def test_vector_dist(exponent):
rn = odl.CudaRn(5)
xarr, yarr, x, y = _vectors(rn, n=2)
weight = _pos_vector(odl.CudaRn(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 = odl.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 = CudaRn(5)
xarr, x = example_vectors(rn)
weight = _pos_vector(CudaRn(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 = odl.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_norm(exponent):
rn = odl.CudaRn(5)
xarr, x = _vectors(rn)
weight = _pos_vector(odl.CudaRn(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 = odl.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_dist(exponent):
rn = CudaRn(5)
[xarr, yarr], [x, y] = example_vectors(rn, n=2)
weight = _pos_vector(CudaRn(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 = odl.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_inner():
rn = odl.CudaRn(5)
xarr, yarr, x, y = _vectors(rn, 2)
weight_vec = _pos_array(odl.Rn(5))
weight_elem = rn.element(weight_vec)
weighting_vec = CudaFnVectorWeighting(weight_vec)
weighting_elem = CudaFnVectorWeighting(weight_elem)
true_inner = np.vdot(yarr, xarr * weight_vec)
assert almost_equal(weighting_vec.inner(x, y), true_inner)
assert almost_equal(weighting_elem.inner(x, y), true_inner)
# Same with free function
inner_vec = odl.cu_weighted_inner(weight_vec)
inner_elem = odl.cu_weighted_inner(weight_elem)
assert almost_equal(inner_vec(x, y), true_inner)
assert almost_equal(inner_elem(x, y), true_inner)
# Exponent != 2 -> no inner product, should raise
with pytest.raises(NotImplementedError):
CudaFnVectorWeighting(weight_vec, exponent=1.0).inner(x, y)
def test_vector_equals():
rn = CudaRn(5)
weight = _pos_vector(rn)
weighting = CudaFnVectorWeighting(weight)
weighting2 = CudaFnVectorWeighting(weight)
assert weighting == weighting2
def test_vector_isvalid():
rn = odl.CudaRn(5)
weight = _pos_vector(rn)
weighting = CudaFnVectorWeighting(weight)
assert weighting.vector_is_valid()
# Invalid
weight[0] = 0
weighting = CudaFnVectorWeighting(weight)
assert not weighting.vector_is_valid()
def test_init_weighting(exponent):
const = 1.5
weight_vec = _pos_vector(CudaRn(3))
weight_elem = CudaFn(3, dtype='float32').element(weight_vec)
f3_none = CudaFn(3, dtype='float32', exponent=exponent)
f3_const = CudaFn(3, dtype='float32', weight=const, exponent=exponent)
f3_vec = CudaFn(3, dtype='float32', weight=weight_vec, exponent=exponent)
f3_elem = CudaFn(3, dtype='float32', weight=weight_elem, exponent=exponent)
weighting_none = CudaFnNoWeighting(exponent=exponent)
weighting_const = CudaFnConstWeighting(const, exponent=exponent)
weighting_vec = CudaFnVectorWeighting(weight_vec, exponent=exponent)
weighting_elem = CudaFnVectorWeighting(weight_elem, exponent=exponent)
assert f3_none.weighting == weighting_none
assert f3_const.weighting == weighting_const
assert f3_vec.weighting == weighting_vec
assert f3_elem.weighting == weighting_elem
def test_vector_inner():
rn = CudaRn(5)
[xarr, yarr], [x, y] = example_vectors(rn, 2)
weight = _pos_vector(CudaRn(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 = odl.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)
def test_vector_isvalid():
rn = odl.CudaRn(5)
weight_vec = _pos_array(rn)
weight_elem = rn.element(weight_vec)
weighting_vec = CudaFnVectorWeighting(weight_vec)
weighting_elem = CudaFnVectorWeighting(weight_elem)
assert weighting_vec.vector_is_valid()
assert weighting_elem.vector_is_valid()
# Invalid
weight_vec[0] = 0
weight_elem[0] = 0
weighting_vec = CudaFnVectorWeighting(weight_vec)
weighting_elem = CudaFnVectorWeighting(weight_elem)
assert not weighting_vec.vector_is_valid()
assert not weighting_elem.vector_is_valid()
def test_vector_is_valid():
rn = CudaRn(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_norm(exponent):
rn = odl.CudaRn(5)
xarr, x = _vectors(rn)
weight_vec = _pos_array(odl.Rn(5))
weight_elem = rn.element(weight_vec)
weighting_vec = CudaFnVectorWeighting(weight_vec, exponent=exponent)
weighting_elem = CudaFnVectorWeighting(weight_elem, exponent=exponent)
if exponent in (1.0, float('inf')):
true_norm = np.linalg.norm(weight_vec * xarr, ord=exponent)
else:
true_norm = np.linalg.norm(weight_vec ** (1 / exponent) * xarr,
ord=exponent)
if exponent == float('inf') or int(exponent) != exponent:
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
weighting_vec.norm(x)
with pytest.raises(NotImplementedError):
weighting_elem.norm(x)
else:
assert almost_equal(weighting_vec.norm(x), true_norm)
assert almost_equal(weighting_elem.norm(x), true_norm)
# Same with free function
pnorm_vec = odl.cu_weighted_norm(weight_vec, exponent=exponent)
pnorm_elem = odl.cu_weighted_norm(weight_elem, exponent=exponent)
if exponent == float('inf') or int(exponent) != exponent:
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
pnorm_vec(x)
with pytest.raises(NotImplementedError):
pnorm_elem(x)
else:
assert almost_equal(pnorm_vec(x), true_norm)
assert almost_equal(pnorm_elem(x), true_norm)
def test_vector_dist(exponent):
rn = odl.CudaRn(5)
xarr, yarr, x, y = _vectors(rn, n=2)
weight_vec = _pos_array(odl.Rn(5))
weight_elem = rn.element(weight_vec)
weighting_vec = CudaFnVectorWeighting(weight_vec, exponent=exponent)
weighting_elem = CudaFnVectorWeighting(weight_elem, exponent=exponent)
if exponent in (1.0, float('inf')):
true_dist = np.linalg.norm(weight_vec * (xarr - yarr), ord=exponent)
else:
true_dist = np.linalg.norm(
weight_vec ** (1 / exponent) * (xarr - yarr), ord=exponent)
if exponent == float('inf') or int(exponent) != exponent:
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
weighting_vec.dist(x, y)
with pytest.raises(NotImplementedError):
weighting_elem.dist(x, y)
else:
assert almost_equal(weighting_vec.dist(x, y), true_dist)
assert almost_equal(weighting_elem.dist(x, y), true_dist)
# Same with free function
pdist_vec = odl.cu_weighted_dist(weight_vec, exponent=exponent)
pdist_elem = odl.cu_weighted_dist(weight_elem, exponent=exponent)
if exponent == float('inf') or int(exponent) != exponent:
# Not yet implemented, should raise
with pytest.raises(NotImplementedError):
pdist_vec(x, y)
with pytest.raises(NotImplementedError):
pdist_elem(x, y)
else:
assert almost_equal(pdist_vec(x, y), true_dist)
assert almost_equal(pdist_elem(x, y), true_dist)
def test_vector_init():
rn = CudaRn(5)
weight_vec = _pos_vector(rn)
CudaFnVectorWeighting(weight_vec)
CudaFnVectorWeighting(rn.element(weight_vec))
