Base class for Multi-Variate Probability Density Function classes. More...

#include <vpdfl_pdf_base.h>

Inheritance diagram for vpdfl_pdf_base:

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_

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 30 of file vpdfl_pdf_base.h.

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_mixture, vpdfl_gaussian, vpdfl_pc_gaussian, vpdfl_axis_gaussian, vpdfl_kernel_pdf, and vpdfl_gaussian_kernel_pdf.

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_mixture, vpdfl_gaussian, vpdfl_pc_gaussian, vpdfl_axis_gaussian, vpdfl_kernel_pdf, and vpdfl_gaussian_kernel_pdf.

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_mixture, vpdfl_gaussian, vpdfl_pc_gaussian, vpdfl_axis_gaussian, and vpdfl_gaussian_kernel_pdf.

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_gaussian, vpdfl_axis_gaussian, vpdfl_mixture, and vpdfl_gaussian_kernel_pdf.

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.

Gradient 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

Computes gradient df/dx of f(x)=log(p(x)) at 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_mixture, vpdfl_gaussian, vpdfl_pc_gaussian, vpdfl_axis_gaussian, vpdfl_kernel_pdf, and vpdfl_gaussian_kernel_pdf.

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_mixture, vpdfl_gaussian, vpdfl_pc_gaussian, vpdfl_axis_gaussian, vpdfl_kernel_pdf, and vpdfl_gaussian_kernel_pdf.

Definition at line 171 of file vpdfl_pdf_base.cxx.

bool vpdfl_pdf_base::is_valid_pdf ( ) const [virtual]