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_dist(exponent):
rn = CudaFn(5)
[xarr, yarr], [x, y] = noise_elements(rn, n=2)
weight = _pos_vector(CudaFn(5))
weighting = CudaFnArrayWeighting(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_const_dist(exponent):
rn = CudaFn(5)
[xarr, yarr], [x, y] = noise_elements(rn, n=2)
constant = 1.5
weighting = CudaFnConstWeighting(constant, exponent=exponent)
factor = 1 if exponent == float('inf') else constant ** (1 / exponent)
true_dist = factor * np.linalg.norm(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(constant, 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_const_dist(exponent):
rn = CudaFn(5)
[xarr, yarr], [x, y] = noise_elements(rn, n=2)
constant = 1.5
weighting = CudaFnConstWeighting(constant, exponent=exponent)
factor = 1 if exponent == float('inf') else constant**(1 / exponent)
true_dist = factor * np.linalg.norm(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(constant, 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)
