def test_pointwise_inner_adjoint():
# 1d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 1)
array = np.array([[[-1, -3],
[2, 0]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2],
[3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([1, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([1, -1]))
# 3d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 3)
array = np.array([[[-1 - 1j, -3],
[2, 2j]],
[[-1j, 0],
[0, 1]],
[[-1, 1 + 2j],
[1, 1]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2],
[3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
def test_pointwise_inner_adjoint_weighted():
# Weighted product space only
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 3, weight=[2, 4, 6])
array = np.array([[[-1 - 1j, -3],
[2, 2j]],
[[-1j, 0],
[0, 1]],
[[-1, 1 + 2j],
[1, 1]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2],
[3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array # same as unweighted case
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
# Using different weighting in the inner product
pwinner = PointwiseInner(vfspace, vecfield=array, weight=[4, 8, 12])
testarr = np.array([[1 + 1j, 2],
[3, 4 - 2j]])
true_inner_adj = 2 * testarr[None, :, :] * array # w / v = (2, 2, 2)
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
def test_pointwise_inner_adjoint():
# 1d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 1)
array = np.array([[[-1, -3], [2, 0]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2], [3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([1, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([1, -1]))
# 3d
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 3)
array = np.array([[[-1 - 1j, -3], [2, 2j]], [[-1j, 0], [0, 1]],
[[-1, 1 + 2j], [1, 1]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2], [3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
def test_pointwise_inner_adjoint_weighted():
# Weighted product space only
fspace = odl.uniform_discr([0, 0], [1, 1], (2, 2), dtype=complex)
vfspace = ProductSpace(fspace, 3, weight=[2, 4, 6])
array = np.array([[[-1 - 1j, -3], [2, 2j]], [[-1j, 0], [0, 1]],
[[-1, 1 + 2j], [1, 1]]])
pwinner = PointwiseInner(vfspace, vecfield=array)
testarr = np.array([[1 + 1j, 2], [3, 4 - 2j]])
true_inner_adj = testarr[None, :, :] * array # same as unweighted case
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
# Using different weighting in the inner product
pwinner = PointwiseInner(vfspace, vecfield=array, weight=[4, 8, 12])
testarr = np.array([[1 + 1j, 2], [3, 4 - 2j]])
true_inner_adj = 2 * testarr[None, :, :] * array # w / v = (2, 2, 2)
testfunc = fspace.element(testarr)
testfunc_pwinner_adj = pwinner.adjoint(testfunc)
assert all_almost_equal(testfunc_pwinner_adj,
true_inner_adj.reshape([3, -1]))
out = vfspace.element()
pwinner.adjoint(testfunc, out=out)
assert all_almost_equal(out, true_inner_adj.reshape([3, -1]))
