* using log directory ‘/data/gannet/ripley/R/packages/tests-devel/geostatsp.Rcheck’ * using R Under development (unstable) (2025-02-15 r87723) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (GCC) 14.2.1 20240912 (Red Hat 14.2.1-3) GNU Fortran (GCC) 14.2.1 20240912 (Red Hat 14.2.1-3) * running under: Fedora Linux 40 (Workstation Edition) * using session charset: UTF-8 * using option ‘--no-stop-on-test-error’ * checking for file ‘geostatsp/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘geostatsp’ version ‘2.0.8’ * checking package namespace information ... OK * checking package dependencies ... INFO Package suggested but not available for checking: ‘RandomFields’ * checking if this is a source package ... WARNING Subdirectory ‘geostatsp/src’ contains apparent object files/libraries Matrix_stubs_here.o gmrfEdge.o gmrfLik.o matern.o maternLogL.o maternLogLopt.o optimize.o register.o Object files/libraries should not be included in a source package. Subdirectory ‘src’ contains: symbols.rds These are unlikely file names for src files. * checking if there is a namespace ... OK * checking for executable files ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘geostatsp’ can be installed ... [62s/88s] OK See 'https://www.r-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/geostatsp-00install.html' for details. * used C compiler: ‘gcc (GCC) 14.2.1 20240912 (Red Hat 14.2.1-3)’ * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... 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[31m/22m] ERROR Running examples in ‘geostatsp-Ex.R’ failed The error most likely occurred in: > ### Name: RFsimulate > ### Title: Simulation of Random Fields > ### Aliases: RFsimulate modelRandomFields RFsimulate RFsimulate-methods > ### RFsimulate,ANY,SpatRaster-method RFsimulate,numeric,SpatRaster-method > ### RFsimulate,numeric,SpatVector-method > ### RFsimulate,RMmodel,SpatVector-method > ### RFsimulate,RMmodel,SpatRaster-method > ### RFsimulate,matrix,SpatRaster-method > ### RFsimulate,matrix,SpatVector-method RFsimulate,data.frame,ANY-method > ### Keywords: spatial > > ### ** Examples > > library('geostatsp') > > # exclude this line to use the RandomFields package > options(useRandomFields = FALSE) > > model1 <- c(var=5, range=1,shape=0.5) > > > myraster = rast(nrows=20,ncols=30,extent = ext(0,6,0,4), + crs="+proj=utm +zone=17 +datum=NAD27 +units=m +no_defs") > > set.seed(0) > > simu <- RFsimulate(model1, x=myraster, n=3) install the RandomFields package for faster simulations * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... [0m/90m] ERROR Running ‘RFsimulate.R’ [31m/22m] Running ‘krige.R’ [25s/33s] Running ‘lgcp.R’ [88s/91s] Running ‘lgm.R’ [71s/83s] Running ‘lgmRaster.R’ [31m/21m] Running ‘likfitLgm.R’ [28s/33s] Running ‘matern.R’ [15s/18s] Running ‘maternGmrfPrec.R’ [31m/21m] Running ‘profLlgm.R’ [0m/22m] Running ‘simLgcp.R’ Running the tests in ‘tests/RFsimulate.R’ failed. Complete output: > library("geostatsp") Loading required package: Matrix Loading required package: terra terra 1.8.21 > > model <- c(var=5, range=20,shape=0.5) > > # any old crs > theCrs = "+proj=utm +zone=17 +datum=NAD27 +units=m +no_defs" > > # don't test using the randomFields package, it's currently broken on some R builds > options(useRandomFields = FALSE) > > myraster = rast(nrows=20,ncols=20,extent = ext(100,110,100,110), + crs=theCrs) > > set.seed(0) > simu = RFsimulate(model = rbind(a=model, b=model+0.1), + x=myraster, n=4 + ) Running the tests in ‘tests/lgmRaster.R’ failed. Complete output: > #+ setup > library('geostatsp') Loading required package: Matrix Loading required package: terra terra 1.8.21 > #' > > #' # simulated data > > # exclude this line to use the RandomFields package > options(useRandomFields = FALSE) > > Ncell = 40 > > myRaster = squareRaster(ext(0,6000,0,6000), Ncell) > > myParam=c(oneminusar=0.1, conditionalVariance=2.5^2,shape=2) > myQ = maternGmrfPrec(myRaster, param=myParam) > attributes(myQ)$info$optimalShape shape variance range cellSize 4.092496 110.524266 900.000000 150.000000 > set.seed(0) > mySim = RFsimulate(attributes(myQ)$info$optimalShape, myRaster) install the RandomFields package for faster simulations Running the tests in ‘tests/maternGmrfPrec.R’ failed. Complete output: > library('geostatsp') Loading required package: Matrix Loading required package: terra terra 1.8.21 > matrix(NNmat(7, 7)[,25], 7, 7) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0 0 0 6 0 0 0 [2,] 0 0 5 4 5 0 0 [3,] 0 5 3 2 3 5 0 [4,] 6 4 2 1 2 4 6 [5,] 0 5 3 2 3 5 0 [6,] 0 0 5 4 5 0 0 [7,] 0 0 0 6 0 0 0 > > myr = squareRaster(ext(0,600,0,300), 60) > theNN = NNmat(myr) > > > params=c(range = 6*xres(myr), + cellSize=xres(myr), + shape=2, + variance=1600) > > > # precision matrix without adjusting for edge effects > system.time({precMat = maternGmrfPrec(N=theNN, param=params, + adjustEdges=FALSE)}) user system elapsed 0.484 0.012 0.608 > > > system.time({theNNadj = NNmat(N=myr, nearest=params['shape']+1, adjustEdges=TRUE)}) user system elapsed 0.225 0.021 0.324 > # and with the adjustment > system.time({precMatCorr =maternGmrfPrec(N=theNNadj, param=params, + adjustEdges=TRUE)}) Running the tests in ‘tests/profLlgm.R’ failed. Complete output: > > library('geostatsp') Loading required package: Matrix Loading required package: terra terra 1.8.21 > data('swissRain') > swissRain = unwrap(swissRain) > swissAltitude = unwrap(swissAltitude) > > Ncores = c(1,2)[1+(.Platform$OS.type=='unix')] > > > > sr2 = swissRain > sr2$elev = extract(swissAltitude, sr2) Warning message: [`[[<-`] only using the first column > swissFit = likfitLgm( + data=sr2, + formula=rain~ elev, + param=c(range=10000,shape=1,nugget=0,boxcox=0.5,anisoRatio=2,anisoAngleDegrees=45), + paramToEstimate = c("range",'anisoAngleDegrees','anisoRatio'), + reml=FALSE, + verbose=FALSE + ) > > > # calculate log-likelihood at the MLE's, but re-estimate variance > sl = loglikLgm( + swissFit$param[c('range','shape','boxcox', 'anisoRatio', 'anisoAngleRadians')], + data=sr2, + formula=rain~ elev, + reml=swissFit$model$reml) > > > # calculate log-likelihood without re-estimating variance > sigSqHat = attributes(sl)$totalVarHat > sl1 = loglikLgm( + c(attributes(sl)$param[ + c('boxcox','anisoRatio','anisoAngleRadians','shape', 'range')], + variance=sigSqHat), + data=sr2, + formula=rain~ elev, + reml=swissFit$model$reml) > > > # re=estimate the anisotropy parameters but not the range > sf2 = likfitLgm( + data=swissFit$data, + formula=swissFit$model$formula, + param= swissFit$param[c('range','nugget','shape','boxcox', 'anisoRatio', 'anisoAngleRadians')], + paramToEstimate = c('variance','anisoAngleRadians','anisoRatio'), + reml=swissFit$model$reml) > > # these should all be the same > as.numeric(sl1) [1] 644.4812 > as.numeric(sl) [1] 644.4812 > swissFit$optim$logL m2logL.ml logL.ml 644.4812 -322.2406 > sf2$optim$logL m2logL.ml logL.ml 644.4812 -322.2406 > > date() [1] "Sat Feb 15 16:36:24 2025" > x=profLlgm(swissFit, mc.cores=Ncores, + range=seq(15000, 55000 , len=12) + ) Execution halted * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... [506s/479s] OK * checking PDF version of manual ... [10s/14s] OK * checking HTML version of manual ... OK * checking for non-standard things in the check directory ... OK * checking for detritus in the temp directory ... OK * DONE Status: 2 ERRORs, 1 WARNING