Bayesian Filtering Library
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Abstract Class representing conditional Pdfs P(x | ...) More...
#include <conditionalpdf.h>
Public Member Functions | |
ConditionalPdf (int dimension=0, unsigned int num_conditional_arguments=0) | |
Constructor. More... | |
virtual | ~ConditionalPdf () |
Destructor. | |
virtual ConditionalPdf< Var, CondArg > * | Clone () const |
Clone function. | |
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< CondArg > & | ConditionalArgumentsGet () const |
Get the whole list of conditional arguments. More... | |
virtual void | ConditionalArgumentsSet (std::vector< CondArg > ConditionalArguments) |
Set the whole list of conditional arguments. More... | |
const CondArg & | ConditionalArgumentGet (unsigned int n_argument) const |
Get the n-th argument of the list. More... | |
virtual void | ConditionalArgumentSet (unsigned int n_argument, const CondArg &argument) |
Set the n-th argument of the list. More... | |
virtual bool | SampleFrom (vector< Sample< Var > > &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< Var > &one_sample, const SampleMthd method=SampleMthd::DEFAULT, void *args=NULL) const |
Draw 1 sample from the Pdf: More... | |
virtual Probability | ProbabilityGet (const Var &input) const |
Get the probability of a certain argument. 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 Var | 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... | |
Abstract Class representing conditional Pdfs P(x | ...)
This class inherits from Pdf Virtual public because of the multiple inheritance that follows Two templates are here to allow a mixture of discrete and continu variables in the Pdf!
Definition at line 49 of file conditionalpdf.h.
ConditionalPdf | ( | int | dimension = 0 , |
unsigned int | num_conditional_arguments = 0 |
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Constructor.
dimension | int representing the number of rows of the state vector |
num_conditional_arguments | the number of arguments behind the | |
Definition at line 116 of file conditionalpdf.h.
const CondArg & ConditionalArgumentGet | ( | unsigned int | n_argument | ) | const |
Get the n-th argument of the list.
Definition at line 165 of file conditionalpdf.h.
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virtual |
Set the n-th argument of the list.
n_argument | which one of the conditional arguments |
argument | value of the n-th argument |
Definition at line 173 of file conditionalpdf.h.
const std::vector< CondArg > & ConditionalArgumentsGet | ( | ) | const |
Get the whole list of conditional arguments.
Definition at line 152 of file conditionalpdf.h.
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virtual |
Set the whole list of conditional arguments.
ConditionalArguments | an STL-vector of type Tcontaining the condtional arguments |
Definition at line 158 of file conditionalpdf.h.
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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
Definition at line 222 of file mixtureParticleFilter.h.
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inlineinherited |
Get the dimension of the argument.
Definition at line 166 of file mixtureParticleFilter.h.
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virtualinherited |
Set the dimension of the argument.
dim | the dimension |
Definition at line 172 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
Definition at line 212 of file mixtureParticleFilter.h.
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inline |
Get the Number of conditional arguments.
Definition at line 135 of file conditionalpdf.h.
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inlinevirtual |
Set the Number of conditional arguments.
numconditionalarguments | the number of conditionalarguments |
Reimplemented in LinearAnalyticConditionalGaussian.
Definition at line 141 of file conditionalpdf.h.
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virtualinherited |
Get the probability of a certain argument.
input | T argument of the Pdf |
Definition at line 204 of file mixtureParticleFilter.h.
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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 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... |
Definition at line 179 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 an enum, eg. SampleMthd::BOXMULLER |
args | Pointer to a struct representing extra sample arguments |
Definition at line 194 of file mixtureParticleFilter.h.