spEMD {spemd} | R Documentation |
spEMD
Description
2D EMD for spatial objects
Usage
spEMD(data, zcol = "z", method = "splines", n.imf.max = 10,
n.sp.max = 5, n.extrema.min = 1, stoprule = "mean.imf",
stoprule.extrema = TRUE, thresh.extrema = 1, tol = 0,
diff.nb.extrema = 0.05, abs.nb.extrema = 5, nb.nn = 4,
n.pts.spline = 4, neig = NULL, save_neig = TRUE, verbose = TRUE)
Arguments
data |
Input dataset, either a 'data.frame' or a 'Spatial*DataFrame' |
zcol |
Name of the column containing the attribute of interest. |
method |
Interpolation method. Currently only 'splines' is supported. |
n.imf.max |
Maximum depth of decomposition (maximum number of IMF). |
n.sp.max |
Number of iterations in the sifting process. |
n.extrema.min |
Minimum number of extrema. |
stoprule |
Rule used to stop the EMD process. Currently only 'mean.imf' is implemented. |
stoprule.extrema |
Should 'spEMD' checks for the number of extrema to be similar? Defaults to 'TRUE'. |
thresh.extrema |
Significative threshold for the extrema. Defaults to 1. |
tol |
Value that the avergae of the IMF candidate need to reach so to be considered as a valid IMF. |
diff.nb.extrema |
Percentage limit difference maxima/minima. If smaller, more permissive on the mean of the IMF candidate. |
abs.nb.extrema |
Absolute difference between number of extrema. |
nb.nn |
Number of nearest neighbours to take into account (when data is on a regular grid). |
n.pts.spline |
Number of points to locally interpolate IMFs. |
neig |
Option the re-use a formerly existing neig object in order to save time. |
save_neig |
Option to save the neig object as a .RData file once created. |
verbose |
Prints progress information messages. Defaults to TRUE. |
Value
.
Author(s)
Pierre Roudier
Examples
# Getting sample data from the gstat package
if (require(gstat)) {
library(sp)
# Example for gridded data
data(ncp.grid, package = 'gstat')
coordinates(ncp.grid) <- ~x+y
gridded(ncp.grid) <- TRUE
res.ncp <- spEMD(ncp.grid, zcol = "depth", thresh.extrema = 0.1, verbose = FALSE)
# Plot results
spplot(res.ncp[, c('imf1', "imf2", "imf3")])
}
#