Groupwise metrics not working with finetune

[Saarialho]

The problem

I'm having trouble with using groupwise metrics with finetune

Reproducible example

pacman::p_load(tidymodels, finetune)
data(ames)

diff_range <- function(x) {
  diff(range(x$.estimate))
}
demographic_parity_ <-
  new_groupwise_metric(
    fn = detection_prevalence,
    name = "demographic_parity",
    aggregate = diff_range
  )

m_set <- metric_set(demographic_parity_(Neighborhood))

set.seed(502)
ames_split <- initial_split(ames)
ames_train <- training(ames_split)
ames_folds <- vfold_cv(ames_train, v = 10)

rf_model <-
  rand_forest(trees = tune()) %>%
  set_engine("ranger") %>%
  set_mode("classification")

rf_wflow <-
  workflow() %>%
  add_formula(
    Lot_Shape ~ Year_Built + Bldg_Type + Latitude + Longitude
  ) %>%
  add_model(rf_model)

grid <- parameters(trees(c(10, 100))) %>%
  grid_max_entropy(size = 10)

tune_res_anova <- tune_race_anova(
  rf_wflow,
  ames_folds,
  grid = grid,
  metrics = m_set
)
#> Warning in max(best_config$B, na.rm = TRUE): no non-missing arguments to max;
#> returning -Inf
#> Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]): contrasts can be applied only to factors with 2 or more levels
#> Warning: package 'ranger' was built under R version 4.2.3
#> Warning: package 'rlang' was built under R version 4.2.3
#> Warning in max(best_config$B, na.rm = TRUE): no non-missing arguments to max;
#> returning -Inf
#> Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]): contrasts can be applied only to factors with 2 or more levels

^{Created on 2024-08-30 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.2.1 (2022-06-23 ucrt)
#>  os       Windows 10 x64 (build 19045)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  Finnish_Finland.utf8
#>  ctype    Finnish_Finland.utf8
#>  tz       Europe/Helsinki
#>  date     2024-08-30
#>  pandoc   2.18 @ C:/Program Files/RStudio/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package      * version     date (UTC) lib source
#>  backports      1.4.1       2021-12-13 [1] CRAN (R 4.2.0)
#>  boot           1.3-28      2021-05-03 [1] CRAN (R 4.2.1)
#>  broom        * 1.0.5       2023-06-09 [1] CRAN (R 4.2.1)
#>  class          7.3-20      2022-01-16 [1] CRAN (R 4.2.1)
#>  cli            3.6.1       2023-03-23 [1] CRAN (R 4.2.3)
#>  codetools      0.2-18      2020-11-04 [1] CRAN (R 4.2.1)
#>  colorspace     2.1-0       2023-01-23 [1] CRAN (R 4.2.3)
#>  data.table     1.14.2      2021-09-27 [1] CRAN (R 4.2.1)
#>  dials        * 1.2.0       2023-04-03 [1] CRAN (R 4.2.3)
#>  DiceDesign     1.9         2021-02-13 [1] CRAN (R 4.2.1)
#>  digest         0.6.30      2022-10-18 [1] CRAN (R 4.2.2)
#>  dplyr        * 1.1.4       2023-11-17 [1] CRAN (R 4.2.3)
#>  evaluate       0.23        2023-11-01 [1] CRAN (R 4.2.3)
#>  fansi          1.0.6       2023-12-08 [1] CRAN (R 4.2.3)
#>  fastmap        1.1.0       2021-01-25 [1] CRAN (R 4.2.1)
#>  finetune     * 1.1.0       2023-04-19 [1] CRAN (R 4.2.3)
#>  foreach        1.5.2       2022-02-02 [1] CRAN (R 4.2.1)
#>  fs             1.5.2       2021-12-08 [1] CRAN (R 4.2.1)
#>  furrr          0.3.1       2022-08-15 [1] CRAN (R 4.2.1)
#>  future         1.33.0      2023-07-01 [1] CRAN (R 4.2.3)
#>  future.apply   1.11.0      2023-05-21 [1] CRAN (R 4.2.3)
#>  generics       0.1.3       2022-07-05 [1] CRAN (R 4.2.1)
#>  ggplot2      * 3.5.0       2024-02-23 [1] CRAN (R 4.2.3)
#>  globals        0.16.2      2022-11-21 [1] CRAN (R 4.2.1)
#>  glue           1.6.2       2022-02-24 [1] CRAN (R 4.2.1)
#>  gower          1.0.1       2022-12-22 [1] CRAN (R 4.2.2)
#>  GPfit          1.0-8       2019-02-08 [1] CRAN (R 4.2.1)
#>  gtable         0.3.5       2024-04-22 [1] CRAN (R 4.2.1)
#>  hardhat        1.3.1.9000  2024-04-11 [1] Github (tidymodels/hardhat@ed8b032)
#>  htmltools      0.5.7       2023-11-03 [1] CRAN (R 4.2.3)
#>  infer        * 1.0.4       2022-12-02 [1] CRAN (R 4.2.3)
#>  ipred          0.9-14      2023-03-09 [1] CRAN (R 4.2.3)
#>  iterators      1.0.14      2022-02-05 [1] CRAN (R 4.2.1)
#>  knitr          1.45        2023-10-30 [1] CRAN (R 4.2.3)
#>  lattice        0.20-45     2021-09-22 [1] CRAN (R 4.2.1)
#>  lava           1.7.2.1     2023-02-27 [1] CRAN (R 4.2.3)
#>  lhs            1.1.5       2022-03-22 [1] CRAN (R 4.2.1)
#>  lifecycle      1.0.4       2023-11-07 [1] CRAN (R 4.2.3)
#>  listenv        0.9.0       2022-12-16 [1] CRAN (R 4.2.3)
#>  lme4           1.1-30      2022-07-08 [1] CRAN (R 4.2.1)
#>  lubridate      1.9.0       2022-11-06 [1] CRAN (R 4.2.2)
#>  magrittr       2.0.3       2022-03-30 [1] CRAN (R 4.2.1)
#>  MASS           7.3-58.1    2022-08-03 [1] CRAN (R 4.2.1)
#>  Matrix         1.5-3       2022-11-11 [1] CRAN (R 4.2.2)
#>  minqa          1.2.4       2014-10-09 [1] CRAN (R 4.2.1)
#>  modeldata    * 1.3.0       2024-01-21 [1] CRAN (R 4.2.3)
#>  modelenv       0.1.0       2022-10-17 [1] CRAN (R 4.2.2)
#>  munsell        0.5.1       2024-04-01 [1] CRAN (R 4.2.3)
#>  nlme           3.1-159     2022-08-09 [1] CRAN (R 4.2.1)
#>  nloptr         2.0.3       2022-05-26 [1] CRAN (R 4.2.1)
#>  nnet           7.3-17      2022-01-16 [1] CRAN (R 4.2.1)
#>  pacman         0.5.1       2019-03-11 [1] CRAN (R 4.2.1)
#>  parallelly     1.36.0      2023-05-26 [1] CRAN (R 4.2.3)
#>  parsnip      * 1.2.1.9001  2024-04-11 [1] Github (tidymodels/parsnip@853d814)
#>  pillar         1.9.0       2023-03-22 [1] CRAN (R 4.2.3)
#>  pkgconfig      2.0.3       2019-09-22 [1] CRAN (R 4.2.1)
#>  prodlim        2023.03.31  2023-04-02 [1] CRAN (R 4.2.3)
#>  purrr        * 1.0.2       2023-08-10 [1] CRAN (R 4.2.3)
#>  R.cache        0.16.0      2022-07-21 [1] CRAN (R 4.2.2)
#>  R.methodsS3    1.8.2       2022-06-13 [1] CRAN (R 4.2.0)
#>  R.oo           1.25.0      2022-06-12 [1] CRAN (R 4.2.0)
#>  R.utils        2.12.2      2022-11-11 [1] CRAN (R 4.2.2)
#>  R6             2.5.1       2021-08-19 [1] CRAN (R 4.2.1)
#>  ranger       * 0.15.1      2023-04-03 [1] CRAN (R 4.2.3)
#>  Rcpp           1.0.9       2022-07-08 [1] CRAN (R 4.2.1)
#>  recipes      * 1.0.10.9000 2024-04-11 [1] Github (tidymodels/recipes@63ced27)
#>  reprex         2.0.2       2022-08-17 [1] CRAN (R 4.2.1)
#>  rlang        * 1.1.3       2024-01-10 [1] CRAN (R 4.2.3)
#>  rmarkdown      2.25        2023-09-18 [1] CRAN (R 4.2.3)
#>  rpart          4.1.16      2022-01-24 [1] CRAN (R 4.2.1)
#>  rsample      * 1.2.0       2023-08-23 [1] CRAN (R 4.2.3)
#>  rstudioapi     0.15.0.9000 2024-02-29 [1] Github (rstudio/rstudioapi@5b639f9)
#>  scales       * 1.3.0       2023-11-28 [1] CRAN (R 4.2.3)
#>  sessioninfo    1.2.2       2021-12-06 [1] CRAN (R 4.2.1)
#>  styler         1.10.2      2023-08-29 [1] CRAN (R 4.2.3)
#>  survival       3.4-0       2022-08-09 [1] CRAN (R 4.2.1)
#>  tibble       * 3.2.1       2023-03-20 [1] CRAN (R 4.2.3)
#>  tidymodels   * 1.1.1       2023-08-24 [1] CRAN (R 4.2.3)
#>  tidyr        * 1.3.1       2024-01-24 [1] CRAN (R 4.2.3)
#>  tidyselect     1.2.1       2024-03-11 [1] CRAN (R 4.2.3)
#>  timechange     0.1.1       2022-11-04 [1] CRAN (R 4.2.2)
#>  timeDate       4022.108    2023-01-07 [1] CRAN (R 4.2.3)
#>  tune         * 1.2.1       2024-04-18 [1] CRAN (R 4.2.3)
#>  utf8           1.2.4       2023-10-22 [1] CRAN (R 4.2.3)
#>  vctrs          0.6.5       2023-12-01 [1] CRAN (R 4.2.3)
#>  withr          3.0.1       2024-07-31 [1] CRAN (R 4.2.1)
#>  workflows    * 1.1.4.9000  2024-04-22 [1] Github (tidymodels/workflows@89005f5)
#>  workflowsets * 1.0.1       2023-04-06 [1] CRAN (R 4.2.3)
#>  xfun           0.42        2024-02-08 [1] CRAN (R 4.2.3)
#>  yaml           2.3.8       2023-12-11 [1] CRAN (R 4.2.3)
#>  yardstick    * 1.3.0       2024-01-19 [1] CRAN (R 4.2.3)
#> 
#>  [1] C:/Users/saariea/R-4.2.1/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────

[simonpcouch]

Just noting that I can reproduce this and 1) don't see the failure with tune_grid() nor 2) with detection_prevalence on its own! Will revisit this when we're focused in on the package again—thanks for the reprex.