astropy:docs

LogParabola1D

class astropy.modeling.powerlaws.LogParabola1D(amplitude, x_0, alpha, beta, **constraints)[source] [edit on github]

Bases: astropy.modeling.core.Parametric1DModel

One dimensional log parabola model (sometimes called curved power law).

Parameters :

amplitude : float

Model amplitude

x_0 : float

Reference point

alpha : float

Power law index

beta : float

Power law curvature

Notes

Model formula (with A for amplitude and \alpha for alpha and \beta for beta):

f(x) = A \left(\frac{x}{x_{0}}\right)^{- \alpha - \beta \log{\left (\frac{x}{x_{0}} \right )}}

Attributes Summary

alpha
amplitude
beta
param_names list() -> new empty list
x_0

Methods Summary

deriv(x, amplitude, x_0, alpha, beta) One dimensional log parabola derivative
eval(x, amplitude, x_0, alpha, beta) One dimenional log parabola model function

Attributes Documentation

alpha
amplitude
beta
param_names = ['amplitude', 'x_0', 'alpha', 'beta']
x_0

Methods Documentation

static deriv(x, amplitude, x_0, alpha, beta)[source] [edit on github]

One dimensional log parabola derivative

static eval(x, amplitude, x_0, alpha, beta)[source] [edit on github]

One dimenional log parabola model function

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