R version 4.4.0 RC (2024-04-16 r86458 ucrt) -- "Puppy Cup"
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> #'
> #'   Header for all (concatenated) test files
> #'
> #'   Require spatstat.univar
> #'   Obtain environment variable controlling tests.
> #'
> #'   $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $
> 
> require(spatstat.univar)
Loading required package: spatstat.univar
spatstat.univar 2.0-3
> 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/weightedstats.R
> # $Revision: 1.2 $ $Date: 2023/11/05 01:40:53 $
> 
> local({
+   if(ALWAYS) { # depends on hardware
+     ## whist()
+     ## check agreement between C and interpreted code for whist()
+     set.seed(98123)
+     x <- runif(1000)
+     w <- sample(1:5, 1000, replace=TRUE)
+     b <- seq(0,1,length=101)
+     aC <- whist(x,b,w, method="C")
+     aR <- whist(x,b,w, method="interpreted")
+     if(!all(aC == aR))
+       stop("Algorithms for whist disagree")
+   }
+   if(FULLTEST) {
+     ## cases of 'unnormdensity()'
+     x <- rnorm(20) 
+     d0 <- unnormdensity(x, weights=rep(0, 20))
+     dneg <- unnormdensity(x, weights=c(-runif(19), 0))
+   }
+ 
+ })
> 
> #'
> #'   tests/parzen.R
> #'
> #'   Tests of the Parzen-Rosenblatt estimator
> #'       (fixed bandwidth, no boundary correction)
> #'
> #'  $Revision: 1.1 $ $Date: 2023/10/22 02:39:49 $
> 
> local({
+   if(FULLTEST) {
+     #' code in kernels.R
+     kernames <- c("gaussian", "rectangular", "triangular",
+                   "epanechnikov", "biweight", "cosine", "optcosine")
+     X <- rnorm(20)
+     U <- runif(20)
+     for(ker in kernames) {
+       dX <- dkernel(X, ker)
+       fX <- pkernel(X, ker)
+       qU <- qkernel(U, ker)
+       m0 <- kernel.moment(0, 0, ker)
+       m1 <- kernel.moment(1, 0, ker)
+       m2 <- kernel.moment(2, 0, ker)
+       m3 <- kernel.moment(3, 0, ker)
+       fa <- kernel.factor(ker)
+       sq <- kernel.squint(ker)
+     }
+   }
+ })
> 
> local({
+   if(ALWAYS) {
+     ## unnormdensity
+     x <- rnorm(20) 
+     d0 <- unnormdensity(x, weights=rep(0, 20))
+     dneg <- unnormdensity(x, weights=c(-runif(19), 0))
+   }
+ })
> #
> # tests/NAinCov.R
> #
> # Testing the response to the presence of NA's in covariates
> #
> # $Revision: 1.9 $ $Date: 2023/11/05 01:45:36 $
> 
> if(FULLTEST) {
+ local({
+   #' quantile.ewcdf
+   f <- ewcdf(runif(100), runif(100))
+   qf <- quantile(f, probs=c(0.1, NA, 0.8))
+   #' quantile.density
+   f <- density(runif(100))
+   qf <- quantile(f, probs=c(0.1, NA, 0.8))
+ })
+ }
> 
> proc.time()
   user  system elapsed 
   0.12    0.04    0.15