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  //
  //  ========================================================================
  //  Copyright (c) 1995-2012 Mort Bay Consulting Pty. Ltd.
  //  ------------------------------------------------------------------------
  //  All rights reserved. This program and the accompanying materials
  //  are made available under the terms of the Eclipse Public License v1.0
  //  and Apache License v2.0 which accompanies this distribution.
  //
  //      The Eclipse Public License is available at
 //      http://www.eclipse.org/legal/epl-v10.html
 //
 //      The Apache License v2.0 is available at
 //      http://www.opensource.org/licenses/apache2.0.php
 //
 //  You may elect to redistribute this code under either of these licenses.
 //  ========================================================================
 //
 
 package org.eclipse.jetty.util.statistic;
 
 
 
 
 /* ------------------------------------------------------------ */
SampledStatistics

Provides max, total, mean, count, variance, and standard deviation of continuous sequence of samples.

Calculates estimates of mean, variance, and standard deviation characteristics of a sample using a non synchronized approximation of the on-line algorithm presented in Donald Knuth's Art of Computer Programming, Volume 2, Seminumerical Algorithms, 3rd edition, page 232, Boston: Addison-Wesley. that cites a 1962 paper by B.P. Welford that can be found by following the link http://www.jstor.org/pss/1266577

This algorithm is also described in Wikipedia at http://en.wikipedia.org/w/index.php?title=Algorithms_for_calculating_variance&section=4#On-line_algorithm

 
 public class SampleStatistic
 {
     protected final AtomicLong _max = new AtomicLong();
     protected final AtomicLong _total = new AtomicLong();
     protected final AtomicLong _count = new AtomicLong();
     protected final AtomicLong _totalVariance100 = new AtomicLong();
 
     public void reset()
     {
         .set(0);
         .set(0);
         .set(0);
         .set(0);
     }
 
     public void set(final long sample)
     {
         long total = .addAndGet(sample);
         long count = .incrementAndGet();
 
         if (count>1)
         {
             long mean10 = total*10/count;
             long delta10 = sample*10 - mean10;
             .addAndGet(delta10*delta10);
         }
 
         Atomics.updateMax(sample);
     }

    

Returns:
the max value
 
     public long getMax()
     {
         return .get();
     }
 
     public long getTotal()
     {
         return .get();
     }
 
     public long getCount()
     {
         return .get();
     }
 
     public double getMean()
     {
         return (double).get()/.get();
     }
 
     public double getVariance()
     {
         final long variance100 = .get();
        final long count = .get();
        return count>1?((double)variance100)/100.0/(count-1):0.0;
    }
    public double getStdDev()
    {
        return Math.sqrt(getVariance());
    }
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