def test_generate_delaunay(self):
vlist = variable_list()
vlist.append(variable(lb=0, ub=1))
vlist.append(variable(lb=1, ub=2))
vlist.append(variable(lb=2, ub=3))
if not (util.numpy_available and util.scipy_available):
with self.assertRaises(ImportError):
util.generate_delaunay(vlist)
else:
tri = util.generate_delaunay(vlist, num=2)
self.assertTrue(isinstance(tri, util.scipy.spatial.Delaunay))
self.assertEqual(len(tri.simplices), 6)
self.assertEqual(len(tri.points), 8)
tri = util.generate_delaunay(vlist, num=3)
self.assertTrue(isinstance(tri, util.scipy.spatial.Delaunay))
self.assertEqual(len(tri.simplices), 62)
self.assertEqual(len(tri.points), 27)
#
# Check cases where not all variables are bounded
#
vlist = variable_list()
vlist.append(variable(lb=0))
with self.assertRaises(ValueError):
util.generate_delaunay(vlist)
vlist = variable_list()
vlist.append(variable(ub=0))
with self.assertRaises(ValueError):
util.generate_delaunay(vlist)
def setUpModule():
global _test_v
global _test_tri
global _test_values
if util.numpy_available and util.scipy_available:
_test_v = variable_list(variable(lb=i, ub=i + 1) for i in range(3))
_test_tri = util.generate_delaunay(_test_v, num=4)
_test_values = []
for _xi in _test_tri.points:
_test_values.append(sum(_xi))
_test_values = util.numpy.array(_test_values)
def test_call(self):
#
# 2d points
#
vlist = variable_list([variable(lb=0, ub=1), variable(lb=0, ub=1)])
tri = util.generate_delaunay(vlist, num=3)
x, y = tri.points.T
values = x * y
g = PiecewiseLinearFunctionND(tri, values)
f = TransformedPiecewiseLinearFunctionND(g)
self.assertTrue(f.parent is None)
self.assertEqual(f.ctype, IBlock)
self.assertTrue(util.numpy.isclose(f(tri.points), values).all())
self.assertAlmostEqual(f([0, 0]), 0.0)
self.assertAlmostEqual(f(util.numpy.array([0, 0])), 0.0)
self.assertAlmostEqual(f([1, 1]), 1.0)
self.assertAlmostEqual(f(util.numpy.array([1, 1])), 1.0)
#
# 3d points
#
vlist = variable_list(
[variable(lb=0, ub=1),
variable(lb=0, ub=1),
variable(lb=0, ub=1)])
tri = util.generate_delaunay(vlist, num=10)
x, y, z = tri.points.T
values = x * y * z
g = PiecewiseLinearFunctionND(tri, values)
f = TransformedPiecewiseLinearFunctionND(g)
self.assertTrue(f.parent is None)
self.assertEqual(f.ctype, IBlock)
self.assertTrue(util.numpy.isclose(f(tri.points), values).all())
self.assertAlmostEqual(f([0, 0, 0]), 0.0)
self.assertAlmostEqual(f(util.numpy.array([0, 0, 0])), 0.0)
self.assertAlmostEqual(f([1, 1, 1]), 1.0)
self.assertAlmostEqual(f(util.numpy.array([1, 1, 1])), 1.0)