Bayesian Filtering Library Generated from SVN r
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Class representing Gaussian (or normal density) More...
#include <gaussian.h>
Public Member Functions | |
Gaussian (const MatrixWrapper::ColumnVector &Mu, const MatrixWrapper::SymmetricMatrix &Sigma) | |
Constructor. | |
Gaussian (int dimension=0) | |
constructor with only dimensions or nothing | |
virtual | ~Gaussian () |
Default Copy Constructor will do. | |
virtual Gaussian * | 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 |
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. | |
void | ExpectedValueSet (const MatrixWrapper::ColumnVector &mu) |
Set the Expected Value. | |
void | CovarianceSet (const MatrixWrapper::SymmetricMatrix &cov) |
Set the Covariance Matrix. | |
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) | |
virtual bool | SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const |
Draw 1 sample from the Pdf: | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. | |
Friends | |
std::ostream & | operator<< (std::ostream &os, const Gaussian &g) |
output stream for Gaussian |
Class representing Gaussian (or normal density)
Definition at line 27 of file gaussian.h.
Gaussian | ( | const MatrixWrapper::ColumnVector & | Mu, |
const MatrixWrapper::SymmetricMatrix & | Sigma | ||
) |
virtual ~Gaussian | ( | ) | [virtual] |
Default Copy Constructor will do.
Destructor
virtual MatrixWrapper::SymmetricMatrix CovarianceGet | ( | ) | const [virtual] |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
Get first order statistic (Covariance) of this AnalyticPdf
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
void CovarianceSet | ( | const MatrixWrapper::SymmetricMatrix & | cov | ) |
Set the Covariance Matrix.
Set the Covariance Matrix
cov | The new Covariance matrix |
unsigned int DimensionGet | ( | ) | const [inherited] |
Get the dimension of the argument.
unsigned int DimensionGet | ( | ) | const [inherited] |
Get the dimension of the argument.
unsigned int DimensionGet | ( | ) | const [inherited] |
Get the dimension of the argument.
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 void DimensionSet | ( | unsigned int | dim | ) | [virtual, inherited] |
Set the dimension of the argument.
dim | the dimension |
virtual void DimensionSet | ( | unsigned int | dim | ) | [virtual, inherited] |
Set the dimension of the argument.
dim | the dimension |
virtual void DimensionSet | ( | unsigned int | dim | ) | [virtual, inherited] |
Set the dimension of the argument.
dim | the dimension |
virtual MatrixWrapper::ColumnVector ExpectedValueGet | ( | ) | const [virtual] |
Get the expected value E[x] of the pdf.
Get low order statistic (Expected Value) of this AnalyticPdf
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
void ExpectedValueSet | ( | const MatrixWrapper::ColumnVector & | mu | ) |
Set the Expected Value.
Set the Expected Value
mu | The new Expected Value |
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 , |
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void * | args = NULL |
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) | const [virtual, inherited] |
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 |
virtual bool SampleFrom | ( | vector< Sample< MatrixWrapper::ColumnVector > > & | list_samples, |
const unsigned int | num_samples, | ||
int | method = DEFAULT , |
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void * | args = NULL |
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) | 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... |