Abstract Syntax Tree for Do-Calculus

The causal module computes every causal query as an Abstract Syntax Tree (AST) that represents the exact probabilistic computations needed to answer a causal query.

The AST is an internal C++ data structure built by the do-calculus identification algorithm. It is organised as a hierarchy of node types:

• Leaf nodes: joint probability $P(X,Y,\ldots)$ and posterior probability $P(X \mid Y,\ldots)$
• Binary operations: $+$, $-$, $\times$, $\div$
• Sum-out node: marginalisation over a set of variables

Accessing the AST

pyagrum.causalImpact() returns a tuple (formula, tensor, explanation) where formula is a pyagrum.CausalImpact object carrying the identified AST. From it you can:

import pyagrum as gum

bn = gum.fastBN("X->Y->Z;X->Z")
cm = gum.CausalModel(bn)

formula, tensor, explanation = gum.causalImpact(cm, on="Z", doing="X")

## Render the identified formula as a LaTeX string
print(formula.toLatex())

## Inspect the AST as a nested dict
print(formula.toDict())

## Pretty-print the AST in the terminal
formula.print_ast()

Note

The AST node classes are internal to the C++ library and are not directly exposed in the Python API. Use pyagrum.causalImpact() to obtain and inspect a causal formula.

SEE ALSO

Causal computation in pyAgrum : pyagrum.causalImpact() and pyagrum.CausalImpact — the entry point for obtaining an AST.