Running 'RMH.R' [18s]
  Running 'Random.R' [162s]
Running the tests in 'tests/Random.R' failed.
Complete output:
  > #'
  > #'   Header for all (concatenated) test files
  > #'
  > #'   Require spatstat.random
  > #'   Obtain environment variable controlling tests.
  > #'
  > #'   $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $
  > 
  > require(spatstat.random)
  Loading required package: spatstat.random
  Loading required package: spatstat.data
  Loading required package: spatstat.geom
  spatstat.geom 3.2-9
  spatstat.random 3.2-3
  > 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/randoms.R
  > #'   Further tests of random generation code
  > #'  $Revision: 1.18 $ $Date: 2024/02/26 05:43:36 $
  > 
  > 
  > local({
  +   if(FULLTEST) {
  +     #' cases not covered in examples
  +     A <- runifdisc(6, nsim=2)
  +     A <- runifpoispp(5, nsim=2)
  +     A <- runifpoispp(0, nsim=2)
  +     A <- rSSI(0.05, 6, nsim=2)
  +     A <- rSSI(0.05, 10, win=square(c(-0.5, 1.5)), x.init=A[[1]], nsim=2)  
  +     A <- rstrat(nx=4, nsim=2)
  +     A <- rcell(square(1), nx=5, nsim=2)
  +   }
  +   if(ALWAYS) { # involves C code etc
  +     A <- rthin(cells, P=0.5, nsim=2)
  +     A <- rthin(cells, runif(42))
  +     A <- rthin(cells[FALSE], P=0.5, nsim=2)
  +   }
  +   f <- function(x,y) { 10*x }
  +   Z <- as.im(f, square(1))
  +   if(ALWAYS) {
  +     A <- rpoint(n=6, f=f, fmax=10, nsim=2)
  +     A <- rpoint(n=6, f=Z, fmax=10, nsim=2)
  +     A <- rpoint(n=0, f=f, fmax=10, nsim=2)
  +     A <- rpoint(n=0, f=Z, fmax=10, nsim=2)
  + 
  +     op <- spatstat.options(fastpois=FALSE)
  +     A <- runifpoispp(5, nsim=2)
  +     A <- rpoispp(Z)
  +     spatstat.options(op)
  +   }
  +   if(FULLTEST) {
  +     b3 <- box3(c(0,1))
  +     b4 <- boxx(c(0,1), c(0,1), c(0,1), c(0,1))
  +     b5 <- c(0, 2, 0, 2)
  +     X <- rMaternInhibition(2, kappa=20, r=0.1, win=b3)
  +     Y <- rMaternInhibition(2, kappa=20, r=0.1, win=b4)
  +     Y <- rMaternInhibition(2, kappa=20, r=0.1, win=b5, nsim=2)
  + 
  +     X <- rSSI(0.05, 6)
  +     Y <- rSSI(0.05, 6, x.init=X) # no extra points
  + 
  +     Z <- rlabel(finpines)
  +   }
  + 
  +   f1 <- function(x,y){(x^2 + y^3)/10}
  +   f2 <- function(x,y){(x^3 + y^2)/10}
  +   ZZ <- solist(A=as.im(f1, letterR),
  +                B=as.im(f2, letterR))
  +   g <- function(x,y,m){(10+as.integer(m)) * (x^2 + y^3)}
  +   if(FULLTEST) {
  +     XX <- rmpoispp(ZZ, nsim=3)
  +     YY <- rmpoint(10, f=ZZ, nsim=3)
  +     UU <- rmpoint(10, f=ZZ[[1]], types=letters[1:2])
  +     VV <- rpoint.multi(10, f=g,
  +                        marks=factor(sample(letters[1:3], 10, replace=TRUE)),
  +                        nsim=3)
  +   }
  +   if(ALWAYS) { # depends on C code
  +     L <- edges(letterR)
  +     E <- runifpoisppOnLines(5, L)
  +     G <- rpoisppOnLines(ZZ, L)
  +     G2 <- rpoisppOnLines(list(A=f1, B=f2), L, lmax=max(sapply(ZZ, max)))
  +   }
  + 
  +   if(FULLTEST) {
  +     #' cluster models + bells + whistles
  +     X <- rThomas(10, 0.2, 5, saveLambda=TRUE)
  +     if(is.null(attr(X, "Lambda")))
  +       stop("rThomas did not save Lambda image")
  +     Y <- rThomas(0, 0.2, 5, saveLambda=TRUE)
  +     if(is.null(attr(Y, "Lambda")))
  +       stop("rThomas did not save Lambda image when kappa=0")
  +     X <- rMatClust(10, 0.05, 4, saveLambda=TRUE)
  +     X <- rCauchy(30, 0.01, 5, saveLambda=TRUE)
  +     X <- rVarGamma(30, 2, 5, nu=0.02, saveLambda=TRUE)
  +     Z <- as.im(function(x,y){ 5 * exp(2 * x - 1) }, owin())
  +     Y <- rThomas(10, 0.2, Z, saveLambda=TRUE)
  +     Y <- rMatClust(10, 0.05, Z, saveLambda=TRUE)
  +     Y <- rCauchy(30, 0.01, Z, saveLambda=TRUE)
  +     Y <- rVarGamma(30, 2, Z, nu=0.02, saveLambda=TRUE)
  +     #' inhomogeneous
  +     Moo <- as.im(function(x,y) { 10 * x }, unit.square())
  +     X <- rMatClust(10, 0.2, Moo)
  +   }
  + 
  +   if(FULLTEST) {
  +     #' perfect simulation code infrastructure
  +     expandwinPerfect(letterR, 2, 3)
  + 
  +     #' trivial cases of random generators for ppx
  +     B4 <- boxx(0:1, 0:1, 0:1, 0:1)
  +     Z0 <- runifpointx(0, domain=B4, nsim=2)
  +     Z1 <- runifpointx(1, domain=B4, nsim=2)
  +   }
  + 
  + })
  > 
  > local({
  +   if(ALWAYS) {
  +     #' Bug in rLGCP spotted by Tilman Davies
  +     X <- rLGCP("matern", function(x,y) { 1 - 0.4* y },
  +                var=2, scale=0.7, nu=0.5, win = square(10),
  +                dimyx=c(32,64))
  +   }
  +   if(FULLTEST) {
  +     ## Bug in rGRFcircembed
  +     ## when handling incompatible data for 'mu' and 'win'
  +     win <- owin(c(0, 3), c(0, 3))
  +     npix <- 300
  +     spatstat.options(npixel = npix)
  +     beta0 <- 3
  +     beta1 <- 0
  +     sigma2x <- 0.2
  +     range <- 1.2
  +     nu <- 1
  +     set.seed(7)
  +     x0 <- seq(0, 3, length=npix)
  +     y0 <- seq(0, 3, length=npix)
  +     gridcov <- outer(x0, y0, function(x,y) cos(x) - sin(y - 2))
  +     MU <- im(beta0 + beta1 * gridcov, xcol = x0, yrow = y0)
  +     lg.s.c <- rLGCP('matern', mu=MU,
  +                     var = sigma2x, scale = range / sqrt(8), 
  +                     nu = 1, win = win)
  +   }
  + })
  > 
  > reset.spatstat.options()
  > 
  > 
  > 
  > proc.time()
     user  system elapsed 
     1.40    0.17    1.51