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147 lines
3.6 KiB
C++
147 lines
3.6 KiB
C++
//
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// FILE: Statistic.cpp
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// AUTHOR: Rob dot Tillaart at gmail dot com
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// modified at 0.3 by Gil Ross at physics dot org
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// VERSION: see STATISTIC_LIB_VERSION in .h
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// PURPOSE: Recursive statistical library for Arduino
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//
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// NOTE: 2011-01-07 Gill Ross
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// Rob Tillaart's Statistic library uses one-pass of the data (allowing
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// each value to be discarded), but expands the Sum of Squares Differences to
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// difference the Sum of Squares and the Average Squared. This is susceptible
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// to bit length precision errors with the float type (only 5 or 6 digits
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// absolute precision) so for long runs and high ratios of
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// the average value to standard deviation the estimate of the
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// standard error (deviation) becomes the difference of two large
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// numbers and will tend to zero.
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//
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// For small numbers of iterations and small Average/SE th original code is
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// likely to work fine.
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// It should also be recognised that for very large samples, questions
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// of stability of the sample assume greater importance than the
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// correctness of the asymptotic estimators.
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//
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// This recursive algorithm, which takes slightly more computation per
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// iteration is numerically stable.
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// It updates the number, mean, max, min and SumOfSquaresDiff each step to
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// deliver max min average, population standard error (standard deviation) and
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// unbiassed SE.
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// -------------
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//
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// HISTORY:
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// 0.1 - 2010-10-29 initial version
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// 0.2 - 2010-10-29 stripped to minimal functionality
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// 0.2.01 - 2010-10-30
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// added minimim, maximum, unbiased stdev,
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// changed counter to long -> int overflows @32K samples
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// 0.3 - 2011-01-07
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// branched from 0.2.01 version of Rob Tillaart's code
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// 0.3.1 - minor edits
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// 0.3.2 - 2012-11-10
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// minor edits
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// changed count -> unsigned long allows for 2^32 samples
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// added variance()
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//
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// Released to the public domain
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//
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#include "Statistic.h"
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Statistic::Statistic()
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{
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clear();
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}
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// resets all counters
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void Statistic::clear()
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{
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_cnt = 0;
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_sum = 0.0;
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_min = 0.0;
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_max = 0.0;
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#ifdef STAT_USE_STDEV
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_ssqdif = 0.0; // not _ssq but sum of square differences
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// which is SUM(from i = 1 to N) of
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// (f(i)-_ave_N)**2
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#endif
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}
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// adds a new value to the data-set
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void Statistic::add(float f)
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{
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if (_cnt == 0)
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{
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_min = f;
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_max = f;
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} else {
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if (f < _min) _min = f;
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if (f > _max) _max = f;
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}
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_sum += f;
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_cnt++;
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#ifdef STAT_USE_STDEV
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if (_cnt >1)
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{
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_store = (_sum / _cnt - f);
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_ssqdif = _ssqdif + _cnt * _store * _store / (_cnt-1);
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}
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#endif
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}
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// returns the number of values added
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unsigned long Statistic::count()
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{
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return _cnt;
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}
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// returns the average of the data-set added sofar
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float Statistic::average()
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{
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if (_cnt == 0) return NAN; // original code returned 0
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return _sum / _cnt;
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}
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// returns the sum of the data-set (0 if no values added)
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float Statistic::sum()
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{
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return _sum;
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}
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// returns the sum of the data-set (0 if no values added)
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float Statistic::minimum()
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{
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return _min;
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}
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// returns the sum of the data-set (0 if no values added)
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float Statistic::maximum()
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{
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return _max;
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}
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// Population standard deviation = s = sqrt [ S ( Xi - <20> )2 / N ]
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// http://www.suite101.com/content/how-is-standard-deviation-used-a99084
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#ifdef STAT_USE_STDEV
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float Statistic::variance()
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{
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if (_cnt == 0) return NAN; // otherwise DIV0 error
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return _ssqdif / _cnt;
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}
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float Statistic::pop_stdev()
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{
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if (_cnt == 0) return NAN; // otherwise DIV0 error
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return sqrt( _ssqdif / _cnt);
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}
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float Statistic::unbiased_stdev()
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{
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if (_cnt < 2) return NAN; // otherwise DIV0 error
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return sqrt( _ssqdif / (_cnt - 1));
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}
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#endif
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// END OF FILE
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