Running ‘spelling.R’ [0s/1s]
  Running ‘testthat.R’ [37s/43s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(partition)
  > 
  > test_check("partition")
  Starting 2 test processes
  [ FAIL 6 | WARN 11 | SKIP 0 | PASS 129 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-misc-partitioner-arguments.R:33:3'): linear and binary searches find the same partition ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─partition::partition(df8, 0.65, partitioner = part_kmeans(search = "linear")) at test-misc-partitioner-arguments.R:33:2
    2. │ └─partition:::reduce_partition_c(...)
    3. ├─partition (local) `<fn>`(...)
    4. │ └─partition:::direct_measure_reduce(.x, partitioner)
    5. │   └─... %>% partitioner$reduce()
    6. ├─partitioner$reduce(.)
    7. │ └─partition::reduce_kmeans(search = search, n_hits = n_hits, ...)
    8. │   └─partition:::linear_k_search(.partition_step, n_hits = n_hits)
    9. │     └─partition::map_cluster(.partition_step, scaled_mean_r, first_match = TRUE)
   10. │       └─partition:::reduce_mappings(.partition_step, target_list)
   11. │         └─... %>% dplyr::arrange(information)
   12. ├─dplyr::arrange(., information)
   13. ├─dplyr::select(., -position)
   14. ├─dplyr::arrange(., position, variable)
   15. ├─dplyr::right_join(., mapping_key, by = "variable")
   16. └─dplyr:::right_join.data.frame(., mapping_key, by = "variable")
   17.   └─dplyr:::join_mutate(...)
   18.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   19.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   20.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   21.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   22.           ├─base::withCallingHandlers(...)
   23.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-misc-partitioner-arguments.R:44:3'): init k searches find the same partition ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─partition::partition(df8, 0.65, partitioner = part_kmeans()) at test-misc-partitioner-arguments.R:44:2
    2. │ └─partition:::reduce_partition_c(...)
    3. ├─partition (local) `<fn>`(...)
    4. │ └─partition:::direct_measure_reduce(.x, partitioner)
    5. │   └─... %>% partitioner$reduce()
    6. ├─partitioner$reduce(.)
    7. │ └─partition::reduce_kmeans(search = search, n_hits = n_hits, ...)
    8. │   └─partition:::binary_k_search(.partition_step)
    9. │     └─partition::map_cluster(.partition_step, scaled_mean_r, first_match = TRUE)
   10. │       └─partition:::reduce_mappings(.partition_step, target_list)
   11. │         └─... %>% dplyr::arrange(information)
   12. ├─dplyr::arrange(., information)
   13. ├─dplyr::select(., -position)
   14. ├─dplyr::arrange(., position, variable)
   15. ├─dplyr::right_join(., mapping_key, by = "variable")
   16. └─dplyr:::right_join.data.frame(., mapping_key, by = "variable")
   17.   └─dplyr:::join_mutate(...)
   18.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   19.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   20.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   21.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   22.           ├─base::withCallingHandlers(...)
   23.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-misc-partitioner-arguments.R:55:3'): r kmeans algorithms work ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─partition::partition(df8, 0.65, partitioner = part_kmeans(algorithm = "Hartigan-Wong")) at test-misc-partitioner-arguments.R:55:2
    2. │ └─partition:::reduce_partition_c(...)
    3. ├─partition (local) `<fn>`(...)
    4. │ └─partition:::direct_measure_reduce(.x, partitioner)
    5. │   └─... %>% partitioner$reduce()
    6. ├─partitioner$reduce(.)
    7. │ └─partition::reduce_kmeans(search = search, n_hits = n_hits, ...)
    8. │   └─partition:::binary_k_search(.partition_step)
    9. │     └─partition::map_cluster(.partition_step, scaled_mean_r, first_match = TRUE)
   10. │       └─partition:::reduce_mappings(.partition_step, target_list)
   11. │         └─... %>% dplyr::arrange(information)
   12. ├─dplyr::arrange(., information)
   13. ├─dplyr::select(., -position)
   14. ├─dplyr::arrange(., position, variable)
   15. ├─dplyr::right_join(., mapping_key, by = "variable")
   16. └─dplyr:::right_join.data.frame(., mapping_key, by = "variable")
   17.   └─dplyr:::join_mutate(...)
   18.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   19.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   20.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   21.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   22.           ├─base::withCallingHandlers(...)
   23.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-partitioners-reduce-correctly.R:36:3'): part_kmeans() reduces correctly, high threshold ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_silent(partition(df, threshold = 0.6, partitioner = part_kmeans())) at test-partitioners-reduce-correctly.R:36:2
    2. │ └─testthat:::quasi_capture(enquo(object), NULL, evaluate_promise)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ ├─withr::with_output_sink(...)
    5. │   │ │ └─base::force(code)
    6. │   │ ├─base::withCallingHandlers(...)
    7. │   │ └─base::withVisible(code)
    8. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    9. ├─partition::partition(df, threshold = 0.6, partitioner = part_kmeans())
   10. │ └─partition:::reduce_partition_c(...)
   11. ├─partition (local) `<fn>`(...)
   12. │ └─partition:::direct_measure_reduce(.x, partitioner)
   13. │   └─... %>% partitioner$reduce()
   14. ├─partitioner$reduce(.)
   15. │ └─partition::reduce_kmeans(search = search, n_hits = n_hits, ...)
   16. │   └─partition:::binary_k_search(.partition_step)
   17. │     └─partition::map_cluster(.partition_step, scaled_mean_r, first_match = TRUE)
   18. │       └─partition:::reduce_mappings(.partition_step, target_list)
   19. │         └─... %>% dplyr::arrange(information)
   20. ├─dplyr::arrange(., information)
   21. ├─dplyr::select(., -position)
   22. ├─dplyr::arrange(., position, variable)
   23. ├─dplyr::right_join(., mapping_key, by = "variable")
   24. └─dplyr:::right_join.data.frame(., mapping_key, by = "variable")
   25.   └─dplyr:::join_mutate(...)
   26.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   27.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   29.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   30.           ├─base::withCallingHandlers(...)
   31.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-partitioners-reduce-correctly.R:44:3'): part_kmeans() reduces correctly, low threshold ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_silent(partition(df, threshold = 0.1, partitioner = part_kmeans())) at test-partitioners-reduce-correctly.R:44:2
    2. │ └─testthat:::quasi_capture(enquo(object), NULL, evaluate_promise)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ ├─withr::with_output_sink(...)
    5. │   │ │ └─base::force(code)
    6. │   │ ├─base::withCallingHandlers(...)
    7. │   │ └─base::withVisible(code)
    8. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    9. ├─partition::partition(df, threshold = 0.1, partitioner = part_kmeans())
   10. │ └─partition:::reduce_partition_c(...)
   11. ├─partition (local) `<fn>`(...)
   12. │ └─partition:::direct_measure_reduce(.x, partitioner)
   13. │   └─... %>% partitioner$reduce()
   14. ├─partitioner$reduce(.)
   15. │ └─partition::reduce_kmeans(search = search, n_hits = n_hits, ...)
   16. │   └─partition:::binary_k_search(.partition_step)
   17. │     └─partition::map_cluster(.partition_step, scaled_mean_r, first_match = TRUE)
   18. │       └─partition:::reduce_mappings(.partition_step, target_list)
   19. │         └─... %>% dplyr::arrange(information)
   20. ├─dplyr::arrange(., information)
   21. ├─dplyr::select(., -position)
   22. ├─dplyr::arrange(., position, variable)
   23. ├─dplyr::right_join(., mapping_key, by = "variable")
   24. └─dplyr:::right_join.data.frame(., mapping_key, by = "variable")
   25.   └─dplyr:::join_mutate(...)
   26.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   27.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   29.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   30.           ├─base::withCallingHandlers(...)
   31.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-partitioners-reduce-correctly.R:138:3'): Data with missing values still reduces ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─base::`[<-`(...) at test-partitioners-reduce-correctly.R:138:2
   2. └─tibble:::`[<-.tbl_df`(...) at test-partitioners-reduce-correctly.R:138:2
   3.   └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   4.     └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   5.       ├─base::withCallingHandlers(...)
   6.       └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  
  [ FAIL 6 | WARN 11 | SKIP 0 | PASS 129 ]
  Error: Test failures
  Execution halted