Namespaces
	BernsteinPolynomialBasis
	Definition of scalar Bernstein polynomial basis.

	DivergenceFreePolynomialBasis
	Definition of the divergence-free polynomial basis.

	GMLS_LinearAlgebra

	ScalarTaylorPolynomialBasis
	Definition of scalar Taylor polynomial basis.

Classes
struct	SubviewND
	Creates 1D subviews of data from a 2D view, generally constructed with CreateNDSliceOnDeviceView. More...

class	Evaluator
	Lightweight Evaluator Helper This class is a lightweight wrapper for extracting and applying all relevant data from a GMLS class in order to transform data into a form that can be acted on by the GMLS operator, apply the action of the GMLS operator, and then transform data again (only if on a manifold) More...

struct	GMLSBasisData

struct	GMLSSolutionData

struct	ApplyTargets
	Functor to apply target evaluation to polynomial coefficients to store in _alphas. More...

struct	EvaluateStandardTargets
	Functor to evaluate targets operations on the basis. More...

struct	ComputePrestencilWeights
	Functor to calculate prestencil weights to apply to data to transform into a format expected by a GMLS stencil. More...

struct	AssembleStandardPsqrtW
	Functor to assemble the Psqrt(weights) matrix and construct sqrt(weights)Identity. More...

struct	ComputeCoarseTangentPlane
	Functor to create a coarse tangent approximation from a given neighborhood of points. More...

struct	AssembleCurvaturePsqrtW
	Functor to assemble the Psqrt(weights) matrix and construct sqrt(weights)Identity for curvature. More...

struct	GetAccurateTangentDirections
	Functor to evaluate curvature targets and construct accurate tangent direction approximation for manifolds. More...

struct	FixTangentDirectionOrdering
	Functor to determine if tangent directions need reordered, and to reorder them if needed We require that the normal is consistent with a right hand rule on the tangent vectors. More...

struct	ApplyCurvatureTargets
	Functor to evaluate curvature targets and apply to coefficients of curvature reconstruction. More...

struct	AssembleManifoldPsqrtW
	Functor to assemble the Psqrt(weights) matrix and construct sqrt(weights)Identity. More...

struct	EvaluateManifoldTargets
	Functor to evaluate targets on a manifold. More...

class	GMLS
	Generalized Moving Least Squares (GMLS) More...

class	KokkosParser
	Class handling Kokkos command line arguments and returning parameters. More...

struct	XYZ

struct	NeighborLists
	NeighborLists assists in accessing entries of compressed row neighborhood lists. More...

struct	SamplingFunctional

class	ParallelManager
	Parallel Manager. More...

class	RadiusResultSet
	Custom RadiusResultSet for nanoflann that uses pre-allocated space for indices and radii instead of using std::vec for std::pairs. More...

class	PointCloudSearch
	PointCloudSearch generates neighbor lists and window sizes for each target site. More...

struct	PointConnections
	Combines NeighborLists with the PointClouds from which it was derived Assumed that memory_space is the same as device, but it can be set to host, if desired. More...

class	Quadrature
	Quadrature. More...

struct	SolutionSet
	All vairables and functionality related to the layout and storage of GMLS solutions (alpha values) More...

struct	Extract

Enumerations
enum	TargetOperation : int { ScalarPointEvaluation, VectorPointEvaluation, LaplacianOfScalarPointEvaluation, VectorLaplacianPointEvaluation, GradientOfScalarPointEvaluation, GradientOfVectorPointEvaluation, DivergenceOfVectorPointEvaluation, CurlOfVectorPointEvaluation, CurlCurlOfVectorPointEvaluation, PartialXOfScalarPointEvaluation, PartialYOfScalarPointEvaluation, PartialZOfScalarPointEvaluation, ChainedStaggeredLaplacianOfScalarPointEvaluation, GaussianCurvaturePointEvaluation, CellAverageEvaluation, CellIntegralEvaluation, FaceNormalAverageEvaluation, FaceNormalIntegralEvaluation, EdgeTangentAverageEvaluation, EdgeTangentIntegralEvaluation, COUNT =20 }
	Available target functionals. More...

enum	ReconstructionSpace : int { ScalarTaylorPolynomial, VectorTaylorPolynomial, VectorOfScalarClonesTaylorPolynomial, DivergenceFreeVectorTaylorPolynomial, BernsteinPolynomial }
	Space in which to reconstruct polynomial. More...

enum	SamplingTransformType : int { Identity, SameForAll, DifferentEachTarget, DifferentEachNeighbor }
	Describes the SamplingFunction relationship to targets, neighbors. More...

enum	DenseSolverType : int { QR, LU }
	Dense solver type. More...

enum	ProblemType : int { STANDARD, MANIFOLD }
	Problem type, that optionally can handle manifolds. More...

enum	ConstraintType : int { NO_CONSTRAINT, NEUMANN_GRAD_SCALAR }
	Constraint type. More...

enum	WeightingFunctionType : int { Power, Gaussian, CubicSpline, CardinalCubicBSpline, Cosine, Sigmoid }
	Available weighting kernel function types. More...

enum	CoordinatesType : int { Ambient, Local }
	Coordinate type for input and output format of vector data on manifold problems. More...

enum	QuadratureType : int { INVALID, LINE, TRI, QUAD, TET, HEX }

Functions
template<typename SolutionData >
KOKKOS_INLINE_FUNCTION void	applyTargetsToCoefficients (const SolutionData &data, const member_type &teamMember, scratch_matrix_right_type Q, scratch_matrix_right_type P_target_row)
	For applying the evaluations from a target functional to the polynomial coefficients. More...

template<typename BasisData >
KOKKOS_INLINE_FUNCTION void	calcPij (const BasisData &data, const member_type &teamMember, double delta, double thread_workspace, const int target_index, int neighbor_index, const double alpha, const int dimension, const int poly_order, bool specific_order_only=false, const scratch_matrix_right_type *V=NULL, const ReconstructionSpace reconstruction_space=ReconstructionSpace::ScalarTaylorPolynomial, const SamplingFunctional polynomial_sampling_functional=PointSample, const int evaluation_site_local_index=0)
	Evaluates the polynomial basis under a particular sampling function. Generally used to fill a row of P. More...

template<typename BasisData >
KOKKOS_INLINE_FUNCTION void	calcGradientPij (const BasisData &data, const member_type &teamMember, double delta, double thread_workspace, const int target_index, int neighbor_index, const double alpha, const int partial_direction, const int dimension, const int poly_order, bool specific_order_only, const scratch_matrix_right_type *V, const ReconstructionSpace reconstruction_space, const SamplingFunctional polynomial_sampling_functional, const int evaluation_site_local_index=0)
	Evaluates the gradient of a polynomial basis under the Dirac Delta (pointwise) sampling function. More...

template<typename BasisData >
KOKKOS_INLINE_FUNCTION void	calcHessianPij (const BasisData &data, const member_type &teamMember, double delta, double thread_workspace, const int target_index, int neighbor_index, const double alpha, const int partial_direction_1, const int partial_direction_2, const int dimension, const int poly_order, bool specific_order_only, const scratch_matrix_right_type *V, const ReconstructionSpace reconstruction_space, const SamplingFunctional polynomial_sampling_functional, const int evaluation_site_local_index=0)
	Evaluates the Hessian of a polynomial basis under the Dirac Delta (pointwise) sampling function. More...

template<typename BasisData >
KOKKOS_INLINE_FUNCTION void	createWeightsAndP (const BasisData &data, const member_type &teamMember, scratch_vector_type delta, scratch_vector_type thread_workspace, scratch_matrix_right_type P, scratch_vector_type w, const int dimension, int polynomial_order, bool weight_p=false, scratch_matrix_right_type *V=NULL, const ReconstructionSpace reconstruction_space=ReconstructionSpace::ScalarTaylorPolynomial, const SamplingFunctional polynomial_sampling_functional=PointSample)
	Fills the _P matrix with either P or P*sqrt(w) More...

template<typename BasisData >
KOKKOS_INLINE_FUNCTION void	createWeightsAndPForCurvature (const BasisData &data, const member_type &teamMember, scratch_vector_type delta, scratch_vector_type thread_workspace, scratch_matrix_right_type P, scratch_vector_type w, const int dimension, bool only_specific_order, scratch_matrix_right_type *V=NULL)
	Fills the _P matrix with P*sqrt(w) for use in solving for curvature. More...

template<typename T , typename T2 >
struct SubviewND< T, T2, enable_if_t<(T::rank< 2)> >{T _data_in;T2 _data_original_view;bool _scalar_as_vector_if_needed;SubviewND(T data_in, T2 data_original_view, bool scalar_as_vector_if_needed){_data_in=data_in;_data_original_view=data_original_view;_scalar_as_vector_if_needed=scalar_as_vector_if_needed;}auto get1DView(const int column_num) ->	decltype (Kokkos::subview(_data_in, Kokkos::ALL))
	Creates 1D subviews of data from a 1D view, generally constructed with CreateNDSliceOnDeviceView. More...

auto	get2DView (const int column_num, const int block_size) -> decltype(Kokkos::subview(_data_in, Kokkos::ALL))

T2	copyToAndReturnOriginalView ()

template<typename T >
auto	CreateNDSliceOnDeviceView (T sampling_input_data_host_or_device, bool scalar_as_vector_if_needed) -> SubviewND< decltype(Kokkos::create_mirror_view(device_memory_space(), sampling_input_data_host_or_device)), T >
	Copies data_in to the device, and then allows for access to 1D columns of data on device. More...

KOKKOS_INLINE_FUNCTION double	MetricFactor (const scratch_vector_type a_, const double h, const double u1, const double u2)
	Metric factor (det(G)) at any point in the local chart. More...

KOKKOS_INLINE_FUNCTION double	GaussianCurvature (const scratch_vector_type a_, const double h, const double u1, const double u2)
	Gaussian curvature K at any point in the local chart. More...

KOKKOS_INLINE_FUNCTION double	SurfaceCurlOfScalar (const scratch_vector_type a_, const double h, const double u1, const double u2, int x_pow, int y_pow, const int component)
	Surface curl at any point in the local chart. More...

KOKKOS_INLINE_FUNCTION XYZ	operator+ (const XYZ &vecA, const XYZ &vecB)

KOKKOS_INLINE_FUNCTION XYZ	operator- (const XYZ &vecA, const XYZ &vecB)

KOKKOS_INLINE_FUNCTION XYZ	operator* (const XYZ &vecA, const XYZ &vecB)

KOKKOS_INLINE_FUNCTION XYZ	operator+ (const XYZ &vecA, const scalar_type &constant)

KOKKOS_INLINE_FUNCTION XYZ	operator+ (const scalar_type &constant, const XYZ &vecA)

KOKKOS_INLINE_FUNCTION XYZ	operator- (const XYZ &vecA, const scalar_type &constant)

KOKKOS_INLINE_FUNCTION XYZ	operator- (const scalar_type &constant, const XYZ &vecA)

KOKKOS_INLINE_FUNCTION XYZ	operator* (const XYZ &vecA, const scalar_type &constant)

KOKKOS_INLINE_FUNCTION XYZ	operator* (const scalar_type &constant, const XYZ &vecA)

KOKKOS_INLINE_FUNCTION XYZ	operator/ (const XYZ &vecA, const scalar_type &constant)

std::ostream &	operator<< (std::ostream &os, const XYZ &vec)

KOKKOS_INLINE_FUNCTION int	pown (int n, unsigned p)
	n^p (n^0 returns 1, regardless of n) More...

KOKKOS_INLINE_FUNCTION int	getAdditionalAlphaSizeFromConstraint (DenseSolverType dense_solver_type, ConstraintType constraint_type)

KOKKOS_INLINE_FUNCTION int	getAdditionalCoeffSizeFromConstraintAndSpace (DenseSolverType dense_solver_type, ConstraintType constraint_type, ReconstructionSpace reconstruction_space, const int dimension)

KOKKOS_INLINE_FUNCTION void	getRHSDims (DenseSolverType dense_solver_type, ConstraintType constraint_type, ReconstructionSpace reconstruction_space, const int dimension, const int M, const int N, int &RHS_row, int &RHS_col)

KOKKOS_INLINE_FUNCTION void	getPDims (DenseSolverType dense_solver_type, ConstraintType constraint_type, ReconstructionSpace reconstruction_space, const int dimension, const int M, const int N, int &out_row, int &out_col)

KOKKOS_INLINE_FUNCTION int	getTargetOutputIndex (const int operation_num, const int output_component_axis_1, const int output_component_axis_2, const int dimensions)
	Helper function for finding alpha coefficients. More...

KOKKOS_INLINE_FUNCTION int	getSamplingOutputIndex (const SamplingFunctional sf, const int output_component_axis_1, const int output_component_axis_2)
	Helper function for finding alpha coefficients. More...

KOKKOS_INLINE_FUNCTION int	getInputRankOfSampling (SamplingFunctional sro)
	Input rank for sampling operation. More...

KOKKOS_INLINE_FUNCTION int	getOutputDimensionOfSampling (SamplingFunctional sro, const int local_dimensions)
	Dimensions ^ output rank for sampling operation (always in local chart if on a manifold, never ambient space) More...

KOKKOS_INLINE_FUNCTION int	getInputDimensionOfSampling (SamplingFunctional sro, const int global_dimensions)
	Dimensions ^ output rank for sampling operation (always in ambient space, never local chart on a manifold) More...

KOKKOS_INLINE_FUNCTION int	calculateBasisMultiplier (const ReconstructionSpace rs, const int local_dimensions)
	Calculate basis_multiplier. More...

KOKKOS_INLINE_FUNCTION int	calculateSamplingMultiplier (const ReconstructionSpace rs, const SamplingFunctional sro, const int local_dimensions)
	Calculate sampling_multiplier. More...

KOKKOS_INLINE_FUNCTION int	getOutputDimensionOfOperation (TargetOperation lro, const int local_dimensions)
	Dimensions ^ output rank for target operation. More...

KOKKOS_INLINE_FUNCTION int	getInputDimensionOfOperation (TargetOperation lro, SamplingFunctional sro, const int local_dimensions)
	Dimensions ^ input rank for target operation (always in local chart if on a manifold, never ambient space) More...

template<typename view_type >
NeighborLists< view_type >	CreateNeighborLists (view_type number_of_neighbors_list)
	CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction. More...

template<typename view_type >
NeighborLists< view_type >	CreateNeighborLists (view_type neighbor_lists, view_type number_of_neighbors_list)
	CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction. More...

template<typename view_type >
NeighborLists< view_type >	CreateNeighborLists (view_type neighbor_lists, view_type number_of_neighbors_list, view_type neighbor_lists_row_offsets)
	CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction. More...

template<typename view_type_2d , typename view_type_1d = Kokkos::View<int*, typename view_type_2d::memory_space, typename view_type_2d::memory_traits>>
NeighborLists< view_type_1d >	Convert2DToCompressedRowNeighborLists (view_type_2d neighbor_lists)
	Converts 2D neighbor lists to compressed row neighbor lists. More...

KOKKOS_INLINE_FUNCTION int	getTargetOutputTensorRank (const int &index)
	Rank of target functional output for each TargetOperation Rank of target functional input for each TargetOperation is based on the output rank of the SamplingFunctional used on the polynomial basis. More...

KOKKOS_INLINE_FUNCTION int	getActualReconstructionSpaceRank (const int &index)
	Number of actual components in the ReconstructionSpace. More...

template<typename view_type >
PointCloudSearch< view_type >	CreatePointCloudSearch (view_type src_view, const local_index_type dimensions=-1, const local_index_type max_leaf=-1)
	CreatePointCloudSearch allows for the construction of an object of type PointCloudSearch with template deduction. More...

template<typename TargetData >
KOKKOS_INLINE_FUNCTION void	computeTargetFunctionals (const TargetData &data, const member_type &teamMember, scratch_vector_type delta, scratch_vector_type thread_workspace, scratch_matrix_right_type P_target_row)
	Evaluates a polynomial basis with a target functional applied to each member of the basis. More...

template<typename TargetData >
KOKKOS_INLINE_FUNCTION void	computeCurvatureFunctionals (const TargetData &data, const member_type &teamMember, scratch_vector_type delta, scratch_vector_type thread_workspace, scratch_matrix_right_type P_target_row, const scratch_matrix_right_type *V, const local_index_type local_neighbor_index=-1)
	Evaluates a polynomial basis for the curvature with a gradient target functional applied. More...

template<typename TargetData >
KOKKOS_INLINE_FUNCTION void	computeTargetFunctionalsOnManifold (const TargetData &data, const member_type &teamMember, scratch_vector_type delta, scratch_vector_type thread_workspace, scratch_matrix_right_type P_target_row, scratch_matrix_right_type V, scratch_vector_type curvature_coefficients)
	Evaluates a polynomial basis with a target functional applied, using information from the manifold curvature. More...

KOKKOS_INLINE_FUNCTION void	getMidpointFromCellVertices (const member_type &teamMember, scratch_vector_type midpoint_storage, scratch_matrix_right_type cell_coordinates, const int cell_num, const int dim=3)

template<typename view_type_1 , typename view_type_2 >
KOKKOS_INLINE_FUNCTION double	getAreaFromVectors (const member_type &teamMember, view_type_1 v1, view_type_2 v2)

template<typename output_memory_space , typename view_type_input_data , typename output_array_layout = typename view_type_input_data::array_layout, typename index_type = int>
Kokkos::View< int *, output_array_layout, output_memory_space >	filterViewByID (view_type_input_data input_data_host_or_device, index_type filtered_value)

KOKKOS_INLINE_FUNCTION void	evaluateConstraints (scratch_matrix_right_type M, scratch_matrix_right_type PsqrtW, const ConstraintType constraint_type, const ReconstructionSpace reconstruction_space, const int NP, const double cutoff_p, const int dimension, const int num_neighbors=0, scratch_matrix_right_type *T=NULL)

Variables
constexpr SamplingFunctional	PointSample = make_sampling_functional(0,0,false,false,(int)Identity)
	Available sampling functionals. More...

constexpr SamplingFunctional	VectorPointSample = make_sampling_functional(1,1,false,false,(int)Identity)
	Point evaluations of the entire vector source function. More...

constexpr SamplingFunctional	ManifoldVectorPointSample = make_sampling_functional(1,1,false,false,(int)DifferentEachTarget)
	Point evaluations of the entire vector source function (but on a manifold, so it includes a transform into local coordinates) More...

constexpr SamplingFunctional	StaggeredEdgeAnalyticGradientIntegralSample = make_sampling_functional(0,0,true,true,(int)SameForAll)
	Analytical integral of a gradient source vector is just a difference of the scalar source at neighbor and target. More...

constexpr SamplingFunctional	StaggeredEdgeIntegralSample = make_sampling_functional(1,0,true,true,(int)DifferentEachNeighbor)
	Samples consist of the result of integrals of a vector dotted with the tangent along edges between neighbor and target. More...

constexpr SamplingFunctional	VaryingManifoldVectorPointSample = make_sampling_functional(1,1,false,false,(int)DifferentEachNeighbor)
	For integrating polynomial dotted with normal over an edge. More...

constexpr SamplingFunctional	FaceNormalIntegralSample = make_sampling_functional(1,0,false,false,(int)Identity)
	For integrating polynomial dotted with normal over an edge. More...

constexpr SamplingFunctional	FaceNormalAverageSample = make_sampling_functional(1,0,false,false,(int)Identity)
	For polynomial dotted with normal on edge. More...

constexpr SamplingFunctional	EdgeTangentIntegralSample = make_sampling_functional(1,0,false,false,(int)Identity)
	For integrating polynomial dotted with tangent over an edge. More...

constexpr SamplingFunctional	EdgeTangentAverageSample = make_sampling_functional(1,0,false,false,(int)Identity)
	For polynomial dotted with tangent. More...

constexpr SamplingFunctional	CellAverageSample = make_sampling_functional(0,0,false,false,(int)DifferentEachNeighbor)
	For polynomial integrated on cells. More...

constexpr SamplingFunctional	CellIntegralSample = make_sampling_functional(0,0,false,false,(int)DifferentEachNeighbor)
	For polynomial integrated on cells. More...

Enumeration Type Documentation

enum Compadre::ConstraintType : int

Constraint type.

Enumerator
NO_CONSTRAINT	No constraint.
NEUMANN_GRAD_SCALAR	Neumann Gradient Scalar Type.

Definition at line 234 of file Compadre_Operators.hpp.

enum Compadre::CoordinatesType : int

Coordinate type for input and output format of vector data on manifold problems.

Anything without a manifold is always Ambient.

Enumerator
Ambient	a 2D manifold in 3D in ambient coordinates would have 3 components for a vector
Local	a 2D manifold in 3D in local coordinates would have 2 components for a vector

Definition at line 253 of file Compadre_Operators.hpp.

enum Compadre::DenseSolverType : int

Dense solver type.

Enumerator
QR	QR+Pivoting factorization performed on P*sqrt(w) matrix.
LU	LU factorization performed on P^TWP matrix.

Definition at line 217 of file Compadre_Operators.hpp.

enum Compadre::ProblemType : int

Problem type, that optionally can handle manifolds.

Enumerator
STANDARD	Standard GMLS problem type.
MANIFOLD	Solve GMLS problem on a manifold (will use QR or SVD to solve the resultant GMLS problem dependent on SamplingNontrivialNullspace.

Definition at line 225 of file Compadre_Operators.hpp.

enum Compadre::QuadratureType : int

Enumerator
INVALID
LINE
TRI
QUAD
TET
HEX

Definition at line 19 of file Compadre_Quadrature.hpp.

enum Compadre::ReconstructionSpace : int

Space in which to reconstruct polynomial.

Enumerator
ScalarTaylorPolynomial	Scalar polynomial basis centered at the target site and scaled by sum of basis powers e.g. would be a member of 3rd order in 3D, where is the coordinate of the target site in 3D coordinates.
VectorTaylorPolynomial	Vector polynomial basis having # of components _dimensions, or (_dimensions-1) in the case of manifolds)
VectorOfScalarClonesTaylorPolynomial	Scalar basis reused as many times as there are components in the vector resulting in a much cheaper polynomial reconstruction.
DivergenceFreeVectorTaylorPolynomial	Divergence-free vector polynomial basis.
BernsteinPolynomial	Bernstein polynomial basis.

Definition at line 103 of file Compadre_Operators.hpp.

enum Compadre::SamplingTransformType : int

Describes the SamplingFunction relationship to targets, neighbors.

Enumerator
Identity	No action performed on data before GMLS target operation.
SameForAll	Each neighbor for each target all apply the same transform.
DifferentEachTarget	Each target applies a different data transform, but the same to each neighbor.
DifferentEachNeighbor	Each target applies a different transform for each neighbor.

Definition at line 133 of file Compadre_Operators.hpp.

enum Compadre::TargetOperation : int

Available target functionals.

Enumerator
ScalarPointEvaluation	Point evaluation of a scalar.
VectorPointEvaluation	Point evaluation of a vector (reconstructs entire vector at once, requiring a ReconstructionSpace having a sufficient number of components in the basis)
LaplacianOfScalarPointEvaluation	Point evaluation of the laplacian of a scalar (could be on a manifold or not)
VectorLaplacianPointEvaluation	Point evaluation of the laplacian of each component of a vector.
GradientOfScalarPointEvaluation	Point evaluation of the gradient of a scalar.
GradientOfVectorPointEvaluation	Point evaluation of the gradient of a vector (results in a matrix, NOT CURRENTLY IMPLEMENTED)
DivergenceOfVectorPointEvaluation	Point evaluation of the divergence of a vector (results in a scalar)
CurlOfVectorPointEvaluation	Point evaluation of the curl of a vector (results in a vector)
CurlCurlOfVectorPointEvaluation	Point evaluation of the curl of a curl of a vector (results in a vector)
PartialXOfScalarPointEvaluation	Point evaluation of the partial with respect to x of a scalar.
PartialYOfScalarPointEvaluation	Point evaluation of the partial with respect to y of a scalar.
PartialZOfScalarPointEvaluation	Point evaluation of the partial with respect to z of a scalar.
ChainedStaggeredLaplacianOfScalarPointEvaluation	Point evaluation of the chained staggered Laplacian acting on VectorTaylorPolynomial basis + StaggeredEdgeIntegralSample sampling functional.
GaussianCurvaturePointEvaluation	Point evaluation of Gaussian curvature.
CellAverageEvaluation	Average values of a cell using quadrature Supported on 2D faces in 3D problems (manifold) and 2D cells in 2D problems.
CellIntegralEvaluation	Integral values over cell using quadrature Supported on 2D faces in 3D problems (manifold) and 2D cells in 2D problems.
FaceNormalAverageEvaluation	Average value of vector dotted with normal direction Supported on 1D edges in 3D problems (2D-manifold) and 1D edges on 2D cells.
FaceNormalIntegralEvaluation	Integral value of vector dotted with normal direction Supported on 1D edges in 3D problems (2D-manifold) and 1D edges on 2D cells.
EdgeTangentAverageEvaluation	Average value of vector dotted with tangent directions Supported on 1D edges in 3D problems (2D-manifold) and 1D edges on 2D cells.
EdgeTangentIntegralEvaluation	Integral value of vector dotted with tangent directions Supported on 1D edges in 3D problems (2D-manifold) and 1D edges on 2D cells.
COUNT	Should be the total count of all available target functionals.

Definition at line 19 of file Compadre_Operators.hpp.

enum Compadre::WeightingFunctionType : int

Available weighting kernel function types.

Enumerator
Power
Gaussian
CubicSpline
CardinalCubicBSpline
Cosine
Sigmoid

Definition at line 242 of file Compadre_Operators.hpp.

Function Documentation

template<typename SolutionData >

KOKKOS_INLINE_FUNCTION void Compadre::applyTargetsToCoefficients	(	const SolutionData &	data,
		const member_type &	teamMember,
		scratch_matrix_right_type	Q,
		scratch_matrix_right_type	P_target_row
	)

For applying the evaluations from a target functional to the polynomial coefficients.

Parameters

data	[out/in] - GMLSSolutionData struct (stores solution in data._d_ss._alphas)
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
Q	[in] - 2D Kokkos View containing the polynomial coefficients
P_target_row	[in] - 1D Kokkos View where the evaluation of the polynomial basis is stored

Definition at line 23 of file Compadre_ApplyTargetEvaluations.hpp.

template<typename BasisData >

KOKKOS_INLINE_FUNCTION void Compadre::calcGradientPij	(	const BasisData &	data,
		const member_type &	teamMember,
		double *	delta,
		double *	thread_workspace,
		const int	target_index,
		int	neighbor_index,
		const double	alpha,
		const int	partial_direction,
		const int	dimension,
		const int	poly_order,
		bool	specific_order_only,
		const scratch_matrix_right_type *	V,
		const ReconstructionSpace	reconstruction_space,
		const SamplingFunctional	polynomial_sampling_functional,
		const int	evaluation_site_local_index = `0`
	)

Evaluates the gradient of a polynomial basis under the Dirac Delta (pointwise) sampling function.

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _poly_order*the spatial dimension of the polynomial basis.
target_index	[in] - target number
neighbor_index	[in] - index of neighbor for this target with respect to local numbering [0,...,number of neighbors for target]
alpha	[in] - double to determine convex combination of target and neighbor site at which to evaluate polynomials. (1-alpha)neighbor + alphatarget
partial_direction	[in] - direction that partial is taken with respect to, e.g. 0 is x direction, 1 is y direction
dimension	[in] - spatial dimension of basis to evaluate. e.g. dimension two basis of order one is 1, x, y, whereas for dimension 3 it is 1, x, y, z
poly_order	[in] - polynomial basis degree
specific_order_only	[in] - boolean for only evaluating one degree of polynomial when true
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane
reconstruction_space	[in] - space of polynomial that a sampling functional is to evaluate
sampling_strategy	[in] - sampling functional specification
evaluation_site_local_index	[in] - local index for evaluation sites (0 is target site)

Definition at line 681 of file Compadre_Basis.hpp.

template<typename BasisData >

KOKKOS_INLINE_FUNCTION void Compadre::calcHessianPij	(	const BasisData &	data,
		const member_type &	teamMember,
		double *	delta,
		double *	thread_workspace,
		const int	target_index,
		int	neighbor_index,
		const double	alpha,
		const int	partial_direction_1,
		const int	partial_direction_2,
		const int	dimension,
		const int	poly_order,
		bool	specific_order_only,
		const scratch_matrix_right_type *	V,
		const ReconstructionSpace	reconstruction_space,
		const SamplingFunctional	polynomial_sampling_functional,
		const int	evaluation_site_local_index = `0`
	)

Evaluates the Hessian of a polynomial basis under the Dirac Delta (pointwise) sampling function.

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _poly_order*the spatial dimension of the polynomial basis.
target_index	[in] - target number
neighbor_index	[in] - index of neighbor for this target with respect to local numbering [0,...,number of neighbors for target]
alpha	[in] - double to determine convex combination of target and neighbor site at which to evaluate polynomials. (1-alpha)neighbor + alphatarget
partial_direction_1	[in] - first direction that partial is taken with respect to, e.g. 0 is x direction, 1 is y direction
partial_direction_2	[in] - second direction that partial is taken with respect to, e.g. 0 is x direction, 1 is y direction
dimension	[in] - spatial dimension of basis to evaluate. e.g. dimension two basis of order one is 1, x, y, whereas for dimension 3 it is 1, x, y, z
poly_order	[in] - polynomial basis degree
specific_order_only	[in] - boolean for only evaluating one degree of polynomial when true
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane
reconstruction_space	[in] - space of polynomial that a sampling functional is to evaluate
sampling_strategy	[in] - sampling functional specification
evaluation_site_local_index	[in] - local index for evaluation sites (0 is target site)

Definition at line 769 of file Compadre_Basis.hpp.

template<typename BasisData >

KOKKOS_INLINE_FUNCTION void Compadre::calcPij	(	const BasisData &	data,
		const member_type &	teamMember,
		double *	delta,
		double *	thread_workspace,
		const int	target_index,
		int	neighbor_index,
		const double	alpha,
		const int	dimension,
		const int	poly_order,
		bool	specific_order_only = `false`,
		const scratch_matrix_right_type *	V = `NULL`,
		const ReconstructionSpace	reconstruction_space = `ReconstructionSpace::ScalarTaylorPolynomial`,
		const SamplingFunctional	polynomial_sampling_functional = `PointSample`,
		const int	evaluation_site_local_index = `0`
	)

Evaluates the polynomial basis under a particular sampling function. Generally used to fill a row of P.

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _poly_order*the spatial dimension of the polynomial basis.
target_index	[in] - target number
neighbor_index	[in] - index of neighbor for this target with respect to local numbering [0,...,number of neighbors for target]
alpha	[in] - double to determine convex combination of target and neighbor site at which to evaluate polynomials. (1-alpha)neighbor + alphatarget
dimension	[in] - spatial dimension of basis to evaluate. e.g. dimension two basis of order one is 1, x, y, whereas for dimension 3 it is 1, x, y, z
poly_order	[in] - polynomial basis degree
specific_order_only	[in] - boolean for only evaluating one degree of polynomial when true
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane
reconstruction_space	[in] - space of polynomial that a sampling functional is to evaluate
sampling_strategy	[in] - sampling functional specification
evaluation_site_local_index	[in] - local index for evaluation sites (0 is target site)

Definition at line 34 of file Compadre_Basis.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::calculateBasisMultiplier	(	const ReconstructionSpace	rs,
		const int	local_dimensions
	)

Calculate basis_multiplier.

Definition at line 268 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::calculateSamplingMultiplier	(	const ReconstructionSpace	rs,
		const SamplingFunctional	sro,
		const int	local_dimensions
	)

Calculate sampling_multiplier.

Definition at line 276 of file Compadre_Misc.hpp.

template<typename TargetData >

KOKKOS_INLINE_FUNCTION void Compadre::computeCurvatureFunctionals	(	const TargetData &	data,
		const member_type &	teamMember,
		scratch_vector_type	delta,
		scratch_vector_type	thread_workspace,
		scratch_matrix_right_type	P_target_row,
		const scratch_matrix_right_type *	V,
		const local_index_type	local_neighbor_index = `-1`
	)

Evaluates a polynomial basis for the curvature with a gradient target functional applied.

data._operations is used by this function which is set through a modifier function

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _curvature_poly_order*the spatial dimension of the polynomial basis.
P_target_row	[out] - 1D Kokkos View where the evaluation of the polynomial basis is stored
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane

Definition at line 1055 of file Compadre_Targets.hpp.

template<typename TargetData >

KOKKOS_INLINE_FUNCTION void Compadre::computeTargetFunctionals	(	const TargetData &	data,
		const member_type &	teamMember,
		scratch_vector_type	delta,
		scratch_vector_type	thread_workspace,
		scratch_matrix_right_type	P_target_row
	)

Evaluates a polynomial basis with a target functional applied to each member of the basis.

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each team has its own copy. Must be at least as large is the _poly_order*_global_dimensions.
P_target_row	[out] - 1D Kokkos View where the evaluation of the polynomial basis is stored

Definition at line 26 of file Compadre_Targets.hpp.

template<typename TargetData >

KOKKOS_INLINE_FUNCTION void Compadre::computeTargetFunctionalsOnManifold	(	const TargetData &	data,
		const member_type &	teamMember,
		scratch_vector_type	delta,
		scratch_vector_type	thread_workspace,
		scratch_matrix_right_type	P_target_row,
		scratch_matrix_right_type	V,
		scratch_vector_type	curvature_coefficients
	)

Evaluates a polynomial basis with a target functional applied, using information from the manifold curvature.

data._operations is used by this function which is set through a modifier function

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _curvature_poly_order*the spatial dimension of the polynomial basis.
P_target_row	[out] - 1D Kokkos View where the evaluation of the polynomial basis is stored
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane
curvature_coefficients	[in] - polynomial coefficients for curvature

Definition at line 1124 of file Compadre_Targets.hpp.

template<typename view_type_2d , typename view_type_1d = Kokkos::View<int*, typename view_type_2d::memory_space, typename view_type_2d::memory_traits>>

NeighborLists<view_type_1d> Compadre::Convert2DToCompressedRowNeighborLists ( view_type_2d neighbor_lists )

Converts 2D neighbor lists to compressed row neighbor lists.

Definition at line 332 of file Compadre_NeighborLists.hpp.

T2 Compadre::copyToAndReturnOriginalView ( )

Definition at line 95 of file Compadre_Evaluator.hpp.

template<typename T >

auto Compadre::CreateNDSliceOnDeviceView	(	T	sampling_input_data_host_or_device,
		bool	scalar_as_vector_if_needed
	)		-> SubviewND<decltype(Kokkos::create_mirror_view( device_memory_space(), sampling_input_data_host_or_device)), T>

Copies data_in to the device, and then allows for access to 1D columns of data on device.

Handles either 2D or 1D views as input, and they can be on the host or the device.

Definition at line 106 of file Compadre_Evaluator.hpp.

template<typename view_type >

NeighborLists<view_type> Compadre::CreateNeighborLists ( view_type number_of_neighbors_list )

CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction.

Definition at line 314 of file Compadre_NeighborLists.hpp.

template<typename view_type >

NeighborLists<view_type> Compadre::CreateNeighborLists	(	view_type	neighbor_lists,
		view_type	number_of_neighbors_list
	)

CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction.

Definition at line 320 of file Compadre_NeighborLists.hpp.

template<typename view_type >

NeighborLists<view_type> Compadre::CreateNeighborLists	(	view_type	neighbor_lists,
		view_type	number_of_neighbors_list,
		view_type	neighbor_lists_row_offsets
	)

CreateNeighborLists allows for the construction of an object of type NeighborLists with template deduction.

Definition at line 326 of file Compadre_NeighborLists.hpp.

template<typename view_type >

PointCloudSearch<view_type> Compadre::CreatePointCloudSearch	(	view_type	src_view,
		const local_index_type	dimensions = `-1`,
		const local_index_type	max_leaf = `-1`
	)

CreatePointCloudSearch allows for the construction of an object of type PointCloudSearch with template deduction.

Examples:: GMLS Tutorial, and Manifold GMLS Tutorial.

Definition at line 796 of file Compadre_PointCloudSearch.hpp.

template<typename BasisData >

KOKKOS_INLINE_FUNCTION void Compadre::createWeightsAndP	(	const BasisData &	data,
		const member_type &	teamMember,
		scratch_vector_type	delta,
		scratch_vector_type	thread_workspace,
		scratch_matrix_right_type	P,
		scratch_vector_type	w,
		const int	dimension,
		int	polynomial_order,
		bool	weight_p = `false`,
		scratch_matrix_right_type *	V = `NULL`,
		const ReconstructionSpace	reconstruction_space = `ReconstructionSpace::ScalarTaylorPolynomial`,
		const SamplingFunctional	polynomial_sampling_functional = `PointSample`
	)

Fills the _P matrix with either P or P*sqrt(w)

Parameters

data	[in] - GMLSBasisData struct
teamMember	[in] - Kokkos::TeamPolicy member type (created by parallel_for)
delta	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the _basis_multipler*the dimension of the polynomial basis.
thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _poly_order*the spatial dimension of the polynomial basis.
P	[out] - 2D Kokkos View which will contain evaluation of sampling functional on polynomial basis for each neighbor the target has (stored column major)
w	[out] - 1D Kokkos View which will contain weighting kernel values for the target with each neighbor if weight_p = true
dimension	[in] - spatial dimension of basis to evaluate. e.g. dimension two basis of order one is 1, x, y, whereas for dimension 3 it is 1, x, y, z
polynomial_order	[in] - polynomial basis degree
weight_p	[in] - boolean whether to fill w with kernel weights
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane
reconstruction_space	[in] - space of polynomial that a sampling functional is to evaluate
sampling_strategy	[in] - sampling functional specification

Definition at line 850 of file Compadre_Basis.hpp.

template<typename BasisData >

KOKKOS_INLINE_FUNCTION void Compadre::createWeightsAndPForCurvature	(	const BasisData &	data,
		const member_type &	teamMember,
		scratch_vector_type	delta,
		scratch_vector_type	thread_workspace,
		scratch_matrix_right_type	P,
		scratch_vector_type	w,
		const int	dimension,
		bool	only_specific_order,
		scratch_matrix_right_type *	V = `NULL`
	)

Fills the _P matrix with P*sqrt(w) for use in solving for curvature.

 Uses _curvature_poly_order as the polynomial order of the basis

\param data                 [in] - GMLSBasisData struct
\param teamMember           [in] - Kokkos::TeamPolicy member type (created by parallel_for)
\param delta            [in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large is the

s_multipler*the dimension of the polynomial basis.

Parameters

thread_workspace	[in/out] - scratch space that is allocated so that each thread has its own copy. Must be at least as large as the _order*the spatial dimension of the polynomial basis.
P	[out] - 2D Kokkos View which will contain evaluation of sampling functional on polynomial basis for each neighbor the target has (stored column major)
w	[out] - 1D Kokkos View which will contain weighting kernel values for the target with each neighbor if weight_p = true
dimension	[in] - spatial dimension of basis to evaluate. e.g. dimension two basis of order one is 1, x, y, whereas for dimension 3 it is 1, x, y, z
only_specific_order	[in] - boolean for only evaluating one degree of polynomial when true
V	[in] - orthonormal basis matrix size _dimensions * _dimensions whose first _dimensions-1 columns are an approximation of the tangent plane

Definition at line 947 of file Compadre_Basis.hpp.

template<typename T , typename T2 >

struct SubviewND< T, T2, enable_if_t<(T::rank< 2)> >{T _data_in;T2 _data_original_view;bool _scalar_as_vector_if_needed;SubviewND(T data_in, T2 data_original_view, bool scalar_as_vector_if_needed){_data_in=data_in;_data_original_view=data_original_view;_scalar_as_vector_if_needed=scalar_as_vector_if_needed;}auto get1DView(const int column_num) -> Compadre::decltype ( Kokkos:: subview_data_in, Kokkos::ALL )

Creates 1D subviews of data from a 1D view, generally constructed with CreateNDSliceOnDeviceView.

Examples:: GMLS Tutorial.

Definition at line 80 of file Compadre_Evaluator.hpp.

KOKKOS_INLINE_FUNCTION void Compadre::evaluateConstraints	(	scratch_matrix_right_type	M,
		scratch_matrix_right_type	PsqrtW,
		const ConstraintType	constraint_type,
		const ReconstructionSpace	reconstruction_space,
		const int	NP,
		const double	cutoff_p,
		const int	dimension,
		const int	num_neighbors = `0`,
		scratch_matrix_right_type *	T = `NULL`
	)

Definition at line 17 of file Compadre_CreateConstraints.hpp.

template<typename output_memory_space , typename view_type_input_data , typename output_array_layout = typename view_type_input_data::array_layout, typename index_type = int>

Kokkos::View<int*, output_array_layout, output_memory_space> Compadre::filterViewByID	(	view_type_input_data	input_data_host_or_device,
		index_type	filtered_value
	)

Definition at line 55 of file Compadre_Utilities.hpp.

KOKKOS_INLINE_FUNCTION double Compadre::GaussianCurvature	(	const scratch_vector_type	a_,
		const double	h,
		const double	u1,
		const double	u2
	)

Gaussian curvature K at any point in the local chart.

Definition at line 58 of file Compadre_Manifold_Functions.hpp.

auto Compadre::get2DView	(	const int	column_num,
		const int	block_size
	)		-> decltype(Kokkos::subview(_data_in, Kokkos::ALL))

Definition at line 90 of file Compadre_Evaluator.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getActualReconstructionSpaceRank ( const int & index )

Number of actual components in the ReconstructionSpace.

< ScalarTaylorPolynomial

< VectorTaylorPolynomial

< VectorOfScalarClonesTaylorPolynomial

< DivergenceFreeVectorTaylorPolynomial

< BernsteinPolynomial

Definition at line 121 of file Compadre_Operators.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getAdditionalAlphaSizeFromConstraint	(	DenseSolverType	dense_solver_type,
		ConstraintType	constraint_type
	)

Definition at line 169 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getAdditionalCoeffSizeFromConstraintAndSpace	(	DenseSolverType	dense_solver_type,
		ConstraintType	constraint_type,
		ReconstructionSpace	reconstruction_space,
		const int	dimension
	)

Definition at line 179 of file Compadre_Misc.hpp.

template<typename view_type_1 , typename view_type_2 >

KOKKOS_INLINE_FUNCTION double Compadre::getAreaFromVectors	(	const member_type &	teamMember,
		view_type_1	v1,
		view_type_2	v2
	)

Definition at line 32 of file Compadre_Utilities.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getInputDimensionOfOperation	(	TargetOperation	lro,
		SamplingFunctional	sro,
		const int	local_dimensions
	)

Dimensions ^ input rank for target operation (always in local chart if on a manifold, never ambient space)

Definition at line 298 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getInputDimensionOfSampling	(	SamplingFunctional	sro,
		const int	global_dimensions
	)

Dimensions ^ output rank for sampling operation (always in ambient space, never local chart on a manifold)

Definition at line 262 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getInputRankOfSampling ( SamplingFunctional sro )

Input rank for sampling operation.

Definition at line 248 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION void Compadre::getMidpointFromCellVertices	(	const member_type &	teamMember,
		scratch_vector_type	midpoint_storage,
		scratch_matrix_right_type	cell_coordinates,
		const int	cell_num,
		const int	dim = `3`
	)

Definition at line 18 of file Compadre_Utilities.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getOutputDimensionOfOperation	(	TargetOperation	lro,
		const int	local_dimensions
	)

Dimensions ^ output rank for target operation.

Definition at line 292 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getOutputDimensionOfSampling	(	SamplingFunctional	sro,
		const int	local_dimensions
	)

Dimensions ^ output rank for sampling operation (always in local chart if on a manifold, never ambient space)

Definition at line 255 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION void Compadre::getPDims	(	DenseSolverType	dense_solver_type,
		ConstraintType	constraint_type,
		ReconstructionSpace	reconstruction_space,
		const int	dimension,
		const int	M,
		const int	N,
		int &	out_row,
		int &	out_col
	)

Definition at line 210 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION void Compadre::getRHSDims	(	DenseSolverType	dense_solver_type,
		ConstraintType	constraint_type,
		ReconstructionSpace	reconstruction_space,
		const int	dimension,
		const int	M,
		const int	N,
		int &	RHS_row,
		int &	RHS_col
	)

Definition at line 190 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getSamplingOutputIndex	(	const SamplingFunctional	sf,
		const int	output_component_axis_1,
		const int	output_component_axis_2
	)

Helper function for finding alpha coefficients.

Definition at line 241 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getTargetOutputIndex	(	const int	operation_num,
		const int	output_component_axis_1,
		const int	output_component_axis_2,
		const int	dimensions
	)

Helper function for finding alpha coefficients.

Definition at line 234 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::getTargetOutputTensorRank ( const int & index )

Rank of target functional output for each TargetOperation Rank of target functional input for each TargetOperation is based on the output rank of the SamplingFunctional used on the polynomial basis.

< PointEvaluation

< VectorPointEvaluation

< LaplacianOfScalarPointEvaluation

< VectorLaplacianPointEvaluation

< GradientOfScalarPointEvaluation

< GradientOfVectorPointEvaluation

< DivergenceOfVectorPointEvaluation

< CurlOfVectorPointEvaluation

< CurlCurlOfVectorPointEvaluation

< PartialXOfScalarPointEvaluation

< PartialYOfScalarPointEvaluation

< PartialZOfScalarPointEvaluation

< ChainedStaggeredLaplacianOfScalarPointEvaluation

< GaussianCurvaturePointEvaluation

< CellAverageEvaluation

< CellIntegralEvaluation

< FaceNormalAverageEvaluation

< FaceNormalIntegralEvaluation

< EdgeTangentAverageEvaluation

< EdgeTangentIntegralEvaluation

Definition at line 76 of file Compadre_Operators.hpp.

KOKKOS_INLINE_FUNCTION double Compadre::MetricFactor	(	const scratch_vector_type	a_,
		const double	h,
		const double	u1,
		const double	u2
	)

Metric factor (det(G)) at any point in the local chart.

Definition at line 14 of file Compadre_Manifold_Functions.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator*	(	const XYZ &	vecA,
		const XYZ &	vecB
	)

Definition at line 113 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator*	(	const XYZ &	vecA,
		const scalar_type &	constant
	)

Definition at line 133 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator*	(	const scalar_type &	constant,
		const XYZ &	vecA
	)

Definition at line 137 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator+	(	const XYZ &	vecA,
		const XYZ &	vecB
	)

Definition at line 105 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator+	(	const XYZ &	vecA,
		const scalar_type &	constant
	)

Definition at line 117 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator+	(	const scalar_type &	constant,
		const XYZ &	vecA
	)

Definition at line 121 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator-	(	const XYZ &	vecA,
		const XYZ &	vecB
	)

Definition at line 109 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator-	(	const XYZ &	vecA,
		const scalar_type &	constant
	)

Definition at line 125 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator-	(	const scalar_type &	constant,
		const XYZ &	vecA
	)

Definition at line 129 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION XYZ Compadre::operator/	(	const XYZ &	vecA,
		const scalar_type &	constant
	)

Definition at line 141 of file Compadre_Misc.hpp.

std::ostream& Compadre::operator<<	(	std::ostream &	os,
		const XYZ &	vec
	)

inline

Definition at line 144 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION int Compadre::pown	(	int	n,
		unsigned	p
	)

n^p (n^0 returns 1, regardless of n)

Definition at line 149 of file Compadre_Misc.hpp.

KOKKOS_INLINE_FUNCTION double Compadre::SurfaceCurlOfScalar	(	const scratch_vector_type	a_,
		const double	h,
		const double	u1,
		const double	u2,
		int	x_pow,
		int	y_pow,
		const int	component
	)

Surface curl at any point in the local chart.

Definition at line 104 of file Compadre_Manifold_Functions.hpp.

Variable Documentation

constexpr SamplingFunctional Compadre::CellAverageSample = make_sampling_functional(0,0,false,false,(int)DifferentEachNeighbor)

For polynomial integrated on cells.

Definition at line 211 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::CellIntegralSample = make_sampling_functional(0,0,false,false,(int)DifferentEachNeighbor)

For polynomial integrated on cells.

Definition at line 214 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::EdgeTangentAverageSample = make_sampling_functional(1,0,false,false,(int)Identity)

For polynomial dotted with tangent.

Definition at line 208 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::EdgeTangentIntegralSample = make_sampling_functional(1,0,false,false,(int)Identity)

For integrating polynomial dotted with tangent over an edge.

Definition at line 205 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::FaceNormalAverageSample = make_sampling_functional(1,0,false,false,(int)Identity)

For polynomial dotted with normal on edge.

Definition at line 202 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::FaceNormalIntegralSample = make_sampling_functional(1,0,false,false,(int)Identity)

For integrating polynomial dotted with normal over an edge.

Definition at line 199 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::ManifoldVectorPointSample = make_sampling_functional(1,1,false,false,(int)DifferentEachTarget)

Point evaluations of the entire vector source function (but on a manifold, so it includes a transform into local coordinates)

Examples:: Manifold GMLS Tutorial.

Definition at line 187 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::PointSample = make_sampling_functional(0,0,false,false,(int)Identity)

Available sampling functionals.

Point evaluations of the scalar source function

Definition at line 180 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::StaggeredEdgeAnalyticGradientIntegralSample = make_sampling_functional(0,0,true,true,(int)SameForAll)

Analytical integral of a gradient source vector is just a difference of the scalar source at neighbor and target.

Definition at line 190 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::StaggeredEdgeIntegralSample = make_sampling_functional(1,0,true,true,(int)DifferentEachNeighbor)

Samples consist of the result of integrals of a vector dotted with the tangent along edges between neighbor and target.

Definition at line 193 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::VaryingManifoldVectorPointSample = make_sampling_functional(1,1,false,false,(int)DifferentEachNeighbor)

For integrating polynomial dotted with normal over an edge.

Definition at line 196 of file Compadre_Operators.hpp.

constexpr SamplingFunctional Compadre::VectorPointSample = make_sampling_functional(1,1,false,false,(int)Identity)

Point evaluations of the entire vector source function.

Examples:: GMLS Tutorial.

Definition at line 183 of file Compadre_Operators.hpp.

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