Public Member Functions | Protected Member Functions | Protected Attributes | Private Attributes
BFL::BFL::MCPdf< T > Class Template Reference

Monte Carlo Pdf: Sample based implementation of Pdf. More...

#include <particlefilter.h>

Inheritance diagram for BFL::BFL::MCPdf< T >:
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List of all members.

Public Member Functions

virtual MCPdf< T > * Clone () const
 Clone function.
virtual MCPdf< T > * Clone () const
 Clone function.
template<>
SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
template<>
SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
MatrixWrapper::SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
MatrixWrapper::SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
template<>
SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
template<>
SymmetricMatrix CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
vector< double > & CumulativePDFGet ()
 Add a sample to the list.
vector< double > & CumulativePDFGet ()
 Add a sample to the list.
template<>
ColumnVector ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
template<>
ColumnVector ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
template<>
unsigned int ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
template<>
unsigned int ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
const vector< WeightedSample
< T > > & 
ListOfSamplesGet () const
 Get the list of weighted samples.
const vector< WeightedSample
< T > > & 
ListOfSamplesGet () const
 Get the list of weighted samples.
bool ListOfSamplesSet (const vector< WeightedSample< T > > &list_of_samples)
 Set the list of weighted samples.
bool ListOfSamplesSet (const vector< WeightedSample< T > > &list_of_samples)
 Set the list of weighted samples.
bool ListOfSamplesSet (const vector< Sample< T > > &list_of_samples)
 Overloading: Set the list of Samples (uniform weights)
bool ListOfSamplesSet (const vector< Sample< T > > &list_of_samples)
 Overloading: Set the list of Samples (uniform weights)
bool ListOfSamplesUpdate (const vector< WeightedSample< T > > &list_of_samples)
 Update the list of samples (overloaded)
bool ListOfSamplesUpdate (const vector< WeightedSample< T > > &list_of_samples)
 Update the list of samples (overloaded)
bool ListOfSamplesUpdate (const vector< Sample< T > > &list_of_samples)
 Update the list of samples (overloaded)
bool ListOfSamplesUpdate (const vector< Sample< T > > &list_of_samples)
 Update the list of samples (overloaded)
template<>
 MCPdf (unsigned int num_samples, unsigned int dimension)
template<>
 MCPdf (unsigned int num_samples, unsigned int dimension)
template<>
 MCPdf (const MCPdf &pdf)
template<>
 MCPdf (const MCPdf &pdf)
 MCPdf (unsigned int num_samples=0, unsigned int dimension=0)
 Constructor.
 MCPdf (unsigned int num_samples=0, unsigned int dimension=0)
 Constructor.
 MCPdf (const MCPdf< T > &)
 copy constructor
 MCPdf (const MCPdf< T > &)
 copy constructor
unsigned int NumSamplesGet () const
 Get number of samples.
unsigned int NumSamplesGet () const
 Get number of samples.
void NumSamplesSet (unsigned int num_samples)
 Set number of samples.
void NumSamplesSet (unsigned int num_samples)
 Set number of samples.
bool SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const
 Draw 1 sample from the Pdf:
bool SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const
 Draw 1 sample from the Pdf:
bool SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const
 Draw multiple samples from the Pdf (overloaded)
bool SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const
 Draw multiple samples from the Pdf (overloaded)
const WeightedSample< T > & SampleGet (unsigned int i) const
 Get one sample.
const WeightedSample< T > & SampleGet (unsigned int i) const
 Get one sample.
virtual ~MCPdf ()
 destructor
virtual ~MCPdf ()
 destructor

Protected Member Functions

void CumPDFUpdate ()
 After updating weights, we have to update the cumPDF.
void CumPDFUpdate ()
 After updating weights, we have to update the cumPDF.
bool NormalizeWeights ()
 Normalizing the weights.
bool NormalizeWeights ()
 Normalizing the weights.
bool SumWeightsUpdate ()
 STL-iterator for cumulative PDF list.
bool SumWeightsUpdate ()
 STL-iterator for cumulative PDF list.

Protected Attributes

vector< double > _CumPDF
 STL-iterator.
vector< WeightedSample< T > > _listOfSamples
 STL-list containing the list of samples.
double _SumWeights
 Sum of all weights: used for normalising purposes.

Private Attributes

SymmetricMatrix _covariance
_CumSum
_diff
Matrix _diffsum
vector< WeightedSample< T >
>::iterator 
_it_los
vector< WeightedSample< T > > _los
_mean

Detailed Description

template<typename T>
class BFL::BFL::MCPdf< T >

Monte Carlo Pdf: Sample based implementation of Pdf.

Class Monte Carlo Pdf: This is a sample based representation of a Pdf P(x), which can both be continu or discrete

Todo:
This class can and should be made far more efficient!!!

Class Monte Carlo Pdf: This is a sample based representation of a Pdf P(x), which can both be continu or discrete

Todo:
This class can and should be made far more efficient!!!

Definition at line 49 of file particlefilter.h.


Constructor & Destructor Documentation

template<typename T >
BFL::BFL::MCPdf< T >::MCPdf ( unsigned int  num_samples = 0,
unsigned int  dimension = 0 
)

Constructor.

Parameters:
num_samplesthe number of samples this pdf has
dimensionthe dimension of these samples. You can use this parameter to avoid runtime memory allocation and

Definition at line 171 of file particlefilter.h.

template<typename T >
BFL::BFL::MCPdf< T >::~MCPdf ( ) [virtual]

destructor

Definition at line 195 of file particlefilter.h.

template<typename T >
BFL::BFL::MCPdf< T >::MCPdf ( const MCPdf< T > &  pdf)

copy constructor

Definition at line 204 of file particlefilter.h.

template<typename T>
BFL::BFL::MCPdf< T >::MCPdf ( unsigned int  num_samples = 0,
unsigned int  dimension = 0 
)

Constructor.

Parameters:
num_samplesthe number of samples this pdf has
dimensionthe dimension of these samples. You can use this parameter to avoid runtime memory allocation and
template<typename T>
virtual BFL::BFL::MCPdf< T >::~MCPdf ( ) [virtual]

destructor

template<typename T>
BFL::BFL::MCPdf< T >::MCPdf ( const MCPdf< T > &  )

copy constructor

template<>
BFL::BFL::MCPdf< ColumnVector >::MCPdf ( unsigned int  num_samples,
unsigned int  dimension 
) [inline]

Definition at line 32 of file particlefilter.h.

template<>
BFL::BFL::MCPdf< ColumnVector >::MCPdf ( const MCPdf< T > &  pdf) [inline]

Definition at line 58 of file particlefilter.h.

template<>
BFL::BFL::MCPdf< ColumnVector >::MCPdf ( unsigned int  num_samples,
unsigned int  dimension 
) [inline]

Definition at line 32 of file particlesmoother.h.

template<>
BFL::BFL::MCPdf< ColumnVector >::MCPdf ( const MCPdf< T > &  pdf) [inline]

Definition at line 58 of file particlesmoother.h.


Member Function Documentation

template<typename T >
MCPdf< T > * BFL::BFL::MCPdf< T >::Clone ( ) const [virtual]

Clone function.

Implements BFL::BFL::Pdf< T >.

Definition at line 222 of file particlefilter.h.

template<typename T>
virtual MCPdf<T>* BFL::BFL::MCPdf< T >::Clone ( ) const [virtual]

Clone function.

Implements BFL::BFL::Pdf< T >.

template<>
SymmetricMatrix BFL::BFL::MCPdf< ColumnVector >::CovarianceGet ( ) const [inline, virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 89 of file particlefilter.h.

template<>
SymmetricMatrix BFL::BFL::MCPdf< ColumnVector >::CovarianceGet ( ) const [inline, virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 89 of file particlesmoother.h.

template<typename T >
MatrixWrapper::SymmetricMatrix BFL::BFL::MCPdf< T >::CovarianceGet ( ) const [virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 541 of file particlefilter.h.

template<typename T>
MatrixWrapper::SymmetricMatrix BFL::BFL::MCPdf< T >::CovarianceGet ( ) const [virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

template<>
SymmetricMatrix BFL::BFL::MCPdf< unsigned int >::CovarianceGet ( ) const [inline, virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 131 of file particlefilter.h.

template<>
SymmetricMatrix BFL::BFL::MCPdf< unsigned int >::CovarianceGet ( ) const [inline, virtual]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 131 of file particlesmoother.h.

template<typename T >
void BFL::BFL::MCPdf< T >::CumPDFUpdate ( ) [protected]

After updating weights, we have to update the cumPDF.

Definition at line 510 of file particlefilter.h.

template<typename T>
void BFL::BFL::MCPdf< T >::CumPDFUpdate ( ) [protected]

After updating weights, we have to update the cumPDF.

template<typename T >
vector< double > & BFL::BFL::MCPdf< T >::CumulativePDFGet ( )

Add a sample to the list.

Parameters:
samplethe sample to be added
Todo:
what's the best way to remove some samples?

Get the Cumulative Pdf

Returns:
a vector of doubles representing the CumulativePDF

Definition at line 554 of file particlefilter.h.

template<typename T>
vector<double>& BFL::BFL::MCPdf< T >::CumulativePDFGet ( )

Add a sample to the list.

Parameters:
samplethe sample to be added
Todo:
what's the best way to remove some samples?

Get the Cumulative Pdf

Returns:
a vector of doubles representing the CumulativePDF
template<>
ColumnVector BFL::BFL::MCPdf< ColumnVector >::ExpectedValueGet ( ) const [inline, virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 78 of file particlefilter.h.

template<>
ColumnVector BFL::BFL::MCPdf< ColumnVector >::ExpectedValueGet ( ) const [inline, virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 78 of file particlesmoother.h.

template<typename T >
T BFL::BFL::MCPdf< T >::ExpectedValueGet ( ) const [virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 529 of file particlefilter.h.

template<typename T>
T BFL::BFL::MCPdf< T >::ExpectedValueGet ( ) const [virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

template<>
unsigned int BFL::BFL::MCPdf< unsigned int >::ExpectedValueGet ( ) const [inline, virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 112 of file particlefilter.h.

template<>
unsigned int BFL::BFL::MCPdf< unsigned int >::ExpectedValueGet ( ) const [inline, virtual]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!
For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 112 of file particlesmoother.h.

template<typename T >
const vector< WeightedSample< T > > & BFL::BFL::MCPdf< T >::ListOfSamplesGet ( ) const

Get the list of weighted samples.

Returns:
an STL-list with the list of weighted samples

Definition at line 422 of file particlefilter.h.

template<typename T>
const vector<WeightedSample<T> >& BFL::BFL::MCPdf< T >::ListOfSamplesGet ( ) const

Get the list of weighted samples.

Returns:
an STL-list with the list of weighted samples
template<typename T >
bool BFL::BFL::MCPdf< T >::ListOfSamplesSet ( const vector< WeightedSample< T > > &  list_of_samples)

Set the list of weighted samples.

Parameters:
list_of_samplesan STL-list containing the list of all weighted samples

Definition at line 382 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::ListOfSamplesSet ( const vector< WeightedSample< T > > &  list_of_samples)

Set the list of weighted samples.

Parameters:
list_of_samplesan STL-list containing the list of all weighted samples
template<typename T>
bool BFL::BFL::MCPdf< T >::ListOfSamplesSet ( const vector< Sample< T > > &  list_of_samples)

Overloading: Set the list of Samples (uniform weights)

Parameters:
list_of_samplesan STL-list containing the list of all samples
template<typename T >
bool BFL::BFL::MCPdf< T >::ListOfSamplesSet ( const vector< Sample< T > > &  list_of_samples)

Overloading: Set the list of Samples (uniform weights)

Parameters:
list_of_samplesan STL-list containing the list of all samples

Definition at line 395 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::ListOfSamplesUpdate ( const vector< WeightedSample< T > > &  list_of_samples)

Update the list of samples (overloaded)

Parameters:
list_of_samplesthe list of weighted samples
Precondition:
list_of_samples must contain exactly as many elements as this->NumSamplesGet() returns
template<typename T >
bool BFL::BFL::MCPdf< T >::ListOfSamplesUpdate ( const vector< WeightedSample< T > > &  list_of_samples)

Update the list of samples (overloaded)

Parameters:
list_of_samplesthe list of weighted samples
Precondition:
list_of_samples must contain exactly as many elements as this->NumSamplesGet() returns

Definition at line 429 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::ListOfSamplesUpdate ( const vector< Sample< T > > &  list_of_samples)

Update the list of samples (overloaded)

Parameters:
list_of_samplesthe list of samples
Precondition:
list_of_samples must contain exactly as many elements as this->NumSamplesGet() returns
template<typename T >
bool BFL::BFL::MCPdf< T >::ListOfSamplesUpdate ( const vector< Sample< T > > &  list_of_samples)

Update the list of samples (overloaded)

Parameters:
list_of_samplesthe list of samples
Precondition:
list_of_samples must contain exactly as many elements as this->NumSamplesGet() returns

Definition at line 441 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::NormalizeWeights ( ) [protected]

Normalizing the weights.

template<typename T >
bool BFL::BFL::MCPdf< T >::NormalizeWeights ( ) [protected]

Normalizing the weights.

Definition at line 492 of file particlefilter.h.

template<typename T >
unsigned int BFL::BFL::MCPdf< T >::NumSamplesGet ( ) const

Get number of samples.

Returns:
the number of samples

Definition at line 330 of file particlefilter.h.

template<typename T>
unsigned int BFL::BFL::MCPdf< T >::NumSamplesGet ( ) const

Get number of samples.

Returns:
the number of samples
template<typename T>
void BFL::BFL::MCPdf< T >::NumSamplesSet ( unsigned int  num_samples)

Set number of samples.

Parameters:
num_samplesthe number of samples offcourse :-)
See also:
sample, weightedsample
template<typename T >
void BFL::BFL::MCPdf< T >::NumSamplesSet ( unsigned int  num_samples)

Set number of samples.

Parameters:
num_samplesthe number of samples offcourse :-)
See also:
sample, weightedsample

Definition at line 344 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::SampleFrom ( Sample< T > &  one_sample,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]

Draw 1 sample from the Pdf:

There's no need to create a list for only 1 sample!

Parameters:
one_samplesample that will contain result of sampling
methodSampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
argsPointer to a struct representing extra sample arguments
See also:
SampleFrom()
Bug:
Sometimes the compiler doesn't know which method to choose!

Reimplemented from BFL::BFL::Pdf< T >.

template<typename T >
bool BFL::BFL::MCPdf< T >::SampleFrom ( Sample< T > &  one_sample,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]

Draw 1 sample from the Pdf:

There's no need to create a list for only 1 sample!

Parameters:
one_samplesample that will contain result of sampling
methodSampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
argsPointer to a struct representing extra sample arguments
See also:
SampleFrom()
Bug:
Sometimes the compiler doesn't know which method to choose!

Reimplemented from BFL::BFL::Pdf< T >.

Definition at line 295 of file particlefilter.h.

template<typename T >
bool BFL::BFL::MCPdf< T >::SampleFrom ( vector< Sample< T > > &  list_samples,
const unsigned int  num_samples,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]

Draw multiple samples from the Pdf (overloaded)

Parameters:
list_sampleslist of samples that will contain result of sampling
num_samplesNumber of Samples to be drawn (iid)
methodSampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
argsPointer 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 from BFL::BFL::Pdf< T >.

Definition at line 228 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::SampleFrom ( vector< Sample< T > > &  list_samples,
const unsigned int  num_samples,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]

Draw multiple samples from the Pdf (overloaded)

Parameters:
list_sampleslist of samples that will contain result of sampling
num_samplesNumber of Samples to be drawn (iid)
methodSampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
argsPointer 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 from BFL::BFL::Pdf< T >.

template<typename T>
const WeightedSample<T>& BFL::BFL::MCPdf< T >::SampleGet ( unsigned int  i) const

Get one sample.

Returns:
sample
Parameters:
ithe ith sample
template<typename T >
const WeightedSample< T > & BFL::BFL::MCPdf< T >::SampleGet ( unsigned int  i) const

Get one sample.

Returns:
sample
Parameters:
ithe ith sample

Definition at line 336 of file particlefilter.h.

template<typename T >
bool BFL::BFL::MCPdf< T >::SumWeightsUpdate ( ) [protected]

STL-iterator for cumulative PDF list.

After updating weights, we have to recalculate the sum of weights

Definition at line 466 of file particlefilter.h.

template<typename T>
bool BFL::BFL::MCPdf< T >::SumWeightsUpdate ( ) [protected]

STL-iterator for cumulative PDF list.

After updating weights, we have to recalculate the sum of weights


Member Data Documentation

template<typename T>
SymmetricMatrix BFL::BFL::MCPdf< T >::_covariance [mutable, private]

Definition at line 79 of file particlefilter.h.

template<typename T>
vector< double > BFL::BFL::MCPdf< T >::_CumPDF [protected]

STL-iterator.

STL-list containing the Cumulative PDF (for efficient sampling)

Definition at line 60 of file particlefilter.h.

template<typename T>
T BFL::BFL::MCPdf< T >::_CumSum [mutable, private]

Definition at line 75 of file particlefilter.h.

template<typename T>
T BFL::BFL::MCPdf< T >::_diff [mutable, private]

Definition at line 78 of file particlefilter.h.

template<typename T>
Matrix BFL::BFL::MCPdf< T >::_diffsum [mutable, private]

Definition at line 80 of file particlefilter.h.

template<typename T>
vector< WeightedSample< T > >::iterator BFL::BFL::MCPdf< T >::_it_los [mutable, private]

Definition at line 81 of file particlefilter.h.

template<typename T>
vector< WeightedSample< T > > BFL::BFL::MCPdf< T >::_listOfSamples [protected]

STL-list containing the list of samples.

Definition at line 56 of file particlefilter.h.

template<typename T>
vector< WeightedSample< T > > BFL::BFL::MCPdf< T >::_los [mutable, private]

Definition at line 76 of file particlefilter.h.

template<typename T>
T BFL::BFL::MCPdf< T >::_mean [mutable, private]

Definition at line 77 of file particlefilter.h.

template<typename T>
double BFL::BFL::MCPdf< T >::_SumWeights [protected]

Sum of all weights: used for normalising purposes.

Definition at line 54 of file particlefilter.h.


The documentation for this class was generated from the following file:


bfl
Author(s): Klaas Gadeyne, Wim Meeussen, Tinne Delaet and many others. See web page for a full contributor list. ROS package maintained by Wim Meeussen.
autogenerated on Fri Aug 28 2015 10:10:22