def test_adk():
# Test properties.
assert ADK(EQ()).stationary
assert not ADK(Linear()).stationary
# Test printing.
assert str(ADK(EQ())) == "EQ()"
assert str(ADK(EQ()) + ADK(Linear())) == "EQ() + Linear()"
assert str(ADK(EQ() + Linear())) == "EQ() + Linear()"
# Test equality.
assert ADK(EQ()) == ADK(EQ())
assert ADK(EQ()) != ADK(Linear())
# Test computation.
x = B.linspace(0, 5, 10)
approx(pairwise(ADK(EQ()), x), pairwise(EQ(), x))
approx(elwise(ADK(EQ()), x), elwise(EQ(), x))
# Check that the dimensionality resolves to `None`.
assert dimensionality(EQ()) == 1
assert dimensionality(ADK(EQ())) is None
def elwise(k: MultiOutputKernel, x: B.Numeric, y: B.Numeric):
return elwise(k, tuple(p(x) for p in k.ps), tuple(p(y) for p in k.ps))
def elwise(k, x, y: tuple):
return elwise(k, (x,), y)
def elwise(k, x: tuple, y):
return elwise(k, x, (y,))
def elwise(k, x: tuple, y: tuple):
if len(x) != len(y):
raise ValueError('"elwise" must be called with similarly sized tuples.')
return B.concat(*[elwise(k, xi, yi) for xi, yi in zip(x, y)], axis=-2)
def elwise(k: AmbiguousDimensionalityKernel, x, y):
return elwise(k[0], x, y)