aGrUM  0.16.0
gum::BayesNet< GUM_SCALAR > Member List

This is the complete list of members for gum::BayesNet< GUM_SCALAR >, including all inherited members.

__clearPotentials()gum::BayesNet< GUM_SCALAR >private
__copyPotentials(const BayesNet< GUM_SCALAR > &source)gum::BayesNet< GUM_SCALAR >private
__probaMapgum::BayesNet< GUM_SCALAR >private
__varMapgum::BayesNet< GUM_SCALAR >private
_daggum::DAGmodelprotected
_unsafeChangePotential(NodeId id, Potential< GUM_SCALAR > *newPot)gum::BayesNet< GUM_SCALAR >private
add(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
add(const std::string &name, unsigned int nbrmod)gum::BayesNet< GUM_SCALAR >
add(const DiscreteVariable &var, MultiDimImplementation< GUM_SCALAR > *aContent)gum::BayesNet< GUM_SCALAR >
add(const DiscreteVariable &var, NodeId id)gum::BayesNet< GUM_SCALAR >
add(const DiscreteVariable &var, MultiDimImplementation< GUM_SCALAR > *aContent, NodeId id)gum::BayesNet< GUM_SCALAR >
addAMPLITUDE(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addAND(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addArc(NodeId tail, NodeId head)gum::BayesNet< GUM_SCALAR >
addArc(const std::string &tail, const std::string &head)gum::BayesNet< GUM_SCALAR >
addCOUNT(const DiscreteVariable &var, Idx value=1)gum::BayesNet< GUM_SCALAR >
addEXISTS(const DiscreteVariable &var, Idx value=1)gum::BayesNet< GUM_SCALAR >
addFORALL(const DiscreteVariable &var, Idx value=1)gum::BayesNet< GUM_SCALAR >
addLogit(const DiscreteVariable &var, GUM_SCALAR external_weight, NodeId id)gum::BayesNet< GUM_SCALAR >
addLogit(const DiscreteVariable &var, GUM_SCALAR external_weight)gum::BayesNet< GUM_SCALAR >
addMAX(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addMEDIAN(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addMIN(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addNoisyAND(const DiscreteVariable &var, GUM_SCALAR external_weight, NodeId id)gum::BayesNet< GUM_SCALAR >
addNoisyAND(const DiscreteVariable &var, GUM_SCALAR external_weight)gum::BayesNet< GUM_SCALAR >
addNoisyOR(const DiscreteVariable &var, GUM_SCALAR external_weight)gum::BayesNet< GUM_SCALAR >
addNoisyOR(const DiscreteVariable &var, GUM_SCALAR external_weight, NodeId id)gum::BayesNet< GUM_SCALAR >
addNoisyORCompound(const DiscreteVariable &var, GUM_SCALAR external_weight)gum::BayesNet< GUM_SCALAR >
addNoisyORCompound(const DiscreteVariable &var, GUM_SCALAR external_weight, NodeId id)gum::BayesNet< GUM_SCALAR >
addNoisyORNet(const DiscreteVariable &var, GUM_SCALAR external_weight)gum::BayesNet< GUM_SCALAR >
addNoisyORNet(const DiscreteVariable &var, GUM_SCALAR external_weight, NodeId id)gum::BayesNet< GUM_SCALAR >
addOR(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
addWeightedArc(NodeId tail, NodeId head, GUM_SCALAR causalWeight)gum::BayesNet< GUM_SCALAR >
addWeightedArc(const std::string &tail, const std::string &head, GUM_SCALAR causalWeight)gum::BayesNet< GUM_SCALAR >inline
arcs() constgum::DAGmodel
BayesNet()gum::BayesNet< GUM_SCALAR >
BayesNet(std::string name)gum::BayesNet< GUM_SCALAR >explicit
BayesNet(const BayesNet< GUM_SCALAR > &source)gum::BayesNet< GUM_SCALAR >
BayesNetFactory< GUM_SCALAR > classgum::BayesNet< GUM_SCALAR >friend
beginTopologyTransformation()gum::BayesNet< GUM_SCALAR >
changePotential(NodeId id, Potential< GUM_SCALAR > *newPot)gum::BayesNet< GUM_SCALAR >
changePotential(const std::string &name, Potential< GUM_SCALAR > *newPot)gum::BayesNet< GUM_SCALAR >
changeVariableLabel(NodeId id, const std::string &old_label, const std::string &new_label)gum::BayesNet< GUM_SCALAR >
changeVariableLabel(const std::string &name, const std::string &old_label, const std::string &new_label)gum::BayesNet< GUM_SCALAR >inline
changeVariableName(NodeId id, const std::string &new_name)gum::BayesNet< GUM_SCALAR >
changeVariableName(const std::string &name, const std::string &new_name)gum::BayesNet< GUM_SCALAR >inline
children(const NodeId id) constgum::DAGmodel
children(const std::string &name) constgum::DAGmodelinline
completeInstantiation() const finalgum::DAGmodelvirtual
cpt(NodeId varId) const finalgum::BayesNet< GUM_SCALAR >virtual
cpt(const std::string &name) constgum::BayesNet< GUM_SCALAR >inline
dag() constgum::DAGmodel
DAGmodel()gum::DAGmodel
DAGmodel(const DAGmodel &source)gum::DAGmodel
dim() constgum::IBayesNet< GUM_SCALAR >
empty() constgum::DAGmodel
endTopologyTransformation()gum::BayesNet< GUM_SCALAR >
erase(NodeId varId)gum::BayesNet< GUM_SCALAR >
erase(const std::string &name)gum::BayesNet< GUM_SCALAR >inline
erase(const DiscreteVariable &var)gum::BayesNet< GUM_SCALAR >
eraseArc(const Arc &arc)gum::BayesNet< GUM_SCALAR >
eraseArc(NodeId tail, NodeId head)gum::BayesNet< GUM_SCALAR >
eraseArc(const std::string &tail, const std::string &head)gum::BayesNet< GUM_SCALAR >inline
fastPrototype(const std::string &dotlike, Size domainSize=2)gum::BayesNet< GUM_SCALAR >static
generateCPT(NodeId node) constgum::BayesNet< GUM_SCALAR >
generateCPT(const std::string &name) constgum::BayesNet< GUM_SCALAR >inline
generateCPTs() constgum::BayesNet< GUM_SCALAR >
hasSameStructure(const DAGmodel &other)gum::DAGmodel
IBayesNet()gum::IBayesNet< GUM_SCALAR >
IBayesNet(std::string name)gum::IBayesNet< GUM_SCALAR >explicit
IBayesNet(const IBayesNet< GUM_SCALAR > &source)gum::IBayesNet< GUM_SCALAR >
idFromName(const std::string &name) const finalgum::BayesNet< GUM_SCALAR >virtual
jointProbability(const Instantiation &i) constgum::IBayesNet< GUM_SCALAR >
log10DomainSize() constgum::DAGmodel
log2JointProbability(const Instantiation &i) constgum::IBayesNet< GUM_SCALAR >
maxNonOneParam() constgum::IBayesNet< GUM_SCALAR >
maxParam() constgum::IBayesNet< GUM_SCALAR >
maxVarDomainSize() constgum::IBayesNet< GUM_SCALAR >
minimalCondSet(NodeId target, const NodeSet &soids) constgum::IBayesNet< GUM_SCALAR >
minimalCondSet(const NodeSet &targets, const NodeSet &soids) constgum::IBayesNet< GUM_SCALAR >
minNonZeroParam() constgum::IBayesNet< GUM_SCALAR >
minParam() constgum::IBayesNet< GUM_SCALAR >
moralGraph(bool clear=true) constgum::DAGmodel
nodeId(const DiscreteVariable &var) const finalgum::BayesNet< GUM_SCALAR >virtual
nodes() constgum::DAGmodel
operator!=(const IBayesNet< GUM_SCALAR > &from) constgum::IBayesNet< GUM_SCALAR >
operator=(const BayesNet< GUM_SCALAR > &source)gum::BayesNet< GUM_SCALAR >
gum::IBayesNet::operator=(const IBayesNet< GUM_SCALAR > &source)gum::IBayesNet< GUM_SCALAR >
gum::DAGmodel::operator=(const DAGmodel &source)gum::DAGmodelprotected
operator==(const IBayesNet< GUM_SCALAR > &from) constgum::IBayesNet< GUM_SCALAR >
parents(const NodeId id) constgum::DAGmodel
parents(const std::string &name) constgum::DAGmodelinline
property(const std::string &name) constgum::DAGmodel
propertyWithDefault(const std::string &name, const std::string &byDefault) constgum::DAGmodel
reverseArc(NodeId tail, NodeId head)gum::BayesNet< GUM_SCALAR >
reverseArc(const std::string &tail, const std::string &head)gum::BayesNet< GUM_SCALAR >inline
reverseArc(const Arc &arc)gum::BayesNet< GUM_SCALAR >
setProperty(const std::string &name, const std::string &value)gum::DAGmodel
size() constgum::DAGmodel
sizeArcs() constgum::DAGmodel
toDot() constgum::IBayesNet< GUM_SCALAR >virtual
topologicalOrder(bool clear=true) constgum::DAGmodel
toString() constgum::IBayesNet< GUM_SCALAR >
variable(NodeId id) const finalgum::BayesNet< GUM_SCALAR >virtual
variable(const std::string &name) constgum::BayesNet< GUM_SCALAR >inline
variableFromName(const std::string &name) const finalgum::BayesNet< GUM_SCALAR >virtual
variableNodeMap() const finalgum::BayesNet< GUM_SCALAR >virtual
~BayesNet() finalgum::BayesNet< GUM_SCALAR >
~DAGmodel()gum::DAGmodelvirtual
~IBayesNet()gum::IBayesNet< GUM_SCALAR >virtual