PowerLaw1D¶
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class
astropy.modeling.powerlaws.
PowerLaw1D
[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
A dictionary
{parameter_name: boolean}
of parameters to not be varied during fitting. True means the parameter is held fixed. Alternatively thefixed
property of a parameter may be used.tied : dict
A dictionary
{parameter_name: callable}
of parameters which are linked to some other parameter. The dictionary values are callables providing the linking relationship. Alternatively thetied
property of a parameter may be used.bounds : dict
eqcons : list
A list of functions of length
n
such thateqcons[j](x0,*args) == 0.0
in a successfully optimized problem.ineqcons : list
A list of functions of length
n
such thatieqcons[j](x0,*args) >= 0.0
is a successfully optimized problem.Notes
Model formula (with \(A\) for
amplitude
and \(\alpha\) foralpha
):\[f(x) = A (x / x_0) ^ {-\alpha}\]Attributes Summary
alpha
amplitude
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
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alpha
¶
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amplitude
¶
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param_names
= ('amplitude', 'x_0', 'alpha')¶
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x_0
¶
Methods Documentation
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static
evaluate
(x, amplitude, x_0, alpha)[source] [edit on github]¶ One dimensional power law model function
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static
fit_deriv
(x, amplitude, x_0, alpha)[source] [edit on github]¶ One dimensional power law derivative with respect to parameters
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