def test_readout_confusion_matrix_repr_and_equality():
mat1 = cirq.testing.random_orthogonal(4, random_state=1234)
mat2 = cirq.testing.random_orthogonal(2, random_state=1234)
q = cirq.LineQubit.range(3)
a = cirq.TensoredConfusionMatrices([mat1, mat2], [q[:2], q[2:]], repetitions=0, timestamp=0)
b = cirq.TensoredConfusionMatrices(mat1, q[:2], repetitions=0, timestamp=0)
c = cirq.TensoredConfusionMatrices(mat2, q[2:], repetitions=0, timestamp=0)
for x in [a, b, c]:
cirq.testing.assert_equivalent_repr(x)
assert cirq.approx_eq(x, x)
assert x._approx_eq_(mat1, 1e-6) is NotImplemented
eq = cirq.testing.EqualsTester()
eq.add_equality_group(a, a)
eq.add_equality_group(b, b)
eq.add_equality_group(c, c)
def test_from_measurement():
qubits = cirq.LineQubit.range(3)
confuse_02 = np.array([[0, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0],
[0, 0, 1, 0]])
confuse_1 = np.array([[0, 1], [1, 0]])
op = cirq.measure(
*qubits,
key='a',
invert_mask=(True, False),
confusion_map={
(0, 2): confuse_02,
(1, ): confuse_1
},
)
tcm = cirq.TensoredConfusionMatrices.from_measurement(op.gate, op.qubits)
expected_tcm = cirq.TensoredConfusionMatrices([confuse_02, confuse_1],
((qubits[0], qubits[2]),
(qubits[1], )),
repetitions=0,
timestamp=0)
assert tcm == expected_tcm
no_cm_op = cirq.measure(*qubits, key='a')
with pytest.raises(ValueError,
match="Measurement has no confusion matrices"):
_ = cirq.TensoredConfusionMatrices.from_measurement(
no_cm_op.gate, no_cm_op.qubits)
def test_readout_confusion_matrix_raises():
num_qubits = 2
confusion_matrix = get_expected_cm(num_qubits, 0.1, 0.2)
qubits = cirq.LineQubit.range(4)
with pytest.raises(ValueError, match=r"measure_qubits cannot be empty"):
_ = cirq.TensoredConfusionMatrices([], [], repetitions=0, timestamp=0)
with pytest.raises(ValueError, match=r"len\(confusion_matrices\)"):
_ = cirq.TensoredConfusionMatrices([confusion_matrix],
[qubits[:2], qubits[2:]],
repetitions=0,
timestamp=0)
with pytest.raises(ValueError,
match="Shape mismatch for confusion matrix"):
_ = cirq.TensoredConfusionMatrices(confusion_matrix,
qubits,
repetitions=0,
timestamp=0)
with pytest.raises(ValueError, match="Repeated qubits not allowed"):
_ = cirq.TensoredConfusionMatrices(
[confusion_matrix, confusion_matrix],
[qubits[:2], qubits[1:3]],
repetitions=0,
timestamp=0,
)
readout_cm = cirq.TensoredConfusionMatrices(
[confusion_matrix, confusion_matrix], [qubits[:2], qubits[2:]],
repetitions=0,
timestamp=0)
with pytest.raises(ValueError, match="should be a subset of"):
_ = readout_cm.confusion_matrix([cirq.NamedQubit("a")])
with pytest.raises(ValueError, match="should be a subset of"):
_ = readout_cm.correction_matrix([cirq.NamedQubit("a")])
with pytest.raises(ValueError, match="result.shape .* should be"):
_ = readout_cm.apply(np.asarray([100]), qubits[:2])
with pytest.raises(ValueError, match="method.* should be"):
_ = readout_cm.apply(np.asarray([1 / 16] * 16), method='l1norm')