pastas.rfunc.Kraijenhoff#

class pastas.rfunc.Kraijenhoff(cutoff: float = 0.999, use_block: bool = True, n_terms: int = 10, **kwargs)#

response function of Van de Leur [1958].

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.

  • n_terms (int, optional) – Number of terms used in the truncated series expansion.

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 Kraijenhoff van de Leur function is explained in Van de Leur [1958].

The function describes the response of a domain between two drainage channels. The function gives the same outcome as equation 133.15 in Bruggeman [1999]. This is the response that is actually calculated with this function.

The response function has three parameters A, a and b:

  • A is the gain (scaled),

  • a is the reservoir coefficient (j in Van de Leur [1958]),

  • b is the location in the domain with the origin in the middle. This means that b=0 is in the middle and b=1/2 is at the drainage channel. At b=1/4 the response function is most similar to the exponential response function.

property nparam: int#

Return number of parameters for the response function.

Returns:

Number of parameters (3 for Kraijenhoff: A, a, b).

Return type:

int

Methods#

get_init_parameters(→ pandas.DataFrame)

Get initial parameters and bounds for the Kraijenhoff response function.

get_tmax(→ float)

Get response time for a certain cutoff for Kraijenhoff response function.

gain(→ float)

Return the gain of the Kraijenhoff response function.

step(→ pastas.typing.ArrayLike)

Return the step function for Kraijenhoff response.

block_from_impulse(→ pastas.typing.ArrayLike)

Compute block response from impulse response for Kraijenhoff.

moment(→ float)

Calculate the moment of a certain order for the Kraijenhoff response function.

impulse(→ pastas.typing.ArrayLike)

Return the impulse response function for Kraijenhoff.

to_dict(→ dict[str, Any])

Export the Kraijenhoff response function object as a dictionary.