vpdfl_pdf_base Class Reference

#include <vpdfl_pdf_base.h>

Inheritance diagram for vpdfl_pdf_base:

Detailed Description

Base class for Multi-Variate Probability Density Function classes.

Functions are available to test the plausibility of a vector or set of parameters, to modify a set of parameters so it is plausible and to choose a threshold of plausibility. Also, for cases where the distributions of parameters are multi-modal, the number and centres of each peak can be recorded. This is particularly useful for non-linear and mixture model representations of the parameter distributions.

Definition at line 29 of file vpdfl_pdf_base.h.

Public Member Functions

vpdfl_pdf_base ()

Dflt ctor.

virtual ~vpdfl_pdf_base ()

Destructor.

const vnl_vector< double > & mean () const

Mean of distribution.

const vnl_vector< double > & variance () const

Variance of each dimension.

int n_dims () const

Number of dimensions.

virtual int n_peaks () const

Number of peaks of distribution.

virtual const vnl_vector<
double > & peak (int) const

Position of the i'th peak.

virtual double log_p (const vnl_vector< double > &x) const =0

Log of probability density at x.

virtual double operator() (const vnl_vector< double > &x) const

Probability density at x.

virtual void gradient (vnl_vector< double > &g, const vnl_vector< double > &x, double &p) const =0

Gradient and value of PDF at x.

virtual void gradient_logp (vnl_vector< double > &g, const vnl_vector< double > &x) const

Gradient and value of log(p(x)) at x.

virtual vpdfl_sampler_base * new_sampler () const =0

Create a sampler object on the heap.

virtual double log_prob_thresh (double pass_proportion) const

Compute threshold for PDF to pass a given proportion.

virtual void nearest_plausible (vnl_vector< double > &x, double log_p_min) const =0

Compute nearest point to x which has a density above a threshold.

virtual bool is_valid_pdf () const

Return true if the object represents a valid PDF.

short version_no () const

Version number for I/O.

virtual vcl_string is_a () const

Name of the class.

virtual bool is_class (vcl_string const &s) const

Does the name of the class match the argument?.

virtual vpdfl_pdf_base * clone () const =0

Create a copy on the heap and return base class pointer.

virtual void print_summary (vcl_ostream &os) const =0

Print class to os.

virtual void b_write (vsl_b_ostream &bfs) const =0

Save class to binary file stream.

virtual void b_read (vsl_b_istream &bfs)=0

Load class from binary file stream.

Protected Member Functions

void set_mean (const vnl_vector< double > &m)

void set_variance (const vnl_vector< double > &v)

Private Attributes

vnl_vector< double > mean_

vnl_vector< double > var_

Constructor & Destructor Documentation

vpdfl_pdf_base::vpdfl_pdf_base ( )

Dflt ctor.

Definition at line 22 of file vpdfl_pdf_base.cxx.

vpdfl_pdf_base::~vpdfl_pdf_base ( ) [virtual]

Destructor.

Definition at line 28 of file vpdfl_pdf_base.cxx.

Member Function Documentation

void vpdfl_pdf_base::b_read ( vsl_b_istream & bfs ) [pure virtual]

Load class from binary file stream.

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 210 of file vpdfl_pdf_base.cxx.

void vpdfl_pdf_base::b_write ( vsl_b_ostream & bfs ) const [pure virtual]

Save class to binary file stream.

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 200 of file vpdfl_pdf_base.cxx.

virtual vpdfl_pdf_base* vpdfl_pdf_base::clone ( ) const [pure virtual]

Create a copy on the heap and return base class pointer.

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.

virtual void vpdfl_pdf_base::gradient ( vnl_vector< double > & g,

const vnl_vector< double > & x,

double & p

) const [pure virtual]

Gradient and value of PDF at x.
Computes gradient of PDF at x, and returns the prob at x in p
Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, and vpdfl_mixture.

void vpdfl_pdf_base::gradient_logp ( vnl_vector< double > & g,

const vnl_vector< double > & x

) const [virtual]

Gradient and value of log(p(x)) at x.
Computes gradient df/dx of f(x)=log(p(x)) at x. Result is vector of same dimensionality as x. Default baseclass implementation uses gradient() to compute grad/p
Reimplemented in vpdfl_axis_gaussian.
Definition at line 127 of file vpdfl_pdf_base.cxx.

vcl_string vpdfl_pdf_base::is_a ( ) const [virtual]

Name of the class.

Reimplemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 163 of file vpdfl_pdf_base.cxx.

bool vpdfl_pdf_base::is_class ( vcl_string const & s ) const [virtual]

Does the name of the class match the argument?.

Reimplemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 171 of file vpdfl_pdf_base.cxx.

bool vpdfl_pdf_base::is_valid_pdf ( ) const [virtual]

Return true if the object represents a valid PDF.
This will return false, if n_dims() is 0, for example just ofter default construction.
Reimplemented in vpdfl_mixture.
Definition at line 141 of file vpdfl_pdf_base.cxx.

virtual double vpdfl_pdf_base::log_p ( const vnl_vector< double > & x ) const [pure virtual]

Log of probability density at x.

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.

double vpdfl_pdf_base::log_prob_thresh ( double pass_proportion ) const [virtual]

Compute threshold for PDF to pass a given proportion.

Reimplemented in vpdfl_axis_gaussian, and vpdfl_gaussian.
Definition at line 40 of file vpdfl_pdf_base.cxx.

const vnl_vector<double>& vpdfl_pdf_base::mean ( ) const [inline]

Mean of distribution.

Definition at line 45 of file vpdfl_pdf_base.h.

int vpdfl_pdf_base::n_dims ( ) const [inline]

Number of dimensions.

Definition at line 51 of file vpdfl_pdf_base.h.

virtual int vpdfl_pdf_base::n_peaks ( ) const [inline, virtual]

Number of peaks of distribution.

Definition at line 54 of file vpdfl_pdf_base.h.

virtual void vpdfl_pdf_base::nearest_plausible ( vnl_vector< double > & x,

double log_p_min

) const [pure virtual]

Compute nearest point to x which has a density above a threshold.
If log_p(x)>log_p_min then x unchanged. Otherwise x is moved (typically up the gradient) until log_p(x)>=log_p_min.
Parameters:

x This may be modified to the nearest plausible position.

log_p_min lower threshold for log_p(x)

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, and vpdfl_mixture.

virtual vpdfl_sampler_base* vpdfl_pdf_base::new_sampler ( ) const [pure virtual]

Create a sampler object on the heap.
Caller is responsible for deletion.
Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, and vpdfl_mixture.

double vpdfl_pdf_base::operator() ( const vnl_vector< double > & x ) const [virtual]

Probability density at x.

Reimplemented in vpdfl_gaussian_kernel_pdf, and vpdfl_mixture.
Definition at line 34 of file vpdfl_pdf_base.cxx.

virtual const vnl_vector<double>& vpdfl_pdf_base::peak ( int ) const [inline, virtual]

Position of the i'th peak.

Definition at line 57 of file vpdfl_pdf_base.h.

void vpdfl_pdf_base::print_summary ( vcl_ostream & os ) const [pure virtual]

Print class to os.

Implemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 190 of file vpdfl_pdf_base.cxx.

void vpdfl_pdf_base::set_mean ( const vnl_vector< double > & m ) [inline, protected]

Reimplemented in vpdfl_gaussian.
Definition at line 34 of file vpdfl_pdf_base.h.

void vpdfl_pdf_base::set_variance ( const vnl_vector< double > & v ) [inline, protected]

Definition at line 35 of file vpdfl_pdf_base.h.

const vnl_vector<double>& vpdfl_pdf_base::variance ( ) const [inline]

Variance of each dimension.

Definition at line 48 of file vpdfl_pdf_base.h.

short vpdfl_pdf_base::version_no ( ) const

Version number for I/O.

Reimplemented in vpdfl_axis_gaussian, vpdfl_gaussian, vpdfl_gaussian_kernel_pdf, vpdfl_kernel_pdf, vpdfl_mixture, and vpdfl_pc_gaussian.
Definition at line 149 of file vpdfl_pdf_base.cxx.

Member Data Documentation

vnl_vector<double> vpdfl_pdf_base::mean_ [private]

Definition at line 31 of file vpdfl_pdf_base.h.

vnl_vector<double> vpdfl_pdf_base::var_ [private]

Definition at line 32 of file vpdfl_pdf_base.h.

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

contrib/mul/vpdfl/vpdfl_pdf_base.h
contrib/mul/vpdfl/vpdfl_pdf_base.cxx

Generated on Thu Jan 10 14:43:35 2008 for contrib/mul/vpdfl by

1.4.4


Public Member Functions
	vpdfl_pdf_base ()
	Dflt ctor.
virtual	~vpdfl_pdf_base ()
	Destructor.
const vnl_vector< double > &	mean () const
	Mean of distribution.
const vnl_vector< double > &	variance () const
	Variance of each dimension.
int	n_dims () const
	Number of dimensions.
virtual int	n_peaks () const
	Number of peaks of distribution.
virtual const vnl_vector< double > &	peak (int) const
	Position of the i'th peak.
virtual double	log_p (const vnl_vector< double > &x) const =0
	Log of probability density at x.
virtual double	operator() (const vnl_vector< double > &x) const
	Probability density at x.
virtual void	gradient (vnl_vector< double > &g, const vnl_vector< double > &x, double &p) const =0
	Gradient and value of PDF at x.
virtual void	gradient_logp (vnl_vector< double > &g, const vnl_vector< double > &x) const
	Gradient and value of log(p(x)) at x.
virtual vpdfl_sampler_base *	new_sampler () const =0
	Create a sampler object on the heap.
virtual double	log_prob_thresh (double pass_proportion) const
	Compute threshold for PDF to pass a given proportion.
virtual void	nearest_plausible (vnl_vector< double > &x, double log_p_min) const =0
	Compute nearest point to x which has a density above a threshold.
virtual bool	is_valid_pdf () const
	Return true if the object represents a valid PDF.
short	version_no () const
	Version number for I/O.
virtual vcl_string	is_a () const
	Name of the class.
virtual bool	is_class (vcl_string const &s) const
	Does the name of the class match the argument?.
virtual vpdfl_pdf_base *	clone () const =0
	Create a copy on the heap and return base class pointer.
virtual void	print_summary (vcl_ostream &os) const =0
	Print class to os.
virtual void	b_write (vsl_b_ostream &bfs) const =0
	Save class to binary file stream.
virtual void	b_read (vsl_b_istream &bfs)=0
	Load class from binary file stream.
Protected Member Functions
void	set_mean (const vnl_vector< double > &m)
void	set_variance (const vnl_vector< double > &v)
Private Attributes
vnl_vector< double >	mean_
vnl_vector< double >	var_