Moffat2D¶
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class
astropy.modeling.functional_models.
Moffat2D
[source] [edit on github]¶ Bases:
astropy.modeling.Fittable2DModel
Two dimensional Moffat model.
Parameters: amplitude : float
Amplitude of the model.
x_0 : float
x position of the maximum of the Moffat model.
y_0 : float
y position of the maximum of the Moffat model.
gamma : float
Core width of the Moffat model.
alpha : float
Power index of the Moffat model.
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.See also
Notes
Model formula:
\[f(x, y) = A \left(1 + \frac{\left(x - x_{0}\right)^{2} + \left(y - y_{0}\right)^{2}}{\gamma^{2}}\right)^{- \alpha}\]Attributes Summary
alpha
amplitude
gamma
param_names
x_0
y_0
Methods Summary
evaluate
(x, y, amplitude, x_0, y_0, gamma, alpha)Two dimensional Moffat model function fit_deriv
(x, y, amplitude, x_0, y_0, gamma, ...)Two dimensional Moffat model derivative with respect to parameters Attributes Documentation
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alpha
¶
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amplitude
¶
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gamma
¶
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param_names
= ('amplitude', 'x_0', 'y_0', 'gamma', 'alpha')¶
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x_0
¶
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y_0
¶
Methods Documentation
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static
evaluate
(x, y, amplitude, x_0, y_0, gamma, alpha)[source] [edit on github]¶ Two dimensional Moffat model function
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static
fit_deriv
(x, y, amplitude, x_0, y_0, gamma, alpha)[source] [edit on github]¶ Two dimensional Moffat model derivative with respect to parameters
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