Samples from a Gaussian PDF. More...
#include <vpdfl_gaussian_sampler.h>
Public Member Functions | |
vpdfl_gaussian_sampler () | |
Dflt ctor. | |
virtual | ~vpdfl_gaussian_sampler () |
Destructor. | |
virtual void | sample (vnl_vector< double > &x) |
Draw random sample from Gaussian distribution. | |
virtual void | reseed (unsigned long) |
Reseeds the internal random number generator. | |
const vpdfl_gaussian & | gaussian () const |
Return a reference to the pdf model. | |
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_sampler_base * | clone () const |
Create a copy on the heap and return base class pointer. | |
const vpdfl_pdf_base & | model () const |
PDF of which this is an instance. | |
virtual void | set_model (const vpdfl_pdf_base &) |
Set model for which this is an instance. | |
virtual void | get_samples (vcl_vector< vnl_vector< double > > &x) |
Fill x with samples drawn from distribution. | |
virtual void | regular_samples (vcl_vector< vnl_vector< double > > &x) |
Fill x with samples possibly chosen so as to represent the distribution. | |
virtual void | regular_samples_and_prob (vcl_vector< vnl_vector< double > > &x, vnl_vector< double > &p) |
Fill x with samples possibly chosen so as to represent the distribution. | |
virtual void | print_summary (vcl_ostream &os) const |
Print class to os. | |
Protected Attributes | |
vnl_random | rng_ |
The random number generator. | |
vnl_vector< double > | b_ |
workspace variable. | |
const vpdfl_pdf_base * | pdf_model_ |
Samples from a Gaussian PDF.
Definition at line 23 of file vpdfl_gaussian_sampler.h.
vpdfl_gaussian_sampler::vpdfl_gaussian_sampler | ( | ) |
Dflt ctor.
Definition at line 21 of file vpdfl_gaussian_sampler.cxx.
vpdfl_gaussian_sampler::~vpdfl_gaussian_sampler | ( | ) | [virtual] |
Destructor.
Definition at line 30 of file vpdfl_gaussian_sampler.cxx.
vpdfl_sampler_base * vpdfl_gaussian_sampler::clone | ( | ) | const [virtual] |
Create a copy on the heap and return base class pointer.
Implements vpdfl_sampler_base.
Reimplemented in vpdfl_pc_gaussian_sampler.
Definition at line 97 of file vpdfl_gaussian_sampler.cxx.
const vpdfl_gaussian & vpdfl_gaussian_sampler::gaussian | ( | ) | const |
Return a reference to the pdf model.
This is properly cast.
Definition at line 66 of file vpdfl_gaussian_sampler.cxx.
void vpdfl_sampler_base::get_samples | ( | vcl_vector< vnl_vector< double > > & | x | ) | [virtual, inherited] |
Fill x with samples drawn from distribution.
Definition at line 48 of file vpdfl_sampler_base.cxx.
vcl_string vpdfl_gaussian_sampler::is_a | ( | ) | const [virtual] |
Name of the class.
Reimplemented from vpdfl_sampler_base.
Reimplemented in vpdfl_pc_gaussian_sampler.
Definition at line 39 of file vpdfl_gaussian_sampler.cxx.
bool vpdfl_gaussian_sampler::is_class | ( | vcl_string const & | s | ) | const [virtual] |
Does the name of the class match the argument?.
Reimplemented from vpdfl_sampler_base.
Reimplemented in vpdfl_pc_gaussian_sampler.
Definition at line 48 of file vpdfl_gaussian_sampler.cxx.
const vpdfl_pdf_base & vpdfl_sampler_base::model | ( | ) | const [inherited] |
PDF of which this is an instance.
Definition at line 40 of file vpdfl_sampler_base.cxx.
void vpdfl_sampler_base::print_summary | ( | vcl_ostream & | os | ) | const [virtual, inherited] |
Print class to os.
Definition at line 104 of file vpdfl_sampler_base.cxx.
void vpdfl_sampler_base::regular_samples | ( | vcl_vector< vnl_vector< double > > & | x | ) | [virtual, inherited] |
Fill x with samples possibly chosen so as to represent the distribution.
Generate a set of pseudo-random samples, chosen so as to be suitable to represent the distribution. This is meant to be used for estimating continuous integrals with sampled approximations. Where there are multiple peaks (e.g. kernel or mixture models), it is preferred that the number of samples from each component is roughly proportional to the weight for the component. When small numbers are requested, this can be done explicitly. The default is simply to call sample() for each element of x
Reimplemented in vpdfl_gaussian_kernel_pdf_sampler.
Definition at line 57 of file vpdfl_sampler_base.cxx.
void vpdfl_sampler_base::regular_samples_and_prob | ( | vcl_vector< vnl_vector< double > > & | x, |
vnl_vector< double > & | p | ||
) | [virtual, inherited] |
Fill x with samples possibly chosen so as to represent the distribution.
As regular_samples(x), but p[i] is set to p(x[i])
Definition at line 67 of file vpdfl_sampler_base.cxx.
void vpdfl_gaussian_sampler::reseed | ( | unsigned long | seed | ) | [virtual] |
Reseeds the internal random number generator.
To achieve quasi-random initialisation use;
#include <vcl_ctime.h>
..
sampler.reseed(vcl_time(0));
Implements vpdfl_sampler_base.
Definition at line 56 of file vpdfl_gaussian_sampler.cxx.
void vpdfl_gaussian_sampler::sample | ( | vnl_vector< double > & | x | ) | [virtual] |
Draw random sample from Gaussian distribution.
Implements vpdfl_sampler_base.
Definition at line 73 of file vpdfl_gaussian_sampler.cxx.
void vpdfl_sampler_base::set_model | ( | const vpdfl_pdf_base & | model | ) | [virtual, inherited] |
Set model for which this is an instance.
Reimplemented in vpdfl_mixture_sampler, vpdfl_axis_gaussian_sampler, and vpdfl_gaussian_kernel_pdf_sampler.
Definition at line 34 of file vpdfl_sampler_base.cxx.
vnl_vector<double> vpdfl_gaussian_sampler::b_ [protected] |
workspace variable.
Reimplemented in vpdfl_pc_gaussian_sampler.
Definition at line 29 of file vpdfl_gaussian_sampler.h.
const vpdfl_pdf_base* vpdfl_sampler_base::pdf_model_ [protected, inherited] |
Definition at line 31 of file vpdfl_sampler_base.h.
vnl_random vpdfl_gaussian_sampler::rng_ [protected] |
The random number generator.
Definition at line 27 of file vpdfl_gaussian_sampler.h.