Synopsis
A weighted sum of a Gaussian and Lorentzian distribution.
Syntax
pseudovoigt1d
Description
Unlike the Voigt1D model, which is a convolution between a Gaussian and Lorentz distribution, this approximates the Voigt profile with a linear combination of the two profiles [1] . It is often used in spectroscopy.
Example
>>> create_model_component("pseudovoigt1d", "mdl") >>> print(mdl)
Create a component of the pseudovoigt1d model and display its default parameters. The output is:
mdl Param Type Value Min Max Units ----- ---- ----- --- --- ----- mdl.frac thawed 0.5 0 1 mdl.fwhm thawed 10 1.17549e-38 3.40282e+38 mdl.pos thawed 0 -3.40282e+38 3.40282e+38 mdl.ampl thawed 1 -3.40282e+38 3.40282e+38
ATTRIBUTES
The attributes for this object are:
Attribute | Definition |
---|---|
frac | The fraction of the model composed of the Gaussian profile (0 to 1). |
fwhm | The full-width half-maximum (FWHM) of each component. |
pos | The center of the profile. |
ampl | The amplitude of the profile. |
Notes
The model can be written as:
f(x) = frac * g(x) + (1 - frac) * l(x)
where g(x) and l(x) are NormGauss1D and Lorentz1D models with the fwhm, pos, and ampl values taken from this model.
References
- [1] https://en.wikipedia.org/wiki/Voigt_profile#Pseudo-Voigt_approximation
Changes in CIAO
Added in CIAO 4.13
The pseudovoigt1d and voigt1d models were added in CIAO 4.13 and replace the absorptionvoigt and emissionvoigt models.
Bugs
See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.
See Also
- models
- voigt1d