pastas.rfunc.FourParam#

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

Four Parameter response function with 4 parameters A, a, b, and n.

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) – If true, use the ‘quad’ method from scipy.integrate to integrate the impulse response function. This may be more accurate but increases computation times.

  • approximate_tmax (bool, optional) – If True, get_tmax will use a fast numerical 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 function is explained in Bakker et al. [2008].

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)

Approximate tmax using adaptive cumulative integration in log-time.

get_tmax(→ float)

Calculate tmax using 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.

block_from_impulse(→ pastas.typing.ArrayLike)

Method to return the block function from the impulse response.

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.