pastas.rfunc.Hantush#

class pastas.rfunc.Hantush(cutoff: float = 0.999, use_block: bool = True, quad: bool = False, approximate_tmax: bool = True, **kwargs)#

The Hantush well function, using the standard A, a, b parameters.

Parameters:

  • cutoff (float, optional) – Fraction of the step response after which the response is truncated. Default is 0.999.

  • use_block (bool, optional) – Use the block response (rather than the impulse response) to simulate the effect of a stress. The block response approximates the stress as uniform during a time interval dt. When False, the impulse response is used which means that the the entire stress occurs midway the time interval dt. The impulse response is generally quicker to compute.

  • quad (bool, optional) – Use quad_step to compute the step response using numerical integration. Default is False.

  • approximate_tmax (bool, optional) – If True, get_tmax will use the fast Lambert W approximation (default). If False, it will use the exact numerical root finding method.

up#

Whether a positive stress causes the head to go up (True), down (False), or either direction (None).

Type:

bool or None, optional

gain_scale_factor#

Scale factor used to set the initial value and bounds of the gain parameter, computed as 1 / gain_scale_factor.

Type:

float, optional

Notes

The implementation used here is explained in Veling and Maas [2010].

property nparam: int#

Number of parameters of the response function.

Methods#

get_init_parameters(→ pandas.DataFrame)

Get initial parameters and bounds. It is called by the stressmodel.

get_tmax_approximation(→ float)

Approximates the time (tmax) when the step response reaches a specified cutoff.

get_tmax(→ float)

Calculate tmax using either the approximation or root finding.

gain(→ float)

Method to return the gain for the response function.

step(→ pastas.typing.ArrayLike)

Method to return the step function.

moment(→ float)

Compute the raw moment of the response function.

impulse(→ pastas.typing.ArrayLike)

Method to return the impulse response function.

to_dict()

Method to export the response function to a dictionary.