PowerLaw1D

class astropy.modeling.powerlaws.PowerLaw1D(amplitude=1, x_0=1, alpha=1, **kwargs)[source] [edit on github]

Bases: astropy.modeling.Fittable1DModel

One dimensional power law model.

Parameters:

amplitude : float

Model amplitude at the reference point

x_0 : float

Reference point

alpha : float

Power law index

Other Parameters:
 

fixed : a dict, optional

A dictionary {parameter_name: boolean} of parameters to not be varied during fitting. True means the parameter is held fixed. Alternatively the fixed property of a parameter may be used.

tied : dict, optional

A dictionary {parameter_name: callable} of parameters which are linked to some other parameter. The dictionary values are callables providing the linking relationship. Alternatively the tied property of a parameter may be used.

bounds : dict, optional

A dictionary {parameter_name: value} of lower and upper bounds of parameters. Keys are parameter names. Values are a list or a tuple of length 2 giving the desired range for the parameter. Alternatively, the min and max properties of a parameter may be used.

eqcons : list, optional

A list of functions of length n such that eqcons[j](x0,*args) == 0.0 in a successfully optimized problem.

ineqcons : list, optional

A list of functions of length n such that ieqcons[j](x0,*args) >= 0.0 is a successfully optimized problem.

Notes

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

\[f(x) = A (x / x_0) ^ {-\alpha}\]

Attributes Summary

alpha
amplitude
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).
param_names
x_0

Methods Summary

evaluate(x, amplitude, x_0, alpha) One dimensional power law model function
fit_deriv(x, amplitude, x_0, alpha) One dimensional power law derivative with respect to parameters

Attributes Documentation

alpha
amplitude
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 overriden since it will return the input units based on the annotations.

param_names = ('amplitude', 'x_0', 'alpha')
x_0

Methods Documentation

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

One dimensional power law model function

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

One dimensional power law derivative with respect to parameters