A 1D distribution. More...

#include <Dbn.h>

Inheritance diagram for YODA::DbnBase< N >:

Public Types
using	BaseT = DbnBase< N >

using	FillDim = std::integral_constant< size_t, N >

using	DataSize = std::integral_constant< size_t, 1+2 (N+1)+(N (N-1)/2)>

Public Member Functions
Constructors
	DbnBase ()
	Default constructor of a new distribution.

template<size_t dim = N, typename = std::enable_if_t<(dim < 2)>>
	DbnBase (const double numEntries, const std::array< double, N+1 > &sumW, const std::array< double, N+1 > &sumW2)
	Constructor to set a distribution with a pre-filled state.

template<size_t dim = N, typename = std::enable_if_t<(dim >= 2)>>
	DbnBase (const double numEntries, const std::array< double, N+1 > &sumW, const std::array< double, N+1 > &sumW2, const std::array< double, N *(N-1)/2 > &sumWcross)
	Constructor to set a distribution with a pre-filled state.

	DbnBase (const DbnBase &)=default

	DbnBase (DbnBase &&)=default

DbnBase &	operator= (const DbnBase &)=default

DbnBase &	operator= (DbnBase &&)=default

Modifiers
void	fill (const std::array< double, N > vals, const double weight=1.0, const double fraction=1.0)
	Contribute a sample at val (from an array) with weight weight.

template<typename... Args>
void	fill (Args &&... args)
	Templated convenience overload of fill method.

void	set (const double numEntries, const std::array< double, N+1 > &sumW, const std::array< double, N+1 > &sumW2, const std::array< double, N *(N-1)/2 > &sumWcross)
	Set a sample with array-based number of entries numEntries, sum of weights sumW (and corresponding moments), sum of squared weights sumW2 (and corresponding moments).

void	set (const double numEntries, const std::vector< double > &sumW, const std::vector< double > &sumW2, const std::vector< double > &sumWcross={})
	Set a sample with vector-based number of entries numEntries, sum of weights sumW (and corresponding moments), sum of squared weights sumW2 (and corresponding moments).

void	set (const DbnBase< N > &other)
	Set a sample with other.

void	set (DbnBase< N > &&other)
	Set a sample with other.

void	reset ()
	Reset the internal counters.

void	scaleW (const double scalefactor)
	Rescale as if all fill weights had been different by factor scalefactor.

void	scale (const size_t dim, const double factor)

Distribution statistics
double	errW () const
	The absolute error on sumW.

double	relErrW () const
	The relative error on sumW.

double	mean (const size_t i) const
	Weighted mean, $\bar{x}$ , of distribution.

double	variance (const size_t i) const
	Weighted variance, $\sigma^2$ , of distribution.

double	stdDev (const size_t i) const
	Weighted standard deviation, $\sigma$ , of distribution.

double	stdErr (const size_t i) const
	Weighted standard error on the mean, $\sim \sigma/\sqrt{N-1}$ , of distribution.

double	relStdErr (const size_t i) const
	Relative weighted standard error on the mean, $\sim \sigma/\sqrt{N-1}$ , of distribution.

double	RMS (const size_t i) const
	Weighted RMS, $\sqrt{ \sum{w x^2}/\sum{w} }$ , of distribution.

Raw distribution running sums
double	numEntries () const
	Number of entries (number of times `fill` was called, ignoring weights)

double	effNumEntries () const
	Effective number of entries $= (\sum w)^2 / \sum w^2$ .

double	sumW () const
	The sum of weights.

double	sumW2 () const
	The sum of weights squared.

double	sumW (const size_t i) const
	The sum of x*weight.

double	sumW2 (const size_t i) const
	The sum of x^2*weight.

template<size_t dim = N, typename = std::enable_if_t<(dim >= 2)>>
double	crossTerm (const size_t A1, const size_t A2) const
	The second-order cross term between axes k and l.

size_t	dim () const

I/O
std::string	toString () const
	String representation of the DbnBase for debugging.

Reduce operations
template<typename... size_t>
DbnBase< sizeof...(size_t)>	reduceTo (size_t... axes) const
	Reduce operation that produces a lower-dimensional DbnBase keeping only the specified axes in the new DbnBase.

template<size_t... Is>
DbnBase< sizeof...(Is)>	reduceTo (std::index_sequence< Is... >) const
	Same as above but using an std::integer_sequence.

template<size_t... axes>
auto	reduce () const
	Reduce operation that produces a lower-dimensional DbnBase removing the specified axes for the new DbnBase.

Operators
DbnBase &	operator+= (const DbnBase &d)
	Add two DbnBases.

DbnBase &	operator+= (DbnBase &&d)
	Add two DbnBases.

DbnBase &	operator-= (const DbnBase &d)
	Subtract one DbnBase from another.

DbnBase &	operator-= (DbnBase &&d)
	Subtract one DbnBase from another.

Detailed Description

template<size_t N>
class YODA::DbnBase< N >

A 1D distribution.

This class is used internally by YODA to centralise the calculation of statistics of unbounded, unbinned sampled distributions. Each distribution fill contributes a weight, , and a value, . By storing the total number of fills (ignoring weights), $\sum w$ , $\sum w^2$ , $\sum wx$ , and $\sum wx^2$ , the Dbn can calculate the mean and spread ( $\sigma^2$ , $\sigma$ and $\hat{\sigma}$ ) of the sampled distribution. It is used to provide this information in bins and for the "hidden" distribution in profile histogram bins.

Definition at line 86 of file Dbn.h.

Member Typedef Documentation

◆ BaseT

template<size_t N>

using YODA::DbnBase< N >::BaseT = DbnBase<N>

Definition at line 89 of file Dbn.h.

◆ DataSize

template<size_t N>

using YODA::DbnBase< N >::DataSize = std::integral_constant<size_t, 1 + 2*(N+1) + (N*(N-1)/2)>

Definition at line 91 of file Dbn.h.

◆ FillDim

template<size_t N>

using YODA::DbnBase< N >::FillDim = std::integral_constant<size_t, N>

Definition at line 90 of file Dbn.h.

Constructor & Destructor Documentation

◆ DbnBase() [1/5]

template<size_t N>

YODA::DbnBase< N >::DbnBase ( )

inline

Default constructor of a new distribution.

Definition at line 97 of file Dbn.h.

97{ reset(); }

YODA::DbnBase::reset

void reset()

Reset the internal counters.

Definition Dbn.h:232

References YODA::DbnBase< N >::reset().

◆ DbnBase() [2/5]

template<size_t N>

template<size_t dim = N, typename = std::enable_if_t<(dim < 2)>>

YODA::DbnBase< N >::DbnBase	(	const double	numEntries,
		const std::array< double, N+1 > &	sumW,
		const std::array< double, N+1 > &	sumW2
	)

inline

Constructor to set a distribution with a pre-filled state.

Principally designed for internal persistency use.

Note: No cross-term possible for 0- and 1D.

Definition at line 105 of file Dbn.h.

106 : _numEntries(numEntries), _sumW(sumW), _sumW2(sumW2) { }

YODA::DbnBase::sumW

double sumW() const

The sum of weights.

Definition Dbn.h:320

YODA::DbnBase::numEntries

double numEntries() const

Number of entries (number of times fill was called, ignoring weights)

Definition Dbn.h:309

YODA::DbnBase::sumW2

double sumW2() const

The sum of weights squared.

Definition Dbn.h:325

◆ DbnBase() [3/5]

template<size_t N>

template<size_t dim = N, typename = std::enable_if_t<(dim >= 2)>>

YODA::DbnBase< N >::DbnBase	(	const double	numEntries,
		const std::array< double, N+1 > &	sumW,
		const std::array< double, N+1 > &	sumW2,
		const std::array< double, N *(N-1)/2 > &	sumWcross
	)

inline

Constructor to set a distribution with a pre-filled state.

Principally designed for internal persistency use.

Note: Includes second-order cross-terms.

Definition at line 113 of file Dbn.h.

115 : _numEntries(numEntries), _sumW(sumW), _sumW2(sumW2), _sumWcross(sumWcross) { }

◆ DbnBase() [4/5]

template<size_t N>

YODA::DbnBase< N >::DbnBase ( const DbnBase< N > & )

default

Copy constructor

Sets all the parameters using the ones provided from an existing DbnBase.

◆ DbnBase() [5/5]

template<size_t N>

YODA::DbnBase< N >::DbnBase ( DbnBase< N > && )

default

Move constructor

Sets all the parameters using the ones provided from an existing DbnBase.

Member Function Documentation

◆ crossTerm()

template<size_t N>

template<size_t dim = N, typename = std::enable_if_t<(dim >= 2)>>

double YODA::DbnBase< N >::crossTerm	(	const size_t	A1,
		const size_t	A2
	)		const

inline

The second-order cross term between axes k and l.

Definition at line 341 of file Dbn.h.

                                                             {
      if (A1 >= N || A2 >= N)  throw RangeError("Invalid axis int, must be in range 0..dim-1");
      if (A1 >= A2)  throw RangeError("Indices need to be different for cross term");
 
      size_t idx = 0;
      for (size_t i = 0; i < (N-1); ++i) {
        for (size_t j = i+1; j < N; ++j) {
          if (i == A1 && j == A2)  break;
          ++idx;
        }
        if (i == A1)  break;
      }
 
      return _sumWcross.at(idx);
    }

Referenced by YODA::DbnBase< N >::reduceTo().

◆ dim()

template<size_t N>

size_t YODA::DbnBase< N >::dim ( ) const

inline

Definition at line 357 of file Dbn.h.

357{ return N; }

Referenced by YODA::DbnBase< N >::scale().

◆ effNumEntries()

template<size_t N>

double YODA::DbnBase< N >::effNumEntries ( ) const

inline

Effective number of entries $= (\sum w)^2 / \sum w^2$ .

Definition at line 314 of file Dbn.h.

                                 {
      if (_sumW2.at(0) == 0) return 0;
      return _sumW.at(0)*_sumW.at(0) / _sumW2.at(0);
    }

◆ errW()

template<size_t N>

double YODA::DbnBase< N >::errW ( ) const

The absolute error on sumW.

Definition at line 506 of file Dbn.h.

                                {
    return sqrt(sumW2(0));
  }

◆ fill() [1/2]

template<size_t N>

template<typename... Args>

void YODA::DbnBase< N >::fill ( Args &&... args )

inline

Templated convenience overload of fill method.

Example:

fill(3.0, 2.1, 3.4, 3.0) // To fill value (X=3.0,Y=2.1,Z=3.0) with weight 3.0

Definition at line 162 of file Dbn.h.

                              {
      // N + 2 - dimension + 2 default parameters
      static_assert(sizeof...(args) <= N + 2,
                    "Value's dimension doesn't match distribution's dimension.");
      std::array<double, sizeof...(args)> vals = {{args...}};
      double weight = 1.0;
      double fraction = 1.0;
      if (vals.size() > N) {
        weight = vals[N];
        if (vals.size() > N + 1)  fraction = vals[N + 1];
      }
      const double sf = fraction * weight;
      _numEntries += fraction;
      _sumW.at(0) += sf;
      _sumW2.at(0) += fraction*sqr(weight);
      for (unsigned int i = 0; i < N; ++i) {
        _sumW.at(i + 1) += sf * vals.at(i);
        _sumW2.at(i + 1) += sf * sqr(vals.at(i));
      }
 
      if constexpr(N >= 2) {
        size_t idx = 0;
        for (size_t i = 0; i < (N-1); ++i) {
          for (size_t j = i+1; j < N; ++j) {
            _sumWcross.at(idx++) += sf * vals.at(i) * vals.at(j);
          }
        }
      }
 
    }

References YODA::sqr().

◆ fill() [2/2]

template<size_t N>

void YODA::DbnBase< N >::fill	(	const std::array< double, N >	vals,
		const double	weight = `1.0`,
		const double	fraction = `1.0`
	)

inline

Contribute a sample at val (from an array) with weight weight.

If you use brace enclosed initializer list and call this method in this way: fill({1,2,3}, 2, 3) and get error from compiler with this note: "no known conversion for argument 1 from ‘<brace-enclosed initializer list>’ to ‘std::array<double, 0>’", it likely means that your value dimension doesn't match distribution's.

Definition at line 152 of file Dbn.h.

                                                                                                      {
      fill(vals, weight, fraction, std::make_index_sequence<N>{});
    }

References YODA::DbnBase< N >::fill().

Referenced by YODA::Dbn< 1 >::fill(), YODA::Dbn< 3 >::fill(), YODA::Dbn< 2 >::fill(), YODA::Dbn< 0 >::fill(), YODA::Dbn< 0 >::fill(), YODA::Dbn< 1 >::fill(), YODA::Dbn< 2 >::fill(), YODA::Dbn< 3 >::fill(), and YODA::DbnBase< N >::fill().

◆ mean()

template<size_t N>

double YODA::DbnBase< N >::mean ( const size_t i ) const

Weighted mean, $\bar{x}$ , of distribution.

Definition at line 519 of file Dbn.h.

                                              {
    return YODA::mean(sumW(i), sumW(0));
  }

References YODA::mean().

Referenced by YODA::DbnStorage< DbnN, AxisT >::mean(), and YODA::DbnBase< N >::toString().

◆ numEntries()

template<size_t N>

double YODA::DbnBase< N >::numEntries ( ) const

inline

Number of entries (number of times fill was called, ignoring weights)

Definition at line 309 of file Dbn.h.

                              {
      return _numEntries;
    }

Referenced by YODA::Dbn< 0 >::set(), and YODA::DbnBase< N >::set().

◆ operator+=() [1/2]

template<size_t N>

DbnBase< N > & YODA::DbnBase< N >::operator+= ( const DbnBase< N > & d )

Add two DbnBases.

Definition at line 551 of file Dbn.h.

                                                          {
    _numEntries += d._numEntries;
    for (size_t i = 0; i <= N; ++i) {
      _sumW.at(i) += d._sumW.at(i);
      _sumW2.at(i) += d._sumW2.at(i);
    }
    for (size_t i = 0; i < _sumWcross.size(); ++i) {
      _sumWcross.at(i) += d._sumWcross.at(i);
    }
    return *this;
  }

◆ operator+=() [2/2]

template<size_t N>

DbnBase< N > & YODA::DbnBase< N >::operator+= ( DbnBase< N > && d )

Add two DbnBases.

Definition at line 565 of file Dbn.h.

                                                     {
    _numEntries += std::move(d._numEntries);
    for (size_t i = 0; i <= N; ++i) {
      _sumW.at(i) += std::move(d._sumW.at(i));
      _sumW2.at(i) += std::move(d._sumW2.at(i));
    }
    for (size_t i = 0; i < _sumWcross.size(); ++i) {
      _sumWcross.at(i) += std::move(d._sumWcross.at(i));
    }
    return *this;
  }

◆ operator-=() [1/2]

template<size_t N>

DbnBase< N > & YODA::DbnBase< N >::operator-= ( const DbnBase< N > & d )

Subtract one DbnBase from another.

Definition at line 579 of file Dbn.h.

                                                          {
    _numEntries -= d._numEntries;
    for (unsigned int i =0; i<= N ; ++i) {
      _sumW.at(i)  -= d._sumW.at(i);
      _sumW2.at(i) += d._sumW2.at(i);
    }
    for (size_t i = 0; i < _sumWcross.size(); ++i) {
      _sumWcross.at(i) -= d._sumWcross.at(i);
    }
    return *this;
  }

◆ operator-=() [2/2]

template<size_t N>

DbnBase< N > & YODA::DbnBase< N >::operator-= ( DbnBase< N > && d )

Subtract one DbnBase from another.

Definition at line 593 of file Dbn.h.

                                                     {
    _numEntries -= std::move(d._numEntries);
    for (unsigned int i =0; i<= N ; ++i) {
      _sumW.at(i)  -= std::move(d._sumW.at(i));
      _sumW2.at(i) += std::move(d._sumW2.at(i));
    }
    for (size_t i = 0; i < _sumWcross.size(); ++i) {
      _sumWcross.at(i) -= std::move(d._sumWcross.at(i));
    }
    return *this;
  }

◆ operator=() [1/2]

template<size_t N>

DbnBase & YODA::DbnBase< N >::operator= ( const DbnBase< N > & )

default

Copy assignment

Sets all the parameters using the ones provided from an existing DbnBase.

◆ operator=() [2/2]

template<size_t N>

DbnBase & YODA::DbnBase< N >::operator= ( DbnBase< N > && )

default

Move assignment

Sets all the parameters using the ones provided from an existing DbnBase.

◆ reduce()

template<size_t N>

template<size_t... axes>

auto YODA::DbnBase< N >::reduce ( ) const

inline

Reduce operation that produces a lower-dimensional DbnBase removing the specified axes for the new DbnBase.

Definition at line 415 of file Dbn.h.

                        {
      constexpr auto new_axes = AxisFilter(std::make_index_sequence<N>{},
        [](size_t i) { return !has_match(i, std::integer_sequence<size_t, axes...>{}); }
      );
      return reduceTo(new_axes);
    }

References YODA::DbnBase< N >::reduceTo().

◆ reduceTo() [1/2]

template<size_t N>

template<typename... size_t>

DbnBase< sizeof...(size_t)> YODA::DbnBase< N >::reduceTo ( size_t... axes ) const

inline

Reduce operation that produces a lower-dimensional DbnBase keeping only the specified axes in the new DbnBase.

Definition at line 383 of file Dbn.h.

                                                              {
      if constexpr (N == sizeof...(axes)) { return *this; } // keep all axes
      else {
        // only select the axis moments to keep (0 is sumW, 1...N are the axis moments)
        std::array<double, sizeof...(axes)+1> newSumW = { _sumW[0], _sumW[axes+1]... };
        std::array<double, sizeof...(axes)+1> newSumW2 = { _sumW2[0], _sumW2[axes+1]... };
        if constexpr (sizeof...(axes) < 2) {
          return DbnBase<sizeof...(axes)>(_numEntries, newSumW, newSumW2);
        }
        else {
          constexpr auto newDim = sizeof...(axes);
          std::array<double, newDim*(newDim-1)/2> newSumWcross;
          unsigned int idx = 0;
          for (unsigned int i : {axes...}) {
            for (unsigned int j : {axes...}) {
              if (i < j) { newSumWcross.at(idx) = crossTerm(i, j); ++idx; }
            }
          }
          return DbnBase<sizeof...(axes)>(_numEntries, newSumW, newSumW2, newSumWcross);
        }
      }
    }

References YODA::DbnBase< N >::crossTerm().

Referenced by YODA::DbnBase< N >::reduce(), and YODA::DbnBase< N >::reduceTo().

◆ reduceTo() [2/2]

template<size_t N>

template<size_t... Is>

DbnBase< sizeof...(Is)> YODA::DbnBase< N >::reduceTo ( std::index_sequence< Is... > ) const

inline

Same as above but using an std::integer_sequence.

Definition at line 408 of file Dbn.h.

                                                                    {
      return reduceTo(Is...);
    }

References YODA::DbnBase< N >::reduceTo().

◆ relErrW()

template<size_t N>

double YODA::DbnBase< N >::relErrW ( ) const

The relative error on sumW.

Definition at line 511 of file Dbn.h.

                                   {
    if (effNumEntries() == 0) {
      return std::numeric_limits<double>::quiet_NaN();
    }
    return errW()/sumW(0);
  }

References YODA::effNumEntries().

◆ relStdErr()

template<size_t N>

double YODA::DbnBase< N >::relStdErr ( const size_t i ) const

Relative weighted standard error on the mean, $\sim \sigma/\sqrt{N-1}$ , of distribution.

Definition at line 537 of file Dbn.h.

                                                   {
    if (effNumEntries() == 0) {
      return std::numeric_limits<double>::quiet_NaN();
    }
    return stdErr(i) / mean(i);
  }

References YODA::effNumEntries(), YODA::mean(), and YODA::stdErr().

◆ reset()

template<size_t N>

void YODA::DbnBase< N >::reset ( )

inline

Reset the internal counters.

Definition at line 232 of file Dbn.h.

                 {
      _numEntries= 0;
      _sumW.fill(0);
      _sumW2.fill(0);
      _sumWcross.fill(0);
    }

Referenced by YODA::DbnBase< N >::DbnBase().

◆ RMS()

template<size_t N>

double YODA::DbnBase< N >::RMS ( const size_t i ) const

Weighted RMS, $\sqrt{ \sum{w x^2}/\sum{w} }$ , of distribution.

Definition at line 546 of file Dbn.h.

                                             {
    return YODA::RMS(sumW2(i), sumW(0), sumW2());
  }

References YODA::RMS().

Referenced by YODA::DbnStorage< DbnN, AxisT >::rms(), and YODA::DbnBase< N >::toString().

◆ scale()

template<size_t N>

void YODA::DbnBase< N >::scale	(	const size_t	dim,
		const double	factor
	)

inline

Definition at line 254 of file Dbn.h.

                                                      {
      if (dim >= N)
        throw RangeError("Dimension index should be less than "+std::to_string(N));
      _sumW.at(dim+1) *= factor;
      _sumW2.at(dim+1) *= sqr(factor);
      size_t idx = 0;
      for (size_t i = 0; i < (N-1); ++i) {
        for (size_t j = i+1; j < N; ++j) {
          if (i == dim || j == dim) {
            _sumWcross.at(idx++) *= factor;
          }
        }
      } // end of double loop
    }

References YODA::DbnBase< N >::dim(), and YODA::sqr().

◆ scaleW()

template<size_t N>

void YODA::DbnBase< N >::scaleW ( const double scalefactor )

inline

Rescale as if all fill weights had been different by factor scalefactor.

Definition at line 241 of file Dbn.h.

                                          {
      _sumW.at(0) *= scalefactor;
      _sumW2.at(0) *= sqr(scalefactor);
      for (size_t i = 0; i< N; ++i) {
        // first- and second-order moments
        _sumW.at(i+1) *= scalefactor;
        _sumW2.at(i+1) *= scalefactor;
      }
      for (size_t i = 0; i < _sumWcross.size(); ++i) {
        _sumWcross.at(i) *= scalefactor;
      }
    }

References YODA::sqr().

◆ set() [1/4]

template<size_t N>

void YODA::DbnBase< N >::set ( const DbnBase< N > & other )

inline

Set a sample with other.

Definition at line 222 of file Dbn.h.

                                      {
      if (this != &other)  *this = other;
    }

◆ set() [2/4]

template<size_t N>

void YODA::DbnBase< N >::set	(	const double	numEntries,
		const std::array< double, N+1 > &	sumW,
		const std::array< double, N+1 > &	sumW2,
		const std::array< double, N *(N-1)/2 > &	sumWcross
	)

inline

Set a sample with array-based number of entries numEntries, sum of weights sumW (and corresponding moments), sum of squared weights sumW2 (and corresponding moments).

Definition at line 197 of file Dbn.h.

                                                                                   {
      _numEntries = numEntries;
      _sumW = sumW;
      _sumW2 = sumW2;
      _sumWcross = sumWcross;
    }

References YODA::DbnBase< N >::numEntries(), YODA::DbnBase< N >::sumW(), and YODA::DbnBase< N >::sumW2().

Referenced by YODA::Dbn< 0 >::set().

◆ set() [3/4]

template<size_t N>

void YODA::DbnBase< N >::set	(	const double	numEntries,
		const std::vector< double > &	sumW,
		const std::vector< double > &	sumW2,
		const std::vector< double > &	sumWcross = `{}`
	)

inline

Set a sample with vector-based number of entries numEntries, sum of weights sumW (and corresponding moments), sum of squared weights sumW2 (and corresponding moments).

Definition at line 209 of file Dbn.h.

                                                                           {}) {
      if (!(sumW.size() <= (N + 1) || sumW2.size() <= (N + 1) || sumWcross.size() <= (N*(N-1)/2)))
        throw UserError("Value's dimension doesn't match distribution's dimension.");
      _numEntries = numEntries;
      std::copy_n(std::make_move_iterator(sumW.begin()),      sumW.size(),      _sumW.begin());
      std::copy_n(std::make_move_iterator(sumW2.begin()),     sumW2.size(),     _sumW2.begin());
      std::copy_n(std::make_move_iterator(sumWcross.begin()), sumWcross.size(), _sumWcross.begin());
    }

◆ set() [4/4]

template<size_t N>

void YODA::DbnBase< N >::set ( DbnBase< N > && other )

inline

Set a sample with other.

Definition at line 227 of file Dbn.h.

                                 {
      if (this != &other)  *this = std::move(other);
    }

◆ stdDev()

template<size_t N>

double YODA::DbnBase< N >::stdDev ( const size_t i ) const

inline

Weighted standard deviation, $\sigma$ , of distribution.

Definition at line 291 of file Dbn.h.

291{ return std::sqrt(variance(i)); }

YODA::DbnBase::variance

double variance(const size_t i) const

Weighted variance, , of distribution.

Definition Dbn.h:525

References YODA::DbnBase< N >::variance().

◆ stdErr()

template<size_t N>

double YODA::DbnBase< N >::stdErr ( const size_t i ) const

Weighted standard error on the mean, $\sim \sigma/\sqrt{N-1}$ , of distribution.

Definition at line 531 of file Dbn.h.

                                                {
    return YODA::stdErr(sumW(i), sumW(0), sumW2(i), sumW2(0));
  }

References YODA::stdErr().

Referenced by YODA::DbnStorage< DbnN, AxisT >::stdErr().

◆ sumW() [1/2]

template<size_t N>

double YODA::DbnBase< N >::sumW ( ) const

inline

The sum of weights.

Definition at line 320 of file Dbn.h.

                        {
      return _sumW.at(0);
    }

Referenced by YODA::Dbn< 0 >::Dbn(), YODA::Dbn< 1 >::Dbn(), YODA::Dbn< 2 >::Dbn(), YODA::Dbn< 3 >::Dbn(), YODA::Dbn< 0 >::set(), YODA::DbnBase< N >::set(), and YODA::DbnBase< N >::toString().

◆ sumW() [2/2]

template<size_t N>

double YODA::DbnBase< N >::sumW ( const size_t i ) const

inline

The sum of x*weight.

Definition at line 330 of file Dbn.h.

                                      {
      return _sumW.at(i);
    }

◆ sumW2() [1/2]

template<size_t N>

double YODA::DbnBase< N >::sumW2 ( ) const

inline

The sum of weights squared.

Definition at line 325 of file Dbn.h.

                         {
      return _sumW2.at(0);
    }

Referenced by YODA::Dbn< 0 >::set(), and YODA::DbnBase< N >::set().

◆ sumW2() [2/2]

template<size_t N>

double YODA::DbnBase< N >::sumW2 ( const size_t i ) const

inline

The sum of x^2*weight.

Definition at line 335 of file Dbn.h.

                                       {
      return _sumW2.at(i);
    }

◆ toString()

template<size_t N>

std::string YODA::DbnBase< N >::toString ( ) const

inline

String representation of the DbnBase for debugging.

Definition at line 365 of file Dbn.h.

                               {
      std::string res ="";
      res += ("numEntries="+ std::to_string(_numEntries))  ;
      if (sumW()) {
        res += (", Mean="+ std::to_string(mean(0)))  ;
        res += (", RMS="+ std::to_string(RMS(0)))  ;
      }
      return res;
    }

References YODA::DbnBase< N >::mean(), YODA::DbnBase< N >::RMS(), and YODA::DbnBase< N >::sumW().

◆ variance()

template<size_t N>

double YODA::DbnBase< N >::variance ( const size_t i ) const

Weighted variance, $\sigma^2$ , of distribution.

Definition at line 525 of file Dbn.h.

                                                  {
    return YODA::variance(sumW(i), sumW(0), sumW2(i), sumW2(0));
  }

References YODA::variance().

Referenced by YODA::DbnBase< N >::stdDev(), and YODA::DbnStorage< DbnN, AxisT >::variance().

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

include/YODA/Dbn.h

Public Types

Public Member Functions

Detailed Description

Member Typedef Documentation

◆ BaseT

◆ DataSize

◆ FillDim

Constructor & Destructor Documentation

◆ DbnBase() [1/5]

◆ DbnBase() [2/5]

◆ DbnBase() [3/5]

◆ DbnBase() [4/5]

◆ DbnBase() [5/5]

Member Function Documentation

◆ crossTerm()

◆ dim()

◆ effNumEntries()

◆ errW()

◆ fill() [1/2]

◆ fill() [2/2]

◆ mean()

◆ numEntries()

◆ operator+=() [1/2]

◆ operator+=() [2/2]

◆ operator-=() [1/2]

◆ operator-=() [2/2]

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ reduce()

◆ reduceTo() [1/2]

◆ reduceTo() [2/2]

◆ relErrW()

◆ relStdErr()

◆ reset()

◆ RMS()

◆ scale()

◆ scaleW()

◆ set() [1/4]

◆ set() [2/4]

◆ set() [3/4]

◆ set() [4/4]

◆ stdDev()

◆ stdErr()

◆ sumW() [1/2]

◆ sumW() [2/2]

◆ sumW2() [1/2]

◆ sumW2() [2/2]

◆ toString()

◆ variance()