albatross-package: tools:::Rd_package_title("albatross")

Description

Day after day, day after day,
We stuck, nor breath nor motion;
As idle as a painted ship
Upon a painted ocean.

Water, water, every where,
And all the boards did shrink;
Water, water, every where,
Nor any drop to drink.

-- Samuel Taylor Coleridge, The Rime of the Ancient Mariner

tools:::Rd_package_description("albatross")

Arguments

Author

Ivan Krylov

Scientific advisor: Timur Labutin

With contrubitions from: Anastasia Drozdova

Details

In order to work with your data, create feem and/or feemcube objects from files or matrix or array objects. Use feemlist to import files in bulk. If your files aren't in one of the formats supported by feem but you can read their contents by other means, you can supply an importer function to feemlist; it should take a file name and return the corresponding feem object.

Operations that can be performed on the objects include plotting (plot.feem), calculation of fluorescence indices (feemindex), inner-filter effect correction (feemife), handling of scattering signal (feemscatter), changing the wavelength grid of the data by means of interpolation (feemgrid), and scaling (feemscale). Scaling may be automatically undone after performing the PARAFAC decomposition so that the resulting scores would correspond to the data as it was before the scaling.

All processing functions can take individual feem objects, lists of them, or feemcube objects and return values of the appropriate kind. For example, feemscatter always returns an object of the same class but with the scattering signal handled, while feemindex returns named numeric vectors for individual feems but data.frames for collections of them. There's a slight memory benefit to using lists of feem objects, but the difference shouldn't be noticeable, so there's nothing to worry about if you started with a feemcube.

In order to compute PARAFAC, you need to convert your data into a feemcube. Whether you perform jack-knifing, split-half analysis, or PARAFAC itself, a copy of the data cube is kept together with the results and can be extracted back using the feemcube function. The result objects support a plot method, or can give you the data as a few-column data.frame using the coef method.

Once the analysis is finished, the PARAFAC model can be exported for the OpenFluor database (write.openfluor) or stored as an R object using standard R tools (save or saveRDS).

tools:::Rd_package_indices("albatross")

References

tools::toRd(bibentry('Article', author = c( person(c('Kathleen', 'R.'), 'Murphy'), person(c('Colin', 'A.'), 'Stedmon'), person('Daniel', 'Graeber'), person('Rasmus', 'Bro') ), title = 'Fluorescence spectroscopy and multi-way techniques. PARAFAC', journal = 'Analytical Methods', doi = '10.1039/c3ay41160e', volume = 5, year = 2013, pages = '6557-6566' ))

tools::toRd(bibentry('Article', author = c( person('Matthias', 'Pucher'), # my kingdom for a backslash! person('Urban', paste0(rawToChar(as.raw(0x5c)), 'enc{Wünsch}{Wuensch}')), person('Gabriele', 'Weigelhofer'), person('Kathleen', 'Murphy'), person('Thomas', 'Hein'), person('Daniel', 'Graeber') ), title = paste( 'staRdom: Versatile Software for Analyzing Spectroscopic Data', 'of Dissolved Organic Matter in R' ), journal = 'Water', volume = 11, number = 11, year = 2019, pages = 2366, doi = '10.3390/w11112366' ))

tools::toRd(bibentry('Article', author = c( person('John', 'Cleese'), person('Terry', 'Jones') ), title = 'Albatross: Flavours of different sea birds', journal = 'Journal of Flying Circus', year = 1970, volume = '1.13', pages = '7:05-7:45' ))

Examples

Run this code

  data(feems)

  dataset <- feemcube(feems, FALSE)
  dataset <- feemscatter(dataset, rep(24, 4), 'pchip')
  dataset <- feemife(dataset, absorp)
  plot(dataset <- feemscale(dataset, na.rm = TRUE))

  # \donttest{
    # takes a long time
    (sh <- feemsplithalf(cube, nfac = 2:5, splits = 4))
    plot(sh)
    jk <- feemjackknife(cube, nfac = 3)
    plot(jk)
  # }

  pf <- feemparafac(cube, nfac = 3)
  plot(pf)