def setUp(self): self.D = 40 self.hs_custom = HarmonySearchV1(D=self.D, nFES=1000, benchmark=MyBenchmark()) self.hs_griewank = HarmonySearchV1(D=self.D, nFES=1000, benchmark=Griewank())
def test_griewank_works_fine(self): hs_griewank = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=Griewank()) hs_griewankc = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=Griewank()) AlgorithmTestCase.algorithm_run_test(self, hs_griewank, hs_griewankc)
def test_custom_works_fine(self): hs_costom = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=MyBenchmark()) hs_costomc = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=MyBenchmark()) AlgorithmTestCase.algorithm_run_test(self, hs_costom, hs_costomc)
def test_type_parameters(self): d = HarmonySearchV1.typeParameters() self.assertIsNone(d.get('b_range', None)) self.assertIsNotNone(d.get('dw_min', None)) self.assertIsNotNone(d.get('dw_max', None)) self.assertTrue(d['dw_min'](10)) self.assertFalse(d['dw_min'](-10)) self.assertTrue(d['dw_max'](10)) self.assertFalse(d['dw_max'](-10))
def plot_example(): task = TaskConvPlot(D=50, nFES=50000, nGEN=50000, benchmark=MyBenchmark()) algo = HarmonySearchV1(HMS=50, r_accept=0.7, r_pa=0.2, b_range=1.1, task=task) best = algo.run() logger.info('%s %s' % (best[0], best[1])) input('Press [enter] to continue')
def simple_example(runs=10): for i in range(runs): algo = HarmonySearchV1(D=50, nFES=50000, HMS=50, r_accept=0.7, r_pa=0.2, benchmark=MyBenchmark()) best = algo.run() logger.info('%s %s' % (best[0], best[1]))
def logging_example(): task = TaskConvPrint(D=50, nFES=50000, nGEN=50000, benchmark=MyBenchmark()) algo = HarmonySearchV1(HMS=50, r_accept=0.7, r_pa=0.2, bw_min=0.32, bw_max=1.5, seed=None, task=task) best = algo.run() logger.info('%s %s' % (best[0], best[1]))
def test_griewank_works_fine(self): hs_griewank = HarmonySearchV1(seed=self.seed) hs_griewankc = HarmonySearchV1(seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, hs_griewank, hs_griewankc)
def test_custom_works_fine(self): hs_costom = HarmonySearchV1(seed=self.seed) hs_costomc = HarmonySearchV1(seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, hs_costom, hs_costomc, 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 from NiaPy.algorithms.basic import HarmonySearchV1 from NiaPy.task import StoppingTask from NiaPy.benchmarks import Sphere # we will run Bat Algorithm for 5 independent runs algo = HarmonySearchV1() for i in range(5): task = StoppingTask(D=10, nGEN=1000, benchmark=Sphere()) best = algo.run(task) print('%s -> %s' % (best[0], best[1])) print(algo.getParameters()) # vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3