alkahest is a lightweight, dependency-free toolbox
for pre-processing XY data from experimental methods (i.e. any signal
that can be measured along a continuous variable). It provides methods
for baseline estimation and correction, smoothing, normalization,
integration and peaks detection.
Baseline estimation methods: Linear, Polynomial (Lieber and
Mahadevan-Jansen 2003), Asymmetric Least Squares (Eilers and Boelens
2005), Rolling Ball (Kneen and Annegarn 1996), Rubberband, SNIP (Morháč
et al. 1997; Morháč and Matoušek 2008; Ryan et al. 1988), 4S Peak
Filling (Liland 2015).
Smoothing methods: Rectangular, Triangular, Loess, Savitzky-Golay
Filter (Gorry 1990; Savitzky and Golay 1964), Whittaker (Eilers 2003),
Penalized Likelihood (De Rooi et al. 2014)
alkahest expects the input data to be in the
simplest form (a two-column matrix or data frame, a two-element list or
two numeric vectors).
## X-ray diffractiondata("XRD")## 4S Peak Filling baselinebaseline <-baseline_peakfilling(XRD, n =10, m =5, by =10, sparse =TRUE)plot(XRD, type ="l", xlab =expression(2*theta), ylab ="Count")lines(baseline, type ="l", col ="red")
## Correct baselineXRD <-signal_drift(XRD, lag = baseline, subtract =TRUE)## Find peakspeaks <-peaks_find(XRD, SNR =3, m =11)plot(XRD, type ="l", xlab =expression(2*theta), ylab ="Count")lines(peaks, type ="p", pch =16, col ="red")
## Simulate dataset.seed(12345)x <-seq(-4, 4, length =100)y <-dnorm(x)z <- y +rnorm(100, mean =0, sd =0.01) # Add some noise## Plot raw dataplot(x, z, type ="l", xlab ="", ylab ="", main ="Raw data")lines(x, y, type ="l", lty =2, col ="red")## Savitzky–Golay filtersmooth <-smooth_savitzky(x, z, m =21, p =2)plot(smooth, type ="l", xlab ="", ylab ="", main ="Savitzky–Golay filter")lines(x, y, type ="l", lty =2, col ="red")
Contributing
Please note that the alkahest project is released
with a Contributor Code
of Conduct. By contributing to this project, you agree to abide by
its terms.
References
Barnes, R. J., M. S. Dhanoa, and Susan J. Lister. 1989. “Standard Normal
Variate Transformation and De-Trending of Near-Infrared Diffuse
Reflectance Spectra.” Applied Spectroscopy 43 (5): 772–77. https://doi.org/10.1366/0003702894202201.
De Rooi, Johan J., Niek M. Van Der Pers, Ruud W. A. Hendrikx, Rob
Delhez, Amarante J. Böttger, and Paul H. C. Eilers. 2014. “Smoothing of
X-ray Diffraction Data and K α
2 Elimination Using Penalized Likelihood and the Composite
Link Model.” Journal of Applied Crystallography 47 (3): 852–60.
https://doi.org/10.1107/S1600576714005809.
Eilers, Paul H. C., and Hans F. M. Boelens. 2005. “Baseline Correction
with Asymmetric Least Squares Smoothing.” October 21, 2005.
Gorry, Peter A. 1990. “General Least-Squares Smoothing and
Differentiation by the Convolution (Savitzky-Golay) Method.”
Analytical Chemistry 62 (6): 570–73. https://doi.org/10.1021/ac00205a007.
Kneen, M. A., and H. J. Annegarn. 1996. “Algorithm for Fitting XRF, SEM
and PIXE X-ray Spectra Backgrounds.”
Nuclear Instruments and Methods in Physics Research Section B: Beam
Interactions with Materials and Atoms 109–110 (April): 209–13. https://doi.org/10.1016/0168-583X(95)00908-6.
Lieber, Chad A., and Anita Mahadevan-Jansen. 2003. “Automated Method for
Subtraction of Fluorescence from Biological Raman Spectra.” Applied
Spectroscopy 57 (11): 1363–67. https://doi.org/10.1366/000370203322554518.
Morháč, Miroslav, Ján Kliman, Vladislav Matoušek, Martin Veselský, and
Ivan Turzo. 1997. “Background Elimination Methods for Multidimensional
Coincidence γ-Ray Spectra.” Nuclear Instruments and Methods in
Physics Research Section A: Accelerators, Spectrometers, Detectors and
Associated Equipment 401 (1): 113–32. https://doi.org/10.1016/S0168-9002(97)01023-1.
Morháč, Miroslav, and Vladislav Matoušek. 2008. “Peak Clipping
Algorithms for Background Estimation in Spectroscopic Data.” Applied
Spectroscopy 62 (1): 91–106. https://doi.org/10.1366/000370208783412762.
Ryan, C. G., E. Clayton, W. L. Griffin, S. H. Sie, and D. R. Cousens.
1988. “SNIP, a Statistics-Sensitive Background Treatment for the
Quantitative Analysis of PIXE Spectra in Geoscience Applications.”
Nuclear Instruments and Methods in Physics Research Section B: Beam
Interactions with Materials and Atoms 34 (3): 396–402. https://doi.org/10.1016/0168-583X(88)90063-8.
Savitzky, Abraham., and M. J. E. Golay. 1964. “Smoothing and
Differentiation of Data by Simplified Least Squares Procedures.”
Analytical Chemistry 36 (8): 1627–39. https://doi.org/10.1021/ac60214a047.
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