Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
gtsam::noiseModel::Constrained Class Reference

#include <NoiseModel.h>

Inheritance diagram for gtsam::noiseModel::Constrained:
Inheritance graph
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Public Types

typedef std::shared_ptr< Constrainedshared_ptr
 
- Public Types inherited from gtsam::noiseModel::Diagonal
typedef std::shared_ptr< Diagonalshared_ptr
 
- Public Types inherited from gtsam::noiseModel::Gaussian
typedef std::shared_ptr< Gaussianshared_ptr
 
- Public Types inherited from gtsam::noiseModel::Base
typedef std::shared_ptr< Baseshared_ptr
 

Public Member Functions

 Constrained (const Vector &sigmas=Z_1x1)
 
bool constrained (size_t i) const
 Return true if a particular dimension is free or constrained. More...
 
bool isConstrained () const override
 true if a constrained noise mode, saves slow/clumsy dynamic casting More...
 
const Vectormu () const
 Access mu as a vector. More...
 
void print (const std::string &name) const override
 
Diagonal::shared_ptr QR (Matrix &Ab) const override
 
double squaredMahalanobisDistance (const Vector &v) const override
 
shared_ptr unit () const
 
Matrix Whiten (const Matrix &H) const override
 
Vector whiten (const Vector &v) const override
 Calculates error vector with weights applied. More...
 
void WhitenInPlace (Eigen::Block< Matrix > H) const override
 
void WhitenInPlace (Matrix &H) const override
 
 ~Constrained () override
 
- Public Member Functions inherited from gtsam::noiseModel::Diagonal
 Diagonal ()
 
double invsigma (size_t i) const
 
const Vectorinvsigmas () const
 
double precision (size_t i) const
 
const Vectorprecisions () const
 
Matrix R () const override
 
double sigma (size_t i) const
 
Vector sigmas () const override
 Calculate standard deviations. More...
 
Vector unwhiten (const Vector &v) const override
 Unwhiten an error vector. More...
 
 ~Diagonal () override
 
- Public Member Functions inherited from gtsam::noiseModel::Gaussian
virtual Matrix covariance () const
 Compute covariance matrix. More...
 
bool equals (const Base &expected, double tol=1e-9) const override
 
 Gaussian (size_t dim=1, const std::optional< Matrix > &sqrt_information={})
 
virtual Matrix information () const
 Compute information matrix. More...
 
void WhitenSystem (Matrix &A, Vector &b) const override
 
void WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const override
 
void WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const override
 
void WhitenSystem (std::vector< Matrix > &A, Vector &b) const override
 
 ~Gaussian () override
 
- Public Member Functions inherited from gtsam::noiseModel::Base
 Base (size_t dim=1)
 primary constructor More...
 
size_t dim () const
 Dimensionality. More...
 
virtual bool isUnit () const
 true if a unit noise model, saves slow/clumsy dynamic casting More...
 
virtual double loss (const double squared_distance) const
 loss function, input is Mahalanobis distance More...
 
virtual double mahalanobisDistance (const Vector &v) const
 Mahalanobis distance. More...
 
virtual Vector unweightedWhiten (const Vector &v) const
 
virtual void unwhitenInPlace (Eigen::Block< Vector > &v) const
 
virtual void unwhitenInPlace (Vector &v) const
 
virtual double weight (const Vector &v) const
 
virtual void whitenInPlace (Eigen::Block< Vector > &v) const
 
virtual void whitenInPlace (Vector &v) const
 
virtual ~Base ()
 

Static Public Member Functions

static shared_ptr All (size_t dim)
 
static shared_ptr All (size_t dim, const Vector &mu)
 
static shared_ptr All (size_t dim, double mu)
 
static shared_ptr MixedPrecisions (const Vector &mu, const Vector &precisions)
 
static shared_ptr MixedPrecisions (const Vector &precisions)
 
static shared_ptr MixedSigmas (const Vector &mu, const Vector &sigmas)
 
static shared_ptr MixedSigmas (const Vector &sigmas)
 
static shared_ptr MixedSigmas (double m, const Vector &sigmas)
 
static shared_ptr MixedVariances (const Vector &mu, const Vector &variances)
 
static shared_ptr MixedVariances (const Vector &variances)
 
- Static Public Member Functions inherited from gtsam::noiseModel::Diagonal
static shared_ptr Precisions (const Vector &precisions, bool smart=true)
 
static shared_ptr Sigmas (const Vector &sigmas, bool smart=true)
 
static shared_ptr Variances (const Vector &variances, bool smart=true)
 
- Static Public Member Functions inherited from gtsam::noiseModel::Gaussian
static shared_ptr Covariance (const Matrix &covariance, bool smart=true)
 
static shared_ptr Information (const Matrix &M, bool smart=true)
 
static shared_ptr SqrtInformation (const Matrix &R, bool smart=true)
 

Protected Member Functions

 Constrained (const Vector &mu, const Vector &sigmas)
 
- Protected Member Functions inherited from gtsam::noiseModel::Diagonal
 Diagonal (const Vector &sigmas)
 

Protected Attributes

Vector mu_
 Penalty function weight - needs to be large enough to dominate soft constraints. More...
 
- Protected Attributes inherited from gtsam::noiseModel::Diagonal
Vector invsigmas_
 
Vector precisions_
 
Vector sigmas_
 
- Protected Attributes inherited from gtsam::noiseModel::Gaussian
std::optional< Matrixsqrt_information_
 
- Protected Attributes inherited from gtsam::noiseModel::Base
size_t dim_
 

Detailed Description

A Constrained constrained model is a specialization of Diagonal which allows some or all of the sigmas to be zero, forcing the error to be zero there. All other Gaussian models are guaranteed to have a non-singular square-root information matrix, but this class is specifically equipped to deal with singular noise models, specifically: whiten will return zero on those components that have zero sigma and zero error, unchanged otherwise.

While a hard constraint may seem to be a case in which there is infinite error, we do not ever produce an error value of infinity to allow for constraints to actually be optimized rather than self-destructing if not initialized correctly.

Definition at line 390 of file NoiseModel.h.

Member Typedef Documentation

◆ shared_ptr

Definition at line 405 of file NoiseModel.h.

Constructor & Destructor Documentation

◆ Constrained() [1/2]

gtsam::noiseModel::Constrained::Constrained ( const Vector mu,
const Vector sigmas 
)
protected

Constructor that prevents any inf values from appearing in invsigmas or precisions. Allows for specifying mu.

Definition at line 340 of file NoiseModel.cpp.

◆ Constrained() [2/2]

gtsam::noiseModel::Constrained::Constrained ( const Vector sigmas = Z_1x1)

protected constructor takes sigmas. prevents any inf values from appearing in invsigmas or precisions. mu set to large default value (1000.0)

Definition at line 334 of file NoiseModel.cpp.

◆ ~Constrained()

gtsam::noiseModel::Constrained::~Constrained ( )
inlineoverride

Definition at line 415 of file NoiseModel.h.

Member Function Documentation

◆ All() [1/3]

static shared_ptr gtsam::noiseModel::Constrained::All ( size_t  dim)
inlinestatic

Fully constrained variations

Definition at line 466 of file NoiseModel.h.

◆ All() [2/3]

static shared_ptr gtsam::noiseModel::Constrained::All ( size_t  dim,
const Vector mu 
)
inlinestatic

Fully constrained variations

Definition at line 471 of file NoiseModel.h.

◆ All() [3/3]

static shared_ptr gtsam::noiseModel::Constrained::All ( size_t  dim,
double  mu 
)
inlinestatic

Fully constrained variations with a mu parameter

Definition at line 476 of file NoiseModel.h.

◆ constrained()

bool gtsam::noiseModel::Constrained::constrained ( size_t  i) const

Return true if a particular dimension is free or constrained.

Definition at line 352 of file NoiseModel.cpp.

◆ isConstrained()

bool gtsam::noiseModel::Constrained::isConstrained ( ) const
inlineoverridevirtual

true if a constrained noise mode, saves slow/clumsy dynamic casting

Reimplemented from gtsam::noiseModel::Base.

Definition at line 418 of file NoiseModel.h.

◆ MixedPrecisions() [1/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedPrecisions ( const Vector mu,
const Vector precisions 
)
static

A diagonal noise model created by specifying a Vector of precisions, some of which might be inf

Definition at line 398 of file NoiseModel.cpp.

◆ MixedPrecisions() [2/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedPrecisions ( const Vector precisions)
static

Definition at line 402 of file NoiseModel.cpp.

◆ MixedSigmas() [1/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas ( const Vector mu,
const Vector sigmas 
)
static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 346 of file NoiseModel.cpp.

◆ MixedSigmas() [2/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas ( const Vector sigmas)
static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 381 of file NoiseModel.cpp.

◆ MixedSigmas() [3/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas ( double  m,
const Vector sigmas 
)
static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 385 of file NoiseModel.cpp.

◆ MixedVariances() [1/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedVariances ( const Vector mu,
const Vector variances 
)
static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 390 of file NoiseModel.cpp.

◆ MixedVariances() [2/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedVariances ( const Vector variances)
static

Definition at line 394 of file NoiseModel.cpp.

◆ mu()

const Vector& gtsam::noiseModel::Constrained::mu ( ) const
inline

Access mu as a vector.

Definition at line 424 of file NoiseModel.h.

◆ print()

void gtsam::noiseModel::Constrained::print ( const std::string &  name) const
overridevirtual

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 358 of file NoiseModel.cpp.

◆ QR()

SharedDiagonal gtsam::noiseModel::Constrained::QR ( Matrix Ab) const
overridevirtual

Apply QR factorization to the system [A b], taking into account constraints Q' * [A b] = [R d] Dimensions: (r*m) * m*(n+1) = r*(n+1), where r = min(m,n). This routine performs an in-place factorization on Ab. Below-diagonal elements are set to zero by this routine.

Parameters
Abis the m*(n+1) augmented system matrix [A b]
Returns
diagonal noise model can be all zeros, mixed, or not-constrained

Reimplemented from gtsam::noiseModel::Gaussian.

Definition at line 472 of file NoiseModel.cpp.

◆ squaredMahalanobisDistance()

double gtsam::noiseModel::Constrained::squaredMahalanobisDistance ( const Vector v) const
overridevirtual

The squaredMahalanobisDistance function for a constrained noisemodel, for non-constrained versions, uses sigmas, otherwise uses the penalty function with mu

Reimplemented from gtsam::noiseModel::Base.

Definition at line 407 of file NoiseModel.cpp.

◆ unit()

Constrained::shared_ptr gtsam::noiseModel::Constrained::unit ( ) const

Returns a Unit version of a constrained noisemodel in which constrained sigmas remain constrained and the rest are unit scaled

Definition at line 439 of file NoiseModel.cpp.

◆ Whiten()

Matrix gtsam::noiseModel::Constrained::Whiten ( const Matrix H) const
overridevirtual

Whitening functions will perform partial whitening on rows with a non-zero sigma. Other rows remain untouched.

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 416 of file NoiseModel.cpp.

◆ whiten()

Vector gtsam::noiseModel::Constrained::whiten ( const Vector v) const
overridevirtual

Calculates error vector with weights applied.

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 364 of file NoiseModel.cpp.

◆ WhitenInPlace() [1/2]

void gtsam::noiseModel::Constrained::WhitenInPlace ( Eigen::Block< Matrix H) const
overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 432 of file NoiseModel.cpp.

◆ WhitenInPlace() [2/2]

void gtsam::noiseModel::Constrained::WhitenInPlace ( Matrix H) const
overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 425 of file NoiseModel.cpp.

Member Data Documentation

◆ mu_

Vector gtsam::noiseModel::Constrained::mu_
protected

Penalty function weight - needs to be large enough to dominate soft constraints.

Definition at line 394 of file NoiseModel.h.


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


gtsam
Author(s):
autogenerated on Thu Jun 13 2024 03:18:17