tests/testthat/_snaps/update.md

In parsnip: A Common API to Modeling and Analysis Functions

update methods work (eg: linear_reg)

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

  Main Arguments:
    mixture = 0

  Engine-Specific Arguments:
    model = FALSE

  Computational engine: lm

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

  Main Arguments:
    mixture = 0

  Computational engine: lm

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

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

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

  Main Arguments:
    penalty = tune()
    mixture = 0

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

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

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

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

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

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

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Engine-Specific Arguments:
    nlambda = 10

  Computational engine: glmnet

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

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Computational engine: glmnet

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

  Main Arguments:
    penalty = 1
    mixture = 0.5

  Computational engine: glmnet

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

  Engine-Specific Arguments:
    family = poisson

  Computational engine: glm

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

  Engine-Specific Arguments:
    family = poisson

  Computational engine: glm

update methods prompt informatively

Code
  expr1 %>% update(param_tibb)
Condition
  Error in `update_main_parameters()`:
  ! At least one argument is not a main argument: `nlambda`

Code
  expr1 %>% update(param_list)
Condition
  Error in `update_main_parameters()`:
  ! At least one argument is not a main argument: `nlambda`

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

Code
  expr1 %>% update(parameters = tibble::tibble(wat = "wat"))
Condition
  Error in `update_main_parameters()`:
  ! At least one argument is not a main argument: `wat`

Code
  linear_reg() %>% update(boop = 0)
Condition
  Error in `update_dot_check()`:
  ! Extra arguments will be ignored: `boop`

parsnip documentation built on Aug. 18, 2023, 1:07 a.m.