The default behavior for adding and solving with noisemodels has changed from Pastas 1.5. Find more information here

pastas.model.Model.simulate#

Model.simulate(p=None, tmin=None, tmax=None, freq=None, warmup=None, return_warmup=False)[source]#

Method to simulate the time series model.

Parameters
  • 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.

  • tmin (str, optional) – String with a start date for the simulation period (E.g. ‘1980’). If none is provided, the tmin from the oseries is used.

  • tmax (str, optional) – String with an end date for the simulation period (E.g. ‘2010’). 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).

  • return_warmup (bool, optional) – Return the simulation including the warmup period or not, default is False.

Returns

sim – pandas.Series containing the simulated time series

Return type

pandas.Series

Notes

This method can be used without any parameters. When the model is solved, the optimal parameters values are used and if not, the initial parameter values are used. This allows the user to get an idea of how the simulation looks with only the initial parameters and no calibration.