def plot_example(D=10, nFES=50000):
task = TaskConvPlot(D=D, nFES=nFES, nGEN=50000, benchmark=MyBenchmark())
algo = HarmonySearch(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 logging_example(D=10, nFES=50000):
task = TaskConvPrint(D=D, nFES=nFES, nGEN=50000, benchmark=MyBenchmark())
algo = HarmonySearch(HMS=50,
r_accept=0.7,
r_pa=0.2,
b_range=1.1,
seed=None,
task=task)
best = algo.run()
logger.info('%s %s' % (best[0], best[1]))
def simple_example(runs=10, D=10, nFES=50000):
for i in range(runs):
algo = HarmonySearch(D=D,
nFES=nFES,
HMS=50,
r_accept=0.7,
r_pa=0.2,
b_range=1.1,
benchmark=MyBenchmark())
best = algo.run()
logger.info('%s %s' % (best[0], best[1]))
class HSTestCase(TestCase):
def setUp(self):
self.D = 40
self.hs_custom = HarmonySearch(D=self.D,
nFES=1000,
benchmark=MyBenchmark())
self.hs_griewank = HarmonySearch(D=self.D,
nFES=1000,
benchmark=Griewank())
def test_custom_works_fine(self):
fun = MyBenchmark().function()
x = self.hs_custom.run()
self.assertTrue(x)
self.assertAlmostEqual(fun(self.D, x[0]), x[1], delta=1e2)
def test_griewank_works_fine(self):
fun = Griewank().function()
x = self.hs_griewank.run()
self.assertTrue(x)
self.assertAlmostEqual(fun(self.D, x[0]), x[1], delta=1e2)
# 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 HarmonySearch
from NiaPy.util import StoppingTask, OptimizationType
from NiaPy.benchmarks import Sphere
#we will run Harmony Search for 5 independent runs
for i in range(5):
task = StoppingTask(D=10,
nFES=10000,
optType=OptimizationType.MINIMIZATION,
benchmark=Sphere())
algo = HarmonySearch()
best = algo.run(task=task)
print(best)