Gaussian1D

class astropy.modeling.functional_models.Gaussian1D(amplitude, mean, stddev, **kwargs)

Bases: astropy.modeling.Fittable1DModel

One dimensional Gaussian model.

Parameters:

amplitude : float

Amplitude of the Gaussian.

mean : float

Mean of the Gaussian.

stddev : float

Standard deviation of the Gaussian.

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.

See also

Gaussian2D, Box1D, Beta1D, Lorentz1D

Notes

Model formula:

Examples

>>> from astropy.modeling import models
>>> def tie_center(model):
...         mean = 50 * model.stddev
...         return mean
>>> tied_parameters = {'mean': tie_center}

Specify that ‘mean’ is a tied parameter in one of two ways:

>>> g1 = models.Gaussian1D(amplitude=10, mean=5, stddev=.3,
...                             tied=tied_parameters)

or

>>> g1 = models.Gaussian1D(amplitude=10, mean=5, stddev=.3)
>>> g1.mean.tied
False
>>> g1.mean.tied = tie_center
>>> g1.mean.tied
<function tie_center at 0x...>

Fixed parameters:

>>> g1 = models.Gaussian1D(amplitude=10, mean=5, stddev=.3,
...                        fixed={'stddev': True})
>>> g1.stddev.fixed
True

or

>>> g1 = models.Gaussian1D(amplitude=10, mean=5, stddev=.3)
>>> g1.stddev.fixed
False
>>> g1.stddev.fixed = True
>>> g1.stddev.fixed
True

Attributes Summary

amplitude
input_names	list() -> new empty list
mean
param_names	list() -> new empty list
stddev

Methods Summary

eval(*args, **kwargs)	Deprecated since version 1.0.
evaluate(x, amplitude, mean, stddev)	Gaussian1D model function.
fit_deriv(x, amplitude, mean, stddev)	Gaussian1D model function derivatives.

Attributes Documentation

amplitude

input_names = ['x']

mean

param_names = ['amplitude', 'mean', 'stddev']

stddev

Methods Documentation

static eval(*args, **kwargs)

Deprecated since version 1.0: The eval method is deprecated and may be removed in a future version. Use Gaussian1D.evaluate instead.

Gaussian1D model function.

static evaluate(x, amplitude, mean, stddev)

Gaussian1D model function.

static fit_deriv(x, amplitude, mean, stddev)

Gaussian1D model function derivatives.