Namespaces
	PythonBindings

Classes
class	ConcatenateKernel

class	ConstantKernel

struct	OptInfo

class	MeanFunctionBase

class	ZeroMean

class	LinearMean

class	LinearTransformMean

class	SumMean

class	GaussianProcess

class	KarhunenLoeveBase

class	KarhunenLoeveExpansion
	Used to compute and evaluate the Karhunen-Loeve decomposition of a zero mean Gaussian process. @sealso SeperableKarhunenLoeve. More...

class	KarhunenLoeveFactory

class	KernelBase
	Base class for all covariance kernels. More...

class	KernelImpl
	Base class in CRTP pattern for covariance kernels. More...

class	LinearTransformKernel

class	MaternKernel

class	ObservationInformation
	Class for defining linear observations of a Gaussian process. More...

class	DerivativeObservation
	Class that defines an observation involving linear combinations of GP derivatives. More...

class	ProductKernel

class	SeparableKarhunenLoeve
	Implements KL expansions that take advantage of separable structure in both the domain and covariance kernel. More...

class	SquaredExpKernel

class	StateSpaceGP

class	SumKernel

class	WhiteNoiseKernel

class	AdaptiveSmolyakPCE

class	PCEFactory
	Factory class for constructing a pseudo-spectral polynomial chaos approximation using a fixed quadrature rule. More...

class	PolynomialChaosExpansion
	A class for representing and using expansions of orthogonal multivariate polynomials. More...

class	SmolyakEstimator

class	BasisExpansion
	Class for defining expansions of basis functions defined by a MultiIndexSet and collection of IndexScalarBasis functions. More...

class	HermiteFunction
	A 1D hermite function based on Physicist Hermite Polynomials. More...

class	IndexedScalarBasis

class	Jacobi
	Family of Jacobi orthogonal polynomials. More...

class	Laguerre
	Family of Laguerre orthogonal polynomials. More...

class	Legendre
	Family of Legendre orthogonal polynomials. More...

class	Monomial
	Family of monomial polynomials, i.e. () \(1\), \(x\), \(x^2\), ect. ...) More...

class	OrthogonalPolynomial
	A 1D orthogonal polynomial. More...

class	PhysicistHermite

class	ProbabilistHermite

class	AdaptiveSmolyakQuadrature

class	ClenshawCurtisQuadrature
	1d Clenshaw Curtis rule More...

class	ExponentialGrowthQuadrature
	1d Quadrature rule with exponential growth More...

class	FullTensorQuadrature
	Multivariate quadrature rule defined by the tensor product of 1d rules. More...

class	GaussPattersonQuadrature
	1d Gauss Patterson nested quadrature rule More...

class	GaussQuadrature
	Class for computing Gauss Quadrature rules from an orthogonal polynomial family. More...

class	Quadrature
	Base class for multivariate quadrature rules. @detail An abstract class for computing nodes and weights of general quadrature rules. @seealso GaussQuadrature. More...

class	SmolyakQuadrature
	Computes static Smolyak quadrature rules for multivariate integration. More...

class	LocalRegression

class	Regression

class	MatrixBlock

class	ColumnSlice

class	VectorSlice

Functions
template<typename KernelType1 , typename KernelType2 >
ConcatenateKernel	Concatenate (KernelType1 const &kernel1, KernelType2 const &kernel2)

double	nlopt_obj (unsigned n, const double x, double nlopt_grad, void *opt_info)

template<typename MeanType , typename = typename std::enable_if<std::is_base_of<MeanFunctionBase, MeanType>::value, MeanType>::type>
LinearTransformMean< MeanType >	operator* (Eigen::MatrixXd const &A, MeanType const &K)

template<typename MeanType1 , typename MeanType2 , typename = typename std::enable_if<std::is_base_of<MeanFunctionBase, MeanType1>::value, MeanType1>::type>
SumMean	operator+ (MeanType1 const &mu1, MeanType2 const &mu2)

template<typename MeanType , typename KernelType >
GaussianProcess	ConstructGP (MeanType const &mean, KernelType const &kernel)

template<typename KernelType >
LinearTransformKernel	TransformKernel (Eigen::MatrixXd const &A, KernelType const &K)

template<typename KernelType , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType>::value>::type>
LinearTransformKernel	operator* (Eigen::MatrixXd const &A, KernelType const &kernel)

template<typename KernelType1 , typename KernelType2 , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType1>::value && std::is_base_of<KernelBase, KernelType2>::value, KernelType1>::type>
ProductKernel	operator* (KernelType1 const &k1, KernelType2 const &k2)

std::shared_ptr< ProductKernel >	operator* (std::shared_ptr< KernelBase > k1, std::shared_ptr< KernelBase > k2)

template<typename KernelType1 , typename KernelType2 , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType1>::value && std::is_base_of<KernelBase, KernelType2>::value, KernelType1>::type>
SumKernel	operator+ (KernelType1 const &k1, KernelType2 const &k2)

std::shared_ptr< SumKernel >	operator+ (std::shared_ptr< KernelBase > k1, std::shared_ptr< KernelBase > k2)

template<typename MatrixType >
unsigned	GetShape (MatrixType const &mat, unsigned dim)

template<typename ScalarType , int rows, int cols>
unsigned	GetShape (Eigen::Matrix< ScalarType, rows, cols > const &mat, unsigned dim)

template<typename Derived >
unsigned	GetShape (MatrixBlock< Derived > const &mat, unsigned dim)

template<typename Derived >
unsigned	GetShape (Eigen::Ref< Derived > const &mat, unsigned dim)

template<typename VectorType1 , typename VectorType2 >
double	CalcSquaredDistance (VectorType1 const &v1, VectorType2 const &v2, int startDim=0, int endDim=-1)
	Calculates the distance squared between two points defined by vectors v1 and v2. More...

template<typename VectorType1 , typename VectorType2 >
double	CalcDistance (VectorType1 const &v1, VectorType2 const &v2)

template<typename MatType >
ColumnSlice< MatType >	GetColumn (MatType &matrix, unsigned col)

template<typename MatType >
VectorSlice< MatType >	GetSlice (MatType &matrix, std::vector< unsigned > const &inds)

template<typename MatType >
MatrixBlock< MatType >	GetBlock (MatType &matrix, unsigned rowStart, unsigned colStart, unsigned numRows, unsigned numCols)

Function Documentation

◆ CalcDistance()

template<typename VectorType1 , typename VectorType2 >

double muq::Approximation::CalcDistance	(	VectorType1 const &	v1,
		VectorType2 const &	v2
	)

Calculates the distance between two points defined by vectors v1 and v2.

Definition at line 88 of file TemplatedArrayUtilities.h.

References CalcSquaredDistance(), and GetShape().

◆ CalcSquaredDistance()

template<typename VectorType1 , typename VectorType2 >

double muq::Approximation::CalcSquaredDistance	(	VectorType1 const &	v1,
		VectorType2 const &	v2,
		int	startDim = `0`,
		int	endDim = `-1`
	)

Calculates the distance squared between two points defined by vectors v1 and v2.

Assumes the vectors are the same size and recursively compute the squared distance between them. The recursion is used for numerical accuracy.

Definition at line 56 of file TemplatedArrayUtilities.h.

References GetShape().

Referenced by CalcDistance().

◆ Concatenate()

template<typename KernelType1 , typename KernelType2 >

ConcatenateKernel muq::Approximation::Concatenate	(	KernelType1 const &	kernel1,
		KernelType2 const &	kernel2
	)

Definition at line 59 of file ConcatenateKernel.h.

◆ GetBlock()

template<typename MatType >

MatrixBlock<MatType> muq::Approximation::GetBlock	(	MatType &	matrix,
		unsigned	rowStart,
		unsigned	colStart,
		unsigned	numRows,
		unsigned	numCols
	)

Definition at line 235 of file TemplatedArrayUtilities.h.

◆ GetColumn()

template<typename MatType >

ColumnSlice<MatType> muq::Approximation::GetColumn	(	MatType &	matrix,
		unsigned	col
	)

Grab a particular column of a matrix and return as an instance of the "ColumnSlice" class.

Definition at line 222 of file TemplatedArrayUtilities.h.

◆ GetShape() [1/4]

template<typename ScalarType , int rows, int cols>

unsigned muq::Approximation::GetShape	(	Eigen::Matrix< ScalarType, rows, cols > const &	mat,
		unsigned	dim
	)

Definition at line 30 of file TemplatedArrayUtilities.h.

◆ GetShape() [2/4]

template<typename Derived >

unsigned muq::Approximation::GetShape	(	Eigen::Ref< Derived > const &	mat,
		unsigned	dim
	)

Definition at line 45 of file TemplatedArrayUtilities.h.

◆ GetShape() [3/4]

template<typename Derived >

unsigned muq::Approximation::GetShape	(	MatrixBlock< Derived > const &	mat,
		unsigned	dim
	)

Definition at line 37 of file TemplatedArrayUtilities.h.

References muq::Approximation::MatrixBlock< MatType >::cols(), and muq::Approximation::MatrixBlock< MatType >::rows().

◆ GetShape() [4/4]

template<typename MatrixType >

unsigned muq::Approximation::GetShape	(	MatrixType const &	mat,
		unsigned	dim
	)

Templated function to get the shape of an array. In Eigen parlance, GetShape(mat,0) is the same as mat.rows() and GetShape(mat,1) is the same as mat.cols().

This function is overloaded to handle general types of arrays. Currently, Kokkos::View<double**> and Eigen matrices are supported.

Definition at line 24 of file TemplatedArrayUtilities.h.

Referenced by CalcDistance(), CalcSquaredDistance(), muq::Approximation::ColumnSlice< MatType >::dimension(), muq::Approximation::MatrixBlock< MatType >::MatrixBlock(), and muq::Approximation::ColumnSlice< MatType >::rows().

◆ GetSlice()

template<typename MatType >

VectorSlice<MatType> muq::Approximation::GetSlice	(	MatType &	matrix,
		std::vector< unsigned > const &	inds
	)

Definition at line 228 of file TemplatedArrayUtilities.h.

◆ nlopt_obj()

double muq::Approximation::nlopt_obj	(	unsigned	n,
		const double *	x,
		double *	nlopt_grad,
		void *	opt_info
	)

Definition at line 9 of file GaussianProcess.cpp.

References muq::Approximation::OptInfo::gp, muq::Approximation::GaussianProcess::Kernel(), muq::Approximation::GaussianProcess::MarginalLogLikelihood(), and nlohmann::detail::dtoa_impl::n.

◆ operator*() [1/4]

template<typename KernelType , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType>::value>::type>

LinearTransformKernel muq::Approximation::operator*	(	Eigen::MatrixXd const &	A,
		KernelType const &	kernel
	)

Definition at line 77 of file LinearTransformKernel.h.

◆ operator*() [2/4]

template<typename MeanType , typename = typename std::enable_if<std::is_base_of<MeanFunctionBase, MeanType>::value, MeanType>::type>

LinearTransformMean<MeanType> muq::Approximation::operator*	(	Eigen::MatrixXd const &	A,
		MeanType const &	K
	)

Definition at line 224 of file GaussianProcess.h.

◆ operator*() [3/4]

template<typename KernelType1 , typename KernelType2 , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType1>::value && std::is_base_of<KernelBase, KernelType2>::value, KernelType1>::type>

ProductKernel muq::Approximation::operator*	(	KernelType1 const &	k1,
		KernelType2 const &	k2
	)

Definition at line 148 of file ProductKernel.h.

◆ operator*() [4/4]

std::shared_ptr< ProductKernel > muq::Approximation::operator*	(	std::shared_ptr< KernelBase >	k1,
		std::shared_ptr< KernelBase >	k2
	)

Definition at line 176 of file ProductKernel.cpp.

◆ operator+() [1/3]

template<typename KernelType1 , typename KernelType2 , typename = typename std::enable_if<std::is_base_of<KernelBase, KernelType1>::value && std::is_base_of<KernelBase, KernelType2>::value, KernelType1>::type>

SumKernel muq::Approximation::operator+	(	KernelType1 const &	k1,
		KernelType2 const &	k2
	)

Definition at line 54 of file SumKernel.h.

◆ operator+() [2/3]

template<typename MeanType1 , typename MeanType2 , typename = typename std::enable_if<std::is_base_of<MeanFunctionBase, MeanType1>::value, MeanType1>::type>

SumMean muq::Approximation::operator+	(	MeanType1 const &	mu1,
		MeanType2 const &	mu2
	)

Definition at line 270 of file GaussianProcess.h.

Referenced by nlohmann::detail::json_reverse_iterator< Base >::operator+().

◆ operator+() [3/3]

std::shared_ptr< SumKernel > muq::Approximation::operator+	(	std::shared_ptr< KernelBase >	k1,
		std::shared_ptr< KernelBase >	k2
	)

Definition at line 80 of file SumKernel.cpp.

◆ TransformKernel()

template<typename KernelType >

LinearTransformKernel muq::Approximation::TransformKernel	(	Eigen::MatrixXd const &	A,
		KernelType const &	K
	)

Definition at line 70 of file LinearTransformKernel.h.

Namespaces

Classes

Functions

Function Documentation

◆ CalcDistance()

◆ CalcSquaredDistance()

◆ Concatenate()

◆ GetBlock()

◆ GetColumn()

◆ GetShape() [1/4]

◆ GetShape() [2/4]

◆ GetShape() [3/4]

◆ GetShape() [4/4]

◆ GetSlice()

◆ nlopt_obj()

◆ operator*() [1/4]

◆ operator*() [2/4]

◆ operator*() [3/4]

◆ operator*() [4/4]

◆ operator+() [1/3]

◆ operator+() [2/3]

◆ operator+() [3/3]

◆ TransformKernel()