Remove "default" decoration and use the same way of decoration in all modules (#846)

Closes #845 

Changes:
1. Removes the ability to have a "default" decoration applied to all
output objects.
2. Makes sure that all our modules follow the same decoration format:
`decorators = list(output_name = teal_transform_module(...))`
3. Improve the error message so the user knows that they have to provide
the names from the available list of names.

<details>
<summary>Decorator examples that should be working</summary>

```r
pkgload::load_all(".")

# ######################################################
#
#   _____                           _
#  |  __ \                         | |
#  | |  | | ___  ___ ___  _ __ __ _| |_ ___  _ __ ___
#  | |  | |/ _ \/ __/ _ \| '__/ _` | __/ _ \| '__/ __|
#  | |__| |  __/ (_| (_) | | | (_| | || (_) | |  \__ \
#  |_____/ \___|\___\___/|_|  \__,_|\__\___/|_|  |___/
#
#
#
#  Decorators
# #####################################################

plot_grob_decorator <- function(default_footnote = "I am a good decorator", .var_to_replace = "plot") {
  teal_transform_module(
    label = "Caption (grob)",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_footnote),
    server = function(id, data) {
      moduleServer(id, function(input, output, session) {
        logger::log_info("🟠 plot_grob with default: {default_footnote}!", namespace = "teal.modules.general")
        reactive({
          req(data(), input$footnote)
          logger::log_info("changing the footnote {default_footnote}", namespace = "teal.modules.general")
          teal.code::eval_code(data(), substitute(
            {
              footnote_grob <- grid::textGrob(footnote, x = 0, hjust = 0, gp = grid::gpar(fontsize = 10, fontface = "italic", col = "gray50"))
              # Arrange the plot and footnote
              .var_to_replace <- gridExtra::arrangeGrob(
                .var_to_replace,
                footnote_grob,
                ncol = 1,
                heights = grid::unit.c(grid::unit(1, "npc") - grid::unit(1, "lines"), grid::unit(1, "lines"))
              )
            },
            env = list(
              footnote = input$footnote,
              .var_to_replace = as.name(.var_to_replace)
            )
          ))
        })
      })
    }
  )
}
caption_decorator <- function(default_caption = "I am a good decorator", .var_to_replace = "plot") {
  print(.var_to_replace)
  teal_transform_module(
    label = "Caption",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_caption),
    server = make_teal_transform_server(
      substitute(
        {
          .var_to_replace <- .var_to_replace + ggplot2::labs(caption = footnote)
        },
        env = list(.var_to_replace = as.name(.var_to_replace))
      )
    )
  )
}
table_decorator <- function(.color1 = "#f9f9f9", .color2 = "#f0f0f0", .var_to_replace = "table") {
  teal_transform_module(
    label = "Table color",
    ui = function(id) {
      selectInput(
        NS(id, "style"),
        "Table Style",
        choices = c("Default", "Color1", "Color2"),
        selected = "Default"
      )
    },
    server = function(id, data) {
      moduleServer(id, function(input, output, session) {
        logger::log_info("🔵 Table row color called to action!", namespace = "teal.modules.general")
        reactive({
          req(data(), input$style)
          logger::log_info("changing the Table row color '{input$style}'", namespace = "teal.modules.general")
          teal.code::eval_code(data(), substitute(
            {
              .var_to_replace <- switch(style,
                "Color1" = DT::formatStyle(
                  .var_to_replace,
                  columns = attr(.var_to_replace$x, "colnames")[-1],
                  target = "row",
                  backgroundColor = .color1
                ),
                "Color2" = DT::formatStyle(
                  .var_to_replace,
                  columns = attr(.var_to_replace$x, "colnames")[-1],
                  target = "row",
                  backgroundColor = .color2
                ),
                .var_to_replace
              )
            },
            env = list(
              style = input$style,
              .var_to_replace = as.name(.var_to_replace),
              .color1 = .color1,
              .color2 = .color2
            )
          ))
        })
      })
    }
  )
}
head_decorator <- function(default_value = 6, .var_to_replace = "object") {
  teal_transform_module(
    label = "Head",
    ui = function(id) shiny::numericInput(shiny::NS(id, "n"), "Footnote", value = default_value),
    server = make_teal_transform_server(
      substitute(
        {
          .var_to_replace <- utils::head(.var_to_replace, n = n)
        },
        env = list(.var_to_replace = as.name(.var_to_replace))
      )
    )
  )
}
treelis_subtitle_decorator <- function(default_caption = "I am a good decorator", .var_to_replace = "plot") {
  teal_transform_module(
    label = "Caption",
    ui = function(id) shiny::textInput(shiny::NS(id, "footnote"), "Footnote", value = default_caption),
    server = make_teal_transform_server(
      substitute(
        {
          .var_to_replace <- update(.var_to_replace, sub = footnote)
        },
        env = list(.var_to_replace = as.name(.var_to_replace))
      )
    )
  )
}
insert_rrow_decorator <- function(default_caption = "I am a good new row", .var_to_replace = "table") {
  teal_transform_module(
    label = "New row",
    ui = function(id) shiny::textInput(shiny::NS(id, "new_row"), "New row", value = default_caption),
    server = make_teal_transform_server(
      substitute(
        {
          .var_to_replace <- rtables::insert_rrow(.var_to_replace, rtables::rrow(new_row))
        },
        env = list(.var_to_replace = as.name(.var_to_replace))
      )
    )
  )
}
do_nothing_decorator <- teal_transform_module(server = function(id, data) moduleServer(id, function(input, output, session) data))

# ##########################################
#
#   _             _      _       _
#  | |           | |    | |     | |
#  | |_ ___  __ _| |  __| | __ _| |_ __ _
#  | __/ _ \/ _` | | / _` |/ _` | __/ _` |
#  | ||  __/ (_| | || (_| | (_| | || (_| |
#   \__\___|\__,_|_| \__,_|\__,_|\__\__,_|
#                ______
#               |______|
#
#  teal_data
# #########################################

data <- teal_data(join_keys = default_cdisc_join_keys[c("ADSL", "ADRS")])
data <- within(data, {
  require(nestcolor)
  ADSL <- rADSL
  ADRS <- rADRS
})

# For tm_outliers
fact_vars_adsl <- names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
vars <- choices_selected(variable_choices(data[["ADSL"]], fact_vars_adsl))

init(
  data = data,
  modules = modules(
    # ####################
    #
    #
    #
    #   _ __   ___ __ _
    #  | '_ \ / __/ _` |
    #  | |_) | (_| (_| |
    #  | .__/ \___\__,_|
    #  | |
    #  |_|
    #
    #  pca
    # ###################
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data = data[["ADSL"]], c("BMRKR1", "AGE", "EOSDY")),
          selected = c("BMRKR1", "AGE")
        )
      ),
      decorators = list(
        elbow_plot = caption_decorator("I am a elbow_plot", "elbow_plot"),
        circle_plot = caption_decorator("I am a circle_plot", "circle_plot"),
        biplot = caption_decorator("I am a biplot", "biplot"),
        eigenvector_plot = caption_decorator("I am a eigenvector_plot", "eigenvector_plot")
      )
    ),
    ###############################################################################
    #
    #  _ __ ___  __ _ _ __ ___  ___ ___(_) ___  _ __
    # | '__/ _ \/ _` | '__/ _ \/ __/ __| |/ _ \| '_ \
    # | | |  __/ (_| | | |  __/\__ \__ \ | (_) | | | |
    # |_|  \___|\__, |_|  \___||___/___/_|\___/|_| |_|
    #            __|_|
    #
    # regression
    #
    ###############################################################################
    tm_a_regression(
      label = "Regression",
      response = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = "BMRKR1",
          selected = "BMRKR1",
          multiple = FALSE,
          fixed = TRUE
        )
      ),
      regressor = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
          selected = "AGE",
          multiple = TRUE,
          fixed = FALSE
        )
      ),
      decorators = list(
        plot = caption_decorator("I am a Regression", "plot")
      )
    ),
    # #######################################################
    #
    #                            _       _   _
    #                           (_)     | | (_)
    #    __ _ ___ ___  ___   ___ _  __ _| |_ _  ___  _ __
    #   / _` / __/ __|/ _ \ / __| |/ _` | __| |/ _ \| '_ \
    #  | (_| \__ \__ \ (_) | (__| | (_| | |_| | (_) | | | |
    #   \__,_|___/___/\___/ \___|_|\__,_|\__|_|\___/|_| |_|
    #
    #
    #
    #  association
    # ######################################################
    tm_g_association(
      ref = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "RACE"
        )
      ),
      vars = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "BMRKR2",
          multiple = TRUE
        )
      ),
      decorators = list(
        plot = plot_grob_decorator("I am a good grob (association)")
      )
    ),
    # ############################################
    #
    #   _     _                 _       _
    #  | |   (_)               (_)     | |
    #  | |__  ___   ____ _ _ __ _  __ _| |_ ___
    #  | '_ \| \ \ / / _` | '__| |/ _` | __/ _ \
    #  | |_) | |\ V / (_| | |  | | (_| | ||  __/
    #  |_.__/|_| \_/ \__,_|_|  |_|\__,_|\__\___|
    #
    #
    #
    #  bivariate
    # ###########################################
    tm_g_bivariate(
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "AGE")
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "SEX")
      ),
      row_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "ARM")
      ),
      col_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]]), selected = "COUNTRY")
      ),
      decorators = list(
        plot = caption_decorator("I am a Bivariate", "plot")
      )
    ),
    ###############################################################################
    #
    #     _ _     _        _ _           _   _
    #  __| (_)___| |_ _ __(_) |__  _   _| |_(_) ___  _ __
    # / _` | / __| __| '__| | '_ \| | | | __| |/ _ \| '_ \
    # | (_| | \__ \ |_| |  | | |_) | |_| | |_| | (_) | | | |
    #  \__,_|_|___/\__|_|  |_|_.__/ \__,_|\__|_|\___/|_| |_|
    #
    #  distribution
    ###############################################################################
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
          selected = "BMRKR1",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      strata_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars,
          multiple = TRUE
        )
      ),
      group_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars,
          multiple = TRUE
        )
      ),
      decorators = list(
        histogram_plot = caption_decorator("I am a Histogram", "histogram_plot"),
        qq_plot = caption_decorator("I am a QQ plot", "qq_plot"),
        summary_table = table_decorator("summary_table", .color1 = "#f0000055"),
        test_table = table_decorator("test_table", .color1 = "#f0000055")
      )
    ),
    # #############################################
    #
    #
    #
    #   _ __ ___  ___ _ __   ___  _ __  ___  ___
    #  | '__/ _ \/ __| '_ \ / _ \| '_ \/ __|/ _ \
    #  | | |  __/\__ \ |_) | (_) | | | \__ \  __/
    #  |_|  \___||___/ .__/ \___/|_| |_|___/\___|
    #                | |
    #                |_|
    #
    #  response
    # ############################################
    tm_g_response(
      label = "Response",
      response = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("BMRKR2", "COUNTRY")))
      ),
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")), selected = "RACE")
      ),
      decorators = list(
        plot = caption_decorator("I am a Response", "plot")
      )
    ),
    #####################################################
    #
    #                 _   _                  _       _
    #                | | | |                | |     | |
    #   ___  ___ __ _| |_| |_ ___ _ __ _ __ | | ___ | |_
    #  / __|/ __/ _` | __| __/ _ \ '__| '_ \| |/ _ \| __|
    #  \__ \ (_| (_| | |_| ||  __/ |  | |_) | | (_) | |_
    #  |___/\___\__,_|\__|\__\___|_|  | .__/|_|\___/ \__|
    #                                 | |
    #                                 |_|
    #
    #  scatterplot
    # ####################################################
    tm_g_scatterplot(
      label = "Scatterplot",
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")))
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
          selected = "BMRKR1"
        )
      ),
      color_by = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      size_by = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")))
      ),
      row_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      col_facet = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
          selected = NULL
        )
      ),
      decorators = list(
        plot = caption_decorator("I am a scatterplot", "plot")
      )
    ),
    # #######################################################################################
    #
    #                 _   _                  _       _                     _        _
    #                | | | |                | |     | |                   | |      (_)
    #   ___  ___ __ _| |_| |_ ___ _ __ _ __ | | ___ | |_   _ __ ___   __ _| |_ _ __ ___  __
    #  / __|/ __/ _` | __| __/ _ \ '__| '_ \| |/ _ \| __| | '_ ` _ \ / _` | __| '__| \ \/ /
    #  \__ \ (_| (_| | |_| ||  __/ |  | |_) | | (_) | |_  | | | | | | (_| | |_| |  | |>  <
    #  |___/\___\__,_|\__|\__\___|_|  | .__/|_|\___/ \__| |_| |_| |_|\__,_|\__|_|  |_/_/\_\
    #                                 | |
    #                                 |_|
    #
    #  scatterplot matrix
    # ######################################################################################
    tm_g_scatterplotmatrix(
      label = "Scatterplot matrix",
      variables = list(
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            choices = variable_choices(data[["ADSL"]]),
            selected = c("AGE", "RACE", "SEX"),
            multiple = TRUE,
            ordered = TRUE
          )
        ),
        data_extract_spec(
          dataname = "ADRS",
          filter = filter_spec(
            label = "Select endpoints:",
            vars = c("PARAMCD", "AVISIT"),
            choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
            selected = "INVET - END OF INDUCTION",
            multiple = TRUE
          ),
          select = select_spec(
            choices = variable_choices(data[["ADRS"]]),
            selected = c("AGE", "AVAL", "ADY"),
            multiple = TRUE,
            ordered = TRUE
          )
        )
      ),
      decorators = list(
        plot = treelis_subtitle_decorator("I am a Scatterplot matrix", "plot")
      )
    ),
    # ##############################################################
    #
    #             _         _                    _       _
    #            (_)       (_)                  | |     | |
    #   _ __ ___  _ ___ ___ _ _ __   __ _     __| | __ _| |_ __ _
    #  | '_ ` _ \| / __/ __| | '_ \ / _` |   / _` |/ _` | __/ _` |
    #  | | | | | | \__ \__ \ | | | | (_| |  | (_| | (_| | || (_| |
    #  |_| |_| |_|_|___/___/_|_| |_|\__, |   \__,_|\__,_|\__\__,_|
    #                                __/ |_____
    #                               |___/______|
    #
    #  missing_data
    # #############################################################
    tm_missing_data(
      label = "Missing data",
      decorators = list(
        summary_plot = plot_grob_decorator("A", "summary_plot"),
        combination_plot = plot_grob_decorator("B", "combination_plot"),
        summary_table = table_decorator("table", .color1 = "#f0000055"),
        by_subject_plot = caption_decorator("I am a by_subject_plot", "by_subject_plot")
      )
    ),
    ######################################
    #
    #               _   _ _
    #              | | | (_)
    #    ___  _   _| |_| |_  ___ _ __ ___
    #   / _ \| | | | __| | |/ _ \ '__/ __|
    #  | (_) | |_| | |_| | |  __/ |  \__ \
    #   \___/ \__,_|\__|_|_|\___|_|  |___/
    #
    #
    #
    #  outliers
    # #####################################
    tm_outliers(
      outlier_var = list(
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            label = "Select variable:",
            choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
            selected = "AGE",
            multiple = FALSE,
            fixed = FALSE
          )
        )
      ),
      categorical_var = list(
        data_extract_spec(
          dataname = "ADSL",
          filter = filter_spec(
            vars = vars,
            choices = value_choices(data[["ADSL"]], vars$selected),
            selected = value_choices(data[["ADSL"]], vars$selected),
            multiple = TRUE
          )
        )
      ),
      decorators = list(
        box_plot = caption_decorator("I am a good decorator", "box_plot"),
        density_plot = caption_decorator("I am a good decorator", "density_plot"),
        cumulative_plot = caption_decorator("I am a good decorator", "cumulative_plot"),
        table = table_decorator("#FFA500", "#800080")
      )
    ),
    # ########################################################
    #
    #                                 _        _     _
    #                                | |      | |   | |
    #    ___ _ __ ___  ___ ___ ______| |_ __ _| |__ | | ___
    #   / __| '__/ _ \/ __/ __|______| __/ _` | '_ \| |/ _ \
    #  | (__| | | (_) \__ \__ \      | || (_| | |_) | |  __/
    #   \___|_|  \___/|___/___/       \__\__,_|_.__/|_|\___|
    #
    #
    #
    #  cross-table
    # #######################################################
    tm_t_crosstable(
      label = "Cross Table",
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], subset = function(data) {
            idx <- !vapply(data, inherits, logical(1), c("Date", "POSIXct", "POSIXlt"))
            return(names(data)[idx])
          }),
          selected = "COUNTRY",
          multiple = TRUE,
          ordered = TRUE
        )
      ),
      y = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["ADSL"]], subset = function(data) {
            idx <- vapply(data, is.factor, logical(1))
            return(names(data)[idx])
          }),
          selected = "SEX"
        )
      ),
      decorators = list(
        table = insert_rrow_decorator("I am a good new row")
      )
    )
  )
) |> shiny::runApp()
```

</details>

---------

Co-authored-by: m7pr <[email protected]>
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>

Author: 3 people

R/tm_a_pca.R

@@ -25,20 +25,18 @@
 #' - `biplot` (`ggplot2`)
 #' - `eigenvector_plot` (`ggplot2`)
 #'
-#' Decorators can be applied to all outputs or only to specific objects using a
-#' named list of `teal_transform_module` objects.
-#' The `"default"` name is reserved for decorators that are applied to all outputs.
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
 #' See code snippet below:
 #'
 #' ```
 #' tm_a_pca(
 #'    ..., # arguments for module
 #'    decorators = list(
-#'      default = list(teal_transform_module(...)), # applied to all outputs
-#'      elbow_plot = list(teal_transform_module(...)), # applied only to `elbow_plot` output
-#'      circle_plot = list(teal_transform_module(...)) # applied only to `circle_plot` output
-#'      biplot = list(teal_transform_module(...)) # applied only to `biplot` output
-#'      eigenvector_plot = list(teal_transform_module(...)) # applied only to `eigenvector_plot` output
+#'      elbow_plot = teal_transform_module(...), # applied to the `elbow_plot` output
+#'      circle_plot = teal_transform_module(...), # applied to the `circle_plot` output
+#'      biplot = teal_transform_module(...), # applied to the `biplot` output
+#'      eigenvector_plot = teal_transform_module(...) # applied to the `eigenvector_plot` output
 #'    )
 #' )
 #' ```
@@ -186,9 +184,7 @@ tm_a_pca <- function(label = "Principal Component Analysis",
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
   available_decorators <- c("elbow_plot", "circle_plot", "biplot", "eigenvector_plot")
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, available_decorators)
-  # End of assertions
 
   # Make UI args
   args <- as.list(environment())

R/tm_a_regression.R

@@ -48,6 +48,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_a_regression(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -225,7 +238,6 @@ tm_a_regression <- function(label = "Regression Analysis",
       .var.name = "label_segment_threshold"
     )
   }
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
   # End of assertions
 

R/tm_g_association.R

@@ -29,6 +29,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`grob` created with [ggplot2::ggplotGrob()])
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_g_association(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -176,7 +189,6 @@ tm_g_association <- function(label = "Association",
   checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
   checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
 
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
   # End of assertions
 

R/tm_g_bivariate.R

@@ -51,6 +51,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_g_bivariate(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -277,7 +290,6 @@ tm_g_bivariate <- function(label = "Bivariate Plots",
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
   # End of assertions
 

R/tm_g_distribution.R

@@ -34,20 +34,18 @@
 #' - `summary_table` (`listing_df` created with [rlistings::as_listing()])
 #' - `test_table` (`listing_df` created with [rlistings::as_listing()])
 #'
-#' Decorators can be applied to all outputs or only to specific objects using a
-#' named list of `teal_transform_module` objects.
-#' The `"default"` name is reserved for decorators that are applied to all outputs.
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
 #' See code snippet below:
 #'
 #' ```
 #' tm_g_distribution(
 #'    ..., # arguments for module
 #'    decorators = list(
-#'      default = list(teal_transform_module(...)), # applied to all outputs
-#'      histogram_plot = list(teal_transform_module(...)), # applied only to `histogram_plot` output
-#'      qq_plot = list(teal_transform_module(...)) # applied only to `qq_plot` output
-#'      summary_table = list(teal_transform_module(...)) # applied only to `summary_table` output
-#'      test_table = list(teal_transform_module(...)) # applied only to `test_table` output
+#'      histogram_plot = teal_transform_module(...), # applied only to `histogram_plot` output
+#'      qq_plot = teal_transform_module(...), # applied only to `qq_plot` output
+#'      summary_table = teal_transform_module(...), # applied only to `summary_table` output
+#'      test_table = teal_transform_module(...) # applied only to `test_table` output
 #'    )
 #' )
 #' ```
@@ -194,7 +192,6 @@ tm_g_distribution <- function(label = "Distribution Module",
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
   available_decorators <- c("histogram_plot", "qq_plot", "test_table", "summary_table")
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, names = available_decorators)
 
   # End of assertions

R/tm_g_response.R

@@ -44,6 +44,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_g_response(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -202,7 +215,6 @@ tm_g_response <- function(label = "Response Plot",
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
   # End of assertions
 

R/tm_g_scatterplot.R

@@ -35,6 +35,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`ggplot2`)
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_g_scatterplot(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -299,7 +312,6 @@ tm_g_scatterplot <- function(label = "Scatterplot",
   checkmate::assert_scalar(table_dec)
   checkmate::assert_class(ggplot2_args, "ggplot2_args")
 
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
 
   # End of assertions

R/tm_g_scatterplotmatrix.R

@@ -23,6 +23,19 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `plot` (`trellis` - output of `lattice::splom`)
 #'
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
+#' See code snippet below:
+#'
+#' ```
+#' tm_g_scatterplotmatrix(
+#'    ..., # arguments for module
+#'    decorators = list(
+#'      plot = teal_transform_module(...) # applied to the `plot` output
+#'    )
+#' )
+#' ```
+#'
 #' For additional details and examples of decorators, refer to the vignette
 #' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
 #'
@@ -199,7 +212,6 @@ tm_g_scatterplotmatrix <- function(label = "Scatterplot Matrix",
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, "plot")
   # End of assertions
 

R/tm_missing_data.R

@@ -25,20 +25,18 @@
 #' - `by_subject_plot` (`ggplot2`)
 #' - `table` (`listing_df` created with [rlistings::as_listing()])
 #'
-#' Decorators can be applied to all outputs or only to specific objects using a
-#' named list of `teal_transform_module` objects.
-#' The `"default"` name is reserved for decorators that are applied to all outputs.
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
 #' See code snippet below:
 #'
 #' ```
 #' tm_missing_data(
 #'    ..., # arguments for module
 #'    decorators = list(
-#'      default = list(teal_transform_module(...)), # applied to all outputs
-#'      summary_plot = list(teal_transform_module(...)), # applied only to `summary_plot` output
-#'      combination_plot = list(teal_transform_module(...)) # applied only to `combination_plot` output
-#'      by_subject_plot = list(teal_transform_module(...)) # applied only to `by_subject_plot` output
-#'      table = list(teal_transform_module(...)) # applied only to `table` output
+#'      summary_plot = teal_transform_module(...), # applied only to `summary_plot` output
+#'      combination_plot = teal_transform_module(...), # applied only to `combination_plot` output
+#'      by_subject_plot = teal_transform_module(...), # applied only to `by_subject_plot` output
+#'      table = teal_transform_module(...) # applied only to `table` output
 #'    )
 #' )
 #' ```
@@ -147,8 +145,7 @@ tm_missing_data <- function(label = "Missing data",
   checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
-  available_decorators <- c("summary_plot", "combination_plot", "by_subject_plot", "summary_table")
-  decorators <- normalize_decorators(decorators)
+  available_decorators <- c("summary_plot", "combination_plot", "by_subject_plot", "table")
   assert_decorators(decorators, names = available_decorators)
   # End of assertions
 
@@ -446,7 +443,7 @@ encoding_missing_data <- function(id, summary_per_patient = FALSE, ggtheme, data
         selected = "counts",
         inline = TRUE
       ),
-      ui_decorate_teal_data(ns("dec_summary_table"), decorators = select_decorators(decorators, "summary_table"))
+      ui_decorate_teal_data(ns("dec_summary_table"), decorators = select_decorators(decorators, "table"))
     ),
     teal.widgets::panel_item(
       title = "Plot settings",
@@ -1295,7 +1292,7 @@ srv_missing_data <- function(id,
     decorated_summary_table_q <- srv_decorate_teal_data(
       id = "dec_summary_table",
       data = summary_table_q,
-      decorators = select_decorators(decorators, "summary_table"),
+      decorators = select_decorators(decorators, "table"),
       expr = table
     )
 

R/tm_outliers.R

@@ -23,20 +23,18 @@
 #' - `cumulative_plot` (`ggplot2`)
 #' - `table` (`listing_df` created with [rlistings::as_listing()])
 #'
-#' Decorators can be applied to all outputs or only to specific objects using a
-#' named list of `teal_transform_module` objects.
-#' The `"default"` name is reserved for decorators that are applied to all outputs.
+#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
+#' The name of this list corresponds to the name of the output to which the decorator is applied.
 #' See code snippet below:
 #'
 #' ```
 #' tm_outliers(
 #'    ..., # arguments for module
 #'    decorators = list(
-#'      default = list(teal_transform_module(...)), # applied to all outputs
-#'      box_plot = list(teal_transform_module(...)), # applied only to `box_plot` output
-#'      density_plot = list(teal_transform_module(...)) # applied only to `density_plot` output
-#'      cumulative_plot = list(teal_transform_module(...)) # applied only to `cumulative_plot` output
-#'      table = list(teal_transform_module(...)) # applied only to `table` output
+#'      box_plot = teal_transform_module(...), # applied only to `box_plot` output
+#'      density_plot = teal_transform_module(...), # applied only to `density_plot` output
+#'      cumulative_plot = teal_transform_module(...), # applied only to `cumulative_plot` output
+#'      table = teal_transform_module(...) # applied only to `table` output
 #'    )
 #' )
 #' ```
@@ -197,7 +195,6 @@ tm_outliers <- function(label = "Outliers Module",
   checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
 
   available_decorators <- c("box_plot", "density_plot", "cumulative_plot", "table")
-  decorators <- normalize_decorators(decorators)
   assert_decorators(decorators, names = available_decorators)
   # End of assertions