| __estimator | gum::SamplingInference< GUM_SCALAR > | protected |
| _addVarSample(NodeId nod, Instantiation *I) | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _burn_in | gum::ApproximationScheme | protected |
| _burnIn() override | gum::WeightedSampling< GUM_SCALAR > | protectedvirtual |
| _current_epsilon | gum::ApproximationScheme | protected |
| _current_rate | gum::ApproximationScheme | protected |
| _current_state | gum::ApproximationScheme | protected |
| _current_step | gum::ApproximationScheme | protected |
| _draw(GUM_SCALAR *w, Instantiation prev) override | gum::WeightedSampling< GUM_SCALAR > | protectedvirtual |
| _enabled_eps | gum::ApproximationScheme | protected |
| _enabled_max_iter | gum::ApproximationScheme | protected |
| _enabled_max_time | gum::ApproximationScheme | protected |
| _enabled_min_rate_eps | gum::ApproximationScheme | protected |
| _eps | gum::ApproximationScheme | protected |
| _history | gum::ApproximationScheme | protected |
| _isTargetedMode() const | gum::MarginalTargetedInference< GUM_SCALAR > | protected |
| _last_epsilon | gum::ApproximationScheme | protected |
| _loopApproxInference() | gum::SamplingInference< GUM_SCALAR > | protected |
| _makeInference() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _max_iter | gum::ApproximationScheme | protected |
| _max_time | gum::ApproximationScheme | protected |
| _min_rate_eps | gum::ApproximationScheme | protected |
| _onAllEvidenceErased(bool contains_hard_evidence) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onAllMarginalTargetsAdded() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onAllMarginalTargetsErased() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onBayesNetChanged(const IBayesNet< GUM_SCALAR > *bn) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onContextualize(BayesNetFragment< GUM_SCALAR > *bn) | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onEvidenceAdded(const NodeId id, bool isHardEvidence) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onEvidenceChanged(const NodeId id, bool hasChangedSoftHard) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onEvidenceErased(const NodeId id, bool isHardEvidence) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onMarginalTargetAdded(const NodeId id) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onMarginalTargetErased(const NodeId id) override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _onStateChanged() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _period_size | gum::ApproximationScheme | protected |
| _posterior(NodeId id) override | gum::SamplingInference< GUM_SCALAR > | virtual |
| _setEstimatorFromBN() | gum::SamplingInference< GUM_SCALAR > | virtual |
| _setEstimatorFromLBP(LoopyBeliefPropagation< GUM_SCALAR > *lbp, GUM_SCALAR virtualLBPSize) | gum::SamplingInference< GUM_SCALAR > | virtual |
| _setOutdatedBNPotentialsState() | gum::BayesNetInference< GUM_SCALAR > | protected |
| _setOutdatedBNStructureState() | gum::BayesNetInference< GUM_SCALAR > | protected |
| _setTargetedMode() | gum::MarginalTargetedInference< GUM_SCALAR > | protected |
| _timer | gum::ApproximationScheme | protected |
| _updateOutdatedBNPotentials() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _updateOutdatedBNStructure() override | gum::SamplingInference< GUM_SCALAR > | protectedvirtual |
| _verbosity | gum::ApproximationScheme | protected |
| addAllTargets() final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| addEvidence(NodeId id, const Idx val) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(const std::string &nodeName, const Idx val) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(NodeId id, const std::string &label) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(const std::string &nodeName, const std::string &label) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(NodeId id, const std::vector< GUM_SCALAR > &vals) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(const std::string &nodeName, const std::vector< GUM_SCALAR > &vals) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(const Potential< GUM_SCALAR > &pot) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addEvidence(Potential< GUM_SCALAR > &&pot) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addListOfEvidence(const List< const Potential< GUM_SCALAR > * > &potlist) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addSetOfEvidence(const Set< const Potential< GUM_SCALAR > * > &potset) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| addTarget(NodeId target) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| addTarget(const std::string &nodeName) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| ApproximateInference(const IBayesNet< GUM_SCALAR > *bn) | gum::ApproximateInference< GUM_SCALAR > | inlineexplicit |
| ApproximationScheme(bool verbosity=false) | gum::ApproximationScheme | |
| ApproximationSchemeSTATE enum name | gum::IApproximationSchemeConfiguration | |
| BayesNetInference(const IBayesNet< GUM_SCALAR > *bn) | gum::BayesNetInference< GUM_SCALAR > | explicit |
| BayesNetInference() | gum::BayesNetInference< GUM_SCALAR > | |
| BN() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(NodeId id, const Idx val) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(const std::string &nodeName, const Idx val) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(NodeId id, const std::string &label) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(const std::string &nodeName, const std::string &label) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(NodeId id, const std::vector< GUM_SCALAR > &vals) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(const std::string &nodeName, const std::vector< GUM_SCALAR > &vals) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| chgEvidence(const Potential< GUM_SCALAR > &pot) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| clear() | gum::BayesNetInference< GUM_SCALAR > | virtual |
| contextualize() | gum::SamplingInference< GUM_SCALAR > | virtual |
| continueApproximationScheme(double error) | gum::ApproximationScheme | |
| currentPosterior(NodeId id) | gum::SamplingInference< GUM_SCALAR > | |
| currentPosterior(const std::string &name) | gum::SamplingInference< GUM_SCALAR > | |
| currentTime() const | gum::ApproximationScheme | virtual |
| disableEpsilon() | gum::ApproximationScheme | virtual |
| disableMaxIter() | gum::ApproximationScheme | virtual |
| disableMaxTime() | gum::ApproximationScheme | virtual |
| disableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| domainSizes() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| enableEpsilon() | gum::ApproximationScheme | virtual |
| enableMaxIter() | gum::ApproximationScheme | virtual |
| enableMaxTime() | gum::ApproximationScheme | virtual |
| enableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| epsilon() const | gum::ApproximationScheme | virtual |
| eraseAllEvidence() final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| eraseAllTargets() | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| eraseEvidence(NodeId id) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| eraseEvidence(const std::string &nodeName) final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| eraseTarget(NodeId target) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| eraseTarget(const std::string &nodeName) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| evidence() const | gum::BayesNetInference< GUM_SCALAR > | |
| evidenceImpact(NodeId target, const NodeSet &evs) | gum::MarginalTargetedInference< GUM_SCALAR > | |
| evidenceImpact(const std::string &target, const std::vector< std::string > &evs) | gum::MarginalTargetedInference< GUM_SCALAR > | |
| H(NodeId X) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| H(const std::string &nodeName) final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| hardEvidence() const | gum::BayesNetInference< GUM_SCALAR > | |
| hardEvidenceNodes() const | gum::BayesNetInference< GUM_SCALAR > | |
| hasEvidence() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasEvidence(NodeId id) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasEvidence(const std::string &nodeName) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasHardEvidence(NodeId id) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasHardEvidence(const std::string &nodeName) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasSoftEvidence(NodeId id) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| hasSoftEvidence(const std::string &nodeName) const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| history() const | gum::ApproximationScheme | virtual |
| IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| initApproximationScheme() | gum::ApproximationScheme | |
| isContextualized | gum::SamplingInference< GUM_SCALAR > | protected |
| isDone() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| isEnabledEpsilon() const | gum::ApproximationScheme | virtual |
| isEnabledMaxIter() const | gum::ApproximationScheme | virtual |
| isEnabledMaxTime() const | gum::ApproximationScheme | virtual |
| isEnabledMinEpsilonRate() const | gum::ApproximationScheme | virtual |
| isInferenceDone() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| isInferenceOutdatedBNPotentials() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| isInferenceOutdatedBNStructure() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| isInferenceReady() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| isSetEstimator | gum::SamplingInference< GUM_SCALAR > | protected |
| isTarget(NodeId node) const final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| isTarget(const std::string &nodeName) const final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| makeInference() final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| MarginalTargetedInference(const IBayesNet< GUM_SCALAR > *bn) | gum::MarginalTargetedInference< GUM_SCALAR > | explicit |
| maxIter() const | gum::ApproximationScheme | virtual |
| maxTime() const | gum::ApproximationScheme | virtual |
| messageApproximationScheme() const | gum::IApproximationSchemeConfiguration | |
| minEpsilonRate() const | gum::ApproximationScheme | virtual |
| nbrEvidence() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| nbrHardEvidence() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| nbrIterations() const | gum::ApproximationScheme | virtual |
| nbrSoftEvidence() const final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| nbrTargets() const noexcept final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| onProgress | gum::IApproximationSchemeConfiguration | |
| onStop | gum::IApproximationSchemeConfiguration | |
| periodSize() const | gum::ApproximationScheme | virtual |
| posterior(NodeId node) | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| posterior(const std::string &nodeName) | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| prepareInference() final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| remainingBurnIn() | gum::ApproximationScheme | |
| samplingBN() | gum::SamplingInference< GUM_SCALAR > | |
| SamplingInference(const IBayesNet< GUM_SCALAR > *bn) | gum::SamplingInference< GUM_SCALAR > | explicit |
| setBN(const IBayesNet< GUM_SCALAR > *bn) | gum::BayesNetInference< GUM_SCALAR > | virtual |
| setEpsilon(double eps) | gum::ApproximationScheme | virtual |
| setMaxIter(Size max) | gum::ApproximationScheme | virtual |
| setMaxTime(double timeout) | gum::ApproximationScheme | virtual |
| setMinEpsilonRate(double rate) | gum::ApproximationScheme | virtual |
| setPeriodSize(Size p) | gum::ApproximationScheme | virtual |
| setVerbosity(bool v) | gum::ApproximationScheme | virtual |
| softEvidenceNodes() const | gum::BayesNetInference< GUM_SCALAR > | |
| startOfPeriod() | gum::ApproximationScheme | |
| state() const noexcept final | gum::BayesNetInference< GUM_SCALAR > | virtual |
| stateApproximationScheme() const | gum::ApproximationScheme | virtual |
| StateOfInference enum name | gum::BayesNetInference< GUM_SCALAR > | |
| stopApproximationScheme() | gum::ApproximationScheme | |
| targets() const noexcept final | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| updateApproximationScheme(unsigned int incr=1) | gum::ApproximationScheme | |
| verbosity() const | gum::ApproximationScheme | virtual |
| WeightedSampling(const IBayesNet< GUM_SCALAR > *bn) | gum::WeightedSampling< GUM_SCALAR > | explicit |
| ~ApproximationScheme() | gum::ApproximationScheme | virtual |
| ~BayesNetInference() | gum::BayesNetInference< GUM_SCALAR > | virtual |
| ~IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| ~MarginalTargetedInference() | gum::MarginalTargetedInference< GUM_SCALAR > | virtual |
| ~SamplingInference() override | gum::SamplingInference< GUM_SCALAR > | |
| ~WeightedSampling() override | gum::WeightedSampling< GUM_SCALAR > | |
