ModelTimeSeries#

The ModelTimeSeries class stores timeseries data extracted from a dynamic GEE dataset (e.g., ERA5) for a specific observation type at a station. It is similar to the SensorData class and is typically used for comparison with observations, quality control, or gap filling.

ModelTimeSeries objects are usually accessed via the .modeldata attribute of Station or Dataset objects.

Constructor#

ModelTimeSeries(site, datarecords, ...)

Class for model-based timeseries at one location.

Attributes#

A summary of all the attributes (and properties) of the ModelTimeSeries class.

`ModelTimeSeries.df`	ModelTimeSeries DataFrame constructor.
`ModelTimeSeries.stationname`	Return the name of the station this SensorData belongs to.
`ModelTimeSeries.tz`	Return the timezone of the stored timestamps.
`ModelTimeSeries.start_datetime`	Return the start datetime of the series.
`ModelTimeSeries.end_datetime`	Return the end datetime of the series.
`ModelTimeSeries.freq`	Return the frequency of the series.

Methods#

A summary of all methods in the ModelTimeSeries class.

`ModelTimeSeries.get_info`([printout])	Print or return information about the ModelTimeSeries.
`ModelTimeSeries.make_plot`([linecolor, ax, ...])	Create a plot of the model time series.
`ModelTimeSeries.pd_plot`(**pdplotkwargs)	A wrapper on the pandas.series.plot function for ModelTimeSeries.
`ModelTimeSeries.to_xr`()	Convert a Modelimeseries object to an xarray.Dataset.

Special methods#

The ModelTimeSeries class implements several Python special methods for convenience:

__add__: Combine two ModelTimeSeries objects.
__eq__: Test equality between two ModelTimeSeries objects.
__str__ and __repr__: String representations for printing and debugging.