def test_complex():
np.random.seed(0)
I = np.eye(5)
A = np.random.randn(5, 5)
B = np.random.randn(5, 5)
C = np.random.randn(3, 5)
Iop = NumpyMatrixOperator(I)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cva = NumpyVectorSpace.from_data(C)
# assemble_lincomb
assert not np.iscomplexobj(
Aop.assemble_lincomb((Iop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1, 1))._matrix)
assert np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1 + 0j, 1 + 0j))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1j, 1))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Bop, Aop), (1, 1j))._matrix)
# apply_inverse
assert not np.iscomplexobj(Aop.apply_inverse(Cva).data)
assert np.iscomplexobj((Aop * 1j).apply_inverse(Cva).data)
assert np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1, 1j)).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.apply_inverse(Cva * 1j).data)
# append
for rsrv in (0, 10):
for o_ind in (slice(None), [0]):
va = NumpyVectorSpace(5).empty(reserve=rsrv)
va.append(Cva)
D = np.random.randn(1, 5) + 1j * np.random.randn(1, 5)
Dva = NumpyVectorSpace.from_data(D)
assert not np.iscomplexobj(va.data)
assert np.iscomplexobj(Dva.data)
va.append(Dva[o_ind])
assert np.iscomplexobj(va.data)
# scal
assert not np.iscomplexobj(Cva.data)
assert np.iscomplexobj((Cva * 1j).data)
assert np.iscomplexobj((Cva * (1 + 0j)).data)
# axpy
assert not np.iscomplexobj(Cva.data)
Cva[0].axpy(1, Dva)
assert np.iscomplexobj(Cva.data)
Cva = NumpyVectorSpace.from_data(C)
assert not np.iscomplexobj(Cva.data)
Cva[0].axpy(1j, Dva)
assert np.iscomplexobj(Cva.data)
def test_complex():
np.random.seed(0)
I = np.eye(5)
A = np.random.randn(5, 5)
B = np.random.randn(5, 5)
C = np.random.randn(3, 5)
Iop = NumpyMatrixOperator(I)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cva = NumpyVectorArray(C)
# assemble_lincomb
assert not np.iscomplexobj(Aop.assemble_lincomb((Iop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1 + 0j, 1 + 0j))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1j, 1))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Bop, Aop), (1, 1j))._matrix)
# apply_inverse
assert not np.iscomplexobj(Aop.apply_inverse(Cva).data)
assert np.iscomplexobj((Aop * 1j).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1, 1j)).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.apply_inverse(Cva * 1j).data)
# append
for rsrv in (0, 10):
for o_ind in (None, [0]):
va = NumpyVectorArray.make_array(subtype=5, reserve=rsrv)
va.append(Cva)
D = np.random.randn(1, 5) + 1j * np.random.randn(1, 5)
Dva = NumpyVectorArray(D)
assert not np.iscomplexobj(va.data)
assert np.iscomplexobj(Dva.data)
va.append(Dva, o_ind)
assert np.iscomplexobj(va.data)
# scal
assert not np.iscomplexobj(Cva.data)
assert np.iscomplexobj((Cva * 1j).data)
assert np.iscomplexobj((Cva * (1 + 0j)).data)
# axpy
assert not np.iscomplexobj(Cva.data)
Cva.axpy(1, Dva, 0)
assert np.iscomplexobj(Cva.data)
Cva = NumpyVectorArray(C)
assert not np.iscomplexobj(Cva.data)
Cva.axpy(1j, Dva, 0)
assert np.iscomplexobj(Cva.data)
def test_complex():
np.random.seed(0)
I = np.eye(5)
A = np.random.randn(5, 5)
B = np.random.randn(5, 5)
C = np.random.randn(3, 5)
Iop = NumpyMatrixOperator(I)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cva = NumpyVectorSpace.from_data(C)
# assemble_lincomb
assert not np.iscomplexobj(Aop.assemble_lincomb((Iop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1 + 0j, 1 + 0j))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1j, 1))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Bop, Aop), (1, 1j))._matrix)
# apply_inverse
assert not np.iscomplexobj(Aop.apply_inverse(Cva).data)
assert np.iscomplexobj((Aop * 1j).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1, 1j)).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.apply_inverse(Cva * 1j).data)
# append
for rsrv in (0, 10):
for o_ind in (slice(None), [0]):
va = NumpyVectorSpace(5).empty(reserve=rsrv)
va.append(Cva)
D = np.random.randn(1, 5) + 1j * np.random.randn(1, 5)
Dva = NumpyVectorSpace.from_data(D)
assert not np.iscomplexobj(va.data)
assert np.iscomplexobj(Dva.data)
va.append(Dva[o_ind])
assert np.iscomplexobj(va.data)
# scal
assert not np.iscomplexobj(Cva.data)
assert np.iscomplexobj((Cva * 1j).data)
assert np.iscomplexobj((Cva * (1 + 0j)).data)
# axpy
assert not np.iscomplexobj(Cva.data)
Cva[0].axpy(1, Dva)
assert np.iscomplexobj(Cva.data)
Cva = NumpyVectorSpace.from_data(C)
assert not np.iscomplexobj(Cva.data)
Cva[0].axpy(1j, Dva)
assert np.iscomplexobj(Cva.data)
def test_complex():
np.random.seed(0)
I = np.eye(5)
A = np.random.randn(5, 5)
B = np.random.randn(5, 5)
C = np.random.randn(3, 5)
Iop = NumpyMatrixOperator(I)
Aop = NumpyMatrixOperator(A)
Bop = NumpyMatrixOperator(B)
Cva = NumpyVectorArray(C)
# assemble_lincomb
assert not np.iscomplexobj(
Aop.assemble_lincomb((Iop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1, 1))._matrix)
assert not np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1 + 0j, 1 + 0j))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Aop, Bop), (1j, 1))._matrix)
assert np.iscomplexobj(Aop.assemble_lincomb((Bop, Aop), (1, 1j))._matrix)
# apply_inverse
assert not np.iscomplexobj(Aop.apply_inverse(Cva).data)
assert np.iscomplexobj((Aop * 1j).apply_inverse(Cva).data)
assert np.iscomplexobj(
Aop.assemble_lincomb((Aop, Bop), (1, 1j)).apply_inverse(Cva).data)
assert np.iscomplexobj(Aop.apply_inverse(Cva * 1j).data)
# append
for rsrv in (0, 10):
for o_ind in (None, [0]):
va = NumpyVectorArray.make_array(subtype=5, reserve=rsrv)
va.append(Cva)
D = np.random.randn(1, 5) + 1j * np.random.randn(1, 5)
Dva = NumpyVectorArray(D)
assert not np.iscomplexobj(va.data)
assert np.iscomplexobj(Dva.data)
va.append(Dva, o_ind)
assert np.iscomplexobj(va.data)
# replace
va = NumpyVectorArray.make_array(subtype=5, reserve=0)
va.append(Cva)
D = np.random.randn(1, 5) + 1j * np.random.randn(1, 5)
Dva = NumpyVectorArray(D)
assert not np.iscomplexobj(va.data)
assert np.iscomplexobj(Dva.data)
va.replace(Dva, 1, 0)
assert np.iscomplexobj(va.data)
# scal
assert not np.iscomplexobj(Cva.data)
assert np.iscomplexobj((Cva * 1j).data)
assert np.iscomplexobj((Cva * (1 + 0j)).data)
# axpy
assert not np.iscomplexobj(Cva.data)
Cva.axpy(1, Dva, 0)
assert np.iscomplexobj(Cva.data)
Cva = NumpyVectorArray(C)
assert not np.iscomplexobj(Cva.data)
Cva.axpy(1j, Dva, 0)
assert np.iscomplexobj(Cva.data)
