def test_mutation(
self,
mock_random_sample,
mocker,
mutation_strategy,
side_effect,
expected_mutated_population,
):
mocked_choice = mocker.Mock(side_effect=side_effect)
mocker.patch.object(np.random, "choice", mocked_choice)
pop_size = 5
tsp_solver = TravellingSalesmanProblemSolver(
G, mutation_strategy=mutation_strategy, pop_size=pop_size, random_state=42,
)
population = np.array(
[
[9, 2, 6, 1, 8, 3, 10, 5, 4, 7],
[1, 2, 9, 6, 4, 5, 8, 10, 7, 3],
[10, 3, 1, 7, 9, 6, 4, 8, 2, 5],
[2, 8, 7, 3, 9, 1, 4, 5, 6, 10],
[2, 6, 5, 9, 1, 8, 7, 4, 3, 10],
]
)
mutated_population = tsp_solver.mutate_population(
population, 2 * tsp_solver.n_genes
)
assert np.allclose(mutated_population, expected_mutated_population, rtol=1e-5)
def test_get_worst_gene(self):
pop_size = 5
tsp_solver = TravellingSalesmanProblemSolver(G, random_state=42)
route = np.arange(1, len(G.nodes))
np.random.shuffle(route)
assert tsp_solver.find_worst_gene(route) == 7
def test_numba_speedup(self, mocker):
mocked_fitness_function = mocker.patch(
"geneal.applications.tsp.travelling_salesman_problem.fitness_function"
)
tsp_solver = TravellingSalesmanProblemSolver(
G, numba_speedup=True, random_state=42
)
route = np.array([2, 6, 5, 9, 1, 8, 7, 4, 3, 10])
_ = tsp_solver.fitness_function(route)
mocked_fitness_function.assert_called()
def test_n_genes_overriding(self, n_genes, expected_n_genes):
tsp_solver = TravellingSalesmanProblemSolver(
G, n_genes=n_genes, random_state=42
)
assert tsp_solver.n_genes == expected_n_genes
def test_check_input(self):
tsp_solver = TravellingSalesmanProblemSolver(
G, n_crossover_points=3, random_state=42
)
assert tsp_solver.n_crossover_points == 2
def test_exception(self):
with pytest.raises(Exception) as excinfo:
mutation_strategy = "invalid_strategy"
tsp_solver = TravellingSalesmanProblemSolver(
G, mutation_strategy="invalid_strategy", random_state=42,
)
tsp_solver.solve()
assert excinfo.type == InvalidInput
assert (
str(excinfo.value) == f"{mutation_strategy} is an invalid mutation strategy"
)
def test_worst_gene_random_mutation(self):
pop_size = 8
tsp_solver = TravellingSalesmanProblemSolver(
G,
pop_size=pop_size,
random_state=42,
)
route = np.array([2, 1, 5, 7, 3, 4, 6, 8])
expected_mutated_route = np.array([2, 1, 5, 7, 3, 4, 8, 6])
mutated_route = tsp_solver.worst_gene_random_mutation_helper(route)
assert np.allclose(mutated_route, expected_mutated_route)
def test_random_gene_nearest_neighbour(self):
pop_size = 8
tsp_solver = TravellingSalesmanProblemSolver(
G,
pop_size=pop_size,
random_state=42,
)
route = np.array([2, 1, 5, 7, 3, 4, 6, 8])
expected_mutated_route = np.array([2, 6, 1, 5, 7, 3, 4, 8])
mutated_route = tsp_solver.random_gene_nearest_neighbour_helper(route)
assert np.allclose(mutated_route, expected_mutated_route)
def test_initialize_population(self, problem_type, expected_result):
pop_size = 5
n_genes = len(G.nodes)
tsp_solver = TravellingSalesmanProblemSolver(
G, pop_size=pop_size, random_state=42,
)
population = tsp_solver.initialize_population()
assert population.shape[0] == pop_size
assert population.shape[1] == n_genes
for route in population:
assert len(set(route)) == n_genes
assert np.allclose(population, expected_result, rtol=1e-05)
def test_random_inversion_mutation(self):
pop_size = 8
tsp_solver = TravellingSalesmanProblemSolver(
G,
pop_size=pop_size,
random_state=42,
)
route = np.array([2, 1, 5, 7, 3, 4, 6, 8])
mutation_cols = tsp_solver.get_consecutive_mutation_cols(route, 1, 5)
expected_mutated_route = np.array([2, 8, 6, 7, 3, 4, 5, 1])
mutated_route = tsp_solver.random_inversion_mutation_helper(
route, mutation_cols)
assert np.allclose(mutated_route, expected_mutated_route)
def test_random_swap_mutation(self):
pop_size = 8
tsp_solver = TravellingSalesmanProblemSolver(
G,
pop_size=pop_size,
random_state=42,
)
route = np.array([[2, 1, 5, 7, 3, 4, 6, 8]])
expected_mutated_route = np.array([2, 3, 5, 7, 1, 4, 6, 8])
mutation_rows = np.array([0])
mutation_cols = np.array([[1, 4]])
mutated_route = tsp_solver.random_swap_mutation(
route, mutation_rows, mutation_cols)
assert np.allclose(mutated_route, expected_mutated_route)
def test_plot_cities(
self,
mocker,
mock_logging,
mock_matplotlib,
mock_plotly_figure_show,
cities,
graph_file,
lat,
lon,
name,
):
mocked_add_trace = mocker.patch(
"geneal.applications.tsp.helpers._plot_cities.add_trace")
with open(f"tests/applications/fixtures/{graph_file}.pickle",
"rb") as f:
G = pickle.load(f)
tsp_solver = TravellingSalesmanProblemSolver(
G,
max_gen=2,
random_state=42,
)
tsp_solver.solve()
plot_cities(
cities,
tsp_solver,
lon=lon,
lat=lat,
name=name,
)
mocked_add_trace.assert_called()
assert mocked_add_trace.call_count == len(G.nodes)
def test_create_offspring(
self, crossover_pt, expected_first_offspring, expected_second_offspring
):
pop_size = 5
tsp_solver = TravellingSalesmanProblemSolver(
G, pop_size=pop_size, random_state=42,
)
first_parent = np.array([1, 3, 4, 7, 2, 5, 8, 6])
sec_parent = np.array([5, 2, 3, 8, 1, 6, 4, 7])
first_offspring = tsp_solver.create_offspring(
first_parent, sec_parent, crossover_pt, "first"
)
second_offspring = tsp_solver.create_offspring(
sec_parent, first_parent, crossover_pt, "second"
)
assert np.allclose(first_offspring, expected_first_offspring, rtol=1e-5)
assert np.allclose(second_offspring, expected_second_offspring, rtol=1e-5)