pastas.rfunc.Gamma#

class pastas.rfunc.Gamma(cutoff: float = 0.999, use_block: bool = True, complex_step: bool = False, **kwargs)#

Gamma response function with 3 parameters A, a, 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.

  • complex_step (bool, optional) – If False (default) uses the (fast) scipy implementation of the Gamma.step function, which does not support complex-step Jacobian evaluation when use_block=True. If True the (slow) mpmath implementation is used, which does support complex-step differentiation, but incurs a significant performance penalty. Note that the scipy implementation does support complex inputs when using the impulse response (use_block=False).

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#

Mean stress value used to scale the initial value so that the final step response times the mean stress equals 1.

Type:

float, optional

property nparam: int#

Return number of parameters for the response function.

Returns:

Number of parameters (3 for Gamma: A, n, a).

Return type:

int

Methods#

get_init_parameters(→ pandas.DataFrame)

Get initial parameters and bounds for the Gamma response function.

get_tmax(→ float)

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

gain(→ float)

Return the gain of the Gamma response function.

step(→ pastas.typing.ArrayLike)

Return the step function for the Gamma response function.

moment(→ float)

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

impulse(→ pastas.typing.ArrayLike)

Return the impulse response function for Gamma.

to_dict(→ dict[str, Any])

Export the Gamma response function object as a dictionary.