def test_to_matrix(self):
"""to matrix text"""
np.testing.assert_array_equal(X.to_matrix(),
Operator.from_label("X").data)
np.testing.assert_array_equal(Y.to_matrix(),
Operator.from_label("Y").data)
np.testing.assert_array_equal(Z.to_matrix(),
Operator.from_label("Z").data)
op1 = Y + H
np.testing.assert_array_almost_equal(op1.to_matrix(),
Y.to_matrix() + H.to_matrix())
op2 = op1 * 0.5
np.testing.assert_array_almost_equal(op2.to_matrix(),
op1.to_matrix() * 0.5)
op3 = (4 - 0.6j) * op2
np.testing.assert_array_almost_equal(op3.to_matrix(),
op2.to_matrix() * (4 - 0.6j))
op4 = op3.tensor(X)
np.testing.assert_array_almost_equal(
op4.to_matrix(), np.kron(op3.to_matrix(), X.to_matrix()))
op5 = op4.compose(H ^ I)
np.testing.assert_array_almost_equal(
op5.to_matrix(), np.dot(op4.to_matrix(), (H ^ I).to_matrix()))
op6 = op5 + PrimitiveOp(Operator.from_label("+r").data)
np.testing.assert_array_almost_equal(
op6.to_matrix(),
op5.to_matrix() + Operator.from_label("+r").data)
param = Parameter("α")
m = np.array([[0, -1j], [1j, 0]])
op7 = MatrixOp(m, param)
np.testing.assert_array_equal(op7.to_matrix(), m * param)
param = Parameter("β")
op8 = PauliOp(primitive=Pauli("Y"), coeff=param)
np.testing.assert_array_equal(op8.to_matrix(), m * param)
param = Parameter("γ")
qc = QuantumCircuit(1)
qc.h(0)
op9 = CircuitOp(qc, coeff=param)
m = np.array([[1, 1], [1, -1]]) / np.sqrt(2)
np.testing.assert_array_equal(op9.to_matrix(), m * param)
def test_io_consistency(self):
""" consistency test """
new_op = X ^ Y ^ I
label = 'XYI'
# label = new_op.primitive.to_label()
self.assertEqual(str(new_op.primitive), label)
np.testing.assert_array_almost_equal(new_op.primitive.to_matrix(),
Operator.from_label(label).data)
self.assertEqual(new_op.primitive, Pauli(label))
x_mat = X.primitive.to_matrix()
y_mat = Y.primitive.to_matrix()
i_mat = np.eye(2, 2)
np.testing.assert_array_almost_equal(new_op.primitive.to_matrix(),
np.kron(np.kron(x_mat, y_mat), i_mat))
hi = np.kron(H.to_matrix(), I.to_matrix())
hi2 = Operator.from_label('HI').data
hi3 = (H ^ I).to_matrix()
np.testing.assert_array_almost_equal(hi, hi2)
np.testing.assert_array_almost_equal(hi2, hi3)
xy = np.kron(X.to_matrix(), Y.to_matrix())
xy2 = Operator.from_label('XY').data
xy3 = (X ^ Y).to_matrix()
np.testing.assert_array_almost_equal(xy, xy2)
np.testing.assert_array_almost_equal(xy2, xy3)
# Check if numpy array instantiation is the same as from Operator
matrix_op = Operator.from_label('+r')
np.testing.assert_array_almost_equal(PrimitiveOp(matrix_op).to_matrix(),
PrimitiveOp(matrix_op.data).to_matrix())
# Ditto list of lists
np.testing.assert_array_almost_equal(PrimitiveOp(matrix_op.data.tolist()).to_matrix(),
PrimitiveOp(matrix_op.data).to_matrix())
def test_is_hermitian(self):
"""Test is_hermitian method."""
with self.subTest("I"):
self.assertTrue(I.is_hermitian())
with self.subTest("X"):
self.assertTrue(X.is_hermitian())
with self.subTest("Y"):
self.assertTrue(Y.is_hermitian())
with self.subTest("Z"):
self.assertTrue(Z.is_hermitian())
with self.subTest("XY"):
self.assertFalse((X @ Y).is_hermitian())
with self.subTest("CX"):
self.assertTrue(CX.is_hermitian())
with self.subTest("T"):
self.assertFalse(T.is_hermitian())
def test_evals(self):
"""evals test"""
# TODO: Think about eval names
self.assertEqual(Z.eval("0").eval("0"), 1)
self.assertEqual(Z.eval("1").eval("0"), 0)
self.assertEqual(Z.eval("0").eval("1"), 0)
self.assertEqual(Z.eval("1").eval("1"), -1)
self.assertEqual(X.eval("0").eval("0"), 0)
self.assertEqual(X.eval("1").eval("0"), 1)
self.assertEqual(X.eval("0").eval("1"), 1)
self.assertEqual(X.eval("1").eval("1"), 0)
self.assertEqual(Y.eval("0").eval("0"), 0)
self.assertEqual(Y.eval("1").eval("0"), -1j)
self.assertEqual(Y.eval("0").eval("1"), 1j)
self.assertEqual(Y.eval("1").eval("1"), 0)
with self.assertRaises(ValueError):
Y.eval("11")
with self.assertRaises(ValueError):
(X ^ Y).eval("1111")
with self.assertRaises(ValueError):
Y.eval((X ^ X).to_matrix_op())
# Check that Pauli logic eval returns same as matrix logic
self.assertEqual(PrimitiveOp(Z.to_matrix()).eval("0").eval("0"), 1)
self.assertEqual(PrimitiveOp(Z.to_matrix()).eval("1").eval("0"), 0)
self.assertEqual(PrimitiveOp(Z.to_matrix()).eval("0").eval("1"), 0)
self.assertEqual(PrimitiveOp(Z.to_matrix()).eval("1").eval("1"), -1)
self.assertEqual(PrimitiveOp(X.to_matrix()).eval("0").eval("0"), 0)
self.assertEqual(PrimitiveOp(X.to_matrix()).eval("1").eval("0"), 1)
self.assertEqual(PrimitiveOp(X.to_matrix()).eval("0").eval("1"), 1)
self.assertEqual(PrimitiveOp(X.to_matrix()).eval("1").eval("1"), 0)
self.assertEqual(PrimitiveOp(Y.to_matrix()).eval("0").eval("0"), 0)
self.assertEqual(PrimitiveOp(Y.to_matrix()).eval("1").eval("0"), -1j)
self.assertEqual(PrimitiveOp(Y.to_matrix()).eval("0").eval("1"), 1j)
self.assertEqual(PrimitiveOp(Y.to_matrix()).eval("1").eval("1"), 0)
pauli_op = Z ^ I ^ X ^ Y
mat_op = PrimitiveOp(pauli_op.to_matrix())
full_basis = list(
map("".join, itertools.product("01", repeat=pauli_op.num_qubits)))
for bstr1, bstr2 in itertools.product(full_basis, full_basis):
# print('{} {} {} {}'.format(bstr1, bstr2, pauli_op.eval(bstr1, bstr2),
# mat_op.eval(bstr1, bstr2)))
np.testing.assert_array_almost_equal(
pauli_op.eval(bstr1).eval(bstr2),
mat_op.eval(bstr1).eval(bstr2))
gnarly_op = SummedOp(
[
(H ^ I ^ Y).compose(X ^ X ^ Z).tensor(Z),
PrimitiveOp(Operator.from_label("+r0I")),
3 * (X ^ CX ^ T),
],
coeff=3 + 0.2j,
)
gnarly_mat_op = PrimitiveOp(gnarly_op.to_matrix())
full_basis = list(
map("".join, itertools.product("01", repeat=gnarly_op.num_qubits)))
for bstr1, bstr2 in itertools.product(full_basis, full_basis):
np.testing.assert_array_almost_equal(
gnarly_op.eval(bstr1).eval(bstr2),
gnarly_mat_op.eval(bstr1).eval(bstr2))