LogParabola1D¶
-
class
astropy.modeling.powerlaws.
LogParabola1D
(amplitude=1, x_0=1, alpha=1, beta=0, **kwargs)[source]¶ Bases:
astropy.modeling.Fittable1DModel
One dimensional log parabola model (sometimes called curved power law).
- Parameters
- amplitudefloat
Model amplitude
- x_0float
Reference point
- alphafloat
Power law index
- betafloat
Power law curvature
Notes
Model formula (with \(A\) for
amplitude
and \(\alpha\) foralpha
and \(\beta\) forbeta
):\[f(x) = A \left(\frac{x}{x_{0}}\right)^{- \alpha - \beta \log{\left (\frac{x}{x_{0}} \right )}}\]Attributes Summary
This property is used to indicate what units or sets of units the evaluate method expects, and returns a dictionary mapping inputs to units (or
None
if any units are accepted).Methods Summary
evaluate
(x, amplitude, x_0, alpha, beta)One dimensional log parabola model function
fit_deriv
(x, amplitude, x_0, alpha, beta)One dimensional log parabola derivative with respect to parameters
Attributes Documentation
-
alpha
¶
-
amplitude
¶
-
beta
¶
-
input_units
¶ This property is used to indicate what units or sets of units the evaluate method expects, and returns a dictionary mapping inputs to units (or
None
if any units are accepted).Model sub-classes can also use function annotations in evaluate to indicate valid input units, in which case this property should not be overridden since it will return the input units based on the annotations.
-
param_names
= ('amplitude', 'x_0', 'alpha', 'beta')¶
-
x_0
¶
Methods Documentation