#include <conditionalgaussian_additivenoise.h>
Public Member Functions | |
ConditionalGaussianAdditiveNoise (const Gaussian &gaus, int num_conditional_arguments=1) | |
Constructor. | |
ConditionalGaussianAdditiveNoise (int dim=0, int num_conditional_arguments=0) | |
Constructor 2, Gaussian not yet known. | |
virtual | ~ConditionalGaussianAdditiveNoise () |
Destructor. | |
virtual MatrixWrapper::SymmetricMatrix | CovarianceGet () const |
Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. | |
const MatrixWrapper::ColumnVector & | AdditiveNoiseMuGet () const |
Get the mean Value of the Additive Gaussian uncertainty. | |
const MatrixWrapper::SymmetricMatrix & | AdditiveNoiseSigmaGet () const |
Get the covariance matrix of the Additive Gaussian uncertainty. | |
void | AdditiveNoiseMuSet (const MatrixWrapper::ColumnVector &mu) |
Set the mean Value of the Additive Gaussian uncertainty. | |
void | AdditiveNoiseSigmaSet (const MatrixWrapper::SymmetricMatrix &sigma) |
Set the covariance of the Additive Gaussian uncertainty. | |
virtual ConditionalGaussian * | Clone () const |
Clone function. | |
virtual Probability | ProbabilityGet (const MatrixWrapper::ColumnVector &input) const |
Get the probability of a certain argument. | |
virtual bool | SampleFrom (Sample< MatrixWrapper::ColumnVector > &sample, int method=DEFAULT, void *args=NULL) const |
Draw 1 sample from the Pdf:. | |
virtual bool | SampleFrom (std::vector< Sample< MatrixWrapper::ColumnVector > > &samples, const int num_samples, int method=DEFAULT, void *args=NULL) const |
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 | NumConditionalArgumentsGet () const |
Get the Number of conditional arguments. | |
virtual void | NumConditionalArgumentsSet (unsigned int numconditionalarguments) |
Set the Number of conditional arguments. | |
const std::vector < MatrixWrapper::ColumnVector > & | ConditionalArgumentsGet () const |
Get the whole list of conditional arguments. | |
virtual void | ConditionalArgumentsSet (std::vector< MatrixWrapper::ColumnVector > ConditionalArguments) |
Set the whole list of conditional arguments. | |
const MatrixWrapper::ColumnVector & | ConditionalArgumentGet (unsigned int n_argument) const |
Get the n-th argument of the list. | |
virtual void | ConditionalArgumentSet (unsigned int n_argument, const MatrixWrapper::ColumnVector &argument) |
Set the n-th argument of the list. | |
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. | |
Protected Attributes | |
MatrixWrapper::ColumnVector | _additiveNoise_Mu |
additive noise expected value | |
MatrixWrapper::SymmetricMatrix | _additiveNoise_Sigma |
additive noise covariance | |
ColumnVector | _diff |
ColumnVector | _Mu |
Matrix | _Low_triangle |
ColumnVector | _samples |
ColumnVector | _SampleValue |
This class represents all Pdf's of the type
where
and
and
f is not necessarily a analytical function
Definition at line 39 of file conditionalgaussian_additivenoise.h.
ConditionalGaussianAdditiveNoise | ( | const Gaussian & | gaus, | |
int | num_conditional_arguments = 1 | |||
) |
Constructor.
gaus | Gaussian representing the additive uncertainty | |
num_conditional_arguments | The number of conditional arguments. |
ConditionalGaussianAdditiveNoise | ( | int | dim = 0 , |
|
int | num_conditional_arguments = 0 | |||
) |
Constructor 2, Gaussian not yet known.
dim | Dimension of state | |
num_conditional_arguments | The number of conditional arguments. |
const MatrixWrapper::ColumnVector& AdditiveNoiseMuGet | ( | ) | const |
void AdditiveNoiseMuSet | ( | const MatrixWrapper::ColumnVector & | mu | ) |
const MatrixWrapper::SymmetricMatrix& AdditiveNoiseSigmaGet | ( | ) | const |
void AdditiveNoiseSigmaSet | ( | const MatrixWrapper::SymmetricMatrix & | sigma | ) |
const MatrixWrapper::ColumnVector & ConditionalArgumentGet | ( | unsigned int | n_argument | ) | const [inherited] |
Get the n-th argument of the list.
virtual void ConditionalArgumentSet | ( | unsigned int | n_argument, | |
const MatrixWrapper::ColumnVector & | argument | |||
) | [virtual, inherited] |
Set the n-th argument of the list.
n_argument | which one of the conditional arguments | |
argument | value of the n-th argument |
const std::vector<MatrixWrapper::ColumnVector >& ConditionalArgumentsGet | ( | ) | const [inherited] |
Get the whole list of conditional arguments.
virtual void ConditionalArgumentsSet | ( | std::vector< MatrixWrapper::ColumnVector > | ConditionalArguments | ) | [virtual, inherited] |
Set the whole list of conditional arguments.
ConditionalArguments | an STL-vector of type Tcontaining the condtional arguments |
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 >.
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.
unsigned int NumConditionalArgumentsGet | ( | ) | const [inherited] |
Get the Number of conditional arguments.
virtual void NumConditionalArgumentsSet | ( | unsigned int | numconditionalarguments | ) | [virtual, inherited] |
Set the Number of conditional arguments.
numconditionalarguments | the number of conditionalarguments |
Reimplemented in LinearAnalyticConditionalGaussian.
virtual Probability ProbabilityGet | ( | const MatrixWrapper::ColumnVector & | input | ) | const [virtual, inherited] |
Get the probability of a certain argument.
input | T argument of the Pdf |
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.
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... |
virtual bool SampleFrom | ( | Sample< MatrixWrapper::ColumnVector > & | one_sample, | |
int | method = DEFAULT , |
|||
void * | args = NULL | |||
) | 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 |
Reimplemented from Pdf< MatrixWrapper::ColumnVector >.