R Under development (unstable) (2024-11-18 r87347 ucrt) -- "Unsuffered Consequences"
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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)
Loading required package: spatstat.model
Loading required package: spatstat.data
Loading required package: spatstat.univar
spatstat.univar 3.1-1
Loading required package: spatstat.geom
spatstat.geom 3.3-4
Loading required package: spatstat.random
spatstat.random 3.3-2
Loading required package: spatstat.explore
Loading required package: nlme
spatstat.explore 3.3-3
Loading required package: rpart
spatstat.model 3.3-3
> FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0)
> ALWAYS   <- TRUE
> cat(paste("--------- Executing",
+           if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of",
+           "test code -----------\n"))
--------- Executing **RESTRICTED** subset of test code -----------
> #'  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()
+ })
> 
> proc.time()
   user  system elapsed 
   1.71    0.31    2.01