Nothing
#############################################################
#
# localdepth.similarity.simp.circular function
# Author: Claudio Agostinelli and Mario Romanazzi
# E-mail: claudio@unive.it
# Date: August, 28, 2008
# Version: 0.1
#
# Copyright (C) 2008 Claudio Agostinelli and Mario Romanazzi
#
#############################################################
localdepth.similarity.simp.circular <- function(x, y=NULL, tau, use=c('volume', 'diameter', 'spherical')) {
use <- match.arg(use)
if (is.null(y))
y <- x
x <- conversion.circular(x, units="radians", zero=0, rotation="counter", modulo="2pi")
attr(x, "class") <- attr(x, "circularp") <- NULL
y <- conversion.circular(y, units="radians", zero=0, rotation="counter", modulo="2pi")
attr(y, "class") <- attr(y, "circularp") <- NULL
if (!is.vector(x)) stop('y must be a vector')
if (!is.vector(y)) stop('y must be a vector')
nx <- length(x)
if (nx < 2) stop('x must have at least length 2')
ny <- length(y)
if (use=='diameter') nuse <- 1
if (use=='volume') nuse <- 2
if (use=='spherical') nuse <- 3
## number of couples
nc <- choose(nx, 2)
diameters <- rep(0, nc)
depth <- rep(0, ny*ny)
localdepth <- rep(0, ny*ny)
res <- .C("ldcircsimpsim", x = as.double(x), y = as.double(y),
nx = as.integer(nx), ny = as.integer(ny), tau = as.double(tau),
nuse = as.integer(nuse), depth = as.double(depth),
localdepth = as.double(localdepth), diameters = as.double(diameters),
DUP = TRUE, NAOK = FALSE, PACKAGE = "localdepth")
depth <- matrix(res$depth, ny, ny, byrow=FALSE)
depth[lower.tri(depth)] <- t(depth)[lower.tri(depth)]
localdepth <- matrix(res$localdepth, ny, ny, byrow=FALSE)
localdepth[lower.tri(localdepth)] <- t(localdepth)[lower.tri(localdepth)]
result <- list()
result$localdepth <- localdepth/nc
result$depth <- depth/nc
result$max.localdepth <- max(result$localdepth)
result$max.depth <- max(result$depth)
result$num <- nc
result$call <- match.call()
result$tau <- tau
result$use <- use
result$type <- 'exact'
result$nsamp <- 'all'
result$method <- 'simplicial'
class(result) <- 'localdepth.similarity'
return(result)
}
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