R Under development (unstable) (2024-03-21 r86166 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > #' > #' 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.geom spatstat.geom 3.2-9 Loading required package: spatstat.random spatstat.random 3.2-3 Loading required package: spatstat.explore Loading required package: nlme spatstat.explore 3.2-7 Loading required package: rpart spatstat.model 3.2-11 > 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/percy.R > ## > ## Tests of Percus-Yevick approximations > ## > ## $Revision: 1.3 $ $Date: 2020/04/30 05:23:52 $ > > if(FULLTEST) { + local({ + fit <- ppm(swedishpines ~1, DiggleGatesStibbard(6)) + K <- Kmodel(fit) + }) + } > > ## > ## tests/pixelgripes.R > ## Problems related to pixellation of windows > ## > ## $Revision: 1.8 $ $Date: 2022/10/23 06:21:10 $ > > if(FULLTEST) { + local({ + + ## From Philipp Hunziker: bug in rNeymanScott (etc) + ## Create an irregular window + PM <- matrix(c(1,0,0.5,1,0,0), 3, 2, byrow=TRUE) + P <- owin(poly=PM) + ## Generate Matern points + X <- rMatClust(50, 0.05, 5, win=P) + ## Some distance function as a covariate + distorigin <- function(x, y) { sqrt(x^2 + y^2) } + ## No covariates: works fine + fit0 <- kppm(X ~ 1, clusters="MatClust") + Y0 <- simulate(fit0, retry=0) + ## Covariates: Simulation fails + fit1 <- kppm(X ~ distorigin, clusters="MatClust") + Y1 <- simulate(fit1, retry=0) + + }) + } > > proc.time() user system elapsed 1.06 0.18 1.23