#include <uniform.h>
Public Member Functions | |
Uniform (const MatrixWrapper::ColumnVector &Center, const MatrixWrapper::ColumnVector &Width) | |
Constructor. | |
Uniform (int dimension=0) | |
constructor with only dimensions or nothing | |
virtual | ~Uniform () |
Default Copy Constructor will do. | |
virtual Uniform * | Clone () const |
Clone function. | |
virtual Probability | ProbabilityGet (const MatrixWrapper::ColumnVector &input) const |
Get the probability of a certain argument. | |
bool | SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const int num_samples, int method=DEFAULT, void *args=NULL) const |
virtual bool | SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const |
Draw 1 sample from the Pdf:. | |
virtual MatrixWrapper::ColumnVector | CenterGet () const |
Get the center of the uniform. | |
virtual MatrixWrapper::ColumnVector | WidthGet () const |
Get the Width of the uniform distribution. | |
void | UniformSet (const MatrixWrapper::ColumnVector ¢er, const MatrixWrapper::ColumnVector &width) |
Set the center and width of the uniform. | |
virtual bool | SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const |
Draw multiple samples from the Pdf (overloaded). | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. | |
virtual MatrixWrapper::ColumnVector | ExpectedValueGet () const |
Get the expected value E[x] of the pdf. | |
virtual MatrixWrapper::SymmetricMatrix | CovarianceGet () const |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. | |
Friends | |
std::ostream & | operator<< (std::ostream &os, const Uniform &u) |
output stream for Uniform distribution |
Definition at line 26 of file uniform.h.
Uniform | ( | const MatrixWrapper::ColumnVector & | Center, | |
const MatrixWrapper::ColumnVector & | Width | |||
) |
Constructor.
Center | center of the uniform distribution | |
Width | width of the uniform distribution |
virtual ~Uniform | ( | ) | [virtual] |
Default Copy Constructor will do.
Destructor
virtual Probability ProbabilityGet | ( | const MatrixWrapper::ColumnVector & | input | ) | const [virtual] |
Get the probability of a certain argument.
input | T argument of the Pdf |
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
virtual bool SampleFrom | ( | Sample< MatrixWrapper::ColumnVector > & | one_sample, | |
int | method = DEFAULT , |
|||
void * | args = NULL | |||
) | const [virtual] |
Draw 1 sample from the Pdf:.
There's no need to create a list for only 1 sample!
one_sample | sample that will contain result of sampling | |
method | Sampling method to be used. Each sampling method is currently represented by a define statement, eg. define BOXMULLER 1 | |
args | Pointer to a struct representing extra sample arguments |
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
virtual MatrixWrapper::ColumnVector CenterGet | ( | ) | const [virtual] |
Get the center of the uniform.
Get the center of the uniform
virtual MatrixWrapper::ColumnVector WidthGet | ( | ) | const [virtual] |
Get the Width of the uniform distribution.
Get the Width of the uniform distribution
void UniformSet | ( | const MatrixWrapper::ColumnVector & | center, | |
const MatrixWrapper::ColumnVector & | width | |||
) |
Set the center and width of the uniform.
Set the center and width of the uniform
center | The new center of uniform distribution | |
width | The new width of the uniform distribution |
virtual bool SampleFrom | ( | vector< Sample< MatrixWrapper::ColumnVector > > & | list_samples, | |
const unsigned int | num_samples, | |||
int | method = DEFAULT , |
|||
void * | args = NULL | |||
) | const [virtual, inherited] |
Draw multiple samples from the Pdf (overloaded).
list_samples | list of samples that will contain result of sampling | |
num_samples | Number of Samples to be drawn (iid) | |
method | Sampling method to be used. Each sampling method is currently represented by a define statement, eg. define BOXMULLER 1 | |
args | Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent... |
unsigned int DimensionGet | ( | ) | const [inherited] |
Get the dimension of the argument.
virtual void DimensionSet | ( | unsigned int | dim | ) | [virtual, inherited] |
Set the dimension of the argument.
dim | the dimension |
virtual MatrixWrapper::ColumnVector ExpectedValueGet | ( | ) | const [virtual, inherited] |
Get the expected value E[x] of the pdf.
Get low order statistic (Expected Value) of this AnalyticPdf
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?
Reimplemented in FilterProposalDensity, Gaussian, LinearAnalyticConditionalGaussian, NonLinearAnalyticConditionalGaussian_Ginac, and OptimalImportanceDensity.
virtual MatrixWrapper::SymmetricMatrix CovarianceGet | ( | ) | const [virtual, inherited] |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
Get first order statistic (Covariance) of this AnalyticPdf
Reimplemented in AnalyticConditionalGaussianAdditiveNoise, ConditionalGaussianAdditiveNoise, FilterProposalDensity, Gaussian, NonLinearAnalyticConditionalGaussian_Ginac, and OptimalImportanceDensity.