Package: fuseMLR Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘fuseMLR.Rmd’ using rmarkdown Quitting from fuseMLR.Rmd:162-167 [varsel] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error in `fru::fru()`: ! unused arguments (num.trees = 1000, mtry = 3, probability = TRUE) --- Backtrace: ▆ 1. └─fuseMLR::varSelection(training = training) 2. └─training$varSelection(ind_subset = ind_subset, verbose = training$getVerbose()) 3. └─layer$varSelection(ind_subset = ind_subset, verbose = self$getVerbose()) 4. └─varsel$varSelection(ind_subset = ind_subset) 5. ├─base::do.call(eval(parse(text = varsel)), varsel_param) 6. ├─Boruta (local) ``(...) 7. └─Boruta:::Boruta.default(...) 8. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 9. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 10. └─fru::importance(...) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error: processing vignette 'fuseMLR.Rmd' failed with diagnostics: unused arguments (num.trees = 1000, mtry = 3, probability = TRUE) --- failed re-building ‘fuseMLR.Rmd’ SUMMARY: processing the following file failed: ‘fuseMLR.Rmd’ Error: Vignette re-building failed. Execution halted Package: fuseMLR Check: tests New result: ERROR Running ‘testthat.R’ [7s/7s] 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/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(fuseMLR) > > test_check("fuseMLR") Class : Data name : geneexpr ind. id. : IDS n : 49 p : 132 Class: HashTable id: test ----------------- [1] key class <0 rows> (or 0-length row.names) Learner : ranger TrainLayer : geneexpr Package : ranger Learn function : ranger Training of base model on layer geneexpr started. Training of base model on layer geneexpr done. Class : Model Learner info. ----------------------- Learner : ranger TrainLayer : geneexpr Package : ranger Learn function : ranger Train data info. ----------------------- TrainData : geneexpr Layer : geneexpr ind. id. : IDS target : disease n : 50 Missing : 0 p : 131 TrainLayer : geneexpr Status : Not trained Empty layer. TrainData : methylation Layer : methylation ind. id. : IDS target : disease n : 50 Missing : 0 p : 367 Layer geneexpr ---------------- TrainLayer : geneexpr Status : Not trained Empty layer. ---------------- Object(s) on layer geneexpr Empty layer Layer geneexpr ---------------- TrainLayer : geneexpr Status : Not trained Nb. of objects stored : 3 ---------------- Object(s) on layer geneexpr ---------------- Learner : ranger TrainLayer : geneexpr Package : ranger Learn function : ranger ---------------- ---------------- VarSel : varsel_geneexpr TrainLayer : geneexpr Package : Boruta Function : Boruta ---------------- ---------------- TrainData : geneexpr Layer : geneexpr Ind. id. : IDS Target : disease n : 50 Missing : 0 p : 131 ---------------- Training of base model on layer geneexpr started. Training of base model on layer geneexpr done. Layer geneexpr ---------------- TrainLayer : geneexpr Status : Trained Nb. of objects stored : 4 ---------------- Object(s) on layer geneexpr ---------------- Learner : ranger TrainLayer : geneexpr Package : ranger Learn function : ranger ---------------- ---------------- VarSel : varsel_geneexpr TrainLayer : geneexpr Package : Boruta Function : Boruta ---------------- ---------------- TrainData : geneexpr Layer : geneexpr Ind. id. : IDS Target : disease n : 50 Missing : 0 p : 131 ---------------- TrainMetaLayer : meta Status : Not trained Empty layer. MetaLayer ---------------- TrainMetaLayer : meta Status : Not trained Empty layer. ---------------- Object(s) on MetaLayer Empty layer Training : training Problem type : classification Status : Not trained Number of layers: 0 Layers trained : 0 Variable selection on layer geneexpr started. Saving _problems/test-Training-148.R VarSel : varsel_geneexpr TrainLayer : geneexpr Package : Boruta Function : Boruta Tuning 'epsilon' via cross-validation with 5 folds. Optimal epsilon: 0.071. Tuning with 5 folds. Tuning 'alpha' and 'epsilon' via cross-validation with 5 folds. Optimal alpha: 1 (1 Learner(s)). Optimal epsilon: 0.313. Tuning with 5 folds. Using user-defined 'epsilon' = 0.1. Tuning 'epsilon' via cross-validation with 10 folds. Tuning 'epsilon' via cross-validation with 10 folds. Tuning 'epsilon' via cross-validation with 10 folds. Tuning 'epsilon' via cross-validation with 10 folds. Tuning 'epsilon' via cross-validation with 10 folds. Tuning 'epsilon' via cross-validation with 10 folds. Optimal epsilon: 0.669. Tuning with 10 folds. Tuning 'alpha' and 'epsilon' via cross-validation with 10 folds. Optimal alpha: 1 (1 Learner(s)). Optimal epsilon: 0.217. Tuning with 10 folds. [ FAIL 1 | WARN 3 | SKIP 2 | PASS 170 ] ══ Skipped tests (2) ═══════════════════════════════════════════════════════════ • On CRAN (2): 'test-TrainMetaLayer.R:60:5', 'test-VarSel.R:43:5' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-Training.R:148:5'): Training: all tests ──────────────────────── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused arguments (num.trees = 50, mtry = 3) Backtrace: ▆ 1. ├─testthat::expect_warning(...) at test-Training.R:141:3 2. │ └─testthat:::expect_condition_matching_(...) 3. │ └─testthat:::quasi_capture(...) 4. │ ├─testthat (local) .capture(...) 5. │ │ └─base::withCallingHandlers(...) 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 7. └─training$varSelection() at test-Training.R:148:5 8. └─layer$varSelection(ind_subset = ind_subset, verbose = self$getVerbose()) 9. └─varsel$varSelection(ind_subset = ind_subset) 10. ├─base::do.call(eval(parse(text = varsel)), varsel_param) 11. ├─Boruta (local) ``(num.trees = 50L, mtry = 3L, x = ``, y = ``) 12. └─Boruta:::Boruta.default(...) 13. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 14. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 15. └─fru::importance(...) [ FAIL 1 | WARN 3 | SKIP 2 | PASS 170 ] Error: ! Test failures. Execution halted Package: mlr3filters Check: tests New result: ERROR Running ‘testthat.R’ [21s/20s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > if (requireNamespace("testthat", quietly = TRUE)) { + library("testthat") + library("mlr3filters") + test_check("mlr3filters") + } Saving _problems/test_filter_boruta-6.R Saving _problems/test_filter_boruta-13.R Saving _problems/test_filter_classif-9.R Saving _problems/test_filter_regr-7.R [ FAIL 4 | WARN 0 | SKIP 3 | PASS 297 ] ══ Skipped tests (3) ═══════════════════════════════════════════════════════════ • {mlr3proba} is not installed (2): 'test_FilterUnivariateCox.R:1:1', 'test_filter_surv.R:1:1' • {mlr3spatiotempcv} is not installed (1): 'test_mlr3spatiotempcv.R:1:1' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_filter_boruta.R:6:3'): filter boruta works ───────────────────── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─f$calculate(task) at test_filter_boruta.R:6:3 2. └─mlr3filters:::.__Filter__calculate(...) 3. └─private$.calculate(task, nfeat) 4. └─mlr3filters:::.__FilterBoruta__.calculate(...) 5. ├─mlr3misc::invoke(...) 6. │ └─base::eval.parent(expr, n = 1L) 7. │ └─base::eval(expr, p) 8. │ └─base::eval(expr, p) 9. ├─Boruta::Boruta(formula = formula, data = data, num.threads = 1L) 10. └─Boruta:::Boruta.formula(formula = formula, data = data, num.threads = 1L) 11. └─Boruta:::Boruta.default(d$X, d$Y, ...) 12. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 13. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 14. └─fru::importance(...) ── Error ('test_filter_boruta.R:13:3'): filter boruta works with factors ─────── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─f$calculate(task) at test_filter_boruta.R:13:3 2. └─mlr3filters:::.__Filter__calculate(...) 3. └─private$.calculate(task, nfeat) 4. └─mlr3filters:::.__FilterBoruta__.calculate(...) 5. ├─mlr3misc::invoke(...) 6. │ └─base::eval.parent(expr, n = 1L) 7. │ └─base::eval(expr, p) 8. │ └─base::eval(expr, p) 9. ├─Boruta::Boruta(formula = formula, data = data, num.threads = 1L) 10. └─Boruta:::Boruta.formula(formula = formula, data = data, num.threads = 1L) 11. └─Boruta:::Boruta.default(d$X, d$Y, ...) 12. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 13. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 14. └─fru::importance(...) ── Error ('test_filter_classif.R:9:7'): all classif filters return correct filter values ── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─f$calculate(task) at test_filter_classif.R:9:7 2. └─mlr3filters:::.__Filter__calculate(...) 3. └─private$.calculate(task, nfeat) 4. └─mlr3filters:::.__FilterBoruta__.calculate(...) 5. ├─mlr3misc::invoke(...) 6. │ └─base::eval.parent(expr, n = 1L) 7. │ └─base::eval(expr, p) 8. │ └─base::eval(expr, p) 9. ├─Boruta::Boruta(formula = formula, data = data, num.threads = 1L) 10. └─Boruta:::Boruta.formula(formula = formula, data = data, num.threads = 1L) 11. └─Boruta:::Boruta.default(d$X, d$Y, ...) 12. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 13. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 14. └─fru::importance(...) ── Error ('test_filter_regr.R:7:7'): all regr filters return correct filter values ── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─f$calculate(task) at test_filter_regr.R:7:7 2. └─mlr3filters:::.__Filter__calculate(...) 3. └─private$.calculate(task, nfeat) 4. └─mlr3filters:::.__FilterBoruta__.calculate(...) 5. ├─mlr3misc::invoke(...) 6. │ └─base::eval.parent(expr, n = 1L) 7. │ └─base::eval(expr, p) 8. │ └─base::eval(expr, p) 9. ├─Boruta::Boruta(formula = formula, data = data, num.threads = 1L) 10. └─Boruta:::Boruta.formula(formula = formula, data = data, num.threads = 1L) 11. └─Boruta:::Boruta.default(d$X, d$Y, ...) 12. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 13. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 14. └─fru::importance(...) [ FAIL 4 | WARN 0 | SKIP 3 | PASS 297 ] Error: ! Test failures. Execution halted Package: SISIR Check: tests New result: ERROR Running ‘testthat.R’ [70s/65s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library("testthat") > library("SISIR") Loading required package: foreach Loading required package: doParallel Loading required package: iterators Loading required package: parallel > > test_check("SISIR") Saving _problems/test_sfcb-66.R Saving _problems/test_sfcb-81.R [ FAIL 2 | WARN 2 | SKIP 0 | PASS 109 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_sfcb.R:65:3'): `sfcb` works for one `at` with selection. ─────── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─SISIR::sfcb(...) at test_sfcb.R:65:3 2. ├─base::system.time(...) 3. └─SISIR (local) selection_function(all_summaries, Y, seed) 4. └─base::sapply(...) 5. └─base::lapply(X = X, FUN = FUN, ...) 6. └─SISIR (local) FUN(X[[i]], ...) 7. ├─Boruta::Boruta(Y ~ ., data = cur_df, num.threads = 1) 8. └─Boruta:::Boruta.formula(Y ~ ., data = cur_df, num.threads = 1) 9. └─Boruta:::Boruta.default(d$X, d$Y, ...) 10. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 11. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 12. └─fru::importance(...) ── Error ('test_sfcb.R:80:3'): `sfcb` works for one `at` with selection. ─────── Error in `fru::fru(x, y, trees = trees, importance = TRUE, ...)`: unused argument (num.threads = 1) Backtrace: ▆ 1. └─SISIR::sfcb(...) at test_sfcb.R:80:3 2. ├─base::system.time(...) 3. └─SISIR (local) selection_function(all_summaries, Y, seed) 4. └─base::sapply(...) 5. └─base::lapply(X = X, FUN = FUN, ...) 6. └─SISIR (local) FUN(X[[i]], ...) 7. ├─Boruta::Boruta(Y ~ ., data = cur_df, num.threads = 1) 8. └─Boruta:::Boruta.formula(Y ~ ., data = cur_df, num.threads = 1) 9. └─Boruta:::Boruta.default(d$X, d$Y, ...) 10. └─Boruta (local) addShadowsAndGetImp(decReg, runs) 11. └─Boruta (local) getImp(cbind(x[, decReg != "Rejected"], xSha), y, ...) 12. └─fru::importance(...) [ FAIL 2 | WARN 2 | SKIP 0 | PASS 109 ] Error: ! Test failures. Execution halted