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()