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#
# idw.R
#
# Inverse-distance weighted smoothing
#
# $Revision: 1.13 $ $Date: 2021/01/07 03:08:41 $
idw <- function(X, power=2, at=c("pixels", "points"), ..., se=FALSE) {
stopifnot(is.ppp(X) && is.marked(X))
at <- match.arg(at)
marx <- marks(X)
if(is.data.frame(marx)) {
if((nc <- ncol(marx)) > 1) {
## multiple columns of marks - process one-by-one
each <- vector(mode="list", length=nc)
for(j in 1:nc)
each[[j]] <- idw(X %mark% marx[,j], power=power, at=at, ..., se=se)
names(each) <- colnames(marx)
##
if(!se) {
## estimates only
switch(at,
pixels = { out <- as.solist(each) },
points = { out <- as.data.frame(each) }
)
} else {
## estimates and standard errors
est <- lapply(each, getElement, name="estimate")
SE <- lapply(each, getElement, name="SE")
switch(at,
pixels = {
out <- list(estimate = as.solist(est),
SE = as.solist(SE))
},
points = {
out <- list(estimate = as.data.frame(est),
SE = as.data.frame(SE))
})
}
return(out)
} else
marx <- marx[,1L]
}
if(!is.numeric(marx))
stop("Marks must be numeric")
check.1.real(power)
switch(at,
pixels = {
## create grid
W <- as.mask(as.owin(X), ...)
dim <- W$dim
npixels <- prod(dim)
## call C
if(!se) {
z <- .C(SC_Cidw,
x = as.double(X$x),
y = as.double(X$y),
v = as.double(marx),
n = as.integer(npoints(X)),
xstart = as.double(W$xcol[1L]),
xstep = as.double(W$xstep),
nx = as.integer(dim[2L]),
ystart = as.double(W$yrow[1L]),
ystep = as.double(W$ystep),
ny = as.integer(dim[1L]),
power = as.double(power),
num = as.double(numeric(npixels)),
den = as.double(numeric(npixels)),
rat = as.double(numeric(npixels)),
PACKAGE="spatstat.core")
out <- as.im(matrix(z$rat, dim[1L], dim[2L]), W=W)
out <- out[W, drop=FALSE]
} else {
z <- .C(SC_Cidw2,
x = as.double(X$x),
y = as.double(X$y),
v = as.double(marx),
n = as.integer(npoints(X)),
xstart = as.double(W$xcol[1L]),
xstep = as.double(W$xstep),
nx = as.integer(dim[2L]),
ystart = as.double(W$yrow[1L]),
ystep = as.double(W$ystep),
ny = as.integer(dim[1L]),
power = as.double(power),
num = as.double(numeric(npixels)),
den = as.double(numeric(npixels)),
rat = as.double(numeric(npixels)),
mtwo = as.double(numeric(npixels)),
wtwo = as.double(numeric(npixels)),
PACKAGE="spatstat.core")
est <- as.im(matrix(z$rat, dim[1L], dim[2L]), W=W)
est <- est[W, drop=FALSE]
sumw <- z$den
sumw2 <- z$wtwo
m2 <- z$mtwo
varden <- sumw - sumw2/sumw
varden[varden <= 0] <- NA
SE <- sqrt(m2/varden)
SE <- as.im(matrix(SE, dim[1L], dim[2L]), W=W)
SE <- SE[W, drop=FALSE]
out <- solist(estimate=est, SE=SE)
}
},
points={
npts <- npoints(X)
if(!se) {
z <- .C(SC_idwloo,
x = as.double(X$x),
y = as.double(X$y),
v = as.double(marx),
n = as.integer(npts),
power = as.double(power),
num = as.double(numeric(npts)),
den = as.double(numeric(npts)),
rat = as.double(numeric(npts)),
PACKAGE="spatstat.core")
out <- z$rat
} else {
z <- .C(SC_idwloo2,
x = as.double(X$x),
y = as.double(X$y),
v = as.double(marx),
n = as.integer(npts),
power = as.double(power),
num = as.double(numeric(npts)),
den = as.double(numeric(npts)),
rat = as.double(numeric(npts)),
mtwo = as.double(numeric(npts)),
wtwo = as.double(numeric(npts)),
PACKAGE="spatstat.core")
est <- z$rat
sumw <- z$den
sumw2 <- z$wtwo
m2 <- z$mtwo
varden <- sumw - sumw2/sumw
varden[varden <= 0] <- NA
SE <- sqrt(m2/varden)
out <- list(estimate=est, SE=SE)
}
})
return(out)
}
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