mlpack::math Namespace Reference

Miscellaneous math routines. More...

Classes
class	Range
	Simple real-valued range. More...
Functions
void	Center (const arma::mat &x, arma::mat &xCentered)
	Creates a centered matrix, where centering is done by subtracting the sum over the columns (a column vector) from each column of the matrix.
double	ClampNonNegative (const double d)
	Forces a number to be non-negative, turning negative numbers into zero.
double	ClampNonPositive (const double d)
	Forces a number to be non-positive, turning positive numbers into zero.
double	ClampRange (double value, const double rangeMin, const double rangeMax)
	Clamp a number between a particular range.
void	Orthogonalize (arma::mat &x)
	Orthogonalize x in-place.
void	Orthogonalize (const arma::mat &x, arma::mat &W)
	Orthogonalize x and return the result in W, using eigendecomposition.
int	RandInt (const int lo, const int hiExclusive)
	Generates a uniform random integer.
int	RandInt (const int hiExclusive)
	Generates a uniform random integer.
double	RandNormal (const double mean, const double variance)
	Generates a normally distributed random number with specified mean and variance.
double	RandNormal ()
	Generates a normally distributed random number with mean 0 and variance 1.
double	Random (const double lo, const double hi)
	Generates a uniform random number in the specified range.
double	Random ()
	Generates a uniform random number between 0 and 1.
void	RandomSeed (const size_t seed)
	Set the random seed used by the random functions (Random() and RandInt()).
void	RandVector (arma::vec &v)
	Overwrites a dimension-N vector to a random vector on the unit sphere in R^N.
void	RemoveRows (const arma::mat &input, const std::vector< size_t > &rowsToRemove, arma::mat &output)
	Remove a certain set of rows in a matrix while copying to a second matrix.
void	VectorPower (arma::vec &vec, double power)
	Auxiliary function to raise vector elements to a specific power.
void	WhitenUsingEig (const arma::mat &x, arma::mat &xWhitened, arma::mat &whiteningMatrix)
	Whitens a matrix using the eigendecomposition of the covariance matrix.
void	WhitenUsingSVD (const arma::mat &x, arma::mat &xWhitened, arma::mat &whiteningMatrix)
	Whitens a matrix using the singular value decomposition of the covariance matrix.
Variables
boost::mt19937	randGen
boost::normal_distribution	randNormalDist
boost::uniform_01 < boost::mt19937, double >	randUniformDist

Detailed Description

Miscellaneous math routines.

Function Documentation

void mlpack::math::Center	(	const arma::mat &	x,
		arma::mat &	xCentered
	)

Creates a centered matrix, where centering is done by subtracting the sum over the columns (a column vector) from each column of the matrix.

Parameters:

	x	Input matrix
	xCentered	Matrix to write centered output into

double mlpack::math::ClampNonNegative ( const double d ) [inline]

Forces a number to be non-negative, turning negative numbers into zero.

Avoids branching costs (this is a measurable improvement).

Parameters:

d

Double to clamp.

Returns:: 0 if d < 0, d otherwise.

Definition at line 38 of file clamp.hpp.

Referenced by ClampRange().

double mlpack::math::ClampNonPositive ( const double d ) [inline]

Forces a number to be non-positive, turning positive numbers into zero.

Avoids branching costs (this is a measurable improvement).

Parameters:

	d	Double to clamp.
	0	if d > 0, d otherwise.

Definition at line 50 of file clamp.hpp.

Referenced by ClampRange().

double mlpack::math::ClampRange	(	double	value,
		const double	rangeMin,
		const double	rangeMax
	)			`[inline]`

Clamp a number between a particular range.

Parameters:

	value	The number to clamp.
	rangeMin	The first of the range.
	rangeMax	The last of the range.

Returns:: max(rangeMin, min(rangeMax, d)).

Definition at line 63 of file clamp.hpp.

References ClampNonNegative(), and ClampNonPositive().

void mlpack::math::Orthogonalize ( arma::mat & x )

Orthogonalize x in-place.

This could be sped up by a custom implementation.

void mlpack::math::Orthogonalize	(	const arma::mat &	x,
		arma::mat &	W
	)

Orthogonalize x and return the result in W, using eigendecomposition.

We will be using the formula $W = x (x^T x)^{-0.5}$ .

int mlpack::math::RandInt	(	const int	lo,
		const int	hiExclusive
	)			`[inline]`

Generates a uniform random integer.

Definition at line 117 of file random.hpp.

References randGen, and randUniformDist.

int mlpack::math::RandInt ( const int hiExclusive ) [inline]

Generates a uniform random integer.

Definition at line 103 of file random.hpp.

References randGen, and randUniformDist.

Referenced by mlpack::sparse_coding::DataDependentRandomInitializer::Initialize(), and mlpack::nmf::RandomAcolInitialization< p >::Initialize().

double mlpack::math::RandNormal	(	const double	mean,
		const double	variance
	)			`[inline]`

Generates a normally distributed random number with specified mean and variance.

Parameters:

	mean	Mean of distribution.
	variance	Variance of distribution.

Definition at line 146 of file random.hpp.

References randGen, and randNormalDist.

double mlpack::math::RandNormal ( ) [inline]

Generates a normally distributed random number with mean 0 and variance 1.

Definition at line 134 of file random.hpp.

References randGen, and randNormalDist.

double mlpack::math::Random	(	const double	lo,
		const double	hi
	)			`[inline]`

Generates a uniform random number in the specified range.

Definition at line 89 of file random.hpp.

References randGen, and randUniformDist.

double mlpack::math::Random ( ) [inline]

Generates a uniform random number between 0 and 1.

Definition at line 75 of file random.hpp.

References randGen, and randUniformDist.

void mlpack::math::RandomSeed ( const size_t seed ) [inline]

Set the random seed used by the random functions (Random() and RandInt()).

The seed is casted to a 32-bit integer before being given to the random number generator, but a size_t is taken as a parameter for API consistency.

Parameters:

seed

Seed for the random number generator.

Definition at line 66 of file random.hpp.

References randGen.

void mlpack::math::RandVector ( arma::vec & v )

Overwrites a dimension-N vector to a random vector on the unit sphere in R^N.

void mlpack::math::RemoveRows	(	const arma::mat &	input,
		const std::vector< size_t > &	rowsToRemove,
		arma::mat &	output
	)

Remove a certain set of rows in a matrix while copying to a second matrix.

Parameters:

	input	Input matrix to copy.
	rowsToRemove	Vector containing indices of rows to be removed.
	output	Matrix to copy non-removed rows into.

void mlpack::math::VectorPower	(	arma::vec &	vec,
		double	power
	)

Auxiliary function to raise vector elements to a specific power.

The sign is ignored in the power operation and then re-added. Useful for eigenvalues.

void mlpack::math::WhitenUsingEig	(	const arma::mat &	x,
		arma::mat &	xWhitened,
		arma::mat &	whiteningMatrix
	)

Whitens a matrix using the eigendecomposition of the covariance matrix.

Whitening means the covariance matrix of the result is the identity matrix.

void mlpack::math::WhitenUsingSVD	(	const arma::mat &	x,
		arma::mat &	xWhitened,
		arma::mat &	whiteningMatrix
	)

Whitens a matrix using the singular value decomposition of the covariance matrix.

Whitening means the covariance matrix of the result is the identity matrix.

Variable Documentation

boost::mt19937 mlpack::math::randGen

Referenced by RandInt(), RandNormal(), Random(), and RandomSeed().

boost::normal_distribution mlpack::math::randNormalDist

Referenced by RandNormal().

boost::uniform_01<boost::mt19937, double> mlpack::math::randUniformDist

Referenced by RandInt(), and Random().

mlpack::math Namespace Reference

Classes

Functions

Variables

Detailed Description

Function Documentation

Variable Documentation