# Gaussian Model¶

The Gaussian model implements a Gaussian function and wraps it in the generic fitter tools.

The simplest and most useful model.

Until 12/23/2011, gaussian fitting used the complicated and somewhat bloated gaussfitter.py code. Now, this is a great example of how to make your own model! Just make a function like gaussian and plug it into the SpectralModel class.

## Module API¶

pyspeckit.spectrum.models.inherited_gaussfitter.gaussian(xarr, amplitude, dx, width, return_components=False, normalized=False, return_hyperfine_components=False)[source] [github] [bitbucket]

Returns a 1-dimensional gaussian of form A*np.exp(-(x-dx)**2/(2*w**2))

Area is sqrt(2*pi*sigma^2)*amplitude - i.e., this is NOT a normalized gaussian, unless normalized=True in which case A = Area

Parameters: xarr : np.ndarray array of x values amplitude : float Amplitude of the Gaussian, i.e. its peak value, unless normalized=True then A is the area of the gaussian dx : float Center or “shift” of the gaussian width : float Width of the gaussian (sigma) return_components : bool dummy variable; return_components does nothing but is required by all fitters return_hyperfine_components : bool dummy variable; does nothing but is required by all fitters normalized : bool Return a normalized Gaussian?
pyspeckit.spectrum.models.inherited_gaussfitter.gaussian_fitter()[source] [github] [bitbucket]

Generator for Gaussian fitter class

pyspeckit.spectrum.models.inherited_gaussfitter.gaussian_integral(amplitude, sigma)[source] [github] [bitbucket]

Integral of a Gaussian

pyspeckit.spectrum.models.inherited_gaussfitter.gaussian_vheight_fitter()[source] [github] [bitbucket]

Generator for Gaussian fitter class