Nothing
.smap_sf_method = \(data,column,target,lib = NULL,pred = NULL,E = 3,tau = 1,k = E+2,
theta = c(0, 1e-04, 3e-04, 0.001, 0.003, 0.01, 0.03,
0.1, 0.3, 0.5, 0.75, 1, 1.5, 2, 3, 4, 6, 8),
nb = NULL, threads = detectThreads(), detrend = TRUE){
vx = .uni_lattice(data,column,detrend)
vy = .uni_lattice(data,target,detrend)
if (is.null(lib)) lib = .internal_library(cbind(vx,vy))
if (is.null(pred)) pred = lib
if (is.null(nb)) nb = .internal_lattice_nb(data)
res = RcppSMap4Lattice(vx,vy,nb,lib,pred,theta,E,tau,k,threads)
return(.bind_xmapself(res,target,"smap"))
}
.smap_spatraster_method = \(data,column,target,lib = NULL,pred = NULL,E = 3,tau = 1,k = E+2,
theta = c(0, 1e-04, 3e-04, 0.001, 0.003, 0.01, 0.03,
0.1, 0.3, 0.5, 0.75, 1, 1.5, 2, 3, 4, 6, 8),
threads = detectThreads(), detrend = TRUE){
mx = .uni_grid(data,column,detrend)
my = .uni_grid(data,target,detrend)
if (is.null(lib)) lib = which(!(is.na(mx) | is.na(my)), arr.ind = TRUE)
if (is.null(pred)) pred = lib
res = RcppSMap4Grid(mx,my,lib,pred,theta,E,tau,k,threads)
return(.bind_xmapself(res,target,"smap"))
}
#' smap forecast
#'
#' @inheritParams simplex
#' @param theta (optional) weighting parameter for distances.
#'
#' @return A list
#' \describe{
#' \item{\code{xmap}}{forecast performance}
#' \item{\code{varname}}{name of target variable}
#' \item{\code{method}}{method of cross mapping}
#' }
#' @export
#' @name smap
#' @aliases smap,sf-method
#' @references
#' Sugihara G. 1994. Nonlinear forecasting for the classification of natural time series. Philosophical Transactions: Physical Sciences and Engineering, 348 (1688):477-495.
#'
#' @examples
#' columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
#' \donttest{
#' smap(columbus,"inc","crime",E = 5,k = 6)
#' }
methods::setMethod("smap", "sf", .smap_sf_method)
#' @rdname smap
methods::setMethod("smap", "SpatRaster", .smap_spatraster_method)
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