diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index 40892de2a..8641bc62b 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -43,22 +43,50 @@
#'
#' @inherit shared_params return
#'
-#' @section Decorating module's output:
-#' Outputs produced by the module can be modified for any application. To do so, one needs to provide
-#' [teal_transform_module()] with `server` modifying outputed object in `data` (`teal_data`). Each
-#' module might have a different output object name and it's type, so there is no standard code to achieve this.
-#' However, `teal` provides couple wrappers which can simplify the process of decorating module's outputs:
-#' - `decorator` as a `language`: provide a simple expression to modify object of interests. For example
-#' `g <- g + ggtitle("Custom Title")`. Provided expression must be a working expression within module internals.
-#' - `decorator` as a `function`: provide a function which will take the output object and modify it in desired way.
-#' When function is provided object names don't need to match module's internal naming. For example
-#' `function(x) x <- x + ggtitle("Custom Title")`.
+#' @section Decorating Module Outputs:
+#'
+#' Decorating module outputs involves modifying the tables and plots generated by a module. This module provides the
+#' ability to execute custom R code to adjust the visual or structural properties of objects displayed within the
+#' application.
+#'
+#' The code specified in [`teal_transform_module`] is executed prior to rendering the outputs in the application. This
+#' allows developers to modify attributes such as titles, labels, sizes, limits, and other features of rendered tables
+#' and plots. However, decorators should be applied with careful consideration of the module's internal object names
+#' to ensure compatibility.
+#'
+#' To customize an output, developers need to identify the name of the table or plot to be modified within the
+#' `teal_transform_module`. This requires specifying a `server` function that modifies the targeted object in the
+#' `data` object (of class `teal_data`). Since each module may use different internal object names or types for its
+#' outputs, there is no universal code to achieve this. However, `teal` provides convenient wrappers to simplify the
+#' process of decorating module outputs:
+#'
+#' - **Decorator as a Language/Expression**: Specify a simple R expression to modify the object of interest.
+#' For example,`plot <- plot + ggtitle("Custom Title")`. The expression must be valid and compatible with the module's
+#' internal environment.
+#' - **Decorator as a Function**: Provide a function that accepts the output object and modifies it as desired.
+#' When using this approach, the function does not need to align with the module’s internal naming conventions for its
+#' objects.
+#'
+#' For additional details and examples of decorators, refer to the vignette
+#' `vignette("decorate-modules-output", package = "teal")` or the [`teal_transform_module()`] documentation.
+#'
+#' @section Decorating `tm_a_regression`:
+#'
+#' This module creates below objects that can be modified with decorators:
+#' - `plot` (`ggplot2`)#'
#'
#' @examplesShinylive
#' library(teal.modules.general)
#' interactive <- function() TRUE
#' {{ next_example }}
#' @examples
+#'
+#' footnote_regression <- teal_transform_module(
+#' server = make_teal_transform_server(expression(
+#' plot <- plot + labs(caption = deparse(summary(fit)[[1]]))
+#' ))
+#' )
+#'
#' # general data example
#' data <- teal_data()
#' data <- within(data, {
@@ -90,7 +118,8 @@
#' multiple = TRUE,
#' fixed = FALSE
#' )
-#' )
+#' ),
+#' decorators = list(footnote_regression)
#' )
#' )
#' )
@@ -135,7 +164,8 @@
#' multiple = TRUE,
#' fixed = FALSE
#' )
-#' )
+#' ),
+#' decorators = list(footnote_regression)
#' )
#' )
#' )
@@ -295,37 +325,37 @@ ui_a_regression <- function(id, decorators, ...) {
conditionalPanel(
condition = "input.plot_type == 'Response vs Regressor'",
ns = ns,
- ui_transform_data(ns("d_0"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_0"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Residuals vs Fitted'",
ns = ns,
- ui_transform_data(ns("d_1"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_1"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Normal Q-Q'",
ns = ns,
- ui_transform_data(ns("d_2"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_2"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Scale-Location'",
ns = ns,
- ui_transform_data(ns("d_3"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_3"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Cook\\'s distance'",
ns = ns,
- ui_transform_data(ns("d_4"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_4"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Residuals vs Leverage'",
ns = ns,
- ui_transform_data(ns("d_5"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_5"), transformators = decorators[[1]])
),
conditionalPanel(
condition = "input.plot_type == 'Cook\\'s dist vs Leverage'",
ns = ns,
- ui_transform_data(ns("d_6"), transforms = decorators[[1]])
+ ui_teal_transform_data(ns("d_6"), transformators = decorators[[1]])
),
),
checkboxInput(ns("show_outlier"), label = "Display outlier labels", value = TRUE),
@@ -610,6 +640,7 @@ srv_a_regression <- function(id,
})
output_plot_0 <- reactive({
+
fit <- fit_r()[["fit"]]
ANL <- anl_merged_q()[["ANL"]]
@@ -677,10 +708,10 @@ srv_a_regression <- function(id,
expr = {
class(fit$residuals) <- NULL
data <- fortify(fit)
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -721,10 +752,10 @@ srv_a_regression <- function(id,
substitute(
expr = {
smoothy <- smooth(data$.fitted, data$.resid)
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -780,10 +811,10 @@ srv_a_regression <- function(id,
plot_base,
substitute(
expr = {
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -823,10 +854,10 @@ srv_a_regression <- function(id,
substitute(
expr = {
smoothy <- smooth(data$.fitted, sqrt(abs(data$.stdresid)))
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -889,10 +920,10 @@ srv_a_regression <- function(id,
plot_base,
substitute(
expr = {
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -944,10 +975,10 @@ srv_a_regression <- function(id,
substitute(
expr = {
smoothy <- smooth(data$.hat, data$.stdresid)
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
@@ -994,22 +1025,22 @@ srv_a_regression <- function(id,
substitute(
expr = {
smoothy <- smooth(data$.hat, data$.cooksd)
- g <- plot
+ plot <- graph
},
env = list(
- plot = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
+ graph = Reduce(function(x, y) call("+", x, y), c(plot, parsed_ggplot2_args))
)
)
)
})
- decorated_output_0 <- srv_transform_data(id = "d_0", data = output_plot_0, transforms = decorators[[1]])
- decorated_output_1 <- srv_transform_data(id = "d_1", data = output_plot_1, transforms = decorators[[1]])
- decorated_output_2 <- srv_transform_data(id = "d_2", data = output_plot_2, transforms = decorators[[1]])
- decorated_output_3 <- srv_transform_data(id = "d_3", data = output_plot_3, transforms = decorators[[1]])
- decorated_output_4 <- srv_transform_data(id = "d_4", data = output_plot_4, transforms = decorators[[1]])
- decorated_output_5 <- srv_transform_data(id = "d_5", data = output_plot_5, transforms = decorators[[1]])
- decorated_output_6 <- srv_transform_data(id = "d_6", data = output_plot_6, transforms = decorators[[1]])
+ decorated_output_0 <- srv_teal_transform_data(id = "d_0", data = output_plot_0, transformators = decorators[[1]])
+ decorated_output_1 <- srv_teal_transform_data(id = "d_1", data = output_plot_1, transformators = decorators[[1]])
+ decorated_output_2 <- srv_teal_transform_data(id = "d_2", data = output_plot_2, transformators = decorators[[1]])
+ decorated_output_3 <- srv_teal_transform_data(id = "d_3", data = output_plot_3, transformators = decorators[[1]])
+ decorated_output_4 <- srv_teal_transform_data(id = "d_4", data = output_plot_4, transformators = decorators[[1]])
+ decorated_output_5 <- srv_teal_transform_data(id = "d_5", data = output_plot_5, transformators = decorators[[1]])
+ decorated_output_6 <- srv_teal_transform_data(id = "d_6", data = output_plot_6, transformators = decorators[[1]])
output_q <- reactive({
@@ -1026,7 +1057,7 @@ srv_a_regression <- function(id,
})
fitted <- reactive(output_q()[["fit"]])
- plot_r <- reactive(output_q()[["g"]])
+ plot_r <- reactive(output_q()[["plot"]])
# Insert the plot into a plot_with_settings module from teal.widgets
pws <- teal.widgets::plot_with_settings_srv(
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index 13de794e2..ec2d4cb17 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -16,7 +16,7 @@
#' @param boxplot_decorator (`list` of `teal_transform_module`) optional,
#' decorator for the box plot.
#' @param violin_decorator (`list` of `teal_transform_module`) optional,
-#' decorator for the violing plot.
+#' decorator for the violin plot.
#' @param density_decorator (`list` of `teal_transform_module`) optional,
#' decorator for the density plot.
#' @param cum_dist_decorator (`list` of `teal_transform_module`) optional,
@@ -27,25 +27,27 @@
#'
#' @inherit shared_params return
#'
-#' @section Decorating the tables and plots:
-#' The act of decoration means to modify the tables and plots output by this module.
-#' The module lets app developers do it by allowing them to execute arbitrary R code
-#' that modifies the objects displayed by the module.
+#' @inheritSection tm_a_regression Decorating Module Outputs
+#' @section Decorating `tm_outliers`:
#'
-#' The module will execute the code contained in [`teal_transform_module`] before
-#' rendering the outputs in the application. This lets app developers modify
-#' features like: titles, labels, sizes, limits, etc. of the rendered tables
-#' and plots.
-#'
-#' The app developer should apply decorators carefuly with respect to the module's internal
-#' object names. To modify an output, app developer needs to find out the name of the table or plot
-#' that is being modified by the code in the `teal_transform_module` list element.
+#' This module creates below objects that can be modified with decorators:
+#' - `table` (`data.frame`)
+#' - `plot` (`ggplot2`)
#'
#' @examplesShinylive
#' library(teal.modules.general)
#' interactive <- function() TRUE
#' {{ next_example }}
#' @examples
+#'
+#' module_decorator <- teal_transform_module(
+#' server = make_teal_transform_server(
+#' expression({
+#' plot <- plot + ggplot2::ggtitle("A new title")
+#' })
+#' )
+#' )
+#'
#' # general data example
#' data <- teal_data()
#' data <- within(data, {
@@ -82,7 +84,8 @@
#' multiple = TRUE
#' )
#' )
-#' )
+#' ),
+#' boxplot_decorator = module_decorator
#' )
#' )
#' )
@@ -95,6 +98,15 @@
#' interactive <- function() TRUE
#' {{ next_example }}
#' @examples
+#'
+#' module_decorator <- teal_transform_module(
+#' server = make_teal_transform_server(
+#' expression({
+#' plot <- plot + ggplot2::ggtitle("A new title")
+#' })
+#' )
+#' )
+#'
#' # CDISC data example
#' data <- teal_data()
#' data <- within(data, {
@@ -105,6 +117,8 @@
#' fact_vars_adsl <- names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
#' vars <- choices_selected(variable_choices(data[["ADSL"]], fact_vars_adsl))
#'
+#'
+#'
#' app <- init(
#' data = data,
#' modules = modules(
@@ -131,7 +145,8 @@
#' multiple = TRUE
#' )
#' )
-#' )
+#' ),
+#' boxplot_decorator = module_decorator
#' )
#' )
#' )
@@ -139,27 +154,6 @@
#' shinyApp(app$ui, app$server)
#' }
#'
-#' # Decorators
-#' function_decorator <- function(p) {
-#' p <- p + ggplot2::ggtitle("A new title")
-#' }
-#'
-#' quote_decorator <- quote({
-#' g <- g + ggplot2::ggtitle("A new title")
-#' })
-#'
-#' module_decorator <- teal_transform_module(
-#' ui = function(id) NULL,
-#' srv = function(id, data) {
-#' within(
-#' data,
-#' {
-#' g <- g + ggplot2::ggtitle("A new title")
-#' }
-#' )
-#' }
-#' )
-#'
#' @export
#'
tm_outliers <- function(label = "Outliers Module",
@@ -251,7 +245,7 @@ ui_outliers <- function(id, ...) {
output = teal.widgets::white_small_well(
uiOutput(ns("total_outliers")),
DT::dataTableOutput(ns("summary_table")),
- ui_transform_data(ns("table_decorator"), transforms = args$table_decorator),
+ ui_teal_transform_data(ns("table_decorator"), args$table_decorator),
uiOutput(ns("total_missing")),
tags$br(), tags$hr(),
tabsetPanel(
@@ -260,22 +254,22 @@ ui_outliers <- function(id, ...) {
"Boxplot",
conditionalPanel(
condition = sprintf("input['%s'] == 'Box plot'", ns("boxplot_alts")),
- ui_transform_data(ns("boxplot_decorator"), args$boxplot_decorator)
+ ui_teal_transform_data(ns("boxplot_decorator"), args$boxplot_decorator)
),
conditionalPanel(
condition = sprintf("input['%s'] == 'Violin plot'", ns("boxplot_alts")),
- ui_transform_data(ns("violin_decorator"), args$violin_decorator)
+ ui_teal_transform_data(ns("violin_decorator"), args$violin_decorator)
),
teal.widgets::plot_with_settings_ui(id = ns("box_plot"))
),
tabPanel(
"Density Plot",
- ui_transform_data(ns("density_decorator"), args$density_decorator),
+ ui_teal_transform_data(ns("density_decorator"), args$density_decorator),
teal.widgets::plot_with_settings_ui(id = ns("density_plot"))
),
tabPanel(
"Cumulative Distribution Plot",
- ui_transform_data(ns("cum_dist_decorator"), args$cum_dist_decorator),
+ ui_teal_transform_data(ns("cum_dist_decorator"), args$cum_dist_decorator),
teal.widgets::plot_with_settings_ui(id = ns("cum_density_plot"))
)
),
@@ -827,7 +821,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
teal.code::eval_code(
common_code_q(),
substitute(
- expr = g <- plot_call +
+ expr = plot <- plot_call +
scale_color_manual(values = c("TRUE" = "red", "FALSE" = "black")) +
labs + ggthemes + themes,
env = list(
@@ -888,7 +882,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
teal.code::eval_code(
common_code_q(),
substitute(
- expr = g <- plot_call + labs + ggthemes + themes,
+ expr = plot <- plot_call + labs + ggthemes + themes,
env = list(
plot_call = plot_call,
labs = parsed_ggplot2_args$labs,
@@ -989,7 +983,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
teal.code::eval_code(
qenv,
substitute(
- expr = g <- plot_call +
+ expr = plot <- plot_call +
geom_point(data = outlier_points, aes(x = outlier_var_name, y = y, color = is_outlier_selected)) +
scale_color_manual(values = c("TRUE" = "red", "FALSE" = "black")) +
labs + ggthemes + themes,
@@ -1004,10 +998,14 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
)
})
- decorated_boxplot_q <- srv_transform_data("boxplot_decorator", data = boxplot_q, transforms = decorators$boxplot)
- decorated_violin_q <- srv_transform_data("violin_decorator", data = boxplot_q, transforms = decorators$violin)
- decorated_density_plot_q <- srv_transform_data("density_decorator", data = density_plot_q, transforms = decorators$density)
- decorated_cumulative_plot_q <- srv_transform_data("cum_dist_decorator", data = cumulative_plot_q, transforms = decorators$cum_dist)
+ decorated_boxplot_q <-
+ srv_teal_transform_data("boxplot_decorator", data = boxplot_q, transformators = decorators$boxplot_decorator)
+ decorated_violin_q <-
+ srv_teal_transform_data("violin_decorator", data = boxplot_q, transformators = decorators$violin_decorator)
+ decorated_density_plot_q <-
+ srv_teal_transform_data("density_decorator", data = density_plot_q, transformators = decorators$density_decorator)
+ decorated_cumulative_plot_q <-
+ srv_teal_transform_data("cum_dist_decorator", data = cumulative_plot_q, transformators = decorators$cum_dist_decorator)
final_q <- reactive({
req(input$tabs)
@@ -1030,7 +1028,7 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
setdiff(names(ANL_OUTLIER), c("is_outlier_selected", "order")),
table_columns
)
- ANL_OUTLIER_EXTENDED[ANL_OUTLIER_EXTENDED$is_outlier_selected, columns_index]
+ table <- ANL_OUTLIER_EXTENDED[ANL_OUTLIER_EXTENDED$is_outlier_selected, columns_index]
},
env = list(
table_columns = input$table_ui_columns
@@ -1039,6 +1037,12 @@ srv_outliers <- function(id, data, reporter, filter_panel_api, outlier_var,
)
})
+
+ decorated_final_q <-
+ srv_teal_transform_data("cum_dist_decorator", data = final_q, transformators = decorators$table_decorator)
+ # TODO:
+ # reuse decorated_final_q in table generation
+
# slider text
output$ui_outlier_help <- renderUI({
req(input$method)
diff --git a/man/tm_a_regression.Rd b/man/tm_a_regression.Rd
index 82a40d327..92ee60d00 100644
--- a/man/tm_a_regression.Rd
+++ b/man/tm_a_regression.Rd
@@ -19,7 +19,7 @@ tm_a_regression(
default_plot_type = 1,
default_outlier_label = "USUBJID",
label_segment_threshold = c(0.5, 0, 10),
- decorator = list(default = teal_transform_module())
+ decorators = list(default = teal_transform_module())
)
}
\arguments{
@@ -97,6 +97,8 @@ It can take the following forms:
It takes the form of \code{c(value, min, max)} and it is passed to the \code{value_min_max}
argument in \code{teal.widgets::optionalSliderInputValMinMax}.
}}
+
+\item{decorators}{(\code{list} of \code{teal_transform_module})}
}
\value{
Object of class \code{teal_module} to be used in \code{teal} applications.
@@ -111,7 +113,53 @@ visualize residuals, and identify outliers.
For more examples, please see the vignette "Using regression plots" via
\code{vignette("using-regression-plots", package = "teal.modules.general")}.
}
+\section{Decorating Module Outputs}{
+
+
+Decorating module outputs involves modifying the tables and plots generated by a module. This module provides the
+ability to execute custom R code to adjust the visual or structural properties of objects displayed within the
+application.
+
+The code specified in \code{\link{teal_transform_module}} is executed prior to rendering the outputs in the application. This
+allows developers to modify attributes such as titles, labels, sizes, limits, and other features of rendered tables
+and plots. However, decorators should be applied with careful consideration of the module's internal object names
+to ensure compatibility.
+
+To customize an output, developers need to identify the name of the table or plot to be modified within the
+\code{teal_transform_module}. This requires specifying a \code{server} function that modifies the targeted object in the
+\code{data} object (of class \code{teal_data}). Since each module may use different internal object names or types for its
+outputs, there is no universal code to achieve this. However, \code{teal} provides convenient wrappers to simplify the
+process of decorating module outputs:
+\itemize{
+\item \strong{Decorator as a Language/Expression}: Specify a simple R expression to modify the object of interest.
+For example,\code{plot <- plot + ggtitle("Custom Title")}. The expression must be valid and compatible with the module's
+internal environment.
+\item \strong{Decorator as a Function}: Provide a function that accepts the output object and modifies it as desired.
+When using this approach, the function does not need to align with the module’s internal naming conventions for its
+objects.
+}
+
+For additional details and examples of decorators, refer to the vignette
+\code{vignette("decorate-modules-output", package = "teal")} or the \code{\link[=teal_transform_module]{teal_transform_module()}} documentation.
+}
+
+\section{Decorating \code{tm_a_regression}}{
+
+
+This module creates below objects that can be modified with decorators:
+\itemize{
+\item \code{plot} (\code{ggplot2})#'
+}
+}
+
\examples{
+
+footnote_regression <- teal_transform_module(
+ server = make_teal_transform_server(expression(
+ plot <- plot + labs(caption = deparse(summary(fit)[[1]]))
+ ))
+)
+
# general data example
data <- teal_data()
data <- within(data, {
@@ -143,7 +191,8 @@ app <- init(
multiple = TRUE,
fixed = FALSE
)
- )
+ ),
+ decorators = footnote_regression
)
)
)
@@ -183,7 +232,8 @@ app <- init(
multiple = TRUE,
fixed = FALSE
)
- )
+ ),
+ decorators = footnote_regression
)
)
)
@@ -195,14 +245,14 @@ if (interactive()) {
\section{Examples in Shinylive}{
\describe{
\item{example-1}{
- \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokqUBiXVIhrqu-lCkULpwAB6wqCJKAUEGxlzUAPoxUDbRgcFGugDutKQAFirsKbi6IEq6uoxwAI6CtNXsPqKkxNREjIoQlQDCAPIATHG6-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}{Open in Shinylive}
+ \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokrcQTRIqQje4AfUY4CSDRUSsIA2Muan9SZghRT0YYfz4hEXYlXV1RGR1GXQBeXRgoAGsAmLiEpKIU-zzGAvY4AA9UUPDrbJzdVGpvKP7B0l0Aal1qKHpRdgI0TRJi3X44VBY89lFBGDK2dhNaUjlgYABGAF1LuUVI3VulO6UAYl0pCDVqVahSKF12rABnAlPxfv8jLpqmC-jZQeDhgB3Y4ACxU7BhUFwuhAvSCAEdBLQguxPqJSMRBow7jkAMIAeQATMMGYylABfZ7QdDDFTHLL3TErTG4XrpYRiFbikRzXo5UipKCBYJdCICvp9ab0ODfEoKMBYFViboQfWi+4a0KoEh5YXg-zteLqUiNVBwAjqjV9THQeArfWss1yr15EQaFah90u0Ruj3Br1TGY6-1gADKOqjui0LFoMxEiCDFoTugIKKItAIkr1YEEqD+lULxb6kY0cH4Kdr9ZBeHjXpgwk0wJWADEAIIAGVTznNTZyRzabZWDhcvZyNK9chnXqCIWN9TtfwdbSdGld7s9CZ9sD01cDPaLGpbYxKT7PcYfXq1yer6bDY2zjC5vQMoFves4lmWFZVlmOZ5gEpblpWcyYmcAZMvq1zYnGhAkAQZq6PqdhBL88BkPqtxbk2T6LtWxAWI2s79tQg4iEuTjTqufTzjRuhjpOrgfmuvabr2azEMwpD1KIKyeN4vjkMqu5hBEwbrncdy0CYujsCo5DMJYOg2LYuL3KIaIQKwo7oOwaCoAAJES2K2XZTQFHc7JKGA7KXEAA}{Open in Shinylive}
\if{html}{\out{}}
- \if{html}{\out{}}
+ \if{html}{\out{}}
}
\item{example-2}{
- \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokqUBiXQGEAIgEkAZS9dfihSKF04AA9YVBElUPCDYy5qAH1EqBsEsIijXQB3WlIACxV2TNxdECVdXUY4AEdBWgb2CDFSYmoiRkUIOoBBHwCAGWT64bGlAF9+gCsiFTSAazhWUQrc23z+OBMoYVI0gn5aUQI0xeW1jeBoeE3MuQBdN2h0CZVi9lqQ3N0AF5-uFcH8+EIRKIgboIcIxL8BnVdKQYGkoGkGhIGqJRFYIIjkcjqFB6HBqDCFGAsHBsWI8SQqWCkUScagSKI9MDMmloqRmBo0qJUHACISicjMg8uboqVNRky-hLdJyRBoYarRcdhaLxcq6iSyRTgVSAuStbotCxaKSRIhFSz9QQSksCGJKWAAEIAWSwAGksABGB365GajRwfgen3+oMh0Owo60OIygBig1GAWczITploUUjMIcLiVEv6yrkOYlWJxol6MJ5fIF2pFYtLRKlsBlcpGCrw7bD5vVwPDLd1A6JhvJHrNatIluttrE9v7juVztd7uBVsYNvoIhOLtobqeuWAwB70zALxeVTbYEGAHFXHhZWAswANJlvrCDLwvuRKwnQc50LE0H2feNQxgJMUyLJxs2AuoTHzMDdHTTNXDXZFyzLUtcP6fpaBMXR2BUchm20OAbFsGokVEMoIFYQZ0HYNBUAAEhaKp2I4zlGB0PpZiUMAZheIA}{Open in Shinylive}
+ \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokqUBiXQGEAIgEkAZS9dfihSKF04AA9YVBElUPCDYy5qAH1EqBsEsIijXQB3WlIACxV2TNxdECVdXUY4AEdBWgb2CDFSYmoiRkUIOoBBHwCAGWT64bGlAF9+gCsiFTSAazhWUQrc23z+OBMoYVI0gn5aUQI0xeW1jeBoeE3MuQBdN2h0CZVi9lqQ3N0AF5-uFcH8+EIRKIgboIcIxL8BnVdKQYGkoGkGhIGqJRFYIIjkcjqFB6HBqDCFGAsHBsWI8SQqWCkUScagSKI9MDMmloqRmBo0qJUHACISicjMg8uboqVNRky-hLdJyRBoYarRcdhaLxcq6iSyRTgVSAuStbotCxaKSRIhFSz9QQSksCGJKWAAEIAWSwAGksABGB365GajRwfgen3+oMh0Owo60OIygBig1GAWczITploUUjMIcLiVEv6yrkOYlWJxol6MJ5fIF2pFYtLRKlsBlcpGCrw7bD5vVwPDLd1A6JhvJHrNatIluttrE9v7juVztd7uBVsYNvoIhOLtobqeuWAwB70zALxeVTbYEGAHFXHhZWAswANJlvrCDLwvuRKwnQc50LE0H2feNQxgJMUyLJxs2AuoTHzMDdHTTNXDXZFyzLKsO1FXowl6aFgRMIgiFICBKLgTFaVrfFS1w-p+loExdHYFRyGbbQ4BsWwaiRUQyggVhBnQdg0FQAASFoqik6TOUYHQ+lmJQwBmF4gA}{Open in Shinylive}
\if{html}{\out{}}
- \if{html}{\out{}}
+ \if{html}{\out{}}
}
}
}
diff --git a/man/tm_outliers.Rd b/man/tm_outliers.Rd
index 7ab4e6585..940198ad1 100644
--- a/man/tm_outliers.Rd
+++ b/man/tm_outliers.Rd
@@ -54,19 +54,19 @@ with text placed before the output to put the output into context. For example a
\item{post_output}{(\code{shiny.tag}) optional, text or UI element to be displayed after the module's output,
adding context or further instructions. Elements like \code{shiny::helpText()} are useful.}
-\item{table_decorator}{(\code{teal_transform_module}, \code{language} or \code{function}) optional,
+\item{table_decorator}{(\code{list} of \code{teal_transform_module}) optional,
decorator for the table.}
-\item{boxplot_decorator}{(\code{teal_transform_module}, \code{language} or \code{function}) optional,
+\item{boxplot_decorator}{(\code{list} of \code{teal_transform_module}) optional,
decorator for the box plot.}
-\item{violin_decorator}{(\code{teal_transform_module}, \code{language} or \code{function}) optional,
-decorator for the violing plot.}
+\item{violin_decorator}{(\code{list} of \code{teal_transform_module}) optional,
+decorator for the violin plot.}
-\item{density_decorator}{(\code{teal_transform_module}, \code{language} or \code{function}) optional,
+\item{density_decorator}{(\code{list} of \code{teal_transform_module}) optional,
decorator for the density plot.}
-\item{cum_dist_decorator}{(\code{teal_transform_module}, \code{language} or \code{function}) optional,
+\item{cum_dist_decorator}{(\code{list} of \code{teal_transform_module}) optional,
decorator for the cumulative distribution plot.}
}
\value{
@@ -77,50 +77,56 @@ Module to analyze and identify outliers using different methods
such as IQR, Z-score, and Percentiles, and offers visualizations including
box plots, density plots, and cumulative distribution plots to help interpret the outliers.
}
-\section{Decorating the tables and plots}{
+\section{Decorating \code{tm_outliers}}{
-The act of decoration means to modify the tables and plots output by this module.
-The module lets app developers do it by allowing them to execute arbitrary R code
-that modifies the objects displayed by the module.
-The decorating parameters accept one of the three types of objects as decorators:
+This module creates below objects that can be modified with decorators:
\itemize{
-\item \code{teal_transform_module}
-\item \code{language}
-\item \code{function} of the output object.
+\item \code{table} (\code{data.frame})
+\item \code{plot} (\code{ggplot2})
+}
}
-The module will execute the code contained in either of the objects just before
-rendering the outputs in the application. This lets app developers modify
-features like: titles, labels, sizes, limits, etc. of the rendered tables
-and plots.
-
-The app developer can pass either of the types. See examples for the proper
-use of each of the type of the decorator.
+\section{Decorating Module Outputs}{
-IMPORTANT
-The \code{language} and \code{teal_transform_module} decorators are required by the module
-to overwrite the binding of the output, otherwise the effect of the decorator
-is not going to be visible. E.g.:
-\if{html}{\out{}}\preformatted{# The module uses `g` variable for the plot
+Decorating module outputs involves modifying the tables and plots generated by a module. This module provides the
+ability to execute custom R code to adjust the visual or structural properties of objects displayed within the
+application.
-# Will work
-lang_dec <- quote(\{
- g <- g + ggplot2::ggtitle("A new title")
-\})
+The code specified in \code{\link{teal_transform_module}} is executed prior to rendering the outputs in the application. This
+allows developers to modify attributes such as titles, labels, sizes, limits, and other features of rendered tables
+and plots. However, decorators should be applied with careful consideration of the module's internal object names
+to ensure compatibility.
-# Will not work because the decorater overwrites `plot` instead of `g`
-lang_dec <- quote(\{
- plot <- g + ggplot2::ggtitle("A new title")
-\})
-}\if{html}{\out{
}}
+To customize an output, developers need to identify the name of the table or plot to be modified within the
+\code{teal_transform_module}. This requires specifying a \code{server} function that modifies the targeted object in the
+\code{data} object (of class \code{teal_data}). Since each module may use different internal object names or types for its
+outputs, there is no universal code to achieve this. However, \code{teal} provides convenient wrappers to simplify the
+process of decorating module outputs:
+\itemize{
+\item \strong{Decorator as a Language/Expression}: Specify a simple R expression to modify the object of interest.
+For example,\code{plot <- plot + ggtitle("Custom Title")}. The expression must be valid and compatible with the module's
+internal environment.
+\item \strong{Decorator as a Function}: Provide a function that accepts the output object and modifies it as desired.
+When using this approach, the function does not need to align with the module’s internal naming conventions for its
+objects.
+}
-The app developer can discover the bindings used for the outputs by inspecting
-the R code generated by the module.
+For additional details and examples of decorators, refer to the vignette
+\code{vignette("decorate-modules-output", package = "teal")} or the \code{\link[=teal_transform_module]{teal_transform_module()}} documentation.
}
\examples{
+
+module_decorator <- teal_transform_module(
+ server = make_teal_transform_server(
+ expression({
+ plot <- plot + ggplot2::ggtitle("A new title")
+ })
+ )
+)
+
# general data example
data <- teal_data()
data <- within(data, {
@@ -157,7 +163,8 @@ app <- init(
multiple = TRUE
)
)
- )
+ ),
+ boxplot_decorator = module_decorator
)
)
)
@@ -165,6 +172,15 @@ if (interactive()) {
shinyApp(app$ui, app$server)
}
+
+module_decorator <- teal_transform_module(
+ server = make_teal_transform_server(
+ expression({
+ plot <- plot + ggplot2::ggtitle("A new title")
+ })
+ )
+)
+
# CDISC data example
data <- teal_data()
data <- within(data, {
@@ -175,6 +191,8 @@ join_keys(data) <- default_cdisc_join_keys[names(data)]
fact_vars_adsl <- names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
vars <- choices_selected(variable_choices(data[["ADSL"]], fact_vars_adsl))
+
+
app <- init(
data = data,
modules = modules(
@@ -201,7 +219,8 @@ app <- init(
multiple = TRUE
)
)
- )
+ ),
+ boxplot_decorator = module_decorator
)
)
)
@@ -209,39 +228,18 @@ if (interactive()) {
shinyApp(app$ui, app$server)
}
-# Decorators
-function_decorator <- function(p) {
- p <- p + ggplot2::ggtitle("A new title")
-}
-
-quote_decorator <- quote({
- g <- g + ggplot2::ggtitle("A new title")
-})
-
-module_decorator <- teal_transform_module(
- ui = function(id) NULL,
- srv = function(id, data) {
- within(
- data,
- {
- g <- g + ggplot2::ggtitle("A new title")
- }
- )
- }
-)
-
}
\section{Examples in Shinylive}{
\describe{
\item{example-1}{
- \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokqUBiXVIhrqu-lCkULpwAB6wqCJKAUEGxlzUAPoxUDbRgcFGugDutKQAFirsKbi6IEq6ugDCAPIATHHV9RVNdcDACmCojLQwLKyJANZwrJ0AumONonAAjokiEOwQjETZ7LV1cooQAL7bAFZEKkMjosUZtlmHx8OsZ9cQJxydG52lL814up3dvf1PnS2bggWhYokaBHyRwIYkS0xEGjg-HYoJ6UHoIkSkOhYnOQXaHzq4zGpQI7E6AAVqFAyG9vmA7KxUHA6Z07Iw4IF4LSwFttko0KhGio8uSIJUUroALz+DK4Fp8IQicEyxXCXEtSqkGCJIiCUh0GRnTWVXR6g20GSJVHS3R0USkMWm52yoKJMKkZgaOHMskml2ummwPQywlvf0u+FwDS2qPe0S+p0Bl3U+hwPyhsAAZXT0dIulRtHRIkQ4fFyed2NoMJVBZYRYxcCxUOruJSBLArzAE1J5MIJAIrLAglQQWGgLk8vLFcqcfI-FtnRHY5ZeAjAZgwk0kRDugAYgBBAAyWecU5nppMtFCSNth5Prmnye2FZfLsnEYIgTgEiIPS-SQ2jK9qOuugbuqEnrqKQPrRkmFYpNA8CLp2nznjOV7UOQjC2ph2GwX6T4VqitYkehF5VjWtqgtQghNpRbYZB2XY9nWjCiAAJHOSIfkRybcQuMo0XRzY4mc7YdKhRLdiSbGcQJvEXpUm5YbQO62g4LhgZUb4Brppr6W+2zbLQJi6OwKjYdB2hwDYtjlOWoiFBArAHug7CChxgi0KUnnTIwOiMNsOxKGAOxjEAA}{Open in Shinylive}
+ \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokrcQ+QkQH1+cYsykRIwGxlzU3qTMEKImwTDensJw7Eq6uqIyOiEAvLowUADWcJFw3JHRsfHemYzZqRDp6XAAHqiMYqJWEOwgaU3pqNREpKG6QyO6ANS6EhITpABMiIhzmqQiqWAAgroQcADuuusiCmCKjU0AvhfpFxdKAMSz0rK6-FCkULqtsENwSg+XzG4V8nygNkB4LGB1opAAFip2ECoLhdH1LgBhADyizGOMW-QJwGAZ3atAKbG8xVYZwAunSxpkAI7eEQ9CCMIgHdgEuQXG5KABWRBU1LgrFEyPBtiMuhFYppUoVEHFHDOBLOaI1uK1ujJjApLFYarO-PcWhYojGBHhooIYhqcBEGjg-HYlsNUHoPlt9rE0q+JJ1hLADLRBC2AAVqFAyHqznZWKgAXh9WA7B1PvB4+dzRAlGhUGMVHCGukUbo8ijcP0kiJrXl6wH+ulSAkiIINrQZFLW01O92ZN5PVXdHRRKRywMmijvK0oupSDUU5H+zP3uDoPAxyGteuZ5kXaM8kf-MvRKvpxuBrH6M7d2AAMrO8+6T20b0iRD7y43pp+rQDqNu+LCfj6JSAcBgZQMGYCamGdIRlsxAWAmYCCKgXzFGaci1n+-4ZK+rr8I+mHYam+GEU0MDCJo-xjgAYtsAAyT7OFR1GmLQLRukxrHsQeAy3DeInCZxAwEJ8cASMEQHlKOeQTlOQmbl884tIuGgrv4143ii256Hke54Kp6QmLQ1DkLk3FWcOl66WZTSeiBLkSYRUFiGOlrUIIkF2kBAYonBCHhqBjCiAAJGeJF4U56QxeQpF5D5fneJ5UrBaS8G6ohaIudFxFJXFBH-rRVm0AxeQOC4TliTO9V3O56T0EQbTDMufgBJ8wRjs2vj+MEPWMP2In3EotAmLo7AqNZS7aCk-Lov0oiIhArDbOg7BFpFgi0GiO21NkApKGAVx0kAA}{Open in Shinylive}
\if{html}{\out{}}
- \if{html}{\out{}}
+ \if{html}{\out{}}
}
\item{example-2}{
- \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokqUBiXQGEAIgEkAZS9dfihSKF04AA9YVBElUPCDYy5qAH1EqBsEsIijXQB3WlIACxV2TNxdECVdXQBBHwCAGWTdRkaWpQBfRQgAKyIVNIBrOFZRCtzbfP44EyhhUjSCflpRAjTB4bGJ4Gh4Scy5AF03CAWNNK0WUTSoflFqNoOxdgAxWmpyRnZ1hxcVVEaDiHEywGACjAnWaUJOJyq6wwl1IREYcgxShujFEbQIJSGBDEaVEcBEGjg-HY2NoUHoIhWBNoRKOuQhUJhcIRpnUy2xdweT0xECUILaKmK7FqIVyugAvDLwrhpXwhCJcQrVcI3tK6qQYGkiIJSHQZJNdXVdEaTbQZNcWPLdHRRKQpRBLR7FVA0tFSMwrqJUHACG7PZ7Mq9HRymrC8Baw6TyaRHYng8tA8HQ2HPdQ6WSo2AAmS07oaXSRIgocr3dmPfjCWJHWX6XBGQ3WeF2dCY1yqiGOQBxVx4XRQgBCAFksABpLAARihGOrtY9qYp-AL9SHVfj2ZgS1ocT0Cve9WaAWcy5XdRMtCilMdp-Prhrtb6b93civdbCcAkaOZbh7UYR1nVdXc6kyH0oj9XkSSDftX2zCNYGPUduy6OMkLDW9vhkR1cJ+eDMwgz1+SbW5vxXetmUbBUbmoQRWxolkpk7SEMNjeEqn5AASNdyH4L9SNXYt1woxjmKZVjwQ4zkwG40tbn4sTBOE7C9wPI9HQBF9r3fbMDI9IzdAMvo+loExdD+VR-U0HQbFsGoa1EMoIFYep0HYEFeMEWgqh80lGB0dEeiUMBuhOIA}{Open in Shinylive}
+ \href{https://shinylive.io/r/app/#code=NobwRAdghgtgpmAXGKAHVA6ASmANGAYwHsIAXOMpMAGwEsAjAJykYE8AKcqajGIgEwCu1OAGcMAcwpxm1AJQAdCLTIyoBUrQBucAAQAeALS6AZoIgbaJdnN0AVLAFUAokrcQ+QkQH1+cYsykRIwGxlzU3qTMEKImwTDensJw7Eq6uqIyOiEAvLowUADWcJFw3JHRsfHemYzZqRDp6XAAHqiMYqJWEOwgaU3pqNREpKG6QyO6ANS6EhITpABMiIhzmqQiqWAAgroQcADuuusiCmCKjU0AvhfpFxdKAMS6AMIAIgCSAMovuvxQpCgulasCGcCU-0BY3CvgBUBsELhYwOtFIAAsVOxIVBcLo+pdtm8vgAZMaMQkkpQ3JQAKyIKm8xVYoixcNsRj+cBMUGEpG8BH4tFEBG8dIZTNEwGg8BZ2LkAF13NyNN4tCxRN4oPxRNQxtKxOwAGK0ajkRjsIUOFy40RoIYcbHAYBnCnEs7y+W4oUYZVBRhyANKNWMURjAho+kEMQ1OAiDRwfjsYO0KD0HzhyMGx3OnZEt1gD2432q9Wa7XyB4Qdx2sYqVENdLY3R5bG4fpJEShvIdg39dKkBJEQQbWgyFl9ppDkcyEu5XR0USkBsDJrY7ytKLqPmiVD+Zcr1dw-XN3QuvNnNuXA-pTJx0Z5W-+be7gj76-paip2Mns5fWNP3Rk1TEREAvCd3wzWgoy7QCWBTNMSkg6DWUBJ0z0pAtPV0V8XQAcVcPBTzAAAhABZLAAGksAARjOANL3fAZH3jfgfx2fCwKvRiYF5WgwRPQ1tmJL5nAYxj0hMWgWgTAShJE8CV1ua8lIGOQxIGAgATgCRgig8pgxPBclwUxs4XXFpNxVHc9xMw9AWPPJ0PzdTr0k00ZBPNyzRqF833fYMYIClyIIjKCxBPNVqEERDQuQ7MnPdLCAoAEmY8h+DU2ymP-FiIu4aL+VirM4TQ3MMMLWCQ1SnL0syrj3x400+JEE8rVcerFNslSmjqg96CINphj5PwAgBYITx7Xx-GCMbGAnJT7iUWgTF0C1VGYSwdBsWx8RvDEIFYbZ0HYO1ksEWhcVO2psguK4lDAK55SAA}{Open in Shinylive}
\if{html}{\out{}}
- \if{html}{\out{}}
+ \if{html}{\out{}}
}
}
}