def test_input_transform():
# Test construction:
p = GP(lambda x: x**2, Linear())
assert (str(p.transform(lambda x: x)) ==
"GP(<lambda> transform <lambda>, Linear() transform <lambda>)")
# Test case:
p_transformed = p.transform(lambda x: B.sqrt(x))
x = B.linspace(0, 5, 10)
y = p_transformed(x).sample()
post = p.measure | (p_transformed(x, B.epsilon), y)
assert_equal_normals(post(p(B.sqrt(x))), post(p_transformed(x)))
assert_equal_normals(post(p(x)), post(p_transformed(x * x)))
def test_input_transform():
# Test construction:
p = GP(TensorProductMean(lambda x: x**2), EQ())
assert (str(p.transform(lambda x: x)) ==
"GP(<lambda> transform <lambda>, EQ() transform <lambda>)")
# Test case:
p = GP(EQ())
p_transformed = p.transform(lambda x: B.sqrt(x))
x = B.linspace(0, 5, 10)
y = p_transformed(x).sample()
post = p.measure | (p_transformed(x), y)
assert_equal_normals(post(p(B.sqrt(x))), post(p_transformed(x)))
assert_equal_normals(post(p(x)), post(p_transformed(x * x)))