Running ‘testthat.R’ [115s/307s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(NeuroDecodeR)
  > 
  > test_check("NeuroDecodeR")
  
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    |======================================================================| 100%[1] "2023-03-18 17:11:48 CET"
   [1] 0.1428571 0.1706349 0.1309524 0.0952381 0.1587302 0.1507937 0.1547619
   [8] 0.1547619 0.1468254 0.1904762 0.3412698 0.8174603 0.8174603 0.7936508
  [15] 0.7698413 0.6944444 0.5753968 0.6428571
  0.9 Mb
  
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    |======================================================================| 100%[ FAIL 2 | WARN 24 | SKIP 0 | PASS 147 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-classifiers.R:139:3'): the cl_svm() claissifier is working ─────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_null(test_valid_classifier(cl)) at test-classifiers.R:139:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─NeuroDecodeR:::test_valid_classifier(cl)
    5. │ ├─NeuroDecodeR::get_predictions(the_classifier, training_set, test_set)
    6. │ └─NeuroDecodeR:::get_predictions.cl_svm(...)
    7. │   ├─... %>% select(-.data$test_point_num)
    8. │   ├─dplyr::full_join(...)
    9. │   └─dplyr:::full_join.data.frame(...)
   10. │     └─dplyr:::join_mutate(...)
   11. │       ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,2]>`)
   12. │       └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,2]>`)
   13. │         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   14. │           └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   15. │             ├─base::withCallingHandlers(...)
   16. │             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
   17. ├─dplyr::select(., -.data$test_point_num)
   18. ├─dplyr::arrange(., .data$test_point_num)
   19. ├─tidyr::spread(., .data$pos_class, .data$tot_wins)
   20. ├─dplyr::select(., .data$pos_class, .data$tot_wins, .data$test_point_num)
   21. ├─dplyr::mutate(., tot_wins = pos_wins + neg_wins)
   22. └─tidyr::replace_na(., list(pos_wins = 0, neg_wins = 0))
  ── Error ('test-classifiers.R:163:3'): the cl_svm classifier constructor correctly adds objects to an ndr container ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─fp %>% cl_svm() at test-classifiers.R:163:2
    2. ├─NeuroDecodeR::cl_svm(.)
    3. │ └─NeuroDecodeR:::put_ndr_object_in_container(...)
    4. │   └─NeuroDecodeR:::add_ndr_object(the_ndr_container, ndr_object)
    5. │     └─NeuroDecodeR::test_valid_ndr_object(ndr_object)
    6. │       ├─base::eval(...)
    7. │       │ └─base::eval(...)
    8. │       └─NeuroDecodeR:::test_valid_classifier(ndr_object)
    9. │         ├─NeuroDecodeR::get_predictions(the_classifier, training_set, test_set)
   10. │         └─NeuroDecodeR:::get_predictions.cl_svm(...)
   11. │           ├─... %>% select(-.data$test_point_num)
   12. │           ├─dplyr::full_join(...)
   13. │           └─dplyr:::full_join.data.frame(...)
   14. │             └─dplyr:::join_mutate(...)
   15. │               ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,2]>`)
   16. │               └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,2]>`)
   17. │                 └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   18. │                   └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   19. │                     ├─base::withCallingHandlers(...)
   20. │                     └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
   21. ├─dplyr::select(., -.data$test_point_num)
   22. ├─dplyr::arrange(., .data$test_point_num)
   23. ├─tidyr::spread(., .data$pos_class, .data$tot_wins)
   24. ├─dplyr::select(., .data$pos_class, .data$tot_wins, .data$test_point_num)
   25. ├─dplyr::mutate(., tot_wins = pos_wins + neg_wins)
   26. └─tidyr::replace_na(., list(pos_wins = 0, neg_wins = 0))
  
  [ FAIL 2 | WARN 24 | SKIP 0 | PASS 147 ]
  Error: Test failures
  Execution halted