gcop::Normal< _n > Class Template Reference

#include <normal.h>

List of all members.

Public Types
typedef Matrix< double, _n, 1 >	Vectornd
typedef Matrix< double, _n, _n >	Matrixnd
Public Member Functions
	Normal (int n=1)
	Normal (const Vectornd &mu, const Matrixnd &P)
virtual	~Normal ()
double	L (const Vectornd &x) const
double	Sample (Vectornd &x)
bool	Update ()
void	Fit (const vector< pair< Vectornd, double > > xps, double a=1)
Public Attributes
Vectornd	mu
	mean
Matrixnd	P
	covariance
double	det
	determinant
Matrixnd	Pinv
	covariance inverse
bool	pd
	covariance is positive-definite
Matrixnd	A
	cholesky factor
Vectornd	rn
	normal random vector
double	norm
	normalizer
int	bd
	force a block-diagonal structure with block dimension bd (0 by default means do not enforce)
bool	bounded
	whether to enforce a box support (false by default)
Vectornd	lb
	lower bound
Vectornd	ub
	upper bound
LLT< Matrixnd >	llt
	LLT object to Cholesky.

template<int _n = Dynamic>
class gcop::Normal< _n >

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Member Typedef Documentation

template<int _n = Dynamic>

typedef Matrix<double, _n, _n> gcop::Normal< _n >::Matrixnd

template<int _n = Dynamic>

typedef Matrix<double, _n, 1> gcop::Normal< _n >::Vectornd

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Constructor & Destructor Documentation

template<int _n>

gcop::Normal< _n >::Normal

(

int

n = 1

)

n-dimensional normal distribution

Parameters:

n

dimension

References gcop::Normal< _n >::A, gcop::Normal< _n >::lb, gcop::Normal< _n >::mu, gcop::Normal< _n >::P, gcop::Normal< _n >::Pinv, gcop::Normal< _n >::rn, and gcop::Normal< _n >::ub.

template<int _n>

gcop::Normal< _n >::Normal	(	const Vectornd &	mu,
		const Matrixnd &	P
	)

n-dimensional normal distribution with mean mu and covariance P

Parameters:

mu	mean
P	covariance

References gcop::Normal< _n >::A, gcop::Normal< _n >::lb, gcop::Normal< _n >::Pinv, gcop::Normal< _n >::rn, gcop::Normal< _n >::ub, and gcop::Normal< _n >::Update().

template<int _n>

gcop::Normal< _n >::~Normal

(

)

[virtual]

---

Member Function Documentation

template<int _n>

void gcop::Normal< _n >::Fit	(	const vector< pair< Vectornd, double > >	xps,
		double	a = 1
	)

Estimate the distribution using data xs and costs cs (optional)

Parameters:

xps	data points and corresponding probabilities (should sum up to 1)
a	smoothing parameter [ mu_new = a*mu + (1-a)*mu_old ], equation to 1 by default

template<int _n>

double gcop::Normal< _n >::L

(

const Vectornd &

x

)

const

Compute likelihood of element x

Parameters:

x	n-dimensional vector

Returns:

likelihood of sample

Referenced by gcop::Normal2dView< _n >::Render().

template<int _n>

double gcop::Normal< _n >::Sample

(

Vectornd &

x

)

Sample from the distribution

Parameters:

x	n-dimensional vector to be sampled

Returns:

likelihood of sample

References gcop::random_normal().

template<int _n>

bool gcop::Normal< _n >::Update

(

)

Updates the Cholesky factor and the normalization constant

Returns:

true if covariance is positive definite

Referenced by gcop::Normal< _n >::Normal().

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Member Data Documentation

template<int _n = Dynamic>

Matrixnd gcop::Normal< _n >::A

cholesky factor

Referenced by gcop::Normal< _n >::Normal().

template<int _n = Dynamic>

int gcop::Normal< _n >::bd

force a block-diagonal structure with block dimension bd (0 by default means do not enforce)

template<int _n = Dynamic>

bool gcop::Normal< _n >::bounded

whether to enforce a box support (false by default)

template<int _n = Dynamic>

double gcop::Normal< _n >::det

determinant

template<int _n = Dynamic>

Vectornd gcop::Normal< _n >::lb

lower bound

Referenced by gcop::Normal< _n >::Normal().

template<int _n = Dynamic>

LLT<Matrixnd> gcop::Normal< _n >::llt

LLT object to Cholesky.

template<int _n = Dynamic>

Vectornd gcop::Normal< _n >::mu

mean

Referenced by gcop::Normal< _n >::Normal(), and gcop::Normal2dView< _n >::Render().

template<int _n = Dynamic>

double gcop::Normal< _n >::norm

normalizer

template<int _n = Dynamic>

Matrixnd gcop::Normal< _n >::P

covariance

Referenced by gcop::Normal< _n >::Normal(), and gcop::Normal2dView< _n >::Render().

template<int _n = Dynamic>

bool gcop::Normal< _n >::pd

covariance is positive-definite

template<int _n = Dynamic>

Matrixnd gcop::Normal< _n >::Pinv

covariance inverse

Referenced by gcop::Normal< _n >::Normal().

template<int _n = Dynamic>

Vectornd gcop::Normal< _n >::rn

normal random vector

Referenced by gcop::Normal< _n >::Normal().

template<int _n = Dynamic>

Vectornd gcop::Normal< _n >::ub

upper bound

Referenced by gcop::Normal< _n >::Normal().

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

• lib/utils/normal.h