Modify some numpy types to be compatible with numpy>=1.20 (quantuml…

…ib#5668)

Part of quantumlib#3767

cirq/experiments/qubit_characterizations.py

@@ -431,7 +431,7 @@ def _measurement(two_qubit_circuit: circuits.Circuit) -> np.ndarray:
 
     # Stores all 27 measured probabilities (P_00, P_01, P_10 after 9
     # different basis rotations).
-    probs = np.array([])
+    probs: np.ndarray = np.array([])
 
     rots = [ops.X**0, ops.X**0.5, ops.Y**0.5]
 

cirq/linalg/combinators.py

@@ -39,7 +39,7 @@ def kron(*factors: Union[np.ndarray, complex, float], shape_len: int = 2) -> np.
     Returns:
         The kronecker product of all the inputs.
     """
-    product = np.ones(shape=(1,) * shape_len)
+    product: np.ndarray = np.ones(shape=(1,) * shape_len)
     for m in factors:
         product = np.kron(product, m)
     return np.array(product)

cirq/protocols/kraus_protocol.py

@@ -33,7 +33,7 @@
 # Sequence[np.ndarray] to ensure the method has the correct type signature in
 # that case. It is checked for using `is`, so it won't have a false positive
 # if the user provides a different (np.array([]),) value.
-RaiseTypeErrorIfNotProvided = (np.array([]),)
+RaiseTypeErrorIfNotProvided: Tuple[np.ndarray] = (np.array([]),)
 
 
 TDefault = TypeVar('TDefault')

cirq/protocols/kraus_protocol_test.py

@@ -14,15 +14,15 @@
 
 """Tests for kraus_protocol.py."""
 
-from typing import Iterable, Sequence, Tuple
+from typing import Iterable, List, Sequence, Tuple
 
 import numpy as np
 import pytest
 
 import cirq
 
 
-LOCAL_DEFAULT = [np.array([])]
+LOCAL_DEFAULT: List[np.ndarray] = [np.array([])]
 
 
 def test_kraus_no_methods():

cirq/protocols/unitary_protocol_test.py

@@ -18,7 +18,7 @@
 
 import cirq
 
-m0 = np.array([])
+m0: np.ndarray = np.array([])
 # yapf: disable
 # X on one qubit
 m1 = np.array([[0, 1],

cirq/qis/clifford_tableau.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import abc
-from typing import Any, Dict, List, Sequence, TYPE_CHECKING
+from typing import Any, Dict, List, Optional, Sequence, TYPE_CHECKING
 import numpy as np
 
 from cirq import protocols
@@ -441,7 +441,7 @@ def destabilizers(self) -> List['cirq.DensePauliString']:
         generators above generate the full Pauli group on n qubits."""
         return [self._row_to_dense_pauli(i) for i in range(self.n)]
 
-    def _measure(self, q, prng: np.random.RandomState) -> int:
+    def _measure(self, q, prng: np.random.RandomState = np.random) -> int:
         """Performs a projective measurement on the q'th qubit.
 
         Returns: the result (0 or 1) of the measurement.
@@ -583,6 +583,6 @@ def apply_global_phase(self, coefficient: linear_dict.Scalar):
         pass
 
     def measure(
-        self, axes: Sequence[int], seed: 'cirq.RANDOM_STATE_OR_SEED_LIKE' = None
+        self, axes: Sequence[int], seed: Optional['cirq.RANDOM_STATE_OR_SEED_LIKE'] = None
     ) -> List[int]:
         return [self._measure(axis, seed) for axis in axes]

cirq/testing/lin_alg_utils.py

@@ -164,7 +164,7 @@ def assert_allclose_up_to_global_phase(
     rtol: float = 1e-7,
     atol: float,  # Require atol to be specified
     equal_nan: bool = True,
-    err_msg: Optional[str] = '',
+    err_msg: str = '',
     verbose: bool = True,
 ) -> None:
     """Checks if a ~= b * exp(i t) for some t.

cirq/vis/histogram.py

@@ -92,7 +92,7 @@ def integrated_histogram(
 
     if not show_zero:
         bin_values = np.linspace(0, 1, n + 1)
-        parameter_values = sorted(np.concatenate(([0], float_data)))
+        parameter_values = sorted(np.concatenate((np.array([0]), np.array(float_data))))
     else:
         bin_values = np.linspace(0, 1, n)
         parameter_values = sorted(float_data)