metobs_toolkit.dataset.Dataset.sync_records#

Dataset.sync_records(obstype: str = 'temp', timestamp_shift_tolerance: str | Timedelta = '2min', freq_shift_tolerance: str | Timedelta = '1min', fixed_origin: Timedelta | None = None) → None[source]#

Synchronize records of sensor data across stations.

Synchronize records of sensor data across stations (for a specific observation type). This method aligns the sensor data of a specified observation type (obstype) across all stations by resampling the data to a common frequency and ensuring alignment errors of timestamps within specified tolerances.

Parameters:

obstype (str, optional) – The observation type to synchronize (e.g., “temp” for temperature). Default is “temp”.
timestamp_shift_tolerance (str or pandas.Timedelta, optional) – The maximum allowed time shift tolerance for aligning data during resampling. Default is 2 minutes.
freq_shift_tolerance (str or pandas.Timedelta, optional) – The maximum allowed error in simplifying the target frequency. Default is “1min”.
fixed_origin (pandas.Timestamp, or None, optional) – A fixed origin timestamp for resampling. If None, the origin is determined automatically. Default is None.

Return type:

None.

Note

In general, this method is a wrapper for Dataset.resample() but making sure that the target frequencies are naturel multiples of each other thus ensuring syncronisation accros stations.

Warning

Since the gaps depend on the record’s frequency and origin, all gaps are removed and re-located. All progress in gap(filling) will be lost.
Cumulative tolerance errors can be introduced when this method is called multiple times.