Nothing
## ----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")
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