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WaverideR

The 'Waverider' R package uses the continuous wavelet transform to analyze cyclostratigraphic data. The continuous wavelet transform enables the observation of transient/non-stationary cyclicity in time-series. The goal of cyclostratigraphic studies is to define frequency/period in the depth/time domain. By conducting the continuous wavelet transform on cyclostratigraphic data series one can observe and extract cyclic signals/signatures from signals. These results can then be visualized and interpreted enabling one to identify/interpret cyclicity in the geological record, which can be used to construct astrochronological age-models and identify and interpret cyclicity in past en present climate systems.

Installation

You can install the development version of WaverideR from GitHub with:

# install.packages("devtools")
devtools::install_github("stratigraphy/WaverideR")

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Install

install.packages('WaverideR')

Monthly Downloads

298

Version

0.4.1

License

GPL (>= 2)

Issues

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Repository

https://github.com/stratigraphy/WaverideR

Maintainer

Michiel Arts

Last Published

April 27th, 2025

Functions in WaverideR (0.4.1)

WaverideR_Datasets

Example data sets for the 'WaverideR' package

analyze_wavelet

Conduct the continuous wavelet transform on a time series/signal

Add a wavelet plot

Convert a proxy record to the time domain using anchor points

anchor_points_Bisciaro_al

XRF records of the Bisciaro Fm

anchor_points_grey

Example anchor points for the grey scale data set of Zeeden et al., (2013)

astrosignal_example

An ETP astronomical solution

age_model_zeeden

Age model of Zeeden et al., (2013) for the (154-174m) interval of the IODP 926 grey scale record

Anchor proxy record to an astronomical solution

add_wavelet_avg

Add a plot of a the average spectral power of a continous wavelet transform

calculate the duration of stratigraphic gaps using astronomical cycles

Convert a tracked tracked to a sedimentation rate curve

depth_rank_example

An example depth rank series

dynamic_extraction

Extract a signal in between tracked boundaries in a wavelet scalogram

delpts_tracked_period_wt

Remove tracking points which were tracked in a wavelet spectra

Convert the tracked curve to a depth time space

completed_series

Complete the tracking of cycle in a wavelet spectra

Convert the re-tracked curve results to a depth time space with uncertainty

Convert data from the depth to the time domain

curve2time_unc_anchor

Convert the re-tracked curve results to a depth time space with uncertainty

extract_signal_stable

Extract a signal/cycle from a wavelet spectra using a set period and boundaries

extract_power_stable

Extract power from a wavelet spectra by using a constant period/duration

Fit linear models to spectral peaks extracted from the wavelet spectra to astronomical cycles multiplied by sedimentation rate x

Generate standard color codes for the Geological Time Scale

extract_signal_standard_deviation

Extract a signal using standard deviation

Generates ages for the boundaries of a geochronological subdivision

extract_amplitude

Extract amplitude from a signal

Extract signal from a wavelet spectra using a traced period curve

extract_signal_stable_V2

Extract signal from a wavelet spectrum using a upper and lower period boundary

Extract power from a wavelet spectra

Detect and filter out all maxima in a signal

Discriticizes lithologs

Generate the mean age of a geological subdivision

Magnetic susceptibility data of the Sullivan core of Pas et al., (2018)

Perform an automatically loess based smoothing of a time series

Tracking points of the precession (22 kyr cycle) IODP 926 grey scale (154-174m) record of Zeeden et al., (2013)

lag-1 autocorrelation coefficient

Detect and filter out all minima in a signal

mag_track_solution

Period of the 405 kyr ecc cycle in the magnetic susceptibility record of the Sullivan core

Grey scale record IODP 926 of Zeeden et al., (2013)

Plot windowed fft based spectral analysis results

percentile_from_red_noise

Calculate average spectral power from red noise curves for a given percentile

Plots a wavelet power spectra

plot_avg_wavelet

Plot the average spectral power of a wavelet spectra

plot_win_timeOpt

plot the windowed timeOpt sedimentation rate estimation

Create an age model using minimal tuning

model_red_noise_wt

Models average spectral power based curves based on a red-noise signal generated using the characteristics of an input signal.

Plot sedimentation modelling results

Re-track cycles using a Monte-Carlo simulation

plot_astro_anchor

Plot proxy record anchored to an astronomical solution

track_period_wavelet

Track the period of a cycle in a wavelet spectra

Use a sedimentation curve to convert data to the time domain

Windowed timeOpt sedimentation rate estimation

Windowed fft based spectral analysis

wavelet_uncertainty

Calculate the uncertainty associated with the wavelet analysis based on the Gabor uncertainty principle

sum_power_sedrate

Calculate sum of maximum spectral power for sedimentation rates for a wavelet spectra

Information of the Geological timescale 2020

Total solar irradiation data (0-9400ka) of steinhilber et al., (2012)

Bisciaro_ca_wt_track

Period of the short kyr ecc cycle in the Ca record of the Bisciaro Fm

Extracting Signals from Wavelet Spectra

Bisciaro_Mg_wt_track

Period of the short kyr ecc cycle in the Mg record of the Bisciaro Fm

Bisciaro_Mn_wt_track

Period of the short kyr ecc cycle in the Mn record of the Bisciaro Fm

Hilbert_transform

Perform a Hilbert transform on a signal

Bisciaro_al_wt_track

Period of the short kyr ecc cycle in the Al record of the Bisciaro Fm

XRF records of the Bisciaro Fm

Bisciaro_sial_wt_track

Period of the short kyr ecc cycle in the si/Al record of the Bisciaro Fm