TruncMean Class Reference

#include "TruncMean.h"

Public Member Functions
	TruncMean ()
	Default constructor. More...
	~TruncMean ()
	Default destructor. More...
void	CalcTruncMeanProfile (const std::vector< float > &rr_v, const std::vector< float > &dq_v, std::vector< float > &dq_trunc_v, const float &nsigma=1)
	Given residual range and dq vectors return truncated local dq. Input vectors are assumed to be match pair-wise (nth entry in rr_v corresponds to nth entry in dq_v vector). Input rr_v values are also assumed to be ordered: monotonically increasing or decreasing. For every dq value a truncated linear dq value is calculated as follows: 0) all dq values within a rr range set by the class variable _rad are selected. 1) the median and rms of these values is calculated. 2) the subset of local dq values within the range [median-rms, median+rms] is selected. 3) the resulting local truncated dq is the average of this truncated subset. std::vector<float> rr_v -> vector of x-axis coordinates (i.e. position for track profile) std::vector<float> dq_v -> vector of measured values for which truncated profile is requested (i.e. charge profile of a track) std::vector<float> dq_trunc_v -> passed by reference -> output stored here float nsigma -> optional parameter, number of sigma to keep around RMS for TM calculation. More...
float	CalcIterativeTruncMean (std::vector< float > v, const size_t &nmin, const size_t &nmax, const size_t &currentiteration, const size_t &lmin, const float &convergencelimit, const float &nsigma, const float &oldmed=kINVALID_FLOAT)
	Iteratively calculate the truncated mean of a distribution std::vector<float> v -> vector of values for which truncated mean is asked size_t nmin -> minimum number of iterations to converge on truncated mean size_t nmax -> maximum number of iterations to converge on truncated mean size_t lmin -> minimum number of entries in vector before exiting and returning current value size_t currentiteration -> current iteration float convergencelimit -> fractional difference between successive iterations under which the iteration is completed, provided nmin iterations have occurred. nsigma -> number of sigma around the median value to keep when the distribution is trimmed. More...
void	setRadius (const float &rad)
	Set the smearing radius over which to take hits for truncated mean computaton. More...

Private Member Functions
float	Mean (const std::vector< float > &v)
float	Median (const std::vector< float > &v)
float	RMS (const std::vector< float > &v)

Private Attributes
double	_rad

Detailed Description

The truncated mean class allows to compute the following quantities 1) the truncated mean profile of an ordered vector of values, such as the charge profile along a particle's track. To create such a profile use the function CalcTruncMeanProfile() 2) Get the truncated mean value of a distribution. This function iteratively hones in on the truncated mean of a distribution by updating the mean and cutting the tails after each iteration. For this functionality use CalcIterativeTruncMean() doxygen documentation!

Definition at line 37 of file TruncMean.h.

Constructor & Destructor Documentation

TruncMean::TruncMean ( )

inline

Default constructor.

Definition at line 42 of file TruncMean.h.

{}

TruncMean::~TruncMean ( )

inline

Default destructor.

Definition at line 45 of file TruncMean.h.

References CalcIterativeTruncMean(), CalcTruncMeanProfile(), and kINVALID_FLOAT.

{}

Member Function Documentation

float TruncMean::CalcIterativeTruncMean	(	std::vector< float >	v,
		const size_t &	nmin,
		const size_t &	nmax,
		const size_t &	currentiteration,
		const size_t &	lmin,
		const float &	convergencelimit,
		const float &	nsigma,
		const float &	oldmed = kINVALID_FLOAT
	)

Iteratively calculate the truncated mean of a distribution std::vector<float> v -> vector of values for which truncated mean is asked size_t nmin -> minimum number of iterations to converge on truncated mean size_t nmax -> maximum number of iterations to converge on truncated mean size_t lmin -> minimum number of entries in vector before exiting and returning current value size_t currentiteration -> current iteration float convergencelimit -> fractional difference between successive iterations under which the iteration is completed, provided nmin iterations have occurred. nsigma -> number of sigma around the median value to keep when the distribution is trimmed.

Definition at line 7 of file TruncMean.cxx.

References pmtana::mean(), Mean(), Median(), RMS(), and x.

Referenced by ~TruncMean().

{

  auto const& mean = Mean(v);
  auto const& med  = Median(v);
  auto const& rms  = RMS(v);

  // if the vector length is below the lower limit -> return
  if (v.size() < lmin)
    return mean;

  // if we have passed the maximum number of iterations -> return
  if (currentiteration >= nmax)
    return mean;

  // if we passed the minimum number of iterations and the mean is close enough to the old value
  float fracdiff = fabs(med-oldmed) / oldmed;
  if ( (currentiteration >= nmin) && (fracdiff < convergencelimit) )
    return mean;
  
  // if reached here it means we have to go on for another iteration

  // cutoff tails of distribution surrounding the mean
  // use erase-remove : https://en.wikipedia.org/wiki/Erase%E2%80%93remove_idiom
  // https://stackoverflow.com/questions/17270837/stdvector-removing-elements-which-fulfill-some-conditions
  v.erase( std::remove_if( v.begin(), v.end(), 
                           [med,nsigma,rms](const float& x) { return ( (x < (med-nsigma*rms)) || (x > (med+nsigma*rms)) ); }), // lamdda condition for events to be removed
           v.end());
  
  return CalcIterativeTruncMean(v, nmin, nmax, lmin, currentiteration+1, convergencelimit, nsigma, med);
}

void TruncMean::CalcTruncMeanProfile	(	const std::vector< float > &	rr_v,
		const std::vector< float > &	dq_v,
		std::vector< float > &	dq_trunc_v,
		const float &	nsigma = 1
	)

Given residual range and dq vectors return truncated local dq. Input vectors are assumed to be match pair-wise (nth entry in rr_v corresponds to nth entry in dq_v vector). Input rr_v values are also assumed to be ordered: monotonically increasing or decreasing. For every dq value a truncated linear dq value is calculated as follows: 0) all dq values within a rr range set by the class variable _rad are selected. 1) the median and rms of these values is calculated. 2) the subset of local dq values within the range [median-rms, median+rms] is selected. 3) the resulting local truncated dq is the average of this truncated subset. std::vector<float> rr_v -> vector of x-axis coordinates (i.e. position for track profile) std::vector<float> dq_v -> vector of measured values for which truncated profile is requested (i.e. charge profile of a track) std::vector<float> dq_trunc_v -> passed by reference -> output stored here float nsigma -> optional parameter, number of sigma to keep around RMS for TM calculation.

Definition at line 43 of file TruncMean.cxx.

References _rad, Median(), n, and RMS().

Referenced by ~TruncMean().

{

  // how many points to sample 
  int Nneighbor = (int)(_rad * 3 * 2);

  dq_trunc_v.clear();
  dq_trunc_v.reserve( rr_v.size() );

  int Nmax = dq_v.size()-1;
  
  for (size_t n=0; n < dq_v.size(); n++) {

    // current residual range
    float rr = rr_v.at(n);

    int nmin = n - Nneighbor;
    int nmax = n + Nneighbor;

    if (nmin < 0) nmin = 0;
    if (nmax > Nmax) nmax = Nmax;

    // vector for local dq values
    std::vector<float> dq_local_v;

    for (int i=nmin; i < nmax; i++) {
      
      float dr = rr - rr_v[i];
      if (dr < 0) dr *= -1;

      if (dr > _rad) continue;

      dq_local_v.push_back( dq_v[i] );
      
    }// for all ticks we want to scan

    if (dq_local_v.size() == 0) {
      dq_trunc_v.push_back( dq_v.at(n) );
      continue;
    }
    
    // calculate median and rms
    float median = Median(dq_local_v);
    float rms    = RMS(dq_local_v);

    float truncated_dq = 0.;
    int npts = 0;
    for (auto const& dq : dq_local_v) {
      if ( ( dq < (median+rms * nsigma) ) && ( dq > (median-rms * nsigma) ) ){
        truncated_dq += dq;
        npts += 1;
      }
    }

    dq_trunc_v.push_back( truncated_dq / npts );
  }// for all values

  return;
}

float TruncMean::Mean ( const std::vector< float > &  v )

private

Definition at line 104 of file TruncMean.cxx.

References pmtana::mean(), and n.

Referenced by CalcIterativeTruncMean(), and setRadius().

{

  float mean = 0.;
  for (auto const& n : v) mean += n;
  mean /= v.size();
  
  return mean;
}

float TruncMean::Median ( const std::vector< float > &  v )

private

Definition at line 114 of file TruncMean.cxx.

Referenced by CalcIterativeTruncMean(), CalcTruncMeanProfile(), and setRadius().

{

  if (v.size() == 1) return v[0];
  
  std::vector<float> vcpy = v;

  std::sort(vcpy.begin(), vcpy.end());

  float median = vcpy[ vcpy.size() / 2 ];

  return median;
}

float TruncMean::RMS ( const std::vector< float > &  v )

private

Definition at line 128 of file TruncMean.cxx.

Referenced by CalcIterativeTruncMean(), CalcTruncMeanProfile(), and setRadius().

{

  float avg = 0.;
  for (auto const& val : v) avg += val;
  avg /= v.size();
  float rms = 0.;
  for (auto const& val : v) rms += (val-avg)*(val-avg);
  rms = sqrt( rms / ( v.size() -  1 ) );

  return rms;
}

void TruncMean::setRadius ( const float &  rad )

inline

Set the smearing radius over which to take hits for truncated mean computaton.

Definition at line 87 of file TruncMean.h.

References _rad, Mean(), Median(), and RMS().

{ _rad = rad; }

Member Data Documentation

double TruncMean::_rad

private

Smearing radius over which charge from neighboring hits is scanned to calculate local truncated mean

Definition at line 99 of file TruncMean.h.

Referenced by CalcTruncMeanProfile(), and setRadius().

---

The documentation for this class was generated from the following files:

• /cvmfs/larsoft.opensciencegrid.org/products/larana/v07_04_02/source/larana/TruncatedMean/Algorithm/TruncMean.h
• /cvmfs/larsoft.opensciencegrid.org/products/larana/v07_04_02/source/larana/TruncatedMean/Algorithm/TruncMean.cxx