covEstimate< T > Class Template Reference

This method attmepts to estimate eignen values and vectors. More...

#include <VFAT/covEstimate.H>

Collaboration diagram for covEstimate< T >:

Public Member Functions
	covEstimate (std::vector< std::vector< T > > &_inputSpace, covHolder< T > &_ch)
	Default constructor, call and input pointer to first matrix.
	covEstimate (std::vector< std::vector< T * > > &_inputSpace, covHolder< T > &_ch)
	for backward compatibility
	covEstimate ()
	Default constructor, call and input pointer to first matrix.
	~covEstimate ()
	Default destructor, call and input pointer to first matrix.
T	getP (std::vector< T > sample, covHolder< T > &_ch, int stop)
	given the stored covarienc matrix what is the prob. of some point P
T	getD (std::vector< T > sample, covHolder< T > &_ch, int stop)
	obtain the distance between this point and the mean found in covEstimate
T	getD (std::vector< T > point1, std::vector< T > point2, std::vector< T > *biasSet, bool useGuass)
	obtain the inverse distance between this point and the other
void	matchPmean (std::vector< covHolder< T > > chNew, long sizeNew, std::vector< covHolder< T > > chOld, long sizeOld, long minSize)
	match clusters from mean values
void	matchPmeanAccum (std::vector< covHolder< T > > ch, unsigned int sizeCH, std::vector< covHolder< T > > accum, unsigned int sizeAccum, long minSize)
	match clusters from mean values
T	gauss (T X, T mu, T std)
	find the gaussian P for some data
void	run ()
	run covestimator with input data
void	setNew (std::vector< std::vector< T > > &_inputSpace, bool doResize, covHolder< T > &_ch, T initVal)
	(1a) call to insert new matrix, force (clear) resize if nessesary
void	setNew (std::vector< std::vector< T * > > &_inputSpace, bool doResize, covHolder< T > &_ch, T initVal)
	(1a) call to insert new matrix, force (clear) resize if nessesary
void	setNew (std::vector< std::vector< T > > &_inputSpace, T initVal, int samples, int dim, covHolder< T > &_ch, bool _resize)
	(1a) call to insert new matrix, force (clear) resize if nessesary
void	setNew (std::vector< std::vector< T * > > &_inputSpace, T initVal, int samples, int dim, covHolder< T > &_ch, bool _resize)
	(1a) call to insert new matrix, force (clear) resize if nessesary
void	setNewF (std::vector< std::vector< float * > > &_inputSpace, T initVal, int samples, int dim, covHolder< T > &_ch, bool _resize)
	set new, but lets us set a float when T = double etc.
void	resize (unsigned int _dimensions, unsigned int _samples, T zero)
	(aux) resize and clear all matrices
void	printDebug ()
	(aux) print debugging data
void	printEigenVals ()
	(aux) this will return an image slice of the matrix in its current form
Image< float >	returnMatrixSlice (int dim1, int dim2, int spaceSize)
Image< float >	returnCovSlice (int dim1, int dim2, int spaceSize, bool inorm=false)
	(aux) this shows how the covarience matrix fits over the data
Image< float >	returnCovSlice (int dim1, int dim2, Image< float > &img, bool inorm=false)
void	dumpMatrix (std::string fileName, int index, std::string ID)
	dump the covMatrix to files, this will append the output to these files
void	dumpMatrix (std::string fileName, covHolder< T > &_ch, int index, std::string ID)
	dump the covMatrix to files, this will append the output to these files
unsigned long	getSampleSize ()
	return the sample size

Detailed Description

template<class T>
class covEstimate< T >

This method attmepts to estimate eignen values and vectors.

The basic idea behind this class is to estimate a gaussian envolope around some given data but do so by avoiding matrix inversion and multiplicaition. Instead, we estimate values and gain an order of complexity in speed.

Definition at line 64 of file covEstimate.H.

Constructor & Destructor Documentation

template<class T>

covEstimate< T >::covEstimate	(	std::vector< std::vector< T > > &	_inputSpace,
		covHolder< T > &	_ch
	)			`[inline]`

Default constructor, call and input pointer to first matrix.

Definition at line 57 of file covEstimate.C.

References covEstimate< T >::setNew().

template<class T>

covEstimate< T >::covEstimate	(	std::vector< std::vector< T * > > &	_inputSpace,
		covHolder< T > &	_ch
	)			`[inline]`

for backward compatibility

Definition at line 68 of file covEstimate.C.

References covEstimate< T >::setNew().

template<class T>

covEstimate< T >::covEstimate ( ) [inline]

Default constructor, call and input pointer to first matrix.

Definition at line 79 of file covEstimate.C.

template<class T >

covEstimate< T >::~covEstimate ( ) [inline]

Default destructor, call and input pointer to first matrix.

Definition at line 86 of file covEstimate.C.

Member Function Documentation

template<class T>

void covEstimate< T >::dumpMatrix	(	std::string	fileName,
		covHolder< T > &	_ch,
		int	index,
		std::string	ID
	)			`[inline]`

dump the covMatrix to files, this will append the output to these files

Definition at line 1345 of file covEstimate.C.

References covEstimate< T >::dumpMatrix().

template<class T >

void covEstimate< T >::dumpMatrix	(	std::string	fileName,
		int	index,
		std::string	ID
	)			`[inline]`

dump the covMatrix to files, this will append the output to these files

Definition at line 1310 of file covEstimate.C.

References vfatTargetInfo< FLOAT >::dim, vfatTargetInfo< FLOAT >::eigenVal, vfatTargetInfo< FLOAT >::mean, mean(), covHolder< FLOAT >::meanRatio, and covHolder< FLOAT >::samples.

Referenced by covEstimate< T >::dumpMatrix().

template<class T>

T covEstimate< T >::gauss	(	T	X,
		T	mu,
		T	std
	)			`[inline]`

find the gaussian P for some data

Definition at line 876 of file covEstimate.C.

References exp(), and sqrt().

Referenced by covEstimate< T >::getD(), and covEstimate< T >::getP().

template<class T>

T covEstimate< T >::getD	(	std::vector< T > *	point1,
		std::vector< T > *	point2,
		std::vector< T > *	biasSet,
		bool	useGuass
	)			`[inline]`

obtain the inverse distance between this point and the other

Definition at line 527 of file covEstimate.C.

References covEstimate< T >::gauss(), and sqrt().

template<class T>

T covEstimate< T >::getD	(	std::vector< T >	sample,
		covHolder< T > &	_ch,
		int	stop
	)			`[inline]`

obtain the distance between this point and the mean found in covEstimate

Parameters:

sample

This a new sample point in the same space as cov matrix

Definition at line 501 of file covEstimate.C.

References ASSERT, vfatTargetInfo< FLOAT >::bias, vfatTargetInfo< FLOAT >::dim, vfatTargetInfo< FLOAT >::mean, and sqrt().

Referenced by covEstimate< T >::matchPmeanAccum().

template<class T>

T covEstimate< T >::getP	(	std::vector< T >	sample,
		covHolder< T > &	_ch,
		int	stop
	)			`[inline]`

given the stored covarienc matrix what is the prob. of some point P

Parameters:

	sample	This a new sample point in the same space as cov matrix
	stop	How early to stop from end of list in diminsions

Definition at line 400 of file covEstimate.C.

References ASSERT, vfatTargetInfo< FLOAT >::bias, vfatTargetInfo< FLOAT >::dim, vfatTargetInfo< FLOAT >::eigenVal, covEstimate< T >::gauss(), vfatTargetInfo< FLOAT >::mean, covHolder< FLOAT >::meanTheta, covHolder< FLOAT >::samples, and sqrt().

template<class T >

unsigned long covEstimate< T >::getSampleSize ( ) [inline]

return the sample size

Definition at line 1355 of file covEstimate.C.

template<class T>

void covEstimate< T >::matchPmean	(	std::vector< covHolder< T > > *	chNew,
		long	sizeNew,
		std::vector< covHolder< T > > *	chOld,
		long	sizeOld,
		long	minSize
	)

match clusters from mean values

This will take in a set of mean values about each cluster and match clusters from one set to clusters in another set based upon mean values.

Parameters:

	ch1	this is a list of covHolders for set 1
	size1	this is the size of the first list
	ch2	this is a list of covHolders for set 2
	size2	this is the size of the second list

template<class T>

void covEstimate< T >::matchPmeanAccum	(	std::vector< covHolder< T > > *	ch,
		unsigned int *	sizeCH,
		std::vector< covHolder< T > > *	accum,
		unsigned int *	sizeAccum,
		long	minSize
	)			`[inline]`

match clusters from mean values

This will take in a set of mean values about each cluster and match clusters from one set to clusters in another set based upon mean values. This one accumulates Classes.

Parameters:

	ch1	this is a list of covHolders for set 1
	size1	this is the size of the first list
	ch2	this is a list of covHolders for set 2
	size2	this is the size of the second list

Definition at line 718 of file covEstimate.C.

References covEstimate< T >::getD().

template<class T >

void covEstimate< T >::printDebug ( ) [inline]

(aux) print debugging data

Definition at line 1030 of file covEstimate.C.

References vfatTargetInfo< FLOAT >::eigenVal, vfatTargetInfo< FLOAT >::mean, covHolder< FLOAT >::meanRatio, and covHolder< FLOAT >::meanTheta.

template<class T >

void covEstimate< T >::printEigenVals ( ) [inline]

(aux) this will return an image slice of the matrix in its current form

This takes a 2D snapshot of the space along the two dimensions provided

Parameters:

spaceSize,this

is the "size" of the image to be returned as a square of size X x X

Definition at line 1088 of file covEstimate.C.

References vfatTargetInfo< FLOAT >::eigenVal, and covHolder< FLOAT >::meanRatio.

template<class T>

void covEstimate< T >::resize	(	unsigned int	_dimensions,
		unsigned int	_samples,
		T	zero
	)			`[inline]`

(aux) resize and clear all matrices

this should not be called directly, but may if you wish

Parameters:

	dimensions	This is the dimension of the input matrix
	samples	This is the number of samples taken
	zero	This is what value you would like to set all elements to

Definition at line 1010 of file covEstimate.C.

Referenced by covEstimate< T >::setNew(), and covEstimate< T >::setNewF().

template<class T >

Image< float > covEstimate< T >::returnCovSlice	(	int	dim1,
		int	dim2,
		int	spaceSize,
		bool	inorm = `false`
	)			`[inline]`

(aux) this shows how the covarience matrix fits over the data

Definition at line 1140 of file covEstimate.C.

References Image< T >::resize().

Referenced by main().

template<class T >

void covEstimate< T >::run ( ) [inline]

run covestimator with input data

Definition at line 885 of file covEstimate.C.

Referenced by main().

template<class T>

void covEstimate< T >::setNew	(	std::vector< std::vector< T * > > &	_inputSpace,
		T	initVal,
		int	samples,
		int	dim,
		covHolder< T > &	_ch,
		bool	_resize = `false`
	)			`[inline]`

(1a) call to insert new matrix, force (clear) resize if nessesary

Definition at line 964 of file covEstimate.C.

References covEstimate< T >::resize(), and covHolder< FLOAT >::samples.

template<class T>

void covEstimate< T >::setNew	(	std::vector< std::vector< T > > &	_inputSpace,
		T	initVal,
		int	samples,
		int	dim,
		covHolder< T > &	_ch,
		bool	_resize = `false`
	)			`[inline]`

(1a) call to insert new matrix, force (clear) resize if nessesary

Definition at line 943 of file covEstimate.C.

References covEstimate< T >::resize(), and covHolder< FLOAT >::samples.

template<class T>

void covEstimate< T >::setNew	(	std::vector< std::vector< T * > > &	_inputSpace,
		bool	doResize,
		covHolder< T > &	_ch,
		T	initVal
	)			`[inline]`

(1a) call to insert new matrix, force (clear) resize if nessesary

Definition at line 922 of file covEstimate.C.

References covEstimate< T >::resize(), and covHolder< FLOAT >::samples.

template<class T>

void covEstimate< T >::setNew	(	std::vector< std::vector< T > > &	_inputSpace,
		bool	doResize,
		covHolder< T > &	_ch,
		T	initVal
	)			`[inline]`

(1a) call to insert new matrix, force (clear) resize if nessesary

Definition at line 901 of file covEstimate.C.

References covEstimate< T >::resize(), and covHolder< FLOAT >::samples.

Referenced by covEstimate< T >::covEstimate().

template<class T>

void covEstimate< T >::setNewF	(	std::vector< std::vector< float * > > &	_inputSpace,
		T	initVal,
		int	samples,
		int	dim,
		covHolder< T > &	_ch,
		bool	_resize = `false`
	)			`[inline]`

set new, but lets us set a float when T = double etc.

Definition at line 987 of file covEstimate.C.

References covEstimate< T >::resize(), and covHolder< FLOAT >::samples.

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

src/VFAT/covEstimate.H
src/VFAT/covEstimate.C

covEstimate< T > Class Template Reference

Public Member Functions

Detailed Description

template<class T> class covEstimate< T >

Constructor & Destructor Documentation

Member Function Documentation

template<class T>
class covEstimate< T >