Last updated on 2025-12-02 23:50:23 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.3 | 18.93 | 658.01 | 676.94 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.0.3 | 11.76 | 452.18 | 463.94 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.0.3 | 43.00 | 1041.95 | 1084.95 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.0.3 | 51.00 | 1075.55 | 1126.55 | OK | |
| r-devel-windows-x86_64 | 1.0.3 | 23.00 | 863.00 | 886.00 | ERROR | |
| r-patched-linux-x86_64 | 1.0.3 | 19.20 | 542.39 | 561.59 | ERROR | |
| r-release-linux-x86_64 | 1.0.3 | 17.28 | 641.45 | 658.73 | OK | |
| r-release-macos-arm64 | 1.0.3 | OK | ||||
| r-release-macos-x86_64 | 1.0.3 | 15.00 | 680.00 | 695.00 | OK | |
| r-release-windows-x86_64 | 1.0.3 | 19.00 | 616.00 | 635.00 | OK | |
| r-oldrel-macos-arm64 | 1.0.3 | OK | ||||
| r-oldrel-macos-x86_64 | 1.0.3 | 12.00 | 393.00 | 405.00 | OK | |
| r-oldrel-windows-x86_64 | 1.0.3 | 27.00 | 831.00 | 858.00 | ERROR |
Version: 1.0.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building 'cast01-CAST-intro.Rmd' using rmarkdown
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_elev.zip'
Content type 'application/zip' length 1332437 bytes (1.3 MB)
==================================================
downloaded 1.3 MB
--- finished re-building 'cast01-CAST-intro.Rmd'
--- re-building 'cast02-plotgeodist.Rmd' using rmarkdown
Quitting from cast02-plotgeodist.Rmd:243-248 [unnamed-chunk-17]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `names(predictors_global) <- c(paste0("bio_", 1:19))`:
! attempt to set an attribute on NULL
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'cast02-plotgeodist.Rmd' failed with diagnostics:
attempt to set an attribute on NULL
--- failed re-building 'cast02-plotgeodist.Rmd'
--- re-building 'cast03-CV.Rmd' using rmarkdown
--- finished re-building 'cast03-CV.Rmd'
--- re-building 'cast04-AOA-tutorial.Rmd' using rmarkdown
--- finished re-building 'cast04-AOA-tutorial.Rmd'
--- re-building 'cast05-parallel.Rmd' using rmarkdown
--- finished re-building 'cast05-parallel.Rmd'
SUMMARY: processing the following file failed:
'cast02-plotgeodist.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 1.0.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘cast01-CAST-intro.Rmd’ using rmarkdown
CAST package:CAST R Documentation
'_<08>c_<08>a_<08>r_<08>e_<08>t' _<08>A_<08>p_<08>p_<08>l_<08>i_<08>c_<08>a_<08>t_<08>i_<08>o_<08>n_<08>s _<08>f_<08>o_<08>r _<08>S_<08>p_<08>a_<08>t_<08>i_<08>a_<08>l-_<08>T_<08>e_<08>m_<08>p_<08>o_<08>r_<08>a_<08>l _<08>M_<08>o_<08>d_<08>e_<08>l_<08>s
_<08>D_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>o_<08>n:
Supporting functionality to run 'caret' with spatial or
spatial-temporal data. 'caret' is a frequently used package for
model training and prediction using machine learning. CAST
includes functions to improve spatial-temporal modelling tasks
using 'caret'. It includes the newly suggested 'Nearest neighbor
distance matching' cross-validation to estimate the performance of
spatial prediction models and allows for spatial variable
selection to selects suitable predictor variables in view to their
contribution to the spatial model performance. CAST further
includes functionality to estimate the (spatial) area of
applicability of prediction models by analysing the similarity
between new data and training data. Methods are described in Meyer
et al. (2018); Meyer et al. (2019); Meyer and Pebesma (2021); Milà
et al. (2022); Meyer and Pebesma (2022); Linnenbrink et al.
(2023). The package is described in detail in Meyer et al. (2024).
_<08>D_<08>e_<08>t_<08>a_<08>i_<08>l_<08>s:
'caret' Applications for Spatio-Temporal models
_<08>A_<08>u_<08>t_<08>h_<08>o_<08>r(_<08>s):
Hanna Meyer, Carles Milà, Marvin Ludwig, Jan Linnenbrink, Fabian
Schumacher
_<08>R_<08>e_<08>f_<08>e_<08>r_<08>e_<08>n_<08>c_<08>e_<08>s:
• Meyer, H., Ludwig, L., Milà, C., Linnenbrink, J., Schumacher,
F. (2024): The CAST package for training and assessment of
spatial prediction models in R. arXiv,
https://doi.org/10.48550/arXiv.2404.06978.
• Linnenbrink, J., Milà, C., Ludwig, M., and Meyer, H.: kNNDM:
k-fold Nearest Neighbour Distance Matching Cross-Validation
for map accuracy estimation, EGUsphere [preprint],
https://doi.org/10.5194/egusphere-2023-1308, 2023.
• Milà, C., Mateu, J., Pebesma, E., Meyer, H. (2022): Nearest
Neighbour Distance Matching Leave-One-Out Cross-Validation
for map validation. Methods in Ecology and Evolution 00, 1–
13.
• Meyer, H., Pebesma, E. (2022): Machine learning-based global
maps of ecological variables and the challenge of assessing
them. Nature Communications. 13.
• Meyer, H., Pebesma, E. (2021): Predicting into unknown space?
Estimating the area of applicability of spatial prediction
models. Methods in Ecology and Evolution. 12, 1620– 1633.
• Meyer, H., Reudenbach, C., Wöllauer, S., Nauss, T. (2019):
Importance of spatial predictor variable selection in machine
learning applications - Moving from data reproduction to
spatial prediction. Ecological Modelling. 411, 108815.
• Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., Nauß, T.
(2018): Improving performance of spatio-temporal machine
learning models using forward feature selection and
target-oriented validation. Environmental Modelling &
Software 101: 1-9.
_<08>S_<08>e_<08>e _<08>A_<08>l_<08>s_<08>o:
Useful links:
• <https://github.com/HannaMeyer/CAST>
• <https://hannameyer.github.io/CAST/>
• Report bugs at <https://github.com/HannaMeyer/CAST/issues/>
Quitting from cast01-CAST-intro.Rmd:51-57 [unnamed-chunk-3]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `library()`:
! there is no package called 'tmap'
---
Backtrace:
▆
1. └─base::library(tmap)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'cast01-CAST-intro.Rmd' failed with diagnostics:
there is no package called 'tmap'
--- failed re-building ‘cast01-CAST-intro.Rmd’
--- re-building ‘cast02-plotgeodist.Rmd’ using rmarkdown
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast02-plotgeodist.Rmd’
--- re-building ‘cast03-CV.Rmd’ using rmarkdown
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast03-CV.Rmd’
--- re-building ‘cast04-AOA-tutorial.Rmd’ using rmarkdown
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast04-AOA-tutorial.Rmd’
--- re-building ‘cast05-parallel.Rmd’ using rmarkdown
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast05-parallel.Rmd’
SUMMARY: processing the following file failed:
‘cast01-CAST-intro.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-patched-linux-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running 'testthat.R' [209s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(CAST)
>
> test_check("CAST")
Loading required package: ggplot2
Loading required package: lattice
note: variables were not weighted either because no weights or model were given,
no variable importance could be retrieved from the given model, or the model has a single feature.
Check caret::varImp(model)
note: No model and no CV folds were given. The DI threshold is therefore based on all training data
note: variables were not weighted either because no weights or model were given,
no variable importance could be retrieved from the given model, or the model has a single feature.
Check caret::varImp(model)
note: No model and no CV folds were given. The DI threshold is therefore based on all training data
[1] "model using Sepal.Length,Sepal.Width will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 8"
[1] "model using Sepal.Length,Petal.Length will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 7"
[1] "model using Sepal.Length,Petal.Width will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 6"
[1] "model using Sepal.Width,Petal.Length will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 5"
[1] "model using Sepal.Width,Petal.Width will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 4"
[1] "model using Petal.Length,Petal.Width will be trained now..."
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
[1] "maximum number of models that still need to be trained: 3"
[1] "vars selected: Petal.Length,Petal.Width with Accuracy 0.953"
[1] "model using additional variable Sepal.Length will be trained now..."
note: only 2 unique complexity parameters in default grid. Truncating the grid to 2 .
[1] "maximum number of models that still need to be trained: 2"
[1] "model using additional variable Sepal.Width will be trained now..."
note: only 2 unique complexity parameters in default grid. Truncating the grid to 2 .
[1] "maximum number of models that still need to be trained: 1"
[1] "vars selected: Petal.Length,Petal.Width,Sepal.Width with Accuracy 0.954"
[1] "model using additional variable Sepal.Length will be trained now..."
[1] "maximum number of models that still need to be trained: 0"
[1] "vars selected: Petal.Length,Petal.Width,Sepal.Width with Accuracy 0.954"
Spherical geometry (s2) switched off
Spherical geometry (s2) switched on
Spherical geometry (s2) switched off
Saving _problems/test-geodist-38.R
Spherical geometry (s2) switched on
Saving _problems/test-geodist-85.R
Saving _problems/test-geodist-107.R
Saving _problems/test-geodist-125.R
Saving _problems/test-geodist-145.R
Spherical geometry (s2) switched off
Spherical geometry (s2) switched on
Saving _problems/test-geodist-188.R
variable(s) 'fct' is (are) treated as categorical variables
Spherical geometry (s2) switched off
Saving _problems/test-geodist-242.R
time variable that has been selected: Date
time variable that has been selected: Date
time variable that has been selected: Date
note: only 2 unique complexity parameters in default grid. Truncating the grid to 2 .
note: only 2 unique complexity parameters in default grid. Truncating the grid to 2 .
Spherical geometry (s2) switched on
although coordinates are longitude/latitude, st_sample assumes that they are
planar
although coordinates are longitude/latitude, st_sample assumes that they are
planar
1000 prediction points are sampled from the modeldomain
Gij <= Gj; a random CV assignment is returned
1000 prediction points are sampled from the modeldomain
Gij <= Gj; a random CV assignment is returned
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
Gij <= Gj; a random CV assignment is returned
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
Gij <= Gj; a random CV assignment is returned
1000 prediction points are sampled from the modeldomain
although coordinates are longitude/latitude, st_sample assumes that they are
planar
predictor values are extracted for prediction points
variable(s) 'fct' is (are) treated as categorical variables
some prediction points contain NAs, which will be removed
Gij <= Gj; a random CV assignment is returned
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
variable(s) 'fct' is (are) treated as categorical variables
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
variable(s) 'fct' is (are) treated as categorical variables
1000 prediction points are sampled from the modeldomain
although coordinates are longitude/latitude, st_sample assumes that they are
planar
predictor values are extracted for prediction points
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
1000 prediction points are sampled from the modeldomain
predictor values are extracted for prediction points
1000 prediction points are sampled from the modeldomain
1000 prediction points are sampled from the modeldomain
1000 prediction points are sampled from the modeldomain
1000 prediction points are sampled from the modeldomain
[ FAIL 7 | WARN 11 | SKIP 10 | PASS 100 ]
══ Skipped tests (10) ══════════════════════════════════════════════════════════
• On CRAN (10): 'test-errorProfiles.R:3:3', 'test-errorProfiles.R:36:3',
'test-errorProfiles.R:67:3', 'test-fss.R:3:3', 'test-fss.R:27:3',
'test-fss.R:47:3', 'test-fss.R:70:3', 'test-fss.R:120:5', 'test-fss.R:135:5',
'test-fss.R:152:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-geodist.R:34:3'): geodist works with points and polygon in feature space ──
Error: [project] cannot get output boundaries for the target crs
Backtrace:
▆
1. └─CAST::geodist(...) at test-geodist.R:34:3
2. └─CAST:::sampleFromArea(...)
3. ├─terra::project(modeldomain, "epsg:4326")
4. └─terra::project(modeldomain, "epsg:4326")
5. └─terra (local) .local(x, ...)
6. └─terra:::messages(x, "project")
7. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:84:3'): geodist works with points and preddata in feature space ──
Error: [rast] empty srs
Backtrace:
▆
1. ├─terra::rast(...) at test-geodist.R:84:3
2. └─terra::rast(...)
3. └─terra (local) .local(x = x, ...)
4. └─terra:::new_rast(...)
5. └─terra:::messages(r, "rast")
6. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:106:3'): geodist works with points and raster in geographic space ──
Error: [rast] empty srs
Backtrace:
▆
1. ├─terra::rast(...) at test-geodist.R:106:3
2. └─terra::rast(...)
3. └─terra (local) .local(x = x, ...)
4. └─terra:::new_rast(...)
5. └─terra:::messages(r, "rast")
6. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:124:3'): geodist works with points and raster in feature space ──
Error: [rast] empty srs
Backtrace:
▆
1. ├─terra::rast(...) at test-geodist.R:124:3
2. └─terra::rast(...)
3. └─terra (local) .local(x = x, ...)
4. └─terra:::new_rast(...)
5. └─terra:::messages(r, "rast")
6. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:143:3'): geodist works with points and stars raster in geographic space ──
Error: [rast] empty srs
Backtrace:
▆
1. ├─stars::st_as_stars(...) at test-geodist.R:143:3
2. ├─terra::rast(...)
3. └─terra::rast(...)
4. └─terra (local) .local(x = x, ...)
5. └─terra:::new_rast(...)
6. └─terra:::messages(r, "rast")
7. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:187:3'): geodist works with points and test data in feature space ──
Error: [rast] empty srs
Backtrace:
▆
1. ├─terra::rast(...) at test-geodist.R:187:3
2. └─terra::rast(...)
3. └─terra (local) .local(x = x, ...)
4. └─terra:::new_rast(...)
5. └─terra:::messages(r, "rast")
6. └─terra:::error(f, x@pntr$getError())
── Error ('test-geodist.R:238:3'): geodist works with categorical variables in feature space ──
Error: [project] cannot get output boundaries for the target crs
Backtrace:
▆
1. └─CAST::geodist(...) at test-geodist.R:238:3
2. └─CAST:::sampleFromArea(...)
3. ├─terra::project(modeldomain, "epsg:4326", method = "near")
4. └─terra::project(modeldomain, "epsg:4326", method = "near")
5. └─terra (local) .local(x, ...)
6. └─terra:::messages(x, "project")
7. └─terra:::error(f, x@pntr$getError())
[ FAIL 7 | WARN 11 | SKIP 10 | PASS 100 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-windows-x86_64
Version: 1.0.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building 'cast01-CAST-intro.Rmd' using rmarkdown
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_elev.zip'
Content type 'application/zip' length 1332437 bytes (1.3 MB)
==================================================
downloaded 1.3 MB
--- finished re-building 'cast01-CAST-intro.Rmd'
--- re-building 'cast02-plotgeodist.Rmd' using rmarkdown
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
Quitting from cast02-plotgeodist.Rmd:252-269 [unnamed-chunk-18]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error:
! [project] cannot get output boundaries for the target crs
---
Backtrace:
▆
1. └─CAST::geodist(...)
2. └─CAST:::sampleFromArea(...)
3. ├─terra::project(modeldomain, "epsg:4326")
4. └─terra::project(modeldomain, "epsg:4326")
5. └─terra (local) .local(x, ...)
6. └─terra:::messages(x, "project")
7. └─terra:::error(f, x@pntr$getError())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'cast02-plotgeodist.Rmd' failed with diagnostics:
[project] cannot get output boundaries for the target crs
--- failed re-building 'cast02-plotgeodist.Rmd'
--- re-building 'cast03-CV.Rmd' using rmarkdown
--- finished re-building 'cast03-CV.Rmd'
--- re-building 'cast04-AOA-tutorial.Rmd' using rmarkdown
--- finished re-building 'cast04-AOA-tutorial.Rmd'
--- re-building 'cast05-parallel.Rmd' using rmarkdown
--- finished re-building 'cast05-parallel.Rmd'
SUMMARY: processing the following file failed:
'cast02-plotgeodist.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-oldrel-windows-x86_64