def test_dfe_parameters():
dag = DAG.from_modelstring('[A]')
dag.vs['levels'] = [["A", "B"] for v in dag.vs]
data = pd.DataFrame({'A': [0, 0]})
dag.estimate_parameters(data,
method="dfe",
method_args={
"iterations": 1,
"learning_rate": 0.1
})
assert np.array_equal(dag.vs[0]['CPD'].cumsum_array, np.array([0.55, 1]))
def test_bif_parser():
bif_path = (Path(__file__).parent.parent / 'baynet' / 'utils' /
'bif_library' / 'earthquake.bif').resolve()
dag = dag_from_bif(bif_path)
earthquake_dag = DAG.from_modelstring(
"[Alarm|Burglary:Earthquake][Burglary][Earthquake][JohnCalls|Alarm][MaryCalls|Alarm]"
)
assert dag.nodes == earthquake_dag.nodes
assert dag.edges == earthquake_dag.edges
dag.sample(10)
with pytest.raises(ValueError):
dag = dag_from_bif("foo")
with pytest.raises(ValueError):
dag = dag_from_bif(Path("foo"))
def partial_dag() -> DAG:
return DAG.from_modelstring("[A][B|C:D][C][D]")
def reversed_dag() -> DAG:
return DAG.from_modelstring(REVERSED_MODELSTRING)
def test_dag() -> DAG:
return DAG.from_modelstring(TEST_MODELSTRING)