Incrementally initializing the test apps so it becomes easier to review the tests.

tests/testthat/helper-TealAppDriver.R

@@ -23,3 +23,18 @@ init_teal_app_driver <- function(...) {
     .package = "teal"
   )
 }
+
+
+# TODO: This will be moved to the `TealAppDriver` class.
+active_module_tws_output <- function(app_driver, element = "table-table-with-settings", which = 1) {
+  app_driver$active_module_element(element) %>%
+    app_driver$get_html_rvest() %>%
+    rvest::html_table(fill = TRUE) %>%
+    {
+      if (identical(., list())) {
+        .
+      } else {
+        .[[which]]
+      }
+    }
+}

tests/testthat/test-shinytest2-tm_g_forest_tte copy.R

@@ -0,0 +1,77 @@
+app_driver_tm_g_ipp <- function() {
+  data <- teal_data() %>%
+    within({
+      library(nestcolor)
+      library(dplyr)
+      ADSL <- tmc_ex_adsl %>%
+        slice(1:20) %>%
+        df_explicit_na()
+      ADLB <- tmc_ex_adlb %>%
+        filter(USUBJID %in% ADSL$USUBJID) %>%
+        df_explicit_na() %>%
+        filter(AVISIT != "SCREENING")
+    })
+
+  datanames <- c("ADSL", "ADLB")
+  teal.data::datanames(data) <- datanames
+  teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[datanames]
+
+  init_teal_app_driver(
+    data = data,
+    modules = teal::modules(
+      tm_g_ipp(
+        label = "Individual Patient Plot",
+        dataname = "ADLB",
+        arm_var = teal.transform::choices_selected(
+          teal.transform::value_choices(data[["ADLB"]], "ARMCD"),
+          "ARM A"
+        ),
+        paramcd = teal.transform::choices_selected(
+          teal.transform::value_choices(data[["ADLB"]], "PARAMCD"),
+          "ALT"
+        ),
+        aval_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("AVAL", "CHG")),
+          "AVAL"
+        ),
+        avalu_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("AVALU")),
+          "AVALU",
+          fixed = TRUE
+        ),
+        id_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("USUBJID")),
+          "USUBJID",
+          fixed = TRUE
+        ),
+        visit_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("AVISIT")),
+          "AVISIT"
+        ),
+        baseline_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("BASE")),
+          "BASE",
+          fixed = TRUE
+        ),
+        add_baseline_hline = FALSE,
+        separate_by_obs = FALSE
+      )
+    )
+  )
+}
+
+testthat::test_that("e2e - tm_g_ipp: Module initializes in teal without errors and produces plot output.", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_ipp()
+  app_driver$expect_no_shiny_error()
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_match(
+    app_driver$get_attr(
+      app_driver$active_module_element("myplot-plot_main > img"),
+      "src"
+    ),
+    "data:image/png;base64,"
+  )
+  app_driver$stop()
+})

tests/testthat/test-shinytest2-tm_g_forest_tte.R

@@ -0,0 +1,69 @@
+app_driver_tm_g_forest_tte <- function() {
+  data <- teal.data::teal_data() %>%
+    within({
+      library(nestcolor)
+      library(formatters)
+
+      ADSL <- tmc_ex_adsl
+      ADTTE <- tmc_ex_adtte
+      ADSL$RACE <- droplevels(ADSL$RACE) %>%
+        with_label("Race")
+    })
+  datanames <- c("ADSL", "ADTTE")
+  teal.data::datanames(data) <- datanames
+  teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[datanames]
+
+  arm_ref_comp <- list(
+    ARM = list(
+      ref = "B: Placebo",
+      comp = c("A: Drug X", "C: Combination")
+    ),
+    ARMCD = list(
+      ref = "ARM B",
+      comp = c("ARM A", "ARM C")
+    )
+  )
+
+  init_teal_app_driver(
+    data = data,
+    modules = teal::modules(
+      tm_g_forest_tte(
+        label = "Forest Survival",
+        dataname = "ADTTE",
+        arm_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("ARM", "ARMCD")),
+          "ARMCD"
+        ),
+        arm_ref_comp = arm_ref_comp,
+        paramcd = teal.transform::choices_selected(
+          teal.transform::value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+          "OS"
+        ),
+        subgroup_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], names(data[["ADSL"]])),
+          c("BMRKR2", "SEX")
+        ),
+        strata_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("STRATA1", "STRATA2")),
+          "STRATA2"
+        )
+      )
+    )
+  )
+}
+
+testthat::test_that("e2e - tm_g_forest_tte: Module initializes in teal without errors and produces plot output.", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_forest_tte()
+  app_driver$expect_no_shiny_error()
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_match(
+    app_driver$get_attr(
+      app_driver$active_module_element("myplot-plot_main > img"),
+      "src"
+    ),
+    "data:image/png;base64,"
+  )
+  app_driver$stop()
+})

tests/testthat/test-shinytest2-tm_g_km.R

@@ -0,0 +1,65 @@
+app_driver_tm_g_km <- function() {
+  data <- teal.data::teal_data() %>%
+    within({
+      ADSL <- tmc_ex_adsl
+      ADTTE <- tmc_ex_adtte
+    })
+
+  datanames <- c("ADSL", "ADTTE")
+  teal.data::datanames(data) <- datanames
+  teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[datanames]
+
+  arm_ref_comp <- list(
+    ACTARMCD = list(
+      ref = "ARM B",
+      comp = c("ARM A", "ARM C")
+    ),
+    ARM = list(
+      ref = "B: Placebo",
+      comp = c("A: Drug X", "C: Combination")
+    )
+  )
+
+  init_teal_app_driver(
+    data = data,
+    modules = teal::modules(
+      tm_g_km(
+        label = "Kaplan-Meier Plot",
+        dataname = "ADTTE",
+        arm_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("ARM", "ARMCD", "ACTARMCD")),
+          "ARM"
+        ),
+        paramcd = teal.transform::choices_selected(
+          teal.transform::value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
+          "OS"
+        ),
+        arm_ref_comp = arm_ref_comp,
+        strata_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("SEX", "BMRKR2")),
+          "SEX"
+        ),
+        facet_var = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("SEX", "BMRKR2")),
+          NULL
+        )
+      )
+    )
+  )
+}
+
+testthat::test_that("e2e - tm_g_km: Module initializes in teal without errors and produces plot output.", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_km()
+  app_driver$expect_no_shiny_error()
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_match(
+    app_driver$get_attr(
+      app_driver$active_module_element("myplot-plot_main > img"),
+      "src"
+    ),
+    "data:image/png;base64,"
+  )
+  app_driver$stop()
+})

tests/testthat/test-shinytest2-tm_g_lineplot.R

@@ -0,0 +1,53 @@
+app_driver_tm_g_lineplot <- function() {
+  data <- teal.data::teal_data() %>%
+    within({
+      library(dplyr)
+      library(forcats)
+
+      ADSL <- tmc_ex_adsl
+      ADLB <- tmc_ex_adlb %>%
+        mutate(AVISIT == fct_reorder(AVISIT, AVISITN, min))
+    })
+
+  datanames <- c("ADSL", "ADLB")
+  teal.data::datanames(data) <- datanames
+  teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[datanames]
+
+  init_teal_app_driver(
+    data = data,
+    modules = teal::modules(
+      tm_g_lineplot(
+        label = "Line Plot",
+        dataname = "ADLB",
+        strata = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADSL"]], c("ARM", "ARMCD", "ACTARMCD")),
+          "ARM"
+        ),
+        y = teal.transform::choices_selected(
+          teal.transform::variable_choices(data[["ADLB"]], c("AVAL", "BASE", "CHG", "PCHG")),
+          "AVAL"
+        ),
+        param = teal.transform::choices_selected(
+          teal.transform::value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
+          "ALT"
+        )
+      )
+    )
+  )
+}
+
+testthat::test_that("e2e - tm_g_lineplot: Module initializes in teal without errors and produces plot output.", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_lineplot()
+  app_driver$expect_no_shiny_error()
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_match(
+    app_driver$get_attr(
+      app_driver$active_module_element("myplot-plot_main > img"),
+      "src"
+    ),
+    "data:image/png;base64,"
+  )
+  app_driver$stop()
+})

tests/testthat/test-shinytest2-tm_g_pp_adverse_events.R

@@ -0,0 +1,70 @@
+app_driver_tm_g_pp_adverse_events <- function() { # nolint: object_length
+  data <- teal.data::teal_data() %>%
+    within({
+      library(dplyr)
+      ADAE <- tmc_ex_adae
+      ADSL <- tmc_ex_adsl %>%
+        filter(USUBJID %in% ADAE$USUBJID)
+    })
+
+  datanames <- c("ADSL", "ADAE")
+  teal.data::datanames(data) <- datanames
+  teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[datanames]
+
+  init_teal_app_driver(
+    data = data,
+    modules = teal::modules(
+      tm_g_pp_adverse_events(
+        label = "Adverse Events",
+        dataname = "ADAE",
+        parentname = "ADSL",
+        patient_col = "USUBJID",
+        plot_height = c(600L, 200L, 2000L),
+        aeterm = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "AETERM"),
+          selected = "AETERM"
+        ),
+        tox_grade = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "AETOXGR"),
+          selected = "AETOXGR"
+        ),
+        causality = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "AEREL"),
+          selected = "AEREL"
+        ),
+        outcome = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "AEOUT"),
+          selected = "AEOUT"
+        ),
+        action = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "AEACN"),
+          selected = "AEACN"
+        ),
+        time = teal.transform::choices_selected(
+          choices = teal.transform::variable_choices(data[["ADAE"]], "ASTDY"),
+          selected = "ASTDY"
+        ),
+        decod = NULL
+      )
+    )
+  )
+}
+
+testthat::test_that(
+  "e2e - tm_g_pp_adverse_events: Module initializes in teal without errors and produces plot output.",
+  {
+    skip_if_too_deep(5)
+    app_driver <- app_driver_tm_g_pp_adverse_events()
+    app_driver$expect_no_shiny_error()
+    app_driver$expect_no_validation_error()
+
+    testthat::expect_match(
+      app_driver$get_attr(
+        app_driver$active_module_element("myplot-plot_main > img"),
+        "src"
+      ),
+      "data:image/png;base64,"
+    )
+    app_driver$stop()
+  }
+)

tests/testthat/test-shinytest2-tm_g_pp_patient_timeline.R

@@ -0,0 +1,19 @@
+app_driver_tm_g_km <- function() {
+
+}
+
+testthat::test_that("e2e - tm_g_km: Module initializes in teal without errors and produces plot output.", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_km()
+  app_driver$expect_no_shiny_error()
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_match(
+    app_driver$get_attr(
+      app_driver$active_module_element("myplot-plot_main > img"),
+      "src"
+    ),
+    "data:image/png;base64,"
+  )
+  app_driver$stop()
+})