Detailed Description

class SRIleastSquares inherits SRI and implements a general least squares algorithm using SRI, including weighted, linear or linearized, robust and/or sequential algorithms.

At any point the state X and covariance P are related to the SRI by X = inverse(R) * z , P = inverse(R) * inverse(transpose(R)), or R = upper triangular square root (Cholesky decomposition) of the inverse of P, and z = R * X.

Definition at line 71 of file SRIleastSquares.hpp.

#include <SRIleastSquares.hpp>

Inheritance diagram for gnsstk::SRIleastSquares:

[legend]

Public Types
using	LSFFunc = void(*)(Vector< double > &X, Vector< double > &f, Matrix< double > &P)
	Function to fit. More...

Public Member Functions
double	conditionNumber ()

double	convergence ()

int	dataUpdate (Vector< double > &D, Vector< double > &X, Matrix< double > &Cov, LSFFunc LSF)

bool	isValid ()

int	iterations ()

SRIleastSquares &	operator= (const SRIleastSquares &right)

void	reset (const int N=0)

Vector< double >	solution ()

	SRIleastSquares ()
	empty constructor More...

	SRIleastSquares (const Matrix< double > &R, const Vector< double > &Z, const Namelist &NL)

	SRIleastSquares (const Namelist &NL)

	SRIleastSquares (const SRIleastSquares &right)

	SRIleastSquares (const unsigned int N)

void	zeroAll ()

Public Member Functions inherited from gnsstk::SRI
void	addAPriori (const Matrix< double > &Cov, const Vector< double > &X)

void	addAPrioriInformation (const Matrix< double > &ICov, const Vector< double > &X)

SRI &	append (const SRI &S)

void	getConditionNumber (double &small, double &big) const

std::string	getName (const unsigned int in) const

Namelist	getNames () const

Matrix< double >	getR () const

void	getState (Vector< double > &X, int *ptrSingularIndex=NULL) const

void	getStateAndCovariance (Vector< double > &X, Matrix< double > &C, double ptrSmall=NULL, double ptrBig=NULL) const

Vector< double >	getZ () const

unsigned int	index (std::string &name)

void	measurementUpdate (Matrix< double > &Partials, Vector< double > &Data)

void	measurementUpdate (SparseMatrix< double > &Partials, Vector< double > &Data)

void	merge (const SRI &S)

SRI &	operator+= (const Namelist &NL)

SRI &	operator+= (const SRI &S)

SRI &	operator= (const SRI &right)
	operator= More...

void	permute (const Namelist &NL)

void	Qbump (const unsigned int in, double q=0.0)

void	reshape (const Namelist &NL)

void	retriangularize (const Matrix< double > &A)

void	retriangularize (Matrix< double > RR, Vector< double > ZZ)

void	setFromCovState (const Matrix< double > &Cov, const Vector< double > &State, const Namelist &NL)

bool	setName (const unsigned int in, const std::string &label)

void	shift (const Vector< double > &X0)

void	shiftZ (const Vector< double > &Z0)

unsigned int	size () const

void	split (const Namelist &NL, SRI &S)

	SRI ()
	empty constructor More...

	SRI (const Matrix< double > &R, const Vector< double > &Z, const Namelist &NL)

	SRI (const Namelist &NL)

	SRI (const SRI &s)
	copy constructor More...

	SRI (const unsigned int N)

void	stateFix (const std::string &name, double value, double sigma, bool restore)

void	stateFix (const unsigned int index, double value, double sigma, bool restore)

void	stateFixAndRemove (const Namelist &drops, const Vector< double > &values)

void	stateFixAndRemove (const unsigned int index, double value)

void	transform (const Matrix< double > &invT, const Namelist &NL)

void	zeroAll (const unsigned int n=0)

void	zeroOne (const unsigned int n)

void	zeroState ()
	Zero out (set all elements to zero) the state (Vector Z) only. More...

Public Attributes
double	convergenceLimit
	limit on the RSS change in solution which produces success More...

double	divergenceLimit
	upper limit on the RSS change in solution which produces an abort More...

bool	doLinearize

bool	doRobust

bool	doSequential

bool	doVerbose
	if true, output intermediate results More...

bool	doWeight

int	iterationsLimit
	limit on the number of iterations More...

Private Member Functions
void	defaults ()
	initialization used by constructors - leastSquaresEstimation() only More...

Private Attributes
double	conditionNum
	condition number, defined in inversion to get state and covariance More...

int	numberBatches
	current number of batches seen More...

int	numberIterations
	current number of iterations More...

double	rmsConvergence
	RMS change in state, used for convergence test. More...

bool	valid
	indicates if the filter is valid - set false when singular More...

Vector< double >	Xsave
	solution X consistent with current information RX=z More...

Friends
std::ostream &	operator<< (std::ostream &s, const SRIleastSquares &srif)
	output operator More...

Additional Inherited Members
Protected Attributes inherited from gnsstk::SRI
Namelist	names
	Namelist parallel to R and Z, labelling the elements of the state vector. More...

Matrix< double >	R
	Information matrix, an upper triangular (square) matrix. More...

Vector< double >	Z
	SRI state vector, of length equal to the dimension (row and col) of R. More...

Member Typedef Documentation

◆ LSFFunc

using gnsstk::SRIleastSquares::LSFFunc = void (*)(Vector<double>& X, Vector<double>& f, Matrix<double>& P)

Function to fit.

Definition at line 76 of file SRIleastSquares.hpp.

Constructor & Destructor Documentation

◆ SRIleastSquares() [1/5]

gnsstk::SRIleastSquares::SRIleastSquares ( )

empty constructor

Definition at line 61 of file SRIleastSquares.cpp.

◆ SRIleastSquares() [2/5]

gnsstk::SRIleastSquares::SRIleastSquares ( const unsigned int N )

constructor given the dimension N.

Parameters

N	dimension of the SRIleastSquares.

Definition at line 65 of file SRIleastSquares.cpp.

◆ SRIleastSquares() [3/5]

gnsstk::SRIleastSquares::SRIleastSquares ( const Namelist & NL )

constructor given a Namelist; its dimension determines the SRI dimension.

Parameters

NL	Namelist for the SRIleastSquares.

Definition at line 75 of file SRIleastSquares.cpp.

◆ SRIleastSquares() [4/5]

gnsstk::SRIleastSquares::SRIleastSquares	(	const Matrix< double > &	R,
		const Vector< double > &	Z,
		const Namelist &	NL
	)

explicit constructor - throw if the dimensions are inconsistent.

Parameters

R	Initial information matrix, an upper triangular matrix of dim N.
Z	Initial information data vector, of length N.
NL	Namelist for the SRIleastSquares, also of length N.

Exceptions

MatrixException if dimensions are not consistent.

Definition at line 89 of file SRIleastSquares.cpp.

◆ SRIleastSquares() [5/5]

gnsstk::SRIleastSquares::SRIleastSquares ( const SRIleastSquares & right )

inline

copy constructor

Parameters

right SRIleastSquares to be copied

Definition at line 108 of file SRIleastSquares.hpp.

Member Function Documentation

◆ conditionNumber()

double gnsstk::SRIleastSquares::conditionNumber ( )

inline

Get the condition number of the covariance matrix from last calls to leastSquaresEstimation() (Larger means 'closer to singular' except zero means condition number is infinite)

Definition at line 200 of file SRIleastSquares.hpp.

◆ convergence()

double gnsstk::SRIleastSquares::convergence ( )

inline

Get the convergence value found in last call to leastSquaresEstimation()

Returns: the convergence value

Definition at line 193 of file SRIleastSquares.hpp.

◆ dataUpdate()

int gnsstk::SRIleastSquares::dataUpdate	(	Vector< double > &	D,
		Vector< double > &	X,
		Matrix< double > &	Cov,
		LSFFunc	LSF
	)

A general least squares update, NOT the SRIF (Kalman) measurement update. Given data and measurement covariance, compute a solution and covariance using the appropriate least squares algorithm.

Parameters

D	Data vector, length M Input: raw data Output: post-fit residuals
X	Solution vector, length N Input: nominal solution X0 (zero when doLinearized is false) Output: final solution
Cov	Covariance matrix, dimension (N,N) Input: (If doWeight is true) inverse measurement covariance or weight matrix(M,M) Output: Solution covariance matrix (N,N)
LSF	Pointer to a function which is used to define the equation to be solved. LSF arguments are: X Nominal solution (input) f Values of the equation f(X) (length M) (output) P Partials matrix df/dX evaluated at X (dimension M,N) (output) When doLinearize is false, LSF ignores X and returns the (constant) partials matrix P and zero for f(X).

Exceptions

MatrixException if the input is inconsistent Return values: 0 ok -1 Problem is underdetermined (M<N) // TD – naturalized sol? -2 Problem is singular -3 Algorithm failed to converge -4 Algorithm diverged

Definition at line 271 of file SRIleastSquares.cpp.

◆ defaults()

void gnsstk::SRIleastSquares::defaults ( )

inlineprivate

initialization used by constructors - leastSquaresEstimation() only

Definition at line 243 of file SRIleastSquares.hpp.

◆ isValid()

bool gnsstk::SRIleastSquares::isValid ( )

inline

Return true if the solution is valid, i.e. if the problem is non-singular.

Definition at line 163 of file SRIleastSquares.hpp.

◆ iterations()

int gnsstk::SRIleastSquares::iterations ( )

inline

Get the number of iterations used in last call to leastSquaresEstimation()

Returns: the number of iterations

Definition at line 186 of file SRIleastSquares.hpp.

◆ operator=()

SRIleastSquares & gnsstk::SRIleastSquares::operator= ( const SRIleastSquares & right )

operator=

Parameters

right SRIleastSquares to be copied

Definition at line 111 of file SRIleastSquares.cpp.

◆ reset()

void gnsstk::SRIleastSquares::reset ( const int N = 0 )

reset the computation, i.e. remove all stored information, and optionally change the dimension. If N is not input, the dimension is not changed.

Parameters

N	new SRIleastSquares dimension (optional).

Exceptions

Exception

Definition at line 628 of file SRIleastSquares.cpp.

◆ solution()

Vector<double> gnsstk::SRIleastSquares::solution ( )

inline

Get the current solution vector

Returns: current solution vector

Definition at line 179 of file SRIleastSquares.hpp.

◆ zeroAll()

void gnsstk::SRIleastSquares::zeroAll ( )

remove all stored information by setting the SRI to zero (does not re-dimension).

Definition at line 616 of file SRIleastSquares.cpp.

Friends And Related Function Documentation

◆ operator<<

std::ostream& operator<<	(	std::ostream &	s,
		const SRIleastSquares &	srif
	)

friend

output operator

Member Data Documentation

◆ conditionNum

double gnsstk::SRIleastSquares::conditionNum

private

condition number, defined in inversion to get state and covariance

Definition at line 282 of file SRIleastSquares.hpp.

◆ convergenceLimit

double gnsstk::SRIleastSquares::convergenceLimit

limit on the RSS change in solution which produces success

Definition at line 207 of file SRIleastSquares.hpp.

◆ divergenceLimit

double gnsstk::SRIleastSquares::divergenceLimit

upper limit on the RSS change in solution which produces an abort

Definition at line 210 of file SRIleastSquares.hpp.

◆ doLinearize

bool gnsstk::SRIleastSquares::doLinearize

if true, equation F(X)=D is non-linear, the algorithm will be iterated, and LSF must return partials matrix and F(X). - default is false

Definition at line 236 of file SRIleastSquares.hpp.

◆ doRobust

bool gnsstk::SRIleastSquares::doRobust

if true, weight the equation using robust statistical techniques

default is false (NB robust & sequential doesn't make much sense)

Definition at line 223 of file SRIleastSquares.hpp.

◆ doSequential

bool gnsstk::SRIleastSquares::doSequential

if true, save information for a sequential solution - default is false (NB robust & sequential doesn't make much sense)

Definition at line 229 of file SRIleastSquares.hpp.

◆ doVerbose

bool gnsstk::SRIleastSquares::doVerbose

if true, output intermediate results

Definition at line 239 of file SRIleastSquares.hpp.

◆ doWeight

bool gnsstk::SRIleastSquares::doWeight

if true, weight the equation using the inverse of covariance matrix on input - default is false

Definition at line 216 of file SRIleastSquares.hpp.

◆ iterationsLimit

int gnsstk::SRIleastSquares::iterationsLimit

limit on the number of iterations

Definition at line 204 of file SRIleastSquares.hpp.

◆ numberBatches

int gnsstk::SRIleastSquares::numberBatches

private

current number of batches seen

Definition at line 276 of file SRIleastSquares.hpp.

◆ numberIterations

int gnsstk::SRIleastSquares::numberIterations

private

current number of iterations

Definition at line 273 of file SRIleastSquares.hpp.

◆ rmsConvergence

double gnsstk::SRIleastSquares::rmsConvergence

private

RMS change in state, used for convergence test.

Definition at line 279 of file SRIleastSquares.hpp.

◆ valid

bool gnsstk::SRIleastSquares::valid

private

indicates if the filter is valid - set false when singular

Definition at line 270 of file SRIleastSquares.hpp.

◆ Xsave

Vector<double> gnsstk::SRIleastSquares::Xsave

private

solution X consistent with current information RX=z

Definition at line 285 of file SRIleastSquares.hpp.

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

Detailed Description

Public Types

Public Member Functions

Public Attributes

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Member Typedef Documentation

◆ LSFFunc

Constructor & Destructor Documentation

◆ SRIleastSquares() [1/5]

◆ SRIleastSquares() [2/5]

◆ SRIleastSquares() [3/5]

◆ SRIleastSquares() [4/5]

◆ SRIleastSquares() [5/5]

Member Function Documentation

◆ conditionNumber()

◆ convergence()

◆ dataUpdate()

◆ defaults()

◆ isValid()

◆ iterations()

◆ operator=()

◆ reset()

◆ solution()

◆ zeroAll()

Friends And Related Function Documentation

◆ operator<<

Member Data Documentation

◆ conditionNum

◆ convergenceLimit

◆ divergenceLimit

◆ doLinearize

◆ doRobust

◆ doSequential

◆ doVerbose

◆ doWeight

◆ iterationsLimit

◆ numberBatches

◆ numberIterations

◆ rmsConvergence

◆ valid

◆ Xsave