WaverideR

Tools for extracting and analysing cyclic signals from stratigraphic and other time series with the continuous wavelet transform and the superlet transform: spectra, significance tests, sedimentation rate estimation, tracking of periods and age-model uncertainty, plus the astrochronology functions of acycle2R and the Bayesian age-model code of astroMCBchron.

Version 0.6.0 (see NEWS.md for all changes).

Installation

# development version
# install.packages("remotes")
# remotes::install_github("stratigraphy/WaverideR")
install.packages("WaverideR", repos = c('https://stratigraphy.r-universe.dev', 'https://cloud.r-project.org'))

A short example

library(WaverideR)

wt <- analyse_wavelet(data = mag[1:300, ], dj = 1/12, lowerPeriod = 0.2, upperPeriod = 32,
                      omega_nr = 8, verbose = FALSE)
sig <- wavelet_significance(wt)                       # red-noise significance (Torrence & Compo)
plot_wavelet(wt, add_avg = TRUE, add_signif = sig)

# significance of the power in a period band, valid for any omega_nr
wavelet_band_significance(wt, period_range = c(0.8, 1.6))

vignette("WaverideR-intro") walks through the workflow.

What is in the package

• Transforms: analyse_wavelet(), analyse_superlet(), cross spectra and coherence (analyse_Xwavelet(), analyse_Xsuperlet(), analyse_wavelet_coherence()), evolutive harmonic analysis (eha_log2()), and multitaper and bispectral tools.
• Significance: wavelet_significance() (analytic and surrogate), wavelet_band_significance() (scale-averaged, any omega_nr), wavelet_uncertainty().
• Sedimentation rate: flmw(), flmw_path(), sum_power_sedrate(), model_red_noise_wt(), COCO and eCOCO.
• Tying to astronomical solutions: astro_anchor() and the interactive, random-order astro_anchor_interactive() (tie, untie, tune and inspect), plot_astro_anchor(), anchor2time().
• Tracking and age models: track_period(), track_ecoco(), curve2time(), curve2time_unc(), astroMCBchron(), modBchron().
• Plots: all scalograms share one set of panel functions, so layouts, palettes and options behave the same.

Parallel computing

Everything is sequential by default. run_multicore = TRUE and n_cores switch on base-R parallel (forked workers on Linux and macOS, PSOCK on Windows and in RStudio). The number of cores is capped by the physical cores, the free memory and the CRAN limit, and results do not depend on it.

Citation

When using WaverideR please cite both the paper that introduced the package and the package itself, for example "... using the WaverideR R package (Arts et al., 2024; Arts, 2023)":

• Arts, M., Corradini, C., Pondrelli, M., Pas, D., Da Silva, A.-C. (2024). Age and orbital forcing in the upper Silurian Cellon section (Carnic Alps, Austria) uncovered using the WaverideR R package. Frontiers in Earth Science 12, 1357751. https://doi.org/10.3389/feart.2024.1357751
• Arts, M.C.M. (2023). WaverideR: Extracting Signals from Wavelet Spectra. R package. https://CRAN.R-project.org/package=WaverideR

citation("WaverideR") prints both entries.