plot_correlogram: Plot a correlogram from noise cross correlation analysis

In coffeemuggler/eseis: Environmental Seismology Toolbox

Plot a correlogram from noise cross correlation analysis

Description

The function uses the output of ncc_correlate() to show an image plot of a noise cross correlation analysis.

Usage

plot_correlogram(data, agg = c(1, 1), legend = TRUE, keep_par = FALSE, ...)

Arguments

data	List object, spectrogram to be plotted. Must be output of ncc_correlate() or of equivalent structure.
agg	Integer vector of length two, factors of image aggregation, i.e. in time and lag dimension. Useful to decrease image size. Default is c(1, 1) (no aggregation).
legend	Logical value, option to add colour bar legend. Legend label can be changed by zlab.
keep_par	Logical value, option to omit resetting plot parameters after function execution. Useful for adding further data to the plot. Default is FALSE (parameters are reset to original values).
...	Additional arguments passed to the plot function.

Value

Graphic output of a correlogram.

Author(s)

Michael Dietze

See Also

ncc_correlate

Examples

## Not run: 
  
  ## calculate correlogram
  cc <- ncc_correlate(start = "2017-04-09 00:30:00", 
                       stop = "2017-04-09 01:30:00", 
                       ID = c("RUEG1", "RUEG2"), 
                       component = c("Z", "Z"), 
                       dir = paste0(system.file("extdata", 
                                    package = "eseis"), "/"), 
                       window = 600, 
                       overlap = 0, 
                       lag = 20, 
                       f = c(0.05, 0.1), 
                       sd = 1)
                       
   ## explicit plot function call with adjusted resolution
   plot_correlogram(data = cc, agg = c(2, 5))
   
   ## define plot colour scale
   cls <- colorRampPalette(colors = c("brown", "white", "green"))
   
   ## simple function call with user-defined colour scale
   plot(cc, col = cls(100))

## End(Not run)

coffeemuggler/eseis documentation built on Nov. 25, 2024, 8:31 p.m.