pastas.model.Model.get_output_series
====================================

.. py:method:: 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.

   :param tmin: 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.
   :type tmin: pandas.Timestamp or str, optional
   :param tmax: 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.
   :type tmax: pandas.Timestamp or str, optional
   :param add_contributions: Add the contributions from the different stresses or not. Default is
                             True.
   :type add_contributions: bool, optional
   :param split_contributions: Passed on to ml.get_contributions. Split the contribution from recharge
                               into evaporation and precipitation. See also ml.get_contributions.
                               Default is True.
   :type split_contributions: bool, optional

   :returns: **df** -- Pandas DataFrame with the time series as columns and DatetimeIndex.
   :rtype: pandas.DataFrame

   .. rubric:: Notes

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

   .. rubric:: Examples

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















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