tests/testthat/_snaps/update.md

In parsnip: A Common API to Modeling and Analysis Functions

update methods work (eg: linear_reg)

Code
  update(expr1, mixture = 0)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    mixture = 0

  Engine-Specific Arguments:
    model = FALSE

  Computational engine: lm

Code
  update(expr1, mixture = 0, fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    mixture = 0

  Computational engine: lm

Code
  update(expr2, nlambda = 10)
Output
  Linear Regression Model Specification (regression)

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr3, mixture = 1, nlambda = 10)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = tune()
    mixture = 1

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr3, mixture = 1, nlambda = 10, fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    mixture = 1

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr3, nlambda = 10)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = tune()
    mixture = 0

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr3, nlambda = 10, fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr4, param_tibb)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr4, param_list)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

Code
  update(expr4, param_tibb, fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Computational engine: glmnet

Code
  update(expr4, param_list, fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Computational engine: glmnet

Code
  update(expr5, family = "poisson")
Output
  Linear Regression Model Specification (regression)

  Engine-Specific Arguments:
    family = poisson

  Computational engine: glm

Code
  update(expr5, family = "poisson", fresh = TRUE)
Output
  Linear Regression Model Specification (regression)

  Engine-Specific Arguments:
    family = poisson

  Computational engine: glm

update methods prompt informatively

Code
  update(expr1, param_tibb)
Condition
  Error in `update()`:
  ! Argument `nlambda` is not a main argument.

Code
  update(expr1, param_list)
Condition
  Error in `update()`:
  ! Argument `nlambda` is not a main argument.

Code
  update(expr1, parameters = "wat")
Condition
  Error in `update()`:
  ! The parameter object should be a list or tibble.

Code
  update(expr1, parameters = tibble::tibble(wat = "wat"))
Condition
  Error in `update()`:
  ! Argument `wat` is not a main argument.

Code
  update(linear_reg(), boop = 0)
Condition
  Error in `update_dot_check()`:
  ! The extra argument `boop` will be ignored.

parsnip documentation built on June 8, 2025, 12:10 p.m.