MexicanHat1D¶

class astropy.modeling.functional_models.MexicanHat1D(amplitude, x_0, sigma, **kwargs)[source] [edit on github]¶

Bases: astropy.modeling.Fittable1DModel

One dimensional Mexican Hat model.

Parameters:

amplitude : float

Amplitude

x_0 : float

Position of the peak

sigma : float

Width of the Mexican hat

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 the fixed 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 the tied property of a parameter may be used.

bounds : dict

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

eqcons : list

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

ineqcons : list

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

Notes

Model formula:

$f(x) = {A \left(1 - \frac{\left(x - x_{0}\right)^{2}}{\sigma^{2}}\right) e^{- \frac{\left(x - x_{0}\right)^{2}}{2 \sigma^{2}}}}$

Attributes Summary

`amplitude`
`input_names`	list() -> new empty list
`param_names`	list() -> new empty list
`sigma`
`x_0`

Methods Summary

`eval`(args, *kwargs)	Deprecated since version 1.0.
`evaluate`(x, amplitude, x_0, sigma)	One dimensional Mexican Hat model function

Attributes Documentation

amplitude¶

input_names = ['x']¶

param_names = ['amplitude', 'x_0', 'sigma']¶

sigma¶

x_0¶

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 MexicanHat1D.evaluate instead.

One dimensional Mexican Hat model function

static evaluate(x, amplitude, x_0, sigma)[source] [edit on github]¶: One dimensional Mexican Hat model function

Navigation

MexicanHat1D¶

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