Running ‘testthat.R’ [46s/51s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(heemod)
  > 
  > ## the Sys.setenv fixes a problem running tests
  > ##   with parallel processing; related to
  > ##   https://github.com/hadley/testthat/issues/86 and
  > ##   https://github.com/hadley/testthat/issues/144
  > 
  > Sys.setenv("R_TESTS" = "")
  > test_check("heemod")
  ── 1. Error: Same results using 1 core or 2. (@test_parallel.R#7)  ─────────────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::run_model_tabular(...)
    2. heemod:::gather_model_info(location, reference)
    3. heemod:::create_parameters_from_tabular(...)
    4. heemod:::define_dsa_(...)
   11. tibble::tibble(dots[i])
   12. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   13. tibble:::check_valid_col(res, col_names[[j]], j)
   14. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 2. Failure: Parameter evaluation (@test_parameters.R#81)  ───────────────────
  `str\(e_par1\)` does not match "10 obs\\. of  5 variables".
  Actual value: "tibble \[10 × 5\] \(S3: eval_parameters/tbl_df/tbl/data\.frame\)\\n \$ model_time  : int \[1:10\] 1 2 3 4 5 6 7 8 9 10\\n \$ markov_cycle: int \[1:10\] 1 2 3 4 5 6 7 8 9 10\\n \$ strategy    : logi \[1:10\] NA NA NA NA NA NA \.\.\.\\n \$ a           : num \[1:10\] 2 2 2 2 2 2 2 2 2 2\\n \$ b           : num \[1:10\] 2 4 6 8 10 12 14 16 18 20"
  
  ── 3. Error: we can run construct_part_surv_tib (@test_part_surv.R#298)  ───────
  no applicable method for 'eval_surv' applied to an object of class "NULL"
  Backtrace:
   1. testthat::expect_equal(...)
   4. heemod::compute_surv(for_A[[1, "part_surv"]]$pfs, 1)
   6. heemod:::`_f`(...)
   7. heemod:::eval_surv(x, cycle_length * time_, ...)
  
  ── 4. Error: define sensitivity (@test_sensitivity.R#5)  ───────────────────────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::define_dsa(a, 10, 45, b, 0.5, 1.5)
    2. heemod:::define_dsa_(...)
    9. tibble::tibble(dots[i])
   10. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   11. tibble:::check_valid_col(res, col_names[[j]], j)
   12. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 5. Error: run sensitivity (@test_sensitivity.R#101)  ────────────────────────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::define_dsa(p1, 0.1, 0.9, p2, 0.1, 0.3)
    2. heemod:::define_dsa_(...)
    9. tibble::tibble(dots[i])
   10. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   11. tibble:::check_valid_col(res, col_names[[j]], j)
   12. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 6. Error: discount rate as a parameter works (@test_sensitivity.R#173)  ─────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::define_dsa(p1, 0.1, 0.9, p2, 0.1, 0.3, r, 0.05, 0.1)
    2. heemod:::define_dsa_(...)
    9. tibble::tibble(dots[i])
   10. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   11. tibble:::check_valid_col(res, col_names[[j]], j)
   12. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 7. Error: sensitivity expression inputs (@test_sensitivity.R#236)  ──────────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::define_dsa(p1, 0.1, 0.9, p2, p1 * 0.5, p1, r, 0.05, 0.1)
    2. heemod:::define_dsa_(...)
    9. tibble::tibble(dots[i])
   10. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   11. tibble:::check_valid_col(res, col_names[[j]], j)
   12. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 8. Error: can read multinomial parameters from file (@test_tabular_input.R#11
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod:::create_parameters_from_tabular(...)
    2. heemod:::define_dsa_(...)
    9. tibble::tibble(dots[i])
   10. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   11. tibble:::check_valid_col(res, col_names[[j]], j)
   12. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 9. Failure: Bad parameter file input is caught. (@test_tabular_input.R#379)  
  `heemod:::create_parameters_from_tabular(pb_par)` threw an error with unexpected message.
  Expected match: "No non-missing values in column 'psa'."
  Actual message: "All columns in a tibble must be vectors.\n✖ Column `dots[i]` is a `lazy_dots` object."
  Backtrace:
    1. testthat::expect_error(...)
    6. heemod:::create_parameters_from_tabular(pb_par)
    7. heemod:::define_dsa_(...)
   14. tibble::tibble(dots[i])
   15. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   16. tibble:::check_valid_col(res, col_names[[j]], j)
   17. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 10. Error: problems with output generate warnings (@test_tabular_input.R#470)
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. testthat::expect_warning(...)
    6. heemod::run_model_tabular(...)
    7. heemod:::gather_model_info(location, reference)
    8. heemod:::create_parameters_from_tabular(...)
    9. heemod:::define_dsa_(...)
   16. tibble::tibble(dots[i])
   17. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   18. tibble:::check_valid_col(res, col_names[[j]], j)
   19. tibble:::check_valid_cols(set_names(list(x), name))
  
  ── 11. Error: absolute path works  ─────────────────────────────────────────────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod:::gather_model_info(testdir, "edited_ref.csv")
    2. heemod:::create_parameters_from_tabular(...)
    3. heemod:::define_dsa_(...)
   10. tibble::tibble(dots[i])
   11. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   12. tibble:::check_valid_col(res, col_names[[j]], j)
   13. tibble:::check_valid_cols(set_names(list(x), name))
  
  A transition matrix, 5 states.
  
                     PrimaryTHR SuccessfulPrimary RevisionTHR    
  PrimaryTHR                    C                                
  SuccessfulPrimary             C                 pHRFailStandard
  RevisionTHR                                                    
  SuccessfulRevision                              0.04           
  Death                                                          
                     SuccessfulRevision Death
  PrimaryTHR                            0.02 
  SuccessfulPrimary                     mr   
  RevisionTHR        C                  0.02 
  SuccessfulRevision C                  mr   
  Death                                 1    
  A list of 5 states with 2 values each.
  
  State names:
  
  PrimaryTHR
  SuccessfulPrimary
  RevisionTHR
  SuccessfulRevision
  Death
  
  State values:
  
  cost
  qaly
  A transition matrix, 5 states.
  
                     PrimaryTHR SuccessfulPrimary RevisionTHR    
  PrimaryTHR                    C                                
  SuccessfulPrimary             C                 pHRFailStandard
  RevisionTHR                                                    
  SuccessfulRevision                              0.04           
  Death                                                          
                     SuccessfulRevision Death    
  PrimaryTHR                            0.02     
  SuccessfulPrimary                     mr       
  RevisionTHR        C                  0.02 + mr
  SuccessfulRevision C                  mr       
  Death                                 1        
  A list of 5 states with 2 values each.
  
  State names:
  
  PrimaryTHR
  SuccessfulPrimary
  RevisionTHR
  SuccessfulRevision
  Death
  
  State values:
  
  cost
  qaly
  A transition matrix, 5 states.
  
                     PrimaryTHR SuccessfulPrimary RevisionTHR SuccessfulRevision
  PrimaryTHR                    C                                               
  SuccessfulPrimary             C                 pHRFailNew                    
  RevisionTHR                                                 C                 
  SuccessfulRevision                              0.04        C                 
  Death                                                                         
                     Death    
  PrimaryTHR         0.02     
  SuccessfulPrimary  mr       
  RevisionTHR        0.02 + mr
  SuccessfulRevision mr       
  Death              1        
  ── 12. Error: Running model from files works. (@test_tabular_input.R#772)  ─────
  All columns in a tibble must be vectors.
  ✖ Column `dots[i]` is a `lazy_dots` object.
  Backtrace:
    1. heemod::run_model_tabular(...)
    2. heemod:::gather_model_info(location, reference)
    3. heemod:::create_parameters_from_tabular(...)
    4. heemod:::define_dsa_(...)
   11. tibble::tibble(dots[i])
   12. tibble:::tibble_quos(xs[!is_null], .rows, .name_repair)
   13. tibble:::check_valid_col(res, col_names[[j]], j)
   14. tibble:::check_valid_cols(set_names(list(x), name))
  
  ══ testthat results  ═══════════════════════════════════════════════════════════
  [ OK: 470 | SKIPPED: 0 | WARNINGS: 1 | FAILED: 12 ]
  1. Error: Same results using 1 core or 2. (@test_parallel.R#7) 
  2. Failure: Parameter evaluation (@test_parameters.R#81) 
  3. Error: we can run construct_part_surv_tib (@test_part_surv.R#298) 
  4. Error: define sensitivity (@test_sensitivity.R#5) 
  5. Error: run sensitivity (@test_sensitivity.R#101) 
  6. Error: discount rate as a parameter works (@test_sensitivity.R#173) 
  7. Error: sensitivity expression inputs (@test_sensitivity.R#236) 
  8. Error: can read multinomial parameters from file (@test_tabular_input.R#110) 
  9. Failure: Bad parameter file input is caught. (@test_tabular_input.R#379) 
  1. ...
  
  Error: testthat unit tests failed
  Execution halted