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

Source: R/sum_power_sedrate.R
sum_power_sedrate.Rd

The sum_power_sedrate function is used calculate the sum of maximum spectral power for a list of astronomical cycles from a wavelet spectra. The data is first normalised using the average spectral power curves for a given percentile based on results of the model_red_noise_wt function

Usage

sum_power_sedrate(
  red_noise = NULL,
  wavelet = NULL,
  percentile = NULL,
  sedrate_low = NULL,
  sedrate_high = NULL,
  spacing = NULL,
  cycles = c(NULL),
  x_lab = "depth",
  y_lab = "sedrate",
  run_multicore = FALSE,
  n_cores = NULL,
  genplot = FALSE,
  plot_res = 1,
  keep_editable = FALSE,
  palette_name = "viridis",
  color_brewer = "viridis",
  verbose = FALSE,
  colour_brewer = NULL
)

Arguments

red_noise

Red-noise power curves (required): the output of model_red_noise_wt for the same wavelet, a matrix with one row per period of wavelet and one column per red-noise simulation. Default=NULL.

wavelet

Wavelet object (required) created with analyse_wavelet, of a record with depth in metres. Default=NULL.

percentile

Percentile of the red-noise power (numeric, between 0 and 1) by which the wavelet power is weighted: at every period the threshold is the percentile quantile of a normal distribution with the mean and standard deviation of the red_noise runs. This accounts for the distortion of the power spectrum by the analytical technique and by random red noise. Required. Default=NULL.

sedrate_low

Lowest sedimentation rate tested, in cm/kyr (numeric, > 0). Required. Default=NULL.

sedrate_high

Highest sedimentation rate tested, in cm/kyr (numeric, > sedrate_low). Required. Default=NULL.

spacing

Step between the tested sedimentation rates, in cm/kyr (numeric, > 0). Required. Default=NULL.

cycles

Periods of the astronomical cycles, in kyr (numeric vector, e.g. c(405, 125, 95, 40, 21)), whose expected periods in depth (sedimentation rate x period) are searched for in the scalogram. Required. Default=c(NULL).

x_lab

Label of the depth axis of the plot (character). Default="depth".

y_lab

Label of the sedimentation rate axis of the plot (character). Default="sedrate".

run_multicore

Run the calculation for the positions along the record in parallel on several cores (logical). Default=FALSE.

n_cores

Number of cores used when run_multicore = TRUE (integer, or NULL). NULL uses an automatic, safe number: physical cores minus one, at most 4, and limited by the free memory; set options(waverider.n_cores = ...) to change it. A value > 1 also switches on parallel computing. Results do not depend on the number of cores. Default=NULL.

genplot

Plot the result (selected with plot_res) as a depth versus sedimentation rate map with its average curve (logical). Default=FALSE.

plot_res

Which result to plot when genplot = TRUE (integer): 1 the normalised sum of maximum spectral power, 2 the number of astronomical components found. Default=1.

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.

palette_name

Name of the colour palette of the power (colour) scale, a character string. Which names are valid depends on color_brewer:

  • color_brewer = "grDevices": "rainbow", "heat.colors", "terrain.colors", "topo.colors", "cm.colors", or any of the 115 hcl.colors palettes (list them with grDevices::hcl.pals()), for example "viridis", "Plasma", "Inferno", "YlOrRd", "Spectral", "Blue-Red", "Zissou 1".

  • color_brewer = "viridis": "viridis", "magma", "inferno", "plasma", "cividis", "rocket", "mako", "turbo".

  • color_brewer = "RColorBrewer": "BrBG", "PiYG", "PRGn", "PuOr", "RdBu", "RdGy", "RdYlBu", "RdYlGn", "Spectral", "Accent", "Dark2", "Paired", "Pastel1", "Pastel2", "Set1", "Set2", "Set3", "Blues", "BuGn", "BuPu", "GnBu", "Greens", "Greys", "Oranges", "OrRd", "PuBu", "PuBuGn", "PuRd", "Purples", "RdPu", "Reds", "YlGn", "YlGnBu", "YlOrBr", "YlOrRd" (also listed by wr_brewer_palettes()).

  • color_brewer = "colorRamps": "blue2green", "blue2green2red", "blue2red", "blue2yellow", "cyan2yellow", "green2red", "magenta2green", "matlab.like", "matlab.like2", "ygobb".

  • color_brewer = "scico" (all except "batlowK" need the scico package): "acton", "bam", "bamako", "bamO", "batlow", "batlowK", "batlowW", "berlin", "bilbao", "broc", "brocO", "buda", "bukavu", "cork", "corkO", "davos", "devon", "fes", "glasgow", "grayC", "hawaii", "imola", "lajolla", "lapaz", "lipari", "lisbon", "managua", "navia", "nuuk", "oleron", "oslo", "roma", "romaO", "tofino", "tokyo", "turku", "vanimo", "vik", "vikO".

Low power is drawn with the first colour of the palette and high power with the last. Default="viridis".

color_brewer

Palette family from which palette_name is taken, a character string: "grDevices", "viridis", "RColorBrewer", "colorRamps" or "scico" (the last one, except for "batlowK", needs the scico package). See palette_name for the palette names of each family. Default="viridis".

verbose

Show the progress of the calculation (logical, TRUE or FALSE). Default=FALSE.

colour_brewer

British spelling of color_brewer, with the same options; if given (not NULL) it overrides color_brewer. Default=NULL.

Value

Returns a list which contains 4 elements element 1: sum of maximum spectral power element 2: number of cycles used in the sum of maximum spectral power element 3: y-axis values of the matrices which is sedimentation rate element 4: x-axis values of the matrices which is depth

If Default="TRUE" a plot is created with 3 subplots. Subplot 1 is plot in which the the sum of maximum spectral power for a given sedimentation rate or nr of cycles is plotted for each depth given depth. Subplot 2 is a plot in which the average sum of maximum spectral power is plotted fro each sedimentation Subplot 3 is a color scale for subplot 1.

References

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

Acycle: Time-series analysis software for paleoclimate research and education, Mingsong Li, Linda Hinnov, Lee Kump, Computers & Geosciences,Volume 127,2019,Pages 12-22,ISSN 0098-3004, <doi:10.1016/j.cageo.2019.02.011>

Tracking variable sedimentation rates and astronomical forcing in Phanerozoic paleoclimate proxy series with evolutionary correlation coefficients and hypothesis testing, Mingsong Li, Lee R. Kump, Linda A. Hinnov, Michael E. Mann, Earth and Planetary Science Letters,Volume 501, T2018,Pages 165-179,ISSN 0012-821X,<doi:10.1016/j.epsl.2018.08.041>

Author

Based on the asm and eAsm functions of the 'astrochron' R package and the 'eCOCO' and 'COCO' functions of the 'Acycle' software

Examples

# \donttest{
#estimate sedimentation rate for the the magnetic susceptibility record
# of the Sullivan core of Pas et al., (2018).

mag_wt <- analyse_wavelet(data = mag[1:200, ],
dj = 1/10,
lowerPeriod = 0.1,
upperPeriod = 32,
verbose = FALSE,
omega_nr = 10)

#increase n_simulations to better define the red noise spectral power curve
mag_wt_red_noise <- model_red_noise_wt(wavelet=mag_wt,
n_simulations = 3,
run_multicore=FALSE,
verbose=FALSE)

sedrates <- sum_power_sedrate(red_noise=mag_wt_red_noise,
wavelet=mag_wt,
percentile=0.75,
sedrate_low = 0.5,
sedrate_high = 4,
spacing = 1,
cycles = c(2376,1600,1180,696,406,110),
x_lab="depth",
y_lab="sedrate",
run_multicore=FALSE,
genplot = FALSE,
plot_res=1,
keep_editable=FALSE,
palette_name = "rainbow",
color_brewer="grDevices",
verbose=FALSE)
# }