Description Usage Arguments Details Value Author(s) See Also Examples
Both functions fit polynomials to be used as baselines. If apply.to
is NULL
, a hyperSpec
object with the polynomial coefficients
is returned, otherwise the polynomials are evaluated on the spectral range
of apply.to
.
spc.fit.poly.below
tries to fit the baseline on appropriate spectral
ranges of the spectra in fit.to
. For details, see the
vignette ("baseline")
.
1 2 3 4 5 6 7  spc.fit.poly(fit.to, apply.to = NULL, poly.order = 1,
offset.wl = !(is.null(apply.to)))
spc.fit.poly.below(fit.to, apply.to = fit.to, poly.order = 1,
npts.min = max(round(nwl(fit.to) * 0.05), 3 * (poly.order + 1)),
noise = 0, offset.wl = FALSE, max.iter = nwl(fit.to),
stop.on.increase = FALSE, debuglevel = hy.getOption("debuglevel"))

fit.to 

apply.to 

poly.order 
order of the polynomial to be used 
offset.wl 
should the wavelength range be mapped to > [0, delta wl]? This enhances numerical stability. 
npts.min 
minimal number of points used for fitting the polynomial 
noise 
noise level to be considered during the fit. It may be given as one value for all the spectra, or for each spectrum separately. 
max.iter 
stop at the latest after so many iterations. 
stop.on.increase 
additional stopping rule: stop if the number of support points would increase, regardless whether npts.min was reached or not. 
debuglevel 
additional output:

spc.fit.poly
calculates the least squares fit of order
poly.order
to the complete spectra given in fit.to
.
Thus fit.to
needs to be cut appropriately.
hyperspec
object containing the baselines in the spectra
matrix, either as polynomial coefficients or as polynomials evaluted on
the spectral range of apply.to
C. Beleites
vignette ("baseline", package = "hyperSpec")
see options
for more on debuglevel
1 2 3 4 5 6 7 8 9 10 11 12 13  ## Not run: vignette ("baseline", package = "hyperSpec")
spc < chondro [1 : 10]
baselines < spc.fit.poly(spc [,, c (625 ~ 640, 1785 ~ 1800)], spc)
plot(spc  baselines)
baselines < spc.fit.poly.below (spc)
plot (spc  baselines)
spc.fit.poly.below(chondro [1:3], debuglevel = 1)
spc.fit.poly.below(chondro [1:3], debuglevel = 2)
spc.fit.poly.below(chondro [1:3], debuglevel = 3, noise = sqrt (rowMeans (chondro [[1:3]])))

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