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Change dtype repr for Numpy 1.24 #5991

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merged 6 commits into from
Apr 3, 2023
+55 −34
Merged

Change dtype repr for Numpy 1.24 #5991

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adf31e6
Change numpy dtype repr
bnavigator Jan 28, 2023
dc4363a
Enforce deprecation of np attributes deprecated in NumPy 1.20
pavoljuhas Mar 10, 2023
9721fb2
update repr test data for numpy dtypes
bnavigator Mar 12, 2023
1b73421
break string not found by black
bnavigator Mar 18, 2023
3012777
fix dumb typo
bnavigator Apr 3, 2023
bd1fb48
Merge branch 'master' into core-np1.24
tanujkhattar Apr 3, 2023
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4 changes: 1 addition & 3 deletions cirq-core/cirq/_compat.py
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Expand Up @@ -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))})'
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5 changes: 4 additions & 1 deletion cirq-core/cirq/_compat_test.py
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Expand Up @@ -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():
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8 changes: 4 additions & 4 deletions cirq-core/cirq/linalg/decompositions_test.py
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Expand Up @@ -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()
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4 changes: 2 additions & 2 deletions cirq-core/cirq/ops/kraus_channel_test.py
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Expand Up @@ -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')"""
)

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13 changes: 9 additions & 4 deletions cirq-core/cirq/ops/measurement_gate_test.py
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Expand Up @@ -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'))})"
)


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8 changes: 4 additions & 4 deletions cirq-core/cirq/ops/mixed_unitary_channel_test.py
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Expand Up @@ -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')"""
)

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2 changes: 1 addition & 1 deletion cirq-core/cirq/protocols/json_test_data/Result.repr_inward
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[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)})]
2 changes: 1 addition & 1 deletion cirq-core/cirq/protocols/json_test_data/ResultDict.repr
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[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)})]
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Were these regenerated using repr(object) ? It looks like dtype=np.uint64 should also be dtype=np.dtype('uint32') instead ?

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do it yourself

2 changes: 1 addition & 1 deletion cirq-core/cirq/protocols/json_test_data/ResultDict.repr_inward
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[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)})]
2 changes: 1 addition & 1 deletion cirq-core/cirq/protocols/json_test_data/TrialResult.repr_inward
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[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'))})]
2 changes: 1 addition & 1 deletion cirq-core/cirq/sim/density_matrix_simulator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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})'
)


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