def test_canonical_relabel():
for _ in range(100):
g = gen_random_connected_graph(4)
relab_g = random_relabel(g)
canon_g = canonical_relabel(g)
canon_relab_g = canonical_relabel(relab_g)
canon_edges = canonical_edge_order(canon_g.edges())
canon_relab_edges = canonical_edge_order(canon_relab_g.edges())
assert canon_edges == canon_relab_edges
def get_adjacency_matrix(graph):
""" Returns the adjacency matrix with a canonical node basis """
# Canonically orders the nodes and edges
key = sorted(graph.nodes())
edges = canonical_edge_order(graph.edges())
# Creates the adjacency matrix and exports to CSV
adj_mat = np.array([[int(tuple(sorted((u, v))) in edges) for u in key]
for v in key])
return adj_mat, key
def test_qubit_LC():
""" Tests local complementation works against abp version """
for _ in range(100):
# Creates a random NetworkX graph and it's equivalent GraphState
g = gen_random_connected_graph(15)
gs = to_GraphState(g)
# Gets the original edges
g_edges = canonical_edge_order(g.edges())
gs_edges = canonical_edge_order(gs.edgelist())
# Randomly picks a node for local complementation
lc_node = random.choice(list(g.nodes()))
# Performs local complementation on both graphs
lc_g = qubit_LC(g, lc_node, 1)
lc_gs = to_GraphState(g)
lc_gs.local_complementation(lc_node)
# Checks that their edgelists are equal
lc_g_edges = canonical_edge_order(lc_g.edges())
lc_gs_edges = canonical_edge_order(lc_gs.edgelist())
assert lc_g_edges == lc_gs_edges
# Performs a second local complementation on same node
lc_lc_g = qubit_LC(lc_g, lc_node, 1)
lc_lc_gs = to_GraphState(lc_g)
lc_lc_gs.local_complementation(lc_node)
# Checks edgelists are equal and also equal to the originals
lc_lc_g_edges = canonical_edge_order(lc_lc_g.edges())
lc_lc_gs_edges = canonical_edge_order(lc_lc_gs.edgelist())
assert lc_lc_g_edges == lc_lc_gs_edges
assert lc_lc_g_edges == g_edges
assert lc_lc_gs_edges == gs_edges