pttools.models.sigmoid

Sigmoid-based model

Classes

class pttools.models.sigmoid.SigmoidModel(pt_temp_ge, pt_temp_gs, steepness_ge, steepness_gs, ge_s, gs_s, ge_b, gs_b)

Bases: ThermoModel

Preliminary idea: ThermoModel based on sigmoid functions

TODO: work in progress

Parameters:

  • pt_temp_ge (float)

  • pt_temp_gs (float)

  • steepness_ge (float)

  • steepness_gs (float)

  • ge_s (float)

  • gs_s (float)

  • ge_b (float)

  • gs_b (float)

dge_dT(temp, phase)

\(\frac{dg_e}{dT}\)

Parameters:
Return type:

float | float64 | ndarray

dgs_dT(temp, phase)

\(\frac{dg_s}{dT}\)

Parameters:
Return type:

float | float64 | ndarray

ge(temp, phase)

Effective degrees of freedom for the energy density \(g_{\text{eff},e}(T)\)

Parameters:

  • temp (float | float64 | ndarray) – temperature \(T\) (MeV)

  • phase (float | float64 | ndarray) – phase \(\phi\)

Returns:

\(g_{\text{eff},e}\)

Return type:

float | float64 | ndarray

gs(temp, phase)

Effective degrees of freedom for the entropy density, \(g_{\text{eff},s}(T)\)

Parameters:

  • temp (float | float64 | ndarray) – temperature \(T\) (MeV)

  • phase (float | float64 | ndarray) – phase \(\phi\)

Returns:

\(g_{\text{eff},s}\)

Return type:

float | float64 | ndarray

Functions

pttools.models.sigmoid.sigmoid(x, midpoint, max_val, steepness)

Logistic function

Parameters:

  • x (float | float64 | ndarray)

  • midpoint (float | float64 | ndarray)

  • max_val (float | float64 | ndarray)

  • steepness (float | float64 | ndarray)

Return type:

float | float64 | ndarray

pttools.models.sigmoid.sigmoid_derivative(x, midpoint, max_val, steepness)

Derivative of the logistic function

Parameters:

  • x (float | float64 | ndarray)

  • midpoint (float | float64 | ndarray)

  • max_val (float | float64 | ndarray)

  • steepness (float | float64 | ndarray)

Return type:

float | float64 | ndarray