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):

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.

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.

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

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.

void	Randomize (const uint32_t seed)
	Randomize the generators.

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.

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

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.

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.

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.

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

Function Documentation

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 349 of file RandomGenerators.h.

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

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 320 of file RandomGenerators.h.

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

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 310 of file RandomGenerators.h.

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

Referenced by mrpt::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_implementation_pfAuxiliaryPFStandardAndOptimal().

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 376 of file RandomGenerators.h.

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

void mrpt::random::Randomize ( )

inline

Definition at line 379 of file RandomGenerators.h.

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

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 399 of file RandomGenerators.h.

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

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 444 of file RandomGenerators.h.

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

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 417 of file RandomGenerators.h.

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

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
	)

Generate multidimensional random samples according to a given covariance matrix.

Exceptions

std::exception On invalid covariance matrix

See Also: randomNormalMultiDimensional

Definition at line 431 of file RandomGenerators.h.

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

template<class T >

void mrpt::random::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.

Definition at line 386 of file RandomGenerators.h.

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

template<class T >

void mrpt::random::vectorRandomNormal	(	std::vector< T > &	v_out,
		const T &	mean = `0`,
		const T &	std = `1`
	)

Generates a random vector with independent, normally distributed samples.

See Also: matrixRandomUni

Definition at line 363 of file RandomGenerators.h.

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

template<class T >

void mrpt::random::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.

See Also: vectorRandomNormal

Definition at line 334 of file RandomGenerators.h.

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

Variable Documentation

BASE_IMPEXP CRandomGenerator mrpt::random::randomGenerator

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

Referenced by matrixRandomNormal(), matrixRandomUni(), mrpt::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_aux_perform_one_rejection_sampling_step(), mrpt::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_implementation_pfAuxiliaryPFStandardAndOptimal(), random_generator_for_STL(), Randomize(), randomNormalMultiDimensional(), randomNormalMultiDimensionalMany(), randomPermutation(), mrpt::bayes::CRejectionSamplingCapable< poses::CPose2D >::rejectionSampling(), mrpt::math::transform_gaussian_montecarlo(), vectorRandomNormal(), and vectorRandomUni().

Detailed Description

Classes

Functions

Variables

Function Documentation

Variable Documentation