<agrum/PRM/structuredBayesBall.h> More...

#include <structuredBayesBall.h>

Collaboration diagram for gum::prm::StructuredBayesBall< GUM_SCALAR >:

Public Member Functions
void	compute (const PRMInstance< GUM_SCALAR > *i, NodeId n)
	Compute the set or requisite nodes for each required instance given the current set of observations. Discard previous computations.
void	compute (const PRMInstance< GUM_SCALAR > &i, NodeId n)
	Compute the set or requisite nodes for each required instance given the current set of observations. Discard previous computations.
bool	_isHardEvidence_ (const PRMInstance< GUM_SCALAR > *i, NodeId n)
	Returns true if there is a hard evidence on i->get(n).
Constructors & destructor.
	StructuredBayesBall (const PRMInference< GUM_SCALAR > &inference)
	Default Constructor.
	~StructuredBayesBall ()
	Destructor.
Getters and Setters.
const std::string &	key (const PRMInstance< GUM_SCALAR > *i) const
	Returns a unique key w.r.t. d-separation for i.
const std::string &	key (const PRMInstance< GUM_SCALAR > &i) const
	Returns a unique key w.r.t. d-separation for i.
const Set< NodeId > &	requisiteNodes (const PRMInstance< GUM_SCALAR > *i) const
	Returns the set of requisite nodes w.r.t. d-separation for i.
const Set< NodeId > &	requisiteNodes (const PRMInstance< GUM_SCALAR > &i) const
	Returns the set of requisite nodes w.r.t. d-separation for i.
Size	occurrence (const std::string &key) const
	Returns the number of occurrence of the given key, which is the number of PRMInstance<GUM_SCALAR> sharing the same set of requisite nodes.
float	liftRatio () const
	Returns the ratio between the total number of instances and the number of instances with the same configuration.
bool	exists (const PRMInstance< GUM_SCALAR > *i) const
	Returns true if i has requisite nodes.
bool	exists (const PRMInstance< GUM_SCALAR > &i) const
	Returns true if i has requisite nodes.

Private Types
using	MarkMap = HashTable< NodeId, std::pair< bool, bool > >
	Code alias.
using	InstanceMap = HashTable< const PRMInstance< GUM_SCALAR >, MarkMap >

Private Member Functions
	StructuredBayesBall (const StructuredBayesBall &source)
	Copy constructor.
StructuredBayesBall &	operator= (const StructuredBayesBall &source)
	Copy operator.
std::pair< bool, bool > &	_getMark_ (InstanceMap &marks, const PRMInstance< GUM_SCALAR > *i, NodeId n)
	Code alias.
const PRMSlotChain< GUM_SCALAR > &	_getSC_ (const PRMInstance< GUM_SCALAR > *i, NodeId n)
	Code alias.
void	_clean_ ()
	Cleans this before a new computation.
void	_compute_ (const PRMInstance< GUM_SCALAR > *i, NodeId n)
	The real compute method.
void	_fromChild_ (const PRMInstance< GUM_SCALAR > *i, NodeId n, InstanceMap &marks)
	When the ball is received on i->get(n) from a child.
void	_fromParent_ (const PRMInstance< GUM_SCALAR > *i, NodeId n, InstanceMap &marks)
	When the ball is receive on i->get(n) from a parent.
void	_fillMaps_ (InstanceMap &marks)
	Fill keyMap and reqMap.
std::string	_buildHashKey_ (const PRMInstance< GUM_SCALAR > *i, Set< NodeId > &req_nodes)
	Builds the HashKey for the given instance and requisite nodes set.

Private Attributes
const PRMInference< GUM_SCALAR > *	_inf_
	The PRM at which model belongs.
HashTable< const PRMInstance< GUM_SCALAR > , std::pair< std::string, Set< NodeId > > >	_keyMap_
	Associate an PRMInstance<GUM_SCALAR> with a unique key w.r.t. d-separation and the set of requisite nodes deduced from d-separation analysis.
HashTable< std::string, std::pair< Set< NodeId > *, Size > >	_reqMap_
	Associate a Key with the set of requisite nodes associated with it. The Size value is the number of instance with the same key.

Detailed Description

template<typename GUM_SCALAR>
class gum::prm::StructuredBayesBall< GUM_SCALAR >

This class represent the BayesBall algorithm applied on PRMs.

Definition at line 67 of file structuredBayesBall.h.

Member Typedef Documentation

◆ InstanceMap

template<typename GUM_SCALAR>

using gum::prm::StructuredBayesBall< GUM_SCALAR >::InstanceMap = HashTable< const PRMInstance< GUM_SCALAR >*, MarkMap* >

private

Definition at line 136 of file structuredBayesBall.h.

◆ MarkMap

template<typename GUM_SCALAR>

using gum::prm::StructuredBayesBall< GUM_SCALAR >::MarkMap = HashTable< NodeId, std::pair< bool, bool > >

private

Code alias.

Definition at line 135 of file structuredBayesBall.h.

Constructor & Destructor Documentation

◆ StructuredBayesBall() [1/2]

template<typename GUM_SCALAR>

INLINE gum::prm::StructuredBayesBall< GUM_SCALAR >::StructuredBayesBall ( const PRMInference< GUM_SCALAR > & inference )

Default Constructor.

Definition at line 265 of file structuredBayesBall_tpl.h.

                                                     : _inf_(&inference) {
      GUM_CONSTRUCTOR(StructuredBayesBall);
    }

References StructuredBayesBall(), and _inf_.

Referenced by StructuredBayesBall(), StructuredBayesBall(), and ~StructuredBayesBall().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ ~StructuredBayesBall()

template<typename GUM_SCALAR>

gum::prm::StructuredBayesBall< GUM_SCALAR >::~StructuredBayesBall ( )

Destructor.

Definition at line 56 of file structuredBayesBall_tpl.h.

                                                            {
      GUM_DESTRUCTOR(StructuredBayesBall);
 
      for (const auto& elt: _reqMap_)
        delete elt.second.first;
    }

References StructuredBayesBall(), and _reqMap_.

Here is the call graph for this function:

◆ StructuredBayesBall() [2/2]

template<typename GUM_SCALAR>

gum::prm::StructuredBayesBall< GUM_SCALAR >::StructuredBayesBall ( const StructuredBayesBall< GUM_SCALAR > & source )

private

Copy constructor.

References StructuredBayesBall().

Here is the call graph for this function:

Member Function Documentation

◆ _buildHashKey_()

template<typename GUM_SCALAR>

std::string gum::prm::StructuredBayesBall< GUM_SCALAR >::_buildHashKey_	(	const PRMInstance< GUM_SCALAR > *	i,
		Set< NodeId > &	req_nodes )

private

Builds the HashKey for the given instance and requisite nodes set.

Definition at line 253 of file structuredBayesBall_tpl.h.

                                                                                    {
      std::stringstream sBuff;
      sBuff << i->type().name();
 
      for (const auto node: i->type().containerDag().nodes())
        if (req_nodes.exists(node)) sBuff << "-" << node;
 
      return sBuff.str();
    }

References gum::Set< Key >::exists(), and gum::prm::PRMInstance< GUM_SCALAR >::type().

Referenced by _fillMaps_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _clean_()

template<typename GUM_SCALAR>

void gum::prm::StructuredBayesBall< GUM_SCALAR >::_clean_ ( )

private

Cleans this before a new computation.

Definition at line 64 of file structuredBayesBall_tpl.h.

                                                    {
      for (const auto& elt: _reqMap_)
        delete elt.second.first;
 
      _keyMap_.clear();
      _reqMap_.clear();
    }

References _keyMap_, and _reqMap_.

Referenced by _compute_().

Here is the caller graph for this function:

◆ _compute_()

template<typename GUM_SCALAR>

void gum::prm::StructuredBayesBall< GUM_SCALAR >::_compute_	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n )

private

The real compute method.

Definition at line 96 of file structuredBayesBall_tpl.h.

                                                                                          {
      _clean_();
      StructuredBayesBall< GUM_SCALAR >::InstanceMap marks;
      _fromChild_(i, n, marks);
      _fillMaps_(marks);
 
      for (const auto& elt: marks)
        delete elt.second;
    }

References _clean_(), _fillMaps_(), and _fromChild_().

Referenced by compute(), and compute().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _fillMaps_()

template<typename GUM_SCALAR>

void gum::prm::StructuredBayesBall< GUM_SCALAR >::_fillMaps_ ( InstanceMap & marks )

private

Fill keyMap and reqMap.

Definition at line 210 of file structuredBayesBall_tpl.h.

                                                                         {
      // First find for each instance it's requisite nodes
      HashTable< const PRMInstance< GUM_SCALAR >*, Set< NodeId >* > req_map;
 
      for (const auto& elt: marks) {
        Set< NodeId >* req_set = new Set< NodeId >();
 
        for (const auto& elt2: *elt.second)
          if (elt2.second.first) req_set->insert(elt2.first);
 
        req_map.insert(elt.first, req_set);
      }
 
      // Remove all instances with 0 requisite nodes
      Set< const PRMInstance< GUM_SCALAR >* > to_remove;
 
      for (const auto& elt: req_map)
        if (elt.second->size() == 0) to_remove.insert(elt.first);
 
      for (const auto remo: to_remove) {
        delete req_map[remo];
        req_map.erase(remo);
      }
 
      // Fill  _reqMap_ and  _keyMap_
      for (const auto& elt: req_map) {
        std::string key = _buildHashKey_(elt.first, *elt.second);
 
        if (_reqMap_.exists(key)) {
          _keyMap_.insert(elt.first,
                          std::pair< std::string, Set< NodeId >* >(key, _reqMap_[key].first));
          _reqMap_[key].second += 1;
          delete elt.second;
          req_map[elt.first] = 0;
        } else {
          _reqMap_.insert(key, std::pair< Set< NodeId >*, Size >(elt.second, 1));
          _keyMap_.insert(elt.first, std::pair< std::string, Set< NodeId >* >(key, elt.second));
        }
      }
    }

References _buildHashKey_(), _keyMap_, _reqMap_, gum::HashTable< Key, Val >::erase(), gum::HashTable< Key, Val >::insert(), gum::Set< Key >::insert(), and key().

Referenced by _compute_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _fromChild_()

template<typename GUM_SCALAR>

void gum::prm::StructuredBayesBall< GUM_SCALAR >::_fromChild_	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n,
		InstanceMap &	marks )

private

When the ball is received on i->get(n) from a child.

Definition at line 110 of file structuredBayesBall_tpl.h.

                                                                                                {
      if (!marks.exists(i)) { marks.insert(i, new StructuredBayesBall< GUM_SCALAR >::MarkMap()); }
 
      if (!marks[i]->exists(n)) { marks[i]->insert(n, std::pair< bool, bool >(false, false)); }
 
      // Sending message to parents
      switch (i->type().get(n).elt_type()) {
        case PRMClassElement< GUM_SCALAR >::prm_slotchain : {
          if (!_getMark_(marks, i, n).first) {
            _getMark_(marks, i, n).first = true;
 
            for (const auto inst: i->getInstances(n))
              _fromChild_(inst, inst->get(_getSC_(i, n).lastElt().safeName()).id(), marks);
          }
 
          if (!_getMark_(marks, i, n).second) {
            _getMark_(marks, i, n).second = true;
 
            for (const auto chi: i->type().containerDag().children(n))
              _fromParent_(i, chi, marks);
          }
 
          break;
        }
 
        case PRMClassElement< GUM_SCALAR >::prm_aggregate :
        case PRMClassElement< GUM_SCALAR >::prm_attribute : {
          if (!_getMark_(marks, i, n).first) {
            _getMark_(marks, i, n).first = true;
 
            if (!_isHardEvidence_(i, n))
              for (const auto par: i->type().containerDag().parents(n))
                _fromChild_(i, par, marks);
          }
 
          if (!_getMark_(marks, i, n).second) {
            _getMark_(marks, i, n).second = true;
 
            // In i.
            for (const auto chi: i->type().containerDag().children(n))
              _fromParent_(i, chi, marks);
 
            // Out of i.
            try {
              const auto& refs = i->getRefAttr(n);
 
              for (auto iter = refs.begin(); iter != refs.end(); ++iter)
                _fromParent_(iter->first, iter->first->type().get(iter->second).id(), marks);
            } catch (NotFound const&) {
              // Not an inverse sc
            }
          }
 
          break;
        }
 
        default : {
          // We shouldn't reach any other PRMClassElement<GUM_DATA> than
          // PRMAttribute
          // or
          // PRMSlotChain<GUM_SCALAR>.
          GUM_ERROR(FatalError, "This case is impossible.")
        }
      }
    }

References _fromChild_(), _fromParent_(), _getMark_(), _getSC_(), _isHardEvidence_(), gum::HashTable< Key, Val >::exists(), exists(), gum::prm::PRMInstance< GUM_SCALAR >::getInstances(), gum::prm::PRMInstance< GUM_SCALAR >::getRefAttr(), GUM_ERROR, gum::HashTable< Key, Val >::insert(), gum::prm::PRMClassElement< GUM_SCALAR >::prm_aggregate, gum::prm::PRMClassElement< GUM_SCALAR >::prm_attribute, gum::prm::PRMClassElement< GUM_SCALAR >::prm_slotchain, and gum::prm::PRMInstance< GUM_SCALAR >::type().

Referenced by _compute_(), _fromChild_(), and _fromParent_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _fromParent_()

template<typename GUM_SCALAR>

void gum::prm::StructuredBayesBall< GUM_SCALAR >::_fromParent_	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n,
		InstanceMap &	marks )

private

When the ball is receive on i->get(n) from a parent.

Definition at line 179 of file structuredBayesBall_tpl.h.

                                                                                                 {
      if (!marks.exists(i)) { marks.insert(i, new StructuredBayesBall< GUM_SCALAR >::MarkMap()); }
 
      if (!marks[i]->exists(n)) { marks[i]->insert(n, std::pair< bool, bool >(false, false)); }
 
      // Concerns only PRMAttribute (because of the hard evidence)
      if ((_isHardEvidence_(i, n)) && (!_getMark_(marks, i, n).first)) {
        _getMark_(marks, i, n).first = true;
 
        for (const auto par: i->type().containerDag().parents(n))
          _fromChild_(i, par, marks);
      } else if (!_getMark_(marks, i, n).second) {
        _getMark_(marks, i, n).second = true;
 
        // In i.
        for (const auto chi: i->type().containerDag().children(n))
          _fromParent_(i, chi, marks);
 
        // Out of i.
        try {
          for (auto iter = i->getRefAttr(n).begin(); iter != i->getRefAttr(n).end(); ++iter)
            _fromParent_(iter->first, iter->first->type().get(iter->second).id(), marks);
        } catch (NotFound const&) {
          // Not an inverse sc
        }
      }
    }

References _fromChild_(), _fromParent_(), _getMark_(), _isHardEvidence_(), gum::HashTable< Key, Val >::exists(), exists(), gum::prm::PRMInstance< GUM_SCALAR >::getRefAttr(), gum::HashTable< Key, Val >::insert(), and gum::prm::PRMInstance< GUM_SCALAR >::type().

Referenced by _fromChild_(), and _fromParent_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _getMark_()

template<typename GUM_SCALAR>

INLINE std::pair< bool, bool > & gum::prm::StructuredBayesBall< GUM_SCALAR >::_getMark_	(	InstanceMap &	marks,
		const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n )

private

Code alias.

Definition at line 349 of file structuredBayesBall_tpl.h.

                                                                                         {
      return (*(marks[i]))[n];
    }

Referenced by _fromChild_(), and _fromParent_().

Here is the caller graph for this function:

◆ _getSC_()

template<typename GUM_SCALAR>

INLINE const PRMSlotChain< GUM_SCALAR > & gum::prm::StructuredBayesBall< GUM_SCALAR >::_getSC_	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n )

private

Code alias.

Definition at line 343 of file structuredBayesBall_tpl.h.

                                                                                               {
      return static_cast< const PRMSlotChain< GUM_SCALAR >& >(i->type().get(n));
    }

References gum::prm::PRMInstance< GUM_SCALAR >::type().

Referenced by _fromChild_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ _isHardEvidence_()

template<typename GUM_SCALAR>

bool gum::prm::StructuredBayesBall< GUM_SCALAR >::_isHardEvidence_	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n )

Returns true if there is a hard evidence on i->get(n).

Definition at line 73 of file structuredBayesBall_tpl.h.

                                                                                                 {
      try {
        typename PRMInference< GUM_SCALAR >::Chain chain = std::make_pair(i, &(i->get(n)));
 
        if (_inf_->hasEvidence(chain)) {
          const Tensor< GUM_SCALAR >* e = _inf_->evidence(i)[n];
          Instantiation               inst(e);
          Size                        count = 0;
 
          for (inst.setFirst(); !inst.end(); inst.inc()) {
            if ((e->get(inst) == (GUM_SCALAR)1.0)) ++count;
            else if (e->get(inst) != (GUM_SCALAR)0.0) return false;
          }
 
          return (count == 1);
        }
 
        return false;
      } catch (NotFound const&) { return false; }
    }

References _inf_, gum::Instantiation::end(), gum::prm::PRMInstance< GUM_SCALAR >::get(), gum::Instantiation::inc(), and gum::Instantiation::setFirst().

Referenced by _fromChild_(), and _fromParent_().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ compute() [1/2]

template<typename GUM_SCALAR>

INLINE void gum::prm::StructuredBayesBall< GUM_SCALAR >::compute	(	const PRMInstance< GUM_SCALAR > &	i,
		NodeId	n )

Compute the set or requisite nodes for each required instance given the current set of observations. Discard previous computations.

Definition at line 336 of file structuredBayesBall_tpl.h.

                                                                                               {
      _compute_(&i, n);
    }

References _compute_().

Here is the call graph for this function:

◆ compute() [2/2]

template<typename GUM_SCALAR>

INLINE void gum::prm::StructuredBayesBall< GUM_SCALAR >::compute	(	const PRMInstance< GUM_SCALAR > *	i,
		NodeId	n )

Compute the set or requisite nodes for each required instance given the current set of observations. Discard previous computations.

Definition at line 330 of file structuredBayesBall_tpl.h.

                                                                                               {
      _compute_(i, n);
    }

References _compute_().

Here is the call graph for this function:

◆ exists() [1/2]

template<typename GUM_SCALAR>

INLINE bool gum::prm::StructuredBayesBall< GUM_SCALAR >::exists ( const PRMInstance< GUM_SCALAR > & i ) const

Returns true if i has requisite nodes.

Definition at line 325 of file structuredBayesBall_tpl.h.

                                                                                          {
      return _keyMap_.exists(&i);
    }

References _keyMap_.

◆ exists() [2/2]

template<typename GUM_SCALAR>

INLINE bool gum::prm::StructuredBayesBall< GUM_SCALAR >::exists ( const PRMInstance< GUM_SCALAR > * i ) const

Returns true if i has requisite nodes.

Definition at line 319 of file structuredBayesBall_tpl.h.

                                                                                          {
      return _keyMap_.exists(i);
    }

References _keyMap_.

Referenced by _fromChild_(), and _fromParent_().

Here is the caller graph for this function:

◆ key() [1/2]

template<typename GUM_SCALAR>

INLINE const std::string & gum::prm::StructuredBayesBall< GUM_SCALAR >::key ( const PRMInstance< GUM_SCALAR > & i ) const

Returns a unique key w.r.t. d-separation for i.

Definition at line 291 of file structuredBayesBall_tpl.h.

                                                                                                {
      return _keyMap_[&i].first;
    }

References _keyMap_.

◆ key() [2/2]

template<typename GUM_SCALAR>

INLINE const std::string & gum::prm::StructuredBayesBall< GUM_SCALAR >::key ( const PRMInstance< GUM_SCALAR > * i ) const

Returns a unique key w.r.t. d-separation for i.

Definition at line 285 of file structuredBayesBall_tpl.h.

                                                                                                {
      return _keyMap_[i].first;
    }

References _keyMap_.

Referenced by _fillMaps_(), and occurrence().

Here is the caller graph for this function:

◆ liftRatio()

template<typename GUM_SCALAR>

INLINE float gum::prm::StructuredBayesBall< GUM_SCALAR >::liftRatio ( ) const

Returns the ratio between the total number of instances and the number of instances with the same configuration.

Definition at line 313 of file structuredBayesBall_tpl.h.

                                                                    {
      return ((float)_reqMap_.size()) / ((float)_keyMap_.size());
    }

References _keyMap_, and _reqMap_.

◆ occurrence()

template<typename GUM_SCALAR>

INLINE Size gum::prm::StructuredBayesBall< GUM_SCALAR >::occurrence ( const std::string & key ) const

Returns the number of occurrence of the given key, which is the number of PRMInstance<GUM_SCALAR> sharing the same set of requisite nodes.

Definition at line 308 of file structuredBayesBall_tpl.h.

                                                                                        {
      return _reqMap_[key].second;
    }

References _reqMap_, and key().

Here is the call graph for this function:

◆ operator=()

template<typename GUM_SCALAR>

INLINE StructuredBayesBall< GUM_SCALAR > & gum::prm::StructuredBayesBall< GUM_SCALAR >::operator= ( const StructuredBayesBall< GUM_SCALAR > & source )

private

Copy operator.

Definition at line 278 of file structuredBayesBall_tpl.h.

                                                         {
      GUM_ERROR(FatalError, "Not allowed.")
    }

References GUM_ERROR.

◆ requisiteNodes() [1/2]

template<typename GUM_SCALAR>

INLINE const Set< NodeId > & gum::prm::StructuredBayesBall< GUM_SCALAR >::requisiteNodes ( const PRMInstance< GUM_SCALAR > & i ) const

Returns the set of requisite nodes w.r.t. d-separation for i.

Definition at line 302 of file structuredBayesBall_tpl.h.

                                                  {
      return *(_keyMap_[&i].second);
    }

References _keyMap_.

◆ requisiteNodes() [2/2]

template<typename GUM_SCALAR>

INLINE const Set< NodeId > & gum::prm::StructuredBayesBall< GUM_SCALAR >::requisiteNodes ( const PRMInstance< GUM_SCALAR > * i ) const

Returns the set of requisite nodes w.r.t. d-separation for i.

Definition at line 296 of file structuredBayesBall_tpl.h.

                                                  {
      return *(_keyMap_[i].second);
    }

References _keyMap_.

Member Data Documentation

◆ _inf_

template<typename GUM_SCALAR>

const PRMInference< GUM_SCALAR >* gum::prm::StructuredBayesBall< GUM_SCALAR >::_inf_

private

The PRM at which model belongs.

Definition at line 163 of file structuredBayesBall.h.

Referenced by StructuredBayesBall(), and _isHardEvidence_().

◆ _keyMap_

template<typename GUM_SCALAR>

HashTable< const PRMInstance< GUM_SCALAR >*, std::pair< std::string, Set< NodeId >* > > gum::prm::StructuredBayesBall< GUM_SCALAR >::_keyMap_

private

Associate an PRMInstance<GUM_SCALAR> with a unique key w.r.t. d-separation and the set of requisite nodes deduced from d-separation analysis.

Definition at line 170 of file structuredBayesBall.h.

Referenced by _clean_(), _fillMaps_(), exists(), exists(), key(), key(), liftRatio(), requisiteNodes(), and requisiteNodes().

◆ _reqMap_

template<typename GUM_SCALAR>

HashTable< std::string, std::pair< Set< NodeId >*, Size > > gum::prm::StructuredBayesBall< GUM_SCALAR >::_reqMap_

private

Associate a Key with the set of requisite nodes associated with it. The Size value is the number of instance with the same key.

Definition at line 174 of file structuredBayesBall.h.

Referenced by ~StructuredBayesBall(), _clean_(), _fillMaps_(), liftRatio(), and occurrence().

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

agrum/PRM/inference/structuredBayesBall.h
agrum/PRM/inference/structuredBayesBall_tpl.h

Public Member Functions

Private Types

Private Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

◆ InstanceMap

◆ MarkMap

Constructor & Destructor Documentation

◆ StructuredBayesBall() [1/2]

◆ ~StructuredBayesBall()

◆ StructuredBayesBall() [2/2]

Member Function Documentation

◆ _buildHashKey_()

◆ _clean_()

◆ _compute_()

◆ _fillMaps_()

◆ _fromChild_()

◆ _fromParent_()

◆ _getMark_()

◆ _getSC_()

◆ _isHardEvidence_()

◆ compute() [1/2]

◆ compute() [2/2]

◆ exists() [1/2]

◆ exists() [2/2]

◆ key() [1/2]

◆ key() [2/2]

◆ liftRatio()

◆ occurrence()

◆ operator=()

◆ requisiteNodes() [1/2]

◆ requisiteNodes() [2/2]

Member Data Documentation

◆ _inf_

◆ _keyMap_

◆ _reqMap_