pdf1d_flat Class Reference

#include <pdf1d_flat.h>

Inheritance diagram for pdf1d_flat:

Detailed Description

Class for univariate flat distributions: p(x)=1/(hi-lo) in [lo,hi].

In range [lo,hi] p(x)=1/(hi-lo)

Definition at line 16 of file pdf1d_flat.h.

Public Member Functions

pdf1d_flat ()

Dflt ctor (creates flat distribution in range [0,1]).

pdf1d_flat (double lo, double hi)

Dflt ctor (creates flat distribution in range [lo,hi]).

virtual ~pdf1d_flat ()

Destructor.

double sd () const

Return standard deviation.

void set (double lo, double hi)

Creates flat distribution in range [lo,hi].

double lo () const

Lower limit of range.

double hi () const

Upper limit of range.

virtual pdf1d_sampler * new_sampler () const

Create a sampler object on the heap.

virtual double operator() (double x) const

Probability density at x.

virtual double log_p (double x) const

Log of probability density at x.

virtual double cdf (double x) const

Cumulative Probability (P(x'<x) for x' drawn from the distribution).

virtual bool cdf_is_analytic () const

Return true if cdf() uses an analytic implementation.

virtual double gradient (double x, double &p) const

Gradient of PDF at x.

virtual double log_prob_thresh (double pass_proportion) const

Compute threshold for PDF to pass a given proportion.

virtual double nearest_plausible (double x, double log_p_min) const

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

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 pdf1d_pdf * clone () const

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

virtual void print_summary (vcl_ostream &os) const

Print class to os.

virtual void b_write (vsl_b_ostream &bfs) const

Save class to binary file stream.

virtual void b_read (vsl_b_istream &bfs)

Load class from binary file stream.

double mean () const

Mean of distribution.

double variance () const

Variance of each dimension.

virtual int n_peaks () const

Number of peaks of distribution.

virtual double peak (int) const

Position of the i'th peak.

virtual double inverse_cdf (double P) const

The inverse cdf.

virtual bool is_valid_pdf () const

Return true if the object represents a valid PDF.

void get_samples (vnl_vector< double > &x) const

Fill x with samples drawn from distribution.

bool write_plot_file (const vcl_string &plot_file, double min_x, double max_x, int n) const

Write values (x,p(x)) to text file suitable for plotting.

Protected Member Functions

void set_mean (double m)

void set_variance (double v)

Private Attributes

double lo_

double hi_

double p_

double log_p_

Constructor & Destructor Documentation

pdf1d_flat::pdf1d_flat ( )

Dflt ctor (creates flat distribution in range [0,1]).

Definition at line 19 of file pdf1d_flat.cxx.

pdf1d_flat::pdf1d_flat ( double lo,

double hi

)

Dflt ctor (creates flat distribution in range [lo,hi]).

Definition at line 24 of file pdf1d_flat.cxx.

pdf1d_flat::~pdf1d_flat ( ) [virtual]

Destructor.

Definition at line 31 of file pdf1d_flat.cxx.

Member Function Documentation

void pdf1d_flat::b_read ( vsl_b_istream & bfs ) [virtual]

Load class from binary file stream.

Implements pdf1d_pdf.
Definition at line 185 of file pdf1d_flat.cxx.

void pdf1d_flat::b_write ( vsl_b_ostream & bfs ) const [virtual]

Save class to binary file stream.

Implements pdf1d_pdf.
Definition at line 173 of file pdf1d_flat.cxx.

double pdf1d_flat::cdf ( double x ) const [virtual]

Cumulative Probability (P(x'<x) for x' drawn from the distribution).

Reimplemented from pdf1d_pdf.
Definition at line 79 of file pdf1d_flat.cxx.

bool pdf1d_flat::cdf_is_analytic ( ) const [virtual]

Return true if cdf() uses an analytic implementation.
Default is false, as the base implementation is to draw samples from the distribution randomly to estimate cdf(x)
Reimplemented from pdf1d_pdf.
Definition at line 89 of file pdf1d_flat.cxx.

pdf1d_pdf * pdf1d_flat::clone ( ) const [virtual]

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

Implements pdf1d_pdf.
Definition at line 154 of file pdf1d_flat.cxx.

void pdf1d_pdf::get_samples ( vnl_vector< double > & x ) const [inherited]

Fill x with samples drawn from distribution.
Utility function. This calls new_sampler() to do the work, then deletes the sampler again. If you intend calling this repeatedly, create a sampler yourself.
Definition at line 131 of file pdf1d_pdf.cxx.

double pdf1d_flat::gradient ( double x,

double & p

) const [virtual]

Gradient of PDF at x.

Implements pdf1d_pdf.
Definition at line 97 of file pdf1d_flat.cxx.

double pdf1d_flat::hi ( ) const [inline]

Upper limit of range.

Definition at line 42 of file pdf1d_flat.h.

double pdf1d_pdf::inverse_cdf ( double P ) const [virtual, inherited]

The inverse cdf.
The value of x: P(x'<x) = P for x' drawn from distribution pdf. The default version of this algorithm uses sampling if !cdf_is_analytic(), and Newton-Raphson root finding otherwise.
Reimplemented in pdf1d_kernel_pdf.
Definition at line 287 of file pdf1d_pdf.cxx.

vcl_string pdf1d_flat::is_a ( ) const [virtual]

Name of the class.

Reimplemented from pdf1d_pdf.
Definition at line 126 of file pdf1d_flat.cxx.

bool pdf1d_flat::is_class ( vcl_string const & s ) const [virtual]

Does the name of the class match the argument?.

Reimplemented from pdf1d_pdf.
Definition at line 136 of file pdf1d_flat.cxx.

bool pdf1d_pdf::is_valid_pdf ( ) const [virtual, inherited]

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 pdf1d_mixture.
Definition at line 125 of file pdf1d_pdf.cxx.

double pdf1d_flat::lo ( ) const [inline]

Lower limit of range.

Definition at line 39 of file pdf1d_flat.h.

double pdf1d_flat::log_p ( double x ) const [virtual]

Log of probability density at x.
This value is also the Normalised Mahalanobis distance from the centroid to the given vector.
Implements pdf1d_pdf.
Definition at line 72 of file pdf1d_flat.cxx.

double pdf1d_flat::log_prob_thresh ( double pass_proportion ) const [virtual]

Compute threshold for PDF to pass a given proportion.

Reimplemented from pdf1d_pdf.
Definition at line 108 of file pdf1d_flat.cxx.

double pdf1d_pdf::mean ( ) const [inline, inherited]

Mean of distribution.

Definition at line 42 of file pdf1d_pdf.h.

virtual int pdf1d_pdf::n_peaks ( ) const [inline, virtual, inherited]

Number of peaks of distribution.

Definition at line 48 of file pdf1d_pdf.h.

double pdf1d_flat::nearest_plausible ( double x,

double log_p_min

) const [virtual]

Compute nearest point to x which has a density above a threshold.
If log_p(x)>log_p_min then x returned 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)

Implements pdf1d_pdf.
Definition at line 115 of file pdf1d_flat.cxx.

pdf1d_sampler * pdf1d_flat::new_sampler ( ) const [virtual]

Create a sampler object on the heap.
Caller is responsible for deletion.
Implements pdf1d_pdf.
Definition at line 55 of file pdf1d_flat.cxx.

double pdf1d_flat::operator() ( double x ) const [virtual]

Probability density at x.

Reimplemented from pdf1d_pdf.
Definition at line 64 of file pdf1d_flat.cxx.

virtual double pdf1d_pdf::peak ( int ) const [inline, virtual, inherited]

Position of the i'th peak.

Definition at line 51 of file pdf1d_pdf.h.

void pdf1d_flat::print_summary ( vcl_ostream & os ) const [virtual]

Print class to os.

Implements pdf1d_pdf.
Definition at line 164 of file pdf1d_flat.cxx.

double pdf1d_flat::sd ( ) const [inline]

Return standard deviation.

Definition at line 33 of file pdf1d_flat.h.

void pdf1d_flat::set ( double lo,

double hi

)

Creates flat distribution in range [lo,hi].

Definition at line 38 of file pdf1d_flat.cxx.

void pdf1d_pdf::set_mean ( double m ) [inline, protected, inherited]

Reimplemented in pdf1d_gaussian.
Definition at line 31 of file pdf1d_pdf.h.

void pdf1d_pdf::set_variance ( double v ) [inline, protected, inherited]

Definition at line 32 of file pdf1d_pdf.h.

double pdf1d_pdf::variance ( ) const [inline, inherited]

Variance of each dimension.

Definition at line 45 of file pdf1d_pdf.h.

short pdf1d_flat::version_no ( ) const

Version number for I/O.

Reimplemented from pdf1d_pdf.
Definition at line 145 of file pdf1d_flat.cxx.

bool pdf1d_pdf::write_plot_file ( const vcl_string & plot_file,

double min_x,

double max_x,

int n

) const [inherited]

Write values (x,p(x)) to text file suitable for plotting.
Evaluate pdf at n points in range [min_x,max_x] and write a text file, each line of which is {x p(x)}, suitable for plotting with many graph packages
Definition at line 141 of file pdf1d_pdf.cxx.

Member Data Documentation

double pdf1d_flat::hi_ [private]

Definition at line 18 of file pdf1d_flat.h.

double pdf1d_flat::lo_ [private]

Definition at line 18 of file pdf1d_flat.h.

double pdf1d_flat::log_p_ [private]

Definition at line 20 of file pdf1d_flat.h.

double pdf1d_flat::p_ [private]

Definition at line 19 of file pdf1d_flat.h.

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

contrib/mul/pdf1d/pdf1d_flat.h
contrib/mul/pdf1d/pdf1d_flat.cxx

Generated on Thu Jan 10 14:43:21 2008 for contrib/mul/pdf1d by

1.4.4


Public Member Functions
	pdf1d_flat ()
	Dflt ctor (creates flat distribution in range [0,1]).
	pdf1d_flat (double lo, double hi)
	Dflt ctor (creates flat distribution in range [lo,hi]).
virtual	~pdf1d_flat ()
	Destructor.
double	sd () const
	Return standard deviation.
void	set (double lo, double hi)
	Creates flat distribution in range [lo,hi].
double	lo () const
	Lower limit of range.
double	hi () const
	Upper limit of range.
virtual pdf1d_sampler *	new_sampler () const
	Create a sampler object on the heap.
virtual double	operator() (double x) const
	Probability density at x.
virtual double	log_p (double x) const
	Log of probability density at x.
virtual double	cdf (double x) const
	Cumulative Probability (P(x'<x) for x' drawn from the distribution).
virtual bool	cdf_is_analytic () const
	Return true if cdf() uses an analytic implementation.
virtual double	gradient (double x, double &p) const
	Gradient of PDF at x.
virtual double	log_prob_thresh (double pass_proportion) const
	Compute threshold for PDF to pass a given proportion.
virtual double	nearest_plausible (double x, double log_p_min) const
	Compute nearest point to x which has a density above a threshold.
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 pdf1d_pdf *	clone () const
	Create a copy on the heap and return base class pointer.
virtual void	print_summary (vcl_ostream &os) const
	Print class to os.
virtual void	b_write (vsl_b_ostream &bfs) const
	Save class to binary file stream.
virtual void	b_read (vsl_b_istream &bfs)
	Load class from binary file stream.
double	mean () const
	Mean of distribution.
double	variance () const
	Variance of each dimension.
virtual int	n_peaks () const
	Number of peaks of distribution.
virtual double	peak (int) const
	Position of the i'th peak.
virtual double	inverse_cdf (double P) const
	The inverse cdf.
virtual bool	is_valid_pdf () const
	Return true if the object represents a valid PDF.
void	get_samples (vnl_vector< double > &x) const
	Fill x with samples drawn from distribution.
bool	write_plot_file (const vcl_string &plot_file, double min_x, double max_x, int n) const
	Write values (x,p(x)) to text file suitable for plotting.
Protected Member Functions
void	set_mean (double m)
void	set_variance (double v)
Private Attributes
double	lo_
double	hi_
double	p_
double	log_p_