviation = 0.0;
069
070                for (Number value : values) {
071                        double deviation = value.doubleValue() - mean;
072                        totalDeviationSquared += deviation * deviation;
073                        totalDeviation += deviation;
074                }
075
076                double x = totalDeviationSquared - (totalDeviation * totalDeviation / values.size());
077                if (sample) {
078                        return x / (values.size() - 1);
079                }
080
081                return x / values.size();
082        }
083
084        /** Returns {@link Double#NaN}. */
085        @Override
086        public double getNeutralElement() {
087                return Double.NaN;
088        }
089}