Nothing
#
# nncross.R
#
#
# $Revision: 1.43 $ $Date: 2024/02/02 02:37:06 $
#
# Copyright (C) Adrian Baddeley, Jens Oehlschlaegel and Rolf Turner 2000-2012
# Licence: GNU Public Licence >= 2
nncross <- function(X, Y, ...) {
UseMethod("nncross")
}
nncross.default <- function(X, Y, ...) {
X <- as.ppp(X, W=boundingbox)
nncross(X, Y, ...)
}
nncross.ppp <- function(X, Y, iX=NULL, iY=NULL,
what = c("dist", "which"),
...,
k = 1,
sortby=c("range", "var", "x", "y"),
is.sorted.X = FALSE,
is.sorted.Y = FALSE,
metric=NULL) {
stopifnot(is.ppp(Y) || is.psp(Y))
if(!is.null(metric)) {
ans <- invoke.metric(metric, "nncross.ppp",
X=X, Y=Y, iX=iX, iY=iY, what=what, ...,
k=k, sortby=sortby,
is.sorted.X=is.sorted.X,
is.sorted.Y=is.sorted.Y)
return(ans)
}
sortby <- match.arg(sortby)
what <- match.arg(what, choices=c("dist", "which"), several.ok=TRUE)
want.dist <- "dist" %in% what
want.which <- "which" %in% what
want.both <- want.dist && want.which
if(!missing(k)) {
# k can be a single integer or an integer vector
if(length(k) == 0)
stop("k is an empty vector")
else if(length(k) == 1) {
if(k != round(k) || k <= 0)
stop("k is not a positive integer")
} else {
if(any(k != round(k)) || any(k <= 0))
stop(paste("some entries of the vector",
sQuote("k"), "are not positive integers"))
}
}
k <- as.integer(k)
kmax <- max(k)
nk <- length(k)
nX <- npoints(X)
nY <- nobjects(Y)
## trivial cases
if(nX == 0 || nY == 0) {
result <- list(dist=matrix(Inf, nrow=nX, ncol=nk),
which=matrix(NA_integer_, nrow=nX, ncol=nk))[what]
result <- as.data.frame(result)
if(ncol(result) == 1)
result <- result[, , drop=TRUE]
return(result)
}
## Y is a line segment pattern
if(is.psp(Y)) {
if(identical(k, 1L))
return(ppllengine(X,Y,"distance")[, what])
## all distances
D <- distppll(coords(X), Y$ends, mintype=0)
ans <- XDtoNN(D, what=what, iX=iX, iY=iX, k=k)
return(ans)
}
# Y is a point pattern
if(is.null(iX) != is.null(iY))
stop("If one of iX, iY is given, then both must be given")
exclude <- (!is.null(iX) || !is.null(iY))
if(exclude) {
stopifnot(is.integer(iX) && is.integer(iY))
if(length(iX) != nX)
stop("length of iX does not match the number of points in X")
if(length(iY) != nY)
stop("length of iY does not match the number of points in Y")
}
if((is.sorted.X || is.sorted.Y) && !(sortby %in% c("x", "y")))
stop(paste("If data are already sorted,",
"the sorting coordinate must be specified explicitly",
"using sortby = \"x\" or \"y\""))
# decide whether to sort on x or y coordinate
switch(sortby,
range = {
WY <- as.owin(Y)
sortby.y <- (diff(WY$xrange) < diff(WY$yrange))
},
var = {
sortby.y <- (var(Y$x) < var(Y$y))
},
x={ sortby.y <- FALSE},
y={ sortby.y <- TRUE}
)
# The C code expects points to be sorted by y coordinate.
if(sortby.y) {
Xx <- X$x
Xy <- X$y
Yx <- Y$x
Yy <- Y$y
} else {
Xx <- X$y
Xy <- X$x
Yx <- Y$y
Yy <- Y$x
}
# sort only if needed
if(!is.sorted.X){
oX <- fave.order(Xy)
Xx <- Xx[oX]
Xy <- Xy[oX]
if(exclude) iX <- iX[oX]
}
if (!is.sorted.Y){
oY <- fave.order(Yy)
Yx <- Yx[oY]
Yy <- Yy[oY]
if(exclude) iY <- iY[oY]
}
#' Largest possible distance computable in double precision
huge <- sqrt(.Machine$double.xmax)
#' Code initialises nndist^2 to huge^2
#' and returns nndist='huge' whenever the set of distances is empty
huge <- 0.999 * huge # Ensures huge^2 <= .Machine$double.xmax
# number of neighbours that are well-defined
kmaxcalc <- min(nY, kmax)
if(kmaxcalc == 1) {
# ............... single nearest neighbour ..................
# call C code
nndv <- if(want.dist) numeric(nX) else numeric(1)
nnwh <- if(want.which) integer(nX) else integer(1)
if(!exclude) iX <- iY <- integer(1)
z <- .C(SG_nnXinterface,
n1=as.integer(nX),
x1=as.double(Xx),
y1=as.double(Xy),
id1=as.integer(iX),
n2=as.integer(nY),
x2=as.double(Yx),
y2=as.double(Yy),
id2=as.integer(iY),
exclude = as.integer(exclude),
wantdist = as.integer(want.dist),
wantwhich = as.integer(want.which),
nnd=as.double(nndv),
nnwhich=as.integer(nnwh),
huge=as.double(huge),
PACKAGE="spatstat.geom")
if(want.which) nnwcode <- z$nnwhich #sic. C code now increments by 1
if(want.dist) nndval <- z$nnd
if(want.which && any(uhoh <- (nnwcode == 0))) {
if(!exclude)
warning("NA's unexpectedly produced in nncross()$which",
call.=FALSE)
nnwcode[uhoh] <- NA
if(want.dist) nndval[uhoh] <- Inf
} else if(want.dist && any(uhoh <- (nndval > 0.99 * huge))) {
if(!exclude)
warning("Infinite distances unexpectedly returned in nncross",
call.=FALSE)
nndval[uhoh] <- Inf
}
# reinterpret in original ordering
if(is.sorted.X){
if(want.dist) nndv <- nndval
if(want.which) nnwh <- if(is.sorted.Y) nnwcode else oY[nnwcode]
} else {
if(want.dist) nndv[oX] <- nndval
if(want.which) nnwh[oX] <- if(is.sorted.Y) nnwcode else oY[nnwcode]
}
if(want.both) return(data.frame(dist=nndv, which=nnwh))
return(if(want.dist) nndv else nnwh)
} else {
# ............... k nearest neighbours ..................
# call C code
nndv <- if(want.dist) numeric(nX * kmaxcalc) else numeric(1)
nnwh <- if(want.which) integer(nX * kmaxcalc) else integer(1)
if(!exclude) iX <- iY <- integer(1)
z <- .C(SG_knnXinterface,
n1=as.integer(nX),
x1=as.double(Xx),
y1=as.double(Xy),
id1=as.integer(iX),
n2=as.integer(nY),
x2=as.double(Yx),
y2=as.double(Yy),
id2=as.integer(iY),
kmax=as.integer(kmaxcalc),
exclude = as.integer(exclude),
wantdist = as.integer(want.dist),
wantwhich = as.integer(want.which),
nnd=as.double(nndv),
nnwhich=as.integer(nnwh),
huge=as.double(huge),
PACKAGE="spatstat.geom")
# extract results
nnD <- z$nnd
nnW <- z$nnwhich
# map 0 to NA
if(want.which && any(uhoh <- (nnW == 0))) {
nnW[uhoh] <- NA
if(want.dist) nnD[uhoh] <- Inf
} else if(want.dist && any(uhoh <- (nnD > 0.99 * huge)))
nnD[uhoh] <- Inf
# reinterpret indices in original ordering
if(!is.sorted.Y) nnW <- oY[nnW]
# reform as matrices
NND <- if(want.dist) matrix(nnD, nrow=nX, ncol=kmaxcalc, byrow=TRUE) else 0
NNW <- if(want.which) matrix(nnW, nrow=nX, ncol=kmaxcalc, byrow=TRUE) else 0
if(!is.sorted.X){
# rearrange rows to correspond to original ordering of points
if(want.dist) NND[oX, ] <- NND
if(want.which) NNW[oX, ] <- NNW
}
# the return value should correspond to the original vector k
if(kmax > kmaxcalc) {
# add columns of NA / Inf
kextra <- kmax - kmaxcalc
if(want.dist)
NND <- cbind(NND, matrix(Inf, nrow=nX, ncol=kextra))
if(want.which)
NNW <- cbind(NNW, matrix(NA_integer_, nrow=nX, ncol=kextra))
}
if(length(k) < kmax) {
# select only the specified columns
if(want.dist)
NND <- NND[, k, drop=TRUE]
if(want.which)
NNW <- NNW[, k, drop=TRUE]
}
result <- as.data.frame(list(dist=NND, which=NNW)[what])
colnames(result) <- c(if(want.dist) paste0("dist.", k) else NULL,
if(want.which) paste0("which.",k) else NULL)
if(ncol(result) == 1)
result <- result[, , drop=TRUE]
return(result)
}
}
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