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#' Kernel smoothed spatial density of point pattern
#'
#' \code{spdensity} computes a kernel smoothed spatial
#' density function from a point pattern. This function is
#' basically a wrapper for \code{\link[spatstat.explore]{density.ppp}}.
#' The \code{\link[spatstat.explore]{density.ppp}} function computes
#' the spatial intensity of a point pattern; the \code{spdensity}
#' function scales the intensity to produce a true spatial density.
#' @inheritParams spatstat.explore::density.ppp
#'
#' @return This function produces the spatial density of \code{x}
#' as an object of class \code{\link[spatstat.geom]{im}}.
#' @author Joshua French
#' @export
#' @seealso \code{\link[spatstat.explore]{density.ppp}}
#' @references Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.
#' @examples
#' data(grave)
#' contour(spdensity(grave))
spdensity <- function(x, sigma = NULL, ..., weights=NULL, edge = TRUE,
varcov = NULL, at = "pixels",
leaveoneout = TRUE, adjust = 1, diggle = FALSE,
kernel = "gaussian", scalekernel = is.character(kernel),
positive = FALSE, verbose = TRUE) {
d <- spatstat.explore::density.ppp(x = x, sigma = sigma, ..., weights = weights,
edge = edge, varcov = varcov, at = at, leaveoneout = leaveoneout,
adjust = adjust, diggle = diggle,
se = FALSE, kernel = kernel, scalekernel = scalekernel,
positive = positive, verbose = verbose)
d$const <- spatstat.geom::integral.im(d)
d$v <- d$v/d$const
class(d) <- c(class(d), "spdensity")
return(d)
}
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