https://github.com/l-ramirez-lopez/prospectr
R package: Misc. Functions for Processing and Sample Selection of Spectroscopic Data
https://github.com/l-ramirez-lopez/prospectr
chemometrics derivatives infrared near-infrared nir pedometrics preprocessing r r-package resample sampling signal soil-spectroscopy spectroscopy
Last synced: 2 months ago
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R package: Misc. Functions for Processing and Sample Selection of Spectroscopic Data
- Host: GitHub
- URL: https://github.com/l-ramirez-lopez/prospectr
- Owner: l-ramirez-lopez
- License: other
- Created: 2020-03-17T16:31:34.000Z (almost 6 years ago)
- Default Branch: main
- Last Pushed: 2025-10-17T20:24:06.000Z (2 months ago)
- Last Synced: 2025-10-18T21:43:01.710Z (2 months ago)
- Topics: chemometrics, derivatives, infrared, near-infrared, nir, pedometrics, preprocessing, r, r-package, resample, sampling, signal, soil-spectroscopy, spectroscopy
- Language: R
- Homepage: https://CRAN.R-project.org/package=prospectr
- Size: 17.4 MB
- Stars: 44
- Watchers: 5
- Forks: 21
- Open Issues: 9
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
title: "README"
output: md_document
date: "2022-09-18"
---
# prospectr
[](https://CRAN.R-project.org/package=prospectr)
[](https://cranlogs.r-pkg.org/badges/prospectr)
Misc. Functions for Processing and Sample Selection of Spectroscopic Data
_Antoine Stevens & Leo Ramirez-Lopez_
_Last update: `r Sys.Date()`_
Version: `r paste(prospectr:::pkg_info()[1:2], collapse = " \U002D\U002D ")`
`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`](https://CRAN.R-project.org/package=signal), the
functions in this package work indifferently for `data.frame`, `matrix` and
`vector` inputs. Besides, several functions are optimized for speed and use
C++ code through the [`Rcpp`](https://CRAN.R-project.org/package=Rcpp)
and [`RcppArmadillo`](https://CRAN.R-project.org/package=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](https://cran.r-project.org/bin/macosx/tools/). Even for R >= 4.0.
For more info, check this [issue](https://github.com/tidyverts/fable/issues/193).
## 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](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 interpolation
- `resample2()` : resample a signal to new coordinates using FWHM values
- `movav()` : moving average
- `standardNormalVariate()` : standard normal variate
- `msc()` : multiplicative scatter correction
- `detrend()` : detrend normalization
- `baseline()` : baseline removal/correction
- `blockScale()` : block scaling
- `blockNorm()` : sum of squares block weighting
- `binning()` : average in column--wise subsets
- `savitzkyGolay()` : Savitzky-Golay filter (smoothing and derivatives)
- `gapDer()` : gap-segment derivative
- `continuumRemoval()` : 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 sampling
- `kenStone()` : CADEX (Kennard--Stone) algorithm
- `duplex()` : DUPLEX algorithm
- `shenkWest()` : SELECT algorithm
- `puchwein()` : Puchwein sampling
- `honigs()` : Unique-sample selection by spectral subtraction
Other useful functions are also available:
- `read_nircal()` : read binary files exported from BUCHI NIRCal software
- `readASD()` : 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 Pro
- `cochranTest()` : detects replicate outliers with the Cochran _C_ test
## Citing the package
Antoine Stevens and Leornardo Ramirez-Lopez (2025). An introduction to the prospectr package. R package
Vignette R package version 0.2.8.
A BibTeX entry for LaTeX users is:
```
@Manual{stevens2022prospectr,
title = {An introduction to the prospectr package},
author = {Antoine Stevens and Leornardo Ramirez-Lopez},
publication = {R package Vignette},
year = {2025},
note = {R package version 0.2.8},
}
```
## Bug report and development version
You can send an email to the package maintainer ()
or create an [issue](https://github.com/l-ramirez-lopez/prospectr/issues) on github.
To install the development version of `prospectr`, simply install [`devtools`](https://CRAN.R-project.org/package=devtools) from
CRAN then run `install_github("l-ramirez-lopez/prospectr")`.