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/* Any copyright is dedicated to the Public Domain.
http://creativecommons.org/publicdomain/zero/1.0/ */
/* Adapted from "Accurately computing running variance - John D. Cook"
http://www.johndcook.com/standard_deviation.html */
#ifndef RUNNING_STAT_H_
#define RUNNING_STAT_H_
#include <math.h>
namespace mozilla {
class RunningStat {
public:
RunningStat() : mN(0), mOldM(0.0), mNewM(0.0), mOldS(0.0), mNewS(0.0) {}
void Clear() { mN = 0; }
void Push(double x) {
mN++;
// See Knuth TAOCP vol 2, 3rd edition, page 232
if (mN == 1) {
mOldM = mNewM = x;
mOldS = 0.0;
} else {
mNewM = mOldM + (x - mOldM) / mN;
mNewS = mOldS + (x - mOldM) * (x - mNewM);
// set up for next iteration
mOldM = mNewM;
mOldS = mNewS;
}
}
int NumDataValues() const { return mN; }
double Mean() const { return (mN > 0) ? mNewM : 0.0; }
double Variance() const { return (mN > 1) ? mNewS / (mN - 1) : 0.0; }
double StandardDeviation() const { return sqrt(Variance()); }
private:
int mN;
double mOldM, mNewM, mOldS, mNewS;
};
} // namespace mozilla
#endif // RUNNING_STAT_H_
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