def test_apply_adjoint():
np.random.seed(0)
A11 = np.random.randn(2, 3)
A12 = np.random.randn(2, 4)
A21 = np.zeros((5, 3))
A22 = np.random.randn(5, 4)
A = np.vstack((np.hstack((A11, A12)), np.hstack((A21, A22))))
A11op = NumpyMatrixOperator(A11)
A12op = NumpyMatrixOperator(A12)
A22op = NumpyMatrixOperator(A22)
Aop = BlockOperator(np.array([[A11op, A12op], [None, A22op]]))
v1 = np.random.randn(2)
v2 = np.random.randn(5)
v = np.hstack((v1, v2))
v1va = NumpyVectorSpace.from_numpy(v1)
v2va = NumpyVectorSpace.from_numpy(v2)
vva = BlockVectorSpace.make_array((v1va, v2va))
wva = Aop.apply_adjoint(vva)
w = np.hstack((wva.block(0).to_numpy(), wva.block(1).to_numpy()))
assert np.allclose(A.T.dot(v), w)
def test_apply_adjoint():
np.random.seed(0)
A11 = np.random.randn(2, 3)
A12 = np.random.randn(2, 4)
A21 = np.zeros((5, 3))
A22 = np.random.randn(5, 4)
A = np.vstack((np.hstack((A11, A12)),
np.hstack((A21, A22))))
A11op = NumpyMatrixOperator(A11)
A12op = NumpyMatrixOperator(A12)
A22op = NumpyMatrixOperator(A22)
Aop = BlockOperator(np.array([[A11op, A12op], [None, A22op]]))
v1 = np.random.randn(2)
v2 = np.random.randn(5)
v = np.hstack((v1, v2))
v1va = NumpyVectorSpace.from_numpy(v1)
v2va = NumpyVectorSpace.from_numpy(v2)
vva = BlockVectorSpace.make_array((v1va, v2va))
wva = Aop.apply_adjoint(vva)
w = np.hstack((wva.block(0).to_numpy(), wva.block(1).to_numpy()))
assert np.allclose(A.T.dot(v), w)
