tbnpy package¶ Submodules¶ tbnpy.variable Overview Quick start Public API Variable Variable Properties Composite-state helpers Hidden helpers (intentionally omitted) Custom probability models When to use CPT vs custom models Minimal interface prob.sample() prob.log_prob() Device and performance notes Examples in the ABCDE tutorial tbnpy.cpt Overview Quick start Public API Cpt Cpt Core data structures Evidence Sampling Log-probability evaluation Advanced / internal helpers Cpt._get_C_binary() Cpt.expand_and_check_compatibility() Cpt.expand_and_check_compatibility_all() Utility functions get_names() tbnpy.inference Overview Glossary Quick start Public API Topological utilities get_ancestor_order() Forward sampling without evidence sample() Forward sampling with evidence sample_evidence_v0() sample_evidence() tbnpy.adaptiveMH Overview Glossary Utility functions Variable type helpers is_discrete() is_continuous() num_categories() Factor construction utilities build_Cs_3d() factor_logp_2d() build_factors_by_var() Proposal kernels Discrete proposals propose_discrete_adaptive() Continuous proposals propose_continuous_rw_gaussian() Adaptation configuration AdaptConfig HybridAdaptiveMH HybridAdaptiveMH Initialisation HybridAdaptiveMH.init_state_from_forward_samples() HybridAdaptiveMH.init_state_random() Core MCMC update HybridAdaptiveMH.mh_update_block() Running the sampler HybridAdaptiveMH.run() Module contents¶