def test_decomposed_fallback():
class Composite(cirq.Gate):
def num_qubits(self) -> int:
return 1
def _decompose_(self, qubits):
yield cirq.X(*qubits)
qid_shape = (2, )
tensor = cirq.to_valid_density_matrix(0,
len(qid_shape),
qid_shape=qid_shape,
dtype=np.complex64)
args = cirq.ActOnDensityMatrixArgs(
target_tensor=tensor,
available_buffer=[np.empty_like(tensor) for _ in range(3)],
qubits=cirq.LineQubit.range(1),
prng=np.random.RandomState(),
log_of_measurement_results={},
qid_shape=qid_shape,
)
cirq.act_on(Composite(), args, cirq.LineQubit.range(1))
np.testing.assert_allclose(
args.target_tensor,
cirq.one_hot(index=(1, 1), shape=(2, 2), dtype=np.complex64))
def test_shallow_copy_buffers():
args = cirq.ActOnDensityMatrixArgs(
qubits=cirq.LineQubit.range(1),
initial_state=0,
)
copy = args.copy(deep_copy_buffers=False)
assert copy.available_buffer is args.available_buffer
def test_shallow_copy_buffers():
qid_shape = (2, )
tensor = cirq.to_valid_density_matrix(0,
len(qid_shape),
qid_shape=qid_shape,
dtype=np.complex64)
args = cirq.ActOnDensityMatrixArgs(target_tensor=tensor)
copy = args.copy(deep_copy_buffers=False)
assert copy.available_buffer is args.available_buffer
def test_positional_argument():
qid_shape = (2,)
tensor = cirq.to_valid_density_matrix(
0, len(qid_shape), qid_shape=qid_shape, dtype=np.complex64
)
with cirq.testing.assert_deprecated(
'specify all the arguments with keywords', deadline='v0.15'
):
cirq.ActOnDensityMatrixArgs(tensor)
def test_default_parameter():
qid_shape = (2, )
tensor = cirq.to_valid_density_matrix(0,
len(qid_shape),
qid_shape=qid_shape,
dtype=np.complex64)
args = cirq.ActOnDensityMatrixArgs(target_tensor=tensor)
assert len(args.available_buffer) == 3
for buffer in args.available_buffer:
assert buffer.shape == tensor.shape
assert buffer.dtype == tensor.dtype
assert args.qid_shape == qid_shape
def test_cannot_act():
class NoDetails:
pass
args = cirq.ActOnDensityMatrixArgs(
qubits=cirq.LineQubit.range(1),
prng=np.random.RandomState(),
log_of_measurement_results={},
initial_state=0,
dtype=np.complex64,
)
with pytest.raises(TypeError, match="Can't simulate operations"):
cirq.act_on(NoDetails(), args, qubits=())
def test_with_qubits():
original = cirq.ActOnDensityMatrixArgs(
qubits=cirq.LineQubit.range(1),
initial_state=1,
dtype=np.complex64,
)
extened = original.with_qubits(cirq.LineQubit.range(1, 2))
np.testing.assert_almost_equal(
extened.target_tensor,
cirq.density_matrix_kronecker_product(
np.array([[0, 0], [0, 1]], dtype=np.complex64),
np.array([[1, 0], [0, 0]], dtype=np.complex64),
),
)
def test_default_parameter():
qid_shape = (2,)
tensor = cirq.to_valid_density_matrix(
0, len(qid_shape), qid_shape=qid_shape, dtype=np.complex64
)
args = cirq.ActOnDensityMatrixArgs(
qubits=cirq.LineQubit.range(1),
initial_state=0,
)
np.testing.assert_almost_equal(args.target_tensor, tensor)
assert len(args.available_buffer) == 3
for buffer in args.available_buffer:
assert buffer.shape == tensor.shape
assert buffer.dtype == tensor.dtype
assert args.qid_shape == qid_shape
def test_cannot_act():
class NoDetails:
pass
qid_shape = (2, )
tensor = cirq.to_valid_density_matrix(0,
len(qid_shape),
qid_shape=qid_shape,
dtype=np.complex64)
args = cirq.ActOnDensityMatrixArgs(
target_tensor=tensor,
available_buffer=[np.empty_like(tensor) for _ in range(3)],
qubits=cirq.LineQubit.range(1),
prng=np.random.RandomState(),
log_of_measurement_results={},
qid_shape=qid_shape,
)
with pytest.raises(TypeError, match="Can't simulate operations"):
cirq.act_on(NoDetails(), args, qubits=())
def test_decomposed_fallback():
class Composite(cirq.Gate):
def num_qubits(self) -> int:
return 1
def _decompose_(self, qubits):
yield cirq.X(*qubits)
args = cirq.ActOnDensityMatrixArgs(
qubits=cirq.LineQubit.range(1),
prng=np.random.RandomState(),
log_of_measurement_results={},
initial_state=0,
dtype=np.complex64,
)
cirq.act_on(Composite(), args, cirq.LineQubit.range(1))
np.testing.assert_allclose(
args.target_tensor, cirq.one_hot(index=(1, 1), shape=(2, 2), dtype=np.complex64)
)
def test_default_parameter_error():
tensor = np.ndarray(shape=(2, ))
with pytest.raises(
ValueError,
match='The dimension of target_tensor is not divisible by 2'):
cirq.ActOnDensityMatrixArgs(target_tensor=tensor)
def test_deprecated_warning_and_default_parameter_error():
tensor = np.ndarray(shape=(2,))
with cirq.testing.assert_deprecated('Use initial_state instead', deadline='v0.15'):
with pytest.raises(ValueError, match='dimension of target_tensor is not divisible by 2'):
cirq.ActOnDensityMatrixArgs(target_tensor=tensor)
def test_axes_deprecation():
shape = (2, )
state = cirq.to_valid_density_matrix(0,
len(shape),
qid_shape=shape,
dtype=np.complex64)
buf = []
log = {}
qids = tuple(cirq.LineQubit.range(1))
rng = np.random.RandomState()
# No kwargs
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
args = cirq.ActOnDensityMatrixArgs(state, buf, (1, ), shape, rng, log,
qids) # type: ignore
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
assert args.axes == (1, )
assert args.target_tensor is state
assert args.available_buffer is buf
assert args.qubits is qids
assert args.qid_shape is shape
assert args.prng is rng
assert args.log_of_measurement_results is log
# kwargs no axes
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
args = cirq.ActOnDensityMatrixArgs(
state,
buf,
(1, ), # type: ignore
qubits=qids,
prng=rng,
log_of_measurement_results=log,
qid_shape=shape,
)
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
assert args.axes == (1, )
assert args.target_tensor is state
assert args.available_buffer is buf
assert args.qubits is qids
assert args.qid_shape is shape
assert args.prng is rng
assert args.log_of_measurement_results is log
# kwargs incl axes
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
args = cirq.ActOnDensityMatrixArgs(
state,
buf,
axes=(1, ),
qubits=qids,
prng=rng,
log_of_measurement_results=log,
qid_shape=shape,
)
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
assert args.axes == (1, )
assert args.target_tensor is state
assert args.available_buffer is buf
assert args.qubits is qids
assert args.qid_shape is shape
assert args.prng is rng
assert args.log_of_measurement_results is log
# all kwargs
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
args = cirq.ActOnDensityMatrixArgs(
target_tensor=state,
available_buffer=buf,
axes=(1, ),
qubits=qids,
prng=rng,
log_of_measurement_results=log,
qid_shape=shape,
)
with cirq.testing.assert_deprecated("axes", deadline="v0.13"):
assert args.axes == (1, )
assert args.target_tensor is state
assert args.available_buffer is buf
assert args.qubits is qids
assert args.qid_shape is shape
assert args.prng is rng
assert args.log_of_measurement_results is log