def test_griewank_works_fine(self):
de_griewank = AgingNpMultiMutationDifferentialEvolution(NP=10,
CR=0.5,
F=0.9,
seed=self.seed)
de_griewankc = AgingNpMultiMutationDifferentialEvolution(
NP=10, CR=0.5, F=0.9, seed=self.seed)
AlgorithmTestCase.algorithm_run_test(self, de_griewank, de_griewankc,
'griewank')
def test_custom_works_fine(self):
de_custom = AgingNpMultiMutationDifferentialEvolution(NP=40,
F=0.5,
CR=0.9,
seed=self.seed)
de_customc = AgingNpMultiMutationDifferentialEvolution(NP=40,
F=0.5,
CR=0.9,
seed=self.seed)
AlgorithmTestCase.algorithm_run_test(self, de_custom, de_customc,
MyBenchmark())
# encoding=utf8
# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys
sys.path.append('../')
# End of fix
import random
from NiaPy.algorithms.basic import AgingNpMultiMutationDifferentialEvolution
from NiaPy.algorithms.basic.de import CrossCurr2Best1, CrossBest2
from NiaPy.task import StoppingTask
from NiaPy.benchmarks import Sphere
# we will run Differential Evolution for 5 independent runs
for i in range(5):
task = StoppingTask(D=10, nFES=5000, benchmark=Sphere())
algo = AgingNpMultiMutationDifferentialEvolution(NP=10, F=0.2, CR=0.65, strategies=(CrossCurr2Best1, CrossBest2), delta_np=0.05, omega=0.9)
best = algo.run(task)
print('%s -> %s' % (best[0], best[1]))
# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3
def test_type_parameters(self):
d = AgingNpMultiMutationDifferentialEvolution.typeParameters()
self.assertIsNotNone(d.pop('Lt_min', None))
self.assertIsNotNone(d.pop('Lt_max', None))
self.assertIsNotNone(d.pop('delta_np', None))
self.assertIsNotNone(d.pop('omega', None))
def test_algorithm_info(self):
self.assertIsNotNone(
AgingNpMultiMutationDifferentialEvolution.algorithmInfo())