Inheritance diagram for hmlp::KernelMatrix< T, Allocator >:

Public Member Functions
	KernelMatrix (size_t m_, size_t n_, size_t d_, kernel_s< T, T > &kernel_, Data< T > &sources_, Data< T > &targets_)

	KernelMatrix (size_t m, size_t n, size_t d, kernel_s< T, T > &kernel, Data< T > &sources)

	KernelMatrix (Data< T > &sources)

	~KernelMatrix ()

virtual T	operator() (size_t i, size_t j) override

virtual Data< T >	operator() (const vector< size_t > &I, const vector< size_t > &J) override

virtual Data< T >	GeometryDistances (const vector< size_t > &I, const vector< size_t > &J) override

Data< T >	Diagonal (vector< size_t > &I)

pair< T, size_t >	ImportantSample (size_t j)

void	Print ()

size_t	dim ()

double	flops (size_t na, size_t nb)

Public Member Functions inherited from hmlp::VirtualMatrix< T, Allocator >
	VirtualMatrix (size_t m, size_t n)

virtual void	resize (size_t m, size_t n)

size_t	row ()

size_t	col ()

Data< T >	KernelDistances (const vector< size_t > &I, const vector< size_t > &J)

Data< T >	AngleDistances (const vector< size_t > &I, const vector< size_t > &J)

virtual Data< T >	UserDistances (const vector< size_t > &I, const vector< size_t > &J)

Data< T >	Distances (DistanceMetric metric, const vector< size_t > &I, const vector< size_t > &J)

virtual Data< pair< T, size_t > >	NeighborSearch (DistanceMetric metric, size_t kappa, const vector< size_t > &Q, const vector< size_t > &R, pair< T, size_t > init)

virtual Data< T >	Diagonal (const vector< size_t > &I)

virtual pair< T, int >	ImportantSample (int j)

Public Member Functions inherited from hmlp::SPDMatrixMPISupport< T >
virtual void	SendIndices (vector< size_t > ids, int dest, mpi::Comm comm)

virtual void	RecvIndices (int src, mpi::Comm comm, mpi::Status *status)

virtual void	BcastIndices (vector< size_t > ids, int root, mpi::Comm comm)

virtual void	RequestIndices (const vector< vector< size_t >> &ids)

Public Member Functions inherited from hmlp::ReadWrite
	ReadWrite ()

void	DependencyAnalysis (ReadWriteType type, Task *task)
	This is the key function that encode the dependency. More...

void	DependencyCleanUp ()

Additional Inherited Members
Public Types inherited from hmlp::VirtualMatrix< T, Allocator >
typedef T	T

Public Attributes inherited from hmlp::ReadWrite
deque< Task * >	read

deque< Task * >	write

Constructor & Destructor Documentation

template<typename T, class Allocator = std::allocator<T>>

hmlp::KernelMatrix< T, Allocator >::KernelMatrix	(	size_t	m_,
		size_t	n_,
		size_t	d_,
		kernel_s< T, T > &	kernel_,
		Data< T > &	sources_,
		Data< T > &	targets_
	)

inline

(Default) constructor for non-symmetric kernel matrices.

template<typename T, class Allocator = std::allocator<T>>

hmlp::KernelMatrix< T, Allocator >::KernelMatrix	(	size_t	m,
		size_t	n,
		size_t	d,
		kernel_s< T, T > &	kernel,
		Data< T > &	sources
	)

inline

(Default) constructor for symmetric kernel matrices.

template<typename T, class Allocator = std::allocator<T>>

hmlp::KernelMatrix< T, Allocator >::~KernelMatrix ( )

inline

(Default) destructor.

Member Function Documentation

template<typename T, class Allocator = std::allocator<T>>

Data<T> hmlp::KernelMatrix< T, Allocator >::Diagonal ( vector< size_t > & I )

inline

end GeometryDistances() get the diagonal of KII, i.e. diag( K( I, I ) )

return values

at this moment we already have the corrdinates on this process

template<typename T, class Allocator = std::allocator<T>>

size_t hmlp::KernelMatrix< T, Allocator >::dim ( )

inline

end Print() Return number of attributes.

template<typename T, class Allocator = std::allocator<T>>

double hmlp::KernelMatrix< T, Allocator >::flops	(	size_t	na,
		size_t	nb
	)

inline

flops required for Kab

template<typename T, class Allocator = std::allocator<T>>

virtual Data<T> hmlp::KernelMatrix< T, Allocator >::GeometryDistances	(	const vector< size_t > &	I,
		const vector< size_t > &	J
	)

inlineoverridevirtual

Early return if possible.

Request for coordinates: A (targets), B (sources).

For symmetry matrices, extract from sources.

For non-symmetry matrices, extract from targets and sources.

Compute inner products.

Compute square 2-norms.

end omp parallel for

Add square norms to inner products to get square distances.

Return all pair-wise distances.

Reimplemented from hmlp::VirtualMatrix< T, Allocator >.

template<typename T, class Allocator = std::allocator<T>>

pair<T, size_t> hmlp::KernelMatrix< T, Allocator >::ImportantSample ( size_t j )

inlinevirtual

important sampling

Reimplemented from hmlp::VirtualMatrix< T, Allocator >.

template<typename T, class Allocator = std::allocator<T>>

virtual T hmlp::KernelMatrix< T, Allocator >::operator()	(	size_t	i,
		size_t	j
	)

inlineoverridevirtual

ESSENTIAL: override the virtual function

Implements hmlp::VirtualMatrix< T, Allocator >.

template<typename T, class Allocator = std::allocator<T>>

virtual Data<T> hmlp::KernelMatrix< T, Allocator >::operator()	(	const vector< size_t > &	I,
		const vector< size_t > &	J
	)

inlineoverridevirtual

(Overwrittable) ESSENTIAL: return K( I, J )

Early return if possible.

Request for coordinates: A (targets), B (sources).

Evaluate KIJ using legacy interface.

Return K( I, J ).

Reimplemented from hmlp::VirtualMatrix< T, Allocator >.

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

/home/chenhany/Projects/hmlp/frame/containers/KernelMatrix.hpp

Public Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation