fix: numpy default NaT handling

Author: ilan-gold

src/zarr/core/dtype/npy/time.py

@@ -559,7 +559,7 @@ def default_scalar(self) -> np.timedelta64:
         This method provides a default value for the timedelta64 scalar, which is
         a 'Not-a-Time' (NaT) value.
         """
-        return np.timedelta64("NaT")
+        return np.timedelta64("NaT", self.unit)
 
     def from_json_scalar(self, data: JSON, *, zarr_format: ZarrFormat) -> np.timedelta64:
         """

tests/test_dtype/test_npy/test_time.py

@@ -115,7 +115,7 @@ class TestTimeDelta64(_TestTimeBase):
 
     cast_value_params = (
         (TimeDelta64(unit="ns", scale_factor=1), "1", np.timedelta64(1, "ns")),
-        (TimeDelta64(unit="ns", scale_factor=1), "NaT", np.timedelta64("NaT")),
+        (TimeDelta64(unit="ns", scale_factor=1), "NaT", np.timedelta64("NaT", "ns")),
     )
     invalid_scalar_params = (
         (TimeDelta64(unit="Y", scale_factor=1), 1.3),
@@ -148,6 +148,12 @@ def test_time_scale_factor_too_low() -> None:
         TimeDelta64(scale_factor=scale_factor)
 
 
+def test_default_is_NaT() -> None:
+    np.testing.assert_equal(
+        TimeDelta64(unit="ns", scale_factor=1).default_scalar(), np.timedelta64("NaT", "ns")
+    )
+
+
 def test_time_scale_factor_too_high() -> None:
     """
     Test that an invalid unit raises a ValueError.