Running ‘testthat.R’ [21s/27s]
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, threads = threads, ...)`: 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) `<fn>`(num.trees = 50L, mtry = 3L, x = `<df[,131]>`, y = `<fct>`)
   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