tests/testthat/_snaps/smogn.md

In themis: Extra Recipes Steps for Dealing with Unbalanced Data

bad distance arg for step_smogn()

Code
  bake(prep(step_smogn(recipe(y ~ x, data = circle_example), y, distance = "L2")),
  new_data = NULL)
Condition
  Error in `step_smogn()`:
  ! `distance` must be one of "euclidean", "cosine", "mahalanobis", "manhattan", "chebyshev", "squared_chord", "matusita", "hellinger", "bhattacharyya", "canberra", "soergel", "lorentzian", "jeffreys", "topsoe", "jensen-shannon", "jensen_difference", "taneja", or "kumar-johnson", not "L2".

errors if no rare values are found

Code
  prep(step_smogn(recipe(y ~ x, data = circle_example), y, relevance = rel))
Condition
  Error in `step_smogn()`:
  Caused by error in `bake()`:
  ! No rare values were found in `y` with the current `threshold`.
  i Lower `threshold` or supply relevance control points via `relevance`.

errors if relevance cannot be derived from a constant outcome

Code
  prep(step_smogn(recipe(y ~ x, data = df), y))
Condition
  Error in `step_smogn()`:
  Caused by error in `bake()`:
  ! Unable to determine rare values automatically for the outcome.
  i The outcome distribution is degenerate (zero interquartile range or heavily tied values), so relevance control points cannot be derived from its boxplot extremes.
  i Supply relevance control points via the `relevance` argument.

errors if relevance is not a two-column matrix

Code
  prep(step_smogn(rec, y, relevance = 1:3))
Condition
  Error in `step_smogn()`:
  Caused by error in `bake()`:
  ! `relevance` must be a matrix with at least two columns (outcome value and relevance).

Code
  prep(step_smogn(rec, y, relevance = matrix(1:3, ncol = 1)))
Condition
  Error in `step_smogn()`:
  Caused by error in `bake()`:
  ! `relevance` must be a matrix with at least two columns (outcome value and relevance).

bad data

Code
  prep(step_smogn(rec, class))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! `class` should be a numeric variable.

Code
  prep(step_smogn(rec, x, y))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! The selector should select at most a single variable.

errors if predictors are not numeric

Code
  prep(step_smogn(recipe(y ~ x + class, data = circle_example), y))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `class`

NA in data

Code
  prep(step_smogn(recipe(y ~ x, data = df), y))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! Cannot have any missing values. NAs found in x.

indicator_column bad args

Code
  step_smogn(recipe(y ~ x, data = circle_example), y, indicator_column = 1)
Condition
  Error in `step_smogn()`:
  ! `indicator_column` must be a single string or `NULL`, not the number 1.

Code
  prep(step_smogn(recipe(y ~ x, data = circle_example), y, indicator_column = "x"))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! Name collision occurred. The following variable names already exist:
  * `x`

bad args

Code
  prep(step_smogn(recipe(mpg ~ ., data = mtcars), mpg, threshold = 2))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! `threshold` must be a number between 0 and 1, not the number 2.

Code
  prep(step_smogn(recipe(mpg ~ ., data = mtcars), mpg, neighbors = TRUE))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! `neighbors` must be a whole number, not `TRUE`.

Code
  prep(step_smogn(recipe(mpg ~ ., data = mtcars), mpg, perturbation = -1))
Condition
  Error in `step_smogn()`:
  Caused by error in `prep()`:
  ! `perturbation` must be a number larger than or equal to 0, not the number -1.

Code
  step_smogn(recipe(mpg ~ ., data = mtcars), mpg, seed = TRUE)
Condition
  Error in `step_smogn()`:
  ! `seed` must be a whole number, not `TRUE`.

bake method errors when needed non-standard role columns are missing

Code
  bake(trained, new_data = circle_example[, -2])
Condition
  Error in `step_smogn()`:
  ! The following required column is missing from `new_data`: y.

empty printing

Code
  rec
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Operations 
  * SMOGN based on: <none>

Code
  rec
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * SMOGN based on: <none> | Trained

printing

Code
  print(rec)
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 1

  -- Operations 
  * SMOGN based on: y

Code
  prep(rec)
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:   1
  predictor: 1

  -- Training information 
  Training data contained 400 data points and no incomplete rows.

  -- Operations 
  * SMOGN based on: y | Trained

themis documentation built on Aug. 2, 2026, 9:07 a.m.