Binary factor to estimate parameters of zero-mean Gaussian white noise. More...
#include <WhiteNoiseFactor.h>
Static Public Member Functions | |
static double | f (double z, double u, double p) |
negative log likelihood as a function of mean and precision 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... | |
Private Types | |
typedef NonlinearFactor | Base |
Private Attributes | |
Key | meanKey_ |
key by which to access mean variable More... | |
Key | precisionKey_ |
key by which to access precision variable More... | |
double | z_ |
Measurement. More... | |
Standard Constructors | |
WhiteNoiseFactor (double z, Key meanKey, Key precisionKey) | |
Advanced Constructors | |
~WhiteNoiseFactor () override | |
Destructor. More... | |
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 |
Advanced Interface | |
std::shared_ptr< GaussianFactor > | linearize (const Values &x) const override |
linearize returns a Hessianfactor that is an approximation of error(p) More... | |
Additional Inherited Members | |
Public Types inherited from gtsam::NonlinearFactor | |
typedef std::shared_ptr< This > | shared_ptr |
Public Types inherited from gtsam::Factor | |
typedef KeyVector::const_iterator | const_iterator |
Const iterator over keys. More... | |
typedef KeyVector::iterator | iterator |
Iterator over keys. More... | |
Public Member Functions inherited from gtsam::NonlinearFactor | |
NonlinearFactor () | |
template<typename CONTAINER > | |
NonlinearFactor (const CONTAINER &keys) | |
virtual bool | equals (const NonlinearFactor &f, double tol=1e-9) const |
double | error (const HybridValues &c) const override |
virtual bool | active (const Values &) const |
virtual shared_ptr | clone () const |
virtual shared_ptr | rekey (const std::map< Key, Key > &rekey_mapping) const |
virtual shared_ptr | rekey (const KeyVector &new_keys) const |
virtual bool | sendable () const |
Public Member Functions inherited from gtsam::Factor | |
virtual | ~Factor ()=default |
Default destructor. More... | |
bool | empty () const |
Whether the factor is empty (involves zero variables). More... | |
Key | front () const |
First key. More... | |
Key | back () const |
Last key. More... | |
const_iterator | find (Key key) const |
find More... | |
const KeyVector & | keys () const |
Access the factor's involved variable keys. More... | |
const_iterator | begin () const |
const_iterator | end () const |
size_t | size () const |
virtual void | printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const |
print only keys More... | |
bool | equals (const This &other, double tol=1e-9) const |
check equality More... | |
KeyVector & | keys () |
iterator | begin () |
iterator | end () |
Protected Types inherited from gtsam::NonlinearFactor | |
typedef Factor | Base |
typedef NonlinearFactor | This |
Protected Member Functions inherited from gtsam::Factor | |
Factor () | |
template<typename CONTAINER > | |
Factor (const CONTAINER &keys) | |
template<typename ITERATOR > | |
Factor (ITERATOR first, ITERATOR last) | |
Static Protected Member Functions inherited from gtsam::Factor | |
template<typename CONTAINER > | |
static Factor | FromKeys (const CONTAINER &keys) |
template<typename ITERATOR > | |
static Factor | FromIterators (ITERATOR first, ITERATOR last) |
Protected Attributes inherited from gtsam::Factor | |
KeyVector | keys_ |
The keys involved in this factor. More... | |
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
Definition at line 41 of file WhiteNoiseFactor.h.
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private |
Definition at line 50 of file WhiteNoiseFactor.h.
Construct from measurement
z | Measurment value |
meanKey | Key for mean variable |
precisionKey | Key for precision variable |
Definition at line 96 of file WhiteNoiseFactor.h.
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inlineoverride |
Destructor.
Definition at line 105 of file WhiteNoiseFactor.h.
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inlineoverridevirtual |
get the dimension of the factor (number of rows on linearization)
Implements gtsam::NonlinearFactor.
Definition at line 124 of file WhiteNoiseFactor.h.
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inlineoverridevirtual |
Calculate the error of the factor, typically equal to log-likelihood.
Reimplemented from gtsam::NonlinearFactor.
Definition at line 129 of file WhiteNoiseFactor.h.
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inlinestatic |
negative log likelihood as a function of mean and precision
Definition at line 61 of file WhiteNoiseFactor.h.
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inlineoverridevirtual |
linearize returns a Hessianfactor that is an approximation of error(p)
Implements gtsam::NonlinearFactor.
Definition at line 158 of file WhiteNoiseFactor.h.
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inlinestatic |
linearize returns a Hessianfactor that approximates error Hessian is
Taylor expansion is
So f = 2 f(x), g = -df(x), G = ddf(x)
Definition at line 75 of file WhiteNoiseFactor.h.
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inlineoverridevirtual |
Print.
Reimplemented from gtsam::NonlinearFactor.
Definition at line 113 of file WhiteNoiseFactor.h.
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.
Definition at line 140 of file WhiteNoiseFactor.h.
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private |
key by which to access mean variable
Definition at line 47 of file WhiteNoiseFactor.h.
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private |
key by which to access precision variable
Definition at line 48 of file WhiteNoiseFactor.h.
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private |
Definition at line 45 of file WhiteNoiseFactor.h.