def test_empty_isomorphic(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(g_a, g_b, id_order=id_order))
def test_from_nodes_and_edges(self):
"""Test from_nodes_edges."""
graph = PyGraph(multigraph=False)
graph.add_nodes_from(range(6))
weighted_edge_list = [
(0, 1, 1.0 + 1.0j),
(0, 2, -1.0),
(2, 3, 2.0),
(4, 2, -1.0),
(4, 4, 3.0),
(2, 5, -1.0),
]
graph.add_edges_from(weighted_edge_list)
lattice = Lattice(graph)
target_num_nodes = 6
target_weighted_edge_list = [
(2, 5, -1.0),
(4, 4, 3),
(4, 2, -1.0),
(2, 3, 2.0),
(0, 2, -1.0),
(0, 1, 1.0 + 1.0j),
]
target_lattice = Lattice.from_nodes_and_edges(
target_num_nodes, target_weighted_edge_list)
self.assertTrue(
is_isomorphic(lattice.graph,
target_lattice.graph,
edge_matcher=lambda x, y: x == y))
def test_from_parameters(self):
"""Test from_parameters."""
coupling_matrix = np.array([[1.0, 1.0 + 1.0j, 2.0 - 2.0j],
[1.0 - 1.0j, 0.0, 0.0],
[2.0 + 2.0j, 0.0, 1.0]])
ism = cast(IsingModel, IsingModel.from_parameters(coupling_matrix))
with self.subTest("Check the graph."):
target_graph = PyGraph(multigraph=False)
target_graph.add_nodes_from(range(3))
target_weight = [(0, 0, 1.0), (0, 1, 1.0 + 1.0j),
(0, 2, 2.0 - 2.0j), (2, 2, 1.0)]
target_graph.add_edges_from(target_weight)
self.assertTrue(
is_isomorphic(ism.lattice.graph,
target_graph,
edge_matcher=lambda x, y: x == y))
with self.subTest("Check the coupling matrix."):
assert_array_equal(ism.coupling_matrix(), coupling_matrix)
with self.subTest("Check the second q op representation."):
coupling = [
("Z_0 Z_1", 1.0 + 1.0j),
("Z_0 Z_2", 2.0 - 2.0j),
("X_0", 1.0),
("X_2", 1.0),
]
ham = coupling
self.assertSetEqual(set(ham), set(ism.second_q_ops().to_list()))
def test_empty_isomorphic(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(dag_a, dag_b, id_order=id_order))
def test_isomorphic_parallel_edges_with_edge_matcher(self):
graph = retworkx.PyGraph()
graph.extend_from_weighted_edge_list([(0, 1, "a"), (0, 1, "b"),
(1, 2, "c")])
self.assertTrue(
retworkx.is_isomorphic(graph,
graph,
edge_matcher=lambda x, y: x == y))
def test_digraph_non_isomorphic_rule_ins_incoming(self):
graph = retworkx.PyDiGraph()
graph.add_nodes_from([0, 1, 2, 3])
graph.add_edges_from_no_data([(1, 0), (2, 0), (2, 1)])
second_graph = retworkx.PyDiGraph()
second_graph.add_nodes_from([0, 1, 2, 3])
second_graph.add_edges_from_no_data([(1, 0), (2, 0), (3, 1)])
self.assertFalse(
retworkx.is_isomorphic(graph, second_graph, id_order=True))
def test_empty_isomorphic_compare_nodes(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(g_a,
g_b,
lambda x, y: x == y,
id_order=id_order))
def test_isomorphic_node_count_not_equal(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(['a_1', 'a_2', 'a_3'])
g_a.add_edges_from([(nodes[0], nodes[1], 'a_1')])
nodes = g_b.add_nodes_from(['a_0', 'a_1'])
g_b.add_edges_from([(nodes[0], nodes[1], 'a_1')])
g_b.remove_node(nodes[0])
self.assertFalse(retworkx.is_isomorphic(g_a, g_b))
def test_uniform_parameters(self):
"""Test uniform_parameters."""
graph = PyGraph(multigraph=False)
graph.add_nodes_from(range(3))
weighted_edge_list = [
(0, 1, 1.0 + 1.0j),
(0, 2, -1.0),
(1, 1, 2.0),
]
graph.add_edges_from(weighted_edge_list)
lattice = Lattice(graph)
uniform_ism = cast(
IsingModel,
IsingModel.uniform_parameters(
lattice,
uniform_interaction=1.0 + 1.0j,
uniform_onsite_potential=0.0,
),
)
with self.subTest("Check the graph."):
target_graph = PyGraph(multigraph=False)
target_graph.add_nodes_from(range(3))
target_weight = [
(0, 1, 1.0 + 1.0j),
(0, 2, 1.0 + 1.0j),
(0, 0, 0.0),
(1, 1, 0.0),
(2, 2, 0.0),
]
target_graph.add_edges_from(target_weight)
self.assertTrue(
is_isomorphic(uniform_ism.lattice.graph,
target_graph,
edge_matcher=lambda x, y: x == y))
with self.subTest("Check the coupling matrix."):
coupling_matrix = uniform_ism.coupling_matrix()
target_matrix = np.array([[0.0, 1.0 + 1.0j, 1.0 + 1.0j],
[1.0 - 1.0j, 0.0, 0.0],
[1.0 - 1.0j, 0.0, 0.0]])
assert_array_equal(coupling_matrix, target_matrix)
with self.subTest("Check the second q op representation."):
coupling = [
("Z_0 Z_1", 1.0 + 1.0j),
("Z_0 Z_2", 1.0 + 1.0j),
("X_0", 0.0),
("X_1", 0.0),
("X_2", 0.0),
]
ham = coupling
self.assertSetEqual(set(ham),
set(uniform_ism.second_q_ops().to_list()))
def test_digraph_non_isomorphic_edge_mismatch_self_loop(self):
graph = retworkx.PyDiGraph()
graph.add_nodes_from([0])
graph.add_edges_from([(0, 0, "a")])
second_graph = retworkx.PyDiGraph()
second_graph.add_nodes_from([0])
second_graph.add_edges_from([(0, 0, "b")])
self.assertFalse(
retworkx.is_isomorphic(graph,
second_graph,
edge_matcher=lambda x, y: x == y))
def test_default_weight(self):
weightless_graph = retworkx.PyGraph()
weightless_graph.extend_from_edge_list([
(0, 1), (0, 2), (0, 3), (0, 4), (1, 5), (2, 6), (3, 7), (4, 8)
]) # MST of the graph is itself
mst_graph_default_weight = retworkx.minimum_spanning_tree(
weightless_graph)
mst_graph_weight_2 = retworkx.minimum_spanning_tree(weightless_graph,
default_weight=2.0)
self.assertTrue(
retworkx.is_isomorphic(
weightless_graph,
mst_graph_default_weight,
))
self.assertTrue(
retworkx.is_isomorphic(
weightless_graph,
mst_graph_weight_2,
))
def test_isomorphic_mismatch_node_data_undirected(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(['a_1', 'a_2', 'a_3'])
g_a.add_edges_from([(nodes[0], nodes[1], 'a_1'),
(nodes[1], nodes[2], 'a_2')])
nodes = g_b.add_nodes_from(['b_1', 'b_2', 'b_3'])
g_b.add_edges_from([(nodes[0], nodes[1], 'b_1'),
(nodes[1], nodes[2], 'b_2')])
self.assertTrue(retworkx.is_isomorphic(g_a, g_b))
def test_isomorphic_compare_nodes_identical_undirected(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(['a_1', 'a_2', 'a_3'])
g_a.add_edges_from([(nodes[0], nodes[1], 'a_1'),
(nodes[1], nodes[2], 'a_2')])
nodes = g_b.add_nodes_from(['a_1', 'a_2', 'a_3'])
g_b.add_edges_from([(nodes[0], nodes[1], 'a_1'),
(nodes[1], nodes[2], 'a_2')])
self.assertTrue(retworkx.is_isomorphic(g_a, g_b, lambda x, y: x == y))
def test_isomorphic_mismatch_node_data(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
node_a = dag_a.add_node('a_1')
dag_a.add_child(node_a, 'a_2', 'a_1')
dag_a.add_child(node_a, 'a_3', 'a_2')
node_b = dag_b.add_node('b_1')
dag_b.add_child(node_b, 'b_2', 'b_1')
dag_b.add_child(node_b, 'b_3', 'b_2')
self.assertTrue(retworkx.is_isomorphic(dag_a, dag_b))
def test_isomorphic_identical(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
node_a = dag_a.add_node('a_1')
dag_a.add_child(node_a, 'a_2', 'a_1')
dag_a.add_child(node_a, 'a_3', 'a_2')
node_b = dag_b.add_node('a_1')
dag_b.add_child(node_b, 'a_2', 'a_1')
dag_b.add_child(node_b, 'a_3', 'a_2')
self.assertTrue(retworkx.is_isomorphic(dag_a, dag_b))
def test_isomorphic_compare_nodes_mismatch_node_data(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
node_a = dag_a.add_node('a_1')
dag_a.add_child(node_a, 'a_2', 'a_1')
dag_a.add_child(node_a, 'a_3', 'a_2')
node_b = dag_b.add_node('b_1')
dag_b.add_child(node_b, 'b_2', 'b_1')
dag_b.add_child(node_b, 'b_3', 'b_2')
self.assertFalse(
retworkx.is_isomorphic(dag_a, dag_b, lambda x, y: x == y))
def test_multigraph(self):
graph = retworkx.PyGraph(multigraph=True)
graph.extend_from_edge_list([(0, 0), (0, 1), (1, 1), (2, 2), (1, 0)])
expected_graph = retworkx.PyGraph(multigraph=True)
expected_graph.extend_from_edge_list([(0, 2), (1, 2)])
complement_graph = retworkx.complement(graph)
self.assertTrue(
retworkx.is_isomorphic(
expected_graph,
complement_graph,
))
def test_init(self):
"""Test init."""
graph = PyGraph(multigraph=False)
graph.add_nodes_from(range(6))
weighted_edge_list = [
(0, 1, 1.0 + 1.0j),
(0, 2, -1.0),
(2, 3, 2.0),
(2, 4, -1.0),
(4, 4, 3.0),
(2, 5, -1.0),
]
graph.add_edges_from(weighted_edge_list)
lattice = Lattice(graph)
with self.subTest("Check the type of lattice."):
self.assertIsInstance(lattice, Lattice)
with self.subTest("Check graph."):
target_graph = PyGraph(multigraph=False)
target_graph.add_nodes_from(range(6))
target_weighted_edge_list = [
(4, 4, 3.0),
(0, 1, 1 + 1j),
(2, 3, 2.0),
(2, 4, -1.0),
(2, 5, -1.0),
(0, 2, -1),
]
target_graph.add_edges_from(target_weighted_edge_list)
self.assertTrue(
is_isomorphic(lattice.graph,
target_graph,
edge_matcher=lambda x, y: x == y))
with self.subTest("Check the number of nodes."):
self.assertEqual(lattice.num_nodes, 6)
with self.subTest("Check the set of nodes."):
self.assertSetEqual(set(lattice.node_indexes), set(range(6)))
with self.subTest("Check the set of weights."):
target_set = {
(0, 1, 1 + 1j),
(4, 4, 3),
(2, 5, -1.0),
(0, 2, -1.0),
(2, 3, 2.0),
(2, 4, -1.0),
}
self.assertEqual(set(lattice.weighted_edge_list), target_set)
def test_init(self):
"""Test init."""
graph = PyGraph(multigraph=False)
graph.add_nodes_from(range(3))
weighted_edge_list = [
(0, 1, 1.0 + 1.0j),
(0, 2, -1.0),
(1, 1, 2.0),
]
graph.add_edges_from(weighted_edge_list)
lattice = Lattice(graph)
fhm = FermiHubbardModel(lattice, onsite_interaction=10.0)
with self.subTest("Check the graph."):
self.assertTrue(
is_isomorphic(fhm.lattice.graph,
lattice.graph,
edge_matcher=lambda x, y: x == y))
with self.subTest("Check the hopping matrix"):
hopping_matrix = fhm.hopping_matrix()
target_matrix = np.array([[0.0, 1.0 + 1.0j, -1.0],
[1.0 - 1.0j, 2.0, 0.0], [-1.0, 0.0,
0.0]])
assert_array_equal(hopping_matrix, target_matrix)
with self.subTest("Check the second q op representation."):
hopping = [
("+_0 -_2", 1.0 + 1.0j),
("-_0 +_2", -(1.0 - 1.0j)),
("+_0 -_4", -1.0),
("-_0 +_4", 1.0),
("+_1 -_3", 1.0 + 1.0j),
("-_1 +_3", -(1.0 - 1.0j)),
("+_1 -_5", -1.0),
("-_1 +_5", 1.0),
("+_2 -_2", 2.0),
("+_3 -_3", 2.0),
]
interaction = [
("+_0 -_0 +_1 -_1", 10.0),
("+_2 -_2 +_3 -_3", 10.0),
("+_4 -_4 +_5 -_5", 10.0),
]
ham = hopping + interaction
self.assertSetEqual(
set(ham),
set(fhm.second_q_ops(display_format="sparse").to_list()))
def test_isomorphic_node_count_not_equal(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3"])
g_a.add_edges_from([(nodes[0], nodes[1], "a_1")])
nodes = g_b.add_nodes_from(["a_0", "a_1"])
g_b.add_edges_from([(nodes[0], nodes[1], "a_1")])
g_b.remove_node(nodes[0])
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertFalse(
retworkx.is_isomorphic(g_a, g_b, id_order=id_order))
def test_from_parameters(self):
"""Test from_parameters."""
hopping_matrix = np.array([[1.0, 1.0 + 1.0j, 2.0 + 2.0j],
[1.0 - 1.0j, 0.0, 0.0],
[2.0 - 2.0j, 0.0, 1.0]])
onsite_interaction = 10.0
fhm = FermiHubbardModel.from_parameters(hopping_matrix,
onsite_interaction)
with self.subTest("Check the graph."):
target_graph = PyGraph(multigraph=False)
target_graph.add_nodes_from(range(3))
target_weight = [(0, 0, 1.0), (0, 1, 1.0 + 1.0j),
(0, 2, 2.0 + 2.0j), (2, 2, 1.0)]
target_graph.add_edges_from(target_weight)
self.assertTrue(
is_isomorphic(fhm.lattice.graph,
target_graph,
edge_matcher=lambda x, y: x == y))
with self.subTest("Check the hopping matrix."):
assert_array_equal(fhm.hopping_matrix(), hopping_matrix)
with self.subTest("Check the second q op representation."):
hopping = [
("+_0 -_2", 1.0 + 1.0j),
("-_0 +_2", -(1.0 - 1.0j)),
("+_0 -_4", 2.0 + 2.0j),
("-_0 +_4", -(2.0 - 2.0j)),
("+_1 -_3", 1.0 + 1.0j),
("-_1 +_3", -(1.0 - 1.0j)),
("+_1 -_5", 2.0 + 2.0j),
("-_1 +_5", -(2.0 - 2.0j)),
("+_0 -_0", 1.0),
("+_1 -_1", 1.0),
("+_4 -_4", 1.0),
("+_5 -_5", 1.0),
]
interaction = [
("+_0 -_0 +_1 -_1", onsite_interaction),
("+_2 -_2 +_3 -_3", onsite_interaction),
("+_4 -_4 +_5 -_5", onsite_interaction),
]
ham = hopping + interaction
self.assertSetEqual(
set(ham),
set(fhm.second_q_ops(display_format="sparse").to_list()))
def test_isomorphic_mismatch_node_data(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
node_a = dag_a.add_node("a_1")
dag_a.add_child(node_a, "a_2", "a_1")
dag_a.add_child(node_a, "a_3", "a_2")
node_b = dag_b.add_node("b_1")
dag_b.add_child(node_b, "b_2", "b_1")
dag_b.add_child(node_b, "b_3", "b_2")
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(dag_a, dag_b, id_order=id_order))
def test_isomorphic_removed_nodes_in_second_graph(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(['a_1', 'a_2', 'a_3'])
g_a.add_edges_from([(nodes[0], nodes[1], 'a_1'),
(nodes[1], nodes[2], 'a_2')])
nodes = g_b.add_nodes_from(['a_0', 'a_2', 'a_1', 'a_3'])
g_b.add_edges_from([(nodes[0], nodes[1], 'e_01'),
(nodes[0], nodes[3], 'e_03'),
(nodes[2], nodes[1], 'a_1'),
(nodes[1], nodes[3], 'a_2')])
g_b.remove_node(nodes[0])
self.assertTrue(retworkx.is_isomorphic(g_a, g_b, lambda x, y: x == y))
def test_isomorphic_compare_edges_identical(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
node_a = dag_a.add_node('a_1')
dag_a.add_child(node_a, 'a_2', 'a_1')
dag_a.add_child(node_a, 'a_3', 'a_2')
node_b = dag_b.add_node('a_1')
dag_b.add_child(node_b, 'a_2', 'a_1')
dag_b.add_child(node_b, 'a_3', 'a_2')
self.assertTrue(
retworkx.is_isomorphic(dag_a,
dag_b,
edge_matcher=lambda x, y: x == y))
def test_union_merge_all(self):
dag_a = retworkx.PyDiGraph()
dag_b = retworkx.PyDiGraph()
node_a = dag_a.add_node("a_1")
dag_a.add_child(node_a, "a_2", "e_1")
dag_a.add_child(node_a, "a_3", "e_2")
node_b = dag_b.add_node("a_1")
dag_b.add_child(node_b, "a_2", "e_1")
dag_b.add_child(node_b, "a_3", "e_2")
dag_c = retworkx.digraph_union(dag_a, dag_b, True, True)
self.assertTrue(retworkx.is_isomorphic(dag_a, dag_c))
def test_isomorphic_mismatch_node_data(self):
g_a = retworkx.PyGraph()
g_b = retworkx.PyGraph()
nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3"])
g_a.add_edges_from([(nodes[0], nodes[1], "a_1"),
(nodes[1], nodes[2], "a_2")])
nodes = g_b.add_nodes_from(["b_1", "b_2", "b_3"])
g_b.add_edges_from([(nodes[0], nodes[1], "b_1"),
(nodes[1], nodes[2], "b_2")])
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(g_a, g_b, id_order=id_order))
def test_empty(self):
N = 5
graph = retworkx.PyGraph()
graph.add_nodes_from([i for i in range(N)])
expected_graph = retworkx.PyGraph()
expected_graph.extend_from_edge_list([(i, j) for i in range(N)
for j in range(N) if i < j])
complement_graph = retworkx.complement(graph)
self.assertTrue(
retworkx.is_isomorphic(
expected_graph,
complement_graph,
))
def test_from_networkx(self):
"""Test initialization from a networkx graph."""
graph = nx.Graph()
graph.add_nodes_from(range(5))
graph.add_edges_from([(i, i + 1) for i in range(4)])
lattice = Lattice(graph)
target_graph = PyGraph()
target_graph.add_nodes_from(range(5))
target_graph.add_edges_from([(i, i + 1, 1) for i in range(4)])
self.assertTrue(
is_isomorphic(lattice.graph,
target_graph,
edge_matcher=lambda x, y: x == y))
def test_graph(self):
"""Test if analytically derived SyndromeGraph is correct."""
error = (
"Error: The analytical SyndromeGraph does not coincide " +
"with the brute force SyndromeGraph in d=7, T=2 RepetitionCode.")
code = RepetitionCode(7, 2)
graph_new = GraphDecoder(code, brute=False).S
graph_old = GraphDecoder(code, brute=True).S
test_passed = True
for node in graph_new.nodes():
test_passed &= node in graph_old.nodes()
for node in graph_old.nodes():
test_passed &= node in graph_new.nodes()
test_passed &= rx.is_isomorphic(graph_new, graph_old,
lambda x, y: x == y)
self.assertTrue(test_passed, error)
def test_isomorphic_compare_nodes_with_removals_deepcopy(self):
dag_a = retworkx.PyDAG()
dag_b = retworkx.PyDAG()
qr_0_in = dag_a.add_node("qr[0]")
qr_1_in = dag_a.add_node("qr[1]")
cr_0_in = dag_a.add_node("cr[0]")
qr_0_out = dag_a.add_node("qr[0]")
qr_1_out = dag_a.add_node("qr[1]")
cr_0_out = dag_a.add_node("qr[0]")
cu1 = dag_a.add_child(qr_0_in, "cu1", "qr[0]")
dag_a.add_edge(qr_1_in, cu1, "qr[1]")
measure_0 = dag_a.add_child(cr_0_in, "measure", "cr[0]")
dag_a.add_edge(cu1, measure_0, "qr[0]")
measure_1 = dag_a.add_child(cu1, "measure", "qr[1]")
dag_a.add_edge(measure_0, measure_1, "cr[0]")
dag_a.add_edge(measure_1, qr_1_out, "qr[1]")
dag_a.add_edge(measure_1, cr_0_out, "cr[0]")
dag_a.add_edge(measure_0, qr_0_out, "qr[0]")
dag_a.remove_node(cu1)
dag_a.add_edge(qr_0_in, measure_0, "qr[0]")
dag_a.add_edge(qr_1_in, measure_1, "qr[1]")
qr_0_in = dag_b.add_node("qr[0]")
qr_1_in = dag_b.add_node("qr[1]")
cr_0_in = dag_b.add_node("cr[0]")
qr_0_out = dag_b.add_node("qr[0]")
qr_1_out = dag_b.add_node("qr[1]")
cr_0_out = dag_b.add_node("qr[0]")
measure_0 = dag_b.add_child(cr_0_in, "measure", "cr[0]")
dag_b.add_edge(qr_0_in, measure_0, "qr[0]")
measure_1 = dag_b.add_child(qr_1_in, "measure", "qr[1]")
dag_b.add_edge(measure_1, qr_1_out, "qr[1]")
dag_b.add_edge(measure_1, cr_0_out, "cr[0]")
dag_b.add_edge(measure_0, measure_1, "cr[0]")
dag_b.add_edge(measure_0, qr_0_out, "qr[0]")
for id_order in [False, True]:
with self.subTest(id_order=id_order):
self.assertTrue(
retworkx.is_isomorphic(
copy.deepcopy(dag_a),
copy.deepcopy(dag_b),
lambda x, y: x == y,
id_order=id_order,
)
)