def test_pointwise_inner_init_properties():
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2))
vfspace = ProductSpace(fspace, 3, exponent=2)
# Make sure the code runs and test the properties
pwinner = PointwiseInner(vfspace, vfspace.one())
assert pwinner.base_space == fspace
assert all_equal(pwinner.weights, [1, 1, 1])
assert not pwinner.is_weighted
repr(pwinner)
pwinner = PointwiseInner(vfspace, vfspace.one(), weight=[1, 2, 3])
assert all_equal(pwinner.weights, [1, 2, 3])
assert pwinner.is_weighted
# Bad input
with pytest.raises(TypeError):
PointwiseInner(odl.Rn(3), odl.Rn(3).one()) # No power space
# TODO: Does not raise currently, although bad_vecfield not in vfspace!
"""
bad_vecfield = ProductSpace(fspace, 3, exponent=1).one()
with pytest.raises(TypeError):
PointwiseInner(vfspace, bad_vecfield)
"""
with pytest.raises(ValueError):
PointwiseInner(vfspace, vfspace.one(), weight=-1) # < 0 not allowed
with pytest.raises(ValueError):
PointwiseInner(vfspace, vfspace.one(), weight=[1, 0, 1]) # 0 invalid
def test_pointwise_inner_init_properties():
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2))
vfspace = ProductSpace(fspace, 3, exponent=2)
# Make sure the code runs and test the properties
pwinner = PointwiseInner(vfspace, vfspace.one())
assert pwinner.base_space == fspace
assert all_equal(pwinner.weights, [1, 1, 1])
assert not pwinner.is_weighted
repr(pwinner)
pwinner = PointwiseInner(vfspace, vfspace.one(), weight=[1, 2, 3])
assert all_equal(pwinner.weights, [1, 2, 3])
assert pwinner.is_weighted
# Bad input
with pytest.raises(TypeError):
PointwiseInner(odl.Rn(3), odl.Rn(3).one()) # No power space
# TODO: Does not raise currently, although bad_vecfield not in vfspace!
"""
bad_vecfield = ProductSpace(fspace, 3, exponent=1).one()
with pytest.raises(TypeError):
PointwiseInner(vfspace, bad_vecfield)
"""
with pytest.raises(ValueError):
PointwiseInner(vfspace, vfspace.one(), weight=-1) # < 0 not allowed
with pytest.raises(ValueError):
PointwiseInner(vfspace, vfspace.one(), weight=[1, 0, 1]) # 0 invalid
def test_pointwise_norm_gradient_real(exponent):
# The operator is not differentiable for exponent 'inf'
if exponent == float('inf'):
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2))
vfspace = ProductSpace(fspace, 1)
pwnorm = PointwiseNorm(vfspace, exponent)
point = vfspace.one()
with pytest.raises(NotImplementedError):
pwnorm.derivative(point)
return
# 1d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2))
vfspace = ProductSpace(fspace, 1)
pwnorm = PointwiseNorm(vfspace, exponent)
point = noise_element(vfspace)
direction = noise_element(vfspace)
# Computing expected result
tmp = pwnorm(point).ufuncs.power(1 - exponent)
v_field = vfspace.element()
for i in range(len(v_field)):
v_field[i] = tmp * point[i] * np.abs(point[i])**(exponent - 2)
pwinner = odl.PointwiseInner(vfspace, v_field)
expected_result = pwinner(direction)
func_pwnorm = pwnorm.derivative(point)
assert all_almost_equal(func_pwnorm(direction), expected_result)
# 3d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2))
vfspace = ProductSpace(fspace, 3)
pwnorm = PointwiseNorm(vfspace, exponent)
point = noise_element(vfspace)
direction = noise_element(vfspace)
# Computing expected result
tmp = pwnorm(point).ufuncs.power(1 - exponent)
v_field = vfspace.element()
for i in range(len(v_field)):
v_field[i] = tmp * point[i] * np.abs(point[i])**(exponent - 2)
pwinner = odl.PointwiseInner(vfspace, v_field)
expected_result = pwinner(direction)
func_pwnorm = pwnorm.derivative(point)
assert all_almost_equal(func_pwnorm(direction), expected_result)
