Random number generation. An instance of this class cannot be used by multiple threads at once (member functions are not const). However, the constructor is thread safe and different instances can be used safely in any number of threads. It is also guaranteed that all created instances will have a different random seed. More...

#include <ompl/util/RandomNumbers.h>

Public Member Functions
	RNG ()
	Constructor. Always sets a different random seed.
	RNG (std::uint_fast32_t localSeed)
	Constructor. Set to the specified instance seed.
double	uniform01 ()
	Generate a random real between 0 and 1.
double	uniformReal (double lower_bound, double upper_bound)
	Generate a random real within given bounds: [lower_bound, upper_bound).
int	uniformInt (int lower_bound, int upper_bound)
	Generate a random integer within given bounds: [lower_bound, upper_bound].
bool	uniformBool ()
	Generate a random boolean.
double	gaussian01 ()
	Generate a random real using a normal distribution with mean 0 and variance 1.
double	gaussian (double mean, double stddev)
	Generate a random real using a normal distribution with given mean and variance.
double	halfNormalReal (double r_min, double r_max, double focus=3.0)
	Generate a random real using a half-normal distribution. The value is within specified bounds [r_min, r_max], but with a bias towards r_max. The function is implemended using a Gaussian distribution with mean at r_max - r_min. The distribution is 'folded' around r_max axis towards r_min. The variance of the distribution is (r_max - r_min) / focus. The higher the focus, the more probable it is that generated numbers are close to r_max.
int	halfNormalInt (int r_min, int r_max, double focus=3.0)
	Generate a random integer using a half-normal distribution. The value is within specified bounds ([r_min, r_max]), but with a bias towards r_max. The function is implemented on top of halfNormalReal().
void	quaternion (double value[4])
	Uniform random unit quaternion sampling. The computed value has the order (x,y,z,w). The return variable value is expected to already exist.
void	eulerRPY (double value[3])
	Uniform random sampling of Euler roll-pitch-yaw angles, each in the range (-pi, pi]. The computed value has the order (roll, pitch, yaw). The return variable value is expected to already exist.
void	setLocalSeed (std::uint_fast32_t localSeed)
	Set the seed used for the instance of a RNG. Use this function to ensure that an instance of an RNG generates the same deterministic sequence of numbers. This function resets the member generators.
std::uint_fast32_t	getLocalSeed () const
	Get the seed used for the instance of a RNG. Passing the returned value to the setInstanceSeed() of another RNG will assure that the two objects generate the same sequence of numbers. Useful for comparing different settings of a planner while maintaining the same stochastic behaviour, assuming that every "random" decision made by the planner is made from the same RNG.
void	uniformNormalVector (std::vector< double > &v)
	Uniform random sampling of a unit-length vector. I.e., the surface of an n-ball. The return variable value is expected to already exist.
void	uniformInBall (double r, std::vector< double > &v)
	Uniform random sampling of the content of an n-ball, with a radius appropriately distributed between [0,r) so that the distribution is uniform in a Cartesian coordinate system. The return variable value is expected to already exist.
void	uniformProlateHyperspheroidSurface (const std::shared_ptr< const ProlateHyperspheroid > &phsPtr, double value[])
	Uniform random sampling of the surface of a prolate hyperspheroid, a special symmetric type of n-dimensional ellipse. The return variable value is expected to already exist.
void	uniformProlateHyperspheroid (const std::shared_ptr< const ProlateHyperspheroid > &phsPtr, double value[])
	Uniform random sampling of a prolate hyperspheroid, a special symmetric type of n-dimensional ellipse. The return variable value is expected to already exist.
template<class RandomAccessIterator>
void	shuffle (RandomAccessIterator first, RandomAccessIterator last)
	randomly rearrange elements in the range [first, last)

Static Public Member Functions
static void	setSeed (std::uint_fast32_t seed)
	Set the seed used to generate the seeds of each RNG instance. Use this function to ensure the same sequence of random numbers is generated across multiple instances of RNG.
static std::uint_fast32_t	getSeed ()
	Get the seed used to generate the seeds of each RNG instance. Passing the returned value to setSeed() at a subsequent execution of the code will ensure deterministic (repeatable) behaviour across multiple instances of RNG. Useful for debugging.

Detailed Description

Random number generation. An instance of this class cannot be used by multiple threads at once (member functions are not const). However, the constructor is thread safe and different instances can be used safely in any number of threads. It is also guaranteed that all created instances will have a different random seed.

Definition at line 56 of file RandomNumbers.h.

Constructor & Destructor Documentation

◆ RNG() [1/2]

ompl::RNG::RNG ( )

Constructor. Always sets a different random seed.

Definition at line 219 of file RandomNumbers.cpp.

◆ RNG() [2/2]

ompl::RNG::RNG ( std::uint_fast32_t localSeed )

Constructor. Set to the specified instance seed.

Definition at line 226 of file RandomNumbers.cpp.

Member Function Documentation

◆ eulerRPY()

void ompl::RNG::eulerRPY ( double value[3] )

Uniform random sampling of Euler roll-pitch-yaw angles, each in the range (-pi, pi]. The computed value has the order (roll, pitch, yaw). The return variable value is expected to already exist.

Definition at line 281 of file RandomNumbers.cpp.

◆ gaussian()

double ompl::RNG::gaussian	(	double	mean,
		double	stddev )

inline

Generate a random real using a normal distribution with given mean and variance.

Definition at line 98 of file RandomNumbers.h.

◆ gaussian01()

double ompl::RNG::gaussian01 ( )

inline

Generate a random real using a normal distribution with mean 0 and variance 1.

Definition at line 92 of file RandomNumbers.h.

◆ getLocalSeed()

std::uint_fast32_t ompl::RNG::getLocalSeed ( ) const

inline

Get the seed used for the instance of a RNG. Passing the returned value to the setInstanceSeed() of another RNG will assure that the two objects generate the same sequence of numbers. Useful for comparing different settings of a planner while maintaining the same stochastic behaviour, assuming that every "random" decision made by the planner is made from the same RNG.

Definition at line 141 of file RandomNumbers.h.

◆ getSeed()

std::uint_fast32_t ompl::RNG::getSeed ( )

static

Get the seed used to generate the seeds of each RNG instance. Passing the returned value to setSeed() at a subsequent execution of the code will ensure deterministic (repeatable) behaviour across multiple instances of RNG. Useful for debugging.

Definition at line 209 of file RandomNumbers.cpp.

◆ halfNormalInt()

int ompl::RNG::halfNormalInt	(	int	r_min,
		int	r_max,
		double	focus = 3.0 )

Generate a random integer using a half-normal distribution. The value is within specified bounds ([r_min, r_max]), but with a bias towards r_max. The function is implemented on top of halfNormalReal().

Definition at line 258 of file RandomNumbers.cpp.

◆ halfNormalReal()

double ompl::RNG::halfNormalReal	(	double	r_min,
		double	r_max,
		double	focus = 3.0 )

Generate a random real using a half-normal distribution. The value is within specified bounds [r_min, r_max], but with a bias towards r_max. The function is implemended using a Gaussian distribution with mean at r_max - r_min. The distribution is 'folded' around r_max axis towards r_min. The variance of the distribution is (r_max - r_min) / focus. The higher the focus, the more probable it is that generated numbers are close to r_max.

Definition at line 245 of file RandomNumbers.cpp.

◆ quaternion()

void ompl::RNG::quaternion ( double value[4] )

Uniform random unit quaternion sampling. The computed value has the order (x,y,z,w). The return variable value is expected to already exist.

Definition at line 266 of file RandomNumbers.cpp.

◆ setLocalSeed()

void ompl::RNG::setLocalSeed ( std::uint_fast32_t localSeed )

Set the seed used for the instance of a RNG. Use this function to ensure that an instance of an RNG generates the same deterministic sequence of numbers. This function resets the member generators.

Definition at line 231 of file RandomNumbers.cpp.

◆ setSeed()

void ompl::RNG::setSeed ( std::uint_fast32_t seed )

static

Set the seed used to generate the seeds of each RNG instance. Use this function to ensure the same sequence of random numbers is generated across multiple instances of RNG.

Definition at line 214 of file RandomNumbers.cpp.

◆ shuffle()

template<class RandomAccessIterator>

void ompl::RNG::shuffle	(	RandomAccessIterator	first,
		RandomAccessIterator	last )

inline

randomly rearrange elements in the range [first, last)

Definition at line 178 of file RandomNumbers.h.

◆ uniform01()

double ompl::RNG::uniform01 ( )

inline

Generate a random real between 0 and 1.

Definition at line 66 of file RandomNumbers.h.

◆ uniformBool()

bool ompl::RNG::uniformBool ( )

inline

Generate a random boolean.

Definition at line 86 of file RandomNumbers.h.

◆ uniformInBall()

void ompl::RNG::uniformInBall	(	double	r,
		std::vector< double > &	v )

Uniform random sampling of the content of an n-ball, with a radius appropriately distributed between [0,r) so that the distribution is uniform in a Cartesian coordinate system. The return variable value is expected to already exist.

Definition at line 296 of file RandomNumbers.cpp.

◆ uniformInt()

int ompl::RNG::uniformInt	(	int	lower_bound,
		int	upper_bound )

inline

Generate a random integer within given bounds: [lower_bound, upper_bound].

Definition at line 79 of file RandomNumbers.h.

◆ uniformNormalVector()

void ompl::RNG::uniformNormalVector ( std::vector< double > & v )

Uniform random sampling of a unit-length vector. I.e., the surface of an n-ball. The return variable value is expected to already exist.

Definition at line 288 of file RandomNumbers.cpp.

◆ uniformProlateHyperspheroid()

void ompl::RNG::uniformProlateHyperspheroid	(	const std::shared_ptr< const ProlateHyperspheroid > &	phsPtr,
		double	value[] )

Uniform random sampling of a prolate hyperspheroid, a special symmetric type of n-dimensional ellipse. The return variable value is expected to already exist.

J. D. Gammell, T. D. Barfoot, S. S. Srinivasa, "Informed sampling for asymptotically optimal path planning." IEEE Transactions on Robotics (T-RO), 34(4): 966-984, Aug. 2018. DOI: TRO.2018.2830331. arXiv: 1706.06454 [cs.RO]. Illustration video. Short description video.

Definition at line 322 of file RandomNumbers.cpp.

◆ uniformProlateHyperspheroidSurface()

void ompl::RNG::uniformProlateHyperspheroidSurface	(	const std::shared_ptr< const ProlateHyperspheroid > &	phsPtr,
		double	value[] )

Uniform random sampling of the surface of a prolate hyperspheroid, a special symmetric type of n-dimensional ellipse. The return variable value is expected to already exist.

J. D. Gammell, T. D. Barfoot, S. S. Srinivasa, "Informed sampling for asymptotically optimal path planning." IEEE Transactions on Robotics (T-RO), 34(4): 966-984, Aug. 2018. DOI: TRO.2018.2830331. arXiv: 1706.06454 [cs.RO] Illustration video. Short description video.

Definition at line 308 of file RandomNumbers.cpp.

◆ uniformReal()

double ompl::RNG::uniformReal	(	double	lower_bound,
		double	upper_bound )

inline

Generate a random real within given bounds: [lower_bound, upper_bound).

Definition at line 72 of file RandomNumbers.h.

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

ompl/util/RandomNumbers.h
ompl/util/src/RandomNumbers.cpp

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ RNG() [1/2]

◆ RNG() [2/2]

Member Function Documentation

◆ eulerRPY()

◆ gaussian()

◆ gaussian01()

◆ getLocalSeed()

◆ getSeed()

◆ halfNormalInt()

◆ halfNormalReal()

◆ quaternion()

◆ setLocalSeed()

◆ setSeed()

◆ shuffle()

◆ uniform01()

◆ uniformBool()

◆ uniformInBall()

◆ uniformInt()

◆ uniformNormalVector()

◆ uniformProlateHyperspheroid()

◆ uniformProlateHyperspheroidSurface()

◆ uniformReal()