def estimate(self):
"""
Estimates the `DAG` structure that fits best to the given data set,
according to the scoring method supplied in the constructor.
Exhaustively searches through all models. Only estimates network structure, no parametrization.
Returns
-------
model: `DAG` instance
A `DAG` with maximal score.
Examples
--------
>>> import pandas as pd
>>> import numpy as np
>>> from pgmpy.estimators import ExhaustiveSearch
>>> # create random data sample with 3 variables, where B and C are identical:
>>> data = pd.DataFrame(np.random.randint(0, 5, size=(5000, 2)), columns=list('AB'))
>>> data['C'] = data['B']
>>> est = ExhaustiveSearch(data)
>>> best_model = est.estimate()
>>> best_model
<pgmpy.base.DAG.DAG object at 0x7f695c535470>
>>> best_model.edges()
[('B', 'C')]
"""
best_dag = max(self.all_dags(), key=self.scoring_method.score)
best_model = DAG()
best_model.add_nodes_from(sorted(best_dag.nodes()))
best_model.add_edges_from(sorted(best_dag.edges()))
return best_model
class TestDoOperator(unittest.TestCase):
def setUp(self):
self.graph = DAG()
self.graph.add_edges_from([("X", "A"), ("A", "Y"), ("A", "B")])
def test_do(self):
dag_do_x = self.graph.do("A")
self.assertEqual(set(dag_do_x.nodes()), set(self.graph.nodes()))
self.assertEqual(sorted(list(dag_do_x.edges())), [("A", "B"), ("A", "Y")])
class TestDAGMoralization(unittest.TestCase):
def setUp(self):
self.graph = DAG()
self.graph.add_edges_from([("diff", "grade"), ("intel", "grade")])
def test_get_parents(self):
self.assertListEqual(sorted(self.graph.get_parents("grade")), ["diff", "intel"])
def test_moralize(self):
moral_graph = self.graph.moralize()
self.assertListEqual(
hf.recursive_sorted(moral_graph.edges()),
[["diff", "grade"], ["diff", "intel"], ["grade", "intel"]],
)
def test_get_children(self):
self.assertListEqual(sorted(self.graph.get_children("diff")), ["grade"])
def tearDown(self):
del self.graph
class TestDAGCreation(unittest.TestCase):
def setUp(self):
self.graph = DAG()
def test_class_init_without_data(self):
self.assertIsInstance(self.graph, DAG)
def test_class_init_with_data_string(self):
self.graph = DAG([("a", "b"), ("b", "c")])
self.assertListEqual(sorted(self.graph.nodes()), ["a", "b", "c"])
self.assertListEqual(
hf.recursive_sorted(self.graph.edges()), [["a", "b"], ["b", "c"]]
)
def test_add_node_string(self):
self.graph.add_node("a")
self.assertListEqual(list(self.graph.nodes()), ["a"])
def test_add_node_nonstring(self):
self.graph.add_node(1)
def test_add_nodes_from_string(self):
self.graph.add_nodes_from(["a", "b", "c", "d"])
self.assertListEqual(sorted(self.graph.nodes()), ["a", "b", "c", "d"])
def test_add_nodes_from_non_string(self):
self.graph.add_nodes_from([1, 2, 3, 4])
def test_add_node_weight(self):
self.graph.add_node("weighted_a", 0.3)
self.assertEqual(self.graph.nodes["weighted_a"]["weight"], 0.3)
def test_add_nodes_from_weight(self):
self.graph.add_nodes_from(["weighted_b", "weighted_c"], [0.5, 0.6])
self.assertEqual(self.graph.nodes["weighted_b"]["weight"], 0.5)
self.assertEqual(self.graph.nodes["weighted_c"]["weight"], 0.6)
self.graph.add_nodes_from(["e", "f"])
self.assertEqual(self.graph.nodes["e"]["weight"], None)
self.assertEqual(self.graph.nodes["f"]["weight"], None)
def test_add_edge_string(self):
self.graph.add_edge("d", "e")
self.assertListEqual(sorted(self.graph.nodes()), ["d", "e"])
self.assertListEqual(list(self.graph.edges()), [("d", "e")])
self.graph.add_nodes_from(["a", "b", "c"])
self.graph.add_edge("a", "b")
self.assertListEqual(
hf.recursive_sorted(self.graph.edges()), [["a", "b"], ["d", "e"]]
)
def test_add_edge_nonstring(self):
self.graph.add_edge(1, 2)
def test_add_edges_from_string(self):
self.graph.add_edges_from([("a", "b"), ("b", "c")])
self.assertListEqual(sorted(self.graph.nodes()), ["a", "b", "c"])
self.assertListEqual(
hf.recursive_sorted(self.graph.edges()), [["a", "b"], ["b", "c"]]
)
self.graph.add_nodes_from(["d", "e", "f"])
self.graph.add_edges_from([("d", "e"), ("e", "f")])
self.assertListEqual(sorted(self.graph.nodes()), ["a", "b", "c", "d", "e", "f"])
self.assertListEqual(
hf.recursive_sorted(self.graph.edges()),
hf.recursive_sorted([("a", "b"), ("b", "c"), ("d", "e"), ("e", "f")]),
)
def test_add_edges_from_nonstring(self):
self.graph.add_edges_from([(1, 2), (2, 3)])
def test_add_edge_weight(self):
self.graph.add_edge("a", "b", weight=0.3)
if nx.__version__.startswith("1"):
self.assertEqual(self.graph.edge["a"]["b"]["weight"], 0.3)
else:
self.assertEqual(self.graph.adj["a"]["b"]["weight"], 0.3)
def test_add_edges_from_weight(self):
self.graph.add_edges_from([("b", "c"), ("c", "d")], weights=[0.5, 0.6])
if nx.__version__.startswith("1"):
self.assertEqual(self.graph.edge["b"]["c"]["weight"], 0.5)
self.assertEqual(self.graph.edge["c"]["d"]["weight"], 0.6)
self.graph.add_edges_from([("e", "f")])
self.assertEqual(self.graph.edge["e"]["f"]["weight"], None)
else:
self.assertEqual(self.graph.adj["b"]["c"]["weight"], 0.5)
self.assertEqual(self.graph.adj["c"]["d"]["weight"], 0.6)
self.graph.add_edges_from([("e", "f")])
self.assertEqual(self.graph.adj["e"]["f"]["weight"], None)
def test_update_node_parents_bm_constructor(self):
self.graph = DAG([("a", "b"), ("b", "c")])
self.assertListEqual(list(self.graph.predecessors("a")), [])
self.assertListEqual(list(self.graph.predecessors("b")), ["a"])
self.assertListEqual(list(self.graph.predecessors("c")), ["b"])
def test_update_node_parents(self):
self.graph.add_nodes_from(["a", "b", "c"])
self.graph.add_edges_from([("a", "b"), ("b", "c")])
self.assertListEqual(list(self.graph.predecessors("a")), [])
self.assertListEqual(list(self.graph.predecessors("b")), ["a"])
self.assertListEqual(list(self.graph.predecessors("c")), ["b"])
def test_get_leaves(self):
self.graph.add_edges_from(
[("A", "B"), ("B", "C"), ("B", "D"), ("D", "E"), ("D", "F"), ("A", "G")]
)
self.assertEqual(sorted(self.graph.get_leaves()), sorted(["C", "G", "E", "F"]))
def test_get_roots(self):
self.graph.add_edges_from(
[("A", "B"), ("B", "C"), ("B", "D"), ("D", "E"), ("D", "F"), ("A", "G")]
)
self.assertEqual(["A"], self.graph.get_roots())
self.graph.add_edge("H", "G")
self.assertEqual(sorted(["A", "H"]), sorted(self.graph.get_roots()))
def test_init_with_cycle(self):
self.assertRaises(ValueError, DAG, [("a", "a")])
self.assertRaises(ValueError, DAG, [("a", "b"), ("b", "a")])
self.assertRaises(ValueError, DAG, [("a", "b"), ("b", "c"), ("c", "a")])
def tearDown(self):
del self.graph