Last updated on 2025-12-04 09:50:25 CET.
| Package | ERROR | OK |
|---|---|---|
| automap | 13 | |
| intamap | 13 | |
| intamapInteractive | 2 | 11 |
| MRG | 1 | 12 |
| 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/16s]
Running ‘biasCorr.R’ [10s/13s]
Running ‘findLocalBias.R’ [9s/11s]
Running ‘findRegionalBias.R’ [10s/14s]
Running ‘optimizingTest.R’ [89m/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)
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’ [10s/15s]
Running ‘biasCorr.R’ [10s/13s]
Running ‘findLocalBias.R’ [9s/12s]
Running ‘findRegionalBias.R’ [9s/11s]
Running ‘optimizingTest.R’ [89m/61m]
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: ERROR: 1, OK: 12
Version: 0.3.21
Check: tests
Result: ERROR
Running 'multiResGrid.R' [15s]
Running the tests in 'tests/multiResGrid.R' failed.
Complete output:
> s1 = Sys.time()
> library(MRG)
> library(tidyr)
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> # Neccessary to silence sf startup messages
> suppressMessages(library(sf))
> if (require(giscoR, quietly = TRUE)) {
+ # Read nuts borders, used for extracting smaller data set
+ borders = gisco_get_nuts(nuts_level = 2)
+ dkb = borders[borders$CNTR_CODE == "DK",] %>% st_transform(crs = 3035)
+ } else {
+ mrgpath = find.package("MRG")
+ load(file.path(mrgpath, "ex/dkb.rda"))
+ }
> #'
> # These are SYNTHETIC agricultural FSS data
> data(ifs_dk) # Census data
> ifs_weight = ifs_dk %>% dplyr::filter(Sample == 1) # Extract weighted subsample
>
> # Create spatial data
> ifg = fssgeo(ifs_dk, locAdj = "LL")
> fsg = fssgeo(ifs_weight, locAdj = "LL")
>
> ifg$dkb = st_join(ifg, dkb)$NUTS_ID
> ifg = ifg[!is.na(ifg$dkb) & ifg$dkb == "DK01",]
> fsg$dkb = st_join(fsg, dkb)$NUTS_ID
> fsg = fsg[!is.na(fsg$dkb) & fsg$dkb == "DK01",]
>
> ifg$ft = as.numeric(substr(ifg$FARMTYPE, 3, 4))^2
>
> s2 = Sys.time()
> #'
> # Set the base resolutions, and create a hierarchical list with gridded data
> ress = c(1,5,10,20,40)*1000
> # Gridding Utilized agricultural area (UAA), organic UAA and ft together
> ifl = gridData(ifg, c("UAA", "UAAXK0000_ORG", "ft"), res = ress)
Error: [rast] empty srs
In addition: Warning message:
PROJ: proj_create_from_database: Cannot find proj.db (GDAL error 1)
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 13
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