## ----library, echo=TRUE, message=FALSE, warning=FALSE, results="hide"--------- library(teal.modules.general) # used to create the app library(dplyr) # used to modify data sets ## ----data, echo=TRUE, message=FALSE, warning=FALSE, results="hide"------------ data <- teal_data() data <- within(data, { ADSL <- teal.data::rADSL ADRS <- teal.data::rADRS ADLB <- teal.data::rADLB }) join_keys(data) <- default_cdisc_join_keys[names(data)] ## ----app, echo=TRUE, message=FALSE, warning=FALSE, results="hide"------------- # configuration for the single wide dataset mod1 <- tm_outliers( label = "Single wide dataset", outlier_var = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")), selected = "AGE", fixed = FALSE ) ), categorical_var = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variables:", choices = variable_choices( data[["ADSL"]], subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor))) ), selected = "RACE", multiple = FALSE, fixed = FALSE ) ) ) # configuration for the wide and long datasets mod2 <- tm_outliers( label = "Wide and long datasets", outlier_var = list( data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")), selected = "AGE", fixed = FALSE ) ), data_extract_spec( dataname = "ADLB", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")), selected = "AVAL", multiple = FALSE, fixed = FALSE ) ) ), categorical_var = data_extract_spec( dataname = "ADSL", select = select_spec( label = "Select variables:", choices = variable_choices( data[["ADSL"]], subset = names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor))) ), selected = "RACE", multiple = FALSE, fixed = FALSE ) ) ) # configuration for the multiple long datasets mod3 <- tm_outliers( label = "Multiple long datasets", outlier_var = list( data_extract_spec( dataname = "ADRS", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADRS"]], c("ADY", "EOSDY")), selected = "ADY", fixed = FALSE ) ), data_extract_spec( dataname = "ADLB", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADLB"]], c("AVAL", "CHG2")), selected = "AVAL", multiple = FALSE, fixed = FALSE ) ) ), categorical_var = list( data_extract_spec( dataname = "ADRS", select = select_spec( label = "Select variables:", choices = variable_choices(data[["ADRS"]], c("ARM", "ACTARM")), selected = "ARM", multiple = FALSE, fixed = FALSE ) ), data_extract_spec( dataname = "ADLB", select = select_spec( label = "Select variables:", choices = variable_choices( data[["ADLB"]], subset = names(Filter(isTRUE, sapply(data[["ADLB"]], is.factor))) ), selected = "RACE", multiple = FALSE, fixed = FALSE ) ) ) ) # initialize the app app <- init( data = data, modules = modules( # tm_outliers ---- modules( label = "Outliers module", mod1, mod2, mod3 ) ) ) ## ----shinyapp, eval=FALSE----------------------------------------------------- # shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024)) ## ----shinylive_url, echo = FALSE, results = 'asis', eval = requireNamespace("roxy.shinylive", quietly = TRUE)---- code <- paste0(c( knitr::knit_code$get("library"), knitr::knit_code$get("data"), knitr::knit_code$get("app"), knitr::knit_code$get("shinyapp") ), collapse = "\n") url <- roxy.shinylive::create_shinylive_url(code) cat(sprintf("[Open in Shinylive](%s)\n\n", url)) ## ----shinylive_iframe, echo = FALSE, out.width = '150%', out.extra = 'style = "position: relative; z-index:1"', eval = requireNamespace("roxy.shinylive", quietly = TRUE) && knitr::is_html_output() && identical(Sys.getenv("IN_PKGDOWN"), "true")---- # knitr::include_url(url, height = "800px")