def test_register_new_local_best_result(self):
"""Register new local best result."""
class Environment(object):
def setInfo(self, info):
self.info = info
def updateParticleBest(self, info):
assert info == self.info
def register(self, particle):
assert self == particle.environment
env = Environment()
position = matrix([1, 2, 3])
fitness = 5
info = Information(position=position, fitness=fitness)
env.setInfo(Information(position=position, fitness=fitness))
particle = Particle(
environment=env, best=info)
position = matrix([4, 5, 6])
fitness = 4
info = Information(position=position, fitness=fitness)
env.setInfo(info)
particle.current = info
def test_cognition(self):
"""Test cognition."""
config = {}
config['cognition'] = 4
env = Environment(config=config)
assert env.config['cognition'] == 4
env = Environment(config={})
assert env.config['cognition'] == 1
def test_social(self):
"""Test social."""
config = {}
config['social'] = 4
env = Environment(config=config)
assert env.config['social'] == 4
env = Environment(config={})
assert env.config['social'] == 1
def test_inertial_weight(self):
"""Test inertial_weight."""
config = {}
config['inertial_weight'] = 4
env = Environment(config=config)
assert env.config['inertial_weight'] == 4
env = Environment(config={})
assert env.config['inertial_weight'] == 1
def test_env_best_result(self):
"""Test the computation of global best result."""
env = Environment(config={})
position = matrix([0, 0, 0])
particles = {}
particles[1] = Particle(
environment=env,
current=Information(position=position, fitness=3))
particles[2] = Particle(
environment=env,
current=Information(position=position, fitness=10))
particles[3] = Particle(
environment=env,
current=Information(position=position, fitness=40))
particles[4] = Particle(
environment=env,
current=Information(position=position, fitness=25))
particles[5] = Particle(
environment=env,
current=Information(position=position, fitness=1))
particles[6] = Particle(
environment=env,
current=Information(position=position, fitness=37))
best = env.best
assert particles[5] == best
assert particles[5].best == best.best
def test_generate(self):
"""Test generation."""
class Random(object):
"""Randomizer."""
def random(self):
"""Return random [0,1) matrix 3x1."""
return matrix([1, 1, 1])
env = Environment({
'random':
Random(),
'base':
matrix([
[0, 0, 0], # beacon 1
[60, -40, 0], # beacon 2
[50, 50, 0], # beacon 3
]),
})
num_beacons = len(env.config['base'])
position_gen = around_beacons(environment=env)
for i in range(3 * num_beacons):
position = next(position_gen)
new_val = env.config['base'][i % num_beacons] + Random().random()
assert (new_val == position).all()
def test_randomizer(self):
"""Test randomizer."""
class Random(object):
def random(self):
return "random"
config = {}
config['random'] = Random()
env = Environment(config=config)
assert env.config['random'].random() == "random"
config['random'] = random
env = Environment(config=config)
assert 0 <= env.config['random'].random() < 1
def test_particle_register_environment(self):
"""Test if particle update environment when set new best value."""
env = Environment(config={})
position = matrix([1, 2, 3])
fitness = 5
myinfo = Information(position=position, fitness=fitness)
p1 = Particle(environment=env, best=myinfo)
assert env.best == p1
def test_index(self):
"""Test particle index."""
env = Environment(config={})
particles = []
for i in range(10):
particles.append(Particle(environment=env, id=i))
for i in range(len(particles)):
p = env.particles[i]
assert p.index == i
def test_register_new_local_best_result(self):
"""Register new local best result."""
class Environment(object):
def setInfo(self, info):
self.info = info
def updateParticleBest(self, info):
assert info == self.info
def register(self, particle):
assert self == particle.environment
env = Environment()
position = matrix([1, 2, 3])
fitness = 5
info = Information(position=position, fitness=fitness)
env.setInfo(Information(position=position, fitness=fitness))
particle = Particle(environment=env, best=info)
position = matrix([4, 5, 6])
fitness = 4
info = Information(position=position, fitness=fitness)
env.setInfo(info)
particle.current = info
def test_id(self):
"""Test if of a particle."""
position = [1, 2, 3]
fitness = 5
myid = "myid"
particle = Particle(environment=Environment(config={}),
id=myid,
best=Information(position=position,
fitness=fitness))
assert myid == particle.id
particle = Particle(environment=Environment(config={}),
best=Information(position=position,
fitness=fitness))
assert str(particle) == particle.id
# test set id == 0
env = Environment(config={})
p = Particle(environment=env, id=0)
assert p.id == 0
assert env.particles[0] == p
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
def test_update_best(self):
"""Test update best result."""
env = Environment(config={})
old_best = Information(position=None, fitness=5)
better_best = Information(position=None, fitness=3)
worse_best = Information(position=None, fitness=7)
particle = Particle(environment=env, current=old_best)
assert particle.best == old_best
particle.current = better_best
assert particle.best == better_best
particle.current = worse_best
assert particle.best == better_best
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_particles = param[4]
velocity_max = param[5]
iterations_per_particle = param[6]
# 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 environment configuration
env_config = {
'inertial_weight': inertial_weight,
'cognition': cognition,
'social': social,
'random': random_generator,
'base': base,
'radius': radius
}
env = Environment(config=env_config)
# particle position generator
position_generator = position_initializator(env)
# particles inside env
for i in range(num_particles):
# particles
PSOParticle(
environment=env,
id="P{}env{}".format(i, index),
current=Information(position=next(position_generator)),
velocity=velocity_max * random_generator.random(),
vmax=velocity_max
)
# engine for env
yield (param, ParticleEngine(
config={
'max_iterations': iterations_per_particle
},
environment=env
))
def test_move_defined_values(self):
"""Test move."""
class Random(object):
def random(self):
return 1
config = {
'inertial_weight': 1,
'cognition': 1,
'social': 1,
'random': Random(),
'base': matrix([
[0, 0, 0], # beacon 1
[7, 5, 0], # beacon 2
[5, -4, 0], # beacon 3
]),
'radius': matrix([
3.024, # beacon 1
6.4, # beacon 2
6.63, # beacon 3
])
}
env = Environment(config)
particle = PSOParticle(environment=env,
current=Information(position=matrix([1, 1, 1])))
particle.fitness()
assert 20.14 < particle.best.fitness < 20.15
particle.move()
assert (particle.current.position == matrix([2, 2, 2])).all()
particle.fitness()
assert 10.85 < particle.best.fitness < 10.86
particle.move()
assert (particle.current.position == matrix([3, 3, 3])).all()
particle.fitness()
assert 47.85 < particle.current.fitness < 47.86
assert 10.85 < particle.best.fitness < 10.86
particle.move()
assert (particle.current.position == matrix([2, 2, 2])).all()
def test_move_one_values(self):
"""Test move."""
class Random(object):
def random(self):
return 1
info = Information(position=matrix([1, 1, 1]), fitness=5)
binfo = Information(position=matrix([1, 1, 1]), fitness=5)
velocity = matrix([1, 1, 1])
config = {}
config['inertial_weight'] = 1
config['cognition'] = 1
config['social'] = 1
config['random'] = Random()
env = Environment(config)
particle = PSOParticle(environment=env,
current=info, best=binfo, velocity=velocity)
new_info = particle.move()
assert (particle.velocity == matrix([1, 1, 1])).all()
assert (new_info.position == matrix([2, 2, 2])).all()
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_set_high_velocity(self):
"""Test set high velocity."""
env = Environment(config={})
position = matrix([1, 2, 3])
fitness = 5
velocity = matrix([3, 100, 10])
info = Information(position=position, fitness=fitness)
particle = Particle(current=info,
environment=env,
vmax=1000,
velocity=velocity)
assert (particle.velocity == matrix([3, 100, 10])).all()
particle = Particle(current=info,
environment=env,
vmax=20,
velocity=velocity)
assert (particle.velocity == matrix([3, 20, 10])).all()
particle = Particle(current=info,
environment=env,
vmax=4,
velocity=velocity)
assert (particle.velocity == matrix([3, 4, 4])).all()
particle = Particle(current=info,
environment=env,
vmax=1,
velocity=velocity)
assert (particle.velocity == matrix([1, 1, 1])).all()
'base':
matrix([
[0, 0, 0], # beacon 1
[60, -40, 0], # beacon 2
[50, 50, 0], # beacon 3
[25, 0, 25] # beacon 4
]),
'radius':
matrix([
20, # beacon 1
60, # beacon 2
60, # beacon 3
30, # beacon 4
])
}
env1 = Environment(config=env_config)
env2 = Environment(config=env_config)
# connect environments
env1.registerNeighbor(env2)
position_generator = around_beacons(env1)
# particles inside env 1
for i in range(int(sys.argv[1])):
PSOParticle(environment=env1,
id="P{}env1".format(i),
current=Information(position=next(position_generator)),
velocity=random_generator.random(),
vmax=5)
# particles inside env 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
))
'random':
Random(),
'base':
matrix([
[0, 0, 0], # beacon 1
[7, 5, 0], # beacon 2
[5, -4, 0], # beacon 3
]),
'radius':
matrix([
3.024, # beacon 1
6.4, # beacon 2
6.63, # beacon 3
])
}
env = Environment(config=config)
PSOParticle(environment=env,
id="P1",
current=Information(position=config['base'][0]),
velocity=matrix([0.1, 0.1, 0.1]),
vmax=3)
PSOParticle(environment=env,
id="P2",
current=Information(position=config['base'][1]),
vmax=10)
PSOParticle(environment=env,
id="P3",
current=Information(position=config['base'][2]),
vmax=10)
base = next(base_generator)
point = next(point_generator)
error = 10
disturbed_point_gen = apply_noise_linear(point=point, error=error)
radius = matrix([distance(b, next(disturbed_point_gen)) for b in base])
env_config = {
'inertial_weight': 2,
'cognition': 2,
'social': 1,
'random': random_generator,
'base': base,
'radius': radius
}
env1 = Environment(config=env_config)
position_generator = around_beacons(env1)
vmax = 5
# particles inside env 1
for i in range(int(sys.argv[1])):
PSOParticle(environment=env1,
id="P{}env1".format(i),
current=Information(position=next(position_generator)),
velocity=vmax * random_generator.random() -
matrix([vmax / 2, vmax / 2, vmax / 2]),
vmax=vmax)
# Load logging configuration
[60, -40, 0], # beacon 2
[50, 50, 0], # beacon 3
[25, 0, 25] # beacon 4
]),
'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
)
def test_empty_environment(self):
"""Test empty environment."""
env = Environment(config={})
with pytest.raises(EmptyEnvironment):
env.best