Bayesian Filtering Library
Generated from SVN r
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Class representing uniform density. More...
#include <uniform.h>
Public Member Functions | |
Uniform (const MatrixWrapper::ColumnVector &Center, const MatrixWrapper::ColumnVector &Width) | |
Constructor. More... | |
Uniform (int dimension=0) | |
constructor with only dimensions or nothing | |
virtual | ~Uniform () |
Default Copy Constructor will do. More... | |
virtual Uniform * | Clone () const |
Clone function. | |
virtual Probability | ProbabilityGet (const MatrixWrapper::ColumnVector &input) const |
Get the probability of a certain argument. More... | |
bool | SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const unsigned 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 | CenterGet () const |
Get the center of the uniform. More... | |
virtual MatrixWrapper::ColumnVector | WidthGet () const |
Get the Width of the uniform distribution. More... | |
void | UniformSet (const MatrixWrapper::ColumnVector ¢er, const MatrixWrapper::ColumnVector &width) |
Set the center and width of the uniform. More... | |
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) More... | |
virtual bool | SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const |
Draw 1 sample from the Pdf: More... | |
unsigned int | DimensionGet () const |
Get the dimension of the argument. More... | |
virtual void | DimensionSet (unsigned int dim) |
Set the dimension of the argument. More... | |
virtual MatrixWrapper::ColumnVector | ExpectedValueGet () const |
Get the expected value E[x] of the pdf. More... | |
virtual MatrixWrapper::SymmetricMatrix | CovarianceGet () const |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. More... | |
Friends | |
std::ostream & | operator<< (std::ostream &os, const Uniform &u) |
output stream for Uniform distribution | |
Uniform | ( | const MatrixWrapper::ColumnVector & | Center, |
const MatrixWrapper::ColumnVector & | Width | ||
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Constructor.
Center | center of the uniform distribution |
Width | width of the uniform distribution |
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virtual |
Default Copy Constructor will do.
Destructor
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virtual |
Get the center of the uniform.
Get the center of the uniform
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virtualinherited |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
Get first order statistic (Covariance) of this AnalyticPdf
Reimplemented in NonLinearAnalyticConditionalGaussian_Ginac, Gaussian, ConditionalGaussianAdditiveNoise, AnalyticConditionalGaussianAdditiveNoise, FilterProposalDensity, and OptimalImportanceDensity.
Definition at line 225 of file mixtureParticleFilter.h.
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inlineinherited |
Get the dimension of the argument.
Definition at line 169 of file mixtureParticleFilter.h.
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virtualinherited |
Set the dimension of the argument.
dim | the dimension |
Reimplemented in Gaussian.
Definition at line 175 of file mixtureParticleFilter.h.
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virtualinherited |
Get the expected value E[x] of the pdf.
Get low order statistic (Expected Value) of this AnalyticPdf
Reimplemented in NonLinearAnalyticConditionalGaussian_Ginac, Gaussian, LinearAnalyticConditionalGaussian, FilterProposalDensity, and OptimalImportanceDensity.
Definition at line 215 of file mixtureParticleFilter.h.
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virtual |
Get the probability of a certain argument.
input | T argument of the Pdf |
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
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virtualinherited |
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... |
Definition at line 182 of file mixtureParticleFilter.h.
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virtualinherited |
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 |
Definition at line 197 of file mixtureParticleFilter.h.
void UniformSet | ( | const MatrixWrapper::ColumnVector & | center, |
const MatrixWrapper::ColumnVector & | width | ||
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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 |
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virtual |
Get the Width of the uniform distribution.
Get the Width of the uniform distribution