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mrpt::random::CRandomGenerator Class Reference

Detailed Description

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

The base algorithm for randomness is platform-independent. See http://en.wikipedia.org/wiki/Mersenne_twister

For real thread-safety, each thread must create and use its own instance of this class.

Single-thread programs can use the static object mrpt::random::randomGenerator

Definition at line 32 of file RandomGenerators.h.

#include <mrpt/random/RandomGenerators.h>

Classes

struct  TMT19937_data
 Data used internally by the MT19937 PRNG algorithm. More...
 

Public Member Functions

Initialization
 CRandomGenerator ()
 Default constructor: initialize random seed based on current time. More...
 
 CRandomGenerator (const uint32_t seed)
 Constructor for providing a custom random seed to initialize the PRNG. More...
 
void randomize (const uint32_t seed)
 Initialize the PRNG from the given random seed. More...
 
void randomize ()
 Randomize the generators, based on current time. More...
 
Uniform pdf
uint32_t drawUniform32bit ()
 Generate a uniformly distributed pseudo-random number using the MT19937 algorithm, in the whole range of 32-bit integers. More...
 
uint64_t drawUniform64bit ()
 Returns a uniformly distributed pseudo-random number by joining two 32bit numbers from drawUniform32bit() More...
 
void drawUniformUnsignedInt (uint32_t &ret_number)
 You can call this overloaded method with either 32 or 64bit unsigned ints for the sake of general coding. More...
 
void drawUniformUnsignedInt (uint64_t &ret_number)
 
template<typename T , typename U , typename V >
void drawUniformUnsignedIntRange (T &ret_number, const U min_val, const V max_val)
 Return a uniform unsigned integer in the range [min_val,max_val] (both inclusive) More...
 
double drawUniform (const double Min, const double Max)
 Generate a uniformly distributed pseudo-random number using the MT19937 algorithm, scaled to the selected range. More...
 
template<class MAT >
void drawUniformMatrix (MAT &matrix, const double unif_min=0, const double unif_max=1)
 Fills the given matrix with independent, uniformly distributed samples. More...
 
template<class VEC >
void drawUniformVector (VEC &v, const double unif_min=0, const double unif_max=1)
 Fills the given vector with independent, uniformly distributed samples. More...
 
Normal/Gaussian pdf
double drawGaussian1D_normalized (double *likelihood=NULL)
 Generate a normalized (mean=0, std=1) normally distributed sample. More...
 
double drawGaussian1D (const double mean, const double std)
 Generate a normally distributed pseudo-random number. More...
 
template<class MAT >
void drawGaussian1DMatrix (MAT &matrix, const double mean=0, const double std=1)
 Fills the given matrix with independent, 1D-normally distributed samples. More...
 
mrpt::math::CMatrixDouble drawDefinitePositiveMatrix (const size_t dim, const double std_scale=1.0, const double diagonal_epsilon=1e-8)
 Generates a random definite-positive matrix of the given size, using the formula C = v*v^t + epsilon*I, with "v" being a vector of gaussian random samples. More...
 
template<class VEC >
void drawGaussian1DVector (VEC &v, const double mean=0, const double std=1)
 Fills the given vector with independent, 1D-normally distributed samples. More...
 
template<typename T >
void drawGaussianMultivariate (std::vector< T > &out_result, const mrpt::math::CMatrixTemplateNumeric< T > &cov, const std::vector< T > *mean=NULL)
 Generate multidimensional random samples according to a given covariance matrix. More...
 
template<class VECTORLIKE , class COVMATRIX >
void drawGaussianMultivariate (VECTORLIKE &out_result, const COVMATRIX &cov, const VECTORLIKE *mean=NULL)
 Generate multidimensional random samples according to a given covariance matrix. More...
 
template<typename VECTOR_OF_VECTORS , typename COVMATRIX >
void drawGaussianMultivariateMany (VECTOR_OF_VECTORS &ret, size_t desiredSamples, const COVMATRIX &cov, const typename VECTOR_OF_VECTORS::value_type *mean=NULL)
 Generate a given number of multidimensional random samples according to a given covariance matrix. More...
 
Miscellaneous
template<class VEC >
void permuteVector (const VEC &in_vector, VEC &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...
 

Protected Member Functions

void MT19937_generateNumbers ()
 
void MT19937_initializeGenerator (const uint32_t &seed)
 

Protected Attributes

struct
mrpt::random::CRandomGenerator::TMT19937_data 
m_MT19937_data
 
bool m_std_gauss_set
 
double m_std_gauss_next
 

Constructor & Destructor Documentation

mrpt::random::CRandomGenerator::CRandomGenerator ( )
inline

Default constructor: initialize random seed based on current time.

Definition at line 57 of file RandomGenerators.h.

mrpt::random::CRandomGenerator::CRandomGenerator ( const uint32_t  seed)
inline

Constructor for providing a custom random seed to initialize the PRNG.

Definition at line 60 of file RandomGenerators.h.

Member Function Documentation

CMatrixDouble CRandomGenerator::drawDefinitePositiveMatrix ( const size_t  dim,
const double  std_scale = 1.0,
const double  diagonal_epsilon = 1e-8 
)

Generates a random definite-positive matrix of the given size, using the formula C = v*v^t + epsilon*I, with "v" being a vector of gaussian random samples.

Definition at line 173 of file RandomGenerator.cpp.

References mrpt::math::cov().

Referenced by TEST().

double mrpt::random::CRandomGenerator::drawGaussian1D ( const double  mean,
const double  std 
)
inline

Generate a normally distributed pseudo-random number.

Parameters
meanThe mean value of desired normal distribution
stdThe standard deviation value of desired normal distribution

Definition at line 139 of file RandomGenerators.h.

Referenced by GraphSlamLevMarqTest< my_graph_t >::create_ring_path(), mrpt::maps::CBeaconMap::internal_insertObservation(), mrpt::random::RandomNormal(), ransac_data_assoc_run(), mrpt::slam::CRejectionSamplingRangeOnlyLocalization::RS_drawFromProposal(), mrpt::maps::CBeaconMap::simulateBeaconReadings(), and mrpt::maps::CLandmarksMap::simulateRangeBearingReadings().

double CRandomGenerator::drawGaussian1D_normalized ( double *  likelihood = NULL)
template<class MAT >
void mrpt::random::CRandomGenerator::drawGaussian1DMatrix ( MAT &  matrix,
const double  mean = 0,
const double  std = 1 
)
inline

Fills the given matrix with independent, 1D-normally distributed samples.

Matrix classes can be mrpt::math::CMatrixTemplateNumeric or mrpt::math::CMatrixFixedNumeric

See Also
drawGaussian1D

Definition at line 148 of file RandomGenerators.h.

References mean().

Referenced by do_test_init_random(), PosePDFGaussTests::generateRandomPose2DPDF(), Pose3DPDFGaussTests::generateRandomPose3DPDF(), and Pose3DQuatPDFGaussTests::generateRandomPose3DPDF().

template<class VEC >
void mrpt::random::CRandomGenerator::drawGaussian1DVector ( VEC &  v,
const double  mean = 0,
const double  std = 1 
)
inline

Fills the given vector with independent, 1D-normally distributed samples.

See Also
drawGaussian1D

Definition at line 166 of file RandomGenerators.h.

References mean().

Referenced by TEST_F().

template<typename T >
void CRandomGenerator::drawGaussianMultivariate ( std::vector< T > &  out_result,
const mrpt::math::CMatrixTemplateNumeric< T > &  cov,
const std::vector< T > *  mean = NULL 
)

Generate multidimensional random samples according to a given covariance matrix.

Mean is assumed to be zero if mean==NULL.

Exceptions
std::exceptionOn invalid covariance matrix
See Also
drawGaussianMultivariateMany

Computes the eigenvalues/eigenvector decomposition of this matrix, so that: M = Z · D · ZT, where columns in Z are the eigenvectors and the diagonal matrix D contains the eigenvalues as diagonal elements, sorted in ascending order.

Definition at line 191 of file RandomGenerator.cpp.

References ASSERT_, mrpt::math::cov(), MRPT_END_WITH_CLEAN_UP, and MRPT_START.

Referenced by 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::CPosePDFGaussian::drawSingleSample(), mrpt::poses::CPose3DPDFGaussian::drawSingleSample(), mrpt::poses::CPointPDFSOG::drawSingleSample(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), and mrpt::random::randomNormalMultiDimensional().

template<class VECTORLIKE , class COVMATRIX >
void mrpt::random::CRandomGenerator::drawGaussianMultivariate ( VECTORLIKE &  out_result,
const COVMATRIX &  cov,
const VECTORLIKE *  mean = NULL 
)
inline

Generate multidimensional random samples according to a given covariance matrix.

Mean is assumed to be zero if mean==NULL.

Exceptions
std::exceptionOn invalid covariance matrix
See Also
drawGaussianMultivariateMany

Definition at line 195 of file RandomGenerators.h.

References ASSERT_, ASSERT_EQUAL_, and mean().

template<typename VECTOR_OF_VECTORS , typename COVMATRIX >
void mrpt::random::CRandomGenerator::drawGaussianMultivariateMany ( VECTOR_OF_VECTORS &  ret,
size_t  desiredSamples,
const COVMATRIX &  cov,
const typename VECTOR_OF_VECTORS::value_type *  mean = NULL 
)
inline

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

Parameters
covThe covariance matrix where to draw the samples from.
desiredSamplesThe number of samples to generate.
retThe output list of samples
meanThe mean, or zeros if mean==NULL.

Definition at line 238 of file RandomGenerators.h.

References ASSERT_EQUAL_, and mean().

Referenced by mrpt::poses::CPosePDFParticles::copyFrom(), 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::random::randomNormalMultiDimensionalMany(), and mrpt::math::transform_gaussian_montecarlo().

double mrpt::random::CRandomGenerator::drawUniform ( const double  Min,
const double  Max 
)
inline
uint32_t CRandomGenerator::drawUniform32bit ( )
uint64_t CRandomGenerator::drawUniform64bit ( )

Returns a uniformly distributed pseudo-random number by joining two 32bit numbers from drawUniform32bit()

Definition at line 75 of file RandomGenerator.cpp.

template<class MAT >
void mrpt::random::CRandomGenerator::drawUniformMatrix ( MAT &  matrix,
const double  unif_min = 0,
const double  unif_max = 1 
)
inline

Fills the given matrix with independent, uniformly distributed samples.

Matrix classes can be mrpt::math::CMatrixTemplateNumeric or mrpt::math::CMatrixFixedNumeric

See Also
drawUniform

Definition at line 101 of file RandomGenerators.h.

void mrpt::random::CRandomGenerator::drawUniformUnsignedInt ( uint32_t ret_number)
inline

You can call this overloaded method with either 32 or 64bit unsigned ints for the sake of general coding.

Definition at line 78 of file RandomGenerators.h.

void mrpt::random::CRandomGenerator::drawUniformUnsignedInt ( uint64_t ret_number)
inline

Definition at line 79 of file RandomGenerators.h.

template<typename T , typename U , typename V >
void mrpt::random::CRandomGenerator::drawUniformUnsignedIntRange ( T &  ret_number,
const U  min_val,
const V  max_val 
)
inline

Return a uniform unsigned integer in the range [min_val,max_val] (both inclusive)

Definition at line 83 of file RandomGenerators.h.

template<class VEC >
void mrpt::random::CRandomGenerator::drawUniformVector ( VEC &  v,
const double  unif_min = 0,
const double  unif_max = 1 
)
inline

Fills the given vector with independent, uniformly distributed samples.

See Also
drawUniform

Definition at line 115 of file RandomGenerators.h.

Referenced by mrpt::bayes::CParticleFilterCapable::computeResampling(), and mrpt::math::RANSAC_Template< NUMTYPE >::execute().

void CRandomGenerator::MT19937_generateNumbers ( )
protected

Definition at line 55 of file RandomGenerator.cpp.

References twist().

void CRandomGenerator::MT19937_initializeGenerator ( const uint32_t seed)
protected

Definition at line 28 of file RandomGenerator.cpp.

template<class VEC >
void mrpt::random::CRandomGenerator::permuteVector ( const VEC &  in_vector,
VEC &  out_result 
)
inline

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 287 of file RandomGenerators.h.

Referenced by mrpt::random::randomPermutation(), mrpt::tfest::se2_l2_robust(), and mrpt::tfest::se3_l2_robust().

void CRandomGenerator::randomize ( const uint32_t  seed)
void CRandomGenerator::randomize ( )

Randomize the generators, based on current time.

Definition at line 114 of file RandomGenerator.cpp.

References mrpt::system::getCurrentTime().

Member Data Documentation

struct mrpt::random::CRandomGenerator::TMT19937_data mrpt::random::CRandomGenerator::m_MT19937_data
protected
double mrpt::random::CRandomGenerator::m_std_gauss_next
protected

Definition at line 46 of file RandomGenerators.h.

bool mrpt::random::CRandomGenerator::m_std_gauss_set
protected

Definition at line 45 of file RandomGenerators.h.




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