def test_firefly(self):
"""
Tests (pychemia.searcher.firefly) :
"""
pcm_log.debug('FireFly')
mini = Sphere().minimum(3)
popu = RealFunction(Sphere.function,
3, [-1, 1],
local_minimization=False)
searcher = FireFly(popu, generation_size=16, stabilization_limit=5)
searcher.run()
popu = RealFunction(Sphere.function,
3, [-1, 1],
local_minimization=True)
searcher = FireFly(popu, {
'delta': 0.1,
'gamma': 0.1,
'beta0': 0.8,
'alpha0': 0,
'multi_move': True
},
generation_size=16,
stabilization_limit=5)
searcher.run()
assert np.linalg.norm(
np.array(searcher.population.db[searcher.population.best_candidate]
['x']) - mini) < 0.2
def test_euclidean(self):
"""
Tests (pychemia.population.RealFunction) :
"""
if not has_connection():
return
popu = RealFunction(funx2, 2, [-1, 1])
popu.add_random()
popu.add_random()
def test_euclidean(self):
"""
Tests (pychemia.population.RealFunction) :
"""
if not has_connection():
return
popu = RealFunction(funx2, 2, [-1, 1])
popu.add_random()
popu.add_random()
def test_genetic(self):
"""
Tests (pychemia.searcher.genetic) :
"""
pcm_log.debug('GeneticAlgorithm')
mini = Sphere().minimum(3)
popu = RealFunction(Sphere.function,
3, [-1, 1],
local_minimization=False)
searcher = GeneticAlgorithm(popu,
generation_size=16,
stabilization_limit=5)
searcher.run()
popu = RealFunction(Sphere.function,
3, [-1, 1],
local_minimization=True)
searcher = GeneticAlgorithm(popu,
generation_size=16,
stabilization_limit=5)
searcher.run()
assert np.linalg.norm(
np.array(searcher.population.db[searcher.population.best_candidate]
['x']) - mini) < 0.2