def test_modeling_4p(self):
exponents = [(0, 1, 1), (0, 1, 2), (1, 4, 0), (1, 3, 0), (1, 4, 1),
(1, 3, 1), (1, 4, 2), (1, 3, 2), (1, 2, 0), (1, 2, 1),
(1, 2, 2), (2, 3, 0), (3, 4, 0), (2, 3, 1), (3, 4, 1),
(4, 5, 0), (2, 3, 2), (3, 4, 2), (1, 1, 0), (1, 1, 1),
(1, 1, 2), (5, 4, 0), (5, 4, 1), (4, 3, 0), (4, 3, 1),
(3, 2, 0), (3, 2, 1), (3, 2, 2), (5, 3, 0), (7, 4, 0),
(2, 1, 0), (2, 1, 1), (2, 1, 2), (9, 4, 0), (7, 3, 0),
(5, 2, 0), (5, 2, 1), (5, 2, 2), (8, 3, 0), (11, 4, 0),
(3, 1, 0), (3, 1, 1)]
points = np.array(
list(zip(*itertools.product([2, 4, 8, 10, 12], repeat=4))))
for expo1, expo2, expo3, expo4 in zip(exponents, exponents[1:],
exponents[2:], exponents[3:]):
termX = CompoundTerm.create(*expo1)
termY = CompoundTerm.create(*expo2)
termZ = CompoundTerm.create(*expo3)
termW = CompoundTerm.create(*expo4)
term = MultiParameterTerm((0, termX), (1, termY), (2, termZ),
(3, termW))
term.coefficient = 10
function = MultiParameterFunction(term)
function.constant_coefficient = 20000
values = function.evaluate(points)
measurements = [
Measurement(Coordinate(p), None, None, v)
for p, v in zip(zip(*points), values)
]
modeler = MultiParameterModeler()
models = modeler.model([measurements])
self.assertEqual(1, len(models))
self.assertApproxFunction(function, models[0].hypothesis.function)
def test_modeling_plus(self):
exponents = [(0, 1, 1), (0, 1, 2), (1, 4, 0), (1, 3, 0), (1, 4, 1), (1, 3, 1), (1, 4, 2), (1, 3, 2),
(1, 2, 0), (1, 2, 1), (1, 2, 2), (2, 3, 0), (3, 4, 0), (2, 3, 1), (3, 4, 1), (4, 5, 0),
(2, 3, 2), (3, 4, 2), (1, 1, 0), (1, 1, 1), (1, 1, 2), (5, 4, 0), (5, 4, 1), (4, 3, 0),
(4, 3, 1), (3, 2, 0), (3, 2, 1), (3, 2, 2), (5, 3, 0), (7, 4, 0), (2, 1, 0), (2, 1, 1),
(2, 1, 2), (9, 4, 0), (7, 3, 0), (5, 2, 0), (5, 2, 1), (5, 2, 2), (8, 3, 0), (11, 4, 0),
(3, 1, 0), (3, 1, 1)]
for expo1, expo2 in zip(exponents, exponents[1:]):
termX = CompoundTerm.create(*expo1)
termY = CompoundTerm.create(*expo2)
term1 = MultiParameterTerm((0, termX))
term1.coefficient = 10
term2 = MultiParameterTerm((1, termY))
term2.coefficient = 20
function = MultiParameterFunction(term1, term2)
function.constant_coefficient = 200
points = [np.array([2, 4, 8, 16, 32, 2, 4, 8, 16, 32, 2, 4, 8, 16, 32, 2, 4, 8, 16, 32, 2, 4, 8, 16, 32]),
np.array([2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 16, 16, 16, 16, 16, 32, 32, 32, 32, 32])]
values = function.evaluate(np.array(points))
measurements = [Measurement(Coordinate(p), None, None, v) for p, v in zip(zip(*points), values)]
modeler = MultiParameterModeler()
models = modeler.model([measurements])
self.assertEqual(1, len(models))
self.assertApproxFunction(function, models[0].hypothesis.function)