LogParabola1D¶

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

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

Methods Summary

`eval`(args, *kwargs)	Deprecated since version 1.0.
`evaluate`(x, amplitude, x_0, alpha, beta)	One dimenional log parabola model function
`fit_deriv`(x, amplitude, x_0, alpha, beta)	One dimensional log parabola derivative with repsect to parameters

Attributes Documentation

Methods Documentation

static eval(*args, **kwargs) [edit on github]¶: Deprecated since version 1.0: The eval method is deprecated and may be removed in a future version. Use LogParabola1D.evaluate instead.

One dimenional log parabola model function

static evaluate(x, amplitude, x_0, alpha, beta)[source] [edit on github]¶: One dimenional log parabola model function

static fit_deriv(x, amplitude, x_0, alpha, beta)[source] [edit on github]¶: One dimensional log parabola derivative with repsect to parameters