Update docs to use the new teal_data instead of TealData

DESCRIPTION

@@ -21,7 +21,7 @@ Depends:
     R (>= 3.6),
     shiny (>= 1.6.0),
     shinyTree,
-    teal (>= 0.14.0)
+    teal (>= 0.14.0.9019)
 Imports:
     checkmate (>= 2.1.0),
     dplyr (>= 1.0.5),
@@ -39,8 +39,8 @@ Imports:
     teal.code (>= 0.4.0),
     teal.logger (>= 0.1.1),
     teal.reporter (>= 0.2.0),
-    teal.slice (>= 0.4.0),
-    teal.transform (>= 0.4.0),
+    teal.slice (>= 0.4.0.9023),
+    teal.transform (>= 0.4.0.9007),
     teal.widgets (>= 0.4.0),
     tern (>= 0.7.10),
     tibble (>= 2.0.0),
@@ -65,7 +65,7 @@ Suggests:
     rlang (>= 1.0.0),
     rtables (>= 0.5.1),
     sparkline,
-    teal.data (>= 0.3.0),
+    teal.data (>= 0.3.0.9010),
     testthat (>= 3.0.4)
 VignetteBuilder:
     knitr

NEWS.md

@@ -1,5 +1,9 @@
 # teal.modules.general 0.2.16.9010
 
+### Enhancements
+
+* Updated the package docs and vignettes with the new way of specifying data for `teal::init()`. The `data` argument will accept a `teal_data` object
+
 ### Miscellaneous
 
 * Specified minimal version of package dependencies.

R/tm_a_pca.R

@@ -24,24 +24,25 @@
 #'
 #' # ADSL example
 #'
-#' library(nestcolor)
-#' ADSL <- teal.modules.general::rADSL
-#'
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset(
-#'       "ADSL", ADSL,
-#'       code = "ADSL <- teal.modules.general::rADSL"
-#'     ),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_a_pca(
 #'       "PCA",
 #'       dat = teal.transform::data_extract_spec(
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
-#'           choices = teal.transform::variable_choices(data = ADSL, c("BMRKR1", "AGE", "EOSDY")),
+#'           choices = teal.transform::variable_choices(
+#'             data = data[["ADSL"]], c("BMRKR1", "AGE", "EOSDY")
+#'           ),
 #'           selected = c("BMRKR1", "AGE"),
 #'           multiple = TRUE
 #'         ),
@@ -56,7 +57,6 @@
 #' if (interactive()) {
 #'   shinyApp(app$ui, app$server)
 #' }
-#'
 tm_a_pca <- function(label = "Principal Component Analysis",
                      dat,
                      plot_height = c(600, 200, 2000),
@@ -257,7 +257,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
       response[[i]]$select$choices <- var_labels(data[[response[[i]]$dataname]]())
       response[[i]]$select$choices <- setdiff(
         response[[i]]$select$choices,
-        unlist(get_join_keys(data)$get(response[[i]]$dataname))
+        unlist(teal.data::join_keys(data)[[response[[i]]$dataname]])
       )
     }
 
@@ -323,7 +323,7 @@ srv_a_pca <- function(id, data, reporter, filter_panel_api, dat, plot_height, pl
     anl_merged_input <- teal.transform::merge_expression_srv(
       selector_list = selector_list,
       datasets = data,
-      join_keys = get_join_keys(data)
+      join_keys = teal.data::join_keys(data)
     )
 
     anl_merged_q <- reactive({

R/tm_a_regression.R

@@ -34,13 +34,17 @@
 #' # Regression graphs from selected response variable (BMRKR1) and
 #' # selected regressors (AGE)
 #'
-#' ADSL <- teal.modules.general::rADSL
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #'
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL, code = "ADSL <- teal.modules.general::rADSL"),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_a_regression(
 #'       label = "Regression",
@@ -58,7 +62,7 @@
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variables:",
-#'           choices = teal.transform::variable_choices(ADSL, c("AGE", "SEX", "RACE")),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
 #'           selected = "AGE",
 #'           multiple = TRUE,
 #'           fixed = FALSE
@@ -291,7 +295,7 @@ srv_a_regression <- function(id,
     anl_merged_input <- teal.transform::merge_expression_srv(
       selector_list = selector_list,
       datasets = data,
-      join_keys = get_join_keys(data)
+      join_keys = teal.data::join_keys(data)
     )
 
     regression_var <- reactive({

R/tm_data_table.R

@@ -25,13 +25,17 @@
 #' @export
 #' @examples
 #'
-#' ADSL <- teal.modules.general::rADSL
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #'
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL, code = "ADSL <- teal.modules.general::rADSL"),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_data_table(
 #'       variables_selected = list(ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX")),

R/tm_file_viewer.R

@@ -13,11 +13,14 @@
 #' @export
 #'
 #' @examples
-#' data <- data.frame(1)
+#' data <- teal_data()
+#' data <- within(data, {
+#'   data <- data.frame(1)
+#' })
+#' datanames(data) <- c("data")
+#'
 #' app <- teal::init(
-#'   data = teal_data(
-#'     dataset("data", data)
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_file_viewer(
 #'       input_path = list(

R/tm_front_page.R

@@ -17,6 +17,15 @@
 #' @export
 #' @examples
 #'
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
+#'
 #' table_1 <- data.frame(Info = c("A", "B"), Text = c("A", "B"))
 #' table_2 <- data.frame(`Column 1` = c("C", "D"), `Column 2` = c(5.5, 6.6), `Column 3` = c("A", "B"))
 #' table_3 <- data.frame(Info = c("E", "F"), Text = c("G", "H"))
@@ -27,15 +36,8 @@
 #'   "Table 3" = table_3
 #' )
 #'
-#' ADSL <- teal.modules.general::rADSL
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL,
-#'       code = "ADSL <- teal.modules.general::rADSL",
-#'       metadata = list("Author" = "NEST team", "data_source" = "synthetic data")
-#'     ),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_front_page(
 #'       header_text = c(

R/tm_g_association.R

@@ -25,22 +25,25 @@
 #' @examples
 #' # Association plot of selected reference variable (SEX)
 #' # against other selected variables (BMRKR1)
-#' library(nestcolor)
-#' ADSL <- teal.modules.general::rADSL
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #'
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL, code = "ADSL <- teal.modules.general::rADSL"),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_g_association(
 #'       ref = teal.transform::data_extract_spec(
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variable:",
 #'           choices = teal.transform::variable_choices(
-#'             ADSL,
+#'             data[["ADSL"]],
 #'             c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
 #'           ),
 #'           selected = "RACE",
@@ -52,7 +55,7 @@
 #'         select = teal.transform::select_spec(
 #'           label = "Select variables:",
 #'           choices = teal.transform::variable_choices(
-#'             ADSL,
+#'             data[["ADSL"]],
 #'             c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
 #'           ),
 #'           selected = "BMRKR2",
@@ -248,7 +251,7 @@ srv_tm_g_association <- function(id,
     anl_merged_input <- teal.transform::merge_expression_srv(
       datasets = data,
       selector_list = selector_list,
-      join_keys = get_join_keys(data)
+      join_keys = teal.data::join_keys(data)
     )
 
     anl_merged_q <- reactive({

R/tm_g_bivariate.R

@@ -45,20 +45,24 @@
 #'
 #' @examples
 #' # Bivariate plot of selected variable (AGE) against selected (SEX)
-#' ADSL <- teal.modules.general::rADSL
+#' data <- teal_data()
+#' data <- within(data, {
+#'   library(nestcolor)
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #'
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL, code = "ADSL <- teal.modules.general::rADSL"),
-#'     check = TRUE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_g_bivariate(
 #'       x = teal.transform::data_extract_spec(
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variable:",
-#'           choices = teal.transform::variable_choices(ADSL),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]]),
 #'           selected = "AGE",
 #'           fixed = FALSE
 #'         )
@@ -67,7 +71,7 @@
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variable:",
-#'           choices = teal.transform::variable_choices(ADSL),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]]),
 #'           selected = "SEX",
 #'           multiple = FALSE,
 #'           fixed = FALSE
@@ -77,7 +81,7 @@
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variable:",
-#'           choices = teal.transform::variable_choices(ADSL),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]]),
 #'           selected = "ARM",
 #'           fixed = FALSE
 #'         )
@@ -86,7 +90,7 @@
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
 #'           label = "Select variable:",
-#'           choices = teal.transform::variable_choices(ADSL),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]]),
 #'           selected = "COUNTRY",
 #'           fixed = FALSE
 #'         )
@@ -437,7 +441,7 @@ srv_g_bivariate <- function(id,
     anl_merged_input <- teal.transform::merge_expression_srv(
       selector_list = selector_list,
       datasets = data,
-      join_keys = get_join_keys(data)
+      join_keys = teal.data::join_keys(data)
     )
 
     anl_merged_q <- reactive({

R/tm_g_distribution.R

@@ -29,8 +29,15 @@
 #'
 #' @examples
 #' # Example with non-clinical data
+#'
+#' data <- teal_data()
+#' data <- within(data, {
+#'   iris <- iris
+#' })
+#' datanames(data) <- c("iris")
+#'
 #' app <- teal::init(
-#'   data = teal_data(dataset("iris", iris)),
+#'   data = data,
 #'   modules = list(
 #'     teal.modules.general::tm_g_distribution(
 #'       dist_var = teal.transform::data_extract_spec(
@@ -48,22 +55,27 @@
 #' }
 #'
 #' # Example with clinical data
-#' ADSL <- teal.modules.general::rADSL
+#' data <- teal_data()
+#' data <- within(data, {
+#'   ADSL <- teal.modules.general::rADSL
+#' })
+#' datanames <- c("ADSL")
+#' datanames(data) <- datanames
+#' join_keys(data) <- default_cdisc_join_keys[datanames]
 #'
-#' vars1 <- choices_selected(variable_choices(ADSL, c("ARM", "COUNTRY", "SEX")), selected = NULL)
+#' vars1 <- choices_selected(
+#'   variable_choices(data[["ADSL"]], c("ARM", "COUNTRY", "SEX")),
+#'   selected = NULL
+#' )
 #'
 #' app <- teal::init(
-#'   data = teal.data::cdisc_data(
-#'     teal.data::cdisc_dataset("ADSL", ADSL),
-#'     code = "ADSL <- teal.modules.general::rADSL",
-#'     check = FALSE
-#'   ),
+#'   data = data,
 #'   modules = teal::modules(
 #'     teal.modules.general::tm_g_distribution(
 #'       dist_var = teal.transform::data_extract_spec(
 #'         dataname = "ADSL",
 #'         select = teal.transform::select_spec(
-#'           choices = teal.transform::variable_choices(ADSL, c("AGE", "BMRKR1")),
+#'           choices = teal.transform::variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
 #'           selected = "BMRKR1",
 #'           multiple = FALSE,
 #'           fixed = FALSE
@@ -435,7 +447,7 @@ srv_distribution <- function(id,
     anl_merged_input <- teal.transform::merge_expression_srv(
       selector_list = selector_list,
       datasets = data,
-      join_keys = get_join_keys(data)
+      join_keys = teal.data::join_keys(data)
     )
 
     anl_merged_q <- reactive({