namespace for EigenRand More...

Classes
class	MersenneTwister
	A vectorized version of Mersenne Twister Engine. More...

class	PacketRandomEngineAdaptor
	Scalar adaptor for random engines which generates packet. More...

Typedefs
template<typename Derived , typename Urng >
using	RandBitsType = CwiseNullaryOp< internal::scalar_randbits_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	UniformIntType = CwiseNullaryOp< internal::scalar_uniform_int_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	BalancedType = CwiseNullaryOp< internal::scalar_balanced_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	UniformRealType = CwiseNullaryOp< internal::scalar_uniform_real_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	NormalType = CwiseNullaryOp< internal::scalar_norm_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	Normal2Type = CwiseNullaryOp< internal::scalar_norm_dist2_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	LognormalType = CwiseNullaryOp< internal::scalar_lognorm_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	ExponentialType = CwiseNullaryOp< internal::scalar_exp_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	GammaType = CwiseNullaryOp< internal::scalar_gamma_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	WeibullType = CwiseNullaryOp< internal::scalar_weibull_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	ExtremeValueType = CwiseNullaryOp< internal::scalar_extreme_value_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	ChiSquaredType = CwiseNullaryOp< internal::scalar_chi_squared_dist_op< typename Derived::Scalar, Urng >, const Derived >

template<typename Derived , typename Urng >
using	DiscreteFType = CwiseNullaryOp< internal::scalar_discrete_dist_op< typename Derived::Scalar, Urng, float >, const Derived >

template<typename Derived , typename Urng >
using	DiscreteDType = CwiseNullaryOp< internal::scalar_discrete_dist_op< typename Derived::Scalar, Urng, double >, const Derived >

template<typename Derived , typename Urng >
using	DiscreteType = CwiseNullaryOp< internal::scalar_discrete_dist_op< typename Derived::Scalar, Urng, int32_t >, const Derived >

template<typename Packet >
using	Pmt19937_64 = MersenneTwister< Packet, 312, 156, 31, 0xb5026f5aa96619e9, 29, 0x5555555555555555, 17, 0x71d67fffeda60000, 37, 0xfff7eee000000000, 43, 6364136223846793005 >
	Alias of Eigen::Rand::MersenneTwister, equivalent to std::mt19937_64. More...

using	Vmt19937_64 = std::mt19937_64
	same as std::mt19937_64 when EIGEN_DONT_VECTORIZE, Pmt19937_64<internal::Packet4i> when SSE2 enabled and Pmt19937_64<internal::Packet8i> when AVX2 enabled More...

Enumerations
enum	RandomEngineType { none, scalar, packet }

Functions
template<typename Derived , typename Urng >
const RandBitsType< Derived, Urng >	randBits (Index rows, Index cols, Urng &&urng)
	generates integers with random bits More...

template<typename Derived , typename Urng >
const RandBitsType< Derived, Urng >	randBitsLike (Derived &o, Urng &&urng)
	generates integers with random bits More...

template<typename Derived , typename Urng >
const UniformIntType< Derived, Urng >	uniformInt (Index rows, Index cols, Urng &&urng, typename Derived::Scalar min, typename Derived::Scalar max)
	generates integers with a given range `[min, max]` More...

template<typename Derived , typename Urng >
const UniformIntType< Derived, Urng >	uniformIntLike (Derived &o, Urng &&urng, typename Derived::Scalar min, typename Derived::Scalar max)
	generates integers with a given range `[min, max]` More...

template<typename Derived , typename Urng >
const BalancedType< Derived, Urng >	balanced (Index rows, Index cols, Urng &&urng)
	generates reals in a range `[-1, 1]` More...

template<typename Derived , typename Urng >
const BalancedType< Derived, Urng >	balancedLike (const Derived &o, Urng &&urng)
	generates reals in a range `[-1, 1]` More...

template<typename Derived , typename Urng >
const UniformRealType< Derived, Urng >	uniformReal (Index rows, Index cols, Urng &&urng)
	generates reals in a range `[0, 1)` More...

template<typename Derived , typename Urng >
const UniformRealType< Derived, Urng >	uniformRealLike (Derived &o, Urng &&urng)
	generates reals in a range `[0, 1)` More...

template<typename Derived , typename Urng >
const NormalType< Derived, Urng >	normal (Index rows, Index cols, Urng &&urng)
	generates reals on a standard normal distribution (`mean` = 0, `stdev`=1) More...

template<typename Derived , typename Urng >
const NormalType< Derived, Urng >	normalLike (Derived &o, Urng &&urng)
	generates reals on a standard normal distribution (`mean` = 0, `stdev`=1) More...

template<typename Derived , typename Urng >
const Normal2Type< Derived, Urng >	normal (Index rows, Index cols, Urng &&urng, typename Derived::Scalar mean, typename Derived::Scalar stdev=1)
	generates reals on a normal distribution with arbitrary `mean` and `stdev`. More...

template<typename Derived , typename Urng >
const Normal2Type< Derived, Urng >	normalLike (Derived &o, Urng &&urng, typename Derived::Scalar mean, typename Derived::Scalar stdev=1)
	generates reals on a normal distribution with arbitrary `mean` and `stdev`. More...

template<typename Derived , typename Urng >
const LognormalType< Derived, Urng >	lognormal (Index rows, Index cols, Urng &&urng, typename Derived::Scalar mean=0, typename Derived::Scalar stdev=1)
	generates reals on a lognormal distribution with arbitrary `mean` and `stdev`. More...

template<typename Derived , typename Urng >
const LognormalType< Derived, Urng >	lognormalLike (Derived &o, Urng &&urng, typename Derived::Scalar mean=0, typename Derived::Scalar stdev=1)
	generates reals on a lognormal distribution with arbitrary `mean` and `stdev`. More...

template<typename Derived , typename Urng >
const ExponentialType< Derived, Urng >	exponential (Index rows, Index cols, Urng &&urng, typename Derived::Scalar lambda=1)
	generates reals on an exponential distribution with arbitrary scale parameter. More...

template<typename Derived , typename Urng >
const ExponentialType< Derived, Urng >	exponentialLike (Derived &o, Urng &&urng, typename Derived::Scalar lambda=1)
	generates reals on an exponential distribution with arbitrary scale parameter. More...

template<typename Derived , typename Urng >
const GammaType< Derived, Urng >	gamma (Index rows, Index cols, Urng &&urng, typename Derived::Scalar alpha=1, typename Derived::Scalar beta=1)
	generates reals on a gamma distribution with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const GammaType< Derived, Urng >	gammaLike (Derived &o, Urng &&urng, typename Derived::Scalar alpha=1, typename Derived::Scalar beta=1)
	generates reals on a gamma distribution with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const WeibullType< Derived, Urng >	weibull (Index rows, Index cols, Urng &&urng, typename Derived::Scalar a=1, typename Derived::Scalar b=1)
	generates reals on a Weibull distribution with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const WeibullType< Derived, Urng >	weibullLike (Derived &o, Urng &&urng, typename Derived::Scalar a=1, typename Derived::Scalar b=1)
	generates reals on a Weibull distribution with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const ExtremeValueType< Derived, Urng >	extremeValue (Index rows, Index cols, Urng &&urng, typename Derived::Scalar a=0, typename Derived::Scalar b=1)
	generates reals on an extreme value distribution (a.k.a Gumbel Type I, log-Weibull, Fisher-Tippett Type I) with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const ExtremeValueType< Derived, Urng >	extremeValueLike (Derived &o, Urng &&urng, typename Derived::Scalar a=0, typename Derived::Scalar b=1)
	generates reals on an extreme value distribution (a.k.a Gumbel Type I, log-Weibull, Fisher-Tippett Type I) with arbitrary shape and scale parameter. More...

template<typename Derived , typename Urng >
const ChiSquaredType< Derived, Urng >	chiSquared (Index rows, Index cols, Urng &&urng, typename Derived::Scalar n=1)
	generates reals on the Chi-squared distribution with arbitrary degrees of freedom. More...

template<typename Derived , typename Urng >
const ChiSquaredType< Derived, Urng >	chiSquaredLike (Derived &o, Urng &&urng, typename Derived::Scalar n=1)
	generates reals on the Chi-squared distribution with arbitrary degrees of freedom. More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteFType< Derived, Urng >	discreteF (Index rows, Index cols, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is float(23bit precision). More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteFType< Derived, Urng >	discreteFLike (Derived &o, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is float(23bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteFType< Derived, Urng >	discreteF (Index rows, Index cols, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is float(23bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteFType< Derived, Urng >	discreteFLike (Derived &o, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is float(23bit precision). More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteDType< Derived, Urng >	discreteD (Index rows, Index cols, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is double(52bit precision). More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteDType< Derived, Urng >	discreteDLike (Derived &o, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is double(52bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteDType< Derived, Urng >	discreteD (Index rows, Index cols, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is double(52bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteDType< Derived, Urng >	discreteDLike (Derived &o, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is double(52bit precision). More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteType< Derived, Urng >	discrete (Index rows, Index cols, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is int32(32bit precision). More...

template<typename Derived , typename Urng , typename RealIter >
const DiscreteType< Derived, Urng >	discreteLike (Derived &o, Urng &&urng, RealIter first, RealIter last)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is int32(32bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteType< Derived, Urng >	discrete (Index rows, Index cols, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is int32(32bit precision). More...

template<typename Derived , typename Urng , typename Real >
const DiscreteType< Derived, Urng >	discreteLike (Derived &o, Urng &&urng, const std::initializer_list< Real > &il)
	generates random integers on the interval `[0, n)`, where the probability of each individual integer `i` is proportional to `w(i)`. The data type used for calculation of probabilities is int32(32bit precision). More...

template<typename UIntType , typename Rng >
auto	makeScalarRng (Rng &&rng) -> typename std::enable_if< IsPacketRandomEngine< typename std::remove_reference< Rng >::type >::value, PacketRandomEngineAdaptor< UIntType, typename std::remove_reference< Rng >::type > >::type
	Helper function for making a PacketRandomEngineAdaptor. More...

Detailed Description

namespace for EigenRand

Typedef Documentation

◆ Pmt19937_64

template<typename Packet >

using Eigen::Rand::Pmt19937_64 = typedef MersenneTwister<Packet, 312, 156, 31, 0xb5026f5aa96619e9, 29, 0x5555555555555555, 17, 0x71d67fffeda60000, 37, 0xfff7eee000000000, 43, 6364136223846793005>

Alias of Eigen::Rand::MersenneTwister, equivalent to std::mt19937_64.

Template Parameters

Packet

◆ Vmt19937_64

using Eigen::Rand::Vmt19937_64 = typedef std::mt19937_64

same as std::mt19937_64 when EIGEN_DONT_VECTORIZE, Pmt19937_64<internal::Packet4i> when SSE2 enabled and Pmt19937_64<internal::Packet8i> when AVX2 enabled

Function Documentation

◆ balanced()

template<typename Derived , typename Urng >

const BalancedType<Derived, Urng> Eigen::Rand::balanced	(	Index	rows,
		Index	cols,
		Urng &&	urng
	)

inline

generates reals in a range [-1, 1]

Template Parameters

Derived	a type of Eigen::DenseBase
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator

Returns: a random matrix expression with a shape (rows, cols)

◆ balancedLike()

template<typename Derived , typename Urng >

const BalancedType<Derived, Urng> Eigen::Rand::balancedLike	(	const Derived &	o,
		Urng &&	urng
	)

inline

generates reals in a range [-1, 1]

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator

Returns: a random matrix expression of the same shape as o

◆ chiSquared()

template<typename Derived , typename Urng >

const ChiSquaredType<Derived, Urng> Eigen::Rand::chiSquared	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	n = `1`
	)

inline

generates reals on the Chi-squared distribution with arbitrary degrees of freedom.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
n	the degrees of freedom of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ chiSquaredLike()

template<typename Derived , typename Urng >

const ChiSquaredType<Derived, Urng> Eigen::Rand::chiSquaredLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	n = `1`
	)

inline

generates reals on the Chi-squared distribution with arbitrary degrees of freedom.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
n	the degrees of freedom of the distribution

Returns: a random matrix expression of the same shape as o

◆ discrete() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteType<Derived, Urng> Eigen::Rand::discrete	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is int32(32bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discrete() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteType<Derived, Urng> Eigen::Rand::discrete	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is int32(32bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discreteD() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteDType<Derived, Urng> Eigen::Rand::discreteD	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is double(52bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discreteD() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteDType<Derived, Urng> Eigen::Rand::discreteD	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is double(52bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discreteDLike() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteDType<Derived, Urng> Eigen::Rand::discreteDLike	(	Derived &	o,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is double(52bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ discreteDLike() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteDType<Derived, Urng> Eigen::Rand::discreteDLike	(	Derived &	o,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is double(52bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ discreteF() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteFType<Derived, Urng> Eigen::Rand::discreteF	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is float(23bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discreteF() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteFType<Derived, Urng> Eigen::Rand::discreteF	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is float(23bit precision).

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression with a shape (rows, cols)

◆ discreteFLike() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteFType<Derived, Urng> Eigen::Rand::discreteFLike	(	Derived &	o,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is float(23bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ discreteFLike() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteFType<Derived, Urng> Eigen::Rand::discreteFLike	(	Derived &	o,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is float(23bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ discreteLike() [1/2]

template<typename Derived , typename Urng , typename Real >

const DiscreteType<Derived, Urng> Eigen::Rand::discreteLike	(	Derived &	o,
		Urng &&	urng,
		const std::initializer_list< Real > &	il
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is int32(32bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
il	an instance of `initializer_list` containing the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ discreteLike() [2/2]

template<typename Derived , typename Urng , typename RealIter >

const DiscreteType<Derived, Urng> Eigen::Rand::discreteLike	(	Derived &	o,
		Urng &&	urng,
		RealIter	first,
		RealIter	last
	)

inline

generates random integers on the interval [0, n), where the probability of each individual integer i is proportional to w(i). The data type used for calculation of probabilities is int32(32bit precision).

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
first,last	the range of elements defining the numbers to use as weights. The type of the elements referred by `RealIter` must be convertible to `double`.

Returns: a random matrix expression of the same shape as o

◆ exponential()

template<typename Derived , typename Urng >

const ExponentialType<Derived, Urng> Eigen::Rand::exponential	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	lambda = `1`
	)

inline

generates reals on an exponential distribution with arbitrary scale parameter.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
lambda	a scale parameter of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ exponentialLike()

template<typename Derived , typename Urng >

const ExponentialType<Derived, Urng> Eigen::Rand::exponentialLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	lambda = `1`
	)

inline

generates reals on an exponential distribution with arbitrary scale parameter.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
lambda	a scale parameter of the distribution

Returns: a random matrix expression of the same shape as o

◆ extremeValue()

template<typename Derived , typename Urng >

const ExtremeValueType<Derived, Urng> Eigen::Rand::extremeValue	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	a = `0`,
		typename Derived::Scalar	b = `1`
	)

inline

generates reals on an extreme value distribution (a.k.a Gumbel Type I, log-Weibull, Fisher-Tippett Type I) with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
a	a location parameter of the distribution
b	a scale parameter of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ extremeValueLike()

template<typename Derived , typename Urng >

const ExtremeValueType<Derived, Urng> Eigen::Rand::extremeValueLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	a = `0`,
		typename Derived::Scalar	b = `1`
	)

inline

generates reals on an extreme value distribution (a.k.a Gumbel Type I, log-Weibull, Fisher-Tippett Type I) with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
a	a location parameter of the distribution
b	a scale parameter of the distribution

Returns: a random matrix expression of the same shape as o

◆ gamma()

template<typename Derived , typename Urng >

const GammaType<Derived, Urng> Eigen::Rand::gamma	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	alpha = `1`,
		typename Derived::Scalar	beta = `1`
	)

inline

generates reals on a gamma distribution with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
alpha	a shape parameter of the distribution
beta	a scale parameter of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ gammaLike()

template<typename Derived , typename Urng >

const GammaType<Derived, Urng> Eigen::Rand::gammaLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	alpha = `1`,
		typename Derived::Scalar	beta = `1`
	)

inline

generates reals on a gamma distribution with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
alpha	a shape parameter of the distribution
beta	a scale parameter of the distribution

Returns: a random matrix expression of the same shape as o

◆ lognormal()

template<typename Derived , typename Urng >

const LognormalType<Derived, Urng> Eigen::Rand::lognormal	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	mean = `0`,
		typename Derived::Scalar	stdev = `1`
	)

inline

generates reals on a lognormal distribution with arbitrary mean and stdev.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
mean	a mean value of the distribution
stdev	a standard deviation value of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ lognormalLike()

template<typename Derived , typename Urng >

const LognormalType<Derived, Urng> Eigen::Rand::lognormalLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	mean = `0`,
		typename Derived::Scalar	stdev = `1`
	)

inline

generates reals on a lognormal distribution with arbitrary mean and stdev.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
mean	a mean value of the distribution
stdev	a standard deviation value of the distribution

Returns: a random matrix expression of the same shape as o

◆ makeScalarRng()

template<typename UIntType , typename Rng >

auto Eigen::Rand::makeScalarRng ( Rng && rng ) -> typename std::enable_if< IsPacketRandomEngine<typename std::remove_reference<Rng>::type>::value, PacketRandomEngineAdaptor<UIntType, typename std::remove_reference<Rng>::type> >::type

Helper function for making a PacketRandomEngineAdaptor.

Template Parameters

UIntType
Rng

Parameters

rng	any random number engine for either packet or scalar type

Returns: an instance of PacketRandomEngineAdaptor for UIntType

◆ normal() [1/2]

template<typename Derived , typename Urng >

const NormalType<Derived, Urng> Eigen::Rand::normal	(	Index	rows,
		Index	cols,
		Urng &&	urng
	)

inline

generates reals on a standard normal distribution (mean = 0, stdev=1)

Template Parameters

Derived	a type of Eigen::DenseBase
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator

Returns: a random matrix expression with a shape (rows, cols)

◆ normal() [2/2]

template<typename Derived , typename Urng >

const Normal2Type<Derived, Urng> Eigen::Rand::normal	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	mean,
		typename Derived::Scalar	stdev = `1`
	)

inline

generates reals on a normal distribution with arbitrary mean and stdev.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
mean	a mean value of the distribution
stdev	a standard deviation value of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ normalLike() [1/2]

template<typename Derived , typename Urng >

const NormalType<Derived, Urng> Eigen::Rand::normalLike	(	Derived &	o,
		Urng &&	urng
	)

inline

generates reals on a standard normal distribution (mean = 0, stdev=1)

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator

Returns: a random matrix expression of the same shape as o

◆ normalLike() [2/2]

template<typename Derived , typename Urng >

const Normal2Type<Derived, Urng> Eigen::Rand::normalLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	mean,
		typename Derived::Scalar	stdev = `1`
	)

inline

generates reals on a normal distribution with arbitrary mean and stdev.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
mean	a mean value of the distribution
stdev	a standard deviation value of the distribution

Returns: a random matrix expression of the same shape as o

◆ randBits()

template<typename Derived , typename Urng >

const RandBitsType<Derived, Urng> Eigen::Rand::randBits	(	Index	rows,
		Index	cols,
		Urng &&	urng
	)

inline

generates integers with random bits

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator

Returns: a random matrix expression with a shape (rows, cols)

◆ randBitsLike()

template<typename Derived , typename Urng >

const RandBitsType<Derived, Urng> Eigen::Rand::randBitsLike	(	Derived &	o,
		Urng &&	urng
	)

inline

generates integers with random bits

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator

Returns: a random matrix expression of the same shape as o

◆ uniformInt()

template<typename Derived , typename Urng >

const UniformIntType<Derived, Urng> Eigen::Rand::uniformInt	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	min,
		typename Derived::Scalar	max
	)

inline

generates integers with a given range [min, max]

Template Parameters

Derived	a type of Eigen::DenseBase
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
min,max	the range of integers being generated

Returns: a random matrix expression with a shape (rows, cols)

◆ uniformIntLike()

template<typename Derived , typename Urng >

const UniformIntType<Derived, Urng> Eigen::Rand::uniformIntLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	min,
		typename Derived::Scalar	max
	)

inline

generates integers with a given range [min, max]

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
min,max	the range of integers being generated

Returns: a random matrix expression of the same shape as o

◆ uniformReal()

template<typename Derived , typename Urng >

const UniformRealType<Derived, Urng> Eigen::Rand::uniformReal	(	Index	rows,
		Index	cols,
		Urng &&	urng
	)

inline

generates reals in a range [0, 1)

Template Parameters

Derived	a type of Eigen::DenseBase
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator

Returns: a random matrix expression with a shape (rows, cols)

◆ uniformRealLike()

template<typename Derived , typename Urng >

const UniformRealType<Derived, Urng> Eigen::Rand::uniformRealLike	(	Derived &	o,
		Urng &&	urng
	)

inline

generates reals in a range [0, 1)

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator

Returns: a random matrix expression of the same shape as o

◆ weibull()

template<typename Derived , typename Urng >

const WeibullType<Derived, Urng> Eigen::Rand::weibull	(	Index	rows,
		Index	cols,
		Urng &&	urng,
		typename Derived::Scalar	a = `1`,
		typename Derived::Scalar	b = `1`
	)

inline

generates reals on a Weibull distribution with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

rows	the number of rows being generated
cols	the number of columns being generated
urng	c++11-style random number generator
a	a shape parameter of the distribution
b	a scale parameter of the distribution

Returns: a random matrix expression with a shape (rows, cols)

◆ weibullLike()

template<typename Derived , typename Urng >

const WeibullType<Derived, Urng> Eigen::Rand::weibullLike	(	Derived &	o,
		Urng &&	urng,
		typename Derived::Scalar	a = `1`,
		typename Derived::Scalar	b = `1`
	)

inline

generates reals on a Weibull distribution with arbitrary shape and scale parameter.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
a	a shape parameter of the distribution
b	a scale parameter of the distribution

Returns: a random matrix expression of the same shape as o

Classes

Typedefs

Enumerations

Functions

Detailed Description

Typedef Documentation

◆ Pmt19937_64

◆ Vmt19937_64

Function Documentation

◆ balanced()

◆ balancedLike()

◆ chiSquared()

◆ chiSquaredLike()

◆ discrete() [1/2]

◆ discrete() [2/2]

◆ discreteD() [1/2]

◆ discreteD() [2/2]

◆ discreteDLike() [1/2]

◆ discreteDLike() [2/2]

◆ discreteF() [1/2]

◆ discreteF() [2/2]

◆ discreteFLike() [1/2]

◆ discreteFLike() [2/2]

◆ discreteLike() [1/2]

◆ discreteLike() [2/2]

◆ exponential()

◆ exponentialLike()

◆ extremeValue()

◆ extremeValueLike()

◆ gamma()

◆ gammaLike()

◆ lognormal()

◆ lognormalLike()

◆ makeScalarRng()

◆ normal() [1/2]

◆ normal() [2/2]

◆ normalLike() [1/2]

◆ normalLike() [2/2]

◆ randBits()

◆ randBitsLike()

◆ uniformInt()

◆ uniformIntLike()

◆ uniformReal()

◆ uniformRealLike()

◆ weibull()

◆ weibullLike()