Member gum::credal::CNLoopyPropagation< GUM_SCALAR >::saveInference (std::string_view path): Use saveMarginals() from InferenceEngine instead. This one is easier to read but harder for scripts to parse.
Member gum::credal::CredalNet< GUM_SCALAR >::_bnCopy_ (BayesNet< GUM_SCALAR > &bn_dest)
Member gum::credal::CredalNet< GUM_SCALAR >::_find_dNode_card_ (const std::vector< std::vector< std::vector< GUM_SCALAR > > > &var_cpt) const
Member gum::credal::CredalNet< GUM_SCALAR >::_H2Vlrs_ (const std::vector< std::vector< GUM_SCALAR > > &h_rep, std::vector< std::vector< GUM_SCALAR > > &v_rep) const: one should use the LrsWrapper class Computes the V-representation of a credal set, i.e. it's vertices, from it's H-representation, i.e. the hyper-plan inequalities. Uses lrs.
Member gum::credal::CredalNet< GUM_SCALAR >::_var_bits_
Member gum::credal::CredalNet< GUM_SCALAR >::intervalToCredalWithFiles (): Use intervalToCredal ( lrsWrapper with no input / output files needed ).
Member gum::credal::InferenceEngine< GUM_SCALAR >::timeSteps_
Member gum::credal::MultipleInferenceEngine< GUM_SCALAR, BNInferenceEngine >::verticesFusion_ (): Fusion of threads vertices.