Classes
struct	all_eig_symm_work
	workspace for subroutine allEigSymm More...

struct	evaluate_model_work
	workspace for subroutine evaluateModel More...

struct	get_svd_J_work
	workspace for subroutine getSvdJ More...

struct	max_eig_work
	workspace for subroutine max_eig More...

struct	min_eig_symm_work
	workspace for subroutine min_eig_work More...

struct	nlls_inform
	inform derived type with component defaults More...

struct	nlls_options

struct	NLLS_workspace
	all workspaces called from the top level More...

struct	solve_general_work
	workspace for subroutine solve_general More...

struct	solve_LLS_work
	workspace for subroutine solve_LLS More...

Functions
void	allEigSymm (const DoubleFortranMatrix &A, DoubleFortranVector &ew, DoubleFortranMatrix &ev)
	Calculate all the eigenvalues of a symmetric matrix. More...

void	applyScaling (const DoubleFortranMatrix &J, DoubleFortranMatrix &A, DoubleFortranVector &v, DoubleFortranVector &scale, const nlls_options &options)
	Apply_scaling input Jacobian matrix, J ouput scaled Hessisan, H, and J^Tf, v. More...

double	calculateRho (double normf, double normfnew, double md, const nlls_options &options)
	Calculate the quantity 0.5\|\|f\|\|^2 - 0.5\|\|fnew\|\|^2 actual_reduction rho = -----------------------— = ----------------— m_k(0) - m_k(d) predicted_reduction. More...

double	dotProduct (const DoubleFortranVector &x, const DoubleFortranVector &y)
	Dot product of two vectors. More...

double	evaluateModel (const DoubleFortranVector &f, const DoubleFortranMatrix &J, const DoubleFortranMatrix &hf, const DoubleFortranVector &d, const nlls_options &options, evaluate_model_work &w)
	Input: f = f(x_k), J = J(x_k), hf = \sum_{i=1}^m f_i(x_k) \nabla^2 f_i(x_k) (or an approx) More...

void MANTID_CURVEFITTING_DLL	getSvdJ (const DoubleFortranMatrix &J, double &s1, double &sn)
	Given an (m x n) matrix J held by columns as a vector, this routine returns the largest and smallest singular values of J. More...

void MANTID_CURVEFITTING_DLL	matmultInner (const DoubleFortranMatrix &J, DoubleFortranMatrix &A)
	Takes an m x n matrix J and forms the n x n matrix A given by A = J' * J. More...

void MANTID_CURVEFITTING_DLL	multJ (const DoubleFortranMatrix &J, const DoubleFortranVector &x, DoubleFortranVector &Jx)
	Multiply a matrix by a vector. More...

void MANTID_CURVEFITTING_DLL	multJt (const DoubleFortranMatrix &J, const DoubleFortranVector &x, DoubleFortranVector &Jtx)
	Multiply a transposed matrix by a vector. More...

double MANTID_CURVEFITTING_DLL	norm2 (const DoubleFortranVector &v)
	Compute the 2-norm of a vector which is a square root of the sum of squares of its elements. More...

void	rankOneUpdate (DoubleFortranMatrix &hf, NLLS_workspace &w)
	Update the Hessian matrix without actually evaluating it (quasi-Newton?) More...

void	testConvergence (double normF, double normJF, double normF0, double normJF0, const nlls_options &options, nlls_inform &inform)
	Test the convergence. More...

void	updateTrustRegionRadius (double &rho, const nlls_options &options, NLLS_workspace &w)
	Update the trust region radius which is hidden in NLLS_workspace w (w.Delta). More...

Variables
const double	EPSILON_MCH = std::numeric_limits<double>::epsilon()
	Too small values don't work well with numerical derivatives. More...

Function Documentation

◆ allEigSymm()

void Mantid::CurveFitting::NLLS::allEigSymm	(	const DoubleFortranMatrix &	A,
		DoubleFortranVector &	ew,
		DoubleFortranMatrix &	ev
	)

Calculate all the eigenvalues of a symmetric matrix.

Parameters

A	:: The input matrix.
ew	:: The output eigenvalues.
ev	:: The output eigenvectors.

Definition at line 348 of file TrustRegion.cpp.

References Mantid::CurveFitting::EigenMatrix::eigenSystem().

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::calculateStep().

◆ applyScaling()

void Mantid::CurveFitting::NLLS::applyScaling	(	const DoubleFortranMatrix &	J,
		DoubleFortranMatrix &	A,
		DoubleFortranVector &	v,
		DoubleFortranVector &	scale,
		const nlls_options &	options
	)

Apply_scaling input Jacobian matrix, J ouput scaled Hessisan, H, and J^Tf, v.

Calculates a diagonal scaling W, stored in w.diag updates v(i) -> (1/W_i) * v(i) A(i,j) -> (1 / (W_i * W_j)) * A(i,j)

Parameters

J	:: The Jacobian.
A	:: The Hessian.
v	:: The gradient (?).
scale	:: Stored scaling data.
options	:: The options.

use the scaling present in gsl: scale by W, W_ii = ||J(i,:)||_2^2

scale using the (approximate) hessian

use the scaling present in gsl: scale by W, W_ii = ||J(i,:)||_2^2

scale using the (approximate) hessian

Definition at line 280 of file TrustRegion.cpp.

◆ calculateRho()

double Mantid::CurveFitting::NLLS::calculateRho	(	double	normf,
		double	normfnew,
		double	md,
		const nlls_options &	options
	)

Calculate the quantity 0.5||f||^2 - 0.5||fnew||^2 actual_reduction rho = -----------------------— = ----------------— m_k(0) - m_k(d) predicted_reduction.

if model is good, rho should be close to one

Parameters

normf	:: The 2-norm of the residuals vector at d = 0.
normfnew	:: The 2-norm of the residuals vector at d != 0.
md	:: The value of the model at the same d as normfnew.
options	:: The options.

Definition at line 148 of file TrustRegion.cpp.

References EPSILON_MCH, fabs, rho, and UNUSED_ARG.

◆ dotProduct()

double Mantid::CurveFitting::NLLS::dotProduct	(	const DoubleFortranVector &	x,
		const DoubleFortranVector &	y
	)

Dot product of two vectors.

Definition at line 93 of file TrustRegion.cpp.

References Mantid::Geometry::x, and Mantid::Geometry::y.

Referenced by evaluateModel(), and rankOneUpdate().

◆ evaluateModel()

double Mantid::CurveFitting::NLLS::evaluateModel	(	const DoubleFortranVector &	f,
		const DoubleFortranMatrix &	J,
		const DoubleFortranMatrix &	hf,
		const DoubleFortranVector &	d,
		const nlls_options &	options,
		evaluate_model_work &	w
	)

Input: f = f(x_k), J = J(x_k), hf = \sum_{i=1}^m f_i(x_k) \nabla^2 f_i(x_k) (or an approx)

We have a model m_k(d) = 0.5 f^T f + d^T J f + 0.5 d^T (J^T J + HF) d

This subroutine evaluates the model at the point d This value is returned as the scalar md :=m_k(d)

Parameters

f	:: Vector of the residuals (at d = 0).
J	:: The Jacobian matrix at d = 0.
hf	:: The Hessian matrix at d = 0.
d	:: The point where to evaluate the model.
options	:: The options.
w	:: The work struct.

Definition at line 112 of file TrustRegion.cpp.

References Mantid::Geometry::d, dotProduct(), Mantid::CurveFitting::NLLS::evaluate_model_work::Hd, Mantid::CurveFitting::NLLS::evaluate_model_work::Jd, Mantid::CurveFitting::NLLS::evaluate_model_work::md_gn, Mantid::CurveFitting::NLLS::nlls_options::model, multJ(), and norm2().

◆ getSvdJ()

void Mantid::CurveFitting::NLLS::getSvdJ	(	const DoubleFortranMatrix &	J,
		double &	s1,
		double &	sn
	)

Given an (m x n) matrix J held by columns as a vector, this routine returns the largest and smallest singular values of J.

Parameters

J	:: The matrix.
s1	:: The largest sv.
sn	:: The smalles sv.

Definition at line 45 of file TrustRegion.cpp.

References Mantid::CurveFitting::EigenMatrix::inspector().

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::iterate().

◆ matmultInner()

void Mantid::CurveFitting::NLLS::matmultInner	(	const DoubleFortranMatrix &	J,
		DoubleFortranMatrix &	A
	)

Takes an m x n matrix J and forms the n x n matrix A given by A = J' * J.

Parameters

J	:: The matrix.
A	:: The result.

Definition at line 31 of file TrustRegion.cpp.

References Mantid::CurveFitting::FortranMatrix< MatrixClass >::allocate(), Mantid::CurveFitting::EigenMatrix::inspector(), Mantid::CurveFitting::FortranMatrix< MatrixClass >::len2(), Mantid::CurveFitting::EigenMatrix::mutator(), and n.

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::calculateStep().

◆ multJ()

void Mantid::CurveFitting::NLLS::multJ	(	const DoubleFortranMatrix &	J,
		const DoubleFortranVector &	x,
		DoubleFortranVector &	Jx
	)

Multiply a matrix by a vector.

Parameters

J	:: The matrix.
x	:: The vector.
Jx	:: The result vector.

Definition at line 68 of file TrustRegion.cpp.

References Mantid::CurveFitting::FortranVector< VectorClass >::allocate(), Mantid::CurveFitting::EigenMatrix::inspector(), Mantid::CurveFitting::FortranVector< VectorClass >::len(), Mantid::CurveFitting::FortranMatrix< MatrixClass >::len1(), Mantid::CurveFitting::EigenVector::mutator(), and Mantid::Geometry::x.

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::calculateStep(), evaluateModel(), and rankOneUpdate().

◆ multJt()

void Mantid::CurveFitting::NLLS::multJt	(	const DoubleFortranMatrix &	J,
		const DoubleFortranVector &	x,
		DoubleFortranVector &	Jtx
	)

Multiply a transposed matrix by a vector.

Parameters

J	:: The matrix.
x	:: The vector.
Jtx	:: The result vector.

Definition at line 82 of file TrustRegion.cpp.

References Mantid::CurveFitting::FortranVector< VectorClass >::allocate(), Mantid::CurveFitting::EigenMatrix::inspector(), Mantid::CurveFitting::FortranVector< VectorClass >::len(), Mantid::CurveFitting::FortranMatrix< MatrixClass >::len2(), Mantid::CurveFitting::EigenVector::mutator(), and Mantid::Geometry::x.

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::calculateStep(), and Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::iterate().

◆ norm2()

double Mantid::CurveFitting::NLLS::norm2 ( const DoubleFortranVector & v )

Compute the 2-norm of a vector which is a square root of the sum of squares of its elements.

Parameters

v	:: The vector.

Definition at line 57 of file TrustRegion.cpp.

References Mantid::CurveFitting::EigenVector::norm(), and Mantid::CurveFitting::EigenVector::size().

Referenced by Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::calculateStep(), evaluateModel(), and Mantid::CurveFitting::FuncMinimisers::TrustRegionMinimizer::iterate().

◆ rankOneUpdate()

void Mantid::CurveFitting::NLLS::rankOneUpdate	(	DoubleFortranMatrix &	hf,
		NLLS_workspace &	w
	)

Update the Hessian matrix without actually evaluating it (quasi-Newton?)

Parameters

hf	:: The matrix to update.
w	:: The work struct.

safeguard: skip this update

Definition at line 167 of file TrustRegion.cpp.

References Mantid::CurveFitting::NLLS::NLLS_workspace::d, dotProduct(), EPSILON_MCH, fabs, Mantid::CurveFitting::NLLS::NLLS_workspace::hf, multJ(), Mantid::CurveFitting::EigenMatrix::mutator(), Mantid::CurveFitting::EigenVector::mutator(), Mantid::CurveFitting::NLLS::NLLS_workspace::Sks, Mantid::CurveFitting::NLLS::NLLS_workspace::y, Mantid::CurveFitting::NLLS::NLLS_workspace::y_sharp, and Mantid::CurveFitting::NLLS::NLLS_workspace::ysharpSks.

◆ testConvergence()

void Mantid::CurveFitting::NLLS::testConvergence	(	double	normF,
		double	normJF,
		double	normF0,
		double	normJF0,
		const nlls_options &	options,
		nlls_inform &	inform
	)

Test the convergence.

Definition at line 254 of file TrustRegion.cpp.

References Mantid::CurveFitting::NLLS::nlls_inform::convergence_normf, Mantid::CurveFitting::NLLS::nlls_inform::convergence_normg, Mantid::CurveFitting::NLLS::nlls_options::stop_g_absolute, and Mantid::CurveFitting::NLLS::nlls_options::stop_g_relative.

◆ updateTrustRegionRadius()

void Mantid::CurveFitting::NLLS::updateTrustRegionRadius	(	double &	rho,
		const nlls_options &	options,
		NLLS_workspace &	w
	)

Update the trust region radius which is hidden in NLLS_workspace w (w.Delta).

Parameters

rho	:: The rho calculated by calculateRho(...). It may also be updated.
options	:: The options.
w	:: The work struct containing the radius that is to be updated (w.Delta).

Definition at line 205 of file TrustRegion.cpp.

Variable Documentation

◆ EPSILON_MCH

const double Mantid::CurveFitting::NLLS::EPSILON_MCH = std::numeric_limits<double>::epsilon()

Too small values don't work well with numerical derivatives.

Definition at line 23 of file TrustRegion.cpp.

Referenced by calculateRho(), and rankOneUpdate().

Classes

Functions

Variables

Function Documentation

◆ allEigSymm()

◆ applyScaling()

◆ calculateRho()

◆ dotProduct()

◆ evaluateModel()

◆ getSvdJ()

◆ matmultInner()

◆ multJ()

◆ multJt()

◆ norm2()

◆ rankOneUpdate()

◆ testConvergence()

◆ updateTrustRegionRadius()

Variable Documentation

◆ EPSILON_MCH