CRAN Package Check Results for Package intamap

Last updated on 2024-09-27 17:51:21 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.5-7 14.48 192.42 206.90 OK
r-devel-linux-x86_64-debian-gcc 1.5-7 9.98 134.08 144.06 OK
r-devel-linux-x86_64-fedora-clang 1.5-7 325.30 OK
r-devel-linux-x86_64-fedora-gcc 1.5-7 288.52 ERROR
r-devel-windows-x86_64 1.5-7 16.00 188.00 204.00 OK
r-patched-linux-x86_64 1.5-7 14.40 181.93 196.33 OK
r-release-linux-x86_64 1.5-7 13.17 183.00 196.17 OK
r-release-macos-arm64 1.5-7 86.00 OK
r-release-macos-x86_64 1.5-7 137.00 OK
r-release-windows-x86_64 1.5-7 16.00 187.00 203.00 OK
r-oldrel-macos-arm64 1.5-7 140.00 OK
r-oldrel-macos-x86_64 1.5-7 207.00 OK
r-oldrel-windows-x86_64 1.5-7 22.00 239.00 261.00 OK

Check Details

Version: 1.5-7
Check: examples
Result: ERROR Running examples in ‘intamap-Ex.R’ failed The error most likely occurred in: > ### Name: plotIntamap > ### Title: plot intamap objects > ### Aliases: plotIntamap plot.default plot.copula plot.idw plot.automap > ### plot.linearVariogram plot.transGaussian plot.yamamoto > ### Keywords: spatial > > ### ** Examples > > data(meuse) > meuse$value = log(meuse$zinc) > data(meuse.grid) > coordinates(meuse) = ~x+y > coordinates(meuse.grid) = ~x+y > object = interpolate(meuse, meuse.grid, + outputWhat = list(mean = TRUE, variance = TRUE, + excprob = 7, excprob = 8, quantile = 0.9, quantile = 0.95), + methodName = "automap") R 2024-09-24 06:45:30.588128 interpolating 155 observations, 3103 prediction locations Warning in predictTime(nObs = dim(observations)[1], nPred = nPred, formulaString = formulaString, : using standard model for estimating time. For better platform spesific predictions, please run timeModels <- generateTimeModels() and save the workspace *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)), newdata, na.action = na.action)) else as.matrix(newdata), object$s, object$weights, object$robust, op$span, op$degree, op$normalize, op$parametric, op$drop.square, op$surface, op$cell, op$family, object$kd, object$divisor, se = se) 2: predict.loess(eModels, data.frame(nObs = nObs), se = TRUE) 3: predict(eModels, data.frame(nObs = nObs), se = TRUE) 4: predictTime(nObs = dim(observations)[1], nPred = nPred, formulaString = formulaString, class = methodName, outputWhat = outputWhat, FUN = "spatialPredict") 5: interpolate(meuse, meuse.grid, outputWhat = list(mean = TRUE, variance = TRUE, excprob = 7, excprob = 8, quantile = 0.9, quantile = 0.95), methodName = "automap") An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.5-7
Check: tests
Result: ERROR Running ‘anisotropyTest.R’ [22s/33s] Running ‘block.R’ [8s/13s] Running ‘idw.R’ [9s/12s] Running ‘interpolate.R’ [5s/14s] Running ‘interpolateBlock.R’ [5s/12s] Running ‘javaR.R’ [5s/12s] Running ‘linearVariogram.R’ [6s/13s] Running ‘minimal.R’ [5s/14s] Running ‘transGaussian.R’ [5s/17s] Running ‘unbiased.R’ [7s/10s] Running the tests in ‘tests/interpolate.R’ failed. Complete output: > options(error = recover) > set.seed(15331) > library(intamap) Loading required package: sp > library(automap) > library(gstat) > library(psgp) > #loadMeuse() > > sessionInfo() R Under development (unstable) (2024-09-23 r87189) Platform: x86_64-pc-linux-gnu Running under: Fedora Linux 36 (Workstation Edition) Matrix products: default BLAS: /data/gannet/ripley/R/R-devel/lib/libRblas.so LAPACK: /usr/lib64/liblapack.so.3.10.1 locale: [1] LC_CTYPE=en_GB.utf8 LC_NUMERIC=C [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=C [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C time zone: Europe/London tzcode source: system (glibc) attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] psgp_0.3-21 gstat_2.1-2 automap_1.1-12 intamap_1.5-7 sp_2.1-4 loaded via a namespace (and not attached): [1] utf8_1.2.4 generics_0.1.3 class_7.3-22 KernSmooth_2.23-24 [5] lattice_0.22-6 magrittr_2.0.3 grid_4.5.0 iterators_1.0.14 [9] mvtnorm_1.3-1 foreach_1.5.2 doParallel_1.0.17 plyr_1.8.9 [13] e1071_1.7-16 reshape_0.8.9 DBI_1.2.3 fansi_1.0.6 [17] scales_1.3.0 codetools_0.2-20 abind_1.4-8 cli_3.6.3 [21] rlang_1.1.4 units_0.8-5 munsell_0.5.1 intervals_0.15.5 [25] FNN_1.1.4.1 tools_4.5.0 parallel_4.5.0 dplyr_1.1.4 [29] colorspace_2.1-1 ggplot2_3.5.1 spacetime_1.3-2 vctrs_0.6.5 [33] MBA_0.1-2 R6_2.5.1 zoo_1.8-12 proxy_0.4-27 [37] lifecycle_1.0.4 classInt_0.4-10 MASS_7.3-61 pkgconfig_2.0.3 [41] pillar_1.9.0 gtable_0.3.5 glue_1.7.0 Rcpp_1.0.13 [45] sf_1.0-17 tibble_3.2.1 tidyselect_1.2.1 xts_0.14.0 [49] compiler_4.5.0 evd_2.3-7.1 stars_0.6-6 > > > crs = CRS("epsg:28992") > data("meuse") > coordinates(meuse) <- ~x+y > proj4string(meuse) <- crs > data("meuse.grid") > coordinates(meuse.grid) <- ~x+y > gridded(meuse.grid) <- TRUE > proj4string(meuse.grid) <- crs > > meuse$value = log(meuse$zinc) > meuse.grid = meuse.grid[sample(1:dim(meuse.grid)[1], 100),] > output = interpolate(meuse, meuse.grid, list(mean=T, variance=T, nsim = 5), methodName = "automap") R 2024-09-24 06:46:45.555843 interpolating 155 observations, 100 prediction locations *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)), newdata, na.action = na.action)) else as.matrix(newdata), object$s, object$weights, object$robust, op$span, op$degree, op$normalize, op$parametric, op$drop.square, op$surface, op$cell, op$family, object$kd, object$divisor, se = se) 2: predict.loess(eModels, data.frame(nObs = nObs), se = TRUE) 3: predict(eModels, data.frame(nObs = nObs), se = TRUE) 4: predictTime(nObs = dim(observations)[1], nPred = nPred, formulaString = formulaString, class = methodName, outputWhat = outputWhat, FUN = "spatialPredict") 5: interpolate(meuse, meuse.grid, list(mean = T, variance = T, nsim = 5), methodName = "automap") An irrecoverable exception occurred. R is aborting now ... Running the tests in ‘tests/interpolateBlock.R’ failed. Complete output: > library(intamap) Loading required package: sp > data(meuse) > coordinates(meuse) = ~x+y > data(meuse.grid) > coordinates(meuse.grid) = ~x+y > set.seed(13531) > > predictionLocations = spsample(meuse,50,"regular") > gridded(predictionLocations) = TRUE > cs = predictionLocations@grid@cellsize[1]/2 > meuse$value = log(meuse$zinc) > > outputWhat = list(mean=TRUE,variance=TRUE,quantile=0.025,quantile=0.0975) > res1 = interpolateBlock(meuse,predictionLocations,outputWhat,methodName = "automap")$outputTable R 2024-09-24 06:46:58.201227 interpolating 155 observations, 48 prediction locations *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)), newdata, na.action = na.action)) else as.matrix(newdata), object$s, object$weights, object$robust, op$span, op$degree, op$normalize, op$parametric, op$drop.square, op$surface, op$cell, op$family, object$kd, object$divisor, se = se) 2: predict.loess(eModels, data.frame(nObs = nObs), se = TRUE) 3: predict(eModels, data.frame(nObs = nObs), se = TRUE) 4: predictTime(nObs = nObs, nPred = nPred, formulaString = formulaString, class = methodName, outputWhat = outputWhat, FUN = "spatialPredict") 5: interpolateBlock(meuse, predictionLocations, outputWhat, methodName = "automap") An irrecoverable exception occurred. R is aborting now ... Running the tests in ‘tests/transGaussian.R’ failed. Complete output: > set.seed(15331) > library(intamap) Loading required package: sp > data(meuse) > data(meuse.grid) > coordinates(meuse) = ~x+y > coordinates(meuse.grid) = ~x+y > > meuse$value=meuse$zinc > output = interpolate(meuse, meuse.grid, list(mean=T, variance=T),methodName = "transGaussian") R 2024-09-24 06:47:52.669213 interpolating 155 observations, 3103 prediction locations *** caught segfault *** address 0x1, cause 'memory not mapped' Traceback: 1: predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)), newdata, na.action = na.action)) else as.matrix(newdata), object$s, object$weights, object$robust, op$span, op$degree, op$normalize, op$parametric, op$drop.square, op$surface, op$cell, op$family, object$kd, object$divisor, se = se) 2: predict.loess(eModels, data.frame(nObs = nObs), se = TRUE) 3: predict(eModels, data.frame(nObs = nObs), se = TRUE) 4: predictTime(nObs = dim(observations)[1], nPred = nPred, formulaString = formulaString, class = methodName, outputWhat = outputWhat, FUN = "spatialPredict") 5: interpolate(meuse, meuse.grid, list(mean = T, variance = T), methodName = "transGaussian") An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-gcc