Wrap calls to deprecated functions in qubit_characterizations_test.py (#8031)

Running `check/pytest` in Python 3.11 on a Debian Linux system produced
a few warnings similar to this:

```
cirq-core/cirq/experiments/qubit_characterizations_test.py::test_parallel_single_qubit_parallel_single_qubit_randomized_benchmarking
   /usr/local/google/home/mhucka/projects/github/cirq-pr-warnings/cirq-core/cirq/experiments/qubit_characterizations_test.py:130: DeprecationWarning: parallel_single_qubit_randomized_benchmarking was used but is deprecated.
   It will be removed in cirq v2.0.
   please use parallel_single_qubit_rb instead

     results = parallel_single_qubit_randomized_benchmarking(
```

These are not critical, but it is a little bit surprising to see them in
Cirq's own unit tests.

This wraps the relevant calls in `qubit_characterizations_test.py` with
the `cirq.testing.assert_deprecated(…)` context manager to indicate that
the deprecation messages are known and expected, and keep them from
bubbling up to developers.

---------

Co-authored-by: Pavol Juhas <juhas@google.com>

Author: mhucka

cirq-core/cirq/experiments/qubit_characterizations_test.py

@@ -14,9 +14,6 @@
 
 from __future__ import annotations
 
-import os
-from unittest import mock
-
 import matplotlib.pyplot as plt
 import numpy as np
 import pytest
@@ -107,29 +104,31 @@ def check_distinct(unitaries):
         assert num_x <= 1
 
 
-@mock.patch.dict(os.environ, clear='CIRQ_TESTING')
 def test_single_qubit_randomized_benchmarking() -> None:
     # Check that the ground state population at the end of the Clifford
     # sequences is always unity.
     simulator = sim.Simulator()
     qubit = GridQubit(0, 0)
     num_cfds = tuple(np.logspace(np.log10(5), 3, 5, dtype=int))
-    results = single_qubit_randomized_benchmarking(simulator, qubit, num_clifford_range=num_cfds)
+    with cirq.testing.assert_deprecated('use single_qubit_rb instead', deadline='v2.0'):
+        results = single_qubit_randomized_benchmarking(
+            simulator, qubit, num_clifford_range=num_cfds
+        )
     g_pops = np.asarray(results.data)[:, 1]
     assert np.isclose(np.mean(g_pops), 1.0)
     assert np.isclose(results.pauli_error(), 0.0, atol=1e-7)  # warning is expected
 
 
-@mock.patch.dict(os.environ, clear='CIRQ_TESTING')
 def test_parallel_single_qubit_parallel_single_qubit_randomized_benchmarking() -> None:
     # Check that the ground state population at the end of the Clifford
     # sequences is always unity.
     simulator = sim.Simulator()
     qubits = (GridQubit(0, 0), GridQubit(0, 1))
     num_cfds = range(5, 20, 5)
-    results = parallel_single_qubit_randomized_benchmarking(
-        simulator, num_clifford_range=num_cfds, repetitions=100, qubits=qubits
-    )
+    with cirq.testing.assert_deprecated('use parallel_single_qubit_rb instead', deadline='v2.0'):
+        results = parallel_single_qubit_randomized_benchmarking(
+            simulator, num_clifford_range=num_cfds, repetitions=100, qubits=qubits
+        )
     for qubit in qubits:
         g_pops = np.asarray(results.results_dictionary[qubit].data)[:, 1]
         assert np.isclose(np.mean(g_pops), 1.0)
@@ -140,14 +139,14 @@ def test_parallel_single_qubit_parallel_single_qubit_randomized_benchmarking() -
     _ = results.plot_integrated_histogram()
 
 
-@mock.patch.dict(os.environ, clear='CIRQ_TESTING')
 def test_parallel_single_qubit_randomized_benchmarking_with_noise() -> None:
     simulator = sim.Simulator(noise=cirq.depolarize(1e-3), seed=0)
     qubits = (GridQubit(0, 0), GridQubit(0, 1))
     num_cfds = range(5, 7, 1)
-    results = parallel_single_qubit_randomized_benchmarking(
-        simulator, num_clifford_range=num_cfds, repetitions=10, qubits=qubits
-    )
+    with cirq.testing.assert_deprecated('use parallel_single_qubit_rb instead', deadline='v2.0'):
+        results = parallel_single_qubit_randomized_benchmarking(
+            simulator, num_clifford_range=num_cfds, repetitions=10, qubits=qubits
+        )
     for qubit in qubits:
         g_pops = np.asarray(results.results_dictionary[qubit].data)[:, 1]
         assert np.isclose(np.mean(g_pops), 0.99, atol=1e-2)