fit.cube: Function to perform kinematic analysis over a VIMOS IFU data...
In oczoske/slacR: R-package to measure v and sigma from VIMOS IFU cubes

Description Usage Arguments Details Value Author(s) See Also

This function is a wrapper function, it calls fit.spectrum for every spectrum in a VIMOS IFU data cube.

fit.cube(config, galspec, template, LOSVD=c("gauss", "gh",
         "gauss-hermite"), mask, output, errors = 0, SN.lim = 8, 
         dv = 25, verbose = TRUE, sigma.max = 1000, normalize = FALSE,
         ...)

`config`	name of a file or list containing relevant data on the object on which the kinematic analysis is to be performed
`galspec`	(optional) a list of galaxy spectra, all on the same wavelength vector. This would be read in from a VIMOS cube with `prepare.cube`. If missing, the name of the data cube is taken from `config`
`template`	(optional) an object of class `spectrum` containing the stellar template spectrum. If missing, the name of the template file is taken from `config`
`LOSVD`	Shape of the LOSVD to be fit to the spectrum. Defaults to Gaussian but can also be set to a Gauss-Hermite series, to order 4.
`mask`	a data.frame with two columns `x1` and `x2` giving the left and right limits of wavelength regions that are to be masked; or, the name of a file containing such a data.frame; or, a logical vector along `galaxy$lambda`, with `TRUE` for pixels that shall be included in the fit
`output`	the name of a file to which the resulting fit will be written by `write.table`
`errors`	Number of Monte Carlo simulations that will be performed for each spectrum in the cube to give an estimate of the error distribution; defaults to zero
`SN.lim`	Only spectra in the cube which have a signal-to-noise ratio larger than this value will be analysed by `fit.spectrum`. All others will have `NA` in their results
`dv`	velocity step on which the template spectrum will be initially sampled; defaults to 25 km/sec
`verbose`	`logical`. If `TRUE`, informative messages will be printed
`sigma.max`	Maximum allowed value for the velocity dispersion, defaults to 1000 km/s. This gives in principle a constrained optimization, although the best fit should not be affected.
`normalize`	Normalization factor for the data cube, defaults to `FALSE`, i.e. no normalization at all
`...`	Further parameters to be passed to `fit.spectrum`. These would be in particular `niter`, `nsig` and `plot`.

Beware of running too many error realizations, this takes a hell of a long time.

An object of class kinmap obtained from fit.spectrum with simple=TRUE. If output is given, the result will be written directly to a file in the form of a data.frame.

`v, sig, gof, h3, h4`	The best fitting values for velocity and velocity dispersion, and the corresponding value of the `merit.function`
`v1, v2`	first and second velocity moments of the best-fitting LOSVD
`dv.low, dv.high, dsig.low, dsig.high,...`	If `errors` is larger than zero, 68% confidence limits for velocity and velocity dispersion and other parameters
`SN, level, noise`	The signal-to-noise, level and noise for the galaxy spectrum.
`rms`	The root-mean-square residuals of the best fit; this can be compared to noise
`L, M`	coordinates of the fibre in the data cube
`template, sptype, FeH, logg, Teff`	some data on the template used