Change numpy dtype repr

Author: bnavigator

cirq-core/cirq/_compat.py

@@ -138,9 +138,7 @@ 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

@@ -110,7 +110,7 @@ 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 +317,23 @@ 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/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})'
         )
 
 

cirq-core/cirq/sim/density_matrix_simulator_test.py

@@ -951,9 +951,9 @@ def test_density_matrix_step_result_repr():
             )
         )
         == "cirq.DensityMatrixStepResult(sim_state=cirq.DensityMatrixSimulationState("
-        "initial_state=np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.complex64), "
+        "initial_state=np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.dtype('complex64')), "
         "qubits=(cirq.LineQubit(0),), "
-        "classical_data=cirq.ClassicalDataDictionaryStore()), dtype=np.complex64)"
+        "classical_data=cirq.ClassicalDataDictionaryStore()), dtype=np.dtype('complex64'))"
     )
 
 
@@ -1034,9 +1034,9 @@ def test_density_matrix_trial_result_repr():
     expected_repr = (
         "cirq.DensityMatrixTrialResult("
         "params=cirq.ParamResolver({'s': 1}), "
-        "measurements={'m': np.array([[1]], dtype=np.int32)}, "
+        "measurements={'m': np.array([[1]], dtype=np.dtype('int32'))}, "
         "final_simulator_state=cirq.DensityMatrixSimulationState("
-        "initial_state=np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.complex64), "
+        "initial_state=np.array([[(0.5+0j), (0.5+0j)], [(0.5+0j), (0.5+0j)]], dtype=np.dtype('complex64')), "
         "qubits=(cirq.LineQubit(0),), "
         "classical_data=cirq.ClassicalDataDictionaryStore()))"
     )

cirq-core/cirq/sim/sparse_simulator.py

@@ -282,5 +282,5 @@ def __repr__(self) -> str:
         # Dtype doesn't have a good repr, so we work around by invoking __name__.
         return (
             f'cirq.SparseSimulatorStep(sim_state={self._sim_state!r},'
-            f' dtype=np.{self._dtype.__name__})'
+            f' dtype=np.{np.dtype(self._dtype)!r})'
         )

cirq-core/cirq/sim/sparse_simulator_test.py

@@ -775,9 +775,9 @@ def test_sparse_simulator_repr():
     # No equality so cannot use cirq.testing.assert_equivalent_repr
     assert (
         repr(step) == "cirq.SparseSimulatorStep(sim_state=cirq.StateVectorSimulationState("
-        "initial_state=np.array([[0j, (1+0j)], [0j, 0j]], dtype=np.complex64), "
+        "initial_state=np.array([[0j, (1+0j)], [0j, 0j]], dtype=np.dtype('complex64')), "
         "qubits=(cirq.LineQubit(0), cirq.LineQubit(1)), "
-        "classical_data=cirq.ClassicalDataDictionaryStore()), dtype=np.complex64)"
+        "classical_data=cirq.ClassicalDataDictionaryStore()), dtype=np.dtype('complex64'))"
     )
 
 

cirq-core/cirq/sim/state_vector_simulator_test.py

@@ -35,9 +35,9 @@ def test_state_vector_trial_result_repr():
     expected_repr = (
         "cirq.StateVectorTrialResult("
         "params=cirq.ParamResolver({'s': 1}), "
-        "measurements={'m': np.array([[1]], dtype=np.int32)}, "
+        "measurements={'m': np.array([[1]], dtype=np.dtype('int32'))}, "
         "final_simulator_state=cirq.StateVectorSimulationState("
-        "initial_state=np.array([0j, (1+0j)], dtype=np.complex64), "
+        "initial_state=np.array([0j, (1+0j)], dtype=np.dtype('complex64')), "
         "qubits=(cirq.NamedQubit('a'),), "
         "classical_data=cirq.ClassicalDataDictionaryStore()))"
     )