Detailed Description

Binary factor to estimate parameters of zero-mean Gaussian white noise.

This factor uses the mean-precision parameterization.

Takes three template arguments: Key: key type to use for mean Key: key type to use for precision Values: Values type for optimization

Inheritance diagram for gtsam::WhiteNoiseFactor:

Standard Constructors
	WhiteNoiseFactor (double z, Key meanKey, Key precisionKey)
	Construct from measurement. More...

Advanced Constructors
	~WhiteNoiseFactor () override
	Destructor.

Testable
void	print (const std::string &p="WhiteNoiseFactor", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const override
	Print. More...

Standard Interface
size_t	dim () const override
	get the dimension of the factor (number of rows on linearization) More...

double	error (const Values &x) const override
	Calculate the error of the factor, typically equal to log-likelihood. More...

virtual Vector	unwhitenedError (const Values &x) const
	Vector of errors "unwhitened" does not make sense for this factor What is meant typically is only "e" above Here we shoehorn sqrt(2*error(p)) TODO: Where is this used? should disappear.

Advanced Interface
boost::shared_ptr< GaussianFactor >	linearize (const Values &x) const override
	linearize returns a Hessianfactor that is an approximation of error(p) More...

Static Public Member Functions
static double	f (double z, double u, double p)
	negative log likelihood as a function of mean \( \mu \) and precision \( \tau \) More...

static HessianFactor::shared_ptr	linearize (double z, double u, double p, Key j1, Key j2)
	linearize returns a Hessianfactor that approximates error Hessian is More...

Additional Inherited Members
Public Member Functions inherited from gtsam::NonlinearFactor
	NonlinearFactor ()
	Default constructor for I/O only.

template<typename CONTAINER >
	NonlinearFactor (const CONTAINER &keys)
	Constructor from a collection of the keys involved in this factor.

virtual bool	equals (const NonlinearFactor &f, double tol=1e-9) const
	Check if two factors are equal. More...

virtual	~NonlinearFactor ()
	Destructor.

virtual bool	active (const Values &) const
	Checks whether a factor should be used based on a set of values. More...

virtual shared_ptr	clone () const
	Creates a shared_ptr clone of the factor - needs to be specialized to allow for subclasses. More...

virtual shared_ptr	rekey (const std::map< Key, Key > &rekey_mapping) const
	Creates a shared_ptr clone of the factor with different keys using a map from old->new keys. More...

virtual shared_ptr	rekey (const KeyVector &new_keys) const
	Clones a factor and fully replaces its keys. More...

virtual bool	sendable () const
	Should the factor be evaluated in the same thread as the caller This is to enable factors that has shared states (like the Python GIL lock) More...

Public Member Functions inherited from gtsam::Factor
virtual	~Factor ()=default
	Default destructor.

KeyVector &	keys ()

iterator	begin ()
	Iterator at beginning of involved variable keys.

iterator	end ()
	Iterator at end of involved variable keys.

virtual void	printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const
	print only keys More...

Key	front () const
	First key.

Key	back () const
	Last key.

const_iterator	find (Key key) const
	find

const KeyVector &	keys () const
	Access the factor's involved variable keys.

const_iterator	begin () const
	Iterator at beginning of involved variable keys.

const_iterator	end () const
	Iterator at end of involved variable keys.

size_t	size () const

Public Types inherited from gtsam::NonlinearFactor
typedef boost::shared_ptr< This >	shared_ptr

Public Types inherited from gtsam::Factor
typedef KeyVector::iterator	iterator
	Iterator over keys.

typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys.

Protected Types inherited from gtsam::NonlinearFactor
typedef Factor	Base

typedef NonlinearFactor	This

Protected Member Functions inherited from gtsam::Factor
	Factor ()
	Default constructor for I/O.

template<typename CONTAINER >
	Factor (const CONTAINER &keys)
	Construct factor from container of keys. More...

template<typename ITERATOR >
	Factor (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys. More...

bool	equals (const This &other, double tol=1e-9) const
	check equality

Static Protected Member Functions inherited from gtsam::Factor
template<typename CONTAINER >
static Factor	FromKeys (const CONTAINER &keys)
	Construct factor from container of keys. More...

template<typename ITERATOR >
static Factor	FromIterators (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys. More...

Protected Attributes inherited from gtsam::Factor
KeyVector	keys_
	The keys involved in this factor.

Constructor & Destructor Documentation

◆ WhiteNoiseFactor()

gtsam::WhiteNoiseFactor::WhiteNoiseFactor	(	double	z,
		Key	meanKey,
		Key	precisionKey
	)

inline

Construct from measurement.

Parameters

z	Measurment value
meanKey	Key for mean variable
precisionKey	Key for precision variable

Member Function Documentation

◆ dim()

size_t gtsam::WhiteNoiseFactor::dim ( ) const

inlineoverridevirtual

get the dimension of the factor (number of rows on linearization)

Implements gtsam::NonlinearFactor.

◆ error()

double gtsam::WhiteNoiseFactor::error ( const Values & x ) const

inlineoverridevirtual

Calculate the error of the factor, typically equal to log-likelihood.

Implements gtsam::NonlinearFactor.

◆ f()

static double gtsam::WhiteNoiseFactor::f	(	double	z,
		double	u,
		double	p
	)

inlinestatic

negative log likelihood as a function of mean \( \mu \) and precision \( \tau \)

\[ f(z, \tau, \mu) = -\log \left( \frac{\sqrt{\tau}}{\sqrt{2\pi}} \exp(-0.5\tau(z-\mu)^2) \right) = \log(\sqrt{2\pi}) - 0.5* \log(\tau) + 0.5\tau(z-\mu)^2 \]

◆ linearize() [1/2]

boost::shared_ptr< GaussianFactor > gtsam::WhiteNoiseFactor::linearize ( const Values & x ) const

inlineoverridevirtual

linearize returns a Hessianfactor that is an approximation of error(p)

Implements gtsam::NonlinearFactor.

◆ linearize() [2/2]

static HessianFactor::shared_ptr gtsam::WhiteNoiseFactor::linearize	(	double	z,
		double	u,
		double	p,
		Key	j1,
		Key	j2
	)

inlinestatic

linearize returns a Hessianfactor that approximates error Hessian is

\[ 0.5f - x^T g + 0.5*x^T G x \]

Taylor expansion is

\[ f(x+dx) = f(x) + df(x) dx + 0.5 ddf(x) dx^2 \]

So f = 2 f(x), g = -df(x), G = ddf(x)

◆ print()

void gtsam::WhiteNoiseFactor::print	(	const std::string &	p = `"WhiteNoiseFactor"`,
		const KeyFormatter &	keyFormatter = `DefaultKeyFormatter`
	)		const

inlineoverridevirtual

Print.

Reimplemented from gtsam::NonlinearFactor.

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

/Users/dellaert/git/github/gtsam/nonlinear/WhiteNoiseFactor.h

Detailed Description

Standard Constructors

Advanced Constructors

Testable

Standard Interface

Advanced Interface

Static Public Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

◆ WhiteNoiseFactor()

Member Function Documentation

◆ dim()

◆ error()

◆ f()

◆ linearize() [1/2]

◆ linearize() [2/2]

◆ print()