Last updated on 2025-09-08 14:50:27 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.0.5 | 7.01 | 174.47 | 181.48 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.0.5 | 3.81 | 150.97 | 154.78 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.0.5 | 238.47 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.0.5 | 317.25 | ERROR | |||
| r-devel-windows-x86_64 | 0.0.5 | 8.00 | 338.00 | 346.00 | OK | |
| r-patched-linux-x86_64 | 0.0.5 | 6.64 | 232.10 | 238.74 | OK | |
| r-release-linux-x86_64 | 0.0.5 | 6.50 | 230.31 | 236.81 | OK | |
| r-release-macos-arm64 | 0.0.5 | 159.00 | OK | |||
| r-release-macos-x86_64 | 0.0.5 | 155.00 | OK | |||
| r-release-windows-x86_64 | 0.0.5 | 8.00 | 338.00 | 346.00 | OK | |
| r-oldrel-macos-arm64 | 0.0.5 | 113.00 | OK | |||
| r-oldrel-macos-x86_64 | 0.0.5 | 167.00 | OK | |||
| r-oldrel-windows-x86_64 | 0.0.5 | 11.00 | 471.00 | 482.00 | OK |
Version: 0.0.5
Check: examples
Result: ERROR
Running examples in ‘mlsurvlrnrs-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: LearnerSurvCoxPHCox
> ### Title: R6 Class to construct a Cox proportional hazards survival
> ### learner
> ### Aliases: LearnerSurvCoxPHCox
>
> ### ** Examples
>
> # survival analysis
>
> dataset <- survival::colon |>
+ data.table::as.data.table() |>
+ na.omit()
> dataset <- dataset[get("etype") == 2, ]
>
> seed <- 123
> surv_cols <- c("status", "time", "rx")
>
> feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
>
> split_vector <- splitTools::multi_strata(
+ df = dataset[, .SD, .SDcols = surv_cols],
+ strategy = "kmeans",
+ k = 4
+ )
>
> train_x <- model.matrix(
+ ~ -1 + .,
+ dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
+ )
> train_y <- survival::Surv(
+ event = (dataset[, get("status")] |>
+ as.character() |>
+ as.integer()),
+ time = dataset[, get("time")],
+ type = "right"
+ )
>
> fold_list <- splitTools::create_folds(
+ y = split_vector,
+ k = 3,
+ type = "stratified",
+ seed = seed
+ )
>
>
> surv_coxph_cox_optimizer <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerSurvCoxPHCox$new(),
+ fold_list = fold_list,
+ ncores = 1L,
+ seed = seed
+ )
> surv_coxph_cox_optimizer$performance_metric <- c_index
>
> # set data
> surv_coxph_cox_optimizer$set_data(
+ x = train_x,
+ y = train_y
+ )
>
> surv_coxph_cox_optimizer$execute()
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.0.5
Check: tests
Result: ERROR
Running ‘testthat.R’ [100s/317s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
>
> Sys.setenv("OMP_THREAD_LIMIT" = 2)
> Sys.setenv("Ncpu" = 2)
>
> library(testthat)
> library(mlsurvlrnrs)
>
> test_check("mlsurvlrnrs")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 6.024 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.948 seconds
3) Running FUN 2 times in 2 thread(s)... 1.101 seconds
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 5.458 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.409 seconds
3) Running FUN 2 times in 2 thread(s)... 1.154 seconds
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 5.863 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.713 seconds
3) Running FUN 2 times in 2 thread(s)... 1.062 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.457 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters... 12.254 seconds
3) Running FUN 2 times in 2 thread(s)... 0.972 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.25 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 11.9 seconds
3) Running FUN 2 times in 2 thread(s)... 0.573 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.422 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search... 0.907 seconds
3) Running FUN 2 times in 2 thread(s)... 0.616 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 4.625 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.544 seconds
3) Running FUN 2 times in 2 thread(s)... 0.699 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.543 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.743 seconds
3) Running FUN 2 times in 2 thread(s)... 0.82 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.631 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.383 seconds
3) Running FUN 2 times in 2 thread(s)... 0.444 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.098 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 11.692 seconds
3) Running FUN 2 times in 2 thread(s)... 0.496 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.909 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 9.135 seconds
3) Running FUN 2 times in 2 thread(s)... 0.902 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.879 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 5.538 seconds
3) Running FUN 2 times in 2 thread(s)... 0.71 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 4.612 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Maximum convergence attempts exceeded - process is probably sampling random points. 87.429 seconds
3) Running FUN 2 times in 2 thread(s)... 0.516 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.26 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 9.783 seconds
3) Running FUN 2 times in 2 thread(s)... 0.352 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 4.239 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.128 seconds
3) Running FUN 2 times in 2 thread(s)... 0.659 seconds
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-surv_coxph_cox.R:56:5'): test cv - surv_coxph_cox ──────────────
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_coxph_cox_optimizer$execute() at test-surv_coxph_cox.R:56:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_aft.R:116:5'): test nested cv, bayesian - surv_xgboost_aft ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:116:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_cox.R:115:5'): test nested cv, bayesian - surv_xgboost_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:115:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.0.5
Check: examples
Result: ERROR
Running examples in ‘mlsurvlrnrs-Ex.R’ failed
The error most likely occurred in:
> ### Name: LearnerSurvCoxPHCox
> ### Title: R6 Class to construct a Cox proportional hazards survival
> ### learner
> ### Aliases: LearnerSurvCoxPHCox
>
> ### ** Examples
>
> # survival analysis
>
> dataset <- survival::colon |>
+ data.table::as.data.table() |>
+ na.omit()
> dataset <- dataset[get("etype") == 2, ]
>
> seed <- 123
> surv_cols <- c("status", "time", "rx")
>
> feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
>
> split_vector <- splitTools::multi_strata(
+ df = dataset[, .SD, .SDcols = surv_cols],
+ strategy = "kmeans",
+ k = 4
+ )
>
> train_x <- model.matrix(
+ ~ -1 + .,
+ dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
+ )
> train_y <- survival::Surv(
+ event = (dataset[, get("status")] |>
+ as.character() |>
+ as.integer()),
+ time = dataset[, get("time")],
+ type = "right"
+ )
>
> fold_list <- splitTools::create_folds(
+ y = split_vector,
+ k = 3,
+ type = "stratified",
+ seed = seed
+ )
>
>
> surv_coxph_cox_optimizer <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerSurvCoxPHCox$new(),
+ fold_list = fold_list,
+ ncores = 1L,
+ seed = seed
+ )
> surv_coxph_cox_optimizer$performance_metric <- c_index
>
> # set data
> surv_coxph_cox_optimizer$set_data(
+ x = train_x,
+ y = train_y
+ )
>
> surv_coxph_cox_optimizer$execute()
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.0.5
Check: tests
Result: ERROR
Running ‘testthat.R’ [122s/405s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
>
> Sys.setenv("OMP_THREAD_LIMIT" = 2)
> Sys.setenv("Ncpu" = 2)
>
> library(testthat)
> library(mlsurvlrnrs)
>
> test_check("mlsurvlrnrs")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 9.703 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.43 seconds
3) Running FUN 2 times in 2 thread(s)... 1.483 seconds
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 9.873 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.606 seconds
3) Running FUN 2 times in 2 thread(s)... 1.493 seconds
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 9.365 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.402 seconds
3) Running FUN 2 times in 2 thread(s)... 1.432 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.202 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Maximum convergence attempts exceeded - process is probably sampling random points. 112 seconds
3) Running FUN 2 times in 2 thread(s)... 0.641 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.292 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 31.118 seconds
3) Running FUN 2 times in 2 thread(s)... 0.814 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.399 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 4.91 seconds
3) Running FUN 2 times in 2 thread(s)... 0.673 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.433 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.918 seconds
3) Running FUN 2 times in 2 thread(s)... 0.557 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.36 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.135 seconds
3) Running FUN 2 times in 2 thread(s)... 1.036 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.618 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.936 seconds
3) Running FUN 2 times in 2 thread(s)... 0.621 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.403 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 18.456 seconds
3) Running FUN 2 times in 2 thread(s)... 0.807 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.621 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 5.441 seconds
3) Running FUN 2 times in 2 thread(s)... 0.796 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.38 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 11.006 seconds
3) Running FUN 2 times in 2 thread(s)... 0.761 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.81 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 6.841 seconds
3) Running FUN 2 times in 2 thread(s)... 0.465 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.855 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters... 14.425 seconds
3) Running FUN 2 times in 2 thread(s)... 0.639 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.37 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 8.252 seconds
3) Running FUN 2 times in 2 thread(s)... 0.52 seconds
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-surv_coxph_cox.R:56:5'): test cv - surv_coxph_cox ──────────────
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_coxph_cox_optimizer$execute() at test-surv_coxph_cox.R:56:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_aft.R:116:5'): test nested cv, bayesian - surv_xgboost_aft ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:116:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_cox.R:115:5'): test nested cv, bayesian - surv_xgboost_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:115:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.0.5
Check: examples
Result: ERROR
Running examples in ‘mlsurvlrnrs-Ex.R’ failed
The error most likely occurred in:
> ### Name: LearnerSurvCoxPHCox
> ### Title: R6 Class to construct a Cox proportional hazards survival
> ### learner
> ### Aliases: LearnerSurvCoxPHCox
>
> ### ** Examples
>
> # survival analysis
>
> dataset <- survival::colon |>
+ data.table::as.data.table() |>
+ na.omit()
> dataset <- dataset[get("etype") == 2, ]
>
> seed <- 123
> surv_cols <- c("status", "time", "rx")
>
> feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
>
> split_vector <- splitTools::multi_strata(
+ df = dataset[, .SD, .SDcols = surv_cols],
+ strategy = "kmeans",
+ k = 4
+ )
>
> train_x <- model.matrix(
+ ~ -1 + .,
+ dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
+ )
> train_y <- survival::Surv(
+ event = (dataset[, get("status")] |>
+ as.character() |>
+ as.integer()),
+ time = dataset[, get("time")],
+ type = "right"
+ )
>
> fold_list <- splitTools::create_folds(
+ y = split_vector,
+ k = 3,
+ type = "stratified",
+ seed = seed
+ )
>
>
> surv_coxph_cox_optimizer <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerSurvCoxPHCox$new(),
+ fold_list = fold_list,
+ ncores = 1L,
+ seed = seed
+ )
> surv_coxph_cox_optimizer$performance_metric <- c_index
>
> # set data
> surv_coxph_cox_optimizer$set_data(
+ x = train_x,
+ y = train_y
+ )
>
> surv_coxph_cox_optimizer$execute()
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
Error in if (fun_name == "PPV") { : argument is of length zero
Calls: <Anonymous> ... .compute_performance -> sapply -> lapply -> FUN -> metric_types_helper
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.0.5
Check: tests
Result: ERROR
Running ‘testthat.R’ [3m/11m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
>
> Sys.setenv("OMP_THREAD_LIMIT" = 2)
> Sys.setenv("Ncpu" = 2)
>
> library(testthat)
> library(mlsurvlrnrs)
>
> test_check("mlsurvlrnrs")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 18.113 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 3.769 seconds
3) Running FUN 2 times in 2 thread(s)... 2.794 seconds
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 23.127 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 5.873 seconds
3) Running FUN 2 times in 2 thread(s)... 3.731 seconds
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 21.358 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 3.62 seconds
3) Running FUN 2 times in 2 thread(s)... 4.17 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 16.748 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters... 26.975 seconds
3) Running FUN 2 times in 2 thread(s)... 1.116 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 13.961 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 62.501 seconds
3) Running FUN 2 times in 2 thread(s)... 1.034 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 12.681 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search... 2.052 seconds
3) Running FUN 2 times in 2 thread(s)... 1.097 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 13.554 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.56 seconds
3) Running FUN 2 times in 2 thread(s)... 0.909 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 12.599 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.431 seconds
3) Running FUN 2 times in 2 thread(s)... 0.887 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 10.399 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.323 seconds
3) Running FUN 2 times in 2 thread(s)... 0.884 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 11.576 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 33.277 seconds
3) Running FUN 2 times in 2 thread(s)... 1.072 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 10.73 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 25.231 seconds
3) Running FUN 2 times in 2 thread(s)... 0.926 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 9.757 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 13.081 seconds
3) Running FUN 2 times in 2 thread(s)... 0.779 seconds
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 7.431 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Maximum convergence attempts exceeded - process is probably sampling random points. 140.881 seconds
3) Running FUN 2 times in 2 thread(s)... 0.479 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.77 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 18.057 seconds
3) Running FUN 2 times in 2 thread(s)... 0.589 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.793 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 3.506 seconds
3) Running FUN 2 times in 2 thread(s)... 0.553 seconds
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-surv_coxph_cox.R:56:5'): test cv - surv_coxph_cox ──────────────
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_coxph_cox_optimizer$execute() at test-surv_coxph_cox.R:56:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_aft.R:116:5'): test nested cv, bayesian - surv_xgboost_aft ──
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:116:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_cox.R:115:5'): test nested cv, bayesian - surv_xgboost_cox ──
Error in `if (fun_name == "PPV") {
metric_metadata$probabilities <- FALSE
}`: argument is of length zero
Backtrace:
▆
1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:115:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc