Module profiles¶
Detailed information about the Gaussian estimates procedure used in function gauest(), can be found in the kmpfit tutorial.
Function¶

kapteyn.profiles.
gauest
(x, y, rms, cutamp, cutsig, q[, ncomp=200, smode=0, flat=False])¶  Function to search for gaussian components in a profile.
Parameters:  x – a onedimensional NumPy array (or slice) containing the profile’s xcoordinates.
 y – a onedimensional NumPy array (or slice) containing the profile’s values.
 rms – the r.m.s. noise level of the profile.
 cutamp – critical amplitude of gaussian. Gaussians below this amplitude will be discarded.
 cutsig – critical dispersion of gaussian.
 q – smoothing parameter used in calculating the second derivative of the profile. It must be greater than zero.
 ncomp – maximum number of gaussian components to be found. It should be \(\geq 1\).
 smode – order in which gaussian components are delivered. 0: decreasing amplitude, 1: decreasing dispersion, 2: decreasing flux.
 flat – True if a ‘flat’ result shoud be returned. See below.
Returns: a list with up to ncomp tuples of which each tuple contains the amplitude, the centre and the dispersion of the gaussian, in that order. If the argument flat is True, a ‘flat’ list with ncomp * 3 numbers is returned which may directly be used as initial estimates for
kmpfit.Fitter
.In this function the second derivative of the profile in the signal region is calculated by fitting a second degree polynomal. The smoothing parameter q determines the number of points used for this (\(2q+1\)). The gaussians are then estimated as described by Schwarz (1968)
See also
Tutorial chapter “Automatic initial estimates for profiles with multi component Gaussians.”