Change dtype repr for Numpy 1.24 (#5991)

* Change numpy dtype repr

* Enforce deprecation of np attributes deprecated in NumPy 1.20

Also fail when attributes are used in eval expressions.

This prepares for upgrade to NumPy 1.24 which removes deprecated names.

* update repr test data for numpy dtypes

* break string not found by black

* fix dumb typo

---------

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

cirq-core/cirq/_compat.py

@@ -165,9 +165,7 @@ def _print(self, expr, **kwargs):
         return Printer().doprint(value)
 
     if isinstance(value, np.ndarray):
-        if np.issubdtype(value.dtype, np.datetime64):
-            return f'np.array({value.tolist()!r}, dtype=np.{value.dtype!r})'
-        return f'np.array({value.tolist()!r}, dtype=np.{value.dtype})'
+        return f'np.array({value.tolist()!r}, dtype=np.{value.dtype!r})'
 
     if isinstance(value, pd.MultiIndex):
         return f'pd.MultiIndex.from_tuples({repr(list(value))}, names={repr(list(value.names))})'

cirq-core/cirq/_compat_test.py

@@ -120,7 +120,10 @@ def __repr__(self):
             return dataclass_repr(self, namespace='cirq.testing')
 
     tc = TestClass2(np.ones(3))
-    assert repr(tc) == "cirq.testing.TestClass2(x=np.array([1.0, 1.0, 1.0], dtype=np.float64))"
+    assert (
+        repr(tc)
+        == "cirq.testing.TestClass2(x=np.array([1.0, 1.0, 1.0], dtype=np.dtype('float64')))"
+    )
 
 
 def test_proper_eq():

cirq-core/cirq/linalg/decompositions_test.py

@@ -367,12 +367,12 @@ def test_kak_repr():
 cirq.KakDecomposition(
     interaction_coefficients=(0.5, 0.25, 0),
     single_qubit_operations_before=(
-        np.array([[0j, (1+0j)], [(1+0j), 0j]], dtype=np.complex128),
-        np.array([[0j, -1j], [1j, 0j]], dtype=np.complex128),
+        np.array([[0j, (1+0j)], [(1+0j), 0j]], dtype=np.dtype('complex128')),
+        np.array([[0j, -1j], [1j, 0j]], dtype=np.dtype('complex128')),
     ),
     single_qubit_operations_after=(
-        np.array([[1.0, 0.0], [0.0, 1.0]], dtype=np.float64),
-        np.array([[(1+0j), 0j], [0j, (-1+0j)]], dtype=np.complex128),
+        np.array([[1.0, 0.0], [0.0, 1.0]], dtype=np.dtype('float64')),
+        np.array([[(1+0j), 0j], [0j, (-1+0j)]], dtype=np.dtype('complex128')),
     ),
     global_phase=1)
 """.strip()

cirq-core/cirq/ops/kraus_channel_test.py

@@ -105,8 +105,8 @@ def test_kraus_channel_repr():
         repr(x_meas)
         == """\
 cirq.KrausChannel(kraus_ops=[\
-np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.complex64), \
-np.array([[(0.5+0j), (-0.5+0j)], [(-0.5+0j), (0.5+0j)]], dtype=np.complex64)], \
+np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.dtype('complex64')), \
+np.array([[(0.5+0j), (-0.5+0j)], [(-0.5+0j), (0.5+0j)]], dtype=np.dtype('complex64'))], \
 key='x_meas')"""
     )
 

cirq-core/cirq/ops/measurement_gate_test.py

@@ -317,23 +317,28 @@ def test_op_repr():
             b,
             key='out',
             invert_mask=(False, True),
-            confusion_map={(0,): np.array([[0, 1], [1, 0]], dtype=np.int64)},
+            confusion_map={(0,): np.array([[0, 1], [1, 0]], dtype=np.dtype('int64'))},
         )
     ) == (
         "cirq.measure(cirq.LineQubit(0), cirq.LineQubit(1), "
         "key=cirq.MeasurementKey(name='out'), "
         "invert_mask=(False, True), "
-        "confusion_map={(0,): np.array([[0, 1], [1, 0]], dtype=np.int64)})"
+        "confusion_map={(0,): np.array([[0, 1], [1, 0]], dtype=np.dtype('int64'))})"
     )
 
 
 def test_repr():
     gate = cirq.MeasurementGate(
-        3, 'a', (True, False), (1, 2, 3), {(2,): np.array([[0, 1], [1, 0]], dtype=np.int64)}
+        3,
+        'a',
+        (True, False),
+        (1, 2, 3),
+        {(2,): np.array([[0, 1], [1, 0]], dtype=np.dtype('int64'))},
     )
     assert repr(gate) == (
         "cirq.MeasurementGate(3, cirq.MeasurementKey(name='a'), (True, False), "
-        "qid_shape=(1, 2, 3), confusion_map={(2,): np.array([[0, 1], [1, 0]], dtype=np.int64)})"
+        "qid_shape=(1, 2, 3), "
+        "confusion_map={(2,): np.array([[0, 1], [1, 0]], dtype=np.dtype('int64'))})"
     )
 
 

cirq-core/cirq/ops/mixed_unitary_channel_test.py

@@ -95,16 +95,16 @@ def test_matrix_mixture_str():
 
 def test_matrix_mixture_repr():
     mix = [
-        (0.5, np.array([[1, 0], [0, 1]], dtype=np.complex64)),
-        (0.5, np.array([[0, 1], [1, 0]], dtype=np.complex64)),
+        (0.5, np.array([[1, 0], [0, 1]], dtype=np.dtype('complex64'))),
+        (0.5, np.array([[0, 1], [1, 0]], dtype=np.dtype('complex64'))),
     ]
     half_flip = cirq.MixedUnitaryChannel(mix, key='flip')
     assert (
         repr(half_flip)
         == """\
 cirq.MixedUnitaryChannel(mixture=[\
-(0.5, np.array([[(1+0j), 0j], [0j, (1+0j)]], dtype=np.complex64)), \
-(0.5, np.array([[0j, (1+0j)], [(1+0j), 0j]], dtype=np.complex64))], \
+(0.5, np.array([[(1+0j), 0j], [0j, (1+0j)]], dtype=np.dtype('complex64'))), \
+(0.5, np.array([[0j, (1+0j)], [(1+0j), 0j]], dtype=np.dtype('complex64')))], \
 key='flip')"""
     )
 

cirq-core/cirq/protocols/json_test_data/Result.repr_inward

@@ -1 +1 @@
-[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=bool)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)})]
+[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=np.dtype('bool'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)})]

cirq-core/cirq/protocols/json_test_data/ResultDict.repr

@@ -1 +1 @@
-[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[True, True, False, True, False]], [[False, True, True, False, False]], [[True, False, True, False, True]]], dtype=bool)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[1, 1, 0, 1, 0]], [[0, 1, 1, 0, 0]], [[1, 0, 1, 0, 1]]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[1, 1, 0, 1, 0]], [[0, 1, 1, 0, 0]], [[1, 0, 1, 0, 1]]], dtype=np.uint8), 'n': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int64)})]
+[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[True, True, False, True, False]], [[False, True, True, False, False]], [[True, False, True, False, True]]], dtype=np.dtype('bool'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[1, 1, 0, 1, 0]], [[0, 1, 1, 0, 0]], [[1, 0, 1, 0, 1]]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), records={'m': np.array([[[1, 1, 0, 1, 0]], [[0, 1, 1, 0, 0]], [[1, 0, 1, 0, 1]]], dtype=np.uint8), 'n': np.array([[[0, 1, 2]], [[3, 4, 5]], [[6, 7, 8]]], dtype=np.int64)})]

cirq-core/cirq/protocols/json_test_data/ResultDict.repr_inward

@@ -1 +1 @@
-[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=bool)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)})]
+[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=np.dtype('bool'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)})]

cirq-core/cirq/protocols/json_test_data/TrialResult.repr_inward

@@ -1 +1 @@
-[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=np.bool)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint8)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint16)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint32)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.uint64)}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.uint8), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int64)})]
+[cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[True, True, False, True, False], [False, True, True, False, False], [True, False, True, False, True]], dtype=np.dtype('bool'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.dtype('uint8'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('int8'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('int16'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('int32'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('int64'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('uint8'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('uint16'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('uint32'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('uint64'))}), cirq.ResultDict(params=cirq.ParamResolver({sympy.Symbol('a'): 0.5}), measurements={'m': np.array([[1, 1, 0, 1, 0], [0, 1, 1, 0, 0], [1, 0, 1, 0, 1]], dtype=np.dtype('uint8')), 'n': np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.dtype('int64'))})]

cirq-core/cirq/sim/density_matrix_simulator.py

@@ -303,7 +303,7 @@ def __repr__(self) -> str:
         # Dtype doesn't have a good repr, so we work around by invoking __name__.
         return (
             f'cirq.DensityMatrixStepResult(sim_state={self._sim_state!r},'
-            f' dtype=np.{self._dtype.__name__})'
+            f' dtype=np.{np.dtype(self._dtype)!r})'
         )