pyAgrum.causal documentation

Causality in pyAgrum

Causality in pyAgrum mainly consists in the ability to build a causal model, i.e. a (observational) Bayesian network and a set of latent variables and their relation with observation variables and in the abilidy to compute using do-calculus the causal impact in such a model.

Causality is a set of pure python3 scripts based on pyAgrum’s tools.

Note

As it can be seen in the figure above, pyAgrum.causal module uses a LaTeX special arrow (\(\hookrightarrow\)) to compactly represent an intervention. If you prefer the classical “do” notation, you can change this behavior by using:

gum.config[“causal”,”latex_do_prefix”]=”do(” gum.config[“causal”,”latex_do_suffix”]=”)”

Tutorial

Reference