ChangeModel#

class ChangeModel(stress, rfunc1, rfunc2, name, tchange, up=True, cutoff=0.999, settings=None, metadata=None)[source]#

Model where the response function changes from one to another over time.

Parameters
  • stress (pandas.Series) – pandas Series object containing the stress.

  • rfunc1 (pastas.rfunc instance (class is deprecated)) – response function used in the convolution with the stress.

  • rfunc2 (pastas.rfunc instance (class is deprecated)) – response function used in the convolution with the stress.

  • name (str) – name of the stress.

  • tchange (str) – string with the approximate date of the change.

  • up (bool or None, optional) – True if response function is positive (default), False if negative. None if you don’t want to define if response is positive or negative.

  • cutoff (float, optional) – float between 0 and 1 to determine how long the response is (default is 99% of the actual response time). Used to reduce computation times.

  • settings (dict or str, optional) – the settings of the stress. This can be a string referring to a predefined settings dict, or a dict with the settings to apply. Refer to the docstring of pastas.Timeseries for further information.

  • metadata (dict, optional) – dictionary containing metadata about the stress. This is passed onto the TimeSeries object.

Notes

This model is based on Obergfell et al. (2019).

Attributes#

nparam

Methods#

__init__

dump_stress

Method to dump all stresses in the stresses list.

get_nsplit

Determine in how many timeseries the contribution can be split.

get_stress

Returns the stress or stresses of the time series object as a pandas DataFrame.

set_init_parameters

Internal method to set the initial parameters.

simulate

to_dict

Method to export the StressModel object.

update_stress

Method to update the settings of the individual TimeSeries.