CRAN Package Check Results for Package intamapInteractive

Last updated on 2025-03-11 12:52:56 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2-6 17.71 181.71 199.42 OK
r-devel-linux-x86_64-debian-gcc 1.2-6 13.15 123.03 136.18 OK
r-devel-linux-x86_64-fedora-clang 1.2-6 346.37 OK
r-devel-linux-x86_64-fedora-gcc 1.2-6 4176.34 ERROR
r-devel-macos-arm64 1.2-6 81.00 OK
r-devel-macos-x86_64 1.2-6 212.00 OK
r-devel-windows-x86_64 1.2-6 21.00 162.00 183.00 OK
r-patched-linux-x86_64 1.2-6 17.62 169.33 186.95 OK
r-release-linux-x86_64 1.2-6 16.68 167.94 184.62 OK
r-release-macos-arm64 1.2-6 78.00 OK
r-release-macos-x86_64 1.2-6 121.00 OK
r-release-windows-x86_64 1.2-6 21.00 160.00 181.00 OK
r-oldrel-macos-arm64 1.2-6 OK
r-oldrel-macos-x86_64 1.2-6 177.00 OK
r-oldrel-windows-x86_64 1.2-6 26.00 210.00 236.00 OK

Check Details

Version: 1.2-6
Check: tests
Result: ERROR Running ‘anisotropyChoice.R’ [9s/14s] Running ‘biasCorr.R’ [9s/13s] Running ‘findLocalBias.R’ [9s/11s] Running ‘findRegionalBias.R’ [9s/13s] Running ‘optimizingTest.R’ [65m/57m] 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

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