def test_generate_solution(self):
"""Test random solution generating."""
expected_min_day_size = 125
expected_max_day_size = 300
real_data_path = 'data/family_data.csv'
dfs = [get_df_families(1000, 20)]
if os.path.isfile(real_data_path):
dfs.append(pd.read_csv(real_data_path))
for df_families in dfs:
antibody = Antibody()
antibody.generate_solution(df_families)
day_sizes = {}
for i, day in enumerate(antibody.families):
value = day_sizes.get(day, 0)
day_sizes[day] = value + df_families.iloc[i]['n_people']
for key, size in antibody.days.items():
expected_day_size = day_sizes[key]
self.assertTrue(
expected_min_day_size <= size <= expected_max_day_size,
msg=f'Number of people scheduled for `{key + 1}th` day is '
f'`{size}`, expected to be '
f'in `<{expected_min_day_size}, '
f'{expected_max_day_size}>`.'
)
self.assertEqual(
size,
expected_day_size,
msg=f'Number of people scheduled for `{key + 1}th` day is '
f'{size}, expected `{expected_day_size}`.'
)
def test_basic_mutate_solutions(self):
"""
Test whether created `Antibody` was mutated by `BasicMutator`
class.
"""
fitness_value = 125
n_mutations = 5
n_performed_mutations = 0
n_families, family_size = 1000, 20
df_families = get_df_families(n_families, family_size)
antibody = Antibody()
antibody.generate_solution(df_families)
antibody.fitness_value = fitness_value
basic_mutator = BasicMutator()
mutated_antibody = basic_mutator.mutate([[copy.deepcopy(antibody)]],
df_families=df_families)[0][0]
for i in range(n_families):
if antibody.families[i] != mutated_antibody.families[i]:
n_performed_mutations += 1
self.assertEqual(
n_mutations,
n_performed_mutations,
msg=f'Number of mutations was `{n_performed_mutations}`, expected '
f'`{n_mutations}`.')
def test_preference_mutate_solutions(self):
"""
Test whether created `Antibody` was mutated by
`PreferenceMutator` and `AdvancedPreferenceMutator` classes.
"""
fitness_value = 125
n_mutations = 5
n_performed_mutations, n_advanced_performed_mutations = 0, 0
n_families, family_size = 1000, 20
df_families = get_df_families(n_families, family_size)
antibody = Antibody()
antibody.generate_solution(df_families)
antibody.fitness_value = fitness_value
preference_mutator = PreferenceMutator()
mutated_antibody = preference_mutator.mutate(
[[copy.deepcopy(antibody)]], df_families=df_families)[0][0]
advanced_preference_mutator = AdvancedPreferenceMutator()
advanced_mutated_antibody = advanced_preference_mutator.mutate(
[[copy.deepcopy(antibody)]], df_families=df_families)[0][0]
families_choices = df_families[[f'choice_{i}' for i in range(10)]] \
.values
for i in range(n_families):
if antibody.families[i] != mutated_antibody.families[i]:
n_performed_mutations += 1
self.assertTrue(
mutated_antibody.families[i] in families_choices[i],
msg=f'Day mutated family is going to workshop is '
f'{mutated_antibody.families[i]}, expected one of '
f'{families_choices[i]}.')
if antibody.families[i] != advanced_mutated_antibody.families[i]:
n_advanced_performed_mutations += 1
self.assertTrue(
advanced_mutated_antibody.families[i]
in families_choices[i],
msg=f'Day advanced mutated family is going to workshop is '
f'{advanced_mutated_antibody.families[i]}, expected '
f'one of {families_choices[i]}.')
self.assertEqual(
n_mutations,
n_performed_mutations,
msg=f'Number of mutations was `{n_performed_mutations}`, expected '
f'`{n_mutations}`.')
self.assertEqual(n_mutations,
n_advanced_performed_mutations,
msg=f'Number of advanced mutations was '
f'`{n_advanced_performed_mutations}`, expected '
f'`{n_mutations}`.')