Running ‘testthat.R’ [80s/123s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(cvms)
  > 
  > if (require("xpectr")) {
  +   test_check("cvms")
  + }
  Loading required package: xpectr
  [ FAIL 41 | WARN 21 | SKIP 69 | PASS 2620 ]
  
  ══ Skipped tests ═══════════════════════════════════════════════════════════════
  • Fails in check - IMPROVE THESE TESTS (1)
  • On CRAN (57)
  • Skipping check for CRAN release due to r_hub failure (1)
  • Skipping parallel tests (3)
  • empty test (1)
  • keras and tensorflow take too long and have too many dependencies (1)
  • mac and ubuntu give different warnings (4)
  • tidymodels have too many dependencies (1)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test_baseline.R:3511:3'): baseline() throws expected errors ─────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_equal(...) at test_baseline.R:3511:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─cvms:::subtract_inf_count_from_na_count(...)
    5.   ├─base::`[<-`(`*tmp*`, NAs_row_number, , value = `<df[,2]>`)
    6.   └─tibble:::`[<-.tbl_df`(`*tmp*`, NAs_row_number, , value = `<df[,2]>`)
    7.     └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    8.       └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
    9.         ├─base::withCallingHandlers(...)
   10.         └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_compational_grid.R:16:3'): the correct grid is created with create_computation_grid() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms:::create_computation_grid(...) at test_compational_grid.R:16:2
   2.   └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
   3.     └─cvms:::create_folds_map(data, fold_cols)
   4.       ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   5.       └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   6.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   7.           └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   8.             ├─base::withCallingHandlers(...)
   9.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_compational_grid.R:76:3'): the correct sampled grid is created with create_computation_grid() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms:::create_computation_grid(...) at test_compational_grid.R:76:2
   2.   └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
   3.     └─cvms:::create_folds_map(data, fold_cols)
   4.       ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   5.       └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   6.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   7.           └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   8.             ├─base::withCallingHandlers(...)
   9.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_compational_grid.R:169:3'): the correct folds map is created with create_folds_map() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms:::create_folds_map(...) at test_compational_grid.R:169:2
   2.   ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   3.   └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   4.     └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   5.       └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   6.         ├─base::withCallingHandlers(...)
   7.         └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_compational_grid.R:194:3'): the grid order is as expected with create_computation_grid() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms:::create_computation_grid(...) at test_compational_grid.R:194:2
   2.   └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
   3.     └─cvms:::create_folds_map(data, fold_cols)
   4.       ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   5.       └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   6.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   7.           └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   8.             ├─base::withCallingHandlers(...)
   9.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate.R:19:3'): binomial models work with cross_validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(...) at test_cross_validate.R:19:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate.R:387:3'): gaussian model with cross_validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(...) at test_cross_validate.R:387:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate.R:554:3'): gaussian mixed models with cross_validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(...) at test_cross_validate.R:554:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate.R:1378:3'): gaussian models work with repeated cross_validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(...) at test_cross_validate.R:1378:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate.R:3267:3'): varying number of folds in repeated cv with cross_validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(...) at test_cross_validate.R:3267:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:20:3'): binomial glm model works with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:20:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:415:3'): gaussian lm model works with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:415:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:1672:3'): multinomial nnet models work with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:1672:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:2740:3'): binomial random predictions work with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:2740:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:2905:3'): gaussian random predictions work with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:2905:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_cross_validate_fn.R:2986:3'): multinomial random predictions work with cross_validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate_fn(...) at test_cross_validate_fn.R:2986:2
    2.   └─cvms:::cross_validate_list(...)
    3.     └─cvms:::create_computation_grid(...)
    4.       └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    5.         └─cvms:::create_folds_map(data, fold_cols)
    6.           ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    7.           └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.               └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   10.                 ├─base::withCallingHandlers(...)
   11.                 └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_evaluate.R:664:3'): multinomial evaluations are correct in evaluate() ──
  Error in `vectbl_assign(x[[j]], cells[[j]], value)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─cvms::evaluate(...) at test_evaluate.R:664:2
    2. │ └─cvms:::run_evaluate(...)
    3. │   ├─... %>% ...
    4. │   └─cvms:::prepare_id_level_evaluation(...)
    5. │     ├─base::`[<-`(`*tmp*`, is.na(majority_vote_probabilities), value = `<dbl>`)
    6. │     └─tibble:::`[<-.tbl_df`(...)
    7. │       └─tibble:::tbl_subassign_matrix(x, j, value, j_arg, substitute(value))
    8. │         ├─base::withCallingHandlers(...)
    9. │         └─tibble:::vectbl_assign(x[[j]], cells[[j]], value)
   10. ├─dplyr::left_join(., grouping_keys_with_indices, by = ".group")
   11. └─dplyr::ungroup(.)
  ── Error ('test_evaluate.R:1411:3'): multinomial evaluations with one predicted class column is correctly unpacked in evaluate() ──
  Error in `vectbl_assign(x[[j]], cells[[j]], value)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─cvms::evaluate(...) at test_evaluate.R:1411:2
    2. │ └─cvms:::run_evaluate(...)
    3. │   ├─... %>% ...
    4. │   └─cvms:::prepare_id_level_evaluation(...)
    5. │     ├─base::`[<-`(`*tmp*`, is.na(majority_vote_probabilities), value = `<dbl>`)
    6. │     └─tibble:::`[<-.tbl_df`(...)
    7. │       └─tibble:::tbl_subassign_matrix(x, j, value, j_arg, substitute(value))
    8. │         ├─base::withCallingHandlers(...)
    9. │         └─tibble:::vectbl_assign(x[[j]], cells[[j]], value)
   10. ├─dplyr::left_join(., grouping_keys_with_indices, by = ".group")
   11. └─dplyr::ungroup(.)
  ── Error ('test_metrics.R:19:3'): Metrics work for glm in validate() ───────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_metrics.R:19:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_metrics.R:78:3'): Metrics work for glmer in validate() ─────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_metrics.R:78:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_metrics.R:140:3'): Metrics work for glm in validate() ──────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_metrics.R:140:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_metrics.R:203:3'): Metrics work for glmer in validate() ────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_metrics.R:203:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_metrics.R:455:3'): Metrics work when 0 is positive class for glmer in validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_metrics.R:455:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_plotting_functions.R:28:3'): plot_confusion_matrix() returns expected plots ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms::plot_confusion_matrix(cm[["Confusion Matrix"]][[1]]) at test_plotting_functions.R:28:2
   2.   └─cvms:::set_arrows(...)
   3.     ├─base::`[<-`(...)
   4.     └─tibble:::`[<-.tbl_df`(...)
   5.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   6.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   7.           ├─base::withCallingHandlers(...)
   8.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_plotting_functions.R:110:3'): plot_confusion_matrix() with multiclass conf mat returns expected plots ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms::plot_confusion_matrix(conf_mat) at test_plotting_functions.R:110:2
   2.   └─cvms:::set_arrows(...)
   3.     ├─base::`[<-`(...)
   4.     └─tibble:::`[<-.tbl_df`(...)
   5.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   6.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   7.           ├─base::withCallingHandlers(...)
   8.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_plotting_functions.R:264:3'): plot_confusion_matrix() with sum tiles, class order, and intensity_by percentage ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms::plot_confusion_matrix(...) at test_plotting_functions.R:264:2
   2.   └─cvms:::set_arrows(...)
   3.     ├─base::`[<-`(...)
   4.     └─tibble:::`[<-.tbl_df`(...)
   5.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   6.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   7.           ├─base::withCallingHandlers(...)
   8.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_plotting_functions.R:393:3'): testing diag_percentages_only argument ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms::plot_confusion_matrix(cm[["Confusion Matrix"]][[1]], diag_percentages_only = TRUE) at test_plotting_functions.R:393:2
   2.   └─cvms:::set_arrows(...)
   3.     ├─base::`[<-`(...)
   4.     └─tibble:::`[<-.tbl_df`(...)
   5.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   6.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   7.           ├─base::withCallingHandlers(...)
   8.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_reconstruct_formulas.R:20:3'): formulas without random effects are properly reconstructed from cross_validate results with reconstruct_formulas() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::cross_validate(data, formulas = model_formulas, family = "gaussian") at test_reconstruct_formulas.R:20:2
    2.   └─cvms:::call_cross_validate(...)
    3.     └─cvms:::cross_validate_list(...)
    4.       └─cvms:::create_computation_grid(...)
    5.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
    6.           └─cvms:::create_folds_map(data, fold_cols)
    7.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
    8.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
    9.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.                   ├─base::withCallingHandlers(...)
   12.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_reconstruct_formulas.R:45:3'): formulas with random effects are properly reconstructed from cross_validate results with reconstruct_formulas() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─xpectr::suppress_mw(...) at test_reconstruct_formulas.R:45:2
    2. │ ├─base::suppressMessages(suppressWarnings(expr))
    3. │ │ └─base::withCallingHandlers(...)
    4. │ └─base::suppressWarnings(expr)
    5. │   └─base::withCallingHandlers(...)
    6. └─cvms::cross_validate(data, formulas = model_formulas, family = "gaussian") at test_reconstruct_formulas.R:46:4
    7.   └─cvms:::call_cross_validate(...)
    8.     └─cvms:::cross_validate_list(...)
    9.       └─cvms:::create_computation_grid(...)
   10.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
   11.           └─cvms:::create_folds_map(data, fold_cols)
   12.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   13.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   14.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   15.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   16.                   ├─base::withCallingHandlers(...)
   17.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_summarize_metrics.R:309:3'): summarize_metrics() works with argument combinations ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. └─cvms::summarize_metrics(...) at test_summarize_metrics.R:309:2
   2.   └─cvms:::subtract_inf_count_from_na_count(summarized_metrics)
   3.     ├─base::`[<-`(`*tmp*`, NAs_row_number, , value = `<df[,3]>`)
   4.     └─tibble:::`[<-.tbl_df`(`*tmp*`, NAs_row_number, , value = `<df[,3]>`)
   5.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   6.         └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   7.           ├─base::withCallingHandlers(...)
   8.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:23:3'): binomial model work with validate() ─────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_validate.R:23:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:190:3'): binomial mixed model work with validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_validate.R:190:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:390:3'): gaussian model with validate() ─────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_validate.R:390:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:484:3'): Right glm model used in validate() ─────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_validate.R:484:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:524:3'): Right glmer model used in validate() ───────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate(...) at test_validate.R:524:2
    2.   └─cvms:::call_validate(...)
    3.     └─cvms:::validate_list(...)
    4.       ├─base::`[<-`(...)
    5.       ├─dplyr:::`[<-.grouped_df`(...)
    6.       ├─base::NextMethod()
    7.       └─tibble:::`[<-.tbl_df`(...)
    8.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    9.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   10.             ├─base::withCallingHandlers(...)
   11.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:574:3'): model using dot in formula ( y ~ . ) works with validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_warning(...) at test_validate.R:574:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─cvms::validate(...)
    7.   └─cvms:::call_validate(...)
    8.     └─cvms:::validate_list(...)
    9.       ├─base::`[<-`(...)
   10.       ├─dplyr:::`[<-.grouped_df`(...)
   11.       ├─base::NextMethod()
   12.       └─tibble:::`[<-.tbl_df`(...)
   13.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   14.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   15.             ├─base::withCallingHandlers(...)
   16.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate.R:610:3'): Singular fit messages counted in validate() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_message(...) at test_validate.R:610:2
    2. │ └─testthat:::quasi_capture(enquo(object), label, capture_messages)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─cvms::validate(...)
    7.   └─cvms:::call_validate(...)
    8.     └─cvms:::validate_list(...)
    9.       ├─base::`[<-`(...)
   10.       ├─dplyr:::`[<-.grouped_df`(...)
   11.       ├─base::NextMethod()
   12.       └─tibble:::`[<-.tbl_df`(...)
   13.         └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   14.           └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   15.             ├─base::withCallingHandlers(...)
   16.             └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Failure ('test_validate.R:643:3'): the expected errors are thrown by validate() ──
  `suppressWarnings(...)` threw an error with unexpected message.
  Expected match: "Model did not converge."
  Actual message: "DLL requires the use of native symbols"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_validate.R:643:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. ├─base::suppressWarnings(...)
    7. │ └─base::withCallingHandlers(...)
    8. └─cvms::validate(...)
    9.   └─cvms:::call_validate(...)
   10.     └─cvms:::validate_list(...)
   11.       └─cvms:::create_computation_grid(...)
   12.         └─cvms:::create_folds_grid(data = data, fold_cols = fold_cols)
   13.           └─cvms:::create_folds_map(data, fold_cols)
   14.             ├─base::`[<-`(`*tmp*`, 1, "start_", value = `<dbl>`)
   15.             └─tibble:::`[<-.tbl_df`(`*tmp*`, 1, "start_", value = `<dbl>`)
   16.               └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   17.                 └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   18.                   ├─base::withCallingHandlers(...)
   19.                   └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate_fn.R:31:3'): quick: binomial glm model works with validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─base::suppressWarnings(...) at test_validate_fn.R:31:2
    2. │ └─base::withCallingHandlers(...)
    3. └─cvms::validate_fn(...)
    4.   └─cvms:::validate_list(...)
    5.     ├─base::`[<-`(...)
    6.     ├─dplyr:::`[<-.grouped_df`(...)
    7.     ├─base::NextMethod()
    8.     └─tibble:::`[<-.tbl_df`(...)
    9.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.         └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
   11.           ├─base::withCallingHandlers(...)
   12.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate_fn.R:4177:3'): testing nested tibbles in multinomial validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate_fn(...) at test_validate_fn.R:4177:2
    2.   └─cvms:::validate_list(...)
    3.     ├─base::`[<-`(...)
    4.     ├─dplyr:::`[<-.grouped_df`(...)
    5.     ├─base::NextMethod()
    6.     └─tibble:::`[<-.tbl_df`(...)
    7.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    8.         └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
    9.           ├─base::withCallingHandlers(...)
   10.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_validate_fn.R:4896:3'): testing nested tibbles in gaussian validate_fn() ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. └─cvms::validate_fn(...) at test_validate_fn.R:4896:2
    2.   └─cvms:::validate_list(...)
    3.     ├─base::`[<-`(...)
    4.     ├─dplyr:::`[<-.grouped_df`(...)
    5.     ├─base::NextMethod()
    6.     └─tibble:::`[<-.tbl_df`(...)
    7.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
    8.         └─tibble:::tbl_subassign_row(xo, i, value, i_arg, value_arg, call)
    9.           ├─base::withCallingHandlers(...)
   10.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  
  [ FAIL 41 | WARN 21 | SKIP 69 | PASS 2620 ]
  Error: Test failures
  Execution halted