Detailed Description

A namespace of pseudo-random numbers genrators of diferent distributions.

The central class in this namespace is mrpt::random::CRandomGenerator

Classes
class	CRandomGenerator
	A thred-safe pseudo random number generator, based on an internal MT19937 randomness generator. More...

Functions
ptrdiff_t	random_generator_for_STL (ptrdiff_t i)
	A random number generator for usage in STL algorithms expecting a function like this (eg, random_shuffle): More...

template<class MAT >
void	matrixRandomUni (MAT &matrix, const double unif_min=0, const double unif_max=1)
	Fills the given matrix with independent, uniformly distributed samples. More...

template<class T >
void	vectorRandomUni (std::vector< T > &v_out, const T &unif_min=0, const T &unif_max=1)
	Fills the given matrix with independent, uniformly distributed samples. More...

template<class MAT >
void	matrixRandomNormal (MAT &matrix, const double mean=0, const double std=1)
	Fills the given matrix with independent, normally distributed samples. More...

template<class T >
void	vectorRandomNormal (std::vector< T > &v_out, const T &mean=0, const T &std=1)
	Generates a random vector with independent, normally distributed samples. More...

void	Randomize (const uint32_t seed)
	Randomize the generators. More...

void	Randomize ()

template<class T >
void	randomPermutation (const std::vector< T > &in_vector, std::vector< T > &out_result)
	Returns a random permutation of a vector: all the elements of the input vector are in the output but at random positions. More...

template<typename T >
void	randomNormalMultiDimensional (const CMatrixTemplateNumeric< T > &cov, std::vector< T > &out_result)
	Generate multidimensional random samples according to a given covariance matrix. More...

template<typename T >
void	randomNormalMultiDimensionalMany (const CMatrixTemplateNumeric< T > &cov, size_t desiredSamples, std::vector< std::vector< T > > &ret, std::vector< T > *samplesLikelihoods=NULL)
	Generate a given number of multidimensional random samples according to a given covariance matrix. More...

template<typename T , size_t N>
void	randomNormalMultiDimensionalMany (const CMatrixFixedNumeric< T, N, N > &cov, size_t desiredSamples, std::vector< std::vector< T > > &ret)
	Generate multidimensional random samples according to a given covariance matrix. More...

template<typename T , size_t N>
void	randomNormalMultiDimensional (const CMatrixFixedNumeric< T, N, N > &cov, std::vector< T > &out_result)
	Generate multidimensional random samples according to a given covariance matrix. More...

Variables
BASE_IMPEXP CRandomGenerator	randomGenerator
	A static instance of a CRandomGenerator class, for use in single-thread applications. More...

Function Documentation

◆ matrixRandomNormal()

template<class MAT >

void mrpt::random::matrixRandomNormal	(	MAT &	matrix,
		const double	mean = `0`,
		const double	std = `1`
	)

Fills the given matrix with independent, normally distributed samples.

Matrix classes can be CMatrixTemplateNumeric or CMatrixFixedNumeric

See also: matrixRandomUni

Definition at line 347 of file RandomGenerators.h.

References mrpt::random::CRandomGenerator::drawGaussian1D_normalized(), mean(), and randomGenerator.

◆ matrixRandomUni()

template<class MAT >

void mrpt::random::matrixRandomUni	(	MAT &	matrix,
		const double	unif_min = `0`,
		const double	unif_max = `1`
	)

Fills the given matrix with independent, uniformly distributed samples.

Matrix classes can be CMatrixTemplateNumeric or CMatrixFixedNumeric

See also: matrixRandomNormal

Definition at line 318 of file RandomGenerators.h.

References mrpt::random::CRandomGenerator::drawUniform(), and randomGenerator.

◆ random_generator_for_STL()

ptrdiff_t mrpt::random::random_generator_for_STL ( ptrdiff_t i )

inline

A random number generator for usage in STL algorithms expecting a function like this (eg, random_shuffle):

Definition at line 308 of file RandomGenerators.h.

References mrpt::random::CRandomGenerator::drawUniform32bit(), and randomGenerator.

Referenced by mrpt::slam::PF_implementation< CPose2D, CMonteCarloLocalization2D >::PF_SLAM_implementation_pfAuxiliaryPFStandardAndOptimal().

◆ Randomize() [1/2]

void mrpt::random::Randomize ( const uint32_t seed )

inline

Randomize the generators.

A seed can be providen, or a current-time based seed can be used (default)

Definition at line 374 of file RandomGenerators.h.

References randomGenerator, and mrpt::random::CRandomGenerator::randomize().

◆ Randomize() [2/2]

void mrpt::random::Randomize ( )

inline

Definition at line 377 of file RandomGenerators.h.

References randomGenerator, and mrpt::random::CRandomGenerator::randomize().

◆ randomNormalMultiDimensional() [1/2]

template<typename T >

void mrpt::random::randomNormalMultiDimensional	(	const CMatrixTemplateNumeric< T > &	cov,
		std::vector< T > &	out_result
	)

Generate multidimensional random samples according to a given covariance matrix.

Exceptions

std::exception On invalid covariance matrix

See also: randomNormalMultiDimensionalMany

Definition at line 397 of file RandomGenerators.h.

References mrpt::math::cov(), mrpt::random::CRandomGenerator::drawGaussianMultivariate(), and randomGenerator.

◆ randomNormalMultiDimensional() [2/2]

template<typename T , size_t N>

void mrpt::random::randomNormalMultiDimensional	(	const CMatrixFixedNumeric< T, N, N > &	cov,
		std::vector< T > &	out_result
	)

Generate multidimensional random samples according to a given covariance matrix.

Exceptions

std::exception On invalid covariance matrix

See also: randomNormalMultiDimensionalMany

Definition at line 442 of file RandomGenerators.h.

References mrpt::math::cov(), mrpt::random::CRandomGenerator::drawGaussianMultivariate(), and randomGenerator.

◆ randomNormalMultiDimensionalMany() [1/2]

template<typename T >

void mrpt::random::randomNormalMultiDimensionalMany	(	const CMatrixTemplateNumeric< T > &	cov,
		size_t	desiredSamples,
		std::vector< std::vector< T > > &	ret,
		std::vector< T > *	samplesLikelihoods = `NULL`
	)

Generate a given number of multidimensional random samples according to a given covariance matrix.

Parameters

cov	The covariance matrix where to draw the samples from.
desiredSamples	The number of samples to generate.
samplesLikelihoods	If desired, set to a valid pointer to a vector, where it will be stored the likelihoods of having obtained each sample: the product of the gaussian-pdf for each independent variable.
ret	The output list of samples

Exceptions

std::exception On invalid covariance matrix

See also: randomNormalMultiDimensional

Definition at line 415 of file RandomGenerators.h.

References mrpt::math::cov(), mrpt::random::CRandomGenerator::drawGaussianMultivariateMany(), and randomGenerator.

◆ randomNormalMultiDimensionalMany() [2/2]

template<typename T , size_t N>

void mrpt::random::randomNormalMultiDimensionalMany	(	const CMatrixFixedNumeric< T, N, N > &	cov,
		size_t	desiredSamples,
		std::vector< std::vector< T > > &	ret
	)