pastas.stressmodels.StepModel#

class pastas.stressmodels.StepModel(tstart: pandas.Timestamp | str, name: str, rfunc: pastas.typing.RFunc | None = None, up: bool = None, max_cache_size: int = None)#

Stressmodel that simulates a step trend.

Parameters:

  • tstart (str or Timestamp) – String with the start date of the step, e.g. ‘2018-01-01’. This value is fixed by default. Use ml.set_parameter(“step_tstart”, vary=True) to vary the start time of the step trend.

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

  • rfunc (pastas.rfunc instance) – Pastas response function used to simulate the effect of the step. Default is ps.rfunc.One(), an instant effect.

  • up (bool, optional) – Force a direction of the step. Default is None.

Notes

The step trend is calculated as follows. First, a binary series is created, with zero values before tstart, and ones after the start. This series is convolved with the block response to simulate a step trend.

Methods#

set_init_parameters(→ None)

Set the initial parameters (back) to their default values.

to_dict(→ dict)

Method to export the StepModel object.