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#'
#' Header for all (concatenated) test files
#'
#' Require spatstat.model
#' Obtain environment variable controlling tests.
#'
#' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $
require(spatstat.model)
FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0)
ALWAYS <- TRUE
cat(paste("--------- Executing",
if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of",
"test code -----------\n"))
#' tests/aucroc.R
#'
#' AUC and ROC code
#'
#' $Revision: 1.6 $ $Date: 2020/11/02 06:26:45 $
local({
if(FULLTEST) {
fit <- kppm(redwood ~ I(y-x))
a <- roc(fit)
b <- auc(fit)
fet <- ppm(amacrine~x+y+marks)
d <- roc(fet)
e <- auc(fet)
}
})
## tests/cdf.test.R
local({
NSIM <- 9
op <- spatstat.options(ndummy.min=16, npixel=32)
if(FULLTEST) {
## Monte Carlo test for Gibbs model
fit <- ppm(cells ~ 1, Strauss(0.07))
cdf.test(fit, "x", nsim=NSIM)
## cdf.test.slrm
fut <- slrm(japanesepines ~ x + y)
Z <- distmap(japanesepines)
cdf.test(fut, Z)
}
reset.spatstat.options()
})
#'
#' tests/contrib.R
#'
#' Tests for user-contributed code in spatstat
#'
#' $Revision: 1.4 $ $Date: 2021/04/17 02:32:24 $
local({
#' Jinhom
#' Marie-Colette van Lieshout and Ottmar Cronie
X <- redwood3
if(FULLTEST) {
fit <- ppm(X ~ polynom(x,y,2))
} else {
X <- X[c(TRUE,FALSE)]
spatstat.options(npixel=32, ndummy.min=16)
fit <- ppm(X ~ x)
}
lam <- predict(fit)
lamX <- fitted(fit, dataonly=TRUE)
lmin <- 0.9 * min(lam)
g1 <- Ginhom(X, lambda=fit, update=TRUE)
if(FULLTEST) {
g2 <- Ginhom(X, lambda=fit, update=FALSE, lmin = lmin)
g3 <- Ginhom(X, lambda=lam, lmin=lmin)
g4 <- Ginhom(X, lambda=lamX, lmin=lmin)
}
if(ALWAYS) {
f2 <- Finhom(X, lambda=fit, update=FALSE)
}
if(FULLTEST) {
f1 <- Finhom(X, lambda=fit, update=TRUE)
f3 <- Finhom(X, lambda=lam, lmin=lmin)
}
if(!FULLTEST) reset.spatstat.options()
})
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