def test_selection():
model = Graph()
# Test construction:
p = GP(EQ(), TensorProductMean(lambda x: x ** 2), graph=model)
yield eq, str(p.select(1)), 'GP(EQ() : [1], <lambda> : [1])'
yield eq, str(p.select(1, 2)), 'GP(EQ() : [1, 2], <lambda> : [1, 2])'
# Test case:
p = GP(EQ(), graph=model) # 1D
p2 = p.select(0) # 2D
n = 5
x = np.linspace(0, 10, n)[:, None]
x1 = np.concatenate((x, np.random.randn(n, 1)), axis=1)
x2 = np.concatenate((x, np.random.randn(n, 1)), axis=1)
y = p2(x).sample()
post = p.condition(p2(x1), y)
yield assert_allclose, post(x).mean, y
yield le, abs_err(B.diag(post(x).var)), 1e-10
post = p.condition(p2(x2), y)
yield assert_allclose, post(x).mean, y
yield le, abs_err(B.diag(post(x).var)), 1e-10
post = p2.condition(p(x), y)
yield assert_allclose, post(x1).mean, y
yield assert_allclose, post(x2).mean, y
yield le, abs_err(B.diag(post(x1).var)), 1e-10
yield le, abs_err(B.diag(post(x2).var)), 1e-10
def test_shorthands():
model = Graph()
p = GP(EQ(), graph=model)
# Construct a normal distribution that serves as in input.
x = p(1)
assert isinstance(x, At)
assert type_parameter(x) is p
assert x.get() == 1
assert str(p(x)) == '{}({})'.format(str(p), str(x))
assert repr(p(x)) == '{}({})'.format(repr(p), repr(x))
# Construct a normal distribution that does not serve as an input.
x = Normal(np.ones((1, 1)))
with pytest.raises(RuntimeError):
type_parameter(x)
with pytest.raises(RuntimeError):
x.get()
with pytest.raises(RuntimeError):
p | (x, 1)
# Test shorthands for stretching and selection.
p = GP(EQ(), graph=Graph())
assert str(p > 2) == str(p.stretch(2))
assert str(p[0]) == str(p.select(0))
def test_shorthands():
model = Graph()
p = GP(EQ(), graph=model)
# Construct a normal distribution that serves as in input.
x = p(1)
yield assert_instance, x, At
yield ok, type_parameter(x) is p
yield eq, x.get(), 1
yield eq, str(p(x)), '{}({})'.format(str(p), str(x))
yield eq, repr(p(x)), '{}({})'.format(repr(p), repr(x))
# Construct a normal distribution that does not serve as an input.
x = Normal(np.ones((1, 1)))
yield raises, RuntimeError, lambda: type_parameter(x)
yield raises, RuntimeError, lambda: x.get()
yield raises, RuntimeError, lambda: p | (x, 1)
# Test shorthands for stretching and selection.
p = GP(EQ(), graph=Graph())
yield eq, str(p > 2), str(p.stretch(2))
yield eq, str(p[0]), str(p.select(0))
