def test_hadamard_code():
"""Picklability test for the Hadamard Code kernel."""
train, _ = generate_dataset(n_graphs=100,
r_vertices=(10, 20),
r_connectivity=(0.4, 0.8),
r_weight_edges=(1, 1),
n_graphs_test=40,
random_state=rs,
features=('nl', 5))
hadamard_code_kernel = HadamardCode(verbose=verbose,
normalize=normalize,
base_graph_kernel=VertexHistogram)
hadamard_code_kernel.fit(train)
assert is_picklable(hadamard_code_kernel)
def test_hadamard_code():
"""Eigenvalue test for the Hadamard Code kernel."""
hadamard_code_kernel = HadamardCode(verbose=verbose, normalize=normalize,
base_graph_kernel=VertexHistogram)
if verbose:
print_kernel("Hadamard-Code/VH [Simple]",
hadamard_code_kernel, dataset_tr, dataset_te)
else:
positive_eig(hadamard_code_kernel, dataset)
def test_hadamard_code():
"""Random input test for the Hadamard Code kernel."""
train, test = generate_dataset(n_graphs=100,
r_vertices=(10, 20),
r_connectivity=(0.4, 0.8),
r_weight_edges=(1, 1),
n_graphs_test=40,
random_state=rs,
features=('nl', 5))
hadamard_code_kernel = HadamardCode(verbose=verbose,
normalize=normalize,
base_kernel=VertexHistogram)
try:
hadamard_code_kernel.fit_transform(train)
hadamard_code_kernel.transform(test)
assert True
except Exception as exception:
assert False, exception
lambda: WeisfeilerLehman(
n_iter=2, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-WL-3":
lambda: WeisfeilerLehman(
n_iter=3, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-WL-4":
lambda: WeisfeilerLehman(
n_iter=4, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-WL-5":
lambda: WeisfeilerLehman(
n_iter=5, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-NH":
lambda: NeighborhoodHash(n_jobs=N_JOBS,
normalize=NORMALIZING_GRAPH_KERNELS),
"GK-HC-1":
lambda: HadamardCode(
n_iter=1, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-HC-2":
lambda: HadamardCode(
n_iter=2, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-HC-3":
lambda: HadamardCode(
n_iter=3, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-HC-4":
lambda: HadamardCode(
n_iter=4, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-HC-5":
lambda: HadamardCode(
n_iter=5, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS),
"GK-NSPD":
lambda: NeighborhoodSubgraphPairwiseDistance(normalize=
NORMALIZING_GRAPH_KERNELS),
n_iter=2, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-WL-3": lambda: WeisfeilerLehman(
n_iter=3, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-WL-4": lambda: WeisfeilerLehman(
n_iter=4, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-WL-5": lambda: WeisfeilerLehman(
n_iter=5, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-NH": lambda: NeighborhoodHash(
n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-HC-5": lambda: HadamardCode(
n_iter=5, n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
),
"GK-NSPD": lambda: NeighborhoodSubgraphPairwiseDistance(
normalize=NORMALIZING_GRAPH_KERNELS
),
}
NOT_TESTED = {
"GK-ShortestPathA": lambda: ShortestPathAttr(normalize=NORMALIZING_GRAPH_KERNELS),
"GK-RandomWalk": lambda: RandomWalk(
n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
), # taking too long
"GK-RandomWalkLabeled": lambda: RandomWalkLabeled(
n_jobs=N_JOBS, normalize=NORMALIZING_GRAPH_KERNELS
), # taking too long
"GK-GraphHopper": lambda: GraphHopper(normalize=NORMALIZING_GRAPH_KERNELS),