PLearn::GeodesicDistanceKernel Class Reference

#include <GeodesicDistanceKernel.h>

Inheritance diagram for PLearn::GeodesicDistanceKernel:

[legend]Collaboration diagram for PLearn::GeodesicDistanceKernel:

[legend]List of all members.


Public Member Functions
	GeodesicDistanceKernel ()
	Default constructor.
	GeodesicDistanceKernel (Ker the_distance_kernel, int the_knn=10, string the_geodesic_file="", bool the_pow_distance=false)
	Convenient 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 (GeodesicDistanceKernel)
int	computeNearestGeodesicNeighbour (int i, const Mat &distances_xi_x_sorted, real *dist_i=0) const
	Return the index j of the data point which satisfies: 1.
real	computeShortestDistance (int i, const Mat &distances_xi_x_sorted) const
	Return the shortest (geodesic) distance to i from a point x whose (non-geodesic) distance to its knn nearest neighbors in the training set is given by the matrix 'distances_xi_x_sorted', whose first column should contain the sorted distances, and whose second column should contain the corresponding indices.
virtual real	evaluate (const Vec &x1, const Vec &x2) const
	Compute K(x1,x2).
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_i_x_again (int i, const Vec &x, real squared_norm_of_x=-1, bool first_time=false) const
	Return evaluate(data(i),x), where x is the same as in the precedent call to this same function (except if 'first_time' is true).
virtual real	evaluate_i_x_from_distances (int i, const Mat &distances_xi_x_sorted) const
	Evaluate K(x_i,x) where x is not given explicitly, but only by the (sorted and non-geodesic) distances to all training points.
virtual void	setDataForKernelMatrix (VMat the_data)
	Overridden to precompute inter-points geodesic distance.
Public Attributes
Ker	distance_kernel
string	geodesic_file
int	knn
bool	pow_distance
string	shortest_algo
VMat	geo_distances
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.
Private Attributes
Mat	dist_xi_x_sorted1
	Used to store data and save memory allocation.
Mat	dist_xi_x_sorted2
	Used to store data and save memory allocation.
Mat	dist_xi_x_sorted
	Used to store data and save memory allocation.

Member Typedef Documentation

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

Reimplemented from PLearn::Kernel.
Definition at line 57 of file GeodesicDistanceKernel.h.

Constructor & Destructor Documentation

PLearn::GeodesicDistanceKernel::GeodesicDistanceKernel ( )

Default constructor.

Definition at line 54 of file GeodesicDistanceKernel.cc.
References distance_kernel.

PLearn::GeodesicDistanceKernel::GeodesicDistanceKernel ( Ker the_distance_kernel,

int the_knn = 10,

string the_geodesic_file = "",

bool the_pow_distance = false

)

Convenient constructor.

Definition at line 63 of file GeodesicDistanceKernel.cc.
References build(), and distance_kernel.

Member Function Documentation

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

Simply calls inherited::build() then build_().

Reimplemented from PLearn::Kernel.
Definition at line 115 of file GeodesicDistanceKernel.cc.
References build_().
Referenced by GeodesicDistanceKernel().

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

This does the actual building.

Reimplemented from PLearn::Kernel.
Definition at line 124 of file GeodesicDistanceKernel.cc.
Referenced by build().

int PLearn::GeodesicDistanceKernel::computeNearestGeodesicNeighbour ( int i,

const Mat & distances_xi_x_sorted,

real * dist_i = 0

) const

Return the index j of the data point which satisfies: 1.
j is among the knn nearest neighbors of the point x from which was computed 'distances_xi_x_sorted' 2. it is such that dist(x,j) + geodesic_dist(j,x_i) is minimum If provided, the 'dist_i' parameter is filled with the geodesic distance from x to x_i.
Definition at line 131 of file GeodesicDistanceKernel.cc.
References PLearn::dist(), geo_distances, knn, PLearn::Mat, and PLearn::min().
Referenced by computeShortestDistance().

real PLearn::GeodesicDistanceKernel::computeShortestDistance ( int i,

const Mat & distances_xi_x_sorted

) const

Return the shortest (geodesic) distance to i from a point x whose (non-geodesic) distance to its knn nearest neighbors in the training set is given by the matrix 'distances_xi_x_sorted', whose first column should contain the sorted distances, and whose second column should contain the corresponding indices.

Definition at line 150 of file GeodesicDistanceKernel.cc.
References computeNearestGeodesicNeighbour().
Referenced by evaluate_i_x_again(), and evaluate_i_x_from_distances().

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

Declares this class' options.

Reimplemented from PLearn::Kernel.
Definition at line 82 of file GeodesicDistanceKernel.cc.
References PLearn::declareOption(), and PLearn::OptionList.

real PLearn::GeodesicDistanceKernel::evaluate ( const Vec & x1,

const Vec & x2

) const [virtual]

Compute K(x1,x2).

Implements PLearn::Kernel.
Definition at line 159 of file GeodesicDistanceKernel.cc.
References PLearn::dist(), dist_xi_x_sorted1, dist_xi_x_sorted2, distance_kernel, geo_distances, k, knn, PLearn::min(), pow_distance, REAL_MAX, PLearn::square(), and PLearn::Vec.

real PLearn::GeodesicDistanceKernel::evaluate_i_j ( int i,

int j

) const [virtual]

returns evaluate(data(i),data(j))

Reimplemented from PLearn::Kernel.
Definition at line 183 of file GeodesicDistanceKernel.cc.
References geo_distances, pow_distance, and PLearn::square().

real PLearn::GeodesicDistanceKernel::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.
Definition at line 194 of file GeodesicDistanceKernel.cc.
References evaluate_i_x_again(), and x.

real PLearn::GeodesicDistanceKernel::evaluate_i_x_again ( int i,

const Vec & x,

real squared_norm_of_x = -1,

bool first_time = false

) const [virtual]

Return evaluate(data(i),x), where x is the same as in the precedent call to this same function (except if 'first_time' is true).
This can be used to speed up successive computations of K(x_i, x) (default version just calls evaluate_i_x).
Reimplemented from PLearn::Kernel.
Definition at line 212 of file GeodesicDistanceKernel.cc.
References computeShortestDistance(), dist_xi_x_sorted, distance_kernel, knn, pow_distance, PLearn::square(), and x.
Referenced by evaluate_i_x().

real PLearn::GeodesicDistanceKernel::evaluate_i_x_from_distances ( int i,

const Mat & distances_xi_x_sorted

) const [virtual]

Evaluate K(x_i,x) where x is not given explicitly, but only by the (sorted and non-geodesic) distances to all training points.

Definition at line 201 of file GeodesicDistanceKernel.cc.
References computeShortestDistance(), pow_distance, and PLearn::square().

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

Transforms a shallow copy into a deep copy.

Definition at line 226 of file GeodesicDistanceKernel.cc.
References PLERROR.

PLearn::GeodesicDistanceKernel::PLEARN_DECLARE_OBJECT ( GeodesicDistanceKernel )

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

Overridden to precompute inter-points geodesic distance.

Reimplemented from PLearn::Kernel.
Definition at line 243 of file GeodesicDistanceKernel.cc.
References PLearn::TVec< T >::append(), PLearn::dist(), distance_kernel, PLearn::TVec< T >::fill(), PLearn::TMat< T >::fill(), geo_distances, geodesic_file, k, knn, PLearn::TVec< T >::length(), PLearn::VMat::length(), PLearn::min(), PLERROR, REAL_MAX, shortest_algo, PLearn::ProgressBar::update(), and PLearn::VMat::width().

Member Data Documentation

Mat PLearn::GeodesicDistanceKernel::dist_xi_x_sorted [mutable, private]

Used to store data and save memory allocation.

Definition at line 60 of file GeodesicDistanceKernel.h.
Referenced by evaluate_i_x_again().

Mat PLearn::GeodesicDistanceKernel::dist_xi_x_sorted1 [mutable, private]

Used to store data and save memory allocation.

Definition at line 60 of file GeodesicDistanceKernel.h.
Referenced by evaluate().

Mat PLearn::GeodesicDistanceKernel::dist_xi_x_sorted2 [mutable, private]

Used to store data and save memory allocation.

Definition at line 60 of file GeodesicDistanceKernel.h.
Referenced by evaluate().

Ker PLearn::GeodesicDistanceKernel::distance_kernel

Definition at line 74 of file GeodesicDistanceKernel.h.
Referenced by evaluate(), evaluate_i_x_again(), GeodesicDistanceKernel(), and setDataForKernelMatrix().

VMat PLearn::GeodesicDistanceKernel::geo_distances

Definition at line 79 of file GeodesicDistanceKernel.h.
Referenced by computeNearestGeodesicNeighbour(), evaluate(), evaluate_i_j(), and setDataForKernelMatrix().

string PLearn::GeodesicDistanceKernel::geodesic_file

Definition at line 75 of file GeodesicDistanceKernel.h.
Referenced by setDataForKernelMatrix().

int PLearn::GeodesicDistanceKernel::knn

Definition at line 76 of file GeodesicDistanceKernel.h.
Referenced by computeNearestGeodesicNeighbour(), evaluate(), evaluate_i_x_again(), and setDataForKernelMatrix().

bool PLearn::GeodesicDistanceKernel::pow_distance

Definition at line 77 of file GeodesicDistanceKernel.h.
Referenced by evaluate(), evaluate_i_j(), evaluate_i_x_again(), and evaluate_i_x_from_distances().

string PLearn::GeodesicDistanceKernel::shortest_algo

Definition at line 78 of file GeodesicDistanceKernel.h.
Referenced by setDataForKernelMatrix().

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

Generated on Tue Aug 17 16:23:27 2004 for PLearn by

1.3.7

PLearn::GeodesicDistanceKernel Class Reference

Public Member Functions

Public Attributes

Static Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation