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import sys
import unittest
import array
import pickle
import operator
import platform
import numpy
from deap import creator
from deap import base
from deap import gp
from deap import tools
def func():
return "True"
class Pickling(unittest.TestCase):
def setUp(self):
creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("IndList", list, fitness=creator.FitnessMax)
creator.create("IndArray", array.array, typecode='f', fitness=creator.FitnessMax)
creator.create("IndNDArray", numpy.ndarray, typecode='f', fitness=creator.FitnessMax)
creator.create("IndTree", gp.PrimitiveTree, fitness=creator.FitnessMax)
self.toolbox = base.Toolbox()
self.toolbox.register("func", func)
self.toolbox.register("lambda_func", lambda: "True")
def tearDown(self):
del creator.FitnessMax
del creator.IndList
del creator.IndArray
del creator.IndNDArray
del creator.IndTree
def test_pickle_fitness(self):
fitness = creator.FitnessMax()
fitness.values = (1.0,)
fitness_s = pickle.dumps(fitness)
fitness_l = pickle.loads(fitness_s)
self.assertEqual(fitness, fitness_l, "Unpickled fitness != pickled fitness")
def test_pickle_ind_list(self):
ind = creator.IndList([1.0, 2.0, 3.0])
ind.fitness.values = (4.0,)
ind_s = pickle.dumps(ind)
ind_l = pickle.loads(ind_s)
self.assertEqual(ind, ind_l, "Unpickled individual list != pickled individual list")
self.assertEqual(ind.fitness, ind_l.fitness, "Unpickled individual fitness != pickled individual fitness")
def test_pickle_ind_array(self):
ind = creator.IndArray([1.0, 2.0, 3.0])
ind.fitness.values = (4.0,)
ind_s = pickle.dumps(ind)
ind_l = pickle.loads(ind_s)
self.assertEqual(ind, ind_l, "Unpickled individual array != pickled individual array")
self.assertEqual(ind.fitness, ind_l.fitness, "Unpickled individual fitness != pickled individual fitness")
# @unittest.skipIf(platform.python_implementation() == "PyPy", "PyPy support for pickling ndarrays is very unstable.")
def test_pickle_ind_ndarray(self):
ind = creator.IndNDArray([1.0, 2.0, 3.0])
ind.fitness.values = (4.0,)
ind_s = pickle.dumps(ind)
ind_l = pickle.loads(ind_s)
self.assertTrue(all(ind == ind_l), "Unpickled individual numpy.ndarray != pickled individual numpy.ndarray")
self.assertEqual(ind.fitness, ind_l.fitness, "Unpickled individual fitness != pickled individual fitness")
def test_pickle_tree_input(self):
pset = gp.PrimitiveSetTyped("MAIN", [int], int, "IN")
pset.addPrimitive(operator.add, [int, int], int)
expr = gp.genFull(pset, min_=1, max_=1)
ind = creator.IndTree(expr)
ind.fitness.values = (1.0,)
ind_s = pickle.dumps(ind, pickle.HIGHEST_PROTOCOL)
ind_l = pickle.loads(ind_s)
msg = "Unpickled individual %s != pickled individual %s" % (str(ind), str(ind_l))
self.assertEqual(ind, ind_l, msg)
msg = "Unpickled fitness %s != pickled fitness %s" % (str(ind.fitness), str(ind_l.fitness))
self.assertEqual(ind.fitness, ind_l.fitness, msg)
def test_pickle_tree_term(self):
pset = gp.PrimitiveSetTyped("MAIN", [], int, "IN")
pset.addPrimitive(operator.add, [int, int], int)
pset.addTerminal(1, int)
expr = gp.genFull(pset, min_=1, max_=1)
ind = creator.IndTree(expr)
ind.fitness.values = (1.0,)
ind_s = pickle.dumps(ind, pickle.HIGHEST_PROTOCOL)
ind_l = pickle.loads(ind_s)
msg = "Unpickled individual %s != pickled individual %s" % (str(ind), str(ind_l))
self.assertEqual(ind, ind_l, msg)
msg = "Unpickled fitness %s != pickled fitness %s" % (str(ind.fitness), str(ind_l.fitness))
self.assertEqual(ind.fitness, ind_l.fitness, msg)
def test_pickle_tree_ephemeral(self):
pset = gp.PrimitiveSetTyped("MAIN", [], int, "IN")
pset.addPrimitive(operator.add, [int, int], int)
pset.addEphemeralConstant("E1", lambda: 2, int)
expr = gp.genFull(pset, min_=1, max_=1)
ind = creator.IndTree(expr)
ind.fitness.values = (1.0,)
ind_s = pickle.dumps(ind, pickle.HIGHEST_PROTOCOL)
ind_l = pickle.loads(ind_s)
msg = "Unpickled individual %s != pickled individual %s" % (str(ind), str(ind_l))
self.assertEqual(ind, ind_l, msg)
msg = "Unpickled fitness %s != pickled fitness %s" % (str(ind.fitness), str(ind_l.fitness))
self.assertEqual(ind.fitness, ind_l.fitness, msg)
def test_pickle_population(self):
ind1 = creator.IndList([1.0,2.0,3.0])
ind1.fitness.values = (1.0,)
ind2 = creator.IndList([4.0,5.0,6.0])
ind2.fitness.values = (2.0,)
ind3 = creator.IndList([7.0,8.0,9.0])
ind3.fitness.values = (3.0,)
pop = [ind1, ind2, ind3]
pop_s = pickle.dumps(pop)
pop_l = pickle.loads(pop_s)
self.assertEqual(pop[0], pop_l[0], "Unpickled individual list != pickled individual list")
self.assertEqual(pop[0].fitness, pop_l[0].fitness, "Unpickled individual fitness != pickled individual fitness")
self.assertEqual(pop[1], pop_l[1], "Unpickled individual list != pickled individual list")
self.assertEqual(pop[1].fitness, pop_l[1].fitness, "Unpickled individual fitness != pickled individual fitness")
self.assertEqual(pop[2], pop_l[2], "Unpickled individual list != pickled individual list")
self.assertEqual(pop[2].fitness, pop_l[2].fitness, "Unpickled individual fitness != pickled individual fitness")
# @unittest.skipIf(platform.python_implementation() == "PyPy", "PyPy support for pickling ndarrays (thus stats) is very unstable.")
def test_pickle_logbook(self):
stats = tools.Statistics()
logbook = tools.Logbook()
stats.register("mean", numpy.mean)
record = stats.compile([1,2,3,4,5,6,8,9,10])
logbook.record(**record)
logbook_s = pickle.dumps(logbook)
logbook_r = pickle.loads(logbook_s)
self.assertEqual(logbook, logbook_r, "Unpickled logbook != pickled logbook")
@unittest.skipIf(sys.version_info < (2, 7), "Skipping test because Python version < 2.7 does not pickle partials.")
def test_pickle_partial(self):
func_s = pickle.dumps(self.toolbox.func)
func_l = pickle.loads(func_s)
self.assertEqual(self.toolbox.func(), func_l())
if __name__ == "__main__":
suite = unittest.TestLoader().loadTestsFromTestCase(Pickling)
unittest.TextTestRunner(verbosity=2).run(suite)
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