Function _decode_datetime_with_pandas

xarray/coding/times.py:472–532

(
    flat_num_dates: np.ndarray,
    units: str,
    calendar: str,
    time_resolution: PDDatetimeUnitOptions = "ns",
)

def _decode_datetime_with_pandas(
    flat_num_dates: np.ndarray,
    units: str,
    calendar: str,
    time_resolution: PDDatetimeUnitOptions = "ns",
) -> np.ndarray:
    if not _is_standard_calendar(calendar):
        raise OutOfBoundsDatetime(
            f"Cannot decode times from a non-standard calendar, {calendar!r}, using "
            "pandas."
        )

    # Work around pandas.to_timedelta issue with dtypes smaller than int64 and
    # NumPy 2.0 by casting all int and uint data to int64 and uint64,
    # respectively. See https://github.com/pandas-dev/pandas/issues/56996 for
    # more details.
    if flat_num_dates.dtype.kind == "i":
        flat_num_dates = flat_num_dates.astype(np.int64)
    elif flat_num_dates.dtype.kind == "u":
        flat_num_dates = flat_num_dates.astype(np.uint64)

    try:
        time_unit, ref_date = _unpack_time_unit_and_ref_date(units)
        ref_date = _align_reference_date_and_unit(ref_date, time_unit)
        # here the highest wanted resolution is set
        ref_date = _align_reference_date_and_unit(ref_date, time_resolution)
    except ValueError as err:
        # ValueError is raised by pd.Timestamp for non-ISO timestamp
        # strings, in which case we fall back to using cftime
        raise OutOfBoundsDatetime from err

    _check_date_is_after_shift(ref_date, calendar)

    with warnings.catch_warnings():
        warnings.filterwarnings("ignore", "invalid value encountered", RuntimeWarning)
        if flat_num_dates.size > 0:
            # avoid size 0 datetimes GH1329
            _check_date_for_units_since_refdate(
                flat_num_dates.min(), time_unit, ref_date
            )
            _check_date_for_units_since_refdate(
                flat_num_dates.max(), time_unit, ref_date
            )

    # To avoid integer overflow when converting to nanosecond units for integer
    # dtypes smaller than np.int64 cast all integer and unsigned integer dtype
    # arrays to np.int64 (GH 2002, GH 6589).  Note this is safe even in the case
    # of np.uint64 values, because any np.uint64 value that would lead to
    # overflow when converting to np.int64 would not be representable with a
    # timedelta64 value, and therefore would raise an error in the lines above.
    if flat_num_dates.dtype.kind in "iu":
        flat_num_dates = flat_num_dates.astype(np.int64)
    elif flat_num_dates.dtype.kind == "f":
        flat_num_dates = flat_num_dates.astype(np.float64)

    timedeltas = _numbers_to_timedelta(
        flat_num_dates, time_unit, ref_date.unit, "datetimes"
    )