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formatted slsDetectorCalibration
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Erik Frojdh
@@ -1,167 +1,158 @@
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// SPDX-License-Identifier: LGPL-3.0-or-other
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// Copyright (C) 2021 Contributors to the SLS Detector Package
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#ifndef MOVINGSTAT_H
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#define MOVINGSTAT_H
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#define MOVINGSTAT_H
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#include <math.h>
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class MovingStat {
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class MovingStat
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{
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/** @short approximated moving average structure */
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public:
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/** constructor
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\param nn number of samples parameter to be used
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*/
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MovingStat(int nn) : n(nn), m_n(0), m_newM(0), m_newM2(0) {}
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// void setPointers(double *me, double *va) {mean=me; var=va;}
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/**
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clears the moving average number of samples parameter, mean and standard
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deviation
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*/
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void Clear() {
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m_n = 0;
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m_newM = 0;
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m_newM2 = 0;
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}
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/** @short approximated moving average structure */
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public:
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/** constructor
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\param nn number of samples parameter to be used
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*/
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MovingStat(int nn) : n(nn), m_n(0), m_newM(0),m_newM2(0) {}
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// void setPointers(double *me, double *va) {mean=me; var=va;}
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/**
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clears the moving average number of samples parameter, mean and standard deviation
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*/
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void Clear()
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{
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m_n = 0;
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m_newM=0;
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m_newM2=0;
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}
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/**
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clears the moving average number of samples parameter, mean and standard deviation
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*/
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void Set(double val, double rms=0, int m=-1)
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{
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if (m>=0) m_n = m; else m_n = n;
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m_newM=val*m_n;
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SetRMS(rms);
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// cout << "set " << val << " " << m << " " << m_n << " " << m_newM << endl;
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}
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/**
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clears the moving average number of samples parameter, mean and standard deviation
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*/
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void SetRMS(double rms)
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{
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if (rms<=0) {
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if (m_n>0)
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m_newM2=m_newM*m_newM/m_n;
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else
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m_newM2=0;
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//m_n=0;
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} else {
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if (m_n>0) {
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m_newM2=(m_n*rms*rms+m_newM*m_newM/m_n);
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} else {
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m_newM2=(m_n*rms*rms+m_newM*m_newM/n);
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m_n=0;
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}
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}
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}
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/** sets number of samples parameter
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\param i number of samples parameter to be set
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*/
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int SetN(int i) {if (i>=1) n=i; return n;};
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/**
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gets number of samples parameter
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\returns actual number of samples parameter
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*/
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int GetN() {return m_n;};
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/** calculates the moving average i.e. adds if number of elements is lower than number of samples parameter, pushes otherwise
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\param x value to calculate the moving average
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*/
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inline void Calc(double x) {
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if (m_n<n) Add(x);
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else Push(x);
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}
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/** adds the element to the accumulated average and standard deviation
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\param x value to add
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*/
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inline void Add(double x) {
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m_n++;
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if (m_n == 1)
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{
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m_newM = x;
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m_newM2 = x*x;
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} else {
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m_newM = m_newM + x;
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m_newM2 = m_newM2 + x*x;
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/**
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clears the moving average number of samples parameter, mean and standard
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deviation
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*/
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void Set(double val, double rms = 0, int m = -1) {
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if (m >= 0)
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m_n = m;
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else
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m_n = n;
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m_newM = val * m_n;
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SetRMS(rms);
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// cout << "set " << val << " " << m << " " << m_n << " " << m_newM <<
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// endl;
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}
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/**
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clears the moving average number of samples parameter, mean and standard
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deviation
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*/
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void SetRMS(double rms) {
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if (rms <= 0) {
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if (m_n > 0)
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m_newM2 = m_newM * m_newM / m_n;
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else
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m_newM2 = 0;
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// m_n=0;
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} else {
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if (m_n > 0) {
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m_newM2 = (m_n * rms * rms + m_newM * m_newM / m_n);
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} else {
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m_newM2 = (m_n * rms * rms + m_newM * m_newM / n);
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m_n = 0;
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}
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}
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inline void Push(double x)
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{
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/** adds the element to the accumulated average and squared mean, while subtracting the current value of the average and squared average
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\param x value to push
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*/
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if (m_n == 0)
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{
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m_newM = x;
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m_newM2 = x*x;
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m_n++;
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}
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else {
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m_newM = m_newM + x - m_newM/m_n;
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m_newM2 = m_newM2 + x*x - m_newM2/m_n;
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}
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}
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/** returns the current number of elements of the moving average
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\returns returns the current number of elements of the moving average
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*/
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int NumDataValues() const
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{
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return m_n;
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}
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/** returns the mean, 0 if no elements are inside
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\returns returns the mean
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*/
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inline double Mean() const
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{
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// cout << "get " << m_n << " " << m_newM << " " << m_newM/m_n << endl;
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return (m_n > 0) ? m_newM/m_n : 0.0;
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}
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}
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/** returns the squared mean, 0 if no elements are inside
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\returns returns the squared average
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*/
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double M2() const
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{
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return ( (m_n > 1) ? m_newM2/m_n : 0.0 );
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}
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/** sets number of samples parameter
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\param i number of samples parameter to be set
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*/
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/** returns the variance, 0 if no elements are inside
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\returns returns the variance
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*/
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inline double Variance() const
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{
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return (m_n > 0) ? m_newM2/m_n-m_newM/m_n*m_newM/m_n : 0.0;
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}
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/** returns the standard deviation, 0 if no elements are inside
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\returns returns the standard deviation
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*/
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inline double StandardDeviation() const
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{
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return sqrt(Variance());//
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}
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private:
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int n; /**< number of samples parameter */
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int m_n; /**< current number of elements */
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double m_newM; /**< accumulated average */
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double m_newM2; /**< accumulated squared average */
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int SetN(int i) {
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if (i >= 1)
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n = i;
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return n;
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};
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/**
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gets number of samples parameter
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\returns actual number of samples parameter
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*/
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int GetN() { return m_n; };
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/** calculates the moving average i.e. adds if number of elements is lower
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than number of samples parameter, pushes otherwise \param x value to
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calculate the moving average
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*/
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inline void Calc(double x) {
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if (m_n < n)
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Add(x);
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else
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Push(x);
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}
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/** adds the element to the accumulated average and standard deviation
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\param x value to add
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*/
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inline void Add(double x) {
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m_n++;
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if (m_n == 1) {
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m_newM = x;
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m_newM2 = x * x;
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} else {
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m_newM = m_newM + x;
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m_newM2 = m_newM2 + x * x;
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}
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}
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inline void Push(double x) {
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/** adds the element to the accumulated average and squared mean, while
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subtracting the current value of the average and squared average
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\param x value to push
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*/
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if (m_n == 0) {
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m_newM = x;
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m_newM2 = x * x;
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m_n++;
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} else {
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m_newM = m_newM + x - m_newM / m_n;
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m_newM2 = m_newM2 + x * x - m_newM2 / m_n;
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}
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}
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/** returns the current number of elements of the moving average
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\returns returns the current number of elements of the moving average
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*/
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int NumDataValues() const { return m_n; }
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/** returns the mean, 0 if no elements are inside
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\returns returns the mean
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*/
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inline double Mean() const {
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// cout << "get " << m_n << " " << m_newM << " " << m_newM/m_n <<
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// endl;
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return (m_n > 0) ? m_newM / m_n : 0.0;
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}
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/** returns the squared mean, 0 if no elements are inside
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\returns returns the squared average
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*/
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double M2() const { return ((m_n > 1) ? m_newM2 / m_n : 0.0); }
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/** returns the variance, 0 if no elements are inside
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\returns returns the variance
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*/
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inline double Variance() const {
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return (m_n > 0) ? m_newM2 / m_n - m_newM / m_n * m_newM / m_n : 0.0;
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}
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/** returns the standard deviation, 0 if no elements are inside
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\returns returns the standard deviation
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*/
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inline double StandardDeviation() const {
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return sqrt(Variance()); //
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}
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private:
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int n; /**< number of samples parameter */
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int m_n; /**< current number of elements */
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double m_newM; /**< accumulated average */
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double m_newM2; /**< accumulated squared average */
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};
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#endif
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