Fix formatting

test/python/algorithms/test_observables_evaluator.py

@@ -72,9 +72,7 @@ def _run_test(
  observables: ListOrDict[BaseOperator | PauliSumOp],
  estimator: Estimator,
  ):
- result = estimate_observables(
- estimator, quantum_state, observables, None, self.threshold
- )
+ result = estimate_observables(estimator, quantum_state, observables, None, self.threshold)
 
  if isinstance(observables, dict):
  np.testing.assert_equal(list(result.keys()), list(expected_result.keys()))

test/python/circuit/library/test_evolved_op_ansatz.py

@@ -38,7 +38,6 @@ def test_evolved_op_ansatz(self, use_opflow):
  evo = EvolvedOperatorAnsatz(ops, 2)
  parameters = evo.parameters
 
-
  else:
  ops = [Pauli("Z" * num_qubits), Pauli("Y" * num_qubits), Pauli("X" * num_qubits)]
  evo = EvolvedOperatorAnsatz(ops, 2)

test/python/opflow/test_expectation_factory.py

@@ -37,4 +37,3 @@ def test_aer_simulator_pauli_sum(self):
  with self.subTest("Include custom"):
  expectation = ExpectationFactory.build(op, backend, include_custom=True)
  self.assertIsInstance(expectation, AerPauliExpectation)
-∂

test/python/opflow/test_gradients.py

@@ -885,7 +885,9 @@ def grad_combo_fn(x):
  qc = RealAmplitudes(2, reps=1)
 
  with self.assertWarns(DeprecationWarning):
- grad_op = ListOp([StateFn(qc.decompose())], combo_fn=combo_fn, grad_combo_fn=grad_combo_fn)
+ grad_op = ListOp(
+ [StateFn(qc.decompose())], combo_fn=combo_fn, grad_combo_fn=grad_combo_fn
+ )
  grad = Gradient(grad_method=method).convert(grad_op)
 
  value_dict = dict(zip(qc.ordered_parameters, np.random.rand(len(qc.ordered_parameters))))
@@ -1152,13 +1154,13 @@ def test_gradient_wrapper(self, backend_type):
  with self.assertWarns(DeprecationWarning):
  if method == "fin_diff":
  np.random.seed(8)
- prob_grad = Gradient(grad_method=method, epsilon=shots ** (-1 / 6.0)).gradient_wrapper(
+ prob_grad = Gradient(
+ grad_method=method, epsilon=shots ** (-1 / 6.0)
+ ).gradient_wrapper(operator=op, bind_params=params, backend=q_instance)
+ else:
+ prob_grad = Gradient(grad_method=method).gradient_wrapper(
  operator=op, bind_params=params, backend=q_instance
  )
- else:
- prob_grad = Gradient(grad_method=method).gradient_wrapper(
- operator=op, bind_params=params, backend=q_instance
- )
 
  values = [[np.pi / 4, 0], [np.pi / 4, np.pi / 4], [np.pi / 2, np.pi]]
  correct_values = [
@@ -1535,7 +1537,7 @@ def test_overlap_qfi_raises_on_multiparam(self):
 
  with self.assertRaises(NotImplementedError):
  with self.assertWarns(DeprecationWarning):
- _ = QFI("overlap_diag").convert(StateFn(circuit), [x])
+  _ = QFI("overlap_diag").convert(StateFn(circuit), [x])
 
  def test_overlap_qfi_raises_on_unsupported_gate(self):
  """Test the overlap QFI raises an appropriate error on multi-param unbound gates."""

test/python/opflow/test_matrix_expectation.py

@@ -154,10 +154,14 @@ def test_pauli_expect_op_vector_state_vector(self):
 
  valids = [[+0, 0, 1, -1], [+0, 0, 0, 0], [-1, 1, 0, -0], [+1, 1, 1, 1]]
  converted_meas = self.expect.convert(~StateFn(paulis_op))
- np.testing.assert_array_almost_equal((converted_meas @ states_op).eval(), valids, decimal=1)
+ np.testing.assert_array_almost_equal(
+ (converted_meas @ states_op).eval(), valids, decimal=1
+ )
 
  sampled = self.sampler.convert(states_op)
- np.testing.assert_array_almost_equal((converted_meas @ sampled).eval(), valids, decimal=1)
+ np.testing.assert_array_almost_equal(
+ (converted_meas @ sampled).eval(), valids, decimal=1
+ )
 
  def test_multi_representation_ops(self):
  """Test observables with mixed representations"""

test/python/opflow/test_pauli_expectation.py

@@ -226,7 +226,9 @@ def test_grouped_pauli_expectation(self):
  num_circuits_ungrouped = len(self.sampler._circuit_ops_cache)
  self.assertEqual(num_circuits_ungrouped, 5)
 
- expect_op_grouped = PauliExpectation(group_paulis=True).convert(~StateFn(two_qubit_H2) @ wf)
+ expect_op_grouped = PauliExpectation(group_paulis=True).convert(
+ ~StateFn(two_qubit_H2) @ wf
+ )
 
  q_instance = QuantumInstance(
  BasicAer.get_backend("statevector_simulator"),