pastas.model.Model.get_output_series#

pastas.model.Model.get_output_series(tmin: pandas.Timestamp | str | None = None, tmax: pandas.Timestamp | str | None = None, add_contributions: bool = True, split_contributions: bool = True, **kwargs) → pandas.DataFrame#

Method to get all the modeled output time series from the Model.

Parameters:

  • tmin (pandas.Timestamp or str, optional) – A string or pandas.Timestamp with the start date for the simulation period (E.g. ‘1980-01-01 00:00:00’). Strings are converted to pandas.Timestamp internally. If none is provided, the tmin from the oseries is used.

  • tmax (pandas.Timestamp or str, optional) – A string or pandas.Timestamp with the end date for the simulation period (E.g. ‘2020-01-01 00:00:00’). Strings are converted to pandas.Timestamp internally. If none is provided, the tmax from the oseries is used.

  • add_contributions (bool, optional) – Add the contributions from the different stresses or not. Default is True.

  • split_contributions (bool, optional) – Passed on to ml.get_contributions. Split the contribution from recharge into evaporation and precipitation. See also ml.get_contributions. Default is True.

Returns:

df – Pandas DataFrame with the time series as columns and DatetimeIndex.

Return type:

pandas.DataFrame

Notes

Export the observed, simulated time series, residuals series, noise series (if present) and the contributions from the different stressmodels.

Examples

>>> df = ml.get_output_series(tmin="2000", tmax="2010")
>>> df.to_csv("fname.csv")