Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise.
More...
AnalyticConditionalGaussianAdditiveNoise (const Gaussian &gaus, int num_conditional_arguments=1)
Constructor. More...
AnalyticConditionalGaussianAdditiveNoise (int dim=0, int num_conditional_arguments=0)
Constructor 2, Gaussian not yet known. More...
virtual ~AnalyticConditionalGaussianAdditiveNoise ()
Destructor.
virtual MatrixWrapper::SymmetricMatrix CovarianceGet () const
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. More...
const MatrixWrapper::ColumnVector & AdditiveNoiseMuGet () const
Get the mean Value of the Additive Gaussian uncertainty. More...
const MatrixWrapper::SymmetricMatrix & AdditiveNoiseSigmaGet () const
Get the covariance matrix of the Additive Gaussian uncertainty. More...
void AdditiveNoiseMuSet (const MatrixWrapper::ColumnVector &mu)
Set the mean Value of the Additive Gaussian uncertainty. More...
void AdditiveNoiseSigmaSet (const MatrixWrapper::SymmetricMatrix &sigma)
Set the covariance of the Additive Gaussian uncertainty. More...
virtual MatrixWrapper::Matrix dfGet (unsigned int i) const
returns derivative from function to n-th conditional variable More...
virtual ConditionalGaussian * Clone () const
Clone function. More...
virtual Probability ProbabilityGet (const MatrixWrapper::ColumnVector &input) const
virtual Probability ProbabilityGet (const T &input) const
Get the probability of a certain argument. More...
virtual bool SampleFrom (Sample < MatrixWrapper::ColumnVector > &sample, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
virtual bool SampleFrom (std::vector< Sample < MatrixWrapper::ColumnVector > > &samples, const unsigned int num_samples, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
virtual bool SampleFrom (vector< Sample < T > > &list_samples, const unsigned int num_samples, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
Draw multiple samples from the Pdf (overloaded) More...
virtual bool SampleFrom (Sample < T > &one_sample, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const
Draw 1 sample from the Pdf : More...
unsigned int NumConditionalArgumentsGet () const
Get the Number of conditional arguments. More...
virtual void NumConditionalArgumentsSet (unsigned int numconditionalarguments)
Set the Number of conditional arguments. More...
const std::vector< MatrixWrapper::ColumnVector > & ConditionalArgumentsGet () const
Get the whole list of conditional arguments. More...
virtual void ConditionalArgumentsSet (std::vector< MatrixWrapper::ColumnVector > ConditionalArguments)
Set the whole list of conditional arguments. More...
const MatrixWrapper::ColumnVector & ConditionalArgumentGet (unsigned int n_argument) const
Get the n-th argument of the list. More...
virtual void ConditionalArgumentSet (unsigned int n_argument, const MatrixWrapper::ColumnVector &argument)
Set the n-th argument of the list. 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 T ExpectedValueGet () const
Get the expected value E[x] of the pdf. More...
Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise.
This class represents all Pdf 's of the type
where
and
and
Definition at line 37 of file analyticconditionalgaussian_additivenoise.h .
bool SampleFrom
(
vector< Sample < T > > &
list_samples ,
const unsigned int
num_samples ,
const SampleMthd
method = SampleMthd::DEFAULT
,
void *
args = NULL
)
const
virtual inherited
Draw multiple samples from the Pdf (overloaded)
Parameters
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 an enum eg. SampleMthd::BOXMULLER
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...
Todo: replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)
Bug: Sometimes the compiler doesn't know which method to choose!
Reimplemented in DiscretePdf , Gaussian , Uniform , MCPdf< T > , and Mixture< T > .
Definition at line 179 of file pdf.h .
Referenced by MCPdf< T >::SampleFrom() , and Mixture< T >::SampleFrom() .