def test_vector_dist(exponent):
rn = CudaFn(5)
[xarr, yarr], [x, y] = noise_elements(rn, n=2)
weight = _pos_vector(CudaFn(5))
weighting = CudaFnVectorWeighting(weight, exponent=exponent)
if exponent in (1.0, float('inf')):
true_dist = np.linalg.norm(weight.asarray() * (xarr - yarr),
ord=exponent)
else:
true_dist = np.linalg.norm(
weight.asarray() ** (1 / exponent) * (xarr - yarr), ord=exponent)
if exponent == float('inf'):
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
weighting.dist(x, y)
else:
assert almost_equal(weighting.dist(x, y), true_dist)
# Same with free function
pdist = cu_weighted_dist(weight, exponent=exponent)
if exponent == float('inf'):
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
pdist(x, y)
else:
assert almost_equal(pdist(x, y), true_dist)
def test_vector_norm(exponent):
rn = CudaFn(5)
xarr, x = noise_elements(rn)
weight = _pos_vector(CudaFn(5))
weighting = CudaFnVectorWeighting(weight, exponent=exponent)
if exponent in (1.0, float('inf')):
true_norm = np.linalg.norm(weight.asarray() * xarr, ord=exponent)
else:
true_norm = np.linalg.norm(weight.asarray() ** (1 / exponent) * xarr,
ord=exponent)
if exponent == float('inf'):
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
weighting.norm(x)
else:
assert almost_equal(weighting.norm(x), true_norm)
# Same with free function
pnorm = cu_weighted_norm(weight, exponent=exponent)
if exponent == float('inf'):
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
pnorm(x)
else:
assert almost_equal(pnorm(x), true_norm)
def test_vector_is_valid():
rn = CudaFn(5)
weight = _pos_vector(rn)
weighting = CudaFnVectorWeighting(weight)
assert weighting.is_valid()
# Invalid
weight[0] = 0
weighting = CudaFnVectorWeighting(weight)
assert not weighting.is_valid()
def test_vector_inner():
rn = CudaFn(5)
[xarr, yarr], [x, y] = noise_elements(rn, 2)
weight = _pos_vector(CudaFn(5))
weighting = CudaFnVectorWeighting(weight)
true_inner = np.vdot(yarr, xarr * weight.asarray())
assert almost_equal(weighting.inner(x, y), true_inner)
# Same with free function
inner_vec = cu_weighted_inner(weight)
assert almost_equal(inner_vec(x, y), true_inner)
# Exponent != 2 -> no inner product, should raise
with pytest.raises(NotImplementedError):
CudaFnVectorWeighting(weight, exponent=1.0).inner(x, y)
