def test_not_progressing_enough(temporal_graph):
rw = TemporalRandomWalk(temporal_graph)
cw_size = 5 # no valid temporal walks of this size
with pytest.raises(RuntimeError, match=r".* discarded .*"):
rw.run(num_cw=1, cw_size=cw_size, max_walk_length=cw_size, seed=None)
def test_init_parameters(temporal_graph):
num_cw = 5
cw_size = 3
max_walk_length = 3
seed = 0
rw = TemporalRandomWalk(
temporal_graph, cw_size=cw_size, max_walk_length=max_walk_length, seed=seed
)
rw_no_params = TemporalRandomWalk(temporal_graph)
run_1 = rw.run(num_cw=num_cw)
run_2 = rw_no_params.run(
num_cw=num_cw, cw_size=cw_size, max_walk_length=max_walk_length, seed=seed
)
assert np.array_equal(run_1, run_2)
def test_init_parameters(temporal_graph):
num_cw = 5
cw_size = 3
max_walk_length = 3
seed = 0
rw = TemporalRandomWalk(temporal_graph,
cw_size=cw_size,
max_walk_length=max_walk_length,
seed=seed)
rw_no_params = TemporalRandomWalk(temporal_graph)
assert rw.run(num_cw=num_cw) == rw_no_params.run(
num_cw=num_cw,
cw_size=cw_size,
max_walk_length=max_walk_length,
seed=seed)
def test_temporal_walks(temporal_graph):
"""
valid time respecting walks (node -[time]-> node):
1 -[2]-> 2 -[10]-> 4
2 -[10]-> 4 -[12]-> 6
3 -[2]-> 2 -[10]-> 4
5 -[4]-> 4 -[12]-> 6
1 -[2]-> 2 -[10]-> 4 -[12]-> 6
3 -[2]-> 2 -[10]-> 4 -[12] -> 6
"""
expected = {(1, 2, 4), (2, 4, 6), (3, 2, 4), (5, 4, 6), (1, 2, 4, 6),
(3, 2, 4, 6)}
rw = TemporalRandomWalk(temporal_graph)
num_cw = 20 # how many walks to be sure we're getting valid temporal walks
for walk in rw.run(num_cw=num_cw, cw_size=3, max_walk_length=4, seed=None):
assert tuple(walk) in expected