def test_reset_y_star_event(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
ei.current = [NormalDistribution(mu=1,sigma=1),
NormalDistribution(mu=1,sigma=1),
NormalDistribution(mu=1,sigma=1)]
ei.execute()
ei.target = array([[2, 2, 2]])
ei.execute()
self.assertEqual(ei.y_star.all(), array([2, 2, 2]).all())
def test_reset_y_star_event(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
ei.current = [
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1)
]
ei.execute()
ei.target = array([[2, 2, 2]])
ei.execute()
self.assertEqual(ei.y_star.all(), array([2, 2, 2]).all())
def test_ei_2obj(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 10], [1, -10]])
ei.current = [NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=0, sigma=1)]
ei.calc_switch = "EI"
ei.execute()
self.assertAlmostEqual([5.0], ei.EI,1)
self.assertEqual(0.5, ei.PI,6)
def test_ei_nobj(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
list_of_cases = [Case(outputs=[("y1", 1), ("y2", 1), ("y3", 1)])]
ei.criteria = ['y1', 'y2', 'y3']
ei.current = [NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1)]
ei.execute()
self.assertAlmostEqual(0.875,ei.PI,1)
def test_ei_2obj(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 10], [1, -10]])
ei.current = [
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=0, sigma=1)
]
ei.calc_switch = "EI"
ei.execute()
self.assertAlmostEqual([5.0], ei.EI, 1)
self.assertEqual(0.5, ei.PI, 6)
def test_ei_calc_switch(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
ei.current = [NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1)]
ei.calc_switch = 'EI'
try:
ei.execute()
except ValueError,err:
self.assertEqual(str(err),': EI calculations not supported'
' for more than 2 objectives')
def test_ei_nobj(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
list_of_cases = [Case(outputs=[("y1", 1), ("y2", 1), ("y3", 1)])]
ei.criteria = ['y1', 'y2', 'y3']
ei.current = [
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1)
]
ei.execute()
self.assertAlmostEqual(0.875, ei.PI, 1)
def test_ei_calc_switch(self):
ei = MultiObjExpectedImprovement()
ei.target = array([[1, 1, 1]])
ei.current = [
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1),
NormalDistribution(mu=1, sigma=1)
]
ei.calc_switch = 'EI'
try:
ei.execute()
except ValueError, err:
self.assertEqual(
str(err), ': EI calculations not supported'
' for more than 2 objectives')