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""" Test the MOArchive3obj class """
from moarchiving.moarchiving3obj import MOArchive3obj
from moarchiving.moarchiving_utils import DLNode, my_lexsort
from moarchiving.moarchiving import BiobjectiveNondominatedSortedList as MOArchive2obj
from moarchiving.tests.point_sampling import (get_non_dominated_points, get_random_points,
get_stacked_points)
import unittest
import math
import random
def list_to_set(lst):
return set([tuple(p) for p in lst])
class TestMOArchiving3obj(unittest.TestCase):
def test_hypervolume_easy(self):
""" test the hypervolume calculation for a simple case """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa = MOArchive3obj(points, reference_point=[4, 4, 4], infos=["A", "B", "C"])
self.assertEqual(moa.hypervolume, 13)
def test_infos_non_dominated(self):
""" test if the infos are stored correctly - if the points are non dominated,
the infos should be the same """
points = [
[1, 2, 3],
[3, 2, 1],
[2, 3, 1],
[1, 3, 2]
]
infos = [str(p) for p in points]
moa = MOArchive3obj(points, [6, 6, 6], infos)
# assert that the infos are stored in the same order as the points
self.assertEqual([str(p[:3]) for p in moa], moa.infos)
# assert that all the points in the archive are non dominated and thus have the same info
self.assertSetEqual(set([str(p) for p in points]), set(moa.infos))
def test_infos_dominated(self):
""" test if the infos about dominated points are removed """
points = [
[1, 2, 3],
[3, 2, 1],
[2, 3, 4],
[2, 1, 0]
]
infos = ["A", "B", "C", "D"]
moa = MOArchive3obj(points, [6, 6, 6], infos)
# assert that only points A and D are stored in the archive
self.assertSetEqual({"A", "D"}, set(moa.infos))
def test_in_domain(self):
""" test if the in_domain function works correctly """
ref_point = [6, 6, 6]
moa = MOArchive3obj([[1, 1, 1]], ref_point)
# test if the points are in the domain
self.assertTrue(moa.in_domain([1, 2, 3]))
self.assertTrue(moa.in_domain([5.9, 5.9, 5.9]))
# test if the point is not in the domain
self.assertFalse(moa.in_domain([7, 8, 9]))
self.assertFalse(moa.in_domain([6, 6, 6]))
self.assertFalse(moa.in_domain([0, 0, 6]))
def test_add(self):
""" test if the add_points function works correctly """
ref_point = [6, 6, 6]
start_points = [[1, 2, 5], [3, 5, 1], [5, 1, 4]]
moa_ref = MOArchive3obj(start_points, ref_point)
moa_no_ref = MOArchive3obj(start_points)
for moa in [moa_ref, moa_no_ref]:
# add point that is not dominated and does not dominate any other point
u1 = [2, 3, 3]
moa.add(u1)
self.assertSetEqual(list_to_set(start_points + [u1]), list_to_set(list(moa)))
# add point that is dominated by another point in the archive
u2 = [4, 5, 2]
moa.add(u2)
self.assertSetEqual(list_to_set(start_points + [u1]), list_to_set(list(moa)))
# add point that dominates another point in the archive
u3 = [3, 1, 2]
moa.add(u3)
self.assertSetEqual(list_to_set(start_points[:2] + [u1, u3]), list_to_set(list(moa)))
def test_hypervolume_after_add(self):
""" Calculate the hypervolume of the archive after adding points and compare it to the
hypervolume obtained by adding the points to a new archive """
ref_point = [1, 1, 1]
pop_size = 20
n_gen = 4
points = get_non_dominated_points(pop_size * n_gen)
for gen in range(1, n_gen + 1):
moa_true = MOArchive3obj(points[:(gen * pop_size)], ref_point)
true_hv = moa_true.hypervolume
moa_add = MOArchive3obj([], ref_point)
for i in range(gen * pop_size):
moa_add.add(points[i])
moa_add_gen = MOArchive3obj([], ref_point)
for i in range(gen):
moa_add_gen.add_list(points[(i * pop_size):((i + 1) * pop_size)])
self.assertAlmostEqual(moa_add.hypervolume, true_hv, places=6)
self.assertAlmostEqual(moa_add_gen.hypervolume, true_hv, places=6)
self.assertEqual(len(moa_add), len(moa_true))
self.assertEqual(len(moa_add_gen), len(moa_true))
def test_length(self):
""" Test that the length of the archive is correct after adding and removing points """
ref_point = [1, 1, 1]
n_points_add = 100
points = get_stacked_points(n_points_add, ['random', 'random', 'random'])
moa = MOArchive3obj([], ref_point)
# add points one by one
for point in points:
moa.add(point)
self.assertEqual(len(moa), len(list(moa)))
# remove points one by one
points = list(moa)
for point in points:
moa.remove(point)
self.assertEqual(len(moa), len(list(moa)))
def test_dominates(self):
""" Test the dominates function """
ref_point = [6, 6, 6]
points = [[1, 3, 5], [5, 3, 1], [4, 4, 4]]
moa = MOArchive3obj(points, ref_point)
# test that the points that are already in the archive are dominated
for p in points:
self.assertTrue(moa.dominates(p))
# test other dominated points
self.assertTrue(moa.dominates([5, 5, 5]))
self.assertTrue(moa.dominates([2, 4, 5]))
# test non dominated points
self.assertFalse(moa.dominates([3, 3, 3]))
self.assertFalse(moa.dominates([2, 5, 4]))
self.assertFalse(moa.dominates([5, 1, 3]))
def test_dominators(self):
""" Test the dominators function """
ref_point = [6, 6, 6]
points = [[1, 2, 3], [3, 1, 2], [2, 3, 1], [3, 2, 1], [2, 1, 3], [1, 3, 2]]
moa = MOArchive3obj(points, ref_point)
# test that the points that are already in the archive are dominated by itself
for p in points:
self.assertEqual([p], moa.dominators(p))
self.assertEqual(1, moa.dominators(p, number_only=True))
# test other dominated points
self.assertEqual(list_to_set([[1, 2, 3], [2, 3, 1], [2, 1, 3], [1, 3, 2]]),
list_to_set(moa.dominators([2, 3, 4])))
self.assertEqual(4, moa.dominators([2, 3, 4], number_only=True))
self.assertEqual([], moa.dominators([2, 2, 2]))
self.assertEqual(0, moa.dominators([2, 2, 2], number_only=True))
self.assertEqual(list_to_set(points), list_to_set(moa.dominators([3, 3, 3])))
self.assertEqual(6, moa.dominators([3, 3, 3], number_only=True))
def test_distance_to_hypervolume_area(self):
""" Test the distance_to_hypervolume_area function first for a case where the
reference point is not set, then for points in and outside the hypervolume area
"""
moa = MOArchive3obj()
self.assertEqual(0, moa.distance_to_hypervolume_area([1, 1, 1]))
moa.reference_point = [2, 2, 2]
# for points in the hypervolume area, the distance should be 0
self.assertEqual(0, moa.distance_to_hypervolume_area([0, 0, 0]))
self.assertEqual(0, moa.distance_to_hypervolume_area([1, 1, 1]))
self.assertEqual(0, moa.distance_to_hypervolume_area([2, 2, 2]))
self.assertEqual(0, moa.distance_to_hypervolume_area([0, 1, 2]))
# for points outside the hypervolume area, the distance should be the Euclidean distance
# to the hypervolume area
self.assertEqual(1, moa.distance_to_hypervolume_area([2, 2, 3]))
self.assertEqual(1, moa.distance_to_hypervolume_area([2, 0, 3]))
self.assertEqual(10, moa.distance_to_hypervolume_area([0, 0, 12]))
self.assertAlmostEqual(math.sqrt(2), moa.distance_to_hypervolume_area([0, 3, 3]), places=6)
self.assertAlmostEqual(math.sqrt(2), moa.distance_to_hypervolume_area([2, 3, 3]), places=6)
self.assertAlmostEqual(math.sqrt(3), moa.distance_to_hypervolume_area([3, 3, 3]), places=6)
self.assertAlmostEqual(math.sqrt(75), moa.distance_to_hypervolume_area([7, 7, 7]), places=6)
def test_distance_to_pareto_front_simple(self):
""" Test the distance_to_pareto_front function by comparing it to hand calculated values """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa = MOArchive3obj(points, reference_point=[6, 6, 6])
self.assertEqual(0, moa.distance_to_pareto_front([1, 1, 1]))
self.assertEqual(3 ** 0.5, moa.distance_to_pareto_front([4, 4, 4]))
self.assertEqual((1 + 1 + 6 ** 2) ** 0.5, moa.distance_to_pareto_front([7, 7, 7]))
self.assertEqual(0, moa.distance_to_pareto_front([2, 4, 3]))
self.assertEqual(0, moa.distance_to_pareto_front([3, 2, 4]))
self.assertEqual(1, moa.distance_to_pareto_front([3, 3, 4]))
def test_distance_to_pareto_front_compare_2obj(self):
""" Test the distance_to_pareto_front function by comparing it to the 2obj version """
n_points = 100
n_test_points = 100
points = get_stacked_points(n_points, ['random', 'random', 0])
moa3obj = MOArchive3obj(points, reference_point=[1, 1, 1])
moa2obj = MOArchive2obj([[p[0], p[1]] for p in points], reference_point=[1, 1])
new_points = get_stacked_points(n_test_points, ['random', 'random', 1])
for point in new_points:
d2 = moa2obj.distance_to_pareto_front(point[:2])
d3 = moa3obj.distance_to_pareto_front(point)
self.assertAlmostEqual(d2, d3, places=8)
def test_copy_DLNode(self):
""" Test the copy function of the DLNode class """
n1 = DLNode([1, 2, 3, 4], "node 1")
n2 = DLNode([5, 6, 7, 8], "node 2")
n1.closest[1] = n2
n2.closest[0] = n1
n1_copy = n1.copy()
n2_copy = n2.copy()
n2_copy.x = [-1, -2, -3, -4]
n1.x[0] = 10
n1.closest[1] = n1
self.assertEqual(n1_copy.x[0], 1)
self.assertEqual(n1_copy.closest[1].x[0], 5)
self.assertEqual(n2.x[0], 5)
self.assertEqual(n2_copy.x[0], -1)
def test_copy_MOArchive(self):
""" Test the copy function of the MOArchive3obj class """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa = MOArchive3obj(points, reference_point=[6, 6, 6])
moa_copy = moa.copy()
self.assertEqual(moa.hypervolume, moa_copy.hypervolume)
moa.add([2, 2, 2])
self.assertEqual(len(moa), 4)
self.assertEqual(len(moa_copy), 3)
self.assertFalse(moa.hypervolume == moa_copy.hypervolume)
def test_remove(self, n_points=100, n_points_remove=50):
""" Test the remove function, by comparing the archive with 100 points added and then
50 removed, to the with only the other 50 points added """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa_remove = MOArchive3obj(points, reference_point=[6, 6, 6])
moa_remove.remove([1, 2, 3])
self.assertEqual(len(moa_remove), 2)
self.assertSetEqual(list_to_set(list(moa_remove)), list_to_set(points[1:]))
self.assertEqual(moa_remove.hypervolume,
MOArchive3obj(points[1:], reference_point=[6, 6, 6]).hypervolume)
points = get_non_dominated_points(n_points)
remove_idx = list(range(n_points_remove))
keep_idx = [i for i in range(n_points) if i not in remove_idx]
moa_true = MOArchive3obj([points[i] for i in keep_idx], reference_point=[1, 1, 1])
moa_remove = MOArchive3obj(points, reference_point=[1, 1, 1])
for i in remove_idx:
moa_remove.remove(points[i])
self.assertEqual(len(moa_remove), len(list(moa_remove)))
moa_add = MOArchive3obj([], reference_point=[1, 1, 1])
for i in keep_idx:
moa_add.add(points[i])
# assert that the points are the same in all archives and the hypervolume is the same
self.assertEqual(len(moa_add), len(moa_true))
self.assertEqual(len(moa_remove), len(moa_true))
self.assertSetEqual(list_to_set(list(moa_remove)), list_to_set(list(moa_true)))
self.assertSetEqual(list_to_set(list(moa_add)), list_to_set(list(moa_true)))
self.assertEqual(moa_remove.hypervolume, moa_true.hypervolume)
self.assertEqual(moa_add.hypervolume, moa_true.hypervolume)
moa = MOArchive3obj([[1, 2, 3], [2, 3, 1], [3, 1, 2]], reference_point=[6, 6, 6])
moa.add([1, 1, 1])
moa.remove([1, 1, 1])
self.assertEqual(len(moa), 0)
def test_contributing_hypervolume(self):
""" Test the contributing_hypervolume function first for a simple case, and then
compare it to the 2obj version, with one objective set to 0 """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa = MOArchive3obj(points, reference_point=[4, 4, 4])
self.assertEqual(moa.contributing_hypervolume([1, 2, 3]), 3)
self.assertEqual(moa.contributing_hypervolume([2, 3, 1]), 3)
self.assertEqual(moa.contributing_hypervolume([3, 1, 2]), 3)
points = [[1, 2, 3], [1, 3, 2], [2, 1, 3], [2, 3, 1], [3, 1, 2], [3, 2, 1]]
moa = MOArchive3obj(points, reference_point=[4, 4, 4])
for p in points:
self.assertEqual(moa.contributing_hypervolume(list(p)), 1)
points = get_stacked_points(100, ['random', 'random', 0])
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
moa2obj = MOArchive2obj([[p[0], p[1]] for p in points], reference_point=[1, 1])
for p in moa2obj:
self.assertAlmostEqual(moa.contributing_hypervolume(p + [0]),
moa2obj.contributing_hypervolume(p), places=8)
def test_hypervolume_improvement(self):
""" Test the hypervolume_improvement function first for a simple case, and then
compare it to the 2obj version, with one objective set to 0 """
points = [[1, 2, 3], [2, 3, 1], [3, 1, 2]]
moa = MOArchive3obj(points, reference_point=[4, 4, 4])
self.assertEqual(moa.hypervolume_improvement([1, 2, 3]), 0)
self.assertEqual(moa.hypervolume_improvement([2, 3, 1]), 0)
self.assertEqual(moa.hypervolume_improvement([3, 1, 2]), 0)
self.assertEqual(moa.hypervolume_improvement([4, 4, 4]),
-moa.distance_to_pareto_front([4, 4, 4]))
self.assertEqual(moa.hypervolume_improvement([1, 1, 1]), 14)
self.assertEqual(moa.hypervolume_improvement([2, 2, 2]), 1)
points = get_stacked_points(100, ['random', 'random', 0])
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
moa2obj = MOArchive2obj([[p[0], p[1]] for p in points], reference_point=[1, 1])
new_points = get_random_points(100, 2)
hv_start = moa.hypervolume
for p in new_points:
hv_imp2obj = float(moa2obj.hypervolume_improvement(p))
if hv_imp2obj > 0:
self.assertAlmostEqual(hv_imp2obj, moa.hypervolume_improvement(p + [0]), places=8)
else:
self.assertAlmostEqual(hv_imp2obj, moa.hypervolume_improvement(p + [1]), places=8)
# make sure this doesn't change the hypervolume of the archive
hv_end = moa.hypervolume
self.assertAlmostEqual(hv_start, hv_end, places=8)
def test_get_non_dominated_points(self):
""" Test the get_non_dominated_points function:
- check if the number of points is correct
- check if the points are non-dominated and in the [0, 1] range """
n_points = 1000
for mode in ['spherical', 'linear']:
points = get_non_dominated_points(n_points, mode=mode)
self.assertEqual(len(points), n_points)
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
self.assertEqual(len(moa), n_points)
self.assertSetEqual(list_to_set(points), list_to_set(moa))
def test_lexsort(self):
""" Test the lexsort function, by comparing it to the output of the numpy implementation """
points = [
[0.16, 0.86, 0.47],
[0.66, 0.37, 0.29],
[0.79, 0.79, 0.04],
[0.28, 0.99, 0.29],
[0.51, 0.37, 0.38],
[0.92, 0.62, 0.07],
[0.16, 0.53, 0.70],
[0.01, 0.98, 0.94],
[0.67, 0.17, 0.54],
[0.79, 0.72, 0.05]
]
my_lexsort_result = my_lexsort(([p[0] for p in points], [p[1] for p in points],
[p[2] for p in points]))
np_lexsort_result = [2, 9, 5, 1, 3, 4, 0, 8, 6, 7]
self.assertEqual(my_lexsort_result, np_lexsort_result)
points = [
[0.6394267984578837, 0.025010755222666936, 0.27502931836911926],
[0.22321073814882275, 0.7364712141640124, 0.6766994874229113],
[0.8921795677048454, 0.08693883262941615, 0.4219218196852704],
[0.029797219438070344, 0.21863797480360336, 0.5053552881033624],
[0.026535969683863625, 0.1988376506866485, 0.6498844377795232],
[0.5449414806032167, 0.2204406220406967, 0.5892656838759087],
[0.8094304566778266, 0.006498759678061017, 0.8058192518328079],
[0.6981393949882269, 0.3402505165179919, 0.15547949981178155],
[0.9572130722067812, 0.33659454511262676, 0.09274584338014791],
[0.09671637683346401, 0.8474943663474598, 0.6037260313668911]
]
my_lexsort_result = my_lexsort(([p[0] for p in points], [p[1] for p in points],
[p[2] for p in points]))
np_lexsort_result = [8, 7, 0, 2, 3, 5, 9, 4, 1, 6]
self.assertEqual(my_lexsort_result, np_lexsort_result)
def test_hypervolume_plus(self):
""" test the hypervolume_plus indicator """
moa = MOArchive3obj(reference_point=[1, 1, 1])
self.assertEqual(moa.hypervolume_plus, -float('inf'))
moa.add([2, 2, 2])
self.assertEqual(moa.hypervolume_plus, -math.sqrt(3))
moa.add_list([[0, 0, 5], [1, 2, 1], [3, 3, 2]])
self.assertEqual(moa.hypervolume_plus, -1)
moa.add([1, 1, 1])
self.assertEqual(moa.hypervolume_plus, 0)
moa.add([0.5, 0.5, 0.5])
self.assertEqual(moa.hypervolume_plus, moa.hypervolume)
moa = MOArchive3obj(reference_point=[1, 1, 1])
prev_hv_plus = moa.hypervolume_plus
for i in range(1000):
point = [10 * random.random(), 10 * random.random(), 10 * random.random()]
moa.add(point)
self.assertLessEqual(prev_hv_plus, moa.hypervolume_plus)
prev_hv_plus = moa.hypervolume_plus
def test_hypervolume(self):
""" test the hypervolume calculation, by comparing to the result of original
implementation in C"""
points = [
[0.16, 0.86, 0.47],
[0.66, 0.37, 0.29],
[0.79, 0.79, 0.04],
[0.28, 0.99, 0.29],
[0.51, 0.37, 0.38],
[0.92, 0.62, 0.07],
[0.16, 0.53, 0.70],
[0.01, 0.98, 0.94],
[0.67, 0.17, 0.54],
[0.79, 0.72, 0.05]
]
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
self.assertAlmostEqual(moa.hypervolume, 0.318694, places=6)
self.assertEqual(moa.hypervolume_plus, moa.hypervolume)
points = [
[0.6394267984578837, 0.025010755222666936, 0.27502931836911926],
[0.22321073814882275, 0.7364712141640124, 0.6766994874229113],
[0.8921795677048454, 0.08693883262941615, 0.4219218196852704],
[0.029797219438070344, 0.21863797480360336, 0.5053552881033624],
[0.026535969683863625, 0.1988376506866485, 0.6498844377795232],
[0.5449414806032167, 0.2204406220406967, 0.5892656838759087],
[0.8094304566778266, 0.006498759678061017, 0.8058192518328079],
[0.6981393949882269, 0.3402505165179919, 0.15547949981178155],
[0.9572130722067812, 0.33659454511262676, 0.09274584338014791],
[0.09671637683346401, 0.8474943663474598, 0.6037260313668911]
]
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
self.assertAlmostEqual(moa.hypervolume, 0.52192086148367, places=6)
self.assertEqual(moa.hypervolume_plus, moa.hypervolume)
points = [
[0.6394267984578837, 0.025010755222666936, 0.27502931836911926],
[0.22321073814882275, 0.7364712141640124, 0.6766994874229113],
[0.8921795677048454, 0.08693883262941615, 0.4219218196852704],
[0.029797219438070344, 0.21863797480360336, 0.5053552881033624],
[0.026535969683863625, 0.1988376506866485, 0.6498844377795232],
[0.5449414806032167, 0.2204406220406967, 0.5892656838759087],
[0.8094304566778266, 0.006498759678061017, 0.8058192518328079],
[0.6981393949882269, 0.3402505165179919, 0.15547949981178155],
[0.9572130722067812, 0.33659454511262676, 0.09274584338014791],
[0.09671637683346401, 0.8474943663474598, 0.6037260313668911],
[0.8071282732743802, 0.7297317866938179, 0.5362280914547007],
[0.9731157639793706, 0.3785343772083535, 0.552040631273227],
[0.8294046642529949, 0.6185197523642461, 0.8617069003107772],
[0.577352145256762, 0.7045718362149235, 0.045824383655662215],
[0.22789827565154686, 0.28938796360210717, 0.0797919769236275],
[0.23279088636103018, 0.10100142940972912, 0.2779736031100921],
[0.6356844442644002, 0.36483217897008424, 0.37018096711688264],
[0.2095070307714877, 0.26697782204911336, 0.936654587712494],
[0.6480353852465935, 0.6091310056669882, 0.171138648198097],
[0.7291267979503492, 0.1634024937619284, 0.3794554417576478],
[0.9895233506365952, 0.6399997598540929, 0.5569497437746462],
[0.6846142509898746, 0.8428519201898096, 0.7759999115462448],
[0.22904807196410437, 0.03210024390403776, 0.3154530480590819],
[0.26774087597570273, 0.21098284358632646, 0.9429097143350544],
[0.8763676264726689, 0.3146778807984779, 0.65543866529488],
[0.39563190106066426, 0.9145475897405435, 0.4588518525873988],
[0.26488016649805246, 0.24662750769398345, 0.5613681341631508],
[0.26274160852293527, 0.5845859902235405, 0.897822883602477],
[0.39940050514039727, 0.21932075915728333, 0.9975376064951103],
[0.5095262936764645, 0.09090941217379389, 0.04711637542473457],
[0.10964913035065915, 0.62744604170309, 0.7920793643629641],
[0.42215996679968404, 0.06352770615195713, 0.38161928650653676],
[0.9961213802400968, 0.529114345099137, 0.9710783776136181],
[0.8607797022344981, 0.011481021942819636, 0.7207218193601946],
[0.6817103690265748, 0.5369703304087952, 0.2668251899525428],
[0.6409617985798081, 0.11155217359587644, 0.434765250669105],
[0.45372370632920644, 0.9538159275210801, 0.8758529403781941],
[0.26338905075109076, 0.5005861130502983, 0.17865188053013137],
[0.9126278393448205, 0.8705185698367669, 0.2984447914486329],
[0.6389494948660052, 0.6089702114381723, 0.1528392685496348],
[0.7625108000751513, 0.5393790301196257, 0.7786264786305582],
[0.5303536721951775, 0.0005718961279435053, 0.3241560570046731],
[0.019476742385832302, 0.9290986162646171, 0.8787218778231842],
[0.8316655293611794, 0.30751412540266143, 0.05792516649418755],
[0.8780095992040405, 0.9469494452979941, 0.08565345206787878],
[0.4859904633166138, 0.06921251846838361, 0.7606021652572316],
[0.7658344293069878, 0.1283914644997628, 0.4752823780987313],
[0.5498035934949439, 0.2650566289400591, 0.8724330410852574],
[0.4231379402008869, 0.21179820544208205, 0.5392960887794583],
[0.7299310690899762, 0.2011510633896959, 0.31171629130089495],
[0.9951493566608947, 0.6498780576394535, 0.43810008391450406],
[0.5175758410355906, 0.12100419586826572, 0.22469733703155736],
[0.33808556214745533, 0.5883087184572333, 0.230114732596577],
[0.22021738445155947, 0.07099308600903254, 0.6311029572700989],
[0.22894178381115438, 0.905420013006128, 0.8596354002537465],
[0.07085734988865344, 0.23800463436899522, 0.6689777782962806],
[0.2142368073704386, 0.132311848725025, 0.935514240580671],
[0.5710430933252845, 0.47267102631179414, 0.7846194242907534],
[0.8074969977666434, 0.1904099143618777, 0.09693081422882333],
[0.4310511824063775, 0.4235786230199208, 0.467024668036675],
[0.7290758494598506, 0.6733645472933015, 0.9841652113659661],
[0.09841787115195888, 0.4026212821022688, 0.33930260539496315],
[0.8616725363527911, 0.24865633392028563, 0.1902089084408115],
[0.4486135478331319, 0.4218816398344042, 0.27854514466694047],
[0.2498064478821005, 0.9232655992760128, 0.44313074505345695],
[0.8613491047618306, 0.5503253124498481, 0.05058832952488124],
[0.9992824684127266, 0.8360275850799519, 0.9689962572847513],
[0.9263669830081276, 0.8486957344143055, 0.16631111060391401],
[0.48564112545071847, 0.21374729919918167, 0.4010402925494526],
[0.058635399972178925, 0.3789731189769161, 0.9853088437797259],
[0.26520305817215195, 0.7840706019485694, 0.4550083673391433],
[0.4230074859901629, 0.9573176408596732, 0.9954226894927138],
[0.5557683234056182, 0.718408275296326, 0.15479682527406413],
[0.2967078254945642, 0.9687093649691588, 0.5791802908162562],
[0.5421952013742742, 0.7479755603790641, 0.05716527290748308],
[0.5841775944589712, 0.5028503829195136, 0.8527198920482854],
[0.15743272793948326, 0.9607789032744504, 0.08011146524058688],
[0.1858249609807232, 0.5950351064500277, 0.6752125536040902],
[0.2352038950009312, 0.11988661394712419, 0.8902873141294375],
[0.24621534778862486, 0.5945191535334412, 0.6193815103321031],
[0.4192249153358725, 0.5836722892912247, 0.5227827155319589],
[0.9347062577364272, 0.20425919942353643, 0.7161918007894148],
[0.23868595261584602, 0.3957858467912545, 0.6716902229599713],
[0.2999970797987622, 0.31617719627185403, 0.7518644924144021],
[0.07254311449315731, 0.4582855226185861, 0.9984544408544423],
[0.9960964478550944, 0.073260721099633, 0.2131543122670404],
[0.26520041475040135, 0.9332593779937091, 0.8808641736864395],
[0.8792702424845428, 0.36952708873888396, 0.15774683235723197],
[0.833744954639807, 0.703539925087371, 0.6116777657259501],
[0.9872330636315043, 0.6539763177107326, 0.007823107152157949],
[0.8171041351154616, 0.2993787521999779, 0.6633887149660773],
[0.9389300039271039, 0.13429111439336772, 0.11542867041910221],
[0.10703597770941764, 0.5532236408848159, 0.2723482123148163],
[0.6048298270302239, 0.7176121871387979, 0.20359731232745293],
[0.6342379588850797, 0.2639839016304094, 0.48853185214937656],
[0.9053364910793232, 0.8461037132948555, 0.09229846771273342],
[0.42357577256372636, 0.27668022397225167, 0.0035456890877823],
[0.7711192230196271, 0.6371133773013796, 0.2619552624343482],
[0.7412309083479308, 0.5516804211263913, 0.42768691898067934],
[0.009669699608339966, 0.07524386007376704, 0.883106393300143]
]
moa = MOArchive3obj(points, reference_point=[1, 1, 1])
self.assertAlmostEqual(moa.hypervolume, 0.812479094965706, places=8)
moa = MOArchive3obj([[p[0] - 1, p[1] - 1, p[2] - 1] for p in points], reference_point=[0, 0, 0])
self.assertAlmostEqual(moa.hypervolume, 0.812479094965706, places=8)
moa = MOArchive3obj(points, reference_point=[1, 2, 3])
self.assertAlmostEqual(moa.hypervolume, 5.61969774713577, places=8)
self.assertEqual(moa.hypervolume_plus, moa.hypervolume)
if __name__ == '__main__':
unittest.main()
|
