This pyAgrum's notebook is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
import pyAgrum as gum
import pyAgrum.lib.notebook as gnb
bn=gum.fastBN("A->B->C->D;A->E->D;F->B;C->H")
ie=gum.LazyPropagation(bn)
bn
Evidence Impact allows the user to analyze the effect of any variables on any other variables
ie.evidenceImpact("B",["A","H"])
Evidence impact is able to find the minimum set of variables which effectively conditions the analyzed variable
ie.evidenceImpact("E",["A","F","B","D"]) # {A,D,B} d-separates E and F
ie.evidenceImpact("E",["A","B","C","D","F"]) # {A,C,D} d-separates E and {B,F}
ie.evidenceJointImpact(["A","F"],["B","C","D","E","H"]) # {B,E} d-separates [A,F] and [C,D,H]