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#' resolve.lambda.R
#'
#' Common code to evaluate the intensity 'lambda' in Kinhom, pcfinhom
#' (and multitype counterparts)
#'
#' resolve.lambda
#' resolve.lambdacross
#' resolve.reciplambda
#' validate.weights
#' updateData (generic) (soon to be deprecated)
#'
#' $Revision: 1.21 $ $Date: 2024/01/10 10:58:02 $
resolve.lambda <- function(X, lambda=NULL, ...) {
UseMethod("resolve.lambda")
}
resolve.lambda.ppp <- function(X, lambda=NULL, ...,
sigma=NULL, varcov=NULL,
leaveoneout=TRUE, update=TRUE,
check=TRUE) {
dangerous <- "lambda"
danger <- TRUE
if(npoints(X) == 0) {
danger <- FALSE
lambda <- numeric(0)
} else if(is.null(lambda)) {
## No intensity data provided
## Estimate density by leave-one-out kernel smoothing
lambda <- density(X, ..., sigma=sigma, varcov=varcov,
at="points", leaveoneout=leaveoneout)
lambda <- as.numeric(lambda)
if(check) validate.weights(lambda, how="density estimation")
danger <- FALSE
} else if(is.im(lambda)) {
lambda <- safelookup(lambda, X)
} else if(is.function(lambda)) {
lambda <- lambda(X$x, X$y)
} else if(is.numeric(lambda) && is.vector(as.numeric(lambda))) {
check.nvector(lambda, npoints(X), vname="lambda")
} else if(inherits(lambda, c("ppm", "kppm", "dppm", "slrm"))) {
if(!requireNamespace("spatstat.model"))
stop("The package spatstat.model is required when 'lambda' is a fitted model",
call.=FALSE)
## model provides intensity
model <- lambda
if(update) {
model <- update(model, X)
danger <- FALSE
}
if(inherits(model, "slrm")) {
#' predict.slrm has different syntax,
#' and does not support leave-one-out prediction
lambda <- predict(model)[X]
} else {
lambda <- fitted(model, dataonly=TRUE, leaveoneout=leaveoneout)
}
} else stop(paste(sQuote("lambda"),
"should be a vector, a pixel image,",
"a fitted model, or a function"))
if(check) validate.weights(lambda)
return(list(lambda=lambda,
danger=danger,
dangerous=if(danger) dangerous else NULL))
}
resolve.reciplambda <- function(X, lambda=NULL, reciplambda=NULL, ...) {
UseMethod("resolve.reciplambda")
}
resolve.reciplambda.ppp <- function(X, lambda=NULL, reciplambda=NULL,
...,
sigma=NULL, varcov=NULL,
leaveoneout=TRUE, update=TRUE,
check=TRUE) {
dangerous <- c("lambda", "reciplambda")
danger <- TRUE
if(npoints(X) == 0) {
danger <- FALSE
lambda <- reciplambda <- numeric(0)
} else if(is.null(lambda) && is.null(reciplambda)) {
## No intensity data provided
danger <- FALSE
## Estimate density by leave-one-out kernel smoothing
lambda <- density(X, ..., sigma=sigma, varcov=varcov,
at="points", leaveoneout=leaveoneout)
lambda <- as.numeric(lambda)
if(check) validate.weights(lambda, how="density estimation")
reciplambda <- 1/lambda
} else if(!is.null(reciplambda)) {
## 1/lambda values provided
lambda <- NULL
if(is.im(reciplambda)) {
reciplambda <- safelookup(reciplambda, X)
if(check) validate.weights(reciplambda, recip=TRUE, how="image lookup")
} else if(is.function(reciplambda)) {
reciplambda <- reciplambda(X$x, X$y)
if(check) validate.weights(reciplambda, recip=TRUE, how="function evaluation")
} else if(is.numeric(reciplambda) && is.vector(as.numeric(reciplambda))) {
check.nvector(reciplambda, npoints(X), vname="reciplambda")
if(check) validate.weights(reciplambda, recip=TRUE)
} else stop(paste(sQuote("reciplambda"),
"should be a vector, a pixel image, or a function"))
} else {
#' lambda values provided
if(is.im(lambda)) {
lambda <- safelookup(lambda, X)
if(check) validate.weights(lambda, how="image lookup")
} else if(is.function(lambda)) {
lambda <- lambda(X$x, X$y)
if(check) validate.weights(lambda, how="function evaluation")
} else if(is.numeric(lambda) && is.vector(as.numeric(lambda))) {
check.nvector(lambda, npoints(X), vname="lambda")
if(check) validate.weights(lambda)
} else if(inherits(lambda, c("ppm", "kppm", "dppm", "slrm"))) {
if(!requireNamespace("spatstat.model"))
stop("The package spatstat.model is required when 'lambda' is a fitted model",
call.=FALSE)
## model provides intensity
model <- lambda
if(update) {
force(X)
env.here <- sys.frame(sys.nframe())
model <- update(model, X, envir=env.here)
danger <- FALSE
}
if(inherits(model, "slrm")) {
#' predict.slrm has different syntax,
#' and does not support leave-one-out prediction
lambda <- predict(model)[X]
} else {
lambda <- fitted(model, dataonly=TRUE, leaveoneout=leaveoneout)
}
if(check) validate.weights(lambda, how="model prediction")
} else stop(paste(sQuote("lambda"),
"should be a vector, a pixel image,",
"a fitted model, or a function"))
## evaluate reciprocal
reciplambda <- 1/lambda
}
return(list(lambda=lambda, reciplambda=reciplambda,
danger=danger,
dangerous=if(danger) dangerous else NULL))
}
resolve.lambdacross <- function(X, I, J,
lambdaI=NULL, lambdaJ=NULL, ...) {
UseMethod("resolve.lambdacross")
}
resolve.lambdacross.ppp <- function(X, I, J,
lambdaI=NULL, lambdaJ=NULL,
...,
lambdaX=NULL,
sigma=NULL, varcov=NULL,
leaveoneout=TRUE, update=TRUE,
lambdaIJ=NULL,
Iexplain="points satisfying condition I",
Jexplain="points satisfying condition J") {
dangerous <- c("lambdaI", "lambdaJ")
dangerI <- dangerJ <- TRUE
XI <- X[I]
XJ <- X[J]
nI <- npoints(XI)
nJ <- npoints(XJ)
lamIname <- short.deparse(substitute(lambdaI))
lamJname <- short.deparse(substitute(lambdaJ))
bothnames <- c(lamIname, lamJname)
givenI <- !is.null(lambdaI)
givenJ <- !is.null(lambdaJ)
givenX <- !is.null(lambdaX)
if(givenI != givenJ) {
givenone <- bothnames[c(givenI, givenJ)]
missedone <- setdiff(bothnames, givenone)
stop(paste("If", givenone, "is given, then",
missedone, "should also be given"),
call.=FALSE)
}
if(givenX && givenI && givenJ)
warning(paste(paste(sQuote(bothnames), collapse=" and "),
"were ignored because", sQuote("lambdaX"),
"was given"),
call.=FALSE)
if(givenX) {
## Intensity values for all points of X
if(is.im(lambdaX)) {
## Look up intensity values
lambdaI <- safelookup(lambdaX, XI)
lambdaJ <- safelookup(lambdaX, XJ)
} else if(is.imlist(lambdaX) &&
is.multitype(X) &&
length(lambdaX) == length(levels(marks(X)))) {
## Look up intensity values
Y <- split(X)
lamY <- mapply("[", x=lambdaX, i=Y, SIMPLIFY=FALSE)
lamX <- unsplit(lamY, marks(X))
lambdaI <- lamX[I]
lambdaJ <- lamX[J]
} else if(is.function(lambdaX)) {
## evaluate function at locations
if(!is.marked(X) || length(formals(lambdaX)) == 2) {
lambdaI <- lambdaX(XI$x, XI$y)
lambdaJ <- lambdaX(XJ$x, XJ$y)
} else {
lambdaI <- lambdaX(XI$x, XI$y, marks(XI))
lambdaJ <- lambdaX(XJ$x, XJ$y, marks(XJ))
}
} else if(is.numeric(lambdaX) && is.vector(as.numeric(lambdaX))) {
## vector of intensity values
if(length(lambdaX) != npoints(X))
stop(paste("The length of", sQuote("lambdaX"),
"should equal the number of points of X"))
lambdaI <- lambdaX[I]
lambdaJ <- lambdaX[J]
} else if(inherits(lambdaX, c("ppm", "kppm", "dppm", "slrm"))) {
if(!requireNamespace("spatstat.model"))
stop("The package spatstat.model is required when 'lambdaX' is a fitted model",
call.=FALSE)
## point process model provides intensity
model <- lambdaX
if(update) {
force(X)
env.here <- sys.frame(sys.nframe())
model <- update(model, X, envir=env.here)
dangerI <- dangerJ <- FALSE
dangerous <- "lambdaIJ"
}
if(inherits(model, "slrm")) {
#' predict.slrm has different syntax,
#' and does not support leave-one-out prediction
Lambda <- predict(model)
lambdaI <- Lambda[XI]
lambdaJ <- Lambda[XJ]
} else {
## re-fit model to data X
lambdaX <- fitted(model, dataonly=TRUE, leaveoneout=leaveoneout)
lambdaI <- lambdaX[I]
lambdaJ <- lambdaX[J]
}
} else stop(paste("Argument lambdaX is not understood:",
"it should be a numeric vector,",
"an image, a function(x,y)",
"or a fitted point process model (ppm, kppm or dppm)"))
} else {
## lambdaI, lambdaJ expected
if(!givenI) {
## estimate intensity
dangerI <- FALSE
dangerous <- setdiff(dangerous, "lambdaI")
lambdaI <- density(XI, ..., sigma=sigma, varcov=varcov,
at="points", leaveoneout=leaveoneout)
} else if(is.im(lambdaI)) {
## look up intensity values
lambdaI <- safelookup(lambdaI, XI)
} else if(is.function(lambdaI)) {
## evaluate function at locations
lambdaI <- lambdaI(XI$x, XI$y)
} else if(is.numeric(lambdaI) && is.vector(as.numeric(lambdaI))) {
## validate intensity vector
check.nvector(lambdaI, nI, things=Iexplain, vname="lambdaI")
} else if(inherits(lambdaI, c("ppm", "kppm", "dppm", "slrm"))) {
if(!requireNamespace("spatstat.model"))
stop("The package spatstat.model is required when 'lambdaI' is a fitted model",
call.=FALSE)
## point process model provides intensity
model <- lambdaI
if(update) {
force(X)
env.here <- sys.frame(sys.nframe())
model <- update(model, X, envir=env.here)
dangerI <- FALSE
dangerous <- setdiff(dangerous, "lambdaI")
}
if(inherits(model, "slrm")) {
#' predict.slrm has different syntax,
#' and does not support leave-one-out prediction
lambdaI <- predict(model)[XI]
} else {
lambdaX <- fitted(model, dataonly=TRUE, leaveoneout=leaveoneout)
lambdaI <- lambdaX[I]
}
} else stop(paste(sQuote("lambdaI"), "should be a vector or an image"))
if(!givenJ) {
## estimate intensity
dangerJ <- FALSE
dangerous <- setdiff(dangerous, "lambdaJ")
lambdaJ <- density(XJ, ..., sigma=sigma, varcov=varcov,
at="points", leaveoneout=leaveoneout)
} else if(is.im(lambdaJ)) {
## look up intensity values
lambdaJ <- safelookup(lambdaJ, XJ)
} else if(is.function(lambdaJ)) {
## evaluate function at locations
lambdaJ <- lambdaJ(XJ$x, XJ$y)
} else if(is.numeric(lambdaJ) && is.vector(as.numeric(lambdaJ))) {
## validate intensity vector
check.nvector(lambdaJ, nJ, things=Jexplain, vname="lambdaJ")
} else if(inherits(lambdaJ, c("ppm", "kppm", "dppm", "slrm"))) {
if(!requireNamespace("spatstat.model"))
stop("The package spatstat.model is required when 'lambdaJ' is a fitted model",
call.=FALSE)
## point process model provides intensity
model <- lambdaJ
if(update) {
force(X)
env.here <- sys.frame(sys.nframe())
model <- update(model, X, envir=env.here)
dangerJ <- FALSE
dangerous <- setdiff(dangerous, "lambdaJ")
}
if(inherits(model, "slrm")) {
#' predict.slrm has different syntax,
#' and does not support leave-one-out prediction
lambdaJ <- predict(model)[XJ]
} else {
lambdaX <- fitted(model, dataonly=TRUE, leaveoneout=leaveoneout)
lambdaJ <- lambdaX[J]
}
} else
stop(paste(sQuote("lambdaJ"), "should be a vector or an image"))
}
## Weight for each pair
if(!is.null(lambdaIJ)) {
dangerIJ <- TRUE
dangerous <- union(dangerous, "lambdaIJ")
if(!is.matrix(lambdaIJ))
stop("lambdaIJ should be a matrix")
if(nrow(lambdaIJ) != nI)
stop(paste("nrow(lambdaIJ) should equal the number of", Iexplain))
if(ncol(lambdaIJ) != nJ)
stop(paste("ncol(lambdaIJ) should equal the number of", Jexplain))
} else {
dangerIJ <- FALSE
}
danger <- dangerI || dangerJ || dangerIJ
return(list(lambdaI = lambdaI, lambdaJ = lambdaJ, lambdaIJ=lambdaIJ,
danger = danger, dangerous = dangerous))
}
validate.weights <- function(x, recip=FALSE, how = NULL,
allowzero = recip,
allowinf = !recip) {
ra <- range(x)
offence <-
if(!allowinf && !all(is.finite(ra))) "infinite" else
if(ra[1] < 0) "negative" else
if(!allowzero && ra[1] == 0) "zero" else NULL
if(!is.null(offence)) {
xname <- deparse(substitute(x))
offenders <- paste(offence, "values of", sQuote(xname))
if(is.null(how))
stop(paste(offenders, "are not allowed"), call.=FALSE)
stop(paste(how, "yielded", offenders), call.=FALSE)
}
return(TRUE)
}
## The following internal functions will soon be removed.
## They will be replaced by the idiom
## model <- update(model, X, ...)
updateData <- function(model, X, ...) {
UseMethod("updateData")
}
updateData.default <- function(model, X, ..., warn=TRUE) {
## for some bizarre reason, method dispatch often fails for this function
## so we do it by hand as a backup
if(inherits(model, c("ppm", "kppm", "dppm", "slrm"))) {
if (requireNamespace("spatstat.model")) {
model <- update(model, X)
} else if (warn) {
warning("Model was not updated; this requires package spatstat.model",
call. = FALSE)
}
} else if(inherits(model, "lppm")) {
if (requireNamespace("spatstat.linnet")) {
model <- update(model, X)
} else if (warn) {
warning("Model was not updated; this requires package spatstat.linnet",
call. = FALSE)
}
} else if (warn) {
warning("Unrecognised kind of 'model'; no update performed",
call. = FALSE)
}
return(model)
}
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