gum::GibbsOperator< GUM_SCALAR > Class Template Reference

class containing all variables and methods required for Gibbssampling More...

#include <agrum/BN/inference/gibbsOperator.h>

Inheritance diagram for gum::GibbsOperator< GUM_SCALAR >:

Collaboration diagram for gum::GibbsOperator< GUM_SCALAR >:

Public Member Functions
	GibbsOperator (const IBayesNet< GUM_SCALAR > &BN, const NodeProperty< Idx > *hardEv, Size nbr=1, bool atRandom=false)
	constructor More...
virtual	~GibbsOperator ()
	Destructor. More...
Size	nbrDrawnVar () const
	Getters and setters. More...
void	setNbrDrawnVar (Size nbr)
bool	isDrawnAtRandom () const
void	setDrawnAtRandom (bool atRandom)
Instantiation	monteCarloSample ()
	draws a Monte Carlo sample More...
Instantiation	nextSample (Instantiation prev)
	draws next sample of Gibbs sampling More...

Protected Attributes
Size	counting_
const IBayesNet< GUM_SCALAR > &	samplingBn_
const NodeProperty< Idx > *	hardEv_
Sequence< NodeId >	samplingNodes_
Size	nbr_
bool	atRandom_

Detailed Description

template<typename GUM_SCALAR>
class gum::GibbsOperator< GUM_SCALAR >

class containing all variables and methods required for Gibbssampling

Definition at line 49 of file gibbsOperator.h.

Constructor & Destructor Documentation

GibbsOperator()

template<typename GUM_SCALAR >

gum::GibbsOperator< GUM_SCALAR >::GibbsOperator	(	const IBayesNet< GUM_SCALAR > &	BN,
		const NodeProperty< Idx > *	hardEv,
		Size	nbr = 1,
		bool	atRandom = false
	)

constructor

Definition at line 36 of file gibbsOperator_tpl.h.

                                                                                      :
      counting_(0),
      samplingBn_(BN), hardEv_(hardEv), nbr_(nbr), atRandom_(atRandom) {
    _updateSamplingNodes_();
    GUM_CONSTRUCTOR(GibbsOperator);
  }

~GibbsOperator()

template<typename GUM_SCALAR >

gum::GibbsOperator< GUM_SCALAR >::~GibbsOperator ( )

virtual

Destructor.

Definition at line 47 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                              {
    GUM_DESTRUCTOR(GibbsOperator);
  }

Here is the call graph for this function:

Member Function Documentation

_drawVarMonteCarlo_()

template<typename GUM_SCALAR >

void gum::GibbsOperator< GUM_SCALAR >::_drawVarMonteCarlo_ ( NodeId  nod, Instantiation *  I  )

private

Definition at line 82 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                                    {
    gum::Instantiation Itop(*I);
    Itop.erase(samplingBn_.variable(nod));
    I->chgVal(samplingBn_.variable(nod), samplingBn_.cpt(nod).extract(Itop).draw());
  }

Here is the call graph for this function:

_GibbsSample_()

template<typename GUM_SCALAR >

void gum::GibbsOperator< GUM_SCALAR >::_GibbsSample_ ( NodeId  id, Instantiation *  I  )

private

change in Instantiation I a new drawn value for id

Definition at line 102 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                             {
    gum::Instantiation Itop(*I);
    Itop.erase(samplingBn_.variable(id));
    gum::Potential< GUM_SCALAR > p = samplingBn_.cpt(id).extract(Itop);
    for (const auto nod: samplingBn_.children(id))
      p *= samplingBn_.cpt(nod).extract(Itop);
    GUM_ASSERT(p.nbrDim() == 1);
    if (p.sum() != 0) {
      p.normalize();
      I->chgVal(samplingBn_.variable(id), p.draw());
    }
  }

Here is the call graph for this function:

_updateSamplingNodes_()

template<typename GUM_SCALAR >

void gum::GibbsOperator< GUM_SCALAR >::_updateSamplingNodes_ ( )

private

Definition at line 52 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                          {
    samplingNodes_.clear();
    for (const auto node: samplingBn_.nodes())
      if (hardEv_ == nullptr || !hardEv_->exists(node)) samplingNodes_.insert(node);
    if (samplingNodes_.size() == 0) {
      GUM_ERROR(InvalidArgument, "No node to sample (too many nodes or too much evidence)!")
    }
    if (nbr_ > samplingNodes_.size()) nbr_ = samplingNodes_.size();
  }

Here is the call graph for this function:

isDrawnAtRandom()

template<typename GUM_SCALAR >

bool gum::GibbsOperator< GUM_SCALAR >::isDrawnAtRandom ( ) const

inline

Definition at line 69 of file gibbsOperator.h.

References gum::GibbsOperator< GUM_SCALAR >::atRandom_.

{ return atRandom_; }

monteCarloSample()

template<typename GUM_SCALAR >

Instantiation gum::GibbsOperator< GUM_SCALAR >::monteCarloSample

(

)

draws a Monte Carlo sample

returns a MC sample This is not a really sample since we take into account evidence without care about parent of evidence, etc. This is just a not-so-bad first sample for GibbsSampler

Definition at line 67 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                              {
    gum::Instantiation I;

    for (const auto nod: samplingBn_.topologicalOrder()) {
      I.add(samplingBn_.variable(nod));
      if (hardEv_ != nullptr && hardEv_->exists(nod)) {
        I.chgVal(samplingBn_.variable(nod), (*hardEv_)[nod]);
      } else {
        _drawVarMonteCarlo_(nod, &I);
      }
    }
    return I;
  }

Here is the call graph for this function:

nbrDrawnVar()

template<typename GUM_SCALAR >

Size gum::GibbsOperator< GUM_SCALAR >::nbrDrawnVar ( ) const

inline

Getters and setters.

Definition at line 65 of file gibbsOperator.h.

{ return nbr_; }

nextSample()

template<typename GUM_SCALAR >

Instantiation gum::GibbsOperator< GUM_SCALAR >::nextSample

(

Instantiation

prev

)

draws next sample of Gibbs sampling

Definition at line 90 of file gibbsOperator_tpl.h.

References gum::Set< Key, Alloc >::emplace().

                                                                          {
    for (Idx i = 0; i < nbr_; i++) {
      auto pos
         = atRandom_ ? randomValue(samplingNodes_.size()) : (counting_ % samplingNodes_.size());
      this->_GibbsSample_(samplingNodes_[pos], &prev);
      counting_++;
    }
    return prev;
  }

Here is the call graph for this function:

setDrawnAtRandom()

template<typename GUM_SCALAR >

void gum::GibbsOperator< GUM_SCALAR >::setDrawnAtRandom ( bool  atRandom )

inline

Definition at line 71 of file gibbsOperator.h.

References gum::GibbsOperator< GUM_SCALAR >::atRandom_.

{ atRandom_ = atRandom; }

setNbrDrawnVar()

template<typename GUM_SCALAR >

void gum::GibbsOperator< GUM_SCALAR >::setNbrDrawnVar ( Size  nbr )

inline

Definition at line 67 of file gibbsOperator.h.

{ nbr_ = nbr; }

Member Data Documentation

atRandom_

template<typename GUM_SCALAR >

bool gum::GibbsOperator< GUM_SCALAR >::atRandom_

protected

Definition at line 86 of file gibbsOperator.h.

Referenced by gum::GibbsOperator< GUM_SCALAR >::isDrawnAtRandom(), and gum::GibbsOperator< GUM_SCALAR >::setDrawnAtRandom().

counting_

template<typename GUM_SCALAR >

Size gum::GibbsOperator< GUM_SCALAR >::counting_

protected

Definition at line 80 of file gibbsOperator.h.

hardEv_

template<typename GUM_SCALAR >

const NodeProperty< Idx >* gum::GibbsOperator< GUM_SCALAR >::hardEv_

protected

Definition at line 82 of file gibbsOperator.h.

nbr_

template<typename GUM_SCALAR >

Size gum::GibbsOperator< GUM_SCALAR >::nbr_

protected

Definition at line 85 of file gibbsOperator.h.

samplingBn_

template<typename GUM_SCALAR >

const IBayesNet< GUM_SCALAR >& gum::GibbsOperator< GUM_SCALAR >::samplingBn_

protected

Definition at line 81 of file gibbsOperator.h.

samplingNodes_

template<typename GUM_SCALAR >

Sequence< NodeId > gum::GibbsOperator< GUM_SCALAR >::samplingNodes_

protected

Definition at line 83 of file gibbsOperator.h.

---

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

• agrum/BN/inference/tools/gibbsOperator.h
• agrum/BN/inference/tools/gibbsOperator_tpl.h