skip if suggested pkgs are not available

tests/testthat/test-aaa_survival_prob.R

@@ -306,6 +306,7 @@ test_that("combine_list_of_survfit_summary() works for survbagg", {
 
 test_that("combine_list_of_survfit_summary() works for ctree", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
 
   lung_pred <- tidyr::drop_na(lung)
 
@@ -338,6 +339,7 @@ test_that("combine_list_of_survfit_summary() works for ctree", {
 
 test_that("combine_list_of_survfit_summary() works for cforest", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
 
   lung_pred <- tidyr::drop_na(lung)
 

tests/testthat/test-bag_tree-rpart.R

@@ -1,6 +1,8 @@
 library(testthat)
 
 test_that("model object", {
+  skip_if_not_installed("ipred")
+
   set.seed(1234)
   exp_f_fit <- ipred::bagging(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -17,6 +19,8 @@ test_that("model object", {
 })
 
 test_that("main args work without set_model_arg()", {
+  skip_if_not_installed("ipred")
+
   set.seed(1234)
   exp_f_fit <- ipred::bagging(
     Surv(time, status) ~ age + ph.ecog, 
@@ -41,6 +45,8 @@ test_that("main args work without set_model_arg()", {
 # prediction: time --------------------------------------------------------
 
 test_that("time predictions", {
+  skip_if_not_installed("ipred")
+
   set.seed(1234)
   exp_f_fit <- ipred::bagging(Surv(time, status) ~ age + ph.ecog, data = lung)
   exp_f_pred <- predict(exp_f_fit, lung)
@@ -64,6 +70,8 @@ test_that("time predictions", {
 })
 
 test_that("time predictions without surrogate splits for NA", {
+  skip_if_not_installed("ipred")
+
   mod_spec <- bag_tree(engine = "rpart") %>% set_mode("censored regression")
   f_fit <- fit(mod_spec, Surv(time, status) ~ ph.ecog, data = lung)
 
@@ -81,6 +89,8 @@ test_that("time predictions without surrogate splits for NA", {
 # prediction: survival ----------------------------------------------------
 
 test_that("survival predictions", {
+  skip_if_not_installed("ipred")
+
   set.seed(1234)
   exp_f_fit <- ipred::bagging(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -131,6 +141,8 @@ test_that("survival predictions", {
 })
 
 test_that("survival_prob_survbagg() works", {
+  skip_if_not_installed("ipred")
+
   set.seed(1234)
   # use only ph.ecog to force missings by avoiding surrogate splits
   mod <- ipred::bagging(Surv(time, status) ~ ph.ecog, data = lung)
@@ -205,6 +217,8 @@ test_that("survival_prob_survbagg() works", {
 })
 
 test_that("survival predictions without surrogate splits for NA", {
+  skip_if_not_installed("ipred")
+
   mod_spec <- bag_tree(engine = "rpart") %>% set_mode("censored regression")
   f_fit <- fit(mod_spec, Surv(time, status) ~ ph.ecog, data = lung)
 
@@ -227,6 +241,8 @@ test_that("survival predictions without surrogate splits for NA", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("ipred")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
 
@@ -243,6 +259,8 @@ test_that("can predict for out-of-domain timepoints", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("ipred")
+
   lung_x <- as.matrix(lung[, c("age", "ph.ecog")])
   lung_y <- Surv(lung$time, lung$status)
   lung_pred <- lung[1:5, ]

tests/testthat/test-decision_tree-partykit.R

@@ -2,6 +2,8 @@ library(testthat)
 
 test_that("model object", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   set.seed(1234)
   exp_f_fit <- partykit::ctree(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -31,6 +33,8 @@ test_that("model object", {
 
 test_that("time predictions", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   set.seed(1234)
   exp_f_fit <- partykit::ctree(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -58,6 +62,8 @@ test_that("time predictions", {
 
 test_that("survival predictions", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   set.seed(1234)
   exp_f_fit <- partykit::ctree(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -106,6 +112,9 @@ test_that("survival predictions", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
 
@@ -122,6 +131,9 @@ test_that("can predict for out-of-domain timepoints", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   lung_x <- as.matrix(lung[, c("age", "ph.ecog")])
   lung_y <- Surv(lung$time, lung$status)
   lung_pred <- lung[1:5, ]

tests/testthat/test-decision_tree-rpart.R

@@ -1,6 +1,8 @@
 library(testthat)
 
 test_that("model object", {
+  skip_if_not_installed("pec")
+
   set.seed(1234)
   exp_f_fit <- pec::pecRpart(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -21,6 +23,8 @@ test_that("model object", {
 # prediction: time --------------------------------------------------------
 
 test_that("time predictions", {
+  skip_if_not_installed("pec")
+
   set.seed(1234)
   exp_f_fit <- pec::pecRpart(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -47,6 +51,8 @@ test_that("time predictions", {
 # prediction: survival ----------------------------------------------------
 
 test_that("survival predictions", {
+  skip_if_not_installed("pec")
+
   set.seed(1234)
   exp_f_fit <- pec::pecRpart(Surv(time, status) ~ age + ph.ecog, data = lung)
 
@@ -96,6 +102,8 @@ test_that("survival predictions", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("pec")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
 
@@ -112,6 +120,7 @@ test_that("can predict for out-of-domain timepoints", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("pec")
   skip_if_not_installed("prodlim", minimum_version = "2023.3.31")
 
   lung_x <- as.matrix(lung[, c("age", "ph.ecog")])

tests/testthat/test-partykit.R

@@ -1,4 +1,7 @@
 test_that("survival_prob_partykit() works for ctree", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   set.seed(1234)
   # use only ph.ecog to rule out surrogate splits
   mod <- partykit::ctree(Surv(time, status) ~ ph.ecog, data = lung)
@@ -69,6 +72,9 @@ test_that("survival_prob_partykit() works for ctree", {
 })
 
 test_that("survival_prob_partykit() works for cforest", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   # partykit::cforest takes care of missing values via some form of randomness
   # hence set the seed before predicting on data with missings
 

tests/testthat/test-proportional_hazards-glmnet.R

@@ -1,4 +1,5 @@
 library(testthat)
+skip_if_not_installed("glmnet")
 suppressPackageStartupMessages(library(glmnet))
 
 test_that("model object", {

tests/testthat/test-rand_forest-aorsf.R

@@ -160,6 +160,8 @@ test_that("survival predictions", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("aorsf")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
   lung_orsf <- na.omit(lung)
@@ -177,6 +179,8 @@ test_that("can predict for out-of-domain timepoints", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("aorsf")
+
   lung_orsf <- na.omit(lung)
 
   lung_x <- as.matrix(lung_orsf[, c("age", "ph.ecog")])
@@ -228,6 +232,8 @@ test_that("`fix_xy()` works", {
 # case weights ------------------------------------------------------------
 
 test_that("can handle case weights", {
+  skip_if_not_installed("aorsf")
+
   dat <- make_cens_wts()
 
   expect_error(

tests/testthat/test-rand_forest-partykit.R

@@ -2,6 +2,7 @@ library(testthat)
 
 test_that("model object", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
 
   set.seed(1234)
   exp_f_fit <- partykit::cforest(
@@ -36,6 +37,7 @@ test_that("model object", {
 
 test_that("time predictions", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
 
   set.seed(1234)
   exp_f_fit <- partykit::cforest(
@@ -69,6 +71,7 @@ test_that("time predictions", {
 
 test_that("survival predictions", {
   skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
 
   set.seed(1234)
   exp_f_fit <- partykit::cforest(
@@ -132,6 +135,9 @@ test_that("survival predictions", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
 
@@ -148,6 +154,9 @@ test_that("can predict for out-of-domain timepoints", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("partykit")
+  skip_if_not_installed("coin")
+
   lung_x <- as.matrix(lung[, c("age", "ph.ecog")])
   lung_y <- Surv(lung$time, lung$status)
   lung_pred <- lung[1:5, ]

tests/testthat/test-survival_reg-flexsurv.R

@@ -1,6 +1,8 @@
 library(testthat)
 
 test_that("model object", {
+  skip_if_not_installed("flexsurv")
+
   set.seed(1234)
   exp_f_fit <- flexsurv::flexsurvreg(
     Surv(time, status) ~ age + ph.ecog,
@@ -29,6 +31,8 @@ test_that("model object", {
 # prediction: time --------------------------------------------------------
 
 test_that("flexsurv time prediction", {
+  skip_if_not_installed("flexsurv")
+
   exp_fit <- flexsurv::flexsurvreg(
     Surv(time, status) ~ age,
     data = lung,
@@ -52,6 +56,8 @@ test_that("flexsurv time prediction", {
 # prediction: survival ----------------------------------------------------
 
 test_that("survival probability prediction", {
+  skip_if_not_installed("flexsurv")
+
   rms_surv <- readRDS(test_path("data", "rms_surv.rds"))
   f_fit <- survival_reg(dist = "weibull") %>%
     set_engine("flexsurv") %>%
@@ -121,6 +127,8 @@ test_that("survival probability prediction", {
 })
 
 test_that("survival probabilities for single eval time point", {
+  skip_if_not_installed("flexsurv")
+
   f_fit <- survival_reg(engine = "flexsurv") %>%
     fit(Surv(time, status) ~ age + sex, data = lung)
 
@@ -140,6 +148,8 @@ test_that("survival probabilities for single eval time point", {
 })
 
 test_that("can predict for out-of-domain timepoints", {
+  skip_if_not_installed("flexsurv")
+
   eval_time_obs_max_and_ood <- c(1022, 2000)
   obs_without_NA <- lung[2,]
 
@@ -160,6 +170,8 @@ test_that("can predict for out-of-domain timepoints", {
 # prediction: linear_pred -------------------------------------------------
 
 test_that("linear predictor", {
+  skip_if_not_installed("flexsurv")
+
   f_fit <- survival_reg() %>%
     set_engine("flexsurv") %>%
     fit(Surv(time, status) ~ age + sex, data = lung)
@@ -201,6 +213,8 @@ test_that("linear predictor", {
 # prediction: quantile ----------------------------------------------------
 
 test_that("quantile predictions", {
+  skip_if_not_installed("flexsurv")
+
   set.seed(1)
   fit_s <- survival_reg() %>%
     set_engine("flexsurv") %>%
@@ -266,6 +280,8 @@ test_that("quantile predictions", {
 # prediction: hazard ------------------------------------------------------
 
 test_that("hazard prediction", {
+  skip_if_not_installed("flexsurv")
+
   rms_haz <- readRDS(test_path("data", "rms_haz.rds"))
   f_fit <- survival_reg(dist = "weibull") %>%
     set_engine("flexsurv") %>%
@@ -314,6 +330,8 @@ test_that("hazard prediction", {
 })
 
 test_that("hazard for single eval time point", {
+  skip_if_not_installed("flexsurv")
+
   f_fit <- survival_reg(engine = "flexsurv") %>%
     fit(Surv(time, status) ~ age + sex, data = lung)
 
@@ -335,6 +353,8 @@ test_that("hazard for single eval time point", {
 # fit via matrix interface ------------------------------------------------
 
 test_that("`fix_xy()` works", {
+  skip_if_not_installed("flexsurv")
+
   lung_x <- as.matrix(lung[, c("age", "ph.ecog")])
   lung_y <- Surv(lung$time, lung$status)
   lung_pred <- lung[1:5, ]