superleaf.timeseries.datetime_utils#

Functions

as_dict(dt)

get_date_range(start[, end, tz, fmt])

get_datetime_range(start, end[, delta, ...])

get_first_time_in_interval(t, start[, end])

get_hours_minutes_seconds(time_1[, time_2])

mean_time(timestamps[, weights, local, ...])

midpoint(dt1, dt2)

nearly_simultaneous(t1, t2, epsilon_seconds)

seconds_in_day(timestamps[, local])

times_to_radians(timestamps[, local])

to_date(dt[, tz, end_of_day])

to_datetime(dt[, tz])

to_period(period_or_start[, end])

to_seconds_in_day(timestamps[, local])

superleaf.timeseries.datetime_utils.to_datetime(dt, tz=None) → DateTime[source]#
superleaf.timeseries.datetime_utils.as_dict(dt) → Dict[str, int][source]#
superleaf.timeseries.datetime_utils.to_date(dt, tz=None, end_of_day=False) → datetime[source]#
superleaf.timeseries.datetime_utils.get_date_range(start, end=None, tz=None, fmt=None)[source]#
superleaf.timeseries.datetime_utils.get_datetime_range(start, end, delta=None, inclusive=False, **timedelta_kwargs) → List[datetime][source]#
superleaf.timeseries.datetime_utils.get_hours_minutes_seconds(time_1, time_2=None) → Tuple[int, int, float][source]#
superleaf.timeseries.datetime_utils.nearly_simultaneous(t1, t2, epsilon_seconds) → bool[source]#
superleaf.timeseries.datetime_utils.to_period(period_or_start, end=None, **delta_kwargs) → Interval[source]#
superleaf.timeseries.datetime_utils.to_seconds_in_day(timestamps, local=False) → ndarray[source]#
superleaf.timeseries.datetime_utils.midpoint(dt1, dt2) → datetime[source]#
superleaf.timeseries.datetime_utils.seconds_in_day(timestamps, local=False) → ndarray[source]#
superleaf.timeseries.datetime_utils.mean_time(timestamps, weights=None, local=False, nan_policy='propagate') → time[source]#
superleaf.timeseries.datetime_utils.times_to_radians(timestamps, local=False) → ndarray[source]#
superleaf.timeseries.datetime_utils.get_first_time_in_interval(t: time, start: datetime | Sequence[datetime], end: datetime | None = None) → datetime | None[source]#