Use a sedimentation curve to convert data to the time domain

Convert a proxy record from the depth to time domain using a sedimentation rate curve

Usage

sedrate2tune(
  data = NULL,
  sed_curve = NULL,
  genplot = FALSE,
  keep_editable = FALSE
)

Arguments

data

Proxy record in the depth domain (required): matrix or data frame with depth in metres in column 1 and the proxy value in column 2. Its depths need not be those of sed_curve: the sedimentation rate is interpolated to every depth of the record. Default=NULL.

sed_curve

Sedimentation rate curve (required): matrix or data frame with depth in metres in column 1 and the sedimentation rate in cm/kyr in column 2, e.g. the output of minimal_tuning with output = 1. It is sorted, cleaned of NA rows and linearly interpolated to the depths of data (constant beyond its ends); the inverse rate is then integrated over depth to time (in kyr, 0 at the first sample of data). Default=NULL.

genplot

Plot the proxy record against time (kyr) (logical). Default=FALSE.

keep_editable

Keep the graphical parameters of the plot after the function returns, so that extra elements can be added (logical); only used with genplot = TRUE. Default=FALSE.

Value

The output is a matrix with 2 columns. The first column is time The second column is the proxy value If genplot=TRUE then a time vs proxy value plot will be plotted.

References

Routines for astrochronologic testing, astronomical time scale construction, and time series analysis <doi:10.1016/j.earscirev.2018.11.015>

Author

Part of the code is based on the sedrate2time function of the 'astrochron' R package

Examples

# \donttest{
# Extract the 405kyr eccentricity cycle from the wavelet scalogram
# from the magnetic susceptibility record of the Sullivan core
# of Pas et al., (2018) and then create a age model using minimal tuning
# (e.g.) set the distance between peaks to 405 kyr. The age model
# (sedimentation rate curve) is then used to convert the data
# from the depth to the time domain

mag_wt <- analyse_wavelet(data = mag,
dj = 1/100,
lowerPeriod = 0.1,
upperPeriod = 254,
verbose = FALSE,
omega_nr = 10)


mag_405 <- extract_signal_stable_V2(
 wavelet = mag_wt,
 period_max = 4,
 period_min = 2,
 add_mean = TRUE,
 plot_residual = FALSE,
 keep_editable = FALSE
)

mag_405_min_tuning <- minimal_tuning(data = mag_405,
pts = 5,
cycle = 405,
tune_opt = "max",
output = 1,
genplot = FALSE,
keep_editable = FALSE)

mag_time <- sedrate2tune(
data=mag,
sed_curve=mag_405_min_tuning,
genplot=FALSE,
keep_editable=FALSE)

# }