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

ArNoiseModel#

class ArNoiseModel(norm=True)[source]#

Noise model with exponential decay of the residuals and weighting.

Parameters

norm (boolean, optional) – Boolean to indicate whether weights are normalized according to the Von Asmuth and Bierkens (2005) paper. Default is True.

Notes

Calculates the noise von Asmuth and Bierkens [2005] according to:

\[v(t_1) = r(t_1) - r(t_0) * \exp(- \Delta t / \alpha)\]

Calculates the weights as

\[w = 1 / \sqrt{(1 - \exp(-2 \Delta t / \alpha))}\]

The units of the alpha parameter is always in days. The first value of the noise is the residual (\(v(t=0=r(t=0)\)). First weight is 1 / sig_residuals (i.e., delt = infty). Normalization of weights as in von Asmuth and Bierkens [2005], optional.

Methods#

__init__

get_correction

Get the correction for a forecast using the noise model.

set_init_parameters

simulate

Simulate noise from the residuals.

to_dict

Method to return a dict to store the noise model

weights

Method to calculate the weights for the noise.