baselines: Polynomial Baseline Fitting These functions fit polynomal...

In hyperSpec: Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

Polynomial Baseline Fitting These functions fit polynomal baselines.

Description

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.

Usage

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")
)

Arguments

fit.to	hyperSpec object on which the baselines are fitted
apply.to	hyperSpec object on which the baselines are evaluted If NULL, a hyperSpec object containing the polynomial coefficients rather than evaluted baselines is returned.
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: 1 shows npts.min, 2 plots support points for the final baseline of 1st spectrum, 3 plots support points for 1st spectrum, 4 plots support points for all spectra.

Details

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.

Value

hyperspec object containing the baselines in the spectra matrix, either as polynomial coefficients or as polynomials evaluted on the spectral range of apply.to

Author(s)

C. Beleites

See Also

vignette ("baseline", package = "hyperSpec")

see options for more on debuglevel

Examples

## 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]])))

hyperSpec documentation built on May 29, 2024, 7:28 a.m.