Eigen::Rand Namespace Reference

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	StudentTType = CwiseNullaryOp< internal::scalar_student_t_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	CauchyType = CwiseNullaryOp< internal::scalar_cauchy_dist_op< typename Derived::Scalar, Urng >, const Derived >
template<typename Derived , typename Urng >
using	FisherFType = CwiseNullaryOp< internal::scalar_fisher_f_dist_op< typename Derived::Scalar, Urng >, const Derived >
template<typename Derived , typename Urng >
using	BetaType = CwiseNullaryOp< internal::scalar_beta_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 Derived , typename Urng >
using	PoissonType = CwiseNullaryOp< internal::scalar_poisson_dist_op< typename Derived::Scalar, Urng >, const Derived >
template<typename Derived , typename Urng >
using	BinomialType = CwiseNullaryOp< internal::scalar_binomial_dist_op< typename Derived::Scalar, Urng >, const Derived >
template<typename Derived , typename Urng >
using	NegativeBinomialType = CwiseNullaryOp< internal::scalar_negative_binomial_dist_op< typename Derived::Scalar, Urng >, const Derived >
template<typename Derived , typename Urng >
using	GeometricType = CwiseNullaryOp< internal::scalar_geometric_dist_op< typename Derived::Scalar, Urng >, 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...
template<typename UIntType , typename Rng >
using	UniversalRandomEngine = typename std::conditional< IsPacketRandomEngine< typename std::remove_reference< Rng >::type >::value, PacketRandomEngineAdaptor< UIntType, typename std::remove_reference< Rng >::type >, typename std::conditional< IsScalarRandomEngine< typename std::remove_reference< Rng >::type >::value, RandomEngineWrapper< typename std::remove_reference< Rng >::type >, void >::type >::type
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 StudentTType< Derived, Urng >	studentT (Index rows, Index cols, Urng &&urng, typename Derived::Scalar n=1)
	generates reals on the Student's t distribution with arbirtrary degress of freedom. More...
template<typename Derived , typename Urng >
const StudentTType< Derived, Urng >	studentTLike (Derived &o, Urng &&urng, typename Derived::Scalar n=1)
	generates reals on the Student's t distribution with arbirtrary degress of freedom. 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 >
const CauchyType< Derived, Urng >	cauchy (Index rows, Index cols, Urng &&urng, typename Derived::Scalar a=0, typename Derived::Scalar b=1)
	generates reals on the Cauchy distribution. More...
template<typename Derived , typename Urng >
const CauchyType< Derived, Urng >	cauchyLike (Derived &o, Urng &&urng, typename Derived::Scalar a=0, typename Derived::Scalar b=1)
	generates reals on the Cauchy distribution. More...
template<typename Derived , typename Urng >
const FisherFType< Derived, Urng >	fisherF (Index rows, Index cols, Urng &&urng, typename Derived::Scalar m=1, typename Derived::Scalar n=1)
	generates reals on the Fisher's F distribution. More...
template<typename Derived , typename Urng >
const FisherFType< Derived, Urng >	fisherFLike (Derived &o, Urng &&urng, typename Derived::Scalar m=1, typename Derived::Scalar n=1)
	generates reals on the Fisher's F distribution. More...
template<typename Derived , typename Urng >
const BetaType< Derived, Urng >	beta (Index rows, Index cols, Urng &&urng, typename Derived::Scalar a=1, typename Derived::Scalar b=1)
	generates reals on the beta distribution. More...
template<typename Derived , typename Urng >
const BetaType< Derived, Urng >	betaLike (Derived &o, Urng &&urng, typename Derived::Scalar a=1, typename Derived::Scalar b=1)
	generates reals on the beta distribution. 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 Derived , typename Urng >
const PoissonType< Derived, Urng >	poisson (Index rows, Index cols, Urng &&urng, double mean=1)
	generates reals on the Poisson distribution. More...
template<typename Derived , typename Urng >
const PoissonType< Derived, Urng >	poissonLike (Derived &o, Urng &&urng, double mean=1)
	generates reals on the Poisson distribution. More...
template<typename Derived , typename Urng >
const BinomialType< Derived, Urng >	binomial (Index rows, Index cols, Urng &&urng, typename Derived::Scalar trials=1, double p=0.5)
	generates reals on the binomial distribution. More...
template<typename Derived , typename Urng >
const BinomialType< Derived, Urng >	binomialLike (Derived &o, Urng &&urng, typename Derived::Scalar trials=1, double p=0.5)
	generates reals on the binomial distribution. More...
template<typename Derived , typename Urng >
const NegativeBinomialType< Derived, Urng >	negativeBinomial (Index rows, Index cols, Urng &&urng, typename Derived::Scalar trials=1, double p=0.5)
	generates reals on the negative binomial distribution. More...
template<typename Derived , typename Urng >
const NegativeBinomialType< Derived, Urng >	negativeBinomialLike (Derived &o, Urng &&urng, typename Derived::Scalar trials=1, double p=0.5)
	generates reals on the negative binomial distribution. More...
template<typename Derived , typename Urng >
const GeometricType< Derived, Urng >	geometric (Index rows, Index cols, Urng &&urng, double p=0.5)
	generates reals on the geometric distribution. More...
template<typename Derived , typename Urng >
const GeometricType< Derived, Urng >	geometricLike (Derived &o, Urng &&urng, double p=0.5)
	generates reals on the geometric distribution. More...
template<typename UIntType , typename Rng >
UniversalRandomEngine< UIntType, Rng >	makeUniversalRng (Rng &&rng)
	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

beta()

template<typename Derived , typename Urng >

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

inline

generates reals on the beta distribution.

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,b	shape parameter

Returns

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

betaLike()

template<typename Derived , typename Urng >

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

inline

generates reals on the beta distribution.

Template Parameters

Derived
Urng

Parameters

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

Returns

a random matrix expression of the same shape as o

binomial()

template<typename Derived , typename Urng >

const BinomialType<Derived, Urng> Eigen::Rand::binomial ( Index  rows, Index  cols, Urng &&  urng, typename Derived::Scalar  trials = 1, double  p = 0.5  )

inline

generates reals on the binomial distribution.

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
trials	the number of trials
p	probability of a trial generating true

Returns

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

binomialLike()

template<typename Derived , typename Urng >

const BinomialType<Derived, Urng> Eigen::Rand::binomialLike ( Derived &  o, Urng &&  urng, typename Derived::Scalar  trials = 1, double  p = 0.5  )

inline

generates reals on the binomial distribution.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
trials	the number of trials
p	probability of a trial generating true

Returns

a random matrix expression of the same shape as o

cauchy()

template<typename Derived , typename Urng >

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

inline

generates reals on the Cauchy distribution.

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)

cauchyLike()

template<typename Derived , typename Urng >

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

inline

generates reals on the Cauchy distribution.

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

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

fisherF()

template<typename Derived , typename Urng >

const FisherFType<Derived, Urng> Eigen::Rand::fisherF ( Index  rows, Index  cols, Urng &&  urng, typename Derived::Scalar  m = 1, typename Derived::Scalar  n = 1  )

inline

generates reals on the Fisher's F distribution.

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
m	degrees of freedom
n	degrees of freedom

Returns

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

fisherFLike()

template<typename Derived , typename Urng >

const FisherFType<Derived, Urng> Eigen::Rand::fisherFLike ( Derived &  o, Urng &&  urng, typename Derived::Scalar  m = 1, typename Derived::Scalar  n = 1  )

inline

generates reals on the Fisher's F distribution.

Template Parameters

Derived
Urng

Parameters

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

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

geometric()

template<typename Derived , typename Urng >

const GeometricType<Derived, Urng> Eigen::Rand::geometric ( Index  rows, Index  cols, Urng &&  urng, double  p = 0.5  )

inline

generates reals on the geometric distribution.

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
p	probability of a trial generating true

Returns

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

geometricLike()

template<typename Derived , typename Urng >

const GeometricType<Derived, Urng> Eigen::Rand::geometricLike ( Derived &  o, Urng &&  urng, double  p = 0.5  )

inline

generates reals on the geometric distribution.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
p	probability of a trial generating true

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

makeUniversalRng()

template<typename UIntType , typename Rng >

UniversalRandomEngine<UIntType, Rng> Eigen::Rand::makeUniversalRng

(

Rng &&

rng

)

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

negativeBinomial()

template<typename Derived , typename Urng >

const NegativeBinomialType<Derived, Urng> Eigen::Rand::negativeBinomial ( Index  rows, Index  cols, Urng &&  urng, typename Derived::Scalar  trials = 1, double  p = 0.5  )

inline

generates reals on the negative binomial distribution.

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
trials	the number of trial successes
p	probability of a trial generating true

Returns

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

negativeBinomialLike()

template<typename Derived , typename Urng >

const NegativeBinomialType<Derived, Urng> Eigen::Rand::negativeBinomialLike ( Derived &  o, Urng &&  urng, typename Derived::Scalar  trials = 1, double  p = 0.5  )

inline

generates reals on the negative binomial distribution.

Template Parameters

Derived
Urng

Parameters

o	an instance of any type of Eigen::DenseBase
urng	c++11-style random number generator
trials	the number of trial successes
p	probability of a trial generating true

Returns

a random matrix expression of the same shape as o

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

poisson()

template<typename Derived , typename Urng >

const PoissonType<Derived, Urng> Eigen::Rand::poisson ( Index  rows, Index  cols, Urng &&  urng, double  mean = 1  )

inline

generates reals on the Poisson distribution.

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	rate parameter

Returns

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

poissonLike()

template<typename Derived , typename Urng >

const PoissonType<Derived, Urng> Eigen::Rand::poissonLike ( Derived &  o, Urng &&  urng, double  mean = 1  )

inline

generates reals on the Poisson distribution.

Template Parameters

Derived
Urng

Parameters

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

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

studentT()

template<typename Derived , typename Urng >

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

inline

generates reals on the Student's t distribution with arbirtrary degress of freedom.

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
n	degrees of freedom

Returns

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

studentTLike()

template<typename Derived , typename Urng >

const StudentTType<Derived, Urng> Eigen::Rand::studentTLike ( Derived &  o, Urng &&  urng, typename Derived::Scalar  n = 1  )

inline

generates reals on the Student's t distribution with arbirtrary degress of freedom.

Template Parameters

Derived
Urng

Parameters

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

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