def test_simple_probs(self):
""" Testing whether migration history matches the expected output for each migration_direction and distribution_type """
for migr_dir in [
migration_direction.source, migration_direction.destination
]:
for dist_type in [
distribution_type.point_to_point,
distribution_type.broadcast
]:
prob = problem.rosenbrock(10)
alg = algorithm.jde(20)
archi = archipelago(alg,
prob,
3,
20,
migration_direction=migr_dir,
distribution_type=dist_type)
top = topology.ring(3)
top.set_weight(0, 1, 0.0)
top.set_weight(0, 2, 0.0)
top.set_weight(1, 2, 0.0)
top.set_weight(1, 0, 1.0)
top.set_weight(2, 0, 1.0)
top.set_weight(2, 1, 1.0)
archi.topology = top
archi.evolve(200)
migr_hist = archi.dump_migr_history()
# Below: After 200 evaluations, there should be some migrants from 1->0, 2->0 and 2->1
# There should be no migrants from 1->0, 2->0 and 2->1
self.assertTrue("(1,0,1)" not in migr_hist)
self.assertTrue("(1,0,2)" not in migr_hist)
self.assertTrue("(1,1,2)" not in migr_hist)
def __test_impl(self,isl_type,algo,prob): from PyGMO import archipelago, topology a = archipelago(topology = topology.ring()) for i in range(0,100): a.push_back(isl_type(algo,prob,6)) a.evolve(10) a.join()
def run_example5():
from PyGMO import archipelago, problem
from PyGMO.algorithm import jde
from PyGMO.topology import ring
from PyKEP import epoch
from PyKEP.planet import jpl_lp
from PyKEP.trajopt import mga_1dsm
# We define an Earth-Venus-Earth problem (single-objective)
seq = [jpl_lp('earth'), jpl_lp('venus'), jpl_lp('earth')]
prob = mga_1dsm(seq=seq)
prob.set_tof(0.7, 3)
prob.set_vinf(2.5)
prob.set_launch_window(epoch(5844), epoch(6209))
prob.set_tof(0.7, 3)
# We solve it!!
algo = jde(100)
topo = ring()
archi = archipelago(algo, prob, 8, 20, topology=topo)
print(
"Running a Self-Adaptive Differential Evolution Algorithm .... on 8 parallel islands"
)
archi.evolve(10)
archi.join()
isl = min(archi, key=lambda x: x.population.champion.f[0])
print("Done!! Best solution found is: " +
str(isl.population.champion.f[0] / 1000) + " km / sec")
prob.pretty(isl.population.champion.x)
prob.plot(isl.population.champion.x)
def run_example5():
from PyGMO import archipelago, problem
from PyGMO.algorithm import jde
from PyGMO.topology import ring
from PyKEP import planet_ss,epoch
from PyKEP.interplanetary import mga_1dsm
#We define an Earth-Venus-Earth problem (single-objective)
seq = [planet_ss('earth'),planet_ss('venus'),planet_ss('earth')]
prob = mga_1dsm(seq=seq)
prob.set_tof(0.7,3)
prob.set_vinf(2.5)
prob.set_launch_window(epoch(5844),epoch(6209))
prob.set_tof(0.7,3)
print prob
#We solve it!!
algo = jde(100)
topo = ring()
archi = archipelago(algo,prob,8,20, topology=topo)
print "Running a Self-Adaptive Differential Evolution Algorithm .... on 8 parallel islands"
archi.evolve(10); archi.join()
isl = min(archi, key=lambda x:x.population.champion.f[0])
print "Done!! Best solution found is: " + str(isl.population.champion.f[0]/1000) + " km / sec"
prob.pretty(isl.population.champion.x)
prob.plot(isl.population.champion.x)
def test_average_path_length(self):
""" Testing the average path length algorithm """
top = topology.ring(2)
self.assertEqual(top.get_average_shortest_path_length(), 1.0)
top = topology.ring(3)
self.assertEqual(top.get_average_shortest_path_length(), 1.0)
top = topology.ring(5)
self.assertEqual(top.get_average_shortest_path_length(), 1.5)
top = topology.ring(9)
self.assertEqual(top.get_average_shortest_path_length(), 2.5)
top = topology.custom()
top.push_back()
top.push_back()
top.push_back()
top.push_back()
top.add_edge(0, 1)
top.add_edge(1, 2)
top.add_edge(2, 3)
top.add_edge(3, 0)
top.add_edge(0, 2)
self.assertEqual(top.get_average_shortest_path_length(), 1.75)
def test_average_path_length(self):
""" Testing the average path length algorithm """
top = topology.ring(2)
self.assertEqual(top.get_average_shortest_path_length(), 1.0)
top = topology.ring(3)
self.assertEqual(top.get_average_shortest_path_length(), 1.0)
top = topology.ring(5)
self.assertEqual(top.get_average_shortest_path_length(), 1.5)
top = topology.ring(9)
self.assertEqual(top.get_average_shortest_path_length(), 2.5)
top = topology.custom()
top.push_back()
top.push_back()
top.push_back()
top.push_back()
top.add_edge(0, 1)
top.add_edge(1, 2)
top.add_edge(2, 3)
top.add_edge(3, 0)
top.add_edge(0, 2)
self.assertEqual(top.get_average_shortest_path_length(), 1.75)
def test_topology_serialize(self):
""" Testing whether the weights are retained after serialization of an archipelago """
prob = problem.rosenbrock(10)
alg = algorithm.jde(20)
archi = archipelago(alg, prob, 4, 20)
top = topology.ring(4)
top.set_weight(0, 1, 0.01)
top.set_weight(0, 3, 0.03)
top.set_weight(1, 2, 0.12)
top.set_weight(2, 1, 0.21)
archi.topology = top
archi.evolve(5)
import pickle
pickle.loads(pickle.dumps(archi))
self.assertEqual(archi.topology.get_weight(0, 1), 0.01)
self.assertEqual(archi.topology.get_weight(0, 3), 0.03)
self.assertEqual(archi.topology.get_weight(1, 2), 0.12)
self.assertEqual(archi.topology.get_weight(2, 1), 0.21)
def test_topology_serialize(self):
""" Testing whether the weights are retained after serialization of an archipelago """
prob = problem.rosenbrock(10)
alg = algorithm.jde(20)
archi = archipelago(alg, prob, 4, 20)
top = topology.ring(4)
top.set_weight(0, 1, 0.01)
top.set_weight(0, 3, 0.03)
top.set_weight(1, 2, 0.12)
top.set_weight(2, 1, 0.21)
archi.topology = top
archi.evolve(5)
import pickle
pickle.loads(pickle.dumps(archi))
self.assertEqual(archi.topology.get_weight(0, 1), 0.01)
self.assertEqual(archi.topology.get_weight(0, 3), 0.03)
self.assertEqual(archi.topology.get_weight(1, 2), 0.12)
self.assertEqual(archi.topology.get_weight(2, 1), 0.21)
def test_ring_topo(self):
""" Tests the getter/setter for the ring topology """
t = topology.ring()
t.push_back()
t.push_back()
# By default the weights are 1.0
self.assertEqual(t.get_weight(0, 1), 1.0)
self.assertEqual(t.get_weight(1, 0), 1.0)
# Once you alter one weight, the remaining are still 1.0
t.set_weight(0, 1, 0.1)
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 1.0)
# Pushing new node should not change anything to the previous ones
t.push_back()
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 1.0)
self.assertEqual(t.get_weight(0, 2), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 1), 1.0)
# Test the all-custom weights for ring topology
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.set_weight(0, 2, 0.3)
t.set_weight(2, 0, 0.4)
t.set_weight(1, 2, 0.5)
t.set_weight(2, 1, 0.6)
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 0.2)
self.assertEqual(t.get_weight(0, 2), 0.3)
self.assertEqual(t.get_weight(2, 0), 0.4)
self.assertEqual(t.get_weight(1, 2), 0.5)
self.assertEqual(t.get_weight(2, 1), 0.6)
def test_ring_topo(self):
""" Tests the getter/setter for the ring topology """
t = topology.ring()
t.push_back()
t.push_back()
# By default the weights are 1.0
self.assertEqual(t.get_weight(0, 1), 1.0)
self.assertEqual(t.get_weight(1, 0), 1.0)
# Once you alter one weight, the remaining are still 1.0
t.set_weight(0, 1, 0.1)
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 1.0)
# Pushing new node should not change anything to the previous ones
t.push_back()
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 1.0)
self.assertEqual(t.get_weight(0, 2), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 1), 1.0)
# Test the all-custom weights for ring topology
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.set_weight(0, 2, 0.3)
t.set_weight(2, 0, 0.4)
t.set_weight(1, 2, 0.5)
t.set_weight(2, 1, 0.6)
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 0.2)
self.assertEqual(t.get_weight(0, 2), 0.3)
self.assertEqual(t.get_weight(2, 0), 0.4)
self.assertEqual(t.get_weight(1, 2), 0.5)
self.assertEqual(t.get_weight(2, 1), 0.6)
def test_simple_probs(self):
""" Testing whether migration history matches the expected output for each migration_direction and distribution_type """
for migr_dir in [migration_direction.source, migration_direction.destination]:
for dist_type in [distribution_type.point_to_point, distribution_type.broadcast]:
prob = problem.rosenbrock(10)
alg = algorithm.jde(20)
archi = archipelago(alg, prob, 3, 20, migration_direction=migr_dir, distribution_type=dist_type)
top = topology.ring(3)
top.set_weight(0, 1, 0.0)
top.set_weight(0, 2, 0.0)
top.set_weight(1, 2, 0.0)
top.set_weight(1, 0, 1.0)
top.set_weight(2, 0, 1.0)
top.set_weight(2, 1, 1.0)
archi.topology = top
archi.evolve(200)
migr_hist = archi.dump_migr_history()
# Below: After 200 evaluations, there should be some migrants from 1->0, 2->0 and 2->1
# There should be no migrants from 1->0, 2->0 and 2->1
self.assertTrue("(1,0,1)" not in migr_hist)
self.assertTrue("(1,0,2)" not in migr_hist)
self.assertTrue("(1,1,2)" not in migr_hist)
def test_chain_break(self):
""" Testing 'chain breaking' after push_back in one-way-ring """
t = topology.ring(2)
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.push_back()
# In two-way ring, the weights between the first and second island should be the same after push_back
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 0.2)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 1), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
self.assertEqual(t.get_weight(0, 2), 1.0)
# In one-way-ring, the edge 1->0 will be broken
# and replaced by 1->2 and 2->0 with weights 1.0 each
t = topology.one_way_ring(2)
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.push_back()
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
def test_chain_break(self):
""" Testing 'chain breaking' after push_back in one-way-ring """
t = topology.ring(2)
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.push_back()
# In two-way ring, the weights between the first and second island should be the same after push_back
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 0), 0.2)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 1), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
self.assertEqual(t.get_weight(0, 2), 1.0)
# In one-way-ring, the edge 1->0 will be broken
# and replaced by 1->2 and 2->0 with weights 1.0 each
t = topology.one_way_ring(2)
t.set_weight(0, 1, 0.1)
t.set_weight(1, 0, 0.2)
t.push_back()
self.assertEqual(t.get_weight(0, 1), 0.1)
self.assertEqual(t.get_weight(1, 2), 1.0)
self.assertEqual(t.get_weight(2, 0), 1.0)
def optimization_run(optimization: BaseOptimization, num_islands: int,
handler: SimpleCSVSolutionsHandler):
solutions = optimization.solve(n_threads=num_islands,
n_individuals=10,
topol=topology.ring())
handler.handle_solutions(solutions, "best_solutions.csv")
def test_incorrect_weights(self):
""" Testing ValueError for getter/setter """
top = topology.ring(4)
self.assertRaises(ValueError, top.get_weight, 0, 2)
self.assertRaises(ValueError, top.set_weight, 0, 2, 0.5)
def test_incorrect_weights(self):
""" Testing ValueError for getter/setter """
top = topology.ring(4)
self.assertRaises(ValueError, top.get_weight, 0, 2)
self.assertRaises(ValueError, top.set_weight, 0, 2, 0.5)