PLearn::SourceKernel Class Reference

#include <SourceKernel.h>

Inheritance diagram for PLearn::SourceKernel:

[legend]Collaboration diagram for PLearn::SourceKernel:

[legend]List of all members.

Public Member Functions
	SourceKernel ()
	Default constructor.
virtual void	build ()
	Simply calls inherited::build() then build_().
virtual void	makeDeepCopyFromShallowCopy (map< const void *, void * > &copies)
	Transforms a shallow copy into a deep copy.
	PLEARN_DECLARE_OBJECT (SourceKernel)
virtual real	evaluate (const Vec &x1, const Vec &x2) const
	Compute K(x1,x2).
virtual void	addDataForKernelMatrix (const Vec &newRow)
	Overridden to forward to source_kernel.
virtual void	computeGramMatrix (Mat K) const
	Call evaluate_i_j to fill each of the entries (i,j) of symmetric matrix K.
virtual real	evaluate_i_j (int i, int j) const
	returns evaluate(data(i),data(j))
virtual real	evaluate_i_x (int i, const Vec &x, real squared_norm_of_x=-1) const
virtual real	evaluate_x_i (const Vec &x, int i, real squared_norm_of_x=-1) const
	returns evaluate(x,data(i)) [default version calls evaluate_i_x if kernel is_symmetric]
virtual void	setDataForKernelMatrix (VMat the_data)
	** Subclasses may overload these methods to provide efficient kernel matrix access **
virtual void	setParameters (Vec paramvec)
	default version produces an error
virtual Vec	getParameters () const
	default version returns an empty Vec
Public Attributes
Ker	source_kernel
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	Declares this class' options.
Private Types
typedef Kernel	inherited
Private Member Functions
void	build_ ()
	This does the actual building.

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Member Typedef Documentation

typedef Kernel PLearn::SourceKernel::inherited [private]

Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 57 of file SourceKernel.h.

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Constructor & Destructor Documentation

PLearn::SourceKernel::SourceKernel (   )

Default constructor. Definition at line 51 of file SourceKernel.cc.

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Member Function Documentation

void PLearn::SourceKernel::addDataForKernelMatrix (  const Vec &  newRow  )  [virtual]

Overridden to forward to source_kernel. Reimplemented from PLearn::Kernel. Definition at line 103 of file SourceKernel.cc. References source_kernel, and PLearn::Vec.

void PLearn::SourceKernel::build (   )  [virtual]

Simply calls inherited::build() then build_(). Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 77 of file SourceKernel.cc. References build_().

void PLearn::SourceKernel::build_ (   )  [private]

This does the actual building. Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 86 of file SourceKernel.cc. References source_kernel. Referenced by build().

void PLearn::SourceKernel::computeGramMatrix (  Mat  K  )  const [virtual]

Call evaluate_i_j to fill each of the entries (i,j) of symmetric matrix K. Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 113 of file SourceKernel.cc. References PLearn::Mat, and source_kernel.

void PLearn::SourceKernel::declareOptions (  OptionList &  ol  )  [static, protected]

Declares this class' options. Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 65 of file SourceKernel.cc. References PLearn::declareOption(), and PLearn::OptionList.

real PLearn::SourceKernel::evaluate (  const Vec &  x1, const Vec &  x2 )  const [virtual]

Compute K(x1,x2). Implements PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 120 of file SourceKernel.cc. References source_kernel.

real PLearn::SourceKernel::evaluate_i_j (  int  i, int  j )  const [virtual]

returns evaluate(data(i),data(j)) Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 127 of file SourceKernel.cc. References source_kernel.

real PLearn::SourceKernel::evaluate_i_x (  int  i, const Vec &  x, real  squared_norm_of_x = -1 )  const [virtual]

returns evaluate(data(i),x) [squared_norm_of_x is just a hint that may allow to speed up computation if it is already known, but it's optional] Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 134 of file SourceKernel.cc. References source_kernel, and x.

real PLearn::SourceKernel::evaluate_x_i (  const Vec &  x, int  i, real  squared_norm_of_x = -1 )  const [virtual]

returns evaluate(x,data(i)) [default version calls evaluate_i_x if kernel is_symmetric] Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 141 of file SourceKernel.cc. References source_kernel, and x.

Vec PLearn::SourceKernel::getParameters (   )  const [virtual]

default version returns an empty Vec Reimplemented from PLearn::Kernel. Definition at line 148 of file SourceKernel.cc. References source_kernel.

void PLearn::SourceKernel::makeDeepCopyFromShallowCopy (  map< const void *, void * > &  copies  )  [virtual]

Transforms a shallow copy into a deep copy. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 155 of file SourceKernel.cc. References PLearn::deepCopyField(), and source_kernel.

PLearn::SourceKernel::PLEARN_DECLARE_OBJECT (  SourceKernel   )

void PLearn::SourceKernel::setDataForKernelMatrix (  VMat  the_data  )  [virtual]

** Subclasses may overload these methods to provide efficient kernel matrix access ** This method sets the data VMat that will be used to define the kernel matrix. It may precompute values from this that may later accelerate the evaluation of a kernel matrix element Reimplemented from PLearn::Kernel. Reimplemented in PLearn::AdditiveNormalizationKernel, and PLearn::DivisiveNormalizationKernel. Definition at line 164 of file SourceKernel.cc. References source_kernel.

void PLearn::SourceKernel::setParameters (  Vec  paramvec  )  [virtual]

default version produces an error Reimplemented from PLearn::Kernel. Definition at line 172 of file SourceKernel.cc. References source_kernel.

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Member Data Documentation

Ker PLearn::SourceKernel::source_kernel

Definition at line 71 of file SourceKernel.h. Referenced by addDataForKernelMatrix(), build_(), computeGramMatrix(), evaluate(), evaluate_i_j(), evaluate_i_x(), evaluate_x_i(), getParameters(), makeDeepCopyFromShallowCopy(), setDataForKernelMatrix(), and setParameters().

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

• SourceKernel.h
• SourceKernel.cc

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