tests/testthat/_snaps/tune_cluster.md

In tidyclust: A Common API to Clustering

verbose argument works

Code
  res <- tune_cluster(wflow, resamples = folds, grid = grid, control = control,
    metrics = metrics)
Message
  i Fold1: preprocessor 1/3
  i Fold1: preprocessor 1/3 (prediction data)
  i Fold1: preprocessor 1/3, model 1/3
  i Fold1: preprocessor 1/3, model 1/3 (model metrics)
  i Fold1: preprocessor 1/3, model 1/3 (extracts)
  i Fold1: preprocessor 1/3, model 2/3
  i Fold1: preprocessor 1/3, model 2/3 (model metrics)
  i Fold1: preprocessor 1/3, model 2/3 (extracts)
  i Fold1: preprocessor 1/3, model 3/3
  i Fold1: preprocessor 1/3, model 3/3 (model metrics)
  i Fold1: preprocessor 1/3, model 3/3 (extracts)
  i Fold1: preprocessor 2/3
  i Fold1: preprocessor 2/3 (prediction data)
  i Fold1: preprocessor 2/3, model 1/3
  i Fold1: preprocessor 2/3, model 1/3 (model metrics)
  i Fold1: preprocessor 2/3, model 1/3 (extracts)
  i Fold1: preprocessor 2/3, model 2/3
  i Fold1: preprocessor 2/3, model 2/3 (model metrics)
  i Fold1: preprocessor 2/3, model 2/3 (extracts)
  i Fold1: preprocessor 2/3, model 3/3
  i Fold1: preprocessor 2/3, model 3/3 (model metrics)
  i Fold1: preprocessor 2/3, model 3/3 (extracts)
  i Fold1: preprocessor 3/3
  i Fold1: preprocessor 3/3 (prediction data)
  i Fold1: preprocessor 3/3, model 1/3
  i Fold1: preprocessor 3/3, model 1/3 (model metrics)
  i Fold1: preprocessor 3/3, model 1/3 (extracts)
  i Fold1: preprocessor 3/3, model 2/3
  i Fold1: preprocessor 3/3, model 2/3 (model metrics)
  i Fold1: preprocessor 3/3, model 2/3 (extracts)
  i Fold1: preprocessor 3/3, model 3/3
  i Fold1: preprocessor 3/3, model 3/3 (model metrics)
  i Fold1: preprocessor 3/3, model 3/3 (extracts)
  i Fold2: preprocessor 1/3
  i Fold2: preprocessor 1/3 (prediction data)
  i Fold2: preprocessor 1/3, model 1/3
  i Fold2: preprocessor 1/3, model 1/3 (model metrics)
  i Fold2: preprocessor 1/3, model 1/3 (extracts)
  i Fold2: preprocessor 1/3, model 2/3
  i Fold2: preprocessor 1/3, model 2/3 (model metrics)
  i Fold2: preprocessor 1/3, model 2/3 (extracts)
  i Fold2: preprocessor 1/3, model 3/3
  i Fold2: preprocessor 1/3, model 3/3 (model metrics)
  i Fold2: preprocessor 1/3, model 3/3 (extracts)
  i Fold2: preprocessor 2/3
  i Fold2: preprocessor 2/3 (prediction data)
  i Fold2: preprocessor 2/3, model 1/3
  i Fold2: preprocessor 2/3, model 1/3 (model metrics)
  i Fold2: preprocessor 2/3, model 1/3 (extracts)
  i Fold2: preprocessor 2/3, model 2/3
  i Fold2: preprocessor 2/3, model 2/3 (model metrics)
  i Fold2: preprocessor 2/3, model 2/3 (extracts)
  i Fold2: preprocessor 2/3, model 3/3
  i Fold2: preprocessor 2/3, model 3/3 (model metrics)
  i Fold2: preprocessor 2/3, model 3/3 (extracts)
  i Fold2: preprocessor 3/3
  i Fold2: preprocessor 3/3 (prediction data)
  i Fold2: preprocessor 3/3, model 1/3
  i Fold2: preprocessor 3/3, model 1/3 (model metrics)
  i Fold2: preprocessor 3/3, model 1/3 (extracts)
  i Fold2: preprocessor 3/3, model 2/3
  i Fold2: preprocessor 3/3, model 2/3 (model metrics)
  i Fold2: preprocessor 3/3, model 2/3 (extracts)
  i Fold2: preprocessor 3/3, model 3/3
  i Fold2: preprocessor 3/3, model 3/3 (model metrics)
  i Fold2: preprocessor 3/3, model 3/3 (extracts)

tune model only - failure in formula is caught elegantly

Code
  cars_res <- tune_cluster(helper_objects$kmeans_mod, ~z, resamples = data_folds,
  grid = cars_grid, control = tune::control_grid(extract = function(x) {
    1
  }, save_pred = TRUE))
Message
  > A | error:   The following predictor was not found in `data`: "z".
Condition
  Warning:
  All models failed.
  i See the `.notes` column.

argument order gives errors for recipes

Code
  tune_cluster(helper_objects$rec_tune_1, helper_objects$kmeans_mod_no_tune,
  rsample::vfold_cv(mtcars, v = 2))
Condition
  Error in `tune_cluster()`:
  ! The first argument to `tune_cluster()` should be either a model or workflow.

argument order gives errors for formula

Code
  tune_cluster(mpg ~ ., helper_objects$kmeans_mod_no_tune, rsample::vfold_cv(
    mtcars, v = 2))
Condition
  Error in `tune_cluster()`:
  ! The first argument to `tune_cluster()` should be either a model or workflow.

ellipses with tune_cluster

Code
  tune_cluster(wflow, resamples = folds, grid = 3, something = "wrong")
Condition
  Warning:
  The `...` are not used in this function but 1 object was passed: "something"
Output
  # Tuning results
  # 2-fold cross-validation 
  # A tibble: 2 x 4
    splits          id    .metrics         .notes          
    <list>          <chr> <list>           <list>          
  1 <split [16/16]> Fold1 <tibble [6 x 5]> <tibble [0 x 4]>
  2 <split [16/16]> Fold2 <tibble [6 x 5]> <tibble [0 x 4]>

select_best() and show_best() works

Code
  tmp <- tune::show_best(res)
Condition
  Warning in `tune::show_best()`:
  No value of `metric` was given; "sse_within_total" will be used.

Code
  tmp <- tune::select_best(res)
Condition
  Warning in `tune::select_best()`:
  No value of `metric` was given; "sse_within_total" will be used.

check_grid warns when no tuning parameters detected

Code
  res <- tune_cluster(wflow, resamples = folds, grid = grid)
Condition
  Warning:
  No tuning parameters have been detected, performance will be evaluated using the resamples with no tuning.
  i Did you want to `tune()` parameters?

check_grid errors when grid is not a data frame

Code
  tune_cluster(wflow, resamples = folds, grid = "not a grid")
Condition
  Error in `check_grid()`:
  ! `grid` should be a positive integer or a data frame.

check_grid warns when duplicate rows in grid

Code
  res <- tune_cluster(wflow, resamples = folds, grid = grid)
Condition
  Warning:
  Duplicate rows in grid of tuning combinations found and removed.

check_grid errors when grid has extra params

Code
  tune_cluster(wflow, resamples = folds, grid = grid)
Condition
  Error in `check_grid()`:
  ! The provided `grid` has parameter column 'extra_param' that has not been marked for tuning by `tune()`.

check_grid errors when grid is missing params

Code
  tune_cluster(wflow, resamples = folds, grid = grid)
Condition
  Error in `check_grid()`:
  ! The provided `grid` is missing parameter column "'num_comp'" that has been marked for tuning by `tune()`.

check_grid errors when numeric grid < 1

Code
  tune_cluster(wflow, resamples = folds, grid = 0)
Condition
  Error in `check_grid()`:
  ! `grid` should be a positive integer or a data frame.

tune_cluster warns on apparent resamples

Code
  tune_cluster(wflow, resamples = apparent_rs, grid = grid)
Condition
  Warning:
  `tune_cluster()` was passed an `apparent()` resample.
  i Metrics from apparent resamples are excluded when summarizing with `collect_metrics(summarize = TRUE)` (the default). Use `collect_metrics(summarize = FALSE)` to see per-resample metrics.
Output
  # Tuning results
  # Apparent sampling 
  # A tibble: 1 x 4
    splits          id       .metrics         .notes          
    <list>          <chr>    <list>           <list>          
  1 <split [32/32]> Apparent <tibble [4 x 5]> <tibble [0 x 4]>

tidyclust documentation built on June 20, 2026, 9:08 a.m.