def birnbaum_importance(sg: SystemGraph, p, bdd_with_root=None, select=None):
b_imps = {}
if select is not None:
for i in select:
p[i] = 1.0
risk_top = risk_by_bdd(sg, p, bdd_with_root)
for i in select:
p[i] = 0.0
risk_bottom = risk_by_bdd(sg, p, bdd_with_root)
b_imps["select"] = risk_top - risk_bottom
return b_imps
for i in sg.nodes:
saved = p[i]
p[i] = 1.0
risk_top = risk_by_bdd(sg, p, bdd_with_root)
p[i] = 0.0
risk_bottom = risk_by_bdd(sg, p, bdd_with_root)
b_imps[i] = risk_top - risk_bottom
p[i] = saved # restore to initial state
del b_imps["indicator"]
return b_imps
def test_risk_by_bdd_minimal(minimal: SystemGraph):
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 0,
"x2": 0,
"x3": 0
}) == 0)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 0,
"x2": 0,
"x3": 1
}) == 1)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 0,
"x2": 1,
"x3": 0
}) == 0)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 1,
"x2": 0,
"x3": 0
}) == 0)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 1,
"x2": 1,
"x3": 0
}) == 1)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 1,
"x2": 1,
"x3": 1
}) == 1)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 0,
"x2": 0,
"x3": 0
}) == 0)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": .5,
"x2": .5,
"x3": 0
}) == .25)
assert (risk_by_bdd(minimal, {
"indicator": 0,
"x1": 0,
"x2": 0,
"x3": .25
}) == .25)
def test_e2e_supplier_choice_solve_bad_supplier_risk(
full_with_supplier_choices: SystemGraph,
full_with_supplier_choices_data):
bad = full_with_supplier_choices_data["edges"][0]
bad["risk"] = 0.99
before = risk_by_bdd(
full_with_supplier_choices,
provide_p_direct_from_data(full_with_supplier_choices,
full_with_supplier_choices_data))
prob = SupplierChoiceProblem(full_with_supplier_choices,
full_with_supplier_choices_data)
results = prob.solve({"alpha": 0.01, "budget": 500})
updated = full_with_supplier_choices.with_suppliers(results[0])
assert Edge(src=bad["src"], dst=bad["dst"]) not in updated.edges
after = risk_by_bdd(
updated,
provide_p_direct_from_data(updated, full_with_supplier_choices_data))
assert before > after
def get_risk(sg: SystemGraph, data: Dict, prefs=None) -> Dict[str, float]:
bdd_with_root = sg.get_bdd_with_root()
validate_data(sg, data)
p = provide_p_direct_from_data(sg, data)
risk = risk_by_bdd(sg, p, bdd_with_root=bdd_with_root)
return {"system": risk}
def test_risk_by_bdd_diamond(diamond: SystemGraph):
assert approx(
risk_by_bdd(diamond, provide_p_unknown_data(diamond)) == 0.625)
def test_risk_by_bdd_canonical(canonical: SystemGraph):
assert approx(
risk_by_bdd(canonical, provide_p_unknown_data(canonical)) ==
0.9748495630919933)