Base class of the pseudorandom number generators providing common methods. More...

#include <prrng.h>

Public Member Functions
double	cumsum_random (size_t n)
	Result of the cumulative sum of `n` random numbers.

double	cumsum_delta (size_t n, double scale=1)
	Result of the cumulative sum of `n` 'random' numbers, distributed according to a delta distribution,.

double	cumsum_exponential (size_t n, double scale=1)
	Result of the cumulative sum of `n` random numbers, distributed according to an exponential distribution, see exponential_distribution(),.

double	cumsum_power (size_t n, double k=1)
	Result of the cumulative sum of `n` random numbers, distributed according to a power distribution, see power_distribution(),.

double	cumsum_gamma (size_t n, double k=1, double scale=1)
	Result of the cumulative sum of `n` random numbers, distributed according to a gamma distribution, see gamma_distribution(),.

double	cumsum_pareto (size_t n, double k=1, double scale=1)
	Result of the cumulative sum of `n` random numbers, distributed according to a Pareto distribution, see pareto_distribution(),.

double	cumsum_weibull (size_t n, double k=1, double scale=1)
	Result of the cumulative sum of `n` random numbers, distributed according to a weibull distribution, see weibull_distribution(),.

double	cumsum_normal (size_t n, double mu=0, double sigma=1)
	Result of the cumulative sum of `n` random numbers, distributed according to a normal distribution, see normal_distribution(),.

template<typename Iterator >
void	shuffle (Iterator begin, Iterator end)
	Draw uniformly distributed permutation and permute the given STL container.

template<class P >
auto	decide (const P &p) -> typename detail::return_type< bool, P >::type
	Decide based on probability per value.

template<class P , class R >
R	decide (const P &p)
	Decide based on probability per value.

template<class P , class R >
void	decide (const P &p, R &ret)
	Decide based on probability per value.

template<class P , class T >
auto	decide_masked (const P &p, const T &mask) -> typename detail::return_type< bool, P >::type
	Decide based on probability per value.

template<class P , class T , class R >
R	decide_masked (const P &p, const T &mask)
	Decide based on probability per value.

template<class P , class T , class R >
void	decide_masked (const P &p, const T &mask, R &ret)
	Decide based on probability per value.

double	random ()
	Generate a random number \( 0 \leq r \leq 1 \).

template<class S >
auto	random (const S &shape) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

template<class R , class S >
R	random (const S &shape)
	Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

template<class I , std::size_t L>
auto	random (const I(&shape)[L]) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

template<class R , class I , std::size_t L>
R	random (const I(&shape)[L])
	Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

template<typename T >
T	randint (T high)
	Generate a random integer \( 0 \leq r < bound \).

template<class S , typename T >
auto	randint (const S &shape, T high) -> typename detail::return_type< T, S >::type
	Generate an nd-array of random integers \( 0 \leq r \leq bound \).

template<class R , class S , typename T >
R	randint (const S &shape, T high)
	Generate an nd-array of random integers \( 0 \leq r \leq bound \).

template<class I , std::size_t L, typename T >
auto	randint (const I(&shape)[L], T high) -> typename detail::return_type_fixed< T, L >::type
	Generate an nd-array of random integers \( 0 \leq r \leq bound \).

template<class R , class I , std::size_t L, typename T >
R	randint (const I(&shape)[L], T high)
	Generate an nd-array of random integers \( 0 \leq r \leq bound \).

template<class S , typename T , typename U >
auto	randint (const S &shape, T low, U high) -> typename detail::return_type< T, S >::type
	Generate an nd-array of random integers \( low \leq r < high \).

template<class R , class S , typename T , typename U >
R	randint (const S &shape, T low, U high)
	Generate an nd-array of random integers \( low \leq r < high \).

template<class I , std::size_t L, typename T , typename U >
auto	randint (const I(&shape)[L], T low, U high) -> typename detail::return_type_fixed< T, L >::type
	Generate an nd-array of random integers \( low \leq r < high \).

template<class R , class I , std::size_t L, typename T , typename U >
R	randint (const I(&shape)[L], T low, U high)
	Generate an nd-array of random integers \( low \leq r < high \).

double	delta (double scale=1)
	Return a number distributed according to a delta distribution.

template<class S >
auto	delta (const S &shape, double scale=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of numbers that are delta distribution.

template<class R , class S >
R	delta (const S &shape, double scale=1)
	Generate an nd-array of numbers that are delta distribution.

template<class I , std::size_t L>
auto	delta (const I(&shape)[L], double scale=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of numbers that are delta distribution.

template<class R , class I , std::size_t L>
R	delta (const I(&shape)[L], double scale=1)
	Generate an nd-array of numbers that are delta distribution.

double	exponential (double scale=1)
	Return a random number distributed according to an exponential distribution.

template<class S >
auto	exponential (const S &shape, double scale=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to an exponential distribution.

template<class R , class S >
R	exponential (const S &shape, double scale=1)
	Generate an nd-array of random numbers distributed according to an exponential distribution.

template<class I , std::size_t L>
auto	exponential (const I(&shape)[L], double scale=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to an exponential distribution.

template<class R , class I , std::size_t L>
R	exponential (const I(&shape)[L], double scale=1)
	Generate an nd-array of random numbers distributed according to an exponential distribution.

double	power (double k=1)
	Return a random number distributed according to an power distribution.

template<class S >
auto	power (const S &shape, double k=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to an power distribution.

template<class R , class S >
R	power (const S &shape, double k=1)
	Generate an nd-array of random numbers distributed according to an power distribution.

template<class I , std::size_t L>
auto	power (const I(&shape)[L], double k=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to an power distribution.

template<class R , class I , std::size_t L>
R	power (const I(&shape)[L], double k=1)
	Generate an nd-array of random numbers distributed according to an power distribution.

double	gamma (double k=1, double scale=1)
	Return a random number distributed according to a Gamma distribution.

template<class S >
auto	gamma (const S &shape, double k=1, double scale=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to a Gamma distribution.

template<class R , class S >
R	gamma (const S &shape, double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Gamma distribution.

template<class I , std::size_t L>
auto	gamma (const I(&shape)[L], double k=1, double scale=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to a Gamma distribution.

template<class R , class I , std::size_t L>
R	gamma (const I(&shape)[L], double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Gamma distribution.

double	pareto (double k=1, double scale=1)
	Return a random number distributed according to a Pareto distribution.

template<class S >
auto	pareto (const S &shape, double k=1, double scale=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to a Pareto distribution.

template<class R , class S >
R	pareto (const S &shape, double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Pareto distribution.

template<class I , std::size_t L>
auto	pareto (const I(&shape)[L], double k=1, double scale=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to a Pareto distribution.

template<class R , class I , std::size_t L>
R	pareto (const I(&shape)[L], double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Pareto distribution.

double	weibull (double k=1, double scale=1)
	Return a random number distributed according to a Weibull distribution.

template<class S >
auto	weibull (const S &shape, double k=1, double scale=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to a Weibull distribution.

template<class R , class S >
R	weibull (const S &shape, double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Weibull distribution.

template<class I , std::size_t L>
auto	weibull (const I(&shape)[L], double k=1, double scale=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to a Weibull distribution.

template<class R , class I , std::size_t L>
R	weibull (const I(&shape)[L], double k=1, double scale=1)
	Generate an nd-array of random numbers distributed according to a Weibull distribution.

double	normal (double mu=0, double sigma=1)
	Return a random number distributed according to a normal distribution.

template<class S >
auto	normal (const S &shape, double mu=0, double sigma=1) -> typename detail::return_type< double, S >::type
	Generate an nd-array of random numbers distributed according to a normal distribution.

template<class R , class S >
R	normal (const S &shape, double mu=0, double sigma=1)
	Generate an nd-array of random numbers distributed according to a normal distribution.

template<class I , std::size_t L>
auto	normal (const I(&shape)[L], double mu=0, double sigma=1) -> typename detail::return_type_fixed< double, L >::type
	Generate an nd-array of random numbers distributed according to a normal distribution.

template<class R , class I , std::size_t L>
R	normal (const I(&shape)[L], double mu=0, double sigma=1)
	Generate an nd-array of random numbers distributed according to a normal distribution.

double	draw (enum prrng::distribution distribution, std::vector< double > parameters=std::vector< double >{}, bool append_default=true)
	Get a random number according to some distribution.

template<class R , class S >
R	draw (const S &shape, enum prrng::distribution distribution, std::vector< double > parameters=std::vector< double >{}, bool append_default=true)
	Get an nd-array of random numbers according to some distribution.

double	cumsum (size_t n, enum prrng::distribution distribution, std::vector< double > parameters=std::vector< double >{}, bool append_default=true)
	Get the cumulative sum of `n` random numbers according to some distribution.

Detailed Description

template<class Derived>
class prrng::GeneratorBase< Derived >

Base class of the pseudorandom number generators providing common methods.

If you want to implement a new generator, you should inherit from this class. The following minimal signature is required:

 class MyGenerator : public GeneratorBase<MyGenerator> {
 public:
     // Return next random number [0, 1).
     double next_double();

     // Return next random number (0, 1).
     double next_positive_double();

     // Return next random number [0, 2^32).
     uint32_t next_uint32();
 };

Template Parameters

Derived Derived class.

Definition at line 1690 of file prrng.h.

Member Function Documentation

◆ cumsum()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum	(	size_t	n,
		enum prrng::distribution	distribution,
		std::vector< double >	parameters = `std::vector<double>{}`,
		bool	append_default = `true`
	)

inline

Get the cumulative sum of n random numbers according to some distribution.

Parameters

n	Number of random numbers to sum.
distribution	Type of distribution, see prrg::distribution.
parameters	Parameters for the distribution, see prrng::default_parameters.
append_default	Append default parameters to `parameters`.

Definition at line 2645 of file prrng.h.

◆ cumsum_delta()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_delta	(	size_t	n,
		double	scale = `1`
	)

inline

Result of the cumulative sum of n 'random' numbers, distributed according to a delta distribution,.

Parameters

n	Number of steps.
scale	Scale.

Returns: Cumulative sum.

Definition at line 1713 of file prrng.h.

◆ cumsum_exponential()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_exponential	(	size_t	n,
		double	scale = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to an exponential distribution, see exponential_distribution(),.

Parameters

n	Number of steps.
scale	Scale.

Returns: Cumulative sum.

Definition at line 1725 of file prrng.h.

◆ cumsum_gamma()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_gamma	(	size_t	n,
		double	k = `1`,
		double	scale = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to a gamma distribution, see gamma_distribution(),.

Parameters

n	Number of steps.
k	Shape.
scale	Scale.

Returns: Cumulative sum.

Definition at line 1759 of file prrng.h.

◆ cumsum_normal()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_normal	(	size_t	n,
		double	mu = `0`,
		double	sigma = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to a normal distribution, see normal_distribution(),.

Parameters

n	Number of steps.
mu	Mean.
sigma	Standard deviation.

Returns: Cumulative sum.

Definition at line 1818 of file prrng.h.

◆ cumsum_pareto()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_pareto	(	size_t	n,
		double	k = `1`,
		double	scale = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to a Pareto distribution, see pareto_distribution(),.

Parameters

n	Number of steps.
k	Shape.
scale	Scale.

Returns: Cumulative sum.

Definition at line 1782 of file prrng.h.

◆ cumsum_power()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_power	(	size_t	n,
		double	k = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to a power distribution, see power_distribution(),.

Parameters

n	Number of steps.
k	Scale.

Returns: Cumulative sum.

Definition at line 1741 of file prrng.h.

◆ cumsum_random()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_random ( size_t n )

inline

Result of the cumulative sum of n random numbers.

Parameters

n	Number of steps.

Returns: Cumulative sum.

Definition at line 1697 of file prrng.h.

◆ cumsum_weibull()

template<class Derived >

double prrng::GeneratorBase< Derived >::cumsum_weibull	(	size_t	n,
		double	k = `1`,
		double	scale = `1`
	)

inline

Result of the cumulative sum of n random numbers, distributed according to a weibull distribution, see weibull_distribution(),.

Parameters

n	Number of steps.
k	Shape.
scale	Scale.

Returns: Cumulative sum.

Definition at line 1800 of file prrng.h.

◆ decide() [1/3]

template<class Derived >

template<class P , class R >

R prrng::GeneratorBase< Derived >::decide ( const P & p )

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].

Returns: Decision for each p.

Definition at line 1874 of file prrng.h.

◆ decide() [2/3]

template<class Derived >

template<class P >

auto prrng::GeneratorBase< Derived >::decide ( const P & p ) -> typename detail::return_type<bool, P>::type

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].

Returns: Decision for each p.

Definition at line 1862 of file prrng.h.

◆ decide() [3/3]

template<class Derived >

template<class P , class R >

void prrng::GeneratorBase< Derived >::decide	(	const P &	p,
		R &	ret
	)

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].
ret	Decision for each `p`.

Definition at line 1891 of file prrng.h.

◆ decide_masked() [1/3]

template<class Derived >

template<class P , class T , class R >

R prrng::GeneratorBase< Derived >::decide_masked	(	const P &	p,
		const T &	mask
	)

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].
mask	Where `true` the decision is `false` (no random number is drawn there).

Returns: Decision for each p.

Definition at line 1928 of file prrng.h.

◆ decide_masked() [2/3]

template<class Derived >

template<class P , class T >

auto prrng::GeneratorBase< Derived >::decide_masked	(	const P &	p,
		const T &	mask
	)		-> typename detail::return_type<bool, P>::type

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].
mask	Where `true` the decision is `false` (no random number is drawn there).

Returns: Decision for each p.

Definition at line 1916 of file prrng.h.

◆ decide_masked() [3/3]

template<class Derived >

template<class P , class T , class R >

void prrng::GeneratorBase< Derived >::decide_masked	(	const P &	p,
		const T &	mask,
		R &	ret
	)

inline

Decide based on probability per value.

This is fully equivalent to generator.random(p.shape) < p, but avoids the memory allocation of random.

Parameters

p	Probability per value [0, 1].
mask	Where `true` the decision is `false` (no random number is drawn there).
ret	Decision for each `p`.

Definition at line 1946 of file prrng.h.

◆ delta() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::delta	(	const I(&)	shape[L],
		double	scale = `1`
	)

inline

Generate an nd-array of numbers that are delta distribution.

These numbers are not random; calling this function does not change the state of the generators.

Parameters

shape	The shape of the nd-array.
scale	The value of the 'peak' of the delta distribution.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2177 of file prrng.h.

◆ delta() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::delta	(	const I(&)	shape[L],
		double	scale = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of numbers that are delta distribution.

These numbers are not random; calling this function does not change the state of the generators.

Parameters

shape	The shape of the nd-array.
scale	The value of the 'peak' of the delta distribution.

Returns: The sample of shape shape.

Definition at line 2165 of file prrng.h.

◆ delta() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::delta	(	const S &	shape,
		double	scale = `1`
	)

inline

Generate an nd-array of numbers that are delta distribution.

These numbers are not random; calling this function does not change the state of the generators.

Parameters

shape	The shape of the nd-array.
scale	The value of the 'peak' of the delta distribution.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2156 of file prrng.h.

◆ delta() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::delta	(	const S &	shape,
		double	scale = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of numbers that are delta distribution.

These numbers are not random; calling this function does not change the state of the generators.

Parameters

shape	The shape of the nd-array.
scale	The value of the 'peak' of the delta distribution.

Returns: The sample of shape shape.

Definition at line 2145 of file prrng.h.

◆ delta() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::delta ( double scale = 1 )

inline

Return a number distributed according to a delta distribution.

Parameters

scale The value of the 'peak' of the delta distribution.

Returns: Random number.

Definition at line 2130 of file prrng.h.

◆ draw() [1/2]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::draw	(	const S &	shape,
		enum prrng::distribution	distribution,
		std::vector< double >	parameters = `std::vector<double>{}`,
		bool	append_default = `true`
	)

inline

Get an nd-array of random numbers according to some distribution.

Parameters

shape	The shape of the nd-array.
distribution	Type of distribution, see prrg::distribution.
parameters	Parameters for the distribution, see prrng::default_parameters.
append_default	Append default parameters to `parameters`.s

Definition at line 2599 of file prrng.h.

◆ draw() [2/2]

template<class Derived >

double prrng::GeneratorBase< Derived >::draw	(	enum prrng::distribution	distribution,
		std::vector< double >	parameters = `std::vector<double>{}`,
		bool	append_default = `true`
	)

inline

Get a random number according to some distribution.

Parameters

distribution	Type of distribution, see prrg::distribution.
parameters	Parameters for the distribution, see prrng::default_parameters.
append_default	Append default parameters to `parameters`.

Definition at line 2553 of file prrng.h.

◆ exponential() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::exponential	(	const I(&)	shape[L],
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to an exponential distribution.

Parameters

shape	The shape of the nd-array.
scale	Scale.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2234 of file prrng.h.

◆ exponential() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::exponential	(	const I(&)	shape[L],
		double	scale = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to an exponential distribution.

Parameters

shape	The shape of the nd-array.
scale	Scale.

Returns: The sample of shape shape.

Definition at line 2222 of file prrng.h.

◆ exponential() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::exponential	(	const S &	shape,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to an exponential distribution.

Parameters

shape	The shape of the nd-array.
scale	Scale.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2213 of file prrng.h.

◆ exponential() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::exponential	(	const S &	shape,
		double	scale = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to an exponential distribution.

Parameters

shape	The shape of the nd-array.
scale	Scale.

Returns: The sample of shape shape.

Definition at line 2201 of file prrng.h.

◆ exponential() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::exponential ( double scale = 1 )

inline

Return a random number distributed according to an exponential distribution.

Parameters

scale Scale.

Returns: Random number.

Definition at line 2188 of file prrng.h.

◆ gamma() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::gamma	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Gamma distribution.

Only available when compiled with PRRNG_USE_BOOST.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2356 of file prrng.h.

◆ gamma() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::gamma	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to a Gamma distribution.

Only available when compiled with PRRNG_USE_BOOST.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2344 of file prrng.h.

◆ gamma() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::gamma	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Gamma distribution.

Only available when compiled with PRRNG_USE_BOOST.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2335 of file prrng.h.

◆ gamma() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::gamma	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to a Gamma distribution.

Only available when compiled with PRRNG_USE_BOOST.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2323 of file prrng.h.

◆ gamma() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::gamma	(	double	k = `1`,
		double	scale = `1`
	)

inline

Return a random number distributed according to a Gamma distribution.

Parameters

k	Shape parameter.
scale	Scale parameter.

Returns: Random number.

Definition at line 2302 of file prrng.h.

◆ normal() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::normal	(	const I(&)	shape[L],
		double	mu = `0`,
		double	sigma = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a normal distribution.

Parameters

shape	The shape of the nd-array.
mu	The average.
sigma	The standard deviation.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2541 of file prrng.h.

◆ normal() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::normal	(	const I(&)	shape[L],
		double	mu = `0`,
		double	sigma = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to a normal distribution.

Parameters

shape	The shape of the nd-array.
mu	The average.
sigma	The standard deviation.

Returns: The sample of shape shape.

Definition at line 2529 of file prrng.h.

◆ normal() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::normal	(	const S &	shape,
		double	mu = `0`,
		double	sigma = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a normal distribution.

Parameters

shape	The shape of the nd-array.
mu	The average.
sigma	The standard deviation.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2520 of file prrng.h.

◆ normal() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::normal	(	const S &	shape,
		double	mu = `0`,
		double	sigma = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to a normal distribution.

Parameters

shape	The shape of the nd-array.
mu	The average.
sigma	The standard deviation.

Returns: The sample of shape shape.

Definition at line 2508 of file prrng.h.

◆ normal() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::normal	(	double	mu = `0`,
		double	sigma = `1`
	)

inline

Return a random number distributed according to a normal distribution.

Parameters

mu	The average.
sigma	The standard deviation.

Returns: Random number.

Definition at line 2487 of file prrng.h.

◆ pareto() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::pareto	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Pareto distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2415 of file prrng.h.

◆ pareto() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::pareto	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to a Pareto distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2403 of file prrng.h.

◆ pareto() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::pareto	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Pareto distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2394 of file prrng.h.

◆ pareto() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::pareto	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to a Pareto distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2382 of file prrng.h.

◆ pareto() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::pareto	(	double	k = `1`,
		double	scale = `1`
	)

inline

Return a random number distributed according to a Pareto distribution.

Parameters

k	Shape parameter.
scale	Scale parameter.

Returns: Random number.

Definition at line 2368 of file prrng.h.

◆ power() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::power	(	const I(&)	shape[L],
		double	k = `1`
	)

inline

Generate an nd-array of random numbers distributed according to an power distribution.

Parameters

shape	The shape of the nd-array.
k	Scale.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2290 of file prrng.h.

◆ power() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::power	(	const I(&)	shape[L],
		double	k = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to an power distribution.

Parameters

shape	The shape of the nd-array.
k	Scale.

Returns: The sample of shape shape.

Definition at line 2278 of file prrng.h.

◆ power() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::power	(	const S &	shape,
		double	k = `1`
	)

inline

Generate an nd-array of random numbers distributed according to an power distribution.

Parameters

shape	The shape of the nd-array.
k	Scale.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2269 of file prrng.h.

◆ power() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::power	(	const S &	shape,
		double	k = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to an power distribution.

Parameters

shape	The shape of the nd-array.
k	Scale.

Returns: The sample of shape shape.

Definition at line 2258 of file prrng.h.

◆ power() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::power ( double k = 1 )

inline

Return a random number distributed according to an power distribution.

Parameters

k Scale.

Returns: Random number.

Definition at line 2245 of file prrng.h.

◆ randint() [1/9]

template<class Derived >

template<class R , class I , std::size_t L, typename T >

R prrng::GeneratorBase< Derived >::randint	(	const I(&)	shape[L],
		T	high
	)

inline

Generate an nd-array of random integers \( 0 \leq r \leq bound \).

Parameters

shape	The shape of the nd-array.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<uint32_t, 1>`

Definition at line 2073 of file prrng.h.

◆ randint() [2/9]

template<class Derived >

template<class I , std::size_t L, typename T >

auto prrng::GeneratorBase< Derived >::randint	(	const I(&)	shape[L],
		T	high
	)		-> typename detail::return_type_fixed<T, L>::type

inline

Generate an nd-array of random integers \( 0 \leq r \leq bound \).

Parameters

shape	The shape of the nd-array.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Definition at line 2062 of file prrng.h.

◆ randint() [3/9]

template<class Derived >

template<class R , class I , std::size_t L, typename T , typename U >

R prrng::GeneratorBase< Derived >::randint	(	const I(&)	shape[L],
		T	low,
		U	high
	)

inline

Generate an nd-array of random integers \( low \leq r < high \).

Parameters

shape	The shape of the nd-array.
low	The lower bound of the random integers.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<uint32_t, 1>`

Definition at line 2119 of file prrng.h.

◆ randint() [4/9]

template<class Derived >

template<class I , std::size_t L, typename T , typename U >

auto prrng::GeneratorBase< Derived >::randint	(	const I(&)	shape[L],
		T	low,
		U	high
	)		-> typename detail::return_type_fixed<T, L>::type

inline

Generate an nd-array of random integers \( low \leq r < high \).

Parameters

shape	The shape of the nd-array.
low	The lower bound of the random integers.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Definition at line 2107 of file prrng.h.

◆ randint() [5/9]

template<class Derived >

template<class R , class S , typename T >

R prrng::GeneratorBase< Derived >::randint	(	const S &	shape,
		T	high
	)

inline

Generate an nd-array of random integers \( 0 \leq r \leq bound \).

Parameters

shape	The shape of the nd-array.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2053 of file prrng.h.

◆ randint() [6/9]

template<class Derived >

template<class S , typename T >

auto prrng::GeneratorBase< Derived >::randint	(	const S &	shape,
		T	high
	)		-> typename detail::return_type<T, S>::type

inline

Generate an nd-array of random integers \( 0 \leq r \leq bound \).

Parameters

shape	The shape of the nd-array.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Definition at line 2042 of file prrng.h.

◆ randint() [7/9]

template<class Derived >

template<class R , class S , typename T , typename U >

R prrng::GeneratorBase< Derived >::randint	(	const S &	shape,
		T	low,
		U	high
	)

inline

Generate an nd-array of random integers \( low \leq r < high \).

Parameters

shape	The shape of the nd-array.
low	The lower bound of the random integers.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2098 of file prrng.h.

◆ randint() [8/9]

template<class Derived >

template<class S , typename T , typename U >

auto prrng::GeneratorBase< Derived >::randint	(	const S &	shape,
		T	low,
		U	high
	)		-> typename detail::return_type<T, S>::type

inline

Generate an nd-array of random integers \( low \leq r < high \).

Parameters

shape	The shape of the nd-array.
low	The lower bound of the random integers.
high	The upper bound of the random integers.

Returns: The sample of shape shape.

Definition at line 2087 of file prrng.h.

◆ randint() [9/9]

template<class Derived >

template<typename T >

T prrng::GeneratorBase< Derived >::randint ( T high )

inline

Generate a random integer \( 0 \leq r < bound \).

Parameters

high	The upper bound of the random integers.

Returns: Random number.

Definition at line 2024 of file prrng.h.

◆ random() [1/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::random ( )

inline

Generate a random number \( 0 \leq r \leq 1 \).

Returns: Random number.

Definition at line 1969 of file prrng.h.

◆ random() [2/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::random ( const I(&) shape[L] )

inline

Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

Parameters

shape The shape of the nd-array.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2012 of file prrng.h.

◆ random() [3/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::random ( const I(&) shape[L] ) -> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

Parameters

shape The shape of the nd-array.

Returns: The sample of shape shape.

Definition at line 2001 of file prrng.h.

◆ random() [4/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::random ( const S & shape )

inline

Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

Parameters

shape The shape of the nd-array.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 1992 of file prrng.h.

◆ random() [5/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::random ( const S & shape ) -> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers \( 0 \leq r \leq 1 \).

Parameters

shape The shape of the nd-array.

Returns: The sample of shape shape.

Definition at line 1981 of file prrng.h.

◆ shuffle()

template<class Derived >

template<typename Iterator >

void prrng::GeneratorBase< Derived >::shuffle	(	Iterator	begin,
		Iterator	end
	)

inline

Draw uniformly distributed permutation and permute the given STL container.

Parameters

begin	Iterator to the beginning of the container.
end	Iterator to the end of the container.

Note: From: Knuth, TAoCP Vol. 2 (3rd 3d), Section 3.4.2

Author: Wenzel Jakob, https://github.com/wjakob/pcg32.

Definition at line 1844 of file prrng.h.

◆ weibull() [1/5]

template<class Derived >

template<class R , class I , std::size_t L>

R prrng::GeneratorBase< Derived >::weibull	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Weibull distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2475 of file prrng.h.

◆ weibull() [2/5]

template<class Derived >

template<class I , std::size_t L>

auto prrng::GeneratorBase< Derived >::weibull	(	const I(&)	shape[L],
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type_fixed<double, L>::type

inline

Generate an nd-array of random numbers distributed according to a Weibull distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2463 of file prrng.h.

◆ weibull() [3/5]

template<class Derived >

template<class R , class S >

R prrng::GeneratorBase< Derived >::weibull	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)

inline

Generate an nd-array of random numbers distributed according to a Weibull distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Template Parameters

R	return type, e.g. `xt::xtensor<double, 1>`

Definition at line 2454 of file prrng.h.

◆ weibull() [4/5]

template<class Derived >

template<class S >

auto prrng::GeneratorBase< Derived >::weibull	(	const S &	shape,
		double	k = `1`,
		double	scale = `1`
	)		-> typename detail::return_type<double, S>::type

inline

Generate an nd-array of random numbers distributed according to a Weibull distribution.

Parameters

shape	The shape of the nd-array.
k	Shape parameter.
scale	Scale parameter.

Returns: The sample of shape shape.

Definition at line 2442 of file prrng.h.

◆ weibull() [5/5]

template<class Derived >

double prrng::GeneratorBase< Derived >::weibull	(	double	k = `1`,
		double	scale = `1`
	)

inline

Return a random number distributed according to a Weibull distribution.

Parameters

k	Shape parameter.
scale	Scale parameter.

Returns: Random number.

Definition at line 2427 of file prrng.h.

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

prrng.h

Public Member Functions

Detailed Description

Member Function Documentation

◆ cumsum()

◆ cumsum_delta()

◆ cumsum_exponential()

◆ cumsum_gamma()

◆ cumsum_normal()

◆ cumsum_pareto()

◆ cumsum_power()

◆ cumsum_random()

◆ cumsum_weibull()

◆ decide() [1/3]

◆ decide() [2/3]

◆ decide() [3/3]

◆ decide_masked() [1/3]

◆ decide_masked() [2/3]

◆ decide_masked() [3/3]

◆ delta() [1/5]

◆ delta() [2/5]

◆ delta() [3/5]

◆ delta() [4/5]

◆ delta() [5/5]

◆ draw() [1/2]

◆ draw() [2/2]

◆ exponential() [1/5]

◆ exponential() [2/5]

◆ exponential() [3/5]

◆ exponential() [4/5]

◆ exponential() [5/5]

◆ gamma() [1/5]

◆ gamma() [2/5]

◆ gamma() [3/5]

◆ gamma() [4/5]

◆ gamma() [5/5]

◆ normal() [1/5]

◆ normal() [2/5]

◆ normal() [3/5]

◆ normal() [4/5]

◆ normal() [5/5]

◆ pareto() [1/5]

◆ pareto() [2/5]

◆ pareto() [3/5]

◆ pareto() [4/5]

◆ pareto() [5/5]

◆ power() [1/5]

◆ power() [2/5]

◆ power() [3/5]

◆ power() [4/5]

◆ power() [5/5]

◆ randint() [1/9]

◆ randint() [2/9]

◆ randint() [3/9]

◆ randint() [4/9]

◆ randint() [5/9]

◆ randint() [6/9]

◆ randint() [7/9]

◆ randint() [8/9]

◆ randint() [9/9]

◆ random() [1/5]

◆ random() [2/5]

◆ random() [3/5]

◆ random() [4/5]

◆ random() [5/5]

◆ shuffle()

◆ weibull() [1/5]

◆ weibull() [2/5]

◆ weibull() [3/5]

◆ weibull() [4/5]

◆ weibull() [5/5]