User-facing Dbn class inheriting from DbnBase. More...

#include <Dbn.h>

Inheritance diagram for YODA::Dbn< N >:

Public Types
using	BaseT = DbnBase< N >

using	BaseT = DbnBase< N >

Public Types inherited from YODA::DbnBase< N >
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
DbnBase &	operator= (const DbnBase &)=default

DbnBase &	operator= (DbnBase &&)=default

Public Member Functions inherited from YODA::DbnBase< N >
	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

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)

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.

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

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

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.

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.