Last updated on 2025-10-10 13:50:01 CEST.
| Package | ERROR | OK |
|---|---|---|
| automap | 13 | |
| intamap | 13 | |
| intamapInteractive | 2 | 11 |
| MRG | 13 | |
| rtop | 13 |
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: ERROR: 2, OK: 11
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘anisotropyChoice.R’ [10s/20s]
Running ‘biasCorr.R’ [10s/14s]
Running ‘findLocalBias.R’ [9s/16s]
Running ‘findRegionalBias.R’ [10s/18s]
Running ‘optimizingTest.R’ [90m/79m]
Running the tests in ‘tests/optimizingTest.R’ failed.
Complete output:
> options(error = recover)
> #test = TRUE
> test = FALSE
> mantest = FALSE
> set.seed(1)
> library(intamapInteractive)
Loading required package: intamap
Loading required package: sp
> library(gstat)
> #require(maptools)
> # for SIC2004 dataset
> data(sic2004)
> coordinates(sic.val) = ~x+y
> observations = sic.val["dayx"]
> coordinates(sic.grid)=~x+y
> predGrid = sic.grid
>
> #Finding the polygon for the candidate locations
> bb = bbox(predGrid)
> boun = SpatialPoints(data.frame(x=c(bb[1,1],bb[1,2],bb[1,2],bb[1,1],bb[1,1]),
+ y=c(bb[2,1],bb[2,1],bb[2,2],bb[2,2],bb[2,1])))
> Srl = Polygons(list(Polygon(boun)),ID = as.character(1))
> candidates = SpatialPolygonsDataFrame(SpatialPolygons(list(Srl)),
+ data = data.frame(ID=1))
>
> # Limits the number of prediction locations to have faster UK
> # computations
> nGrid = dim(coordinates(predGrid))[1]
> predGrid = predGrid[sample(seq(1,nGrid),1000),]
> # Fits the variogram model (using function fit.variogram from package
> # gstat)
> model = fit.variogram(variogram(dayx~x+y, sic.val), vgm(50, "Sph", 250000, 250))
> #plot(variogram(dayx~x+y, sic.val), model=model)
> # Computes the Mukv of the current network
> initMukv <- calculateMukv(observations, predGrid, model, formulaString = dayx~x+y)
OMP: Warning #96: Cannot form a team with 24 threads, using 2 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘anisotropyChoice.R’ [9s/13s]
Running ‘biasCorr.R’ [10s/16s]
Running ‘findLocalBias.R’ [9s/12s]
Running ‘findRegionalBias.R’ [9s/14s]
Running ‘optimizingTest.R’ [89m/62m]
Running the tests in ‘tests/optimizingTest.R’ failed.
Complete output:
> options(error = recover)
> #test = TRUE
> test = FALSE
> mantest = FALSE
> set.seed(1)
> library(intamapInteractive)
Loading required package: intamap
Loading required package: sp
> library(gstat)
> #require(maptools)
> # for SIC2004 dataset
> data(sic2004)
> coordinates(sic.val) = ~x+y
> observations = sic.val["dayx"]
> coordinates(sic.grid)=~x+y
> predGrid = sic.grid
>
> #Finding the polygon for the candidate locations
> bb = bbox(predGrid)
> boun = SpatialPoints(data.frame(x=c(bb[1,1],bb[1,2],bb[1,2],bb[1,1],bb[1,1]),
+ y=c(bb[2,1],bb[2,1],bb[2,2],bb[2,2],bb[2,1])))
> Srl = Polygons(list(Polygon(boun)),ID = as.character(1))
> candidates = SpatialPolygonsDataFrame(SpatialPolygons(list(Srl)),
+ data = data.frame(ID=1))
>
> # Limits the number of prediction locations to have faster UK
> # computations
> nGrid = dim(coordinates(predGrid))[1]
> predGrid = predGrid[sample(seq(1,nGrid),1000),]
> # Fits the variogram model (using function fit.variogram from package
> # gstat)
> model = fit.variogram(variogram(dayx~x+y, sic.val), vgm(50, "Sph", 250000, 250))
> #plot(variogram(dayx~x+y, sic.val), model=model)
> # Computes the Mukv of the current network
> initMukv <- calculateMukv(observations, predGrid, model, formulaString = dayx~x+y)
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: OK: 13
Current CRAN status: OK: 13
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