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The Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF 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, 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 org.apache.commons.math.stat.descriptive;

import java.io.Serializable;
import org.apache.commons.math.util.MathUtils;

/**
 *  Value object representing the results of a univariate statistical summary.
 *
 * @version $Revision: 762087 $ $Date: 2009-04-05 10:20:18 -0400 (Sun, 05 Apr 2009) $
 */
public class StatisticalSummaryValues implements Serializable, 
    StatisticalSummary {
   
    /** Serialization id */
    private static final long serialVersionUID = -5108854841843722536L;

    /** The sample mean */
    private final double mean;
    
    /** The sample variance */
    private final double variance;
    
    /** The number of observations in the sample */
    private final long n;
    
    /** The maximum value */
    private final double max;
    
    /** The minimum value */
    private final double min;
    
    /** The sum of the sample values */
    private final double sum;
    
    /**
      * Constructor
      * 
      * @param mean  the sample mean
      * @param variance  the sample variance
      * @param n  the number of observations in the sample 
      * @param max  the maximum value
      * @param min  the minimum value
      * @param sum  the sum of the values
     */
    public StatisticalSummaryValues(double mean, double variance, long n,
        double max, double min, double sum) {
        super();
        this.mean = mean;
        this.variance = variance;
        this.n = n;
        this.max = max;
        this.min = min;
        this.sum = sum;
    }

    /**
     * @return Returns the max.
     */
    public double getMax() {
        return max;
    }

    /**
     * @return Returns the mean.
     */
    public double getMean() {
        return mean;
    }

    /**
     * @return Returns the min.
     */
    public double getMin() {
        return min;
    }

    /**
     * @return Returns the number of values.
     */
    public long getN() {
        return n;
    }

    /**
     * @return Returns the sum.
     */
    public double getSum() {
        return sum;
    }
    
    /**
     * @return Returns the standard deviation
     */
    public double getStandardDeviation() {
        return Math.sqrt(variance);
    }

    /**
     * @return Returns the variance.
     */
    public double getVariance() {
        return variance;
    }
    
    /**
     * Returns true iff object is a 
     * StatisticalSummaryValues instance and all statistics have
     *  the same values as this.
     * 
     * @param object the object to test equality against.
     * @return true if object equals this
     */
    @Override
    public boolean equals(Object object) {
        if (object == this ) {
            return true;
        }
        if (object instanceof StatisticalSummaryValues == false) {
            return false;
        }
        StatisticalSummaryValues stat = (StatisticalSummaryValues) object;
        return (MathUtils.equals(stat.getMax(), this.getMax()) && 
                MathUtils.equals(stat.getMean(),this.getMean()) &&
                MathUtils.equals(stat.getMin(),this.getMin()) &&
                MathUtils.equals(stat.getN(), this.getN()) &&
                MathUtils.equals(stat.getSum(), this.getSum()) &&
                MathUtils.equals(stat.getVariance(),this.getVariance()));
    }
    
    /**
     * Returns hash code based on values of statistics
     * 
     * @return hash code
     */
    @Override
    public int hashCode() {
        int result = 31 + MathUtils.hash(getMax());
        result = result * 31 + MathUtils.hash(getMean());
        result = result * 31 + MathUtils.hash(getMin());
        result = result * 31 + MathUtils.hash(getN());
        result = result * 31 + MathUtils.hash(getSum());
        result = result * 31 + MathUtils.hash(getVariance());
        return result;
    }

}