Running ‘testthat.R’ [53s/57s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(mlr3viz)
  > 
  > test_check("mlr3viz")
  ══ Warnings ════════════════════════════════════════════════════════════════════
  ── Warning (test_PredictionClust.R:18:3): autoplot.PredictionClust ─────────────
  `select_()` is deprecated as of dplyr 0.7.0.
  Please use `select()` instead.
  This warning is displayed once every 8 hours.
  Call `lifecycle::last_warnings()` to see where this warning was generated.
  Backtrace:
   1. ggplot2::autoplot(prediction, task, type = "pca") test_PredictionClust.R:18:2
   2. mlr3viz:::autoplot.PredictionClust(prediction, task, type = "pca")
   4. ggfortify:::autoplot.prcomp(...)
   6. ggfortify:::fortify.prcomp(object, data = data)
   7. ggfortify:::cbind_wraps(data, values)
   8. dplyr::select_(df2, .dots = dots)
   9. dplyr:::lazy_deprec("select", hint = FALSE)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error (test_LearnerClassifCVGlmnet.R:9:3): autoplot.LearnerClassifCVGlmnet ──
  Error: 'NA' indices are not (yet?) supported for sparse Matrices
  Backtrace:
       █
    1. └─mlr3::lrn("classif.cv_glmnet")$train(mlr3::tsk("wine")) test_LearnerClassifCVGlmnet.R:9:2
    2.   └─mlr3:::.__Learner__train(...)
    3.     └─mlr3:::learner_train(self, task, row_ids)
    4.       └─mlr3misc::encapsulate(...)
    5.         ├─mlr3misc::invoke(...)
    6.         │ └─base::eval.parent(expr, n = 1L)
    7.         │   └─base::eval(expr, p)
    8.         │     └─base::eval(expr, p)
    9.         └─mlr3:::.f(learner = <environment>, task = <environment>)
   10.           └─get_private(learner)$.train(task)
   11.             └─mlr3learners:::.__LearnerClassifCVGlmnet__.train(...)
   12.               ├─mlr3misc::invoke(glmnet::cv.glmnet, x = data, y = target, .args = pars)
   13.               │ └─base::eval.parent(expr, n = 1L)
   14.               │   └─base::eval(expr, p)
   15.               │     └─base::eval(expr, p)
   16.               └─glmnet::cv.glmnet(x = data, y = target, family = "multinomial")
   17.                 └─glmnet:::cv.glmnet.raw(...)
   18.                   ├─glmnet::buildPredmat(...)
   19.                   └─glmnet:::buildPredmat.multnetlist(...)
   20.                     └─glmnet:::buildPredmat.array(...)
   21.                       ├─stats::predict(...)
   22.                       └─glmnet:::predict.multnet(...)
   23.                         ├─kbeta[, lamlist$left, drop = FALSE]
   24.                         └─kbeta[, lamlist$left, drop = FALSE]
   25.                           └─Matrix:::subCsp_cols(x, j, drop = drop)
   26.                             └─Matrix:::intI(j, n = x@Dim[2], dn[[2]], give.dn = FALSE)
  ── Error (test_LearnerRegrCVGlmnet.R:9:3): autoplot.LearnerRegrGlmnet ──────────
  Error: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. └─mlr3::lrn("regr.cv_glmnet")$train(mlr3::tsk("mtcars")) test_LearnerRegrCVGlmnet.R:9:2
    2.   └─mlr3:::.__Learner__train(...)
    3.     └─mlr3:::learner_train(self, task, row_ids)
    4.       └─mlr3misc::encapsulate(...)
    5.         ├─mlr3misc::invoke(...)
    6.         │ └─base::eval.parent(expr, n = 1L)
    7.         │   └─base::eval(expr, p)
    8.         │     └─base::eval(expr, p)
    9.         └─mlr3:::.f(learner = <environment>, task = <environment>)
   10.           └─get_private(learner)$.train(task)
   11.             └─mlr3learners:::.__LearnerRegrCVGlmnet__.train(...)
   12.               ├─mlr3misc::invoke(glmnet::cv.glmnet, x = data, y = target, .args = pars)
   13.               │ └─base::eval.parent(expr, n = 1L)
   14.               │   └─base::eval(expr, p)
   15.               │     └─base::eval(expr, p)
   16.               └─glmnet::cv.glmnet(x = data, y = target, family = "gaussian")
   17.                 └─glmnet:::cv.glmnet.raw(...)
   18.                   └─glmnet::glmnet(...)
   19.                     └─glmnet:::elnet(...)
  ── Error (test_LearnerRegrGlmnet.R:9:3): autoplot.LearnerRegrGlmnet ────────────
  Error: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. └─mlr3::lrn("regr.glmnet")$train(mlr3::tsk("mtcars")) test_LearnerRegrGlmnet.R:9:2
    2.   └─mlr3:::.__Learner__train(...)
    3.     └─mlr3:::learner_train(self, task, row_ids)
    4.       └─mlr3misc::encapsulate(...)
    5.         ├─mlr3misc::invoke(...)
    6.         │ └─base::eval.parent(expr, n = 1L)
    7.         │   └─base::eval(expr, p)
    8.         │     └─base::eval(expr, p)
    9.         └─mlr3:::.f(learner = <environment>, task = <environment>)
   10.           └─get_private(learner)$.train(task)
   11.             └─mlr3learners:::.__LearnerRegrGlmnet__.train(...)
   12.               ├─mlr3misc::invoke(glmnet::glmnet, x = data, y = target, .args = pars)
   13.               │ └─base::eval.parent(expr, n = 1L)
   14.               │   └─base::eval(expr, p)
   15.               │     └─base::eval(expr, p)
   16.               └─glmnet::glmnet(x = data, y = target, family = "gaussian")
   17.                 └─glmnet:::elnet(...)
  
  [ FAIL 3 | WARN 1 | SKIP 0 | PASS 103 ]
  Error: Test failures
  Execution halted