Abstract Syntax Tree for Do-Calculus

The pyCausal package compute every causal query into an Abstract Syntax Tree (CausalFormula) that represents the exact computations to be done in order to answer to the probabilistic causal query.

The different types of node in an CausalFormula are presented below and are organized as a hierarchy of classes from pyAgrum.causal.ASTtree.

Inheritance diagram of pyAgrum.causal.ASTplus, pyAgrum.causal.ASTminus, pyAgrum.causal.ASTdiv, pyAgrum.causal.ASTmult, pyAgrum.causal.ASTsum, pyAgrum.causal.ASTjointProba, pyAgrum.causal.ASTposteriorProba

Internal node structure

class pyAgrum.causal.ASTtree(typ, verbose=False)

Represents a generic node for the CausalFormula. The type of the node will be registered in a string.

Parameters

typ (str) – the type of the node (will be specified in concrete children classes.
verbose (bool) – if True, add some messages

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

class pyAgrum.causal.ASTBinaryOp(typ, op1, op2)

Represents a generic binary node for the CausalFormula. The op1 and op2 are the two operands of the class.

Parameters

typ (str) – the type of the node (will be specified in concrete children classes
op1 (ASTtree) – left operand
op2 (ASTtree) – right operand

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property op1: ASTtree

Returns: the left operand
Return type: ASTtree

property op2: ASTtree

Returns: the right operand
Return type: ASTtree

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

Basic Binary Operations

class pyAgrum.causal.ASTplus(op1, op2)

Represents the sum of 2 causal.ASTtree

Parameters

op1 (ASTtree) – left operand
op2 (ASTtree) – right operand

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property op1: ASTtree

Returns: the left operand
Return type: ASTtree

property op2: ASTtree

Returns: the right operand
Return type: ASTtree

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

class pyAgrum.causal.ASTminus(op1, op2)

Represents the substraction of 2 causal.ASTtree

Parameters

op1 (ASTtree) – left operand
op2 (ASTtree) – right operand

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property op1: ASTtree

Returns: the left operand
Return type: ASTtree

property op2: ASTtree

Returns: the right operand
Return type: ASTtree

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

class pyAgrum.causal.ASTdiv(op1, op2)

Represents the division of 2 causal.ASTtree

Parameters

op1 (ASTtree) – left operand
op2 (ASTtree) – right operand

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property op1: ASTtree

Returns: the left operand
Return type: ASTtree

property op2: ASTtree

Returns: the right operand
Return type: ASTtree

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

class pyAgrum.causal.ASTmult(op1, op2)

Represents the multiplication of 2 causal.ASTtree

Parameters

op1 (ASTtree) – left operand
op2 (ASTtree) – right operand

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property op1: ASTtree

Returns: the left operand
Return type: ASTtree

property op2: ASTtree

Returns: the right operand
Return type: ASTtree

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

Complex operations

class pyAgrum.causal.ASTsum(var, term)

Represents a sum over a variable of a causal.ASTtree.

Parameters

var (str) – name of the variable on which to sum
term (ASTtree) – the tree to be evaluated

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

property term: ASTtree

Returns: the term to sum
Return type: ASTtree

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

class pyAgrum.causal.ASTjointProba(varNames)

Represent a joint probability in the base observational part of the causal.CausalModel

Parameters: varNames (Set[str]) – a set of variable names

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

property varNames: Set[str]

Returns: the set of names of var
Return type: Set[str]

class pyAgrum.causal.ASTposteriorProba(bn, varset, knw)

Represent a conditional probability \(P_{bn}(vars|knw)\) that can be computed by an inference in a BN.

Parameters

bn (pyAgrum.BayesNet) – the pyAgrum:pyAgrum.BayesNet
varset (Set[str]) – a set of variable names (in the BN) conditioned in the posterior
knw (Set[str]) – a set of variable names (in the BN) conditioning in the posterior

property bn: BayesNet

Returns: the observationnal BayesNet in \(P_{bn}(vars|knw)\)
Return type: pyAgrum.BayesNet

copy()

Copy an CausalFormula tree

Returns: the new causal tree
Return type: ASTtree

eval(contextual_bn)

Evaluation of a AST tree from inside a BN

Parameters: contextual_bn (pyAgrum.BayesNet) – the observational Bayesian network in which will be done the computations
Returns: the resulting Potential
Return type: pyAgrum.Potential

fastToLatex(nameOccur)

Internal virtual function to create a LaTeX representation of the ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property knw: Set[str]

Returns: (Conditioning) knw in \(P_{bn}(vars|knw)\)
Return type: Set[str]

protectToLatex(nameOccur)

Create a protected LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int]) – the number of occurrence for each variable
Returns: a protected version of LaTeX representation of the tree
Return type: str

toLatex(nameOccur=None)

Create a LaTeX representation of a ASTtree

Parameters: nameOccur (Dict[str,int] default=None) – the number of occurrence for each variable
Returns: LaTeX representation of the tree
Return type: str

property type: str

Returns: the type of the node
Return type: str

property vars: Set[str]

Returns: (Conditioned) vars in \(P_{bn}(vars|knw)\)
Return type: Set[str]