    001    /*
    002     * Licensed to the Apache Software Foundation (ASF) under one or more
    003     * contributor license agreements.  See the NOTICE file distributed with
    004     * this work for additional information regarding copyright ownership.
    005     * The ASF licenses this file to You under the Apache License, Version 2.0
    006     * (the "License"); you may not use this file except in compliance with
    007     * the License.  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     */
    017    package org.apache.commons.math.stat.descriptive;
    018
    019    import java.io.Serializable;
    020
    021    import org.apache.commons.math.util.FastMath;
    022    import org.apache.commons.math.util.MathUtils;
    023
    024    /**
    025     *  Value object representing the results of a univariate statistical summary.
    026     *
    027     * @version $Revision: 1054186 $ $Date: 2011-01-01 03:28:46 +0100 (sam. 01 janv. 2011) $
    028     */
    029    public class StatisticalSummaryValues implements Serializable,
    030        StatisticalSummary {
    031
    032        /** Serialization id */
    033        private static final long serialVersionUID = -5108854841843722536L;
    034
    035        /** The sample mean */
    036        private final double mean;
    037
    038        /** The sample variance */
    039        private final double variance;
    040
    041        /** The number of observations in the sample */
    042        private final long n;
    043
    044        /** The maximum value */
    045        private final double max;
    046
    047        /** The minimum value */
    048        private final double min;
    049
    050        /** The sum of the sample values */
    051        private final double sum;
    052
    053        /**
    054          * Constructor
    055          *
    056          * @param mean  the sample mean
    057          * @param variance  the sample variance
    058          * @param n  the number of observations in the sample
    059          * @param max  the maximum value
    060          * @param min  the minimum value
    061          * @param sum  the sum of the values
    062         */
    063        public StatisticalSummaryValues(double mean, double variance, long n,
    064            double max, double min, double sum) {
    065            super();
    066            this.mean = mean;
    067            this.variance = variance;
    068            this.n = n;
    069            this.max = max;
    070            this.min = min;
    071            this.sum = sum;
    072        }
    073
    074        /**
    075         * @return Returns the max.
    076         */
    077        public double getMax() {
    078            return max;
    079        }
    080
    081        /**
    082         * @return Returns the mean.
    083         */
    084        public double getMean() {
    085            return mean;
    086        }
    087
    088        /**
    089         * @return Returns the min.
    090         */
    091        public double getMin() {
    092            return min;
    093        }
    094
    095        /**
    096         * @return Returns the number of values.
    097         */
    098        public long getN() {
    099            return n;
    100        }
    101
    102        /**
    103         * @return Returns the sum.
    104         */
    105        public double getSum() {
    106            return sum;
    107        }
    108
    109        /**
    110         * @return Returns the standard deviation
    111         */
    112        public double getStandardDeviation() {
    113            return FastMath.sqrt(variance);
    114        }
    115
    116        /**
    117         * @return Returns the variance.
    118         */
    119        public double getVariance() {
    120            return variance;
    121        }
    122
    123        /**
    124         * Returns true iff <code>object</code> is a
    125         * <code>StatisticalSummaryValues</code> instance and all statistics have
    126         *  the same values as this.
    127         *
    128         * @param object the object to test equality against.
    129         * @return true if object equals this
    130         */
    131        @Override
    132        public boolean equals(Object object) {
    133            if (object == this ) {
    134                return true;
    135            }
    136            if (object instanceof StatisticalSummaryValues == false) {
    137                return false;
    138            }
    139            StatisticalSummaryValues stat = (StatisticalSummaryValues) object;
    140            return MathUtils.equalsIncludingNaN(stat.getMax(),      getMax())  &&
    141                   MathUtils.equalsIncludingNaN(stat.getMean(),     getMean()) &&
    142                   MathUtils.equalsIncludingNaN(stat.getMin(),      getMin())  &&
    143                   MathUtils.equalsIncludingNaN(stat.getN(),        getN())    &&
    144                   MathUtils.equalsIncludingNaN(stat.getSum(),      getSum())  &&
    145                   MathUtils.equalsIncludingNaN(stat.getVariance(), getVariance());
    146        }
    147
    148        /**
    149         * Returns hash code based on values of statistics
    150         *
    151         * @return hash code
    152         */
    153        @Override
    154        public int hashCode() {
    155            int result = 31 + MathUtils.hash(getMax());
    156            result = result * 31 + MathUtils.hash(getMean());
    157            result = result * 31 + MathUtils.hash(getMin());
    158            result = result * 31 + MathUtils.hash(getN());
    159            result = result * 31 + MathUtils.hash(getSum());
    160            result = result * 31 + MathUtils.hash(getVariance());
    161            return result;
    162        }
    163
    164        /**
    165         * Generates a text report displaying values of statistics.
    166         * Each statistic is displayed on a separate line.
    167         *
    168         * @return String with line feeds displaying statistics
    169         */
    170        @Override
    171        public String toString() {
    172            StringBuilder outBuffer = new StringBuilder();
    173            String endl = "\n";
    174            outBuffer.append("StatisticalSummaryValues:").append(endl);
    175            outBuffer.append("n: ").append(getN()).append(endl);
    176            outBuffer.append("min: ").append(getMin()).append(endl);
    177            outBuffer.append("max: ").append(getMax()).append(endl);
    178            outBuffer.append("mean: ").append(getMean()).append(endl);
    179            outBuffer.append("std dev: ").append(getStandardDeviation())
    180                .append(endl);
    181            outBuffer.append("variance: ").append(getVariance()).append(endl);
    182            outBuffer.append("sum: ").append(getSum()).append(endl);
    183            return outBuffer.toString();
    184        }
    185
    186    }