aGrUM  0.18.1
a C++ library for (probabilistic) graphical models
exceptions.h File Reference

Copyright 2005-2020 Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org. More...

#include <iomanip>
#include <iostream>
#include <string>
#include <agrum/tools/core/types.h>
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Classes

class  gum::Exception
 Base class for all aGrUM's exceptions. More...
 

Namespaces

 gum
 Copyright 2005-2020 Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org.
 

Macros

#define GUM_ERROR_IN_EXPR(type, msg)   throw(type(msg))
 
#define GUM_ERROR(type, msg)
 
#define GUM_SHOWERROR(e)
 
#define GUM_MAKE_ERROR(TYPE, SUPERCLASS, MSG)
 
#define GUM_SYNTAX_ERROR(msg, line, column)
 

Detailed Description

Copyright 2005-2020 Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org.

This library is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with this library. If not, see http://www.gnu.org/licenses/. aGrUM's exceptions

Author
Pierre-Henri WUILLEMIN() & Christophe GONZALES()

Definition in file exceptions.h.

Macro Definition Documentation

◆ GUM_ERROR

#define GUM_ERROR (   type,
  msg 
)
Value:
{ \
std::ostringstream error_stream; \
error_stream << __FILE__ << ":" << __LINE__ << ": " << msg; \
throw(type(error_stream.str())); \
}

Definition at line 55 of file exceptions.h.

Referenced by gum::Instantiation::actAsSlave(), gum::FMDP< double >::actionId(), gum::FMDP< double >::actionName(), gum::MultiDimWithOffset< GUM_SCALAR >::add(), gum::MultiDimDecorator< GUM_SCALAR >::add(), gum::MultiDimBijArray< GUM_SCALAR >::add(), gum::MultiDimImplementation< std::string >::add(), gum::prm::PRMSystem< double >::add(), gum::prm::PRMInterface< double >::add(), gum::prm::PRMClass< double >::add(), gum::BayesNet< double >::add(), gum::Instantiation::add(), gum::prm::PRMInstance< GUM_SCALAR >::add(), gum::FMDP< double >::addAction(), gum::prm::PRMFactory< GUM_SCALAR >::addAggregator(), gum::AggregatorDecomposition< GUM_SCALAR >::addAggregator_(), gum::MarginalTargetedInference< GUM_SCALAR >::addAllTargets(), gum::MarginalTargetedMNInference< GUM_SCALAR >::addAllTargets(), gum::BayesNet< double >::addAND(), gum::prm::PRMInterface< double >::addArc(), gum::prm::gspan::Pattern::addArc(), gum::DAG::addArc(), gum::DiGraph::addArc(), gum::prm::PRMClass< double >::addArc(), gum::DAGCycleDetector::addArc(), gum::InfluenceDiagram< GUM_SCALAR >::addArc(), gum::BayesNet< double >::addArc(), gum::prm::PRMSystem< double >::addArray(), gum::prm::PRMFactory< GUM_SCALAR >::addAttribute(), gum::prm::PRMParameter< double >::addChild(), gum::credal::lp::LpInterface< GUM_SCALAR >::addCols(), gum::FMDP< double >::addCostForAction(), gum::AggregatorDecomposition< GUM_SCALAR >::addDepthLayer_(), gum::UndiGraph::addEdge(), gum::prm::PRMInference< double >::addEvidence(), gum::MarkovNetInference< GUM_SCALAR >::addEvidence(), gum::BayesNetInference< GUM_SCALAR >::addEvidence(), gum::BayesNet< double >::addEXISTS(), gum::BayesNet< double >::addFORALL(), gum::prm::PRMFactory< GUM_SCALAR >::addImport(), gum::prm::PRMFactory< GUM_SCALAR >::addInstance(), gum::JointTargetedInference< GUM_SCALAR >::addJointTarget(), gum::JointTargetedMNInference< GUM_SCALAR >::addJointTarget(), gum::prm::PRMFactory< GUM_SCALAR >::addLabel(), gum::NodeGraphPart::addNodeWithId(), gum::prm::PRMFactory< GUM_SCALAR >::addNoisyOrCompound(), gum::BayesNet< double >::addOR(), gum::prm::o3prm::O3ClassFactory< GUM_SCALAR >::addParameters__(), gum::prm::PRMFormAttribute< GUM_SCALAR >::addParent(), gum::prm::PRMParameter< double >::addParent(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::addParent(), gum::prm::PRMFactory< GUM_SCALAR >::addParent__(), gum::prm::o3prmr::O3prmrInterpreter::addPath(), gum::prm::PRMFactory< GUM_SCALAR >::addRangeType(), gum::prm::PRMFactory< GUM_SCALAR >::addReferenceSlot(), gum::FMDP< double >::addRewardForAction(), gum::credal::lp::LpInterface< GUM_SCALAR >::addRow(), gum::credal::lp::LpExpr::addSide__(), gum::MarginalTargetedInference< GUM_SCALAR >::addTarget(), gum::MarginalTargetedMNInference< GUM_SCALAR >::addTarget(), gum::prm::PRMFactory< GUM_SCALAR >::addTick(), gum::FMDP< double >::addTransitionForAction(), gum::InfluenceDiagram< GUM_SCALAR >::addUtilityNode(), gum::FMDP< double >::addVariable(), gum::credal::CredalNet< GUM_SCALAR >::addVariable(), gum::BayesNet< double >::addWeightedArc(), gum::Instantiation::addWithMaster(), gum::ApproximationSchemeListener::ApproximationSchemeListener(), gum::FormulaPart::argc(), gum::HashTableList< Val, Size, IndexAllocator >::at(), gum::SequenceImplementation< gum::prm::PRMClassElement< double > *, std::allocator< gum::prm::PRMClassElement< double > *>, std::is_scalar< gum::prm::PRMClassElement< double > *>::value >::atPos(), gum::SplayTree< Element >::back(), gum::List< const gum::Potential< GUM_SCALAR > * >::back(), gum::BayesNetFactory< GUM_SCALAR >::BayesNetFactory(), gum::prm::PRMSystem< double >::begin(), gum::prm::PRMInstance< GUM_SCALAR >::begin(), gum::BayesNetInference< GUM_SCALAR >::BN(), gum::learning::BNLearnerListener::BNLearnerListener(), gum::credal::CredalNet< GUM_SCALAR >::bnToCredal(), gum::MultiDimBucket< GUM_SCALAR >::bucket(), gum::prm::o3prm::O3TypeFactory< GUM_SCALAR >::build(), gum::build_node(), gum::prm::PRMAggregate< double >::buildImpl(), gum::MarkovBlanket::buildMarkovBlanket__(), gum::prm::PRMClassElement< double >::cast(), gum::MultiDimICIModel< GUM_SCALAR >::causalWeight(), gum::BayesNet< double >::changePotential(), gum::BayesNet< double >::changeVariableLabel(), gum::prm::o3prm::O3ClassFactory< GUM_SCALAR >::checkAggParameters__(), gum::BNdistance< GUM_SCALAR >::checkCompatibility__(), gum::BayesNetFragment< GUM_SCALAR >::checkConsistency(), gum::learning::genericBNLearner::checkFileName__(), gum::prm::gspan::DFSTree< GUM_SCALAR >::checkGrowth__(), gum::prm::PRMClass< double >::checkInterface__(), gum::prm::PRMFactory< GUM_SCALAR >::checkInterfaceImplementation__(), gum::FMDPFactory< GUM_SCALAR >::checkModalityInBag__(), gum::BayesNetFactory< GUM_SCALAR >::checkModalityInBag__(), gum::prm::o3prm::O3SystemFactory< GUM_SCALAR >::checkParameters__(), gum::prm::PRMClass< double >::checkRefInterface__(), gum::prm::PRMFactory< GUM_SCALAR >::checkStack__(), gum::prm::PRMFactory< GUM_SCALAR >::checkStackContainter__(), gum::BayesNetFactory< GUM_SCALAR >::checkVariableModality__(), gum::BayesNetFactory< GUM_SCALAR >::checkVariableName__(), gum::MarkovNetInference< GUM_SCALAR >::chgEvidence(), gum::BayesNetInference< GUM_SCALAR >::chgEvidence(), gum::Instantiation::chgVal(), gum::prm::gspan::DFSTree< GUM_SCALAR >::children(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::chooseCloseNodes__(), gum::Instantiation::clear(), gum::credal::CNLoopyPropagation< GUM_SCALAR >::CNLoopyPropagation(), gum::prm::PRMClass< double >::completeInheritance(), gum::DefaultJunctionTreeStrategy::computeJunctionTree__(), gum::BNdistance< GUM_SCALAR >::computeKL_(), gum::MultiDimBucket< GUM_SCALAR >::computeValue__(), gum::credal::LRSWrapper< GUM_SCALAR >::computeVolume(), gum::prm::PRMFactory< GUM_SCALAR >::continueAggregator(), gum::ApproximationScheme::continueApproximationScheme(), gum::prm::PRMFactory< GUM_SCALAR >::continueAttribute(), gum::prm::PRMFactory< GUM_SCALAR >::continueClass(), gum::prm::PRMFactory< GUM_SCALAR >::continueInterface(), gum::BinaryJoinTreeConverterDefault::convert(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::copy(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::copyAndMultiplyByScalar(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::copyAndReassign(), gum::MultiDimICIModel< GUM_SCALAR >::copyFrom(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::copyFrom(), gum::aggregator::MultiDimAggregator< GUM_SCALAR >::copyFrom(), gum::MultiDimContainer< GUM_SCALAR >::copyFrom(), gum::prm::PRMSlotChain< double >::copyLastElt__(), gum::prm::copyPotential(), gum::FMDP< double >::cost(), gum::prm::PRMParameter< double >::cpf(), gum::prm::PRMReferenceSlot< double >::cpf(), gum::prm::PRMAggregate< double >::cpf(), gum::BayesNetFragment< GUM_SCALAR >::cpt(), gum::learning::genericBNLearner::createApriori__(), gum::learning::genericBNLearner::createCorrectedMutualInformation__(), gum::MarkovNetInference< GUM_SCALAR >::createHardEvidence__(), gum::BayesNetInference< GUM_SCALAR >::createHardEvidence__(), gum::learning::genericBNLearner::createParamEstimator__(), gum::learning::genericBNLearner::createScore__(), gum::learning::genericBNLearner::currentTime(), gum::prm::PRMFactory< GUM_SCALAR >::currentType(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::database(), gum::learning::genericBNLearner::Database::Database(), gum::LinearApproximationPolicy< GUM_SCALAR >::decode(), gum::AggregatorDecomposition< GUM_SCALAR >::decomposeAggregator_(), gum::DiGraphListener::DiGraphListener(), gum::ArcGraphPart::directedPath(), gum::ArcGraphPart::directedUnorientedPath(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::disturbBN(), gum::Potential< GUM_SCALAR >::draw(), gum::credal::InferenceEngine< GUM_SCALAR >::dynamicExpMax(), gum::credal::InferenceEngine< GUM_SCALAR >::dynamicExpMin(), gum::prm::gspan::Pattern::edgeCode(), gum::prm::SVE< GUM_SCALAR >::eliminateNodesWithEvidence__(), gum::IncrementalTriangulation::eliminationTree(), gum::OrderedEliminationSequenceStrategy::eliminationUpdate(), gum::credal::LRSWrapper< GUM_SCALAR >::elimRedundVrep(), gum::LinearApproximationPolicy< GUM_SCALAR >::encode(), gum::prm::PRMSystem< double >::end(), gum::prm::PRMFactory< GUM_SCALAR >::endDiscreteType(), gum::prm::PRMFactory< GUM_SCALAR >::endDiscretizedType(), gum::prm::PRMFactory< GUM_SCALAR >::endSystem(), gum::FMDPFactory< GUM_SCALAR >::endVariableDeclaration(), gum::BayesNetFactory< GUM_SCALAR >::endVariableDeclaration(), gum::learning::genericBNLearner::epsilon(), gum::MultiDimBijArray< GUM_SCALAR >::erase(), gum::MultiDimImplementation< std::string >::erase(), gum::Instantiation::erase(), gum::HashTableList< Val, Size, IndexAllocator >::erase(), gum::JointTargetedInference< GUM_SCALAR >::eraseJointTarget(), gum::JointTargetedMNInference< GUM_SCALAR >::eraseJointTarget(), gum::MultiDimFunctionGraphManager< bool, ExactTerminalNodePolicy >::eraseNode(), gum::MarginalTargetedInference< GUM_SCALAR >::eraseTarget(), gum::MarginalTargetedMNInference< GUM_SCALAR >::eraseTarget(), gum::Instantiation::eraseWithMaster(), gum::FormulaPart::eval(), gum::prm::PRMInference< double >::evidence(), gum::MarginalTargetedInference< GUM_SCALAR >::evidenceImpact(), gum::MarginalTargetedMNInference< GUM_SCALAR >::evidenceImpact(), gum::JointTargetedInference< GUM_SCALAR >::evidenceJointImpact(), gum::JointTargetedMNInference< GUM_SCALAR >::evidenceJointImpact(), gum::MultiDimContainer< GUM_SCALAR >::extractFrom(), gum::MultiDimReadOnly< GUM_SCALAR >::fill(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::fill(), gum::MultiDimBijArray< GUM_SCALAR >::fill(), gum::credal::CredalNet< GUM_SCALAR >::fillConstraint(), gum::credal::CredalNet< GUM_SCALAR >::fillConstraints(), gum::prm::PRMFormAttribute< GUM_SCALAR >::fillCpf__(), gum::credal::LRSWrapper< GUM_SCALAR >::fillH(), gum::IncrementalTriangulation::fillIns(), gum::credal::LRSWrapper< GUM_SCALAR >::fillMatrix(), gum::credal::LRSWrapper< GUM_SCALAR >::fillV(), gum::Potential< GUM_SCALAR >::fillWith(), gum::Formula::finalize__(), gum::FMDPFactory< GUM_SCALAR >::fmdp(), gum::prm::StructuredBayesBall< GUM_SCALAR >::fromChild__(), gum::SplayTree< Element >::front(), gum::List< const gum::Potential< GUM_SCALAR > * >::front(), gum::func2str(), gum::FormulaPart::function_argc__(), gum::FormulaPart::function_eval__(), gum::GammaLog2::gammaLog2(), gum::prm::ClusteredLayerGenerator< GUM_SCALAR >::generate(), gum::prm::LayerGenerator< GUM_SCALAR >::generate(), gum::prm::ClusteredLayerGenerator< GUM_SCALAR >::generateCluster__(), gum::prm::ClusteredLayerGenerator< GUM_SCALAR >::generateSystem__(), gum::prm::PRMSystem< double >::get(), gum::MultiDimLogit< GUM_SCALAR >::get(), gum::MultiDimNoisyORNet< GUM_SCALAR >::get(), gum::prm::PRMInterface< double >::get(), gum::MultiDimNoisyORCompound< GUM_SCALAR >::get(), gum::aggregator::MultiDimAggregator< GUM_SCALAR >::get(), gum::MultiDimNoisyAND< GUM_SCALAR >::get(), gum::prm::PRMInstance< GUM_SCALAR >::get(), gum::prm::PRMClass< double >::get(), gum::MultiDimReadOnly< GUM_SCALAR >::get_(), gum::MultiDimSparse< GUM_SCALAR >::get_(), gum::MultiDimBijArray< GUM_SCALAR >::get_(), gum::MultiDimDecorator< GUM_SCALAR >::get_(), gum::MultiDimBucket< GUM_SCALAR >::get_(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::get_(), gum::prm::InstanceBayesNet< GUM_SCALAR >::get__(), gum::prm::ClassBayesNet< GUM_SCALAR >::get__(), gum::learning::genericBNLearner::getAprioriType__(), gum::prm::PRMSystem< double >::getArray(), gum::prm::PRMSystem< double >::getArrayType(), gum::prm::GroundedInference< GUM_SCALAR >::getBNInference(), gum::MultiDimArray< GUM_SCALAR >::getByOffset(), gum::prm::PRMFormAttribute< GUM_SCALAR >::getCastDescendant(), gum::prm::PRMParameter< double >::getCastDescendant(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::getCastDescendant(), gum::prm::PRMReferenceSlot< double >::getCastDescendant(), gum::prm::PRMSlotChain< double >::getCastDescendant(), gum::prm::PRMAggregate< double >::getCastDescendant(), gum::prm::PRMFactory< GUM_SCALAR >::getCurrent(), gum::IndexedTree< Key, Data >::getData(), gum::InfluenceDiagram< GUM_SCALAR >::getDecisionOrder(), gum::credal::VarMod2BNsMap< GUM_SCALAR >::getFullBNOptsFromKey(), gum::prm::PRMInstance< GUM_SCALAR >::getInstance(), gum::prm::PRMInstance< GUM_SCALAR >::getInstances(), gum::prm::PRMClassElementContainer< double >::getIOFlag_(), gum::MultiDimWithOffset< GUM_SCALAR >::getOffs_(), gum::credal::LRSWrapper< GUM_SCALAR >::getVolume(), gum::prm::PRMSystem< double >::groundAgg__(), gum::prm::GroundedInference< GUM_SCALAR >::GroundedInference(), gum::prm::PRMSystem< double >::groundPotential__(), gum::prm::gspan::DFSTree< GUM_SCALAR >::growPattern(), gum::credal::LRSWrapper< GUM_SCALAR >::H2V(), gum::credal::CredalNet< GUM_SCALAR >::H2Vlrs__(), gum::DAGCycleDetector::hasCycleFromModifications(), gum::HashTableConstIterator< Key, bool >::HashTableConstIterator(), gum::HashTableConstIteratorSafe< const gum::DiscreteVariable *, Idx >::HashTableConstIteratorSafe(), gum::ApproximationScheme::history(), gum::learning::genericBNLearner::history(), gum::JointTargetedInference< GUM_SCALAR >::I(), gum::JointTargetedMNInference< GUM_SCALAR >::I(), gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::IBayesNetGenerator(), gum::BayesNetFragment< GUM_SCALAR >::idFromName(), gum::learning::genericBNLearner::Database::idFromName(), gum::credal::CredalNet< GUM_SCALAR >::idmLearning(), gum::FMDPFactory< GUM_SCALAR >::illegalStateError__(), gum::BayesNetFactory< GUM_SCALAR >::illegalStateError__(), gum::prm::PRMClass< double >::implements(), gum::prm::PRMFactory< GUM_SCALAR >::incArray(), gum::RangeVariable::index(), gum::credal::CNLoopyPropagation< GUM_SCALAR >::initialize_(), gum::credal::LRSWrapper< GUM_SCALAR >::initLrs__(), gum::prm::SVED< GUM_SCALAR >::initReqSets__(), gum::List< const gum::Potential< GUM_SCALAR > * >::insert(), gum::BijectionImplementation< Idx, const std::string *, std::allocator< const std::string * >, std::is_scalar< Idx >::value &&std::is_scalar< const std::string * >::value >::insert__(), gum::List< const gum::Potential< GUM_SCALAR > * >::insert__(), gum::HashTable< Val, Size, IndexAllocator >::insert__(), gum::credal::InferenceEngine< GUM_SCALAR >::insertEvidenceFile(), gum::credal::InferenceEngine< GUM_SCALAR >::insertModalsFile(), gum::IndexedTree< Key, Data >::insertNode(), gum::credal::InferenceEngine< GUM_SCALAR >::insertQueryFile(), gum::BayesNetFragment< GUM_SCALAR >::installCPT(), gum::BayesNetFragment< GUM_SCALAR >::installMarginal(), gum::BayesNetFragment< GUM_SCALAR >::installNode(), gum::credal::CredalNet< GUM_SCALAR >::intervalToCredal__(), gum::prm::PRMClass< double >::isCastDescendant(), gum::prm::PRMAggregate< double >::isDecomposable(), gum::learning::genericBNLearner::isEnabledEpsilon(), gum::learning::genericBNLearner::isEnabledMaxIter(), gum::learning::genericBNLearner::isEnabledMaxTime(), gum::learning::genericBNLearner::isEnabledMinEpsilonRate(), gum::MarkovNetInference< GUM_SCALAR >::isHardEvidence__(), gum::BayesNetInference< GUM_SCALAR >::isHardEvidence__(), gum::JointTargetedInference< GUM_SCALAR >::isJointTarget(), gum::JointTargetedMNInference< GUM_SCALAR >::isJointTarget(), gum::FormulaPart::isLeftAssociative(), gum::prm::gspan::DFSTree< GUM_SCALAR >::iso_graph(), gum::prm::gspan::DFSTree< GUM_SCALAR >::iso_map(), gum::prm::PRMInterface< double >::isSubTypeOf(), gum::prm::PRMClass< double >::isSubTypeOf(), gum::MarginalTargetedInference< GUM_SCALAR >::isTarget(), gum::MarginalTargetedMNInference< GUM_SCALAR >::isTarget(), gum::prm::PRMInference< double >::joint(), gum::prm::SVED< GUM_SCALAR >::joint_(), gum::prm::SVE< GUM_SCALAR >::joint_(), gum::prm::GroundedInference< GUM_SCALAR >::joint_(), gum::prm::StructuredInference< GUM_SCALAR >::joint_(), gum::JointTargetedInference< GUM_SCALAR >::jointMutualInformation(), gum::JointTargetedMNInference< GUM_SCALAR >::jointMutualInformation(), gum::JointTargetedInference< GUM_SCALAR >::jointPosterior(), gum::JointTargetedMNInference< GUM_SCALAR >::jointPosterior(), gum::HashTable< Val, Size, IndexAllocator >::key(), gum::HashTableConstIteratorSafe< const gum::DiscreteVariable *, Idx >::key(), gum::HashTableConstIterator< Key, bool >::key(), gum::HashTable< Val, Size, IndexAllocator >::keyByVal(), gum::Potential< GUM_SCALAR >::KL(), gum::prm::gspan::Pattern::label(), gum::RangeVariable::label(), gum::prm::PRMAggregate< double >::label(), gum::prm::PRMType::label_map(), gum::credal::CredalNet< GUM_SCALAR >::lagrangeNormalization(), gum::prm::gspan::Pattern::lastAdded(), gum::learning::genericBNLearner::latentVariables(), gum::learning::genericBNLearner::learnDAG__(), gum::learning::genericBNLearner::learnMixedStructure(), gum::learning::GreedyHillClimbing::learnStructure(), gum::learning::LocalSearchWithTabuList::learnStructure(), gum::LinearApproximationPolicy< GUM_SCALAR >::LinearApproximationPolicy(), gum::ListConstIterator< Val >::ListConstIterator(), gum::ListConstIteratorSafe< Val >::ListConstIteratorSafe(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::log2likelihood(), gum::credal::lp::LpRow::LpRow(), gum::MarkovBlanket::MarkovBlanket(), gum::prm::gspan::DFSTree< GUM_SCALAR >::max_indep_set(), gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::MaxInducedWidthMCBayesNetGenerator(), gum::learning::genericBNLearner::maxIter(), gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::MaxParentsMCBayesNetGenerator(), gum::learning::genericBNLearner::maxTime(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::MCBayesNetGenerator(), gum::learning::genericBNLearner::minEpsilonRate(), gum::MixedGraphListener::MixedGraphListener(), gum::MixedGraph::mixedOrientedPath(), gum::MixedGraph::mixedUnorientedPath(), gum::MarkovNetInference< GUM_SCALAR >::MN(), gum::MultiDimNoisyAND< GUM_SCALAR >::MultiDimNoisyAND(), gum::learning::genericBNLearner::Database::nameFromId(), gum::ApproximationScheme::nbrIterations(), gum::learning::genericBNLearner::nbrIterations(), gum::credal::LRSWrapper< GUM_SCALAR >::nextHInput(), gum::prm::NameGenerator::nextName(), gum::OrderedEliminationSequenceStrategy::nextNodeToEliminate(), gum::DefaultEliminationSequenceStrategy::nextNodeToEliminate(), gum::DefaultPartialOrderedEliminationSequenceStrategy::nextNodeToEliminate(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::node(), gum::BayesNetFragment< GUM_SCALAR >::nodeId(), gum::DefaultPartialOrderedEliminationSequenceStrategy::nodeToEliminate__(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::nodeValue(), gum::Potential< GUM_SCALAR >::noising(), gum::Potential< GUM_SCALAR >::normalizeAsCPT(), gum::MultiDimDecorator< GUM_SCALAR >::notifyChange(), gum::SamplingInference< GUM_SCALAR >::onEvidenceAdded_(), gum::SamplingInference< GUM_SCALAR >::onEvidenceChanged_(), gum::NodeGraphPartIterator::operator*(), gum::RefPtr< Val >::operator*(), gum::ListConstIterator< Val >::operator*(), gum::HashTableConstIteratorSafe< const gum::DiscreteVariable *, Idx >::operator*(), gum::ListConstIteratorSafe< Val >::operator*(), gum::HashTableConstIterator< Key, bool >::operator*(), gum::credal::lp::LpExpr::operator+=(), gum::credal::lp::LpExpr::operator-=(), gum::RefPtr< Val >::operator->(), gum::ListConstIterator< Val >::operator->(), gum::ListConstIteratorSafe< Val >::operator->(), gum::operator<<(), gum::learning::BNLearnerListener::operator=(), gum::prm::PRMFuncAttribute< GUM_SCALAR >::operator=(), gum::ApproximationSchemeListener::operator=(), gum::ProgressListener::operator=(), gum::learning::DAG2BNLearner< ALLOC >::operator=(), gum::DiGraphListener::operator=(), gum::UndiGraphListener::operator=(), gum::MultiDimBijArray< GUM_SCALAR >::operator=(), gum::prm::PRMFormAttribute< GUM_SCALAR >::operator=(), gum::prm::StructuredBayesBall< GUM_SCALAR >::operator=(), gum::prm::PRMParameter< double >::operator=(), gum::MixedGraphListener::operator=(), gum::Instantiation::operator=(), gum::prm::GroundedInference< GUM_SCALAR >::operator=(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::operator=(), gum::prm::PRMReferenceSlot< double >::operator=(), gum::prm::gspan::InterfaceGraph< GUM_SCALAR >::operator=(), gum::prm::PRMSlotChain< double >::operator=(), gum::prm::PRMType::operator=(), gum::prm::PRMAggregate< double >::operator=(), gum::FMDPFactory< GUM_SCALAR >::operator=(), gum::prm::PRMClassElementContainer< double >::operator=(), gum::BayesNetFactory< GUM_SCALAR >::operator=(), gum::prm::PRMInstance< GUM_SCALAR >::operator=(), gum::BijectionImplementation< Idx, const std::string *, std::allocator< const std::string * >, std::is_scalar< Idx >::value &&std::is_scalar< const std::string * >::value >::operator=(), gum::SequenceImplementation< gum::prm::PRMClassElement< double > *, std::allocator< gum::prm::PRMClassElement< double > *>, std::is_scalar< gum::prm::PRMClassElement< double > *>::value >::operator=(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::operator=(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::operator[](), gum::Heap< Val, Cmp, Alloc >::operator[](), gum::MultiPriorityQueue< gum::LeafPair *, double, std::less< double > >::operator[](), gum::SplayTree< Element >::operator[](), gum::HashTableList< Val, Size, IndexAllocator >::operator[](), gum::List< const gum::Potential< GUM_SCALAR > * >::operator[](), gum::FormulaPart::operator_argc__(), gum::FormulaPart::operator_eval__(), gum::OrderedEliminationSequenceStrategy::OrderedEliminationSequenceStrategy(), gum::prm::PRMClass< double >::overload(), gum::prm::PRMInterface< double >::overload(), gum::prm::PRMClass< double >::overloadReference__(), gum::prm::gspan::DFSTree< GUM_SCALAR >::parent(), gum::prm::gspan::DFSTree< GUM_SCALAR >::pattern(), gum::learning::genericBNLearner::periodSize(), gum::Heap< Val, Cmp, Alloc >::pop(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::pop(), gum::MultiPriorityQueue< gum::LeafPair *, double, std::less< double > >::pop(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::populate(), gum::MultiDimBijArray< GUM_SCALAR >::populate(), gum::MultiDimContainer< GUM_SCALAR >::populate(), gum::MultiDimDecorator< GUM_SCALAR >::populate(), gum::SequenceIteratorSafe< NodeId >::pos(), gum::MarginalTargetedInference< GUM_SCALAR >::posterior(), gum::MarginalTargetedMNInference< GUM_SCALAR >::posterior(), gum::Estimator< GUM_SCALAR >::posterior(), gum::prm::PRMInference< double >::posterior(), gum::prm::GroundedInference< GUM_SCALAR >::posterior_(), gum::FormulaPart::precedence(), gum::MarkovNetInference< GUM_SCALAR >::prepareInference(), gum::BayesNetInference< GUM_SCALAR >::prepareInference(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::priorityByPos(), gum::prm::PRMAggregate< double >::PRMAggregate(), gum::prm::PRMAttribute< double >::PRMAttribute(), gum::prm::PRMClassElementContainer< double >::PRMClassElementContainer(), gum::prm::PRMFormAttribute< GUM_SCALAR >::PRMFormAttribute(), gum::prm::PRMFuncAttribute< GUM_SCALAR >::PRMFuncAttribute(), gum::prm::PRMInstance< GUM_SCALAR >::PRMInstance(), gum::prm::PRMInterface< double >::PRMInterface(), gum::prm::PRMParameter< double >::PRMParameter(), gum::prm::PRMReferenceSlot< double >::PRMReferenceSlot(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::PRMScalarAttribute(), gum::prm::PRMSlotChain< double >::PRMSlotChain(), gum::prm::PRMType::PRMType(), gum::ProgressListener::ProgressListener(), gum::GraphicalModel::property(), gum::Formula::push_comma__(), gum::Formula::push_function__(), gum::Formula::push_identifier__(), gum::Formula::push_rightParenthesis__(), gum::Formula::push_variable__(), gum::Potential< GUM_SCALAR >::putFirst(), gum::learning::readFile(), gum::prm::o3prmr::O3prmrInterpreter::readFile__(), gum::prm::o3prm::O3prmReader< double >::readStream__(), gum::Formula::reduceOperatorOrFunction__(), gum::prm::gspan::Pattern::remove(), gum::Instantiation::reorder(), gum::Potential< GUM_SCALAR >::reorganize(), gum::credal::InferenceEngine< GUM_SCALAR >::repetitiveInit_(), gum::MultiDimInterface::replace(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::replace_(), gum::Formula::result(), gum::prm::PRMFactory< GUM_SCALAR >::retrieveClass__(), gum::prm::PRMFactory< GUM_SCALAR >::retrieveCommonType__(), gum::prm::PRMFactory< GUM_SCALAR >::retrieveInputs__(), gum::prm::PRMFactory< GUM_SCALAR >::retrieveInterface__(), gum::prm::PRMFactory< GUM_SCALAR >::retrieveType__(), gum::DAGCycleDetector::reverseArc(), gum::BayesNet< double >::reverseArc(), gum::FMDP< double >::reward(), gum::LinearApproximationPolicy< GUM_SCALAR >::safeFromExact(), gum::credal::CredalNet< GUM_SCALAR >::saveBNsMinMax(), gum::credal::InferenceEngine< GUM_SCALAR >::saveExpectations(), gum::credal::CNLoopyPropagation< GUM_SCALAR >::saveInference(), gum::credal::InferenceEngine< GUM_SCALAR >::saveMarginals(), gum::credal::InferenceEngine< GUM_SCALAR >::saveVertices(), gum::MultiDimReadOnly< GUM_SCALAR >::set(), gum::MultiDimBijArray< GUM_SCALAR >::set(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::set(), gum::learning::genericBNLearner::setAprioriWeight__(), gum::prm::PRMFormAttribute< GUM_SCALAR >::setAsCastDescendant(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::setAsCastDescendant(), gum::SequenceImplementation< gum::prm::PRMClassElement< double > *, std::allocator< gum::prm::PRMClassElement< double > *>, std::is_scalar< gum::prm::PRMClassElement< double > *>::value >::setAtPos(), gum::MultiDimArray< GUM_SCALAR >::setByOffset(), gum::prm::PRMFuncAttribute< GUM_SCALAR >::setCpf_(), gum::prm::PRMFactory< GUM_SCALAR >::setCPFByFloatRule(), gum::prm::PRMFactory< GUM_SCALAR >::setCPFByRule(), gum::credal::CredalNet< GUM_SCALAR >::setCPT(), gum::credal::CredalNet< GUM_SCALAR >::setCPTs(), gum::setDynamicThreadsNumber(), gum::ApproximationScheme::setEpsilon(), gum::EliminationSequenceStrategy::setGraph(), gum::LinearApproximationPolicy< GUM_SCALAR >::setHighLimit(), gum::prm::PRMClassElementContainer< double >::setInputNode(), gum::LinearApproximationPolicy< GUM_SCALAR >::setLimits(), gum::LinearApproximationPolicy< GUM_SCALAR >::setLowLimit(), gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setMaxArcs(), gum::AggregatorDecomposition< GUM_SCALAR >::setMaximumArity(), gum::ApproximationScheme::setMaxIter(), gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::setMaxlog10InducedWidth(), gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setMaxModality(), gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::setMaxParents(), gum::ApproximationScheme::setMaxTime(), gum::ApproximationScheme::setMinEpsilonRate(), gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setNbrNodes(), gum::setNestedParallelism(), gum::setNumberOfThreads(), gum::prm::PRMClassElementContainer< double >::setOutputNode(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::setP(), gum::ApproximationScheme::setPeriodSize(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::setPriorityByPos(), gum::MultiPriorityQueue< gum::LeafPair *, double, std::less< double > >::setPriorityByPos(), gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >::setQ(), gum::prm::PRMFactory< GUM_SCALAR >::setRawCPFByColumns(), gum::prm::PRMFactory< GUM_SCALAR >::setRawCPFByFloatColumns(), gum::prm::PRMFactory< GUM_SCALAR >::setRawCPFByFloatLines(), gum::prm::PRMFactory< GUM_SCALAR >::setRawCPFByLines(), gum::prm::PRMFactory< GUM_SCALAR >::setReferenceSlot(), gum::MultiDimFunctionGraphManager< bool, ExactTerminalNodePolicy >::setSon(), gum::prm::PRMType::setSuper(), gum::credal::LRSWrapper< GUM_SCALAR >::setUpH(), gum::credal::LRSWrapper< GUM_SCALAR >::setUpV(), gum::Instantiation::setValsFrom(), gum::BayesNetFactory< GUM_SCALAR >::setVariable(), gum::BayesNetFactory< GUM_SCALAR >::setVariableCPT(), gum::BayesNetFactory< GUM_SCALAR >::setVariableCPTImplementation(), gum::BayesNetFactory< GUM_SCALAR >::setVariableValues(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::setVarOrder(), gum::IMarkovNet< GUM_SCALAR >::smallestFactorFromNode(), gum::SpanningForestPrim::SpanningForestPrim(), gum::SplayTree< Element >::split_by_val(), gum::prm::PRMFactory< GUM_SCALAR >::startAggregator(), gum::prm::PRMFactory< GUM_SCALAR >::startClass(), gum::prm::PRMFactory< GUM_SCALAR >::startDiscreteType(), gum::prm::PRMFactory< GUM_SCALAR >::startDiscretizedType(), gum::prm::PRMFactory< GUM_SCALAR >::startInterface(), gum::prm::PRMFactory< GUM_SCALAR >::startSystem(), gum::learning::genericBNLearner::stateApproximationScheme(), gum::FormulaPart::str(), gum::prm::PRMAggregate< double >::str2enum(), gum::prm::StructuredBayesBall< GUM_SCALAR >::StructuredBayesBall(), gum::prm::PRMInterface< double >::super(), gum::prm::PRMClass< double >::super(), gum::prm::PRMType::superType(), gum::prm::PRMFormAttribute< GUM_SCALAR >::swap(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::swap(), gum::Instantiation::synchronizeWithMaster(), gum::BayesNetFragment< GUM_SCALAR >::toBN(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::toCSV(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::toDatabaseTable(), gum::Heap< Val, Cmp, Alloc >::top(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::top(), gum::MultiPriorityQueue< gum::LeafPair *, double, std::less< double > >::top(), gum::DiGraph::topologicalOrder__(), gum::PriorityQueueImplementation< NodeId, double, std::greater< double >, std::allocator< NodeId >, std::is_scalar< NodeId >::value >::topPriority(), gum::MultiPriorityQueue< gum::LeafPair *, double, std::less< double > >::topPriority(), gum::learning::GraphChange::toString(), gum::FMDP< double >::transition(), gum::prm::StructuredInference< GUM_SCALAR >::translatePotSet__(), gum::IncrementalTriangulation::triangulatedGraph(), gum::prm::PRMParameter< double >::type(), gum::prm::PRMReferenceSlot< double >::type(), gum::prm::PRMFormAttribute< GUM_SCALAR >::type_(), gum::prm::PRMScalarAttribute< GUM_SCALAR >::type_(), gum::UndiGraphListener::UndiGraphListener(), gum::EdgeGraphPart::undirectedPath(), gum::GibbsOperator< GUM_SCALAR >::updateSamplingNodes__(), gum::learning::genericBNLearner::useAprioriBDeu(), gum::learning::genericBNLearner::useAprioriDirichlet(), gum::learning::genericBNLearner::useAprioriSmoothing(), gum::learning::genericBNLearner::useCrossValidationFold(), gum::learning::genericBNLearner::useMDL(), gum::learning::genericBNLearner::useNML(), gum::learning::genericBNLearner::useNoCorr(), gum::credal::LRSWrapper< GUM_SCALAR >::V2H(), gum::Instantiation::val(), gum::HashTableConstIteratorSafe< const gum::DiscreteVariable *, Idx >::val(), gum::HashTableConstIterator< Key, bool >::val(), gum::HashTableIterator< int, int >::val(), gum::FMDPFactory< GUM_SCALAR >::variable(), gum::BayesNetFactory< GUM_SCALAR >::variable(), gum::BayesNetFragment< GUM_SCALAR >::variable(), gum::MultiDimImplementation< std::string >::variable(), gum::Instantiation::variable(), gum::BayesNetFragment< GUM_SCALAR >::variableFromName(), gum::BayesNetFactory< GUM_SCALAR >::variableId(), gum::FMDPFactory< GUM_SCALAR >::variableName(), gum::BayesNetFactory< GUM_SCALAR >::variableName(), gum::prm::InstanceBayesNet< GUM_SCALAR >::variableNodeMap(), gum::prm::ClassBayesNet< GUM_SCALAR >::variableNodeMap(), gum::BayesNetFragment< GUM_SCALAR >::variableNodeMap(), gum::BayesNetFactory< GUM_SCALAR >::variableType(), gum::MultiDimFunctionGraph< bool, ExactTerminalNodePolicy >::varNodeListe(), gum::learning::BNDatabaseGenerator< GUM_SCALAR >::varOrderFromCSV__(), and gum::learning::genericBNLearner::verbosity().

◆ GUM_ERROR_IN_EXPR

#define GUM_ERROR_IN_EXPR (   type,
  msg 
)    throw(type(msg))

Definition at line 39 of file exceptions.h.

◆ GUM_MAKE_ERROR

#define GUM_MAKE_ERROR (   TYPE,
  SUPERCLASS,
  MSG 
)
Value:
class TYPE: public SUPERCLASS { \
public: \
TYPE(std::string aMsg, std::string aType = MSG) : SUPERCLASS(aMsg, aType){}; \
TYPE(const TYPE& src) : SUPERCLASS(src){}; \
};

Definition at line 87 of file exceptions.h.

◆ GUM_SHOWERROR

◆ GUM_SYNTAX_ERROR

#define GUM_SYNTAX_ERROR (   msg,
  line,
  column 
)
Value:
{ \
std::ostringstream error_stream; \
error_stream << msg; \
throw(gum::SyntaxError(error_stream.str(), line, column)); \
}

Definition at line 94 of file exceptions.h.