pastas.model.Model.get_stress#

pastas.model.Model.get_stress(name: str, tmin: pandas.Timestamp | str | None = None, tmax: pandas.Timestamp | str | None = None, freq: str | None = None, warmup: float | None = None, istress: int | None = None, return_warmup: bool = False, p: pastas.typing.ArrayLike | None = None) → pandas.Series | list[pandas.Series]#

Method to obtain the stress(es) from the stressmodel.

Parameters:

  • name (str) – String with the name of the stressmodel.

  • 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.

  • freq (str, optional) – String with the frequency the stressmodels are simulated. Must be one of the following: (D, h, m, s, ms, us, ns) or a multiple of that e.g. “7D”.

  • warmup (float, optional) – Warmup period (in Days).

  • istress (int, optional) – When multiple stresses are present in a stressmodel, this keyword can be used to obtain the contribution of an individual stress.

  • return_warmup (bool, optional) – Include warmup in contribution calculation or not.

  • p (array_like, optional) – array_like object with the values as floats representing the model parameters. See Model.get_parameters() for more info if parameters is None.

Returns:

stress – If one stress is present, a pandas Series is returned. If more are present, a list of pandas Series is returned.

Return type:

pandas.Series or list of pandas.Series