def test_compute_position_return_values(swarm, bounds, static):
"""Test if compute_position() gives the expected shape and range"""
topology = Pyramid(static=static)
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, static):
"""Test if compute_velocity() gives the expected shape and range"""
topology = Pyramid(static=static)
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_compute_gbest_return_values(swarm, static):
"""Test if compute_gbest() gives the expected return values"""
topology = Pyramid(static=static)
expected_cost = 1.0002528364353296
expected_pos = np.array([9.90438476e-01, 2.50379538e-03, 1.87405987e-05])
pos, cost = topology.compute_gbest(swarm)
assert cost == pytest.approx(expected_cost)
assert pos == pytest.approx(expected_pos)
variables = np.array(variables)
dist = 1 / (IF**CONVERT_FACTOR)
dim = n * 3 # Dimension of X
epsilon = 1
max_bound = maxD / 2 * np.ones(dim)
min_bound = -max_bound
bounds = (min_bound, max_bound)
lr = 0.5
clamp = (-lr, lr)
if (topoModel == "pyramid"):
from pyswarms.backend.topology import Pyramid
my_topology = Pyramid(static=False)
optimizer = ps.single.GeneralOptimizerPSO(n_particles=swarm_size,
dimensions=dim,
options=options,
velocity_clamp=clamp,
topology=my_topology)
elif (topoModel == "random"):
from pyswarms.backend.topology import Random as PSOTopoRandom
my_topology = PSOTopoRandom()
options = {'c1': c1, 'c2': c2, 'w': w, 'k': k, 'p': p}
optimizer = ps.single.GeneralOptimizerPSO(n_particles=swarm_size,
dimensions=dim,
options=options,
velocity_clamp=clamp,
topology=my_topology)
elif (topoModel == "star"):
def test_neighbor_idx(swarm, static):
"""Test if the neighbor_idx attribute is assigned"""
topology = Pyramid(static=static)
topology.compute_gbest(swarm)
assert topology.neighbor_idx is not None
@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_