spectralem

Installation

1. If RcppFaddeeva is not available for the current R version use:

remotes::install_github("cran/RcppFaddeeva")

2. You can install the development version with:

remotes::install_github("jan-meissner/spectralem")

Examples

Fitting 30 Peaks:

library(spectralem)

data <- synthetic.signal(seed = 1, K = 30, noise = 0.001)
x <- data$x
y <- data$y

res <- spectralem(x, y, K = 30)
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# get position of fitted peaks
res$fit_params$pos
#>  [1] 670.9607 503.3100 316.2073 274.8785 801.8549 251.4250 706.4645 411.1184
#>  [9] 772.3675 354.4219 187.9791 549.1562 854.1438 726.5067 326.5962 572.6050
#> [17] 314.2619 688.0916 502.1091 516.8439 203.5130 238.0623 810.7499 772.4268
#> [25] 253.0410 549.7478 308.1590 178.2623 801.5274 276.4495

# plot the fit
library(ggplot2)
pd <- data.frame(x = x, y = y, fit = voigt.model(x, res$fit_params))
ggplot(pd, aes(x)) +
  geom_line(aes(y = y, colour = "y")) +
  geom_line(aes(y = fit, colour = "fit")) +
  theme_bw()

Funding

This work was developed under a Seed Fund Project (2021) of the RWTH Aachen University, funded under “the Excellence Strategy of the Federal Government and the Länder”. Project: “Spectra-Bayes: A Bayesian statistical machine learning model for spectral reconstruction” (Project Leaders: Prof. Dr. Maria Kateri, Prof. Dr.-Ing. Hans-Jürgen Koß)