pastas.typing.types.ModelSettingsDict#

class pastas.typing.types.ModelSettingsDict#

Model settings dictionary defining logic for handling time series and model fitting.

Parameters:

  • tmin (pandas.Timestamp) – A pandas.Timestamp with the start date for the simulation period (E.g. ‘1980-01-01 00:00:00’). If none is provided, the tmin from the oseries is used.

  • tmax (pandas.Timestamp) – A pandas.Timestamp with the end date for the simulation period (E.g. ‘2020-01-01 00:00:00’). If none is provided, the tmax from the oseries is used.

  • freq (str) – 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 (Timedelta) – Warmup period (in days) for which the simulation is calculated, but not used for the calibration period.

  • fit_constant (bool, optional) – Argument that determines if the constant is fitted as a parameter. If it is set to False, the constant is set equal to the mean of the residuals.

  • freq_obs (str, optional) – String with the frequency of the observations that the model will be calibrated on. Must be one of the following (D, h, m, s, ms, us, ns) or a multiple of that e.g. “7D”. Should generally be larger than the frequency of the original observations and the model frequency (freq). If freq_obs is None, the frequency of the model (freq) will be used.