def test_sort_population(optim):
ga = StandardGA(fitness_test_sin_func, optim=optim)
ga.population = list(unsorted_population)
ga._sort_population()
required_population = sort_population(optim, list(unsorted_population))
assert ga.population == required_population
def test_sort_population(optim):
ga = StandardGA(fitness_test_sin_func, optim=optim)
ga.population = list(unsorted_population)
ga._sort_population()
required_population = sort_population(optim, list(unsorted_population))
assert ga.population == required_population
def test_extend_population():
ga = StandardGA(fitness_test_sin_func, optim='min')
ga.population = [IndividualGA(1, 100)]
new_elems = [IndividualGA(2, 50), IndividualGA(3, 150)]
ga.extend_population(new_elems)
assert ga.best_solution == (2, 50)
result = []
for i, individ in zip(range(len(ga.population)), ga.population):
result.append((individ.chromosome, individ.fitness_val))
assert result == [(3, 150), (1, 100), (2, 50)]
def test_extend_population():
ga = StandardGA(fitness_test_sin_func, optim='min')
ga.population = [IndividualGA(1, 100)]
new_elems = [IndividualGA(2, 50), IndividualGA(3, 150)]
ga.extend_population(new_elems)
assert ga.best_solution == (2, 50)
result = []
for i, individ in zip(range(len(ga.population)), ga.population):
result.append((individ.chromosome, individ.fitness_val))
assert result == [(3, 150), (1, 100), (2, 50)]