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- import numpy as np
- from pandas._libs.tslibs.dtypes import abbrev_to_npy_unit
- from pandas._libs.tslibs.vectorized import is_date_array_normalized
- # a datetime64 ndarray which *is* normalized
- day_arr = np.arange(10, dtype="i8").view("M8[D]")
- class TestIsDateArrayNormalized:
- def test_is_date_array_normalized_day(self):
- arr = day_arr
- abbrev = "D"
- unit = abbrev_to_npy_unit(abbrev)
- result = is_date_array_normalized(arr.view("i8"), None, unit)
- assert result is True
- def test_is_date_array_normalized_seconds(self):
- abbrev = "s"
- arr = day_arr.astype(f"M8[{abbrev}]")
- unit = abbrev_to_npy_unit(abbrev)
- result = is_date_array_normalized(arr.view("i8"), None, unit)
- assert result is True
- arr[0] += np.timedelta64(1, abbrev)
- result2 = is_date_array_normalized(arr.view("i8"), None, unit)
- assert result2 is False
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