The ProbabilityDistribution class
Abstract class for all probability distributions. More...

#include <distribution.hpp>

Inheritance diagram for randlib::ProbabilityDistribution< T >:

[legend]

Public Types
using	value_type = T

Public Member Functions
virtual	~ProbabilityDistribution ()=default

virtual std::string	Name () const =0

virtual T	MinValue () const =0

virtual T	MaxValue () const =0

virtual double	F (const T &x) const =0

void	CumulativeDistributionFunction (std::span< const T > x, std::span< double > y) const

virtual double	S (const T &x) const

void	SurvivalFunction (std::span< const T > x, std::span< double > y) const

template<std::uniform_random_bit_generator G>
T	operator() (G &g) const
	Draws a variate with the given engine through the virtual interface.

T	Variate () const
	Uses the engine of this object, so it is not thread-safe for one object; use operator() with one engine per thread instead.

void	Sample (std::span< T > outputData) const
	Fills the output with variates drawn with the engine of this object.

template<std::uniform_random_bit_generator G>
void	Sample (G &g, std::span< T > outputData) const
	Fills the output with variates drawn with the given engine.

void	Reseed (std::uint64_t seed)

Protected Member Functions
std::string	toStringWithPrecision (const double a_value, const int n=6) const

	ProbabilityDistribution ()=default

DefaultEngine &	engine () const

virtual T	variate (detail::EngineRef g) const =0
	Every concrete distribution implements this by calling its templated operator()

virtual void	sample (detail::EngineRef g, std::span< T > outputData) const
	Fills the output with variate(g); distributions with a faster bulk algorithm override it.

fit_error	fitError (FitErrorCode code, const std::string &explanation) const

Static Protected Attributes
static constexpr size_t	MAX_ITER_REJECTION = detail::MAX_ITER_REJECTION
	MAX_ITER_REJECTION upper boundary for maximum amount of iterations in rejection methods one thousand should be enough to be sure there is a bug (or rejection method is too slow to be used)

static constexpr char	POSITIVITY_VIOLATION [] = "All elements should be positive"

static constexpr char	NON_NEGATIVITY_VIOLATION [] = "All elements should be non-negative"

static constexpr char	UPPER_LIMIT_VIOLATION [] = "No element should be greater than "

static constexpr char	LOWER_LIMIT_VIOLATION [] = "No element should be smaller than "

Detailed Description

template<typename T>
class randlib::ProbabilityDistribution< T >

The ProbabilityDistribution class
Abstract class for all probability distributions.

Member Typedef Documentation

◆ value_type

template<typename T >

using randlib::ProbabilityDistribution< T >::value_type = T

Constructor & Destructor Documentation

◆ ProbabilityDistribution()

template<typename T >

randlib::ProbabilityDistribution< T >::ProbabilityDistribution ( )

protecteddefault

◆ ~ProbabilityDistribution()

template<typename T >

virtual randlib::ProbabilityDistribution< T >::~ProbabilityDistribution ( )

virtualdefault

Member Function Documentation

◆ CumulativeDistributionFunction()

template<typename T >

void randlib::ProbabilityDistribution< T >::CumulativeDistributionFunction	(	std::span< const T >	x,
		std::span< double >	y
	)		const

Parameters

x	input vector
y	output vector: y = P(X ≤ x)

◆ engine()

template<typename T >

DefaultEngine & randlib::ProbabilityDistribution< T >::engine ( ) const

inlineprotected

Returns: the engine of this object, seeded with random_seed() on first use unless Reseed was called

◆ F()

template<typename T >

virtual double randlib::ProbabilityDistribution< T >::F ( const T & x ) const

pure virtual

Parameters

x

Returns: P(X ≤ x)

◆ fitError()

template<typename T >

fit_error randlib::ProbabilityDistribution< T >::fitError	(	FitErrorCode	code,
		const std::string &	explanation
	)		const

protected

Parameters

code	reason of the failure
explanation	details

Returns: fit_error whose message names this distribution, the reason and the details

◆ MaxValue()

template<typename T >

virtual T randlib::ProbabilityDistribution< T >::MaxValue ( ) const

pure virtual

Returns: maximum possible value that can be achieved by random variable

◆ MinValue()

template<typename T >

virtual T randlib::ProbabilityDistribution< T >::MinValue ( ) const

pure virtual

Returns: minimum possible value that can be achieved by random variable

◆ Name()

template<typename T >

virtual std::string randlib::ProbabilityDistribution< T >::Name ( ) const

pure virtual

Returns: title of distribution, for instance "Normal(0, 1)"

◆ operator()()

template<typename T >

template<std::uniform_random_bit_generator G>

T randlib::ProbabilityDistribution< T >::operator() ( G & g ) const

inline

Draws a variate with the given engine through the virtual interface.

Concrete distribution classes hide it with a fully templated version, which is faster.

Parameters

g	any uniform random bit generator, such as std::mt19937 or DefaultEngine

Returns: random variable

◆ Reseed()

template<typename T >

void randlib::ProbabilityDistribution< T >::Reseed ( std::uint64_t seed )

inline

Parameters

seed	seed of the engine of this object

◆ S()

template<typename T >

double randlib::ProbabilityDistribution< T >::S ( const T & x ) const

virtual

Parameters

x

Returns: P(X > x)

◆ sample()

template<typename T >

virtual void randlib::ProbabilityDistribution< T >::sample	(	detail::EngineRef	g,
		std::span< T >	outputData
	)		const

inlineprotectedvirtual

Fills the output with variate(g); distributions with a faster bulk algorithm override it.

Parameters

g	engine
outputData

◆ Sample() [1/2]

template<typename T >

template<std::uniform_random_bit_generator G>

void randlib::ProbabilityDistribution< T >::Sample	(	G &	g,
		std::span< T >	outputData
	)		const

inline

Fills the output with variates drawn with the given engine.

Parameters

g	any uniform random bit generator
outputData

◆ Sample() [2/2]

template<typename T >

void randlib::ProbabilityDistribution< T >::Sample ( std::span< T > outputData ) const

inline

Fills the output with variates drawn with the engine of this object.

Parameters

outputData

◆ SurvivalFunction()

template<typename T >

void randlib::ProbabilityDistribution< T >::SurvivalFunction	(	std::span< const T >	x,
		std::span< double >	y
	)		const

Parameters

x	input vector
y	output vector: y = P(X > x)

◆ toStringWithPrecision()

template<typename T >

std::string randlib::ProbabilityDistribution< T >::toStringWithPrecision	(	const double	a_value,
		const int	n = `6`
	)		const

protected

◆ Variate()

template<typename T >

T randlib::ProbabilityDistribution< T >::Variate ( ) const

inline

Uses the engine of this object, so it is not thread-safe for one object; use operator() with one engine per thread instead.

Returns: random variable

◆ variate()

template<typename T >

virtual T randlib::ProbabilityDistribution< T >::variate ( detail::EngineRef g ) const

protectedpure virtual

Every concrete distribution implements this by calling its templated operator()

Parameters

g engine

Returns: random variable

Member Data Documentation

◆ LOWER_LIMIT_VIOLATION

template<typename T >

constexpr char randlib::ProbabilityDistribution< T >::LOWER_LIMIT_VIOLATION = "No element should be smaller than "

staticconstexprprotected

◆ MAX_ITER_REJECTION

template<typename T >

constexpr size_t randlib::ProbabilityDistribution< T >::MAX_ITER_REJECTION = detail::MAX_ITER_REJECTION

staticconstexprprotected

MAX_ITER_REJECTION upper boundary for maximum amount of iterations in rejection methods one thousand should be enough to be sure there is a bug (or rejection method is too slow to be used)

◆ NON_NEGATIVITY_VIOLATION

template<typename T >

constexpr char randlib::ProbabilityDistribution< T >::NON_NEGATIVITY_VIOLATION = "All elements should be non-negative"

staticconstexprprotected

◆ POSITIVITY_VIOLATION

template<typename T >

constexpr char randlib::ProbabilityDistribution< T >::POSITIVITY_VIOLATION = "All elements should be positive"

staticconstexprprotected

◆ UPPER_LIMIT_VIOLATION

template<typename T >

constexpr char randlib::ProbabilityDistribution< T >::UPPER_LIMIT_VIOLATION = "No element should be greater than "

staticconstexprprotected

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

distribution.hpp

Public Types

Public Member Functions

Protected Member Functions

Static Protected Attributes

Detailed Description

Member Typedef Documentation

◆ value_type

Constructor & Destructor Documentation

◆ ProbabilityDistribution()

◆ ~ProbabilityDistribution()

Member Function Documentation

◆ CumulativeDistributionFunction()

◆ engine()

◆ F()

◆ fitError()

◆ MaxValue()

◆ MinValue()

◆ Name()

◆ operator()()

◆ Reseed()

◆ S()

◆ sample()

◆ Sample() [1/2]

◆ Sample() [2/2]

◆ SurvivalFunction()

◆ toStringWithPrecision()

◆ Variate()

◆ variate()

Member Data Documentation

◆ LOWER_LIMIT_VIOLATION

◆ MAX_ITER_REJECTION

◆ NON_NEGATIVITY_VIOLATION

◆ POSITIVITY_VIOLATION

◆ UPPER_LIMIT_VIOLATION