Running ‘testthat.R’ [164s/302s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > 
  > # Machine Learning
  > library(tidymodels)
  ── Attaching packages ────────────────────────────────────── tidymodels 1.3.0 ──
  ✔ broom        1.0.9     ✔ recipes      1.3.1
  ✔ dials        1.4.1     ✔ rsample      1.3.1
  ✔ dplyr        1.1.4     ✔ tibble       3.3.0
  ✔ ggplot2      3.5.2     ✔ tidyr        1.3.1
  ✔ infer        1.0.9     ✔ tune         2.0.0
  ✔ modeldata    1.5.1     ✔ workflows    1.3.0
  ✔ parsnip      1.3.3     ✔ workflowsets 1.1.1
  ✔ purrr        1.1.0     ✔ yardstick    1.3.2
  ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
  ✖ purrr::discard() masks scales::discard()
  ✖ dplyr::filter()  masks stats::filter()
  ✖ purrr::is_null() masks testthat::is_null()
  ✖ dplyr::lag()     masks stats::lag()
  ✖ tidyr::matches() masks rsample::matches(), dplyr::matches(), testthat::matches()
  ✖ recipes::step()  masks stats::step()
  > library(modeltime)
  > library(modeltime.ensemble)
  Loading required package: modeltime.resample
  > library(modeltime.resample)
  > 
  > # Model dependencies
  > library(xgboost)
  
  Attaching package: 'xgboost'
  
  The following object is masked from 'package:dplyr':
  
      slice
  
  > library(glmnet)
  Loading required package: Matrix
  
  Attaching package: 'Matrix'
  
  The following objects are masked from 'package:tidyr':
  
      expand, pack, unpack
  
  Loaded glmnet 4.1-10
  > 
  > # Core Packages
  > library(timetk)
  > library(lubridate)
  
  Attaching package: 'lubridate'
  
  The following objects are masked from 'package:base':
  
      date, intersect, setdiff, union
  
  > 
  > test_check("modeltime.ensemble")
  ── Modeltime Ensemble ───────────────────────────────────────────
  Ensemble of 3 Models (WEIGHTED) 
  
  # Modeltime Table
  # A tibble: 3 × 4
    .model_id .model     .model_desc             .loadings
        <int> <list>     <chr>                       <dbl>
  1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]     0.5  
  2         2 <workflow> PROPHET                     0.333
  3         3 <workflow> GLMNET                      0.167
  
  
  
  
  
  
  
  
  [ FAIL 1 | WARN 1 | SKIP 4 | PASS 85 ]
  
  ══ Skipped tests (4) ═══════════════════════════════════════════════════════════
  • On CRAN (4): 'test-conf_by_id.R:6:5', 'test-ensemble_average.R:57:5',
    'test-ensemble_model_spec.R:55:5', 'test-nested-ensembles.R:189:5'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-panel-data.R:175:5'): ensemble_model_spec(): Forecast Jumbled ──
  Error in `model.frame.default(formula = ..y ~ ., data = data, drop.unused.levels = TRUE)`: invalid type (list) for variable '.model_id_1'
  Backtrace:
       ▆
    1. ├─resample_tscv %>% ... at test-panel-data.R:175:5
    2. ├─modeltime.ensemble::ensemble_model_spec(...)
    3. ├─modeltime.ensemble:::ensemble_model_spec.mdl_time_tbl(...)
    4. │ └─modeltime.ensemble:::generate_stacking_results(...)
    5. │   └─wflw_spec %>% generics::fit(data_prepared_tbl)
    6. ├─generics::fit(., data_prepared_tbl)
    7. ├─workflows:::fit.workflow(., data_prepared_tbl)
    8. │ └─workflows::.fit_model(workflow, control)
    9. │   ├─generics::fit(action_model, workflow = workflow, control = control)
   10. │   └─workflows:::fit.action_model(...)
   11. │     └─workflows:::fit_from_xy(spec, mold, case_weights, control_parsnip)
   12. │       ├─generics::fit_xy(...)
   13. │       └─parsnip::fit_xy.model_spec(...)
   14. │         └─parsnip:::xy_form(...)
   15. │           └─parsnip:::form_form(...)
   16. │             └─parsnip:::eval_mod(...)
   17. │               └─rlang::eval_tidy(e, env = envir, ...)
   18. └─stats::lm(formula = ..y ~ ., data = data)
   19.   └─base::eval(mf, parent.frame())
   20.     └─base::eval(mf, parent.frame())
   21.       ├─stats::model.frame(formula = ..y ~ ., data = data, drop.unused.levels = TRUE)
   22.       └─stats::model.frame.default(formula = ..y ~ ., data = data, drop.unused.levels = TRUE)
  
  [ FAIL 1 | WARN 1 | SKIP 4 | PASS 85 ]
  Error: Test failures
  Execution halted