mrpt::random Namespace Reference

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 mrpt::math::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 mrpt::math::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 , typename MATRIXLIKE >
void	randomNormalMultiDimensionalMany (const MATRIXLIKE &cov, size_t desiredSamples, std::vector< std::vector< T > > &ret)
	Generate multidimensional random samples according to a given covariance matrix. More...
template<typename T , typename MATRIXLIKE >
void	randomNormalMultiDimensional (const MATRIXLIKE &cov, std::vector< T > &out_result)
	Generate multidimensional random samples according to a given covariance matrix. More...
double	normalizedGaussian (double *likelihood)
double	RandomNormal (double mean, double std)
uint32_t	RandomUniInt ()
double	RandomUni (const double min, const double max)

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 mrpt::math::CMatrixTemplateNumeric or mrpt::math::CMatrixFixedNumeric

See also

matrixRandomUni

Definition at line 345 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 mrpt::math::CMatrixTemplateNumeric or mrpt::math::CMatrixFixedNumeric

See also

matrixRandomNormal

Definition at line 316 of file RandomGenerators.h.

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

normalizedGaussian()

double mrpt::random::normalizedGaussian

(

double *

likelihood

)

Definition at line 255 of file RandomGenerator.cpp.

References mrpt::random::CRandomGenerator::drawGaussian1D_normalized(), 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 306 of file RandomGenerators.h.

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

Referenced by mrpt::slam::PF_implementation< mrpt::poses::CPose3D, CMonteCarloLocalization3D >::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 372 of file RandomGenerators.h.

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

Randomize() [2/2]

void mrpt::random::Randomize ( )

inline

Definition at line 375 of file RandomGenerators.h.

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

RandomNormal()

double mrpt::random::RandomNormal	(	double	mean,
		double	std
	)

Definition at line 259 of file RandomGenerator.cpp.

References mrpt::random::CRandomGenerator::drawGaussian1D(), mean(), and randomGenerator.

randomNormalMultiDimensional() [1/2]

template<typename T >

void mrpt::random::randomNormalMultiDimensional	(	const mrpt::math::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 395 of file RandomGenerators.h.

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

randomNormalMultiDimensional() [2/2]

template<typename T , typename MATRIXLIKE >

void mrpt::random::randomNormalMultiDimensional	(	const MATRIXLIKE &	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 440 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 mrpt::math::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 413 of file RandomGenerators.h.

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

randomNormalMultiDimensionalMany() [2/2]

template<typename T , typename MATRIXLIKE >

void mrpt::random::randomNormalMultiDimensionalMany	(	const MATRIXLIKE &	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 427 of file RandomGenerators.h.

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

randomPermutation()

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 382 of file RandomGenerators.h.

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

RandomUni()

double mrpt::random::RandomUni	(	const double	min,
		const double	max
	)

Definition at line 267 of file RandomGenerator.cpp.

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

RandomUniInt()

uint32_t mrpt::random::RandomUniInt

(

)

Definition at line 263 of file RandomGenerator.cpp.

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

vectorRandomNormal()

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 359 of file RandomGenerators.h.

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

vectorRandomUni()

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 330 of file RandomGenerators.h.

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

Variable Documentation

randomGenerator

CRandomGenerator mrpt::random::randomGenerator

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

Definition at line 23 of file RandomGenerator.cpp.

Referenced by EdgeAdder< mrpt::poses::CPosePDFGaussianInf >::add(), EdgeAdder< mrpt::poses::CPose3DPDFGaussianInf >::add(), mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), atan2_lut_test(), mrpt::hmtslam::CHierarchicalMapMHPartition::computeCoordinatesTransformationBetweenNodes(), mrpt::obs::CActionRobotMovement3D::computeFromOdometry_model6DOF(), mrpt::obs::CActionRobotMovement2D::computeFromOdometry_modelThrun(), mrpt::bayes::CParticleFilterCapable::computeResampling(), mrpt::poses::CPosePDFParticles::copyFrom(), GraphSlamLevMarqTest< my_graph_t >::create_ring_path(), mrpt::opengl::CPolyhedron::CreateRandomPolyhedron(), mrpt::poses::CPoseRandomSampler::do_sample_2D(), mrpt::poses::CPoseRandomSampler::do_sample_3D(), do_test_init_random(), mrpt::poses::CPose3DQuatPDFGaussian::drawManySamples(), mrpt::poses::CPose3DQuatPDFGaussianInf::drawManySamples(), mrpt::poses::CPose3DPDFGaussianInf::drawManySamples(), mrpt::poses::CPosePDFGaussianInf::drawManySamples(), mrpt::poses::CPosePDFGaussian::drawManySamples(), mrpt::poses::CPose3DPDFGaussian::drawManySamples(), mrpt::poses::CPoint2DPDFGaussian::drawSingleSample(), mrpt::poses::CPose3DQuatPDFGaussian::drawSingleSample(), mrpt::poses::CPose3DQuatPDFGaussianInf::drawSingleSample(), mrpt::poses::CPointPDFGaussian::drawSingleSample(), mrpt::poses::CPose3DPDFGaussianInf::drawSingleSample(), mrpt::poses::CPosePDFGaussianInf::drawSingleSample(), mrpt::poses::CPosePDFParticles::drawSingleSample(), mrpt::poses::CPosePDFGaussian::drawSingleSample(), mrpt::poses::CPose3DPDFGaussian::drawSingleSample(), mrpt::poses::CPointPDFSOG::drawSingleSample(), mrpt::obs::CActionRobotMovement2D::drawSingleSample_modelThrun(), mrpt::math::RANSAC_Template< NUMTYPE >::execute(), mrpt::bayes::CParticleFilterCapable::fastDrawSample(), mrpt::obs::CActionRobotMovement2D::fastDrawSingleSample_modelGaussian(), PosePDFGaussTests::generateRandomPose2DPDF(), Pose3DPDFGaussTests::generateRandomPose3DPDF(), Pose3DQuatPDFGaussTests::generateRandomPose3DPDF(), generateRandomSparseMatrix(), mrpt::maps::CBeaconMap::internal_insertObservation(), matrixRandomNormal(), matrixRandomUni(), my_CriticalSections_Multi(), normalizedGaussian(), mrpt::slam::PF_implementation< mrpt::poses::CPose3D, CMonteCarloLocalization3D >::PF_SLAM_aux_perform_one_rejection_sampling_step(), mrpt::slam::PF_implementation< mrpt::poses::CPose3D, CMonteCarloLocalization3D >::PF_SLAM_implementation_pfAuxiliaryPFStandardAndOptimal(), mrpt::hmtslam::CLSLAM_RBPF_2DLASER::prediction_and_update_pfAuxiliaryPFOptimal(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), random_generator_for_STL(), Randomize(), RandomNormal(), randomNormalMultiDimensional(), randomNormalMultiDimensionalMany(), randomPermutation(), RandomUni(), RandomUniInt(), ransac_data_assoc_run(), mrpt::bayes::CRejectionSamplingCapable< mrpt::poses::CPose2D >::rejectionSampling(), mrpt::poses::CPosePDFParticles::resetAroundSetOfPoses(), mrpt::poses::CPosePDFParticles::resetUniform(), mrpt::slam::CMonteCarloLocalization2D::resetUniformFreeSpace(), mrpt::slam::CRejectionSamplingRangeOnlyLocalization::RS_drawFromProposal(), run_test_pf_localization(), mrpt::maps::COccupancyGridMap2D::saveAsBitmapTwoMapsWithCorrespondences(), mrpt::tfest::se2_l2_robust(), mrpt::tfest::se3_l2_robust(), sem_thread_example(), mrpt::maps::CBeaconMap::simulateBeaconReadings(), mrpt::maps::CLandmarksMap::simulateBeaconReadings(), mrpt::kinematics::CVehicleSimulVirtualBase::simulateOneTimeStep(), mrpt::maps::CLandmarksMap::simulateRangeBearingReadings(), mrpt::maps::COccupancyGridMap2D::simulateScanRay(), mrpt::nav::PlannerRRT_SE2_TPS::solve(), TEST(), TEST_F(), thread_example(), mrpt::hmtslam::CHMTSLAM::thread_LSLAM(), mrpt::hmtslam::CHMTSLAM::thread_TBI(), mrpt::math::transform_gaussian_montecarlo(), vectorRandomNormal(), and vectorRandomUni().