diff --git a/DESCRIPTION b/DESCRIPTION index 17e687a84..71cc57e76 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: parsnip Title: A Common API to Modeling and Analysis Functions -Version: 1.3.1.9000 +Version: 1.3.2 Authors@R: c( person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")), person("Davis", "Vaughan", , "davis@posit.co", role = "aut"), diff --git a/NEWS.md b/NEWS.md index 1ab48e6bd..65941d95b 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,10 @@ -# parsnip (development version) +# parsnip 1.3.2 + +* Switch to base R pipe + +* Requires changes for CRAN's "No Suggests" check. + +* Avoid issues with reading from package files. (#1271) # parsnip 1.3.1 diff --git a/R/aaa_archive.R b/R/aaa_archive.R index df98d84bd..01e0397bf 100644 --- a/R/aaa_archive.R +++ b/R/aaa_archive.R @@ -1,147 +1,148 @@ # no fmt model_info_table <- - tibble::tribble( - ~model, ~mode, ~engine, ~pkg, - "C5_rules", "classification", "C5.0", "rules", - "auto_ml", "classification", "h2o", "agua", - "auto_ml", "regression", "h2o", "agua", - "bag_mars", "classification", "earth", "baguette", - "bag_mars", "regression", "earth", "baguette", - "bag_mlp", "classification", "nnet", "baguette", - "bag_mlp", "regression", "nnet", "baguette", - "bag_tree", "censored regression", "rpart", "censored", - "bag_tree", "classification", "C5.0", "baguette", - "bag_tree", "classification", "rpart", "baguette", - "bag_tree", "regression", "rpart", "baguette", - "bart", "classification", "dbarts", NA, - "bart", "regression", "dbarts", NA, - "boost_tree", "censored regression", "mboost", "censored", - "boost_tree", "classification", "C5.0", NA, - "boost_tree", "classification", "h2o", "agua", - "boost_tree", "classification", "h2o_gbm", "agua", - "boost_tree", "classification", "lightgbm", "bonsai", - "boost_tree", "classification", "spark", NA, - "boost_tree", "classification", "xgboost", NA, - "boost_tree", "regression", "h2o", "agua", - "boost_tree", "regression", "h2o_gbm", "agua", - "boost_tree", "regression", "lightgbm", "bonsai", - "boost_tree", "regression", "spark", NA, - "boost_tree", "regression", "xgboost", NA, - "cubist_rules", "regression", "Cubist", "rules", - "decision_tree", "censored regression", "partykit", "censored", - "decision_tree", "censored regression", "rpart", "censored", - "decision_tree", "classification", "C5.0", NA, - "decision_tree", "classification", "partykit", "bonsai", - "decision_tree", "classification", "rpart", NA, - "decision_tree", "classification", "spark", NA, - "decision_tree", "regression", "partykit", "bonsai", - "decision_tree", "regression", "rpart", NA, - "decision_tree", "regression", "spark", NA, - "discrim_flexible", "classification", "earth", "discrim", - "discrim_linear", "classification", "MASS", "discrim", - "discrim_linear", "classification", "mda", "discrim", - "discrim_linear", "classification", "sda", "discrim", - "discrim_linear", "classification", "sparsediscrim", "discrim", - "discrim_quad", "classification", "MASS", "discrim", - "discrim_quad", "classification", "sparsediscrim", "discrim", - "discrim_regularized", "classification", "klaR", "discrim", - "gen_additive_mod", "classification", "mgcv", NA, - "gen_additive_mod", "regression", "mgcv", NA, - "linear_reg", "quantile regression", "quantreg", NA, - "linear_reg", "regression", "brulee", NA, - "linear_reg", "regression", "gee", "multilevelmod", - "linear_reg", "regression", "glm", NA, - "linear_reg", "regression", "glmer", "multilevelmod", - "linear_reg", "regression", "glmnet", NA, - "linear_reg", "regression", "gls", "multilevelmod", - "linear_reg", "regression", "h2o", "agua", - "linear_reg", "regression", "keras", NA, - "linear_reg", "regression", "lm", NA, - "linear_reg", "regression", "lme", "multilevelmod", - "linear_reg", "regression", "lmer", "multilevelmod", - "linear_reg", "regression", "spark", NA, - "linear_reg", "regression", "stan", NA, - "linear_reg", "regression", "stan_glmer", "multilevelmod", - "logistic_reg", "classification", "LiblineaR", NA, - "logistic_reg", "classification", "brulee", NA, - "logistic_reg", "classification", "gee", "multilevelmod", - "logistic_reg", "classification", "glm", NA, - "logistic_reg", "classification", "glmer", "multilevelmod", - "logistic_reg", "classification", "glmnet", NA, - "logistic_reg", "classification", "h2o", "agua", - "logistic_reg", "classification", "keras", NA, - "logistic_reg", "classification", "spark", NA, - "logistic_reg", "classification", "stan", NA, - "logistic_reg", "classification", "stan_glmer", "multilevelmod", - "mars", "classification", "earth", NA, - "mars", "regression", "earth", NA, - "mlp", "classification", "brulee", NA, - "mlp", "classification", "brulee_two_layer", NA, - "mlp", "classification", "h2o", "agua", - "mlp", "classification", "keras", NA, - "mlp", "classification", "nnet", NA, - "mlp", "regression", "brulee", NA, - "mlp", "regression", "brulee_two_layer", NA, - "mlp", "regression", "h2o", "agua", - "mlp", "regression", "keras", NA, - "mlp", "regression", "nnet", NA, - "multinom_reg", "classification", "brulee", NA, - "multinom_reg", "classification", "glmnet", NA, - "multinom_reg", "classification", "h2o", "agua", - "multinom_reg", "classification", "keras", NA, - "multinom_reg", "classification", "nnet", NA, - "multinom_reg", "classification", "spark", NA, - "naive_Bayes", "classification", "h2o", "agua", - "naive_Bayes", "classification", "klaR", "discrim", - "naive_Bayes", "classification", "naivebayes", "discrim", - "nearest_neighbor", "classification", "kknn", NA, - "nearest_neighbor", "regression", "kknn", NA, - "null_model", "classification", "parsnip", NA, - "null_model", "regression", "parsnip", NA, - "pls", "classification", "mixOmics", "plsmod", - "pls", "regression", "mixOmics", "plsmod", - "poisson_reg", "regression", "gee", "multilevelmod", - "poisson_reg", "regression", "glm", "poissonreg", - "poisson_reg", "regression", "glmer", "multilevelmod", - "poisson_reg", "regression", "glmnet", "poissonreg", - "poisson_reg", "regression", "h2o", "agua", - "poisson_reg", "regression", "hurdle", "poissonreg", - "poisson_reg", "regression", "stan", "poissonreg", - "poisson_reg", "regression", "stan_glmer", "multilevelmod", - "poisson_reg", "regression", "zeroinfl", "poissonreg", - "proportional_hazards", "censored regression", "glmnet", "censored", - "proportional_hazards", "censored regression", "survival", "censored", - "rand_forest", "censored regression", "aorsf", "censored", - "rand_forest", "censored regression", "partykit", "censored", - "rand_forest", "classification", "aorsf", "bonsai", - "rand_forest", "classification", "h2o", "agua", - "rand_forest", "classification", "partykit", "bonsai", - "rand_forest", "classification", "randomForest", NA, - "rand_forest", "classification", "ranger", NA, - "rand_forest", "classification", "spark", NA, - "rand_forest", "regression", "aorsf", "bonsai", - "rand_forest", "regression", "h2o", "agua", - "rand_forest", "regression", "partykit", "bonsai", - "rand_forest", "regression", "randomForest", NA, - "rand_forest", "regression", "ranger", NA, - "rand_forest", "regression", "spark", NA, - "rule_fit", "classification", "h2o", "agua", - "rule_fit", "classification", "xrf", "rules", - "rule_fit", "regression", "h2o", "agua", - "rule_fit", "regression", "xrf", "rules", - "surv_reg", "regression", "flexsurv", NA, - "surv_reg", "regression", "survival", NA, - "survival_reg", "censored regression", "flexsurv", "censored", - "survival_reg", "censored regression", "flexsurvspline", "censored", - "survival_reg", "censored regression", "survival", "censored", - "svm_linear", "classification", "LiblineaR", NA, - "svm_linear", "classification", "kernlab", NA, - "svm_linear", "regression", "LiblineaR", NA, - "svm_linear", "regression", "kernlab", NA, - "svm_poly", "classification", "kernlab", NA, - "svm_poly", "regression", "kernlab", NA, - "svm_rbf", "classification", "kernlab", NA, - "svm_rbf", "classification", "liquidSVM", NA, - "svm_rbf", "regression", "kernlab", NA, - "svm_rbf", "regression", "liquidSVM", NA - ) + tibble::tribble( + ~model, ~mode, ~engine, ~pkg, + "bag_tree", "censored regression", "rpart", "censored", + "boost_tree", "censored regression", "mboost", "censored", + "decision_tree", "censored regression", "partykit", "censored", + "decision_tree", "censored regression", "rpart", "censored", + "proportional_hazards", "censored regression", "glmnet", "censored", + "proportional_hazards", "censored regression", "survival", "censored", + "rand_forest", "censored regression", "aorsf", "censored", + "rand_forest", "censored regression", "partykit", "censored", + "survival_reg", "censored regression", "flexsurv", "censored", + "survival_reg", "censored regression", "flexsurvspline", "censored", + "survival_reg", "censored regression", "survival", "censored", + "C5_rules", "classification", "C5.0", "rules", + "auto_ml", "classification", "h2o", "agua", + "bag_mars", "classification", "earth", "baguette", + "bag_mlp", "classification", "nnet", "baguette", + "bag_tree", "classification", "C5.0", "baguette", + "bag_tree", "classification", "rpart", "baguette", + "bart", "classification", "dbarts", NA, + "boost_tree", "classification", "C5.0", NA, + "boost_tree", "classification", "h2o", "agua", + "boost_tree", "classification", "h2o_gbm", "agua", + "boost_tree", "classification", "lightgbm", "bonsai", + "boost_tree", "classification", "spark", NA, + "boost_tree", "classification", "xgboost", NA, + "decision_tree", "classification", "C5.0", NA, + "decision_tree", "classification", "partykit", "bonsai", + "decision_tree", "classification", "rpart", NA, + "decision_tree", "classification", "spark", NA, + "discrim_flexible", "classification", "earth", "discrim", + "discrim_linear", "classification", "MASS", "discrim", + "discrim_linear", "classification", "mda", "discrim", + "discrim_linear", "classification", "sda", "discrim", + "discrim_linear", "classification", "sparsediscrim", "discrim", + "discrim_quad", "classification", "MASS", "discrim", + "discrim_quad", "classification", "sparsediscrim", "discrim", + "discrim_regularized", "classification", "klaR", "discrim", + "gen_additive_mod", "classification", "mgcv", NA, + "logistic_reg", "classification", "LiblineaR", NA, + "logistic_reg", "classification", "brulee", NA, + "logistic_reg", "classification", "gee", "multilevelmod", + "logistic_reg", "classification", "glm", NA, + "logistic_reg", "classification", "glmer", "multilevelmod", + "logistic_reg", "classification", "glmnet", NA, + "logistic_reg", "classification", "h2o", "agua", + "logistic_reg", "classification", "keras", NA, + "logistic_reg", "classification", "spark", NA, + "logistic_reg", "classification", "stan", NA, + "logistic_reg", "classification", "stan_glmer", "multilevelmod", + "mars", "classification", "earth", NA, + "mlp", "classification", "brulee", NA, + "mlp", "classification", "brulee_two_layer", NA, + "mlp", "classification", "h2o", "agua", + "mlp", "classification", "keras", NA, + "mlp", "classification", "nnet", NA, + "multinom_reg", "classification", "brulee", NA, + "multinom_reg", "classification", "glmnet", NA, + "multinom_reg", "classification", "h2o", "agua", + "multinom_reg", "classification", "keras", NA, + "multinom_reg", "classification", "nnet", NA, + "multinom_reg", "classification", "spark", NA, + "naive_Bayes", "classification", "h2o", "agua", + "naive_Bayes", "classification", "klaR", "discrim", + "naive_Bayes", "classification", "naivebayes", "discrim", + "nearest_neighbor", "classification", "kknn", NA, + "null_model", "classification", "parsnip", NA, + "pls", "classification", "mixOmics", "plsmod", + "rand_forest", "classification", "aorsf", "bonsai", + "rand_forest", "classification", "h2o", "agua", + "rand_forest", "classification", "partykit", "bonsai", + "rand_forest", "classification", "randomForest", NA, + "rand_forest", "classification", "ranger", NA, + "rand_forest", "classification", "spark", NA, + "rule_fit", "classification", "h2o", "agua", + "rule_fit", "classification", "xrf", "rules", + "svm_linear", "classification", "LiblineaR", NA, + "svm_linear", "classification", "kernlab", NA, + "svm_poly", "classification", "kernlab", NA, + "svm_rbf", "classification", "kernlab", NA, + "svm_rbf", "classification", "liquidSVM", NA, + "linear_reg", "quantile regression", "quantreg", NA, + "auto_ml", "regression", "h2o", "agua", + "bag_mars", "regression", "earth", "baguette", + "bag_mlp", "regression", "nnet", "baguette", + "bag_tree", "regression", "rpart", "baguette", + "bart", "regression", "dbarts", NA, + "boost_tree", "regression", "h2o", "agua", + "boost_tree", "regression", "h2o_gbm", "agua", + "boost_tree", "regression", "lightgbm", "bonsai", + "boost_tree", "regression", "spark", NA, + "boost_tree", "regression", "xgboost", NA, + "cubist_rules", "regression", "Cubist", "rules", + "decision_tree", "regression", "partykit", "bonsai", + "decision_tree", "regression", "rpart", NA, + "decision_tree", "regression", "spark", NA, + "gen_additive_mod", "regression", "mgcv", NA, + "linear_reg", "regression", "brulee", NA, + "linear_reg", "regression", "gee", "multilevelmod", + "linear_reg", "regression", "glm", NA, + "linear_reg", "regression", "glmer", "multilevelmod", + "linear_reg", "regression", "glmnet", NA, + "linear_reg", "regression", "gls", "multilevelmod", + "linear_reg", "regression", "h2o", "agua", + "linear_reg", "regression", "keras", NA, + "linear_reg", "regression", "lm", NA, + "linear_reg", "regression", "lme", "multilevelmod", + "linear_reg", "regression", "lmer", "multilevelmod", + "linear_reg", "regression", "spark", NA, + "linear_reg", "regression", "stan", NA, + "linear_reg", "regression", "stan_glmer", "multilevelmod", + "mars", "regression", "earth", NA, + "mlp", "regression", "brulee", NA, + "mlp", "regression", "brulee_two_layer", NA, + "mlp", "regression", "h2o", "agua", + "mlp", "regression", "keras", NA, + "mlp", "regression", "nnet", NA, + "nearest_neighbor", "regression", "kknn", NA, + "null_model", "regression", "parsnip", NA, + "pls", "regression", "mixOmics", "plsmod", + "poisson_reg", "regression", "gee", "multilevelmod", + "poisson_reg", "regression", "glm", "poissonreg", + "poisson_reg", "regression", "glmer", "multilevelmod", + "poisson_reg", "regression", "glmnet", "poissonreg", + "poisson_reg", "regression", "h2o", "agua", + "poisson_reg", "regression", "hurdle", "poissonreg", + "poisson_reg", "regression", "stan", "poissonreg", + "poisson_reg", "regression", "stan_glmer", "multilevelmod", + "poisson_reg", "regression", "zeroinfl", "poissonreg", + "rand_forest", "regression", "aorsf", "bonsai", + "rand_forest", "regression", "h2o", "agua", + "rand_forest", "regression", "partykit", "bonsai", + "rand_forest", "regression", "randomForest", NA, + "rand_forest", "regression", "ranger", NA, + "rand_forest", "regression", "spark", NA, + "rule_fit", "regression", "h2o", "agua", + "rule_fit", "regression", "xrf", "rules", + "surv_reg", "regression", "flexsurv", NA, + "surv_reg", "regression", "survival", NA, + "svm_linear", "regression", "LiblineaR", NA, + "svm_linear", "regression", "kernlab", NA, + "svm_poly", "regression", "kernlab", NA, + "svm_rbf", "regression", "kernlab", NA, + "svm_rbf", "regression", "liquidSVM", NA + ) + diff --git a/R/boost_tree.R b/R/boost_tree.R index 29db77ebe..8e67bf999 100644 --- a/R/boost_tree.R +++ b/R/boost_tree.R @@ -552,7 +552,7 @@ xgb_by_tree <- function(tree, object, new_data, type, ...) { #' @param weights An optional numeric vector of case weights. Note #' that the data used for the case weights will not be used as a #' splitting variable in the model (see -#' \url{https://www.rulequest.com/see5-info.html} for +#' `https://www.rulequest.com/see5-info.html` for #' Quinlan's notes on case weights). #' @param minCases An integer for the smallest number of samples #' that must be put in at least two of the splits. diff --git a/R/engine_docs.R b/R/engine_docs.R index 1de60bad6..044d10af2 100644 --- a/R/engine_docs.R +++ b/R/engine_docs.R @@ -208,7 +208,7 @@ make_engine_list <- function(mod) { } exts <- - utils::read.delim(system.file("models.tsv", package = "parsnip")) |> + model_info_table |> dplyr::filter(model == mod) |> dplyr::group_by(engine, mode) |> dplyr::summarize(extensions = sum(!is.na(pkg)), .groups = "drop") |> diff --git a/man/C5.0_train.Rd b/man/C5.0_train.Rd index 264b85a6a..b9fe77c18 100644 --- a/man/C5.0_train.Rd +++ b/man/C5.0_train.Rd @@ -14,7 +14,7 @@ C5.0_train(x, y, weights = NULL, trials = 15, minCases = 2, sample = 0, ...) \item{weights}{An optional numeric vector of case weights. Note that the data used for the case weights will not be used as a splitting variable in the model (see -\url{https://www.rulequest.com/see5-info.html} for +\verb{https://www.rulequest.com/see5-info.html} for Quinlan's notes on case weights).} \item{trials}{An integer specifying the number of boosting diff --git a/man/details_bart_dbarts.Rd b/man/details_bart_dbarts.Rd index 2017b2046..53b80fa05 100644 --- a/man/details_bart_dbarts.Rd +++ b/man/details_bart_dbarts.Rd @@ -21,6 +21,8 @@ double, default: 2.00) \item \code{prior_outcome_range}: Prior for Outcome Range (type: double, default: 2.00) } + +Parsnip changes the default range for \code{trees} to \code{c(50, 500)}. } \subsection{Important engine-specific options}{ @@ -48,7 +50,7 @@ times number of observations. \subsection{Translation from parsnip to the original package (classification)}{ -\if{html}{\out{
}}\preformatted{bart( +\if{html}{\out{
}}\preformatted{parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -56,7 +58,8 @@ times number of observations. ) |> set_engine("dbarts") |> set_mode("classification") |> - translate() + translate() |> + print_model_spec() }\if{html}{\out{
}} \if{html}{\out{
}}\preformatted{## BART Model Specification (classification) @@ -78,7 +81,7 @@ times number of observations. \subsection{Translation from parsnip to the original package (regression)}{ -\if{html}{\out{
}}\preformatted{bart( +\if{html}{\out{
}}\preformatted{parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -86,7 +89,8 @@ times number of observations. ) |> set_engine("dbarts") |> set_mode("regression") |> - translate() + translate()|> + print_model_spec() }\if{html}{\out{
}} \if{html}{\out{
}}\preformatted{## BART Model Specification (regression) diff --git a/man/rmd/aaa.Rmd b/man/rmd/aaa.Rmd index acb6bd581..4f7761a54 100644 --- a/man/rmd/aaa.Rmd +++ b/man/rmd/aaa.Rmd @@ -32,7 +32,7 @@ check_pkg_for_docs(parsnip:::extensions()) make_mode_list <- function(mod, eng) { modes <- c("regression", "classification", "censored regression") exts <- - utils::read.delim(system.file("models.tsv", package = "parsnip")) |> + model_info_table |> dplyr::filter(model == mod & engine == eng) |> dplyr::mutate(mode = factor(mode, levels = modes)) |> dplyr::arrange(mode) @@ -128,7 +128,7 @@ descr_models <- function(mod, eng) { uses_extension <- function(mod, eng, mod_mode) { exts <- - utils::read.delim(system.file("models.tsv", package = "parsnip")) |> + model_info_table |> dplyr::filter( model == mod & engine == eng & diff --git a/man/rmd/bart_dbarts.Rmd b/man/rmd/bart_dbarts.Rmd index 09b5c08a9..95a737800 100644 --- a/man/rmd/bart_dbarts.Rmd +++ b/man/rmd/bart_dbarts.Rmd @@ -56,7 +56,7 @@ Some relevant arguments that can be passed to `set_engine()`: ```{r} #| label: bart-cls -bart( +parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -64,7 +64,8 @@ bart( ) |> set_engine("dbarts") |> set_mode("classification") |> - translate() + translate() |> + print_model_spec() ``` @@ -72,7 +73,7 @@ bart( ```{r} #| label: bart-reg -bart( +parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -80,7 +81,8 @@ bart( ) |> set_engine("dbarts") |> set_mode("regression") |> - translate() + translate()|> + print_model_spec() ``` ## Preprocessing requirements diff --git a/man/rmd/bart_dbarts.md b/man/rmd/bart_dbarts.md index ac7b9e453..1d9f0ab04 100644 --- a/man/rmd/bart_dbarts.md +++ b/man/rmd/bart_dbarts.md @@ -41,7 +41,7 @@ Some relevant arguments that can be passed to `set_engine()`: ``` r -bart( +parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -49,13 +49,25 @@ bart( ) |> set_engine("dbarts") |> set_mode("classification") |> - translate() + translate() |> + print_model_spec() ``` ``` +## BART Model Specification (classification) ## -## Call: -## NULL +## Main Arguments: +## trees = integer(1) +## prior_terminal_node_coef = double(1) +## prior_terminal_node_expo = double(1) +## prior_outcome_range = double(1) +## +## Computational engine: dbarts +## +## Model fit template: +## dbarts::bart(x = missing_arg(), y = missing_arg(), ntree = integer(1), +## base = double(1), power = double(1), k = double(1), verbose = FALSE, +## keeptrees = TRUE, keepcall = FALSE) ``` @@ -63,7 +75,7 @@ bart( ``` r -bart( +parsnip::bart( trees = integer(1), prior_terminal_node_coef = double(1), prior_terminal_node_expo = double(1), @@ -71,13 +83,25 @@ bart( ) |> set_engine("dbarts") |> set_mode("regression") |> - translate() + translate()|> + print_model_spec() ``` ``` +## BART Model Specification (regression) +## +## Main Arguments: +## trees = integer(1) +## prior_terminal_node_coef = double(1) +## prior_terminal_node_expo = double(1) +## prior_outcome_range = double(1) +## +## Computational engine: dbarts ## -## Call: -## NULL +## Model fit template: +## dbarts::bart(x = missing_arg(), y = missing_arg(), ntree = integer(1), +## base = double(1), power = double(1), k = double(1), verbose = FALSE, +## keeptrees = TRUE, keepcall = FALSE) ``` ## Preprocessing requirements diff --git a/tests/testthat/helper-objects.R b/tests/testthat/helper-objects.R index 96ced47a0..86f61ed78 100644 --- a/tests/testthat/helper-objects.R +++ b/tests/testthat/helper-objects.R @@ -113,3 +113,17 @@ if (rlang::is_installed("modeldata")) { } } +if (rlang::is_installed("survival")) { + data(cancer, package = "survival") + basic_form <- survival::Surv(time, status) ~ age + complete_form <- survival::Surv(time) ~ age + + if (R.Version()$major < "4") { + data(lung, package = 'survival') + } else { + data(cancer, package = 'survival') + } + + basic_form <- survival::Surv(time, status) ~ group + complete_form <- survival::Surv(time) ~ group +} diff --git a/tests/testthat/test-surv_reg_flexsurv.R b/tests/testthat/test-surv_reg_flexsurv.R index 273a47255..11da8531c 100644 --- a/tests/testthat/test-surv_reg_flexsurv.R +++ b/tests/testthat/test-surv_reg_flexsurv.R @@ -1,12 +1,10 @@ -data(cancer, package = "survival") -basic_form <- survival::Surv(time, status) ~ age -complete_form <- survival::Surv(time) ~ age # ------------------------------------------------------------------------------ test_that('flexsurv execution', { skip_if_not_installed("flexsurv") + skip_if_not_installed("survival") rlang::local_options(lifecycle_verbosity = "quiet") surv_basic <- surv_reg() |> set_engine("flexsurv") @@ -43,6 +41,8 @@ test_that('flexsurv execution', { test_that('flexsurv prediction', { skip_if_not_installed("flexsurv") + skip_if_not_installed("survival") + rlang::local_options(lifecycle_verbosity = "quiet") surv_basic <- surv_reg() |> set_engine("flexsurv") diff --git a/tests/testthat/test-surv_reg_survreg.R b/tests/testthat/test-surv_reg_survreg.R index d34a9181f..6463d309c 100644 --- a/tests/testthat/test-surv_reg_survreg.R +++ b/tests/testthat/test-surv_reg_survreg.R @@ -1,11 +1,4 @@ -if (R.Version()$major < "4") { - data(lung, package = 'survival') -} else { - data(cancer, package = 'survival') -} -basic_form <- survival::Surv(time, status) ~ group -complete_form <- survival::Surv(time) ~ group # ------------------------------------------------------------------------------