class TaskTestCase(TestCase):
r"""Test case for testing the Task class.
Date:
April 2019
Author:
Klemen Berkovič
See Also:
* :class:`niapy.util.Task`
"""
def setUp(self):
self.D, self.nFES, self.nGEN = 10, 10, 10
self.Lower, self.Upper = [2, 1, 1], [10, 10, 5]
self.task = Task(dimension=self.D,
lower=self.Lower,
upper=self.Upper,
problem='sphere',
max_evals=self.nFES,
max_iters=self.nGEN,
cutoff_value=0.0)
def test_dim_ok(self):
self.assertEqual(self.D, self.task.dimension)
self.assertEqual(self.D, self.task.dimension)
def test_lower(self):
self.assertTrue(
np.array_equal(full_array(self.Lower, self.D), self.task.lower))
self.assertTrue(
np.array_equal(full_array(self.Lower, self.D), self.task.lower))
def test_upper(self):
self.assertTrue(
np.array_equal(full_array(self.Upper, self.D), self.task.upper))
self.assertTrue(
np.array_equal(full_array(self.Upper, self.D), self.task.upper))
def test_range(self):
self.assertTrue(
np.array_equal(
full_array(self.Upper, self.D) -
full_array(self.Lower, self.D), self.task.range))
self.assertTrue(
np.array_equal(
full_array(self.Upper, self.D) -
full_array(self.Lower, self.D), self.task.range))
def test_max_iters(self):
self.assertEqual(self.nGEN, self.task.max_iters)
def test_max_evals(self):
self.assertEqual(self.nFES, self.task.max_evals)
def test_is_feasible(self):
x = np.full(self.D, 2)
self.assertTrue(self.task.is_feasible(x))
x = np.full(self.D, 3)
self.assertTrue(self.task.is_feasible(x))
x = default_rng().uniform(self.task.lower, self.task.upper, self.D)
self.assertTrue(self.task.is_feasible(x))
x = np.full(self.D, -20)
self.assertFalse(self.task.is_feasible(x))
x = np.full(self.D, 20)
self.assertFalse(self.task.is_feasible(x))
def test_next_iter(self):
for i in range(self.nGEN):
self.assertFalse(self.task.stopping_condition())
self.task.next_iter()
self.assertTrue(self.task.stopping_condition())
def test_stop_cond_iter(self):
for i in range(self.nGEN):
self.assertFalse(self.task.stopping_condition_iter(),
msg='Error at %s iteration!!!' % i)
self.assertTrue(self.task.stopping_condition_iter())
def test_eval(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.assertAlmostEqual(self.task.eval(x),
self.D,
msg='Error at %s iteration!!!' % i)
self.assertTrue(self.task.stopping_condition())
def test_eval_over_max_evals(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.task.eval(x)
self.assertEqual(np.inf, self.task.eval(x))
self.assertTrue(self.task.stopping_condition())
def test_eval_over_max_iters(self):
x = np.ones(self.D)
for i in range(self.nGEN):
self.task.next_iter()
self.assertEqual(np.inf, self.task.eval(x))
self.assertTrue(self.task.stopping_condition())
def test_evals_count(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.task.eval(x)
self.assertEqual(self.task.evals, i + 1,
'Error at %s. evaluation' % (i + 1))
def test_iters_count(self):
for i in range(self.nGEN):
self.task.next_iter()
self.assertEqual(self.task.iters, i + 1,
'Error at %s. iteration' % (i + 1))
def test_stop_cond_evals(self):
x = np.ones(self.D)
for i in range(self.nFES - 1):
self.task.eval(x)
self.assertFalse(self.task.stopping_condition())
self.task.eval(x)
self.assertTrue(self.task.stopping_condition())
def test_stop_cond_iters(self):
for i in range(self.nGEN - 1):
self.task.next_iter()
self.assertFalse(self.task.stopping_condition())
self.task.next_iter()
self.assertTrue(self.task.stopping_condition())
def test_stop_cond_cutoff_value(self):
x = np.ones(self.D)
for i in range(self.nGEN - 5):
self.assertFalse(self.task.stopping_condition())
self.assertEqual(self.D, self.task.eval(x))
self.task.next_iter()
x = np.zeros(self.D)
self.assertEqual(0, self.task.eval(x))
self.assertTrue(self.task.stopping_condition())
self.assertEqual(self.nGEN - 5, self.task.iters)
def test_print_conv_one(self):
r1, r2 = [], []
for i in range(self.nFES):
x = np.full(self.D, 10 - i)
r1.append(i + 1), r2.append(self.task.eval(x))
t_r1, t_r2 = self.task.return_conv()
self.assertTrue(np.array_equal(r1, t_r1))
self.assertTrue(np.array_equal(r2, t_r2))
def test_print_conv_two(self):
r1, r2 = [], []
for i in range(self.nFES):
x = np.full(self.D, 10 - i if i not in (3, 4, 5) else 4)
r1.append(i + 1), r2.append(self.task.eval(x))
t_r1, t_r2 = self.task.return_conv()
self.assertTrue(np.array_equal(r2, t_r2))
self.assertTrue(np.array_equal(r1, t_r1))
# encoding=utf8
# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys
sys.path.append('../')
# End of fix
from niapy.task import Task
from niapy.problems import Sphere
from niapy.algorithms.basic import DifferentialEvolution
# Storing improvements during the evolutionary cycle
task = Task(max_evals=10000, problem=Sphere(dimension=10))
algo = DifferentialEvolution(population_size=40,
crossover_probability=0.9,
differential_weight=0.5)
best = algo.run(task)
evals, x_f = task.return_conv()
print(evals) # print function evaluations
print(x_f) # print values
