Avoid np._bool

cirq-core/cirq/linalg/predicates.py

@@ -20,7 +20,7 @@
 from cirq import value
 
 
-def is_diagonal(matrix: np.ndarray, *, atol: float = 1e-8) -> np.bool_:
+def is_diagonal(matrix: np.ndarray, *, atol: float = 1e-8) -> bool:
     """Determines if a matrix is a approximately diagonal.
 
     A matrix is diagonal if i!=j implies m[i,j]==0.

cirq-core/cirq/linalg/tolerance.py

@@ -22,19 +22,19 @@
     from numpy.typing import ArrayLike
 
 
-def all_near_zero(a: 'ArrayLike', *, atol: float = 1e-8) -> np.bool_:
+def all_near_zero(a: 'ArrayLike', *, atol: float = 1e-8) -> bool:
     """Checks if the tensor's elements are all near zero.
 
     Args:
         a: Tensor of elements that could all be near zero.
         atol: Absolute tolerance.
     """
-    return np.all(np.less_equal(np.abs(a), atol))
+    return bool(np.all(np.less_equal(np.abs(a), atol)))
 
 
 def all_near_zero_mod(
     a: Union[float, complex, Iterable[float], np.ndarray], period: float, *, atol: float = 1e-8
-) -> np.bool_:
+) -> bool:
     """Checks if the tensor's elements are all near multiples of the period.
 
     Args:
@@ -43,7 +43,7 @@ def all_near_zero_mod(
         atol: Absolute tolerance.
     """
     b = (np.asarray(a) + period / 2) % period - period / 2
-    return np.all(np.less_equal(np.abs(b), atol))
+    return bool(np.all(np.less_equal(np.abs(b), atol)))
 
 
 def near_zero(a: float, *, atol: float = 1e-8) -> bool:

docs/tutorials/hidden_linear_function.ipynb

@@ -417,7 +417,7 @@
     "    ans = []\n",
     "    while np.max(A) != 0:\n",
     "        edges_group = []\n",
-    "        used = np.zeros(n, dtype=np.bool)\n",
+    "        used = np.zeros(n, dtype=bool)\n",
     "        for i in range(n):\n",
     "            for j in range(n):\n",
     "                if A[i][j] == 1 and not used[i] and not used[j]:\n",
@@ -667,4 +667,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}