def test_copy_from_and_mutate_does_not_influence_another_condition(
self, cfg):
""" Verify that not just reference to Condition copied (changing which
will change the original - definitily not original C++ code did). """
# given
s = cfg.mu * 0.5 # less then MU
b = 1 - (1 - cfg.mu) * 0.5 # more then MU
operation_time = 123
original_cl = Classifier(condition='1###1011', cfg=cfg)
copied_cl = Classifier.copy_from(original_cl, operation_time)
# when
mutate(copied_cl, cfg.mu, RandomMock([s, b, b, b, b]))
# then
assert Condition('####1011') == copied_cl.condition
assert Condition('1###1011') == original_cl.condition
# when
mutate(original_cl, cfg.mu, RandomMock([b, s, b, b, b]))
# then
assert Condition('1####011') == original_cl.condition
assert Condition('####1011') == copied_cl.condition
def test_quality_and_numerosity_influence_parent_selection(self, cfg):
# given
population = ClassifiersList(cfg=cfg)
c0 = Classifier(condition='######00', quality=1, numerosity=1, cfg=cfg)
c1 = Classifier(condition='######01', cfg=cfg)
c2 = Classifier(condition='######10', cfg=cfg)
population.append(c0) # q3num = 1
population.append(c1) # q3num = 0.0625
population.append(c2) # q3num = 0.0625
# when
p1, p2 = roulette_wheel_parents_selection(population,
randomfunc=(RandomMock(
[0.888, 0.999])))
# then
assert c1 == p1
assert c2 == p2
# when
p1, p2 = roulette_wheel_parents_selection(population,
randomfunc=(RandomMock(
[0.888, 0.777])))
# then
assert c0 == p1
assert c1 == p2
def test_delete_ga_classifiers(self, cfg):
# given
cl_1 = Classifier(action=1, cfg=cfg)
cl_2 = Classifier(action=2, numerosity=20, cfg=cfg)
cl_3 = Classifier(action=3, cfg=cfg)
cl_4 = Classifier(action=4, cfg=cfg)
action_set = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
match_set = ClassifiersList(*[cl_2], cfg=cfg)
population = ClassifiersList(*[cl_1, cl_2, cl_3, cl_4], cfg=cfg)
# when
action_set.delete_ga_classifiers(population,
match_set,
2,
randomfunc=RandomMock(
([0.5, 0.1] + [0.5] * 19) * 3))
expected_action_set = ClassifiersList(
*[cl_1, Classifier(action=2, numerosity=17, cfg=cfg)], cfg=cfg)
expected_match_set = ClassifiersList(
*[Classifier(action=2, numerosity=17, cfg=cfg)], cfg=cfg)
expected_population = ClassifiersList(
*[cl_1,
Classifier(action=2, numerosity=17, cfg=cfg), cl_3, cl_4],
cfg=cfg)
# then
assert expected_action_set == action_set
assert expected_match_set == match_set
assert expected_population == population
def test_delete_a_classifier_decrease_numerosity(self, cfg):
# given
cl_1 = Classifier(action=1, cfg=cfg)
cl_2 = Classifier(action=2, numerosity=3, cfg=cfg)
cl_3 = Classifier(action=3, cfg=cfg)
cl_4 = Classifier(action=4, cfg=cfg)
action_set = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
match_set = ClassifiersList(*[cl_2], cfg=cfg)
population = ClassifiersList(*[cl_1, cl_2, cl_3, cl_4], cfg=cfg)
# when
action_set.delete_a_classifier(match_set,
population,
randomfunc=RandomMock(
[0.5, 0.1, 0.5, 0.5]))
expected_action_set = ClassifiersList(
*[cl_1, Classifier(action=2, numerosity=2, cfg=cfg)], cfg=cfg)
expected_match_set = ClassifiersList(
*[Classifier(action=2, numerosity=2, cfg=cfg)], cfg=cfg)
expected_population = ClassifiersList(
*[cl_1,
Classifier(action=2, numerosity=2, cfg=cfg), cl_3, cl_4],
cfg=cfg)
# then
assert expected_action_set == action_set
assert expected_match_set == match_set
assert expected_population == population
def test_apply_ga(self, cfg):
# given
cl_1 = Classifier(condition='#1#1#1#1', numerosity=12, cfg=cfg)
cl_2 = Classifier(condition='0#0#0#0#', numerosity=9, cfg=cfg)
action_set = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
match_set = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
population = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
random_sequence = \
[
0.1, 0.6, # parent selection
0.1, 0.5, 0.5, 0.5, # mutation of child1
0.5, 0.1, 0.5, 0.5, # mutation of child2
0.1, # do crossover
] + [0.5] * 12 + [0.2] + [0.5] * 8 + \
[0.2] + [0.5] * 20 + [0.2] + [0.5] * 20
# when
action_set.apply_ga(101,
population,
match_set,
None,
randomfunc=RandomMock(random_sequence),
samplefunc=SampleMock([0, 4]))
# then
modified_parent1 = Classifier(condition='#1#1#1#1',
numerosity=10,
tga=101,
cfg=cfg)
modified_parent2 = Classifier(condition='0#0#0#0#',
numerosity=8,
tga=101,
cfg=cfg)
child1 = Classifier(condition='0####1#1',
quality=0.25,
talp=101,
tga=101,
cfg=cfg)
child2 = Classifier(condition='###10#0#',
quality=0.25,
talp=101,
tga=101,
cfg=cfg)
expected_population = ClassifiersList(
*[modified_parent1, modified_parent2, child1, child2], cfg=cfg)
# it might sometime fails because one function RNDG is not mocked
assert expected_population == population
assert expected_population == match_set
assert expected_population == action_set
def test_mutate_2(self, cfg):
# given
cl = Classifier(Condition('##011###'), cfg=cfg)
s = cfg.mu * 0.5 # less then MU
b = 1 - (1 - cfg.mu) * 0.5 # more then MU
# when
mutate(cl, cfg.mu, randomfunc=RandomMock([b, b, s]))
# then
assert Condition('##01####') == cl.condition
def test_should_select_parents1(self, cfg):
# given
population = ClassifiersList(cfg=cfg)
c0 = Classifier(condition='######00', cfg=cfg)
c1 = Classifier(condition='######01', cfg=cfg)
c2 = Classifier(condition='######10', cfg=cfg)
c3 = Classifier(condition='######11', cfg=cfg)
population.append(c0)
population.append(c1)
population.append(c2)
population.append(c3)
# when
p1, p2 = roulette_wheel_parents_selection(population,
randomfunc=(RandomMock(
[0.7, 0.1])))
# then
assert c0 == p1
# when
p1, p2 = roulette_wheel_parents_selection(population,
randomfunc=(RandomMock(
[0.3, 0.6])))
# then
assert c1 == p1
assert c2 == p2
# when
p1, p2 = roulette_wheel_parents_selection(population,
randomfunc=(RandomMock(
[0.2, 0.8])))
# then
assert c0 == p1
assert c3 == p2
def test_select_classifier_to_delete(self, cfg):
# given
selected_first = Classifier(quality=0.5, cfg=cfg)
much_worse = Classifier(quality=0.2, cfg=cfg)
yet_another_to_consider = Classifier(quality=0.2, cfg=cfg)
classifiers = ClassifiersList(*[
Classifier(cfg=cfg), selected_first,
Classifier(cfg=cfg), much_worse, yet_another_to_consider,
Classifier(cfg=cfg)
],
cfg=cfg)
# when
actual_selected = classifiers.select_classifier_to_delete(
randomfunc=RandomMock([0.5, 0.1, 0.5, 0.1, 0.1, 0.5]))
# then
assert much_worse == actual_selected
def test_delete_a_classifier_delete(self, cfg):
# given
cl_1 = Classifier(action=1, cfg=cfg)
cl_2 = Classifier(action=2, cfg=cfg)
cl_3 = Classifier(action=3, cfg=cfg)
cl_4 = Classifier(action=4, cfg=cfg)
action_set = ClassifiersList(*[cl_1, cl_2], cfg=cfg)
match_set = ClassifiersList(*[cl_2], cfg=cfg)
population = ClassifiersList(*[cl_1, cl_2, cl_3, cl_4], cfg=cfg)
# when
action_set.delete_a_classifier(match_set,
population,
randomfunc=RandomMock(
[0.5, 0.1, 0.5, 0.5]))
# then
assert ClassifiersList(*[cl_1], cfg=cfg) == action_set
assert ClassifiersList(cfg=cfg) == match_set
assert ClassifiersList(*[cl_1, cl_3, cl_4], cfg=cfg) == population
def test_randommock_returns_values_in_a_given_sequence(self):
f = RandomMock([0.1, 0.2, 0.3])
assert 0.1 == f()
assert 0.2 == f()
assert 0.3 == f()