Update black requirement from ~=19.10b0 to ~=22.1 (#1110)

* Update black requirement from ~=19.10b0 to ~=22.1

Updates the requirements on [black](https://github.com/psf/black) to permit the latest version.
- [Release notes](https://github.com/psf/black/releases)
- [Changelog](https://github.com/psf/black/blob/main/CHANGES.md)
- [Commits](psf/black@19.10b0...22.1.0)

---
updated-dependencies:
- dependency-name: black
  dependency-type: direct:development
...

Signed-off-by: dependabot[bot] <[email protected]>

* applying new black rules

* fixing flake

Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Sarah Kaiser <[email protected]>

dev_requirements.txt

@@ -9,7 +9,7 @@ amazon-braket-sdk~=1.14.0
 pytest-xdist[psutil]~=2.5.0
 pytest-cov~=3.0.0
 flake8~=4.0.1
-black~=19.10b0
+black~=22.1
 mypy~=0.931
 
 # Documentation and examples.

mitiq/benchmarks/ghz_circuits.py

@@ -22,19 +22,20 @@
 
 
 def generate_ghz_circuit(
-    n_qubits: int, return_type: Optional[str] = None,
+    n_qubits: int,
+    return_type: Optional[str] = None,
 ) -> QPROGRAM:
     """Returns a GHZ circuit ie a circuit that prepares an ``n_qubits`` GHZ state.
 
-        Args:
-            n_qubits: The number of qubits in the circuit.
-            return_type: String which specifies the type of the returned
-                circuits. See the keys of ``mitiq.SUPPORTED_PROGRAM_TYPES``
-                for options. If ``None``, the returned circuits have type
-                ``cirq.Circuit``.
+    Args:
+        n_qubits: The number of qubits in the circuit.
+        return_type: String which specifies the type of the returned
+            circuits. See the keys of ``mitiq.SUPPORTED_PROGRAM_TYPES``
+            for options. If ``None``, the returned circuits have type
+            ``cirq.Circuit``.
 
-        Returns:
-            A GHZ circuit acting on ``n_qubits`` qubits.
+    Returns:
+        A GHZ circuit acting on ``n_qubits`` qubits.
     """
     if n_qubits <= 0:
         raise ValueError(

mitiq/benchmarks/randomized_benchmarking.py

@@ -71,11 +71,17 @@ def generate_rb_circuits(
         ]
     else:
         cfd_matrices = _two_qubit_clifford_matrices(
-            qubits[0], qubits[1], cliffords,
+            qubits[0],
+            qubits[1],
+            cliffords,
         )
         circuits = [
             _random_two_q_clifford(
-                qubits[0], qubits[1], num_cliffords, cfd_matrices, cliffords,
+                qubits[0],
+                qubits[1],
+                num_cliffords,
+                cfd_matrices,
+                cliffords,
             )
             for _ in range(trials)
         ]

mitiq/cdr/clifford_training_data.py

@@ -301,7 +301,8 @@ def _replace(
     return [
         cirq.ops.rz(a).on(*q)
         for (a, q) in zip(
-            clifford_angles, [op.qubits for op in non_clifford_ops],
+            clifford_angles,
+            [op.qubits for op in non_clifford_ops],
         )
     ]
 
@@ -344,7 +345,10 @@ def _closest_clifford(angles: np.ndarray) -> float:
 
 
 @np.vectorize
-def _is_clifford_angle(angles: np.ndarray, tol: float = 10 ** -5,) -> bool:
+def _is_clifford_angle(
+    angles: np.ndarray,
+    tol: float = 10**-5,
+) -> bool:
     """Function to check if a given angle is Clifford.
 
     Args:
@@ -376,7 +380,7 @@ def _angle_to_proximities(angle: np.ndarray, sigma: float) -> List[float]:
     for exponent in range(4):
         if exponent == 0:
             exponent = 4
-        diff = np.linalg.norm(rz_matrix - s_matrix ** exponent)
+        diff = np.linalg.norm(rz_matrix - s_matrix**exponent)
         dists.append(np.exp(-((diff / sigma) ** 2)))
     return dists
 
@@ -400,7 +404,9 @@ def _angle_to_proximity(angle: np.ndarray, sigma: float) -> float:
 
 @np.vectorize
 def _probabilistic_angle_to_clifford(
-    angles: np.ndarray, sigma: float, random_state: np.random.RandomState,
+    angles: np.ndarray,
+    sigma: float,
+    random_state: np.random.RandomState,
 ) -> float:
     """Returns a Clifford angle sampled from the distribution
 

mitiq/cdr/tests/test_cdr.py

@@ -65,7 +65,9 @@ def simulate(circuit: QPROGRAM) -> np.ndarray:
 @pytest.mark.parametrize("random_state", [1, 2, 3, 4, 5])
 def test_execute_with_cdr(circuit_type, fit_function, kwargs, random_state):
     circuit = random_x_z_cnot_circuit(
-        LineQubit.range(2), n_moments=5, random_state=random_state,
+        LineQubit.range(2),
+        n_moments=5,
+        random_state=random_state,
     )
     circuit = convert_from_mitiq(circuit, circuit_type)
     obs = Observable(PauliString("XZ"), PauliString("YY"))
@@ -125,7 +127,10 @@ def test_no_num_fit_parameters_with_custom_fit_raises_error():
 
 def test_execute_with_cdr_using_clifford_circuit():
     a, b = cirq.LineQubit.range(2)
-    clifCirc = cirq.Circuit(cirq.H.on(a), cirq.H.on(b),)
+    clifCirc = cirq.Circuit(
+        cirq.H.on(a),
+        cirq.H.on(b),
+    )
     obs = Observable(PauliString("XZ"), PauliString("YY"))
     cdr_value = execute_with_cdr(
         clifCirc, observable=obs, executor=execute, simulator=simulate

mitiq/cdr/tests/test_clifford_training_data.py

@@ -156,7 +156,9 @@ def test_generate_training_circuits_bad_methods():
 def test_generate_training_circuits_with_clifford_circuit():
     circuit = Circuit(cirq.ops.rx(0.0).on(cirq.LineQubit(0)))
     assert generate_training_circuits(
-        circuit, num_training_circuits=2, fraction_non_clifford=0.0,
+        circuit,
+        num_training_circuits=2,
+        fraction_non_clifford=0.0,
     ) == [circuit, circuit]
 
 

mitiq/interface/conversions.py

@@ -282,7 +282,8 @@ def new_scaling_function(
 
             scaled_circuit.remove_final_measurements()
             _transform_registers(
-                scaled_circuit, new_qregs=circuit.qregs,  # type: ignore
+                scaled_circuit,
+                new_qregs=circuit.qregs,  # type: ignore
             )
             if circuit.cregs and not scaled_circuit.cregs:  # type: ignore
                 scaled_circuit.add_register(*circuit.cregs)  # type: ignore

mitiq/interface/mitiq_braket/conversions.py

@@ -285,7 +285,8 @@ def _translate_two_qubit_braket_instruction_to_cirq_operation(
 
 
 def _translate_one_qubit_cirq_operation_to_braket_instruction(
-    op: Union[np.ndarray, cirq_ops.Operation], target: Optional[int] = None,
+    op: Union[np.ndarray, cirq_ops.Operation],
+    target: Optional[int] = None,
 ) -> List[Instruction]:
     """Translates a one-qubit Cirq operation to a (sequence of) Braket
     instruction(s) according to the following rules:

mitiq/interface/mitiq_braket/tests/test_conversions_braket.py

@@ -185,7 +185,7 @@ def test_from_braket_three_qubit_gates():
 
 
 def _rotation_of_pi_over_7(num_qubits):
-    matrix = np.identity(2 ** num_qubits)
+    matrix = np.identity(2**num_qubits)
     matrix[0:2, 0:2] = [
         [np.cos(np.pi / 7), np.sin(np.pi / 7)],
         [-np.sin(np.pi / 7), np.cos(np.pi / 7)],
@@ -307,7 +307,11 @@ def test_to_from_braket_uncommon_two_qubit_gates(uncommon_gate):
 
 
 @pytest.mark.parametrize(
-    "common_gate", [ops.TOFFOLI, ops.FREDKIN,],
+    "common_gate",
+    [
+        ops.TOFFOLI,
+        ops.FREDKIN,
+    ],
 )
 def test_to_from_braket_common_three_qubit_gates(common_gate):
     """These gates should stay the same (i.e., not get decomposed) when

mitiq/interface/mitiq_pennylane/tests/test_conversions_pennylane.py

@@ -98,7 +98,8 @@ def test_non_consecutive_wires_error():
     with qml.tape.QuantumTape() as tape:
         qml.CNOT(wires=[0, 2])
     with pytest.raises(
-        UnsupportedQuantumTapeError, match="contiguously pack",
+        UnsupportedQuantumTapeError,
+        match="contiguously pack",
     ):
         from_pennylane(tape)
 

mitiq/interface/mitiq_pyquil/tests/test_zne_mitiq_pyquil.py

@@ -41,7 +41,10 @@ def noiseless_executor(program: pyquil.Program) -> float:
 
 def test_run_factory():
     (qp,) = benchmarks.generate_rb_circuits(
-        n_qubits=1, num_cliffords=TEST_DEPTH, trials=1, return_type="pyquil",
+        n_qubits=1,
+        num_cliffords=TEST_DEPTH,
+        trials=1,
+        return_type="pyquil",
     )
 
     fac = zne.inference.RichardsonFactory([1.0, 2.0, 3.0])
@@ -55,15 +58,21 @@ def test_run_factory():
 
 def test_execute_with_zne():
     (qp,) = benchmarks.generate_rb_circuits(
-        n_qubits=1, num_cliffords=TEST_DEPTH, trials=1, return_type="pyquil",
+        n_qubits=1,
+        num_cliffords=TEST_DEPTH,
+        trials=1,
+        return_type="pyquil",
     )
     result = zne.execute_with_zne(qp, noiseless_executor)
     assert np.isclose(result, 1.0, atol=1e-5)
 
 
 def test_mitigate_executor():
     (qp,) = benchmarks.generate_rb_circuits(
-        n_qubits=1, num_cliffords=TEST_DEPTH, trials=1, return_type="pyquil",
+        n_qubits=1,
+        num_cliffords=TEST_DEPTH,
+        trials=1,
+        return_type="pyquil",
     )
 
     new_executor = zne.mitigate_executor(noiseless_executor)
@@ -78,7 +87,10 @@ def decorated_executor(qp: pyquil.Program) -> float:
 
 def test_zne_decorator():
     (qp,) = benchmarks.generate_rb_circuits(
-        n_qubits=1, num_cliffords=TEST_DEPTH, trials=1, return_type="pyquil",
+        n_qubits=1,
+        num_cliffords=TEST_DEPTH,
+        trials=1,
+        return_type="pyquil",
     )
 
     result = decorated_executor(qp)

mitiq/interface/mitiq_qiskit/qiskit_utils.py

@@ -80,7 +80,10 @@ def execute_with_shots(
     """
 
     return execute_with_shots_and_noise(
-        circuit, obs, noise_model=None, shots=shots,
+        circuit,
+        obs,
+        noise_model=None,
+        shots=shots,
     )
 
 

mitiq/interface/mitiq_qiskit/tests/test_qiskit_utils.py

@@ -32,7 +32,7 @@
 
 
 def test_execute():
-    """ Tests the Qiskit wavefunction simulation executor returns
+    """Tests the Qiskit wavefunction simulation executor returns
     appropriate expectation value given an observable.
     """
 
@@ -47,7 +47,7 @@ def test_execute():
 
 
 def test_execute_with_shots():
-    """ Tests the Qiskit wavefunction sampling simulation executor returns
+    """Tests the Qiskit wavefunction sampling simulation executor returns
     appropriate expectation value given an observable.
     """
 
@@ -66,7 +66,7 @@ def test_execute_with_shots():
 
 
 def test_execute_with_depolarizing_noise_single_qubit():
-    """ Tests the noisy sampling executor across increasing levels
+    """Tests the noisy sampling executor across increasing levels
     of single qubit gate noise
     """
 
@@ -88,7 +88,7 @@ def test_execute_with_depolarizing_noise_single_qubit():
 
 
 def test_execute_with_depolarizing_noise_two_qubit():
-    """ Tests the noisy sampling executor across increasing levels of
+    """Tests the noisy sampling executor across increasing levels of
     two qubit gate noise.
     """
 
@@ -110,7 +110,7 @@ def test_execute_with_depolarizing_noise_two_qubit():
 
 
 def test_execute_with_shots_and_depolarizing_noise_single_qubit():
-    """ Tests the noisy sampling executor across increasing levels
+    """Tests the noisy sampling executor across increasing levels
     of single qubit gate noise.
     """
 
@@ -133,7 +133,7 @@ def test_execute_with_shots_and_depolarizing_noise_single_qubit():
 
 
 def test_execute_with_shots_and_depolarizing_noise_two_qubit():
-    """ Tests the noisy sampling executor across increasing levels of
+    """Tests the noisy sampling executor across increasing levels of
     two qubit gate noise.
     """
 

mitiq/observable/observable.py

@@ -25,7 +25,7 @@
 
 class Observable:
     """A quantum observable typically used to compute its mitigated expectation
-     value.
+    value.
 
     """
 
@@ -115,7 +115,7 @@ def matrix(
             qubit_indices = self.qubit_indices
         n = len(qubit_indices)
 
-        matrix = np.zeros(shape=(2 ** n, 2 ** n), dtype=dtype)
+        matrix = np.zeros(shape=(2**n, 2**n), dtype=dtype)
         for pauli in self._paulis:
             matrix += pauli.matrix(
                 qubit_indices_to_include=qubit_indices

mitiq/observable/tests/test_pauli.py

@@ -222,25 +222,41 @@ def test_expectation_from_measurements_identity(seed, nqubits):
         rng.randint(low=0, high=1 + 1, size=(100, nqubits)).tolist()
     )
     assert np.isclose(
-        pauli._expectation_from_measurements(measurements), coeff,
+        pauli._expectation_from_measurements(measurements),
+        coeff,
     )
 
 
 def test_expectation_from_measurements_two_qubits():
     measurements = MeasurementResult([[0, 1] * 1_000])
 
     z0 = PauliString(spec="Z", support=(0,))
-    assert np.isclose(z0._expectation_from_measurements(measurements), 1.0,)
+    assert np.isclose(
+        z0._expectation_from_measurements(measurements),
+        1.0,
+    )
     zi = PauliString(spec="ZI")
-    assert np.isclose(zi._expectation_from_measurements(measurements), 1.0,)
+    assert np.isclose(
+        zi._expectation_from_measurements(measurements),
+        1.0,
+    )
 
     z1 = PauliString(spec="Z", support=(1,))
-    assert np.isclose(z1._expectation_from_measurements(measurements), -1.0,)
+    assert np.isclose(
+        z1._expectation_from_measurements(measurements),
+        -1.0,
+    )
     iz = PauliString(spec="IZ")
-    assert np.isclose(iz._expectation_from_measurements(measurements), -1.0,)
+    assert np.isclose(
+        iz._expectation_from_measurements(measurements),
+        -1.0,
+    )
 
     zz = PauliString(spec="ZZ")
-    assert np.isclose(zz._expectation_from_measurements(measurements), -1.0,)
+    assert np.isclose(
+        zz._expectation_from_measurements(measurements),
+        -1.0,
+    )
 
 
 def test_pstringcollection():

mitiq/pec/channels.py

@@ -126,12 +126,13 @@ def matrix_to_vector(density_matrix: np.ndarray) -> np.ndarray:
 
 
 def _safe_sqrt(
-    perfect_square: int, error_str: str = "The input must be a square number.",
+    perfect_square: int,
+    error_str: str = "The input must be a square number.",
 ) -> int:
     """Takes the square root of the input integer and
     raises an error if the input is not a perfect square."""
     square_root = int(np.round(np.sqrt(perfect_square)))
-    if square_root ** 2 != perfect_square:
+    if square_root**2 != perfect_square:
         raise ValueError(error_str)
     return square_root
 
@@ -182,7 +183,7 @@ def choi_to_super(choi_state: np.ndarray) -> np.ndarray:
 
     choi_kl_ij = choi_state.reshape(dim, dim, dim, dim)
     choi_ki_lj = choi_kl_ij.transpose(0, 2, 1, 3)
-    super_not_normalized = choi_ki_lj.reshape(dim ** 2, dim ** 2)
+    super_not_normalized = choi_ki_lj.reshape(dim**2, dim**2)
     return dim * super_not_normalized