def test_local_bha_discrete(supplyDiscreteFitnessFunction):
bha = darwin.Algorithm(darwin.opt.BlackHoleAlgorithm)
bha.particles = np.random.randint(5, 20)
bha.iterations = np.random.randint(5, 15)
bha.executionEngine = darwin.drm.TaskSpooler
bha.addVariable('map1', map1, discrete=True)
bha.addVariable('map2', map2, discrete=True)
bha.function = supplyDiscreteFitnessFunction
bha.submitFile = 'sanity_discrete.submit'
bha.start()
def test_local_bha_continuous(supplyFitnessFunction):
bha = darwin.Algorithm(darwin.opt.BlackHoleAlgorithm)
bha.particles = np.random.randint(5, 20)
bha.iterations = np.random.randint(5, 15)
bha.executionEngine = darwin.drm.TaskSpooler
bha.addVariable('x', x)
bha.addVariable('y', y)
bha.function = supplyFitnessFunction
bha.submitFile = 'sanity.submit'
bha.start()
def test_local_ga_discrete(supplyDiscreteFitnessFunction):
ga = darwin.Algorithm(darwin.opt.GeneticAlgorithm)
ga.mutationProbability = np.random.uniform(0.05, 0.25)
ga.particles = np.random.randint(5, 15)
ga.iterations = np.random.randint(5, 15)
ga.executionEngine = darwin.drm.TaskSpooler
ga.addVariable('map1', map1, discrete=True)
ga.addVariable('map2', map2, discrete=True)
ga.function = supplyDiscreteFitnessFunction
ga.submitFile = 'sanity_discrete.submit'
ga.start()
def test_local_ga_continuous(supplyFitnessFunction):
ga = darwin.Algorithm(darwin.opt.GeneticAlgorithm)
ga.mutationProbability = np.random.uniform(0.05, 0.25)
ga.particles = np.random.randint(5, 15)
ga.iterations = np.random.randint(5, 15)
ga.executionEngine = darwin.drm.TaskSpooler
ga.addVariable('x', x)
ga.addVariable('y', y)
ga.function = supplyFitnessFunction
ga.submitFile = 'sanity.submit'
ga.start()
def test_local_sa_discrete(supplyDiscreteFitnessFunction):
sa = darwin.Algorithm(darwin.opt.SimulatedAnnealing)
sa.initialTemperature = np.random.uniform(0, 1)
sa.finalTemperature = np.random.uniform(1.5, 3.5)
sa.particles = np.random.randint(5, 20)
sa.iterations = np.random.randint(5, 15)
sa.executionEngine = darwin.drm.TaskSpooler
sa.addVariable('map1', map1, discrete=True)
sa.addVariable('map2', map2, discrete=True)
sa.function = supplyDiscreteFitnessFunction
sa.submitFile = 'sanity_discrete.submit'
sa.start()
def test_htcondor_sa(supplyFitnessFunction):
sa = darwin.Algorithm(darwin.opt.SimulatedAnnealing)
sa.initialTemperature = np.random.uniform(0, 1)
sa.finalTemperature = np.random.uniform(1.5, 3.5)
sa.particles = np.random.randint(5, 20)
sa.iterations = np.random.randint(5, 15)
sa.executionEngine = darwin.drm.HTCondor
sa.addVariable('x', x)
sa.addVariable('y', y)
sa.function = supplyFitnessFunction
sa.submitFile = 'sanity.submit'
sa.start()
def test_local_de_discrete(supplyDiscreteFitnessFunction):
de = darwin.Algorithm(darwin.opt.DifferentialEvolution)
de.mutationFactor = np.random.uniform(0.05, 0.25)
de.crossoverProbability = np.random.uniform(0.05, 0.25)
de.particles = np.random.randint(5, 15)
de.iterations = np.random.randint(5, 15)
de.executionEngine = darwin.drm.TaskSpooler
de.addVariable('map1', map1, discrete=True)
de.addVariable('map2', map2, discrete=True)
de.function = supplyDiscreteFitnessFunction
de.submitFile = 'sanity_discrete.submit'
de.start()
def test_local_de_continuous(supplyFitnessFunction):
de = darwin.Algorithm(darwin.opt.DifferentialEvolution)
de.mutationFactor = np.random.uniform(0.05, 0.25)
de.crossoverProbability = np.random.uniform(0.05, 0.25)
de.particles = np.random.randint(5, 15)
de.iterations = np.random.randint(5, 15)
de.executionEngine = darwin.drm.TaskSpooler
de.addVariable('x', x)
de.addVariable('y', y)
de.function = supplyFitnessFunction
de.submitFile = 'sanity.submit'
de.start()
def test_local_pso_discrete(supplyDiscreteFitnessFunction):
pso = darwin.Algorithm(darwin.opt.ParticleSwarmOptimization)
pso.c1 = np.random.uniform(0, 1)
pso.c2 = np.random.uniform(0, 1)
pso.w = np.random.uniform(0, 1)
pso.particles = np.random.randint(5, 20)
pso.iterations = np.random.randint(5, 15)
pso.executionEngine = darwin.drm.TaskSpooler
pso.addVariable('map1', map1, discrete=True)
pso.addVariable('map2', map2, discrete=True)
pso.function = supplyDiscreteFitnessFunction
pso.submitFile = 'sanity_discrete.submit'
pso.start()
def test_local_pso(supplyFitnessFunction):
pso = darwin.Algorithm(darwin.opt.ParticleSwarmOptimization)
pso.c1 = np.random.uniform(0, 1)
pso.c2 = np.random.uniform(0, 1)
pso.w = np.random.uniform(0, 1)
pso.particles = np.random.randint(5, 20)
pso.iterations = np.random.randint(5, 15)
pso.executionEngine = darwin.drm.TaskSpooler
pso.addVariable('x', x)
pso.addVariable('y', y)
pso.function = supplyFitnessFunction
pso.submitFile = 'sanity.submit'
pso.start()
def test_local_ba_discrete(supplyDiscreteFitnessFunction):
ba = darwin.Algorithm(darwin.opt.BatAlgorithm)
ba.maxFrequency = np.random.uniform(0.3, 0.8)
ba.minFrequency = np.random.uniform(0.2, 0.5)
ba.pulseRate = np.random.uniform(0.3, 0.98)
ba.loudness = np.random.uniform(0.5, 1.5)
ba.particles = np.random.randint(5, 20)
ba.iterations = np.random.randint(5, 15)
ba.executionEngine = darwin.drm.TaskSpooler
ba.addVariable('map1', map1, discrete=True)
ba.addVariable('map2', map2, discrete=True)
ba.function = supplyDiscreteFitnessFunction
ba.submitFile = 'sanity_discrete.submit'
ba.start()
def test_local_ba_continuous(supplyFitnessFunction):
ba = darwin.Algorithm(darwin.opt.BatAlgorithm)
ba.maxFrequency = np.random.uniform(0.3, 0.8)
ba.minFrequency = np.random.uniform(0.2, 0.5)
ba.pulseRate = np.random.uniform(0.3, 0.98)
ba.loudness = np.random.uniform(0.5, 1.5)
ba.particles = np.random.randint(5, 20)
ba.iterations = np.random.randint(5, 15)
ba.executionEngine = darwin.drm.TaskSpooler
ba.addVariable('x', x)
ba.addVariable('y', y)
ba.function = supplyFitnessFunction
ba.submitFile = 'sanity.submit'
ba.start()