def test_compute_position_return_values(swarm, bounds):
"""Test if compute_position() gives the expected shape and range"""
topology = VonNeumann()
p = topology.compute_position(swarm, bounds)
assert p.shape == swarm.velocity.shape
if bounds is not None:
assert (bounds[0] <= p).all() and (bounds[1] >= p).all()
def test_compute_velocity_return_values(swarm, clamp):
"""Test if compute_velocity() gives the expected shape and range"""
topology = VonNeumann()
v = topology.compute_velocity(swarm, clamp)
assert v.shape == swarm.position.shape
if clamp is not None:
assert (clamp[0] <= v).all() and (clamp[1] >= v).all()
def test_update_gbest_neighborhood(swarm, p, r):
"""Test if update_gbest_neighborhood gives the expected return values"""
topology = VonNeumann()
pos, cost = topology.compute_gbest(swarm, p=p, r=r)
expected_pos = np.array([9.90438476e-01, 2.50379538e-03, 1.87405987e-05])
expected_cost = 1.0002528364353296
assert cost == pytest.approx(expected_cost)
assert pos == pytest.approx(expected_pos)
def test_delannoy_numbers(m, n):
expected_values = np.array([
1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 25, 41, 61, 63, 85, 113, 129, 145,
181, 231, 321, 377, 575, 681, 833, 1159, 1289, 1683, 2241, 3649, 3653,
5641, 7183, 8989, 13073, 19825, 40081, 48639, 75517, 108545, 22363,
224143, 265729, 598417
])
print(VonNeumann.delannoy(m, n))
assert VonNeumann.delannoy(m, n) in expected_values
def test_invalid_r_or_p_values(options):
"""Tests if exception is thrown when passing
an invalid value for r or p when using a Von Neumann topology"""
with pytest.raises(ValueError):
GeneralOptimizerPSO(5, 2, options, VonNeumann())
def test_keyword_exception_vonneumann(options, static):
"""Tests if exceptions are thrown when keywords are missing and a VonNeumann topology is chosen"""
with pytest.raises(KeyError):
GeneralOptimizerPSO(5, 2, options, VonNeumann())
def test_delannoy_numbers(self, m, n):
expected_values = np.array([1, 3, 5, 7, 9, 11, 13, 15, 17])
assert VonNeumann.delannoy(m, n) in expected_values
@pytest.fixture(scope="module")
def binary_reset():
"""Returns a BinaryPSO instance that has been run and reset to check
default value"""
pso = BinaryPSO(10, 2, {"c1": 0.5, "c2": 0.7, "w": 0.5, "k": 2, "p": 2})
pso.optimize(sphere_func, 10, verbose=0)
pso.reset()
return pso
@pytest.fixture
def options():
"""Default options dictionary for most PSO use-cases"""
options_ = {"c1": 0.5, "c2": 0.7, "w": 0.5, "k": 2, "p": 2, "r": 1}
return options_
@pytest.fixture(params=[
Star(),
Ring(static=False), Ring(static=True),
Pyramid(static=False), Pyramid(static=True),
Random(static=False), Random(static=True),
VonNeumann()
])
def topology(request):
"""Parametrized topology parameter"""
topology_ = request.param
return topology_
def test_neighbor_idx(swarm, p, r):
"""Test if the neighbor_idx attribute is assigned"""
topology = VonNeumann()
topology.compute_gbest(swarm, p=p, r=r)
assert topology.neighbor_idx is not None
