Last updated on 2024-11-13 11:49:32 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.5-7 | 14.11 | 196.43 | 210.54 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.5-7 | 9.93 | 133.49 | 143.42 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.5-7 | 330.25 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.5-7 | 287.78 | ERROR | |||
| r-devel-windows-x86_64 | 1.5-7 | 15.00 | 187.00 | 202.00 | OK | |
| r-patched-linux-x86_64 | 1.5-7 | 14.70 | 182.50 | 197.20 | OK | |
| r-release-linux-x86_64 | 1.5-7 | 13.00 | 183.78 | 196.78 | 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 | 15.00 | 197.00 | 212.00 | 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 | 240.00 | 262.00 | OK |
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 2024-11-08 07:53:51.798834 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/30s]
Running ‘block.R’ [8s/10s]
Running ‘idw.R’ [9s/13s]
Running ‘interpolate.R’ [5s/11s]
Running ‘interpolateBlock.R’ [6s/11s]
Running ‘javaR.R’
Running ‘linearVariogram.R’
Running ‘minimal.R’
Running ‘transGaussian.R’ [5s/12s]
Running ‘unbiased.R’ [8s/11s]
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) (2024-11-07 r87302)
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_1.3-2 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_0.3.6 glue_1.8.0 Rcpp_1.0.13-1
[45] sf_1.0-19 tibble_3.2.1 tidyselect_1.2.1 xts_0.14.1
[49] compiler_4.5.0 evd_2.3-7.1 stars_0.6-7
>
>
> 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 2024-11-08 07:54:58.023848 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")$outputTable
R 2024-11-08 07:55:08.744328 interpolating 155 observations, 48 prediction locations
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: predLoess(object$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$zinc
> output = interpolate(meuse, meuse.grid, list(mean=T, variance=T),methodName = "transGaussian")
R 2024-11-08 07:55:41.130658 interpolating 155 observations, 3103 prediction locations
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: predLoess(object$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