def test_register_neighbord(self):
"""Test register neighboard."""
env1 = Environment({})
env2 = Environment({})
assert env1 not in env2.neighbors
assert env2 not in env1.neighbors
assert len(list(filter(lambda x: x == env1, env1.neighbors))) == 1
assert len(list(filter(lambda x: x == env2, env2.neighbors))) == 1
env1.registerNeighbor(env2)
assert env1 in env2.neighbors
assert env2 in env1.neighbors
assert len(list(filter(lambda x: x == env1, env1.neighbors))) == 1
assert len(list(filter(lambda x: x == env2, env2.neighbors))) == 1
# try to register 2 times
env1.registerNeighbor(env2)
assert len(list(filter(lambda x: x == env2, env1.neighbors))) == 1
assert len(list(filter(lambda x: x == env1, env2.neighbors))) == 1
def test_best_neighbor_env(self):
"""Test the best particle from all environments neighbor."""
position = matrix([0, 0, 0])
env1 = Environment({})
env2 = Environment({})
env1.registerNeighbor(env2)
particles = {}
particles[1] = Particle(
environment=env1,
current=Information(position=position, fitness=3))
particles[2] = Particle(
environment=env2,
current=Information(position=position, fitness=10))
particles[3] = Particle(
environment=env1,
current=Information(position=position, fitness=40))
particles[4] = Particle(
environment=env2,
current=Information(position=position, fitness=25))
particles[5] = Particle(
environment=env1,
current=Information(position=position, fitness=1))
particles[6] = Particle(
environment=env2,
current=Information(position=position, fitness=37))
best = env1.neighborBest
assert particles[5] == best
assert particles[5].best == best.best
best = env2.neighborBest
assert particles[5] == best
assert particles[5].best == best.best
]),
'radius': matrix([
20, # beacon 1
60, # beacon 2
60, # beacon 3
30, # beacon 4
])
}
config_env2 = deepcopy(config_env1)
config_env2['random'] = Random3D()
env1 = Environment(config=config_env1)
env2 = Environment(config=config_env2)
# connect environments
env1.registerNeighbor(env2)
position_generator = around_beacons(env1)
# particles inside env 1
for i in range(int(sys.argv[1])):
GlobalBestPSOParticle(
environment=env1,
id="P{}env1".format(i),
current=Information(position=next(position_generator)),
velocity=random_generator.random(),
vmax=5
)
# particles inside env 2
for i in range(int(sys.argv[2])):
def builder(base, point, params, random_generator, position_initializator):
"""Sistematically generate environments from parameters combination."""
index = 1
for param in parameters_matrix(params):
# read parameters from the matrix
error = param[0]
inertial_weight = param[1]
cognition = param[2]
social = param[3]
num_psoparticles = param[4]
num_fbparticles = param[5]
velocity_max = param[6]
iterations_per_particle = param[7]
# point disturbed by a gaussian noise
disturbed_point_gen = apply_noise_linear(point=point, error=error)
# compute radius
radius = matrix([distance(b, next(disturbed_point_gen)) for b in base])
# build environments configuration
env_config = {
'inertial_weight': inertial_weight,
'cognition': cognition,
'social': social,
'random': random_generator,
'base': base,
'radius': radius
}
# [ENV1 - PSOParticles]
env1 = Environment(config=env_config)
# particle position generator
position_generator = position_initializator(env1)
# particles inside env1
for i in range(num_psoparticles):
# particles
PSOParticle(
environment=env1,
id="P{}env1-{}".format(i, index),
current=Information(position=next(position_generator)),
velocity=random_generator.random(),
vmax=velocity_max
)
# [ENV2 - FollowBestParticles]
env2 = Environment(config=env_config)
# particle position generator
position_generator = position_initializator(env2)
# particles inside env2
for i in range(num_fbparticles):
# particles
FollowBestParticle(
environment=env2,
id="P{}env2-{}".format(i, index),
current=Information(position=next(position_generator)),
velocity=random_generator.random(),
vmax=velocity_max
)
# connect environments
env1.registerNeighbor(env2)
# engines for env1 and env2
yield (param,
ParticleEngine(
config={
'max_iterations': iterations_per_particle
},
environment=env1
),
ParticleEngine(
config={
'max_iterations': iterations_per_particle
},
environment=env2
))
