Classes
class	DistributionSampler

class	mt19937_RG

class	RandomGenerator
	Random number generator system. More...

class	ReservoirSampler
	Simple container for keeping K random values. More...

class	standard_RG
	Generator based on rand() < clib > function. More...

class	uniform_RG
	Uniform random number generator. More...

class	WeightedReservoirItem

class	WeightedReservoirSampler

class	WeightedSampler

Typedefs
typedef platform::Size	Size

typedef utility::pointer::owning_ptr < uniform_RG >	uniform_RG_OP

typedef utility::pointer::owning_ptr < uniform_RG const >	uniform_RG_COP

Enumerations
enum	RND_RunType { _RND_NormalRun_, _RND_TestRun_ }
	Different type of initialization scheme: RND_NormalRun - all instances of RandomGenerator will be pointing to just one generator. This is main production mode. We do not use multiple generators here because putting many generators will effectively produce long-range correlations between random numbers obtained from different places of program. (By using N generators instead of one we effectively reducing dimensionality of random generator by at least N. Now take in to account number of nodes in computer cluster and its look like we can quickly run in to trouble even with 600 dimensional Mersenne twister.) Somewhat helpful presentation on this topic: "Don't Trust Parallel Monte Carlo!" by Peter Hellekalek, available online at: http://random.mat.sbg.ac.at/~peter/pads98.ps. More...

Functions
static void	lshift128 (w128_t out, const w128_t in, int shift)

static uint32_t	ini_func1 (uint32_t x)

static uint32_t	ini_func2 (uint32_t x)

static int	sformat_idxof (int i)

static void	do_recursion (w128_t r, w128_t a, w128_t b, w128_t c, w128_t *lung)

double	uniform (void)

double	gaussian (void)

int	random_range (int low, int high)

uniform_RG *	createRG (string const &type)
	uniform_RG factory More...

template<class T >
void	random_permutation (utility::vector1< T > &vect, RandomGenerator &rg)

template<class T >
void	random_permutation (utility::vector0< T > &vect, RandomGenerator &rg)

template<class T >
void	random_permutation (std::vector< T > &vect, RandomGenerator &rg)

template<typename RandomAccessIterator >
void	random_permutation (RandomAccessIterator first, RandomAccessIterator last, RandomGenerator &rg)
	randomly shuffle elements of a sequence More...

numeric::Real	reservoir_sample_accept_prob (numeric::Size n_wanted, numeric::Size const n_seen)
	Returns the probability that the Nth value in a sequence should be accepted using the reservoir sampling criterion. More...

template<typename T >
utility::vector1< T >	reservoir_sample (utility::vector1< T > const &vec, numeric::Size const n_wanted, RandomGenerator &rg)

Variables
RandomGenerator	RG (0)

Typedef Documentation

typedef platform::Size numeric::random::Size

typedef utility::pointer::owning_ptr< uniform_RG const > numeric::random::uniform_RG_COP

typedef utility::pointer::owning_ptr< uniform_RG > numeric::random::uniform_RG_OP

Enumeration Type Documentation

enum numeric::random::RND_RunType

Different type of initialization scheme: RND_NormalRun - all instances of RandomGenerator will be pointing to just one generator. This is main production mode. We do not use multiple generators here because putting many generators will effectively produce long-range correlations between random numbers obtained from different places of program. (By using N generators instead of one we effectively reducing dimensionality of random generator by at least N. Now take in to account number of nodes in computer cluster and its look like we can quickly run in to trouble even with 600 dimensional Mersenne twister.) Somewhat helpful presentation on this topic: "Don't Trust Parallel Monte Carlo!" by Peter Hellekalek, available online at: http://random.mat.sbg.ac.at/~peter/pads98.ps.

RND_TestRun - each instance of RandomGenerator will have its own generator with its own seed. We using this approach because we trying to increase stability of unit test / performance tests / scientific test. WARNING: This mode design specifically for testing purpose and SHOULD NOT be used in production environment (see comment above).

Enumerator
_RND_NormalRun_
_RND_TestRun_

Function Documentation

uniform_RG* numeric::random::createRG ( string const & type )

uniform_RG factory

References utility_exit_with_message.

Referenced by numeric::random::RandomGenerator::initializeRandomGenerators().

static void numeric::random::do_recursion	(	w128_t *	r,
		w128_t *	a,
		w128_t *	b,
		w128_t *	c,
		w128_t *	lung
	)

inlinestatic

This function represents the recursion formula.

Parameters

r	output
a	a 128-bit part of the internal state array
b	a 128-bit part of the internal state array
c	a 128-bit part of the internal state array
lung	a 128-bit part of the internal state array

References DSFMT_HIGH_CONST, DSFMT_LOW_MASK, DSFMT_MSK1, DSFMT_MSK2, DSFMT_SL1, DSFMT_SL2, DSFMT_SR1, DSFMT_SR2, lshift128(), and W128_T::u.

Referenced by numeric::random::mt19937_RG::gen_rand_all().

double numeric::random::gaussian ( void )

References numeric::random::RandomGenerator::gaussian(), and RG.

static uint32_t numeric::random::ini_func1 ( uint32_t x )

inlinestatic

This function represents a function used in the initialization by init_by_array

Parameters

x	32-bit integer

Returns: 32-bit integer

Referenced by numeric::random::mt19937_RG::init_by_array().

static uint32_t numeric::random::ini_func2 ( uint32_t x )

inlinestatic

This function represents a function used in the initialization by init_by_array

Parameters

x	32-bit integer

Returns: 32-bit integer

Referenced by numeric::random::mt19937_RG::init_by_array().

static void numeric::random::lshift128	(	w128_t *	out,
		const w128_t *	in,
		int	shift
	)

inlinestatic

This function simulates SIMD 128-bit left shift by the standard C. The 128-bit integer given in in is shifted by (shift * 8) bits. This function simulates the LITTLE ENDIAN SIMD.

Parameters

out	the output of this function
in	the 128-bit data to be shifted
shift	the shift value

References W128_T::u.

Referenced by do_recursion().

template<class T >

void numeric::random::random_permutation	(	utility::vector1< T > &	vect,
		RandomGenerator &	rg
	)

References basic::T(), and numeric::random::RandomGenerator::uniform().

template<class T >

void numeric::random::random_permutation	(	utility::vector0< T > &	vect,
		RandomGenerator &	rg
	)

References basic::T(), and numeric::random::RandomGenerator::uniform().

template<class T >

void numeric::random::random_permutation	(	std::vector< T > &	vect,
		RandomGenerator &	rg
	)

References basic::T(), and numeric::random::RandomGenerator::uniform().

template<typename RandomAccessIterator >

void numeric::random::random_permutation	(	RandomAccessIterator	first,
		RandomAccessIterator	last,
		RandomGenerator &	rg
	)

randomly shuffle elements of a sequence

References numeric::random::RandomGenerator::uniform().

int numeric::random::random_range	(	int	low,
		int	high
	)

References numeric::random::RandomGenerator::random_range(), and RG.

Referenced by numeric::random::ReservoirSampler< T >::add_value().

template<typename T >

utility::vector1< T > numeric::random::reservoir_sample	(	utility::vector1< T > const &	vec,
		numeric::Size const	n_wanted,
		RandomGenerator &	rg
	)

References basic::options::OptionKeys::cutoutdomain::end, numeric::random::RandomGenerator::random_range(), reservoir_sample_accept_prob(), and numeric::random::RandomGenerator::uniform().

numeric::Real numeric::random::reservoir_sample_accept_prob	(	numeric::Size	n_wanted,
		numeric::Size const	n_seen
	)

inline

Returns the probability that the Nth value in a sequence should be accepted using the reservoir sampling criterion.

Detailed: If we've seen N values and we want to keep K of them,: the probability of the Nth value being accepted is min(K/N,1.0).

References min().

Referenced by numeric::random::ReservoirSampler< T >::add_value(), and reservoir_sample().

static int numeric::random::sformat_idxof ( int i )

inlinestatic

This function simulate a 32-bit array index overlapped to 64-bit array of LITTLE ENDIAN in BIG ENDIAN machine.

Referenced by numeric::random::mt19937_RG::init_by_array(), and numeric::random::mt19937_RG::setSeed().

double numeric::random::uniform ( void )

References RG, and numeric::random::RandomGenerator::uniform().

Referenced by numeric::random::ReservoirSampler< T >::add_value(), numeric::random::WeightedReservoirSampler< T >::consider_sample(), numeric::random::RandomGenerator::random_range(), and numeric::random::DistributionSampler< T >::sample().

Variable Documentation

RandomGenerator numeric::random::RG

Referenced by gaussian(), numeric::random::RandomGenerator::initializeRandomGenerators(), random_range(), and uniform().

Classes

Typedefs

Enumerations

Functions

Variables

Typedef Documentation

Enumeration Type Documentation

Function Documentation

Variable Documentation