feemscatter: Handle scattering signal in FEEMs

In albatross: PARAFAC Analysis of Fluorescence Excitation-Emission Matrices

Handle scattering signal in FEEMs

Description

Remove or interpolate scattering signal in individual FEEM objects, FEEM cube objects, or lists of them.

Usage

  feemscatter(x, ...)
  ## S3 method for class 'list'
feemscatter(x, ..., cl, progress = TRUE)
  ## S3 method for class 'feemcube'
feemscatter(x, ..., cl, progress = TRUE)
  ## S3 method for class 'feem'
feemscatter(
    x, widths, method = c("omit", "pchip", "loess", "kriging", "whittaker"),
    add.zeroes = 30, Raman.shift = 3400, ...
  )

Arguments

x

An individual FEEM object, FEEM cube object, or a list of them, to handle the scattering signal in.

widths

A numeric vector or a list containing the half-widths of the scattering bands, in nm. Rayleigh scattering is followed by Raman scattering, followed by second diffraction order for Rayleigh and Raman, and so on. (Typically, there's no need for anything higher than third order, and even that is rare.) For example: Rayleigh scattering Raman scattering Rayleigh scattering, 3{2\lambda 2 lambda2λ \item Raman scattering, 3{2\lambda

2 lambda2λ ...

Details

The “pchip” method works by default as described in Bahram2006: each emission spectrum at different excitation wavelengths is considered one by one. Zeroes are inserted in the corners of the spectrum if they are undefined (NA) to prevent extrapolation from blowing up, then the margins are interpolated using the corner points, then the rest of the spectrum is interpolated line by line. Since pchip requires at least 3 points to interpolate, the function falls back to linear interpolation if it has only two defined points to work with. The by argument controls whether the function proceeds by rows of the matrix (“emission”, default), by columns of the matrix (“excitation”), or does both (“both”) and averages the results to make the resulting artefacts less severe Pucher2019 (see the staRdom package itself).

The “loess” method feeds the whole FEEM except the area to be interpolated to loess, then asks it to predict the remaining part of the spectrum. Any negative values predicted by loess are replaced by 0.

The “kriging” method NR3-Kriging is much more computationally expensive than the previous two, but, on some spectra, provides best results, not affected by artefacts resulting from line-by-line one-dimensional interpolation (pchip) or varying degrees of smoothness in different areas of the spectrum (loess). Any negative values returned by kriging are replaced by 0.

Whittaker smoothing

The “whittaker” method Krylov2023 works by minimising a sum of penalties, requiring the interpolated surface to be close to the original points around it and to be smooth in terms of derivatives by 3{\lambda_\mathrm{em}

emission wavelengthλ_em and 3{\lambda_\mathrm{ex}

Value

An object of the same kind (FEEM object / FEEM cube / list of them) with scattering signal handled as requested.

References

\bibliography

See Also

feem, feemcube

Examples

  data(feems)
  plot(x <- feemscatter(
    feems[[1]], widths = c(25, 25, 20, 20),
    method = 'whittaker', Raman.shift = 3500
  ))

albatross documentation built on May 29, 2024, 9:10 a.m.