Causal Formula¶
CausalFormula is the class that represents a causal query in a causal model. Mainly it consits in
 a reference to the CausalModel
 Three sets of variables name that represent the 3 sets of variable in the query P(set1  doing(set2),knowing(set3)).
 the AST for compute the query.

class
pyAgrum.causal.
CausalFormula
(cm: 'CausalModel', root: ASTtree, on: Union(str, NameSet), doing: Union(str, NameSet), knowing: Optional[NameSet] = None)¶ Represents a causal query in a causal model. The query is encoded as an CausalFormula that can be evaluated in the causal model : $P(onknowing,overhook (doing))$
Parameters:  cm – the causal model
 root – the syntax tree as the root ASTtree
 on – the variable or the set of variables of interest
 doing – the intervention variables
:param knowing : the observation variables

cm
¶ return: the causal model

copy
() → CausalFormula¶ Copy theAST. Note that the causal model is just referenced. The tree is copied.
Returns: the new CausalFormula

eval
() → pyAgrum.pyAgrum.Potential¶ Compute the Potential from the CausalFormula over vars using cond as value for others variables
Parameters: bn – the BN where to infer Returns:

latexQuery
(values: Optional[Dict[str, str]] = None) → str¶ Returns a string representing the query compiled by this Formula. If values, the query is annotated with the values in the dictionary.
Parameters: values – the values to add in the query representation Returns: the string representing the causal query for this CausalFormula

root
¶ return: ASTtree root of the CausalFormula tree

toLatex
() → str¶ Returns: a LaTeX representation of the CausalFormula
Causal Inference¶
Obtaining and evaluating a CausalFormula is done using one these functions :

pyAgrum.causal.
causalImpact
(cm: pyAgrum.causal._CausalModel.CausalModel, on: Union[str, Set[str]], doing: Union[str, Set[str]], knowing: Optional[Set[str]] = None, values: Optional[Dict[str, int]] = None) → Tuple[pyAgrum.causal._CausalFormula.CausalFormula, pyAgrum.pyAgrum.Potential, str]¶ Determines the causal impact of interventions.
Determines the causal impact of the interventions specified in
doing
on the single or list of variableson
knowing the states of the variables inknowing
(optional). These last parameters is dictionary <variable name>:<value>. The causal impact is determined in the causal DAGcm
. This function returns a triplet with a latex format formula used to compute the causal impact, a potential representing the probability distribution ofon
given the interventions and observations as parameters, and an explanation of the method allowing the identification. If there is no impact, the joint probability ofon
is simply returned. If the impact is not identifiable the formula and the adjustment will beNone
but an explanation is still given.Parameters:  cm – causal model
 on – variable name or variable names set
 doing – variable name or variable names set
 knowing – variable names set
 values – Dictionary
Returns: the CausalFormula, the computation, the explanation

pyAgrum.causal.
doCalculusWithObservation
(cm: pyAgrum.causal._CausalModel.CausalModel, on: str, doing: Set[str], knowing: Optional[Set[str]] = None) → pyAgrum.causal._CausalFormula.CausalFormula¶ Compute the CausalFormula for an impact analysis given the causal model, the observed variables and the variable on which there will be intervention.
Parameters:  on – the variables of interest
 cm – the causal model
 doing – the interventions
 knowing – the observations
Returns: the CausalFormula for computing this causal impact

pyAgrum.causal.
identifyingIntervention
(cm: pyAgrum.causal._CausalModel.CausalModel, Y: Set[str], X: Set[str], P: pyAgrum.causal._doAST.ASTtree = None) → pyAgrum.causal._doAST.ASTtree¶ Following Shpitser, Ilya and Judea Pearl. ‘Identification of Conditional Interventional Distributions.’ UAI2006 and ‘Complete Identification Methods for the Causal Hierarchy’ JMLR 2008
Parameters:  cm – the causal model
 Y – The variables of interest (named following the paper)
 X – The variable of intervention (named following the paper)
 P – The ASTtree representing the calculus in ruction
Returns: the ASTtree representing the calculus