LightGaussianRing

class dysmalpy.models.LightGaussianRing(tracer=None, **kwargs)

Bases: LightModel, _DysmalFittable1DModel

Light distribution following a Gaussian ring profile.

Parameters:

• R_peak (float) – Peak of gaussian (radius) in kpc

• FWHM (float) – FWHM of gaussian, in kpc

• L_tot (float) – Total luminsoity of component. Arbitrary units

• tracer (string) – (Attribute): Name of the dynamical tracer

Notes

Model formula:

\[I(r)=I_0\exp\left[-\frac{(r-r_{peak})^2}{2\sigma_R^2}\right]\]

Attributes Summary

FWHM
L_tot
R_peak
param_names	Names of the parameters that describe models of this type.

Methods Summary

evaluate(r, R_peak, FWHM, L_tot)	Gaussian ring light surface density.
light_profile(r)	Conversion from mass to light as a function of radius
sigma_R()

Attributes Documentation

FWHM = DysmalParameter('FWHM', value=1.0, bounds=(0, 50), prior=<dysmalpy.parameters.UniformPrior object>)

L_tot = DysmalParameter('L_tot', value=1.0, bounds=(0, 50), prior=<dysmalpy.parameters.UniformPrior object>)

R_peak = DysmalParameter('R_peak', value=1.0, bounds=(0, 50), prior=<dysmalpy.parameters.UniformPrior object>)

param_names = ('R_peak', 'FWHM', 'L_tot')

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the Parameter attributes defined in the class body.

Methods Documentation

static evaluate(r, R_peak, FWHM, L_tot)

Gaussian ring light surface density. Radius r must be in kpc

light_profile(r)

Conversion from mass to light as a function of radius

Parameters:

r (float or array) – Radii at which to calculate the enclosed mass, in kpc

Returns:

light – Relative line flux as a function of radius

Return type:

float or array

sigma_R()