Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data.
prospectr
Misc. Functions for Processing and Sample Selection of Spectroscopic Data
Antoine Stevens & Leo Ramirez-LopezLast update: 2024-02-16
Version: 0.2.7 – cakes
prospectr
is becoming more and more used in spectroscopic applications, which is evidenced by the number of scientific publications citing the package. This package is very useful for signal processing and chemometrics in general as it provides various utilities for pre–processing and sample selection of spectral data. While similar functions are available in other packages, like signal
, the functions in this package works indifferently for data.frame
, matrix
and vector
inputs. Besides, several functions are optimized for speed and use C++ code through the Rcpp
and RcppArmadillo
packages.
Installing it from GitHub
Install this package from github by:
remotes::install_github("l-ramirez-lopez/prospectr")
NOTE: in some MAC Os it is still recommended to install gfortran
and clang
from here. Even for R >= 4.0. For more info, check this issue.
News
Check the NEWS document for new functionality and general changes in the package.
Vignette
A vignette for prospectr
explaining its core functionality is available at https://CRAN.R-project.org/package=prospectr/vignettes/prospectr.html.
Core functionality
A vignette gives an overview of the main functions of the package. Just type vignette("prospectr-intro")
in the console to access it. Currently, the following preprocessing functions are available:
resample()
: resample a signal to new coordinates by linear or spline interpolationresample2()
: resample a signal to new coordinates using FWHM valuesmovav()
: moving averagestandardNormalVariate()
: standard normal variatemsc()
: multiplicative scatter correctiondetrend()
: detrend normalizationbaseline()
: baseline removal/correctionblockScale()
: block scalingblockNorm()
: sum of squares block weightingbinning()
: average in column–wise subsetssavitzkyGolay()
: Savitzky-Golay filter (smoothing and derivatives)gapDer()
: gap-segment derivativecontinuumRemoval()
: continuum-removed absorbance or reflectance values
The selection of representative samples/observations for calibration of spectral models can be achieved with one of the following functions:
naes()
: k-means samplingkenStone()
: CADEX (Kennard–Stone) algorithmduplex()
: DUPLEX algorithmshenkWest()
: SELECT algorithmpuchwein()
: Puchwein samplinghonigs()
: Unique-sample selection by spectral subtraction
Other useful functions are also available:
read_nircal()
: read binary files exported from BUCHI NIRCal softwarereadASD()
: read binary or text files from an ASD instrument (Indico Pro format)spliceCorrection()
: correct spectra for steps at the splice of detectors in an ASD FieldSpec ProcochranTest()
: detects replicate outliers with the Cochran C test
Citing the package
Antoine Stevens and Leornardo Ramirez-Lopez (2024). An introduction to the prospectr package. R package Vignette R package version 0.2.4. A BibTeX entry for LaTeX users is:
@Manual{stevens2024prospectr,
title = {An introduction to the prospectr package},
author = {Antoine Stevens and Leornardo Ramirez-Lopez},
publication = {R package Vignette},
year = {2024},
note = {R package version 0.2.7},
}
Bug report and development version
You can send an email to the package maintainer ([email protected]) or create an issue on github. To install the development version of prospectr
, simply install devtools
from CRAN then run install_github("l-ramirez-lopez/prospectr")
.