fair-aaa.md
In yardstick: Tidy Characterizations of Model Performance

metric factory print method works

Code
  equal_opportunity
Output
  A metric factory (`?yardstick::new_groupwise_metric()`)

handles `direction` input

Code
  new_groupwise_metric(sens, "bad_direction", diff_range, direction = "boop")
Condition
  Error in `new_groupwise_metric()`:
  ! `direction` must be one of "maximize", "minimize", or "zero", not "boop".

errors informatively with bad input

Code
  new_groupwise_metric()
Condition
  Error in `new_groupwise_metric()`:
  ! `fn` must be a metric function or metric set.

Code
  new_groupwise_metric(sens)
Condition
  Error in `new_groupwise_metric()`:
  ! `name` must be a string.

Code
  new_groupwise_metric(sens, "bop")
Condition
  Error in `new_groupwise_metric()`:
  ! `aggregate` must be a function.

Code
  new_groupwise_metric("boop", "bop", identity)
Condition
  Error in `new_groupwise_metric()`:
  ! `fn` must be a metric function or metric set.

Code
  new_groupwise_metric(identity, "bop", identity)
Condition
  Error in `new_groupwise_metric()`:
  ! `fn` must be a metric function or metric set.

Code
  new_groupwise_metric(sens, 1, identity)
Condition
  Error in `new_groupwise_metric()`:
  ! `name` must be a string.

Code
  new_groupwise_metric(sens, "bop", "boop")
Condition
  Error in `new_groupwise_metric()`:
  ! `aggregate` must be a function.

outputted function errors informatively with bad input

Code
  bad_aggregate(Resample)(hpc_cv, truth = obs, estimate = pred)
Condition
  Error in `new_groupwise_metric()`:
  ! `aggregate` must return a single numeric value.

Code
  bad_by(hpc_cv, truth = obs, estimate = pred)
Condition
  Error in `dplyr::group_by()`:
  ! Must group by variables found in `.data`.
  x Column `nonexistent_column` is not found.

Code
  bad_truth_metric_set(hpc_cv, truth = VF, estimate = pred)
Condition
  Error in `bop()`:
  ! `truth` should be a factor, not a a double vector.

Code
  bad_truth_metric(hpc_cv, truth = VF, estimate = pred)
Condition
  Error in `bop()`:
  ! `truth` should be a factor, not a a double vector.

outputted function errors informatively with redundant grouping

Code
  hpc_cv %>% dplyr::group_by(Resample) %>% demographic_parity(Resample)(truth = obs,
    estimate = pred)
Condition
  Error:
  ! Metric is internally grouped by Resample; grouping `data` by Resample is not well-defined.

Code
  hpc_cv %>% dplyr::group_by(Resample) %>% dp_res(truth = obs, estimate = pred)
Condition
  Error in `dp_res()`:
  ! Metric is internally grouped by Resample; grouping `data` by Resample is not well-defined.