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#' Shared parameters documentation
#'
#' Defines common arguments shared across multiple functions in the package
#' to avoid repetition by using `inheritParams`.
#'
#' @param plot_height (`numeric`) optional, specifies the plot height as a three-element vector of
#' `value`, `min`, and `max` intended for use with a slider UI element.
#' @param plot_width (`numeric`) optional, specifies the plot width as a three-element vector of
#' `value`, `min`, and `max` for a slider encoding the plot width.
#' @param rotate_xaxis_labels (`logical`) optional, whether to rotate plot X axis labels. Does not
#' rotate by default (`FALSE`).
#' @param ggtheme (`character`) optional, `ggplot2` theme to be used by default. Defaults to `"gray"`.
#' @param ggplot2_args (`ggplot2_args`) object created by [teal.widgets::ggplot2_args()]
#' with settings for the module plot.
#' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
#'
#' For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`
#' @param basic_table_args (`basic_table_args`) object created by [teal.widgets::basic_table_args()]
#' with settings for the module table.
#' The argument is merged with options variable `teal.basic_table_args` and default module setup.
#'
#' For more details see the vignette: `vignette("custom-basic-table-arguments", package = "teal.widgets")`
#' @param pre_output (`shiny.tag`) optional, text or UI element to be displayed before the module's output,
#' providing context or a title.
#'  with text placed before the output to put the output into context. For example a title.
#' @param post_output (`shiny.tag`) optional, text or UI element to be displayed after the module's output,
#' adding context or further instructions. Elements like `shiny::helpText()` are useful.
#' @param alpha (`integer(1)` or `integer(3)`) optional, specifies point opacity.
#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
#' vector of `value`, `min`, and `max`.
#' @param size (`integer(1)` or `integer(3)`) optional, specifies point size.
#' - When the length of `size` is one: the plot point sizes will have a fixed size.
#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
#' vector of `value`, `min`, and `max`.
#' @param decorators `r lifecycle::badge("experimental")`
#' (`list` of `teal_transform_module`, named `list` of `teal_transform_module`) optional,
#' decorator for tables or plots included in the module output reported.
#' When a named list of `teal_transform_module`, the decorators are applied to the respective output objects.
#'
#' Otherwise, the decorators are applied to all objects, which is equivalent as using the name `default`.
#'
#' See section "Decorating Module" below for more details.
#'
#' @return Object of class `teal_module` to be used in `teal` applications.
#'
#' @name shared_params
#' @keywords internal
NULL

#' Add labels for facets to a `ggplot2` object
#'
#' Enhances a `ggplot2` plot by adding labels that describe
#' the faceting variables along the x and y axes.
#'
#' @param p (`ggplot2`) object to which facet labels will be added.
#' @param xfacet_label (`character`) Label for the facet along the x-axis.
#' If `NULL`, no label is added. If a vector, labels are joined with " & ".
#' @param yfacet_label (`character`) Label for the facet along the y-axis.
#' Similar behavior to `xfacet_label`.
#'
#' @return Returns `grid` or `grob` object (to be drawn with `grid.draw`)
#'
#' @examples
#' library(ggplot2)
#' library(grid)
#'
#' p <- ggplot(mtcars) +
#'   aes(x = mpg, y = disp) +
#'   geom_point() +
#'   facet_grid(gear ~ cyl)
#'
#' xfacet_label <- "cylinders"
#' yfacet_label <- "gear"
#' res <- add_facet_labels(p, xfacet_label, yfacet_label)
#' grid.newpage()
#' grid.draw(res)
#'
#' grid.newpage()
#' grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label))
#' grid.newpage()
#' grid.draw(add_facet_labels(p, xfacet_label, yfacet_label = NULL))
#' grid.newpage()
#' grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL))
#'
#' @export
#'
add_facet_labels <- function(p, xfacet_label = NULL, yfacet_label = NULL) {
  checkmate::assert_class(p, classes = "ggplot")
  checkmate::assert_character(xfacet_label, null.ok = TRUE, min.len = 1)
  checkmate::assert_character(yfacet_label, null.ok = TRUE, min.len = 1)
  if (is.null(xfacet_label) && is.null(yfacet_label)) {
    return(ggplotGrob(p))
  }
  grid::grid.grabExpr({
    g <- ggplotGrob(p)

    # we are going to replace these, so we make sure they have nothing in them
    checkmate::assert_class(g$grobs[[grep("xlab-t", g$layout$name, fixed = TRUE)]], "zeroGrob")
    checkmate::assert_class(g$grobs[[grep("ylab-r", g$layout$name, fixed = TRUE)]], "zeroGrob")

    xaxis_label_grob <- g$grobs[[grep("xlab-b", g$layout$name, fixed = TRUE)]]
    xaxis_label_grob$children[[1]]$label <- paste(xfacet_label, collapse = " & ")
    yaxis_label_grob <- g$grobs[[grep("ylab-l", g$layout$name, fixed = TRUE)]]
    yaxis_label_grob$children[[1]]$label <- paste(yfacet_label, collapse = " & ")
    yaxis_label_grob$children[[1]]$rot <- 270

    top_height <- if (is.null(xfacet_label)) 0 else grid::unit(2, "line")
    right_width <- if (is.null(yfacet_label)) 0 else grid::unit(2, "line")

    grid::grid.newpage()
    grid::pushViewport(grid::plotViewport(margins = c(0, 0, top_height, right_width), name = "ggplot"))
    grid::grid.draw(g)
    grid::upViewport(1)

    # draw x facet
    if (!is.null(xfacet_label)) {
      grid::pushViewport(grid::viewport(
        x = 0, y = grid::unit(1, "npc") - top_height, width = grid::unit(1, "npc"),
        height = top_height, just = c("left", "bottom"), name = "topxaxis"
      ))
      grid::grid.draw(xaxis_label_grob)
      grid::upViewport(1)
    }

    # draw y facet
    if (!is.null(yfacet_label)) {
      grid::pushViewport(grid::viewport(
        x = grid::unit(1, "npc") - grid::unit(as.numeric(right_width) / 2, "line"), y = 0, width = right_width,
        height = grid::unit(1, "npc"), just = c("left", "bottom"), name = "rightyaxis"
      ))
      grid::grid.draw(yaxis_label_grob)
      grid::upViewport(1)
    }
  })
}

#' Call a function with a character vector for the `...` argument
#'
#' @param fun (`character`) Name of a function where the `...` argument shall be replaced by values from `str_args`.
#' @param str_args (`character`) A character vector that the function shall be executed with
#'
#' @return
#' Value of call to `fun` with arguments specified in `str_args`.
#'
#' @keywords internal
call_fun_dots <- function(fun, str_args) {
  do.call("call", c(list(fun), lapply(str_args, as.name)), quote = TRUE)
}

#' Generate a string for a variable including its label
#'
#' @param var_names (`character`) Name of variable to extract labels from.
#' @param dataset (`dataset`) Name of analysis dataset.
#' @param prefix,suffix (`character`) String to paste to the beginning/end of the variable name with label.
#' @param wrap_width (`numeric`) Number of characters to wrap original label to. Defaults to 80.
#'
#' @return (`character`) String with variable name and label.
#'
#' @keywords internal
#'
varname_w_label <- function(var_names,
                            dataset,
                            wrap_width = 80,
                            prefix = NULL,
                            suffix = NULL) {
  add_label <- function(var_names) {
    label <- vapply(
      dataset[var_names], function(x) {
        attr_label <- attr(x, "label")
        `if`(is.null(attr_label), "", attr_label)
      },
      character(1)
    )

    if (length(label) == 1 && !is.na(label) && !identical(label, "")) {
      paste0(prefix, label, " [", var_names, "]", suffix)
    } else {
      var_names
    }
  }

  if (length(var_names) < 1) {
    NULL
  } else if (length(var_names) == 1) {
    stringr::str_wrap(add_label(var_names), width = wrap_width)
  } else if (length(var_names) > 1) {
    stringr::str_wrap(vapply(var_names, add_label, character(1)), width = wrap_width)
  }
}

# see vignette("ggplot2-specs", package="ggplot2")
shape_names <- c(
  "circle", paste("circle", c("open", "filled", "cross", "plus", "small")), "bullet",
  "square", paste("square", c("open", "filled", "cross", "plus", "triangle")),
  "diamond", paste("diamond", c("open", "filled", "plus")),
  "triangle", paste("triangle", c("open", "filled", "square")),
  paste("triangle down", c("open", "filled")),
  "plus", "cross", "asterisk"
)

#' Get icons to represent variable types in dataset
#'
#' @param var_type (`character`) of R internal types (classes).
#' @return (`character`) vector of HTML icons corresponding to data type in each column.
#' @keywords internal
variable_type_icons <- function(var_type) {
  checkmate::assert_character(var_type, any.missing = FALSE)

  class_to_icon <- list(
    numeric = "arrow-up-1-9",
    integer = "arrow-up-1-9",
    logical = "pause",
    Date = "calendar",
    POSIXct = "calendar",
    POSIXlt = "calendar",
    factor = "chart-bar",
    character = "keyboard",
    primary_key = "key",
    unknown = "circle-question"
  )
  class_to_icon <- lapply(class_to_icon, function(icon_name) toString(icon(icon_name, lib = "font-awesome")))

  unname(vapply(
    var_type,
    FUN.VALUE = character(1),
    FUN = function(class) {
      if (class == "") {
        class
      } else if (is.null(class_to_icon[[class]])) {
        class_to_icon[["unknown"]]
      } else {
        class_to_icon[[class]]
      }
    }
  ))
}

#' Include `CSS` files from `/inst/css/` package directory to application header
#'
#' `system.file` should not be used to access files in other packages, it does
#' not work with `devtools`. Therefore, we redefine this method in each package
#' as needed. Thus, we do not export this method
#'
#' @param pattern (`character`) optional, regular expression to match the file names to be included.
#'
#' @return HTML code that includes `CSS` files.
#' @keywords internal
#'
include_css_files <- function(pattern = "*") {
  css_files <- list.files(
    system.file("css", package = "teal.modules.general", mustWork = TRUE),
    pattern = pattern, full.names = TRUE
  )
  if (length(css_files) == 0) {
    return(NULL)
  }
  singleton(tags$head(lapply(css_files, includeCSS)))
}

#' JavaScript condition to check if a specific tab is active
#'
#' @param id (`character(1)`) the id of the tab panel with tabs.
#' @param name (`character(1)`) the name of the tab.
#' @return JavaScript expression to be used in `shiny::conditionalPanel()` to determine
#' if the specified tab is active.
#' @keywords internal
#'
is_tab_active_js <- function(id, name) {
  # supporting the bs3 and higher version at the same time
  sprintf(
    "$(\"#%1$s > li.active\").text().trim() == '%2$s' || $(\"#%1$s > li a.active\").text().trim() == '%2$s'",
    id, name
  )
}

#' Assert single selection on `data_extract_spec` object
#' Helper to reduce code in assertions
#' @noRd
#'
assert_single_selection <- function(x,
                                    .var.name = checkmate::vname(x)) { # nolint: object_name.
  if (any(vapply(x, function(.x) .x$select$multiple, logical(1)))) {
    stop("'", .var.name, "' should not allow multiple selection")
  }
  invisible(TRUE)
}

#' Wrappers around `srv_transform_teal_data` that allows to decorate the data
#' @inheritParams teal::srv_transform_teal_data
#' @param expr (`expression` or `reactive`) to evaluate on the output of the decoration.
#' When an expression it must be inline code. See [within()]
#' Default is `NULL` which won't evaluate any appending code.
#' @param expr_is_reactive (`logical(1)`) whether `expr` is a reactive expression
#' that skips defusing the argument.
#' @details
#' `srv_decorate_teal_data` is a wrapper around `srv_transform_teal_data` that
#' allows to decorate the data with additional expressions.
#' When original `teal_data` object is in error state, it will show that error
#' first.
#'
#' @keywords internal
srv_decorate_teal_data <- function(id, data, decorators, expr, expr_is_reactive = FALSE) {
  checkmate::assert_class(data, classes = "reactive")
  checkmate::assert_list(decorators, "teal_transform_module")
  checkmate::assert_flag(expr_is_reactive)

  missing_expr <- missing(expr)
  if (!missing_expr && !expr_is_reactive) {
    expr <- dplyr::enexpr(expr) # Using dplyr re-export to avoid adding rlang to Imports
  }

  moduleServer(id, function(input, output, session) {
    decorated_output <- srv_transform_teal_data("inner", data = data, transformators = decorators)

    reactive({
      data_out <- try(data(), silent = TRUE)
      if (inherits(data_out, "qenv.error")) {
        data()
      } else {
        # ensure original errors are displayed and `eval_code` is never executed with NULL
        req(data(), decorated_output())
        if (missing_expr) {
          decorated_output()
        } else if (expr_is_reactive) {
          teal.code::eval_code(decorated_output(), expr())
        } else {
          teal.code::eval_code(decorated_output(), expr)
        }
      }
    })
  })
}

#' @rdname srv_decorate_teal_data
#' @details
#' `ui_decorate_teal_data` is a wrapper around `ui_transform_teal_data`.
#' @keywords internal
ui_decorate_teal_data <- function(id, decorators, ...) {
  teal::ui_transform_teal_data(NS(id, "inner"), transformators = decorators, ...)
}

#' Internal function to check if decorators is a valid object
#' @noRd
check_decorators <- function(x, names = NULL) { # nolint: object_name.

  check_message <- checkmate::check_list(x, names = "named")

  if (!is.null(names)) {
    if (isTRUE(check_message)) {
      if (length(names(x)) != length(unique(names(x)))) {
        check_message <- sprintf(
          "The `decorators` must contain unique names from these names: %s.",
          paste(names, collapse = ", ")
        )
      }
    } else {
      check_message <- sprintf(
        "The `decorators` must be a named list from these names: %s.",
        paste(names, collapse = ", ")
      )
    }
  }

  if (!isTRUE(check_message)) {
    return(check_message)
  }

  valid_elements <- vapply(
    x,
    checkmate::test_class,
    classes = "teal_transform_module",
    FUN.VALUE = logical(1L)
  )

  if (all(valid_elements)) {
    return(TRUE)
  }

  "Make sure that the named list contains 'teal_transform_module' objects created using `teal_transform_module()`."
}
#' Internal assertion on decorators
#' @noRd
assert_decorators <- checkmate::makeAssertionFunction(check_decorators)

#' Subset decorators based on the scope
#'
#' @param scope (`character`) a character vector of decorator names to include.
#' @param decorators (named `list`) of list decorators to subset.
#'
#' @return Subsetted list with all decorators to include.
#' It can be an empty list if none of the scope exists in `decorators` argument.
#' @keywords internal
select_decorators <- function(decorators, scope) {
  checkmate::assert_character(scope, null.ok = TRUE)
  if (scope %in% names(decorators)) {
    decorators[scope]
  } else {
    list()
  }
}

1		.onLoad <- function(libname, pkgname) {
2	!	teal.logger::register_logger(namespace = "teal.modules.general")
3	!	teal.logger::register_handlers("teal.modules.general")
4		}
5
6		### global variables
7		ggplot_themes <- c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void")
8
9		#' @importFrom lifecycle deprecated
10		interactive <- NULL

1		#' `teal` module: Front page
2		#'
3		#' Creates a simple front page for `teal` applications, displaying
4		#' introductory text, tables, additional `html` or `shiny` tags, and footnotes.
5		#'
6		#' @inheritParams teal::module
7		#' @param header_text (`character` vector) text to be shown at the top of the module, for each
8		#' element, if named the name is shown first in bold as a header followed by the value. The first
9		#' element's header is displayed larger than the others.
10		#' @param tables (`named list` of `data.frame`s) tables to be shown in the module.
11		#' @param additional_tags (`shiny.tag.list` or `html`) additional `shiny` tags or `html` to be included after the table,
12		#' for example to include an image, `tagList(tags$img(src = "image.png"))` or to include further `html`,
13		#' `HTML("html text here")`.
14		#' @param footnotes (`character` vector) of text to be shown at the bottom of the module, for each
15		#' element, if named the name is shown first in bold, followed by the value.
16		#' @param show_metadata (`logical`) `r lifecycle::badge("deprecated")` indicating
17		#' whether the metadata of the datasets be available on the module.
18		#' Metadata shown automatically when `datanames` set.
19		#' @inheritParams tm_variable_browser
20		#'
21		#' @inherit shared_params return
22		#'
23		#' @examplesShinylive
24		#' library(teal.modules.general)
25		#' interactive <- function() TRUE
26		#' {{ next_example }}
27		#' @examples
28		#' data <- teal_data()
29		#' data <- within(data, {
30		#' require(nestcolor)
31		#' ADSL <- teal.data::rADSL
32		#' attr(ADSL, "metadata") <- list("Author" = "NEST team", "data_source" = "synthetic data")
33		#' })
34		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
35		#'
36		#' table_1 <- data.frame(Info = c("A", "B"), Text = c("A", "B"))
37		#' table_2 <- data.frame(`Column 1` = c("C", "D"), `Column 2` = c(5.5, 6.6), `Column 3` = c("A", "B"))
38		#' table_3 <- data.frame(Info = c("E", "F"), Text = c("G", "H"))
39		#'
40		#' table_input <- list(
41		#' "Table 1" = table_1,
42		#' "Table 2" = table_2,
43		#' "Table 3" = table_3
44		#' )
45		#'
46		#' app <- init(
47		#' data = data,
48		#' modules = modules(
49		#' tm_front_page(
50		#' header_text = c(
51		#' "Important information" = "It can go here.",
52		#' "Other information" = "Can go here."
53		#' ),
54		#' tables = table_input,
55		#' additional_tags = HTML("Additional HTML or shiny tags go here <br>"),
56		#' footnotes = c("X" = "is the first footnote", "Y is the second footnote")
57		#' )
58		#' )
59		#' ) \|>
60		#' modify_header(tags$h1("Sample Application")) \|>
61		#' modify_footer(tags$p("Application footer"))
62		#'
63		#' if (interactive()) {
64		#' shinyApp(app$ui, app$server)
65		#' }
66		#'
67		#' @export
68		#'
69		tm_front_page <- function(label = "Front page",
70		header_text = character(0),
71		tables = list(),
72		additional_tags = tagList(),
73		footnotes = character(0),
74		show_metadata = deprecated(),
75		datanames = if (missing(show_metadata)) NULL else "all",
76		transformators = list()) {
77	!	message("Initializing tm_front_page")
78
79		# Start of assertions
80	!	checkmate::assert_string(label)
81	!	checkmate::assert_character(header_text, min.len = 0, any.missing = FALSE)
82	!	checkmate::assert_list(tables, types = "data.frame", names = "named", any.missing = FALSE)
83	!	checkmate::assert_multi_class(additional_tags, classes = c("shiny.tag.list", "html"))
84	!	checkmate::assert_character(footnotes, min.len = 0, any.missing = FALSE)
85	!	if (!missing(show_metadata)) {
86	!	lifecycle::deprecate_soft(
87	!	when = "0.4.0",
88	!	what = "tm_front_page(show_metadata)",
89	!	with = "tm_front_page(datanames)",
90	!	details = c(
91	!	"With `datanames` you can select which datasets are displayed.",
92	!	i = "Use `tm_front_page(datanames = 'all')` to keep the previous behavior and avoid this warning."
93		)
94		)
95		}
96	!	checkmate::assert_character(datanames, min.len = 0, min.chars = 1, null.ok = TRUE)
97
98		# End of assertions
99
100		# Make UI args
101	!	args <- as.list(environment())
102
103	!	ans <- module(
104	!	label = label,
105	!	server = srv_front_page,
106	!	ui = ui_front_page,
107	!	ui_args = args,
108	!	server_args = list(tables = tables),
109	!	datanames = datanames, ,
110	!	transformators = transformators
111		)
112	!	attr(ans, "teal_bookmarkable") <- TRUE
113	!	ans
114		}
115
116		# UI function for the front page module
117		ui_front_page <- function(id, ...) {
118	!	args <- list(...)
119	!	ns <- NS(id)
120
121	!	tagList(
122	!	include_css_files("custom"),
123	!	tags$div(
124	!	id = "front_page_content",
125	!	class = "ml-8",
126	!	tags$div(
127	!	id = "front_page_headers",
128	!	get_header_tags(args$header_text)
129		),
130	!	tags$div(
131	!	id = "front_page_tables",
132	!	class = "ml-4",
133	!	get_table_tags(args$tables, ns)
134		),
135	!	tags$div(
136	!	id = "front_page_custom_html",
137	!	class = "my-4",
138	!	args$additional_tags
139		),
140	!	if (length(args$datanames) > 0L) {
141	!	tags$div(
142	!	id = "front_page_metabutton",
143	!	class = "m-4",
144	!	actionButton(ns("metadata_button"), "Show metadata")
145		)
146		},
147	!	tags$footer(
148	!	class = ".small",
149	!	get_footer_tags(args$footnotes)
150		)
151		)
152		)
153		}
154
155		# Server function for the front page module
156		srv_front_page <- function(id, data, tables) {
157	!	checkmate::assert_class(data, "reactive")
158	!	checkmate::assert_class(isolate(data()), "teal_data")
159	!	moduleServer(id, function(input, output, session) {
160	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
161
162	!	ns <- session$ns
163
164	!	setBookmarkExclude("metadata_button")
165
166	!	lapply(seq_along(tables), function(idx) {
167	!	output[[paste0("table_", idx)]] <- renderTable(
168	!	tables[[idx]],
169	!	bordered = TRUE,
170	!	caption = names(tables)[idx],
171	!	caption.placement = "top"
172		)
173		})
174	!	if (length(isolate(names(data()))) > 0L) {
175	!	observeEvent(
176	!	input$metadata_button, showModal(
177	!	modalDialog(
178	!	title = "Metadata",
179	!	dataTableOutput(ns("metadata_table")),
180	!	size = "l",
181	!	easyClose = TRUE
182		)
183		)
184		)
185
186	!	metadata_data_frame <- reactive({
187	!	datanames <- names(data())
188	!	convert_metadata_to_dataframe(
189	!	lapply(datanames, function(dataname) attr(data()[[dataname]], "metadata")),
190	!	datanames
191		)
192		})
193
194	!	output$metadata_table <- renderDataTable({
195	!	validate(need(nrow(metadata_data_frame()) > 0, "The data has no associated metadata"))
196	!	metadata_data_frame()
197		})
198		}
199		})
200		}
201
202		## utils functions
203
204		get_header_tags <- function(header_text) {
205	!	if (length(header_text) == 0) {
206	!	return(list())
207		}
208
209	!	get_single_header_tags <- function(header_text, p_text, header_tag = tags$h4) {
210	!	tagList(
211	!	tags$div(
212	!	if (!is.null(header_text) && nchar(header_text) > 0) header_tag(header_text),
213	!	tags$p(p_text)
214		)
215		)
216		}
217
218	!	header_tags <- get_single_header_tags(names(header_text[1]), header_text[1], header_tag = tags$h3)
219	!	c(header_tags, mapply(get_single_header_tags, utils::tail(names(header_text), -1), utils::tail(header_text, -1)))
220		}
221
222		get_table_tags <- function(tables, ns) {
223	!	if (length(tables) == 0) {
224	!	return(list())
225		}
226	!	table_tags <- c(lapply(seq_along(tables), function(idx) {
227	!	list(
228	!	tableOutput(ns(paste0("table_", idx)))
229		)
230		}))
231	!	return(table_tags)
232		}
233
234		get_footer_tags <- function(footnotes) {
235	!	if (length(footnotes) == 0) {
236	!	return(list())
237		}
238	!	bold_texts <- if (is.null(names(footnotes))) rep("", length(footnotes)) else names(footnotes)
239	!	footnote_tags <- mapply(function(bold_text, value) {
240	!	list(
241	!	tags$div(
242	!	tags$b(bold_text),
243	!	value,
244	!	tags$br()
245		)
246		)
247	!	}, bold_text = bold_texts, value = footnotes)
248		}
249
250		# take a list of metadata, one item per dataset (raw_metadata each element from datasets$get_metadata())
251		# and the corresponding datanames and output a data.frame with columns {Dataset, Name, Value}.
252		# which are, the Dataset the metadata came from, the metadata's name and value
253		convert_metadata_to_dataframe <- function(raw_metadata, datanames) {
254	4x	output <- mapply(function(metadata, dataname) {
255	6x	if (is.null(metadata)) {
256	2x	return(data.frame(Dataset = character(0), Name = character(0), Value = character(0)))
257		}
258	4x	return(data.frame(
259	4x	Dataset = dataname,
260	4x	Name = names(metadata),
261	4x	Value = unname(unlist(lapply(metadata, as.character)))
262		))
263	4x	}, raw_metadata, datanames, SIMPLIFY = FALSE)
264	4x	do.call(rbind, output)
265		}

1		#' `teal` module: Stack plots of variables and show association with reference variable
2		#'
3		#' Module provides functionality for visualizing the distribution of variables and
4		#' their association with a reference variable.
5		#' It supports configuring the appearance of the plots, including themes and whether to show associations.
6		#'
7		#'
8		#' @note For more examples, please see the vignette "Using association plot" via
9		#' `vignette("using-association-plot", package = "teal.modules.general")`.
10		#'
11		#' @inheritParams teal::module
12		#' @inheritParams shared_params
13		#' @param ref (`data_extract_spec` or `list` of multiple `data_extract_spec`)
14		#' Reference variable, must accepts a `data_extract_spec` with `select_spec(multiple = FALSE)`
15		#' to ensure single selection option.
16		#' @param vars (`data_extract_spec` or `list` of multiple `data_extract_spec`)
17		#' Variables to be associated with the reference variable.
18		#' @param show_association (`logical`) optional, whether show association of `vars`
19		#' with reference variable. Defaults to `TRUE`.
20		#' @param distribution_theme,association_theme (`character`) optional, `ggplot2` themes to be used by default.
21		#' Default to `"gray"`.
22		#'
23		#' @param ggplot2_args `r roxygen_ggplot2_args_param("Bivariate1", "Bivariate2")`
24		#'
25		#' @inherit shared_params return
26		#'
27		#' @section Decorating Module:
28		#'
29		#' This module generates the following objects, which can be modified in place using decorators:
30		#' - `plot` (`grob` created with [ggplot2::ggplotGrob()])
31		#'
32		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
33		#' The name of this list corresponds to the name of the output to which the decorator is applied.
34		#' See code snippet below:
35		#'
36		#' ```
37		#' tm_g_association(
38		#' ..., # arguments for module
39		#' decorators = list(
40		#' plot = teal_transform_module(...) # applied to the `plot` output
41		#' )
42		#' )
43		#' ```
44		#'
45		#' For additional details and examples of decorators, refer to the vignette
46		#' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
47		#'
48		#' @examplesShinylive
49		#' library(teal.modules.general)
50		#' interactive <- function() TRUE
51		#' {{ next_example }}
52		#' @examples
53		#' # general data example
54		#' data <- teal_data()
55		#' data <- within(data, {
56		#' require(nestcolor)
57		#' CO2 <- CO2
58		#' factors <- names(Filter(isTRUE, vapply(CO2, is.factor, logical(1L))))
59		#' CO2[factors] <- lapply(CO2[factors], as.character)
60		#' })
61		#'
62		#' app <- init(
63		#' data = data,
64		#' modules = modules(
65		#' tm_g_association(
66		#' ref = data_extract_spec(
67		#' dataname = "CO2",
68		#' select = select_spec(
69		#' label = "Select variable:",
70		#' choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
71		#' selected = "Plant",
72		#' fixed = FALSE
73		#' )
74		#' ),
75		#' vars = data_extract_spec(
76		#' dataname = "CO2",
77		#' select = select_spec(
78		#' label = "Select variables:",
79		#' choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
80		#' selected = "Treatment",
81		#' multiple = TRUE,
82		#' fixed = FALSE
83		#' )
84		#' )
85		#' )
86		#' )
87		#' )
88		#' if (interactive()) {
89		#' shinyApp(app$ui, app$server)
90		#' }
91		#'
92		#' @examplesShinylive
93		#' library(teal.modules.general)
94		#' interactive <- function() TRUE
95		#' {{ next_example }}
96		#' @examples
97		#' # CDISC data example
98		#' data <- teal_data()
99		#' data <- within(data, {
100		#' require(nestcolor)
101		#' ADSL <- teal.data::rADSL
102		#' })
103		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
104		#'
105		#' app <- init(
106		#' data = data,
107		#' modules = modules(
108		#' tm_g_association(
109		#' ref = data_extract_spec(
110		#' dataname = "ADSL",
111		#' select = select_spec(
112		#' label = "Select variable:",
113		#' choices = variable_choices(
114		#' data[["ADSL"]],
115		#' c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
116		#' ),
117		#' selected = "RACE",
118		#' fixed = FALSE
119		#' )
120		#' ),
121		#' vars = data_extract_spec(
122		#' dataname = "ADSL",
123		#' select = select_spec(
124		#' label = "Select variables:",
125		#' choices = variable_choices(
126		#' data[["ADSL"]],
127		#' c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
128		#' ),
129		#' selected = "BMRKR2",
130		#' multiple = TRUE,
131		#' fixed = FALSE
132		#' )
133		#' )
134		#' )
135		#' )
136		#' )
137		#' if (interactive()) {
138		#' shinyApp(app$ui, app$server)
139		#' }
140		#'
141		#' @export
142		#'
143		tm_g_association <- function(label = "Association",
144		ref,
145		vars,
146		show_association = TRUE,
147		plot_height = c(600, 400, 5000),
148		plot_width = NULL,
149		distribution_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint: line_length.
150		association_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint: line_length.
151		pre_output = NULL,
152		post_output = NULL,
153		ggplot2_args = teal.widgets::ggplot2_args(),
154		transformators = list(),
155		decorators = list()) {
156	!	message("Initializing tm_g_association")
157
158		# Normalize the parameters
159	!	if (inherits(ref, "data_extract_spec")) ref <- list(ref)
160	!	if (inherits(vars, "data_extract_spec")) vars <- list(vars)
161	!	if (inherits(ggplot2_args, "ggplot2_args")) ggplot2_args <- list(default = ggplot2_args)
162
163		# Start of assertions
164	!	checkmate::assert_string(label)
165
166	!	checkmate::assert_list(ref, types = "data_extract_spec")
167	!	if (!all(vapply(ref, function(x) !x$select$multiple, logical(1)))) {
168	!	stop("'ref' should not allow multiple selection")
169		}
170
171	!	checkmate::assert_list(vars, types = "data_extract_spec")
172	!	checkmate::assert_flag(show_association)
173
174	!	checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
175	!	checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
176	!	checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
177	!	checkmate::assert_numeric(
178	!	plot_width[1],
179	!	lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
180		)
181
182	!	distribution_theme <- match.arg(distribution_theme)
183	!	association_theme <- match.arg(association_theme)
184
185	!	checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
186	!	checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
187
188	!	plot_choices <- c("Bivariate1", "Bivariate2")
189	!	checkmate::assert_list(ggplot2_args, types = "ggplot2_args")
190	!	checkmate::assert_subset(names(ggplot2_args), c("default", plot_choices))
191
192	!	assert_decorators(decorators, "plot")
193		# End of assertions
194
195		# Make UI args
196	!	args <- as.list(environment())
197
198	!	data_extract_list <- list(
199	!	ref = ref,
200	!	vars = vars
201		)
202
203	!	ans <- module(
204	!	label = label,
205	!	server = srv_tm_g_association,
206	!	ui = ui_tm_g_association,
207	!	ui_args = args,
208	!	server_args = c(
209	!	data_extract_list,
210	!	list(plot_height = plot_height, plot_width = plot_width, ggplot2_args = ggplot2_args, decorators = decorators)
211		),
212	!	transformators = transformators,
213	!	datanames = teal.transform::get_extract_datanames(data_extract_list)
214		)
215	!	attr(ans, "teal_bookmarkable") <- TRUE
216	!	ans
217		}
218
219		# UI function for the association module
220		ui_tm_g_association <- function(id, ...) {
221	!	ns <- NS(id)
222	!	args <- list(...)
223	!	is_single_dataset_value <- teal.transform::is_single_dataset(args$ref, args$vars)
224
225	!	teal.widgets::standard_layout(
226	!	output = teal.widgets::white_small_well(
227	!	textOutput(ns("title")),
228	!	tags$br(),
229	!	teal.widgets::plot_with_settings_ui(id = ns("myplot"))
230		),
231	!	encoding = tags$div(
232		### Reporter
233	!	teal.reporter::simple_reporter_ui(ns("simple_reporter")),
234		###
235	!	tags$label("Encodings", class = "text-primary"),
236	!	teal.transform::datanames_input(args[c("ref", "vars")]),
237	!	teal.transform::data_extract_ui(
238	!	id = ns("ref"),
239	!	label = "Reference variable",
240	!	data_extract_spec = args$ref,
241	!	is_single_dataset = is_single_dataset_value
242		),
243	!	teal.transform::data_extract_ui(
244	!	id = ns("vars"),
245	!	label = "Associated variables",
246	!	data_extract_spec = args$vars,
247	!	is_single_dataset = is_single_dataset_value
248		),
249	!	checkboxInput(
250	!	ns("association"),
251	!	"Association with reference variable",
252	!	value = args$show_association
253		),
254	!	checkboxInput(
255	!	ns("show_dist"),
256	!	"Scaled frequencies",
257	!	value = FALSE
258		),
259	!	checkboxInput(
260	!	ns("log_transformation"),
261	!	"Log transformed",
262	!	value = FALSE
263		),
264	!	ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(args$decorators, "plot")),
265	!	teal.widgets::panel_group(
266	!	teal.widgets::panel_item(
267	!	title = "Plot settings",
268	!	teal.widgets::optionalSliderInputValMinMax(ns("alpha"), "Scatterplot opacity:", c(0.5, 0, 1), ticks = FALSE),
269	!	teal.widgets::optionalSliderInputValMinMax(ns("size"), "Scatterplot points size:", c(2, 1, 8), ticks = FALSE),
270	!	checkboxInput(ns("swap_axes"), "Swap axes", value = FALSE),
271	!	checkboxInput(ns("rotate_xaxis_labels"), "Rotate X axis labels", value = FALSE),
272	!	selectInput(
273	!	inputId = ns("distribution_theme"),
274	!	label = "Distribution theme (by ggplot):",
275	!	choices = ggplot_themes,
276	!	selected = args$distribution_theme,
277	!	multiple = FALSE
278		),
279	!	selectInput(
280	!	inputId = ns("association_theme"),
281	!	label = "Association theme (by ggplot):",
282	!	choices = ggplot_themes,
283	!	selected = args$association_theme,
284	!	multiple = FALSE
285		)
286		)
287		)
288		),
289	!	forms = tagList(
290	!	teal.widgets::verbatim_popup_ui(ns("rcode"), "Show R code")
291		),
292	!	pre_output = args$pre_output,
293	!	post_output = args$post_output
294		)
295		}
296
297		# Server function for the association module
298		srv_tm_g_association <- function(id,
299		data,
300		reporter,
301		filter_panel_api,
302		ref,
303		vars,
304		plot_height,
305		plot_width,
306		ggplot2_args,
307		decorators) {
308	!	with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
309	!	with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
310	!	checkmate::assert_class(data, "reactive")
311	!	checkmate::assert_class(isolate(data()), "teal_data")
312
313	!	moduleServer(id, function(input, output, session) {
314	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
315
316	!	selector_list <- teal.transform::data_extract_multiple_srv(
317	!	data_extract = list(ref = ref, vars = vars),
318	!	datasets = data,
319	!	select_validation_rule = list(
320	!	ref = shinyvalidate::compose_rules(
321	!	shinyvalidate::sv_required("A reference variable needs to be selected."),
322	!	~ if ((.) %in% selector_list()$vars()$select) {
323	!	"Associated variables and reference variable cannot overlap"
324		}
325		),
326	!	vars = shinyvalidate::compose_rules(
327	!	shinyvalidate::sv_required("An associated variable needs to be selected."),
328	!	~ if (length(selector_list()$ref()$select) != 0 && selector_list()$ref()$select %in% (.)) {
329	!	"Associated variables and reference variable cannot overlap"
330		}
331		)
332		)
333		)
334
335	!	iv_r <- reactive({
336	!	iv <- shinyvalidate::InputValidator$new()
337	!	teal.transform::compose_and_enable_validators(iv, selector_list)
338		})
339
340	!	anl_merged_input <- teal.transform::merge_expression_srv(
341	!	datasets = data,
342	!	selector_list = selector_list
343		)
344
345	!	anl_merged_q <- reactive({
346	!	req(anl_merged_input())
347	!	data() %>% teal.code::eval_code(as.expression(anl_merged_input()$expr))
348		})
349
350	!	merged <- list(
351	!	anl_input_r = anl_merged_input,
352	!	anl_q_r = anl_merged_q
353		)
354
355	!	output_q <- reactive({
356	!	teal::validate_inputs(iv_r())
357
358	!	ANL <- merged$anl_q_r()[["ANL"]]
359	!	teal::validate_has_data(ANL, 3)
360
361	!	vars_names <- merged$anl_input_r()$columns_source$vars
362
363	!	ref_name <- as.vector(merged$anl_input_r()$columns_source$ref)
364	!	association <- input$association
365	!	show_dist <- input$show_dist
366	!	log_transformation <- input$log_transformation
367	!	rotate_xaxis_labels <- input$rotate_xaxis_labels
368	!	swap_axes <- input$swap_axes
369	!	distribution_theme <- input$distribution_theme
370	!	association_theme <- input$association_theme
371
372	!	is_scatterplot <- is.numeric(ANL[[ref_name]]) && any(vapply(ANL[vars_names], is.numeric, logical(1)))
373	!	if (is_scatterplot) {
374	!	shinyjs::show("alpha")
375	!	shinyjs::show("size")
376	!	alpha <- input$alpha
377	!	size <- input$size
378		} else {
379	!	shinyjs::hide("alpha")
380	!	shinyjs::hide("size")
381	!	alpha <- 0.5
382	!	size <- 2
383		}
384
385	!	teal::validate_has_data(ANL[, c(ref_name, vars_names)], 3, complete = TRUE, allow_inf = FALSE)
386
387		# reference
388	!	ref_class <- class(ANL[[ref_name]])[1]
389	!	if (is.numeric(ANL[[ref_name]]) && log_transformation) {
390		# works for both integers and doubles
391	!	ref_cl_name <- call("log", as.name(ref_name))
392	!	ref_cl_lbl <- varname_w_label(ref_name, ANL, prefix = "Log of ")
393		} else {
394		# silently ignore when non-numeric even if `log` is selected because some
395		# variables may be numeric and others not
396	!	ref_cl_name <- as.name(ref_name)
397	!	ref_cl_lbl <- varname_w_label(ref_name, ANL)
398		}
399
400	!	user_ggplot2_args <- teal.widgets::resolve_ggplot2_args(
401	!	user_plot = ggplot2_args[["Bivariate1"]],
402	!	user_default = ggplot2_args$default
403		)
404
405	!	ref_call <- bivariate_plot_call(
406	!	data_name = "ANL",
407	!	x = ref_cl_name,
408	!	x_class = ref_class,
409	!	x_label = ref_cl_lbl,
410	!	freq = !show_dist,
411	!	theme = distribution_theme,
412	!	rotate_xaxis_labels = rotate_xaxis_labels,
413	!	swap_axes = FALSE,
414	!	size = size,
415	!	alpha = alpha,
416	!	ggplot2_args = user_ggplot2_args
417		)
418
419		# association
420	!	ref_class_cov <- ifelse(association, ref_class, "NULL")
421
422	!	var_calls <- lapply(vars_names, function(var_i) {
423	!	var_class <- class(ANL[[var_i]])[1]
424	!	if (is.numeric(ANL[[var_i]]) && log_transformation) {
425		# works for both integers and doubles
426	!	var_cl_name <- call("log", as.name(var_i))
427	!	var_cl_lbl <- varname_w_label(var_i, ANL, prefix = "Log of ")
428		} else {
429		# silently ignore when non-numeric even if `log` is selected because some
430		# variables may be numeric and others not
431	!	var_cl_name <- as.name(var_i)
432	!	var_cl_lbl <- varname_w_label(var_i, ANL)
433		}
434
435	!	user_ggplot2_args <- teal.widgets::resolve_ggplot2_args(
436	!	user_plot = ggplot2_args[["Bivariate2"]],
437	!	user_default = ggplot2_args$default
438		)
439
440	!	bivariate_plot_call(
441	!	data_name = "ANL",
442	!	x = ref_cl_name,
443	!	y = var_cl_name,
444	!	x_class = ref_class_cov,
445	!	y_class = var_class,
446	!	x_label = ref_cl_lbl,
447	!	y_label = var_cl_lbl,
448	!	theme = association_theme,
449	!	freq = !show_dist,
450	!	rotate_xaxis_labels = rotate_xaxis_labels,
451	!	swap_axes = swap_axes,
452	!	alpha = alpha,
453	!	size = size,
454	!	ggplot2_args = user_ggplot2_args
455		)
456		})
457
458		# helper function to format variable name
459	!	format_varnames <- function(x) {
460	!	if (is.numeric(ANL[[x]]) && log_transformation) {
461	!	varname_w_label(x, ANL, prefix = "Log of ")
462		} else {
463	!	varname_w_label(x, ANL)
464		}
465		}
466	!	new_title <-
467	!	if (association) {
468	!	switch(as.character(length(vars_names)),
469	!	"0" = sprintf("Value distribution for %s", ref_cl_lbl),
470	!	"1" = sprintf(
471	!	"Association between %s and %s",
472	!	ref_cl_lbl,
473	!	format_varnames(vars_names)
474		),
475	!	sprintf(
476	!	"Associations between %s and: %s",
477	!	ref_cl_lbl,
478	!	paste(lapply(vars_names, format_varnames), collapse = ", ")
479		)
480		)
481		} else {
482	!	switch(as.character(length(vars_names)),
483	!	"0" = sprintf("Value distribution for %s", ref_cl_lbl),
484	!	sprintf(
485	!	"Value distributions for %s and %s",
486	!	ref_cl_lbl,
487	!	paste(lapply(vars_names, format_varnames), collapse = ", ")
488		)
489		)
490		}
491	!	teal.code::eval_code(
492	!	merged$anl_q_r(),
493	!	substitute(
494	!	expr = title <- new_title,
495	!	env = list(new_title = new_title)
496		)
497		) %>%
498	!	teal.code::eval_code(
499	!	substitute(
500	!	expr = {
501	!	plot_top <- plot_calls[[1]]
502	!	plot_bottom <- plot_calls[[1]]
503	!	plot <- tern::stack_grobs(grobs = lapply(list(plot_top, plot_bottom), ggplotGrob))
504		},
505	!	env = list(
506	!	plot_calls = do.call(
507	!	"call",
508	!	c(list("list", ref_call), var_calls),
509	!	quote = TRUE
510		)
511		)
512		)
513		)
514		})
515
516	!	decorated_output_grob_q <- srv_decorate_teal_data(
517	!	id = "decorator",
518	!	data = output_q,
519	!	decorators = select_decorators(decorators, "plot"),
520	!	expr = {
521	!	grid::grid.newpage()
522	!	grid::grid.draw(plot)
523		}
524		)
525
526	!	plot_r <- reactive({
527	!	req(iv_r()$is_valid())
528	!	req(decorated_output_grob_q())[["plot"]]
529		})
530
531	!	pws <- teal.widgets::plot_with_settings_srv(
532	!	id = "myplot",
533	!	plot_r = plot_r,
534	!	height = plot_height,
535	!	width = plot_width
536		)
537
538	!	output$title <- renderText({
539	!	teal.code::dev_suppress(output_q()[["title"]])
540		})
541
542		# Render R code.
543	!	source_code_r <- reactive(teal.code::get_code(req(decorated_output_grob_q())))
544
545	!	teal.widgets::verbatim_popup_srv(
546	!	id = "rcode",
547	!	verbatim_content = source_code_r,
548	!	title = "Association Plot"
549		)
550
551		### REPORTER
552	!	if (with_reporter) {
553	!	card_fun <- function(comment, label) {
554	!	card <- teal::report_card_template(
555	!	title = "Association Plot",
556	!	label = label,
557	!	with_filter = with_filter,
558	!	filter_panel_api = filter_panel_api
559		)
560	!	card$append_text("Plot", "header3")
561	!	card$append_plot(plot_r(), dim = pws$dim())
562	!	if (!comment == "") {
563	!	card$append_text("Comment", "header3")
564	!	card$append_text(comment)
565		}
566	!	card$append_src(source_code_r())
567	!	card
568		}
569	!	teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
570		}
571		###
572		})
573		}

1		#' `teal` module: Response plot
2		#'
3		#' Generates a response plot for a given `response` and `x` variables.
4		#' This module allows users customize and add annotations to the plot depending
5		#' on the module's arguments.
6		#' It supports showing the counts grouped by other variable facets (by row / column),
7		#' swapping the coordinates, show count annotations and displaying the response plot
8		#' as frequency or density.
9		#'
10		#' @inheritParams teal::module
11		#' @inheritParams shared_params
12		#' @param response (`data_extract_spec` or `list` of multiple `data_extract_spec`)
13		#' Which variable to use as the response.
14		#' You can define one fixed column by setting `fixed = TRUE` inside the `select_spec`.
15		#'
16		#' The `data_extract_spec` must not allow multiple selection in this case.
17		#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
18		#' Specifies which variable to use on the X-axis of the response plot.
19		#' Allow the user to select multiple columns from the `data` allowed in teal.
20		#'
21		#' The `data_extract_spec` must not allow multiple selection in this case.
22		#' @param row_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`)
23		#' optional specification of the data variable(s) to use for faceting rows.
24		#' @param col_facet (`data_extract_spec` or `list` of multiple `data_extract_spec`)
25		#' optional specification of the data variable(s) to use for faceting columns.
26		#' @param coord_flip (`logical(1)`)
27		#' Indicates whether to flip coordinates between `x` and `response`.
28		#' The default value is `FALSE` and it will show the `x` variable on the x-axis
29		#' and the `response` variable on the y-axis.
30		#' @param count_labels (`logical(1)`)
31		#' Indicates whether to show count labels.
32		#' Defaults to `TRUE`.
33		#' @param freq (`logical(1)`)
34		#' Indicates whether to display frequency (`TRUE`) or density (`FALSE`).
35		#' Defaults to density (`FALSE`).
36		#'
37		#' @inherit shared_params return
38		#'
39		#' @note For more examples, please see the vignette "Using response plot" via
40		#' `vignette("using-response-plot", package = "teal.modules.general")`.
41		#'
42		#' @section Decorating Module:
43		#'
44		#' This module generates the following objects, which can be modified in place using decorators:
45		#' - `plot` (`ggplot2`)
46		#'
47		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
48		#' The name of this list corresponds to the name of the output to which the decorator is applied.
49		#' See code snippet below:
50		#'
51		#' ```
52		#' tm_g_response(
53		#' ..., # arguments for module
54		#' decorators = list(
55		#' plot = teal_transform_module(...) # applied to the `plot` output
56		#' )
57		#' )
58		#' ```
59		#'
60		#' For additional details and examples of decorators, refer to the vignette
61		#' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
62		#'
63		#' @examplesShinylive
64		#' library(teal.modules.general)
65		#' interactive <- function() TRUE
66		#' {{ next_example }}
67		#' @examples
68		#' # general data example
69		#' data <- teal_data()
70		#' data <- within(data, {
71		#' require(nestcolor)
72		#' mtcars <- mtcars
73		#' for (v in c("cyl", "vs", "am", "gear")) {
74		#' mtcars[[v]] <- as.factor(mtcars[[v]])
75		#' }
76		#' })
77		#'
78		#' app <- init(
79		#' data = data,
80		#' modules = modules(
81		#' tm_g_response(
82		#' label = "Response Plots",
83		#' response = data_extract_spec(
84		#' dataname = "mtcars",
85		#' select = select_spec(
86		#' label = "Select variable:",
87		#' choices = variable_choices(data[["mtcars"]], c("cyl", "gear")),
88		#' selected = "cyl",
89		#' multiple = FALSE,
90		#' fixed = FALSE
91		#' )
92		#' ),
93		#' x = data_extract_spec(
94		#' dataname = "mtcars",
95		#' select = select_spec(
96		#' label = "Select variable:",
97		#' choices = variable_choices(data[["mtcars"]], c("vs", "am")),
98		#' selected = "vs",
99		#' multiple = FALSE,
100		#' fixed = FALSE
101		#' )
102		#' )
103		#' )
104		#' )
105		#' )
106		#' if (interactive()) {
107		#' shinyApp(app$ui, app$server)
108		#' }
109		#'
110		#' @examplesShinylive
111		#' library(teal.modules.general)
112		#' interactive <- function() TRUE
113		#' {{ next_example }}
114		#' @examples
115		#' # CDISC data example
116		#' data <- teal_data()
117		#' data <- within(data, {
118		#' require(nestcolor)
119		#' ADSL <- teal.data::rADSL
120		#' })
121		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
122		#'
123		#' app <- init(
124		#' data = data,
125		#' modules = modules(
126		#' tm_g_response(
127		#' label = "Response Plots",
128		#' response = data_extract_spec(
129		#' dataname = "ADSL",
130		#' select = select_spec(
131		#' label = "Select variable:",
132		#' choices = variable_choices(data[["ADSL"]], c("BMRKR2", "COUNTRY")),
133		#' selected = "BMRKR2",
134		#' multiple = FALSE,
135		#' fixed = FALSE
136		#' )
137		#' ),
138		#' x = data_extract_spec(
139		#' dataname = "ADSL",
140		#' select = select_spec(
141		#' label = "Select variable:",
142		#' choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
143		#' selected = "RACE",
144		#' multiple = FALSE,
145		#' fixed = FALSE
146		#' )
147		#' )
148		#' )
149		#' )
150		#' )
151		#' if (interactive()) {
152		#' shinyApp(app$ui, app$server)
153		#' }
154		#'
155		#' @export
156		#'
157		tm_g_response <- function(label = "Response Plot",
158		response,
159		x,
160		row_facet = NULL,
161		col_facet = NULL,
162		coord_flip = FALSE,
163		count_labels = TRUE,
164		rotate_xaxis_labels = FALSE,
165		freq = FALSE,
166		plot_height = c(600, 400, 5000),
167		plot_width = NULL,
168		ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"),
169		ggplot2_args = teal.widgets::ggplot2_args(),
170		pre_output = NULL,
171		post_output = NULL,
172		transformators = list(),
173		decorators = list()) {
174	!	message("Initializing tm_g_response")
175
176		# Normalize the parameters
177	!	if (inherits(response, "data_extract_spec")) response <- list(response)
178	!	if (inherits(x, "data_extract_spec")) x <- list(x)
179	!	if (inherits(row_facet, "data_extract_spec")) row_facet <- list(row_facet)
180	!	if (inherits(col_facet, "data_extract_spec")) col_facet <- list(col_facet)
181
182		# Start of assertions
183	!	checkmate::assert_string(label)
184
185	!	checkmate::assert_list(response, types = "data_extract_spec")
186	!	if (!all(vapply(response, function(x) !("" %in% x$select$choices), logical(1)))) {
187	!	stop("'response' should not allow empty values")
188		}
189	!	assert_single_selection(response)
190
191	!	checkmate::assert_list(x, types = "data_extract_spec")
192	!	if (!all(vapply(x, function(x) !("" %in% x$select$choices), logical(1)))) {
193	!	stop("'x' should not allow empty values")
194		}
195	!	assert_single_selection(x)
196
197	!	checkmate::assert_list(row_facet, types = "data_extract_spec", null.ok = TRUE)
198	!	checkmate::assert_list(col_facet, types = "data_extract_spec", null.ok = TRUE)
199	!	checkmate::assert_flag(coord_flip)
200	!	checkmate::assert_flag(count_labels)
201	!	checkmate::assert_flag(rotate_xaxis_labels)
202	!	checkmate::assert_flag(freq)
203
204	!	checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
205	!	checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
206	!	checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
207	!	checkmate::assert_numeric(
208	!	plot_width[1],
209	!	lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
210		)
211
212	!	ggtheme <- match.arg(ggtheme)
213	!	checkmate::assert_class(ggplot2_args, "ggplot2_args")
214
215	!	checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
216	!	checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
217
218	!	assert_decorators(decorators, "plot")
219		# End of assertions
220
221		# Make UI args
222	!	args <- as.list(environment())
223
224	!	data_extract_list <- list(
225	!	response = response,
226	!	x = x,
227	!	row_facet = row_facet,
228	!	col_facet = col_facet
229		)
230
231	!	ans <- module(
232	!	label = label,
233	!	server = srv_g_response,
234	!	ui = ui_g_response,
235	!	ui_args = args,
236	!	server_args = c(
237	!	data_extract_list,
238	!	list(
239	!	plot_height = plot_height,
240	!	plot_width = plot_width,
241	!	ggplot2_args = ggplot2_args,
242	!	decorators = decorators
243		)
244		),
245	!	transformators = transformators,
246	!	datanames = teal.transform::get_extract_datanames(data_extract_list)
247		)
248	!	attr(ans, "teal_bookmarkable") <- TRUE
249	!	ans
250		}
251
252		# UI function for the response module
253		ui_g_response <- function(id, ...) {
254	!	ns <- NS(id)
255	!	args <- list(...)
256	!	is_single_dataset_value <- teal.transform::is_single_dataset(args$response, args$x, args$row_facet, args$col_facet)
257
258	!	teal.widgets::standard_layout(
259	!	output = teal.widgets::white_small_well(
260	!	teal.widgets::plot_with_settings_ui(id = ns("myplot"))
261		),
262	!	encoding = tags$div(
263		### Reporter
264	!	teal.reporter::simple_reporter_ui(ns("simple_reporter")),
265		###
266	!	tags$label("Encodings", class = "text-primary"),
267	!	teal.transform::datanames_input(args[c("response", "x", "row_facet", "col_facet")]),
268	!	teal.transform::data_extract_ui(
269	!	id = ns("response"),
270	!	label = "Response variable",
271	!	data_extract_spec = args$response,
272	!	is_single_dataset = is_single_dataset_value
273		),
274	!	teal.transform::data_extract_ui(
275	!	id = ns("x"),
276	!	label = "X variable",
277	!	data_extract_spec = args$x,
278	!	is_single_dataset = is_single_dataset_value
279		),
280	!	if (!is.null(args$row_facet)) {
281	!	teal.transform::data_extract_ui(
282	!	id = ns("row_facet"),
283	!	label = "Row facetting",
284	!	data_extract_spec = args$row_facet,
285	!	is_single_dataset = is_single_dataset_value
286		)
287		},
288	!	if (!is.null(args$col_facet)) {
289	!	teal.transform::data_extract_ui(
290	!	id = ns("col_facet"),
291	!	label = "Column facetting",
292	!	data_extract_spec = args$col_facet,
293	!	is_single_dataset = is_single_dataset_value
294		)
295		},
296	!	shinyWidgets::radioGroupButtons(
297	!	inputId = ns("freq"),
298	!	label = NULL,
299	!	choices = c("frequency", "density"),
300	!	selected = ifelse(args$freq, "frequency", "density"),
301	!	justified = TRUE
302		),
303	!	ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(args$decorators, "plot")),
304	!	teal.widgets::panel_group(
305	!	teal.widgets::panel_item(
306	!	title = "Plot settings",
307	!	checkboxInput(ns("count_labels"), "Add count labels", value = args$count_labels),
308	!	checkboxInput(ns("coord_flip"), "Swap axes", value = args$coord_flip),
309	!	checkboxInput(ns("rotate_xaxis_labels"), "Rotate X axis labels", value = args$rotate_xaxis_labels),
310	!	selectInput(
311	!	inputId = ns("ggtheme"),
312	!	label = "Theme (by ggplot):",
313	!	choices = ggplot_themes,
314	!	selected = args$ggtheme,
315	!	multiple = FALSE
316		)
317		)
318		)
319		),
320	!	forms = tagList(
321	!	teal.widgets::verbatim_popup_ui(ns("rcode"), "Show R code")
322		),
323	!	pre_output = args$pre_output,
324	!	post_output = args$post_output
325		)
326		}
327
328		# Server function for the response module
329		srv_g_response <- function(id,
330		data,
331		reporter,
332		filter_panel_api,
333		response,
334		x,
335		row_facet,
336		col_facet,
337		plot_height,
338		plot_width,
339		ggplot2_args,
340		decorators) {
341	!	with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
342	!	with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
343	!	checkmate::assert_class(data, "reactive")
344	!	checkmate::assert_class(isolate(data()), "teal_data")
345	!	moduleServer(id, function(input, output, session) {
346	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
347
348	!	data_extract <- list(response = response, x = x, row_facet = row_facet, col_facet = col_facet)
349
350	!	rule_diff <- function(other) {
351	!	function(value) {
352	!	if (other %in% names(selector_list())) {
353	!	othervalue <- selector_list()[[other]]()[["select"]]
354	!	if (!is.null(othervalue)) {
355	!	if (identical(value, othervalue)) {
356	!	"Row and column facetting variables must be different."
357		}
358		}
359		}
360		}
361		}
362
363	!	selector_list <- teal.transform::data_extract_multiple_srv(
364	!	data_extract = data_extract,
365	!	datasets = data,
366	!	select_validation_rule = list(
367	!	response = shinyvalidate::sv_required("Please define a column for the response variable"),
368	!	x = shinyvalidate::sv_required("Please define a column for X variable"),
369	!	row_facet = shinyvalidate::compose_rules(
370	!	shinyvalidate::sv_optional(),
371	!	~ if (length(.) > 1) "There must be 1 or no row facetting variable.",
372	!	rule_diff("col_facet")
373		),
374	!	col_facet = shinyvalidate::compose_rules(
375	!	shinyvalidate::sv_optional(),
376	!	~ if (length(.) > 1) "There must be 1 or no column facetting variable.",
377	!	rule_diff("row_facet")
378		)
379		)
380		)
381
382	!	iv_r <- reactive({
383	!	iv <- shinyvalidate::InputValidator$new()
384	!	iv$add_rule("ggtheme", shinyvalidate::sv_required("Please select a theme"))
385	!	teal.transform::compose_and_enable_validators(iv, selector_list)
386		})
387
388	!	anl_merged_input <- teal.transform::merge_expression_srv(
389	!	selector_list = selector_list,
390	!	datasets = data
391		)
392
393	!	anl_merged_q <- reactive({
394	!	req(anl_merged_input())
395	!	data() %>%
396	!	teal.code::eval_code(as.expression(anl_merged_input()$expr))
397		})
398
399	!	merged <- list(
400	!	anl_input_r = anl_merged_input,
401	!	anl_q_r = anl_merged_q
402		)
403
404	!	output_q <- reactive({
405	!	teal::validate_inputs(iv_r())
406
407	!	qenv <- merged$anl_q_r()
408	!	ANL <- qenv[["ANL"]]
409	!	resp_var <- as.vector(merged$anl_input_r()$columns_source$response)
410	!	x <- as.vector(merged$anl_input_r()$columns_source$x)
411
412	!	validate(need(is.factor(ANL[[resp_var]]), "Please select a factor variable as the response."))
413	!	validate(need(is.factor(ANL[[x]]), "Please select a factor variable as the X-Variable."))
414	!	teal::validate_has_data(ANL, 10)
415	!	teal::validate_has_data(ANL[, c(resp_var, x)], 10, complete = TRUE, allow_inf = FALSE)
416
417	!	row_facet_name <- if (length(merged$anl_input_r()$columns_source$row_facet) == 0) {
418	!	character(0)
419		} else {
420	!	as.vector(merged$anl_input_r()$columns_source$row_facet)
421		}
422	!	col_facet_name <- if (length(merged$anl_input_r()$columns_source$col_facet) == 0) {
423	!	character(0)
424		} else {
425	!	as.vector(merged$anl_input_r()$columns_source$col_facet)
426		}
427
428	!	freq <- input$freq == "frequency"
429	!	swap_axes <- input$coord_flip
430	!	counts <- input$count_labels
431	!	rotate_xaxis_labels <- input$rotate_xaxis_labels
432	!	ggtheme <- input$ggtheme
433
434	!	arg_position <- if (freq) "stack" else "fill"
435
436	!	rowf <- if (length(row_facet_name) != 0) as.name(row_facet_name)
437	!	colf <- if (length(col_facet_name) != 0) as.name(col_facet_name)
438	!	resp_cl <- as.name(resp_var)
439	!	x_cl <- as.name(x)
440
441	!	if (swap_axes) {
442	!	qenv <- teal.code::eval_code(
443	!	qenv,
444	!	substitute(
445	!	expr = ANL[[x]] <- with(ANL, forcats::fct_rev(x_cl)),
446	!	env = list(x = x, x_cl = x_cl)
447		)
448		)
449		}
450
451	!	qenv <- teal.code::eval_code(
452	!	qenv,
453	!	substitute(
454	!	expr = ANL[[resp_var]] <- factor(ANL[[resp_var]]),
455	!	env = list(resp_var = resp_var)
456		)
457		) %>%
458		# rowf and colf will be a NULL if not set by a user
459	!	teal.code::eval_code(
460	!	substitute(
461	!	expr = ANL2 <- ANL %>%
462	!	dplyr::group_by_at(dplyr::vars(x_cl, resp_cl, rowf, colf)) %>%
463	!	dplyr::summarise(ns = dplyr::n()) %>%
464	!	dplyr::group_by_at(dplyr::vars(x_cl, rowf, colf)) %>%
465	!	dplyr::mutate(sums = sum(ns), percent = round(ns / sums * 100, 1)),
466	!	env = list(x_cl = x_cl, resp_cl = resp_cl, rowf = rowf, colf = colf)
467		)
468		) %>%
469	!	teal.code::eval_code(
470	!	substitute(
471	!	expr = ANL3 <- ANL %>%
472	!	dplyr::group_by_at(dplyr::vars(x_cl, rowf, colf)) %>%
473	!	dplyr::summarise(ns = dplyr::n()),
474	!	env = list(x_cl = x_cl, rowf = rowf, colf = colf)
475		)
476		)
477
478	!	plot_call <- substitute(
479	!	expr = ggplot(ANL2, aes(x = x_cl, y = ns)) +
480	!	geom_bar(aes(fill = resp_cl), stat = "identity", position = arg_position),
481	!	env = list(
482	!	x_cl = x_cl,
483	!	resp_cl = resp_cl,
484	!	arg_position = arg_position
485		)
486		)
487
488	!	if (!freq) {
489	!	plot_call <- substitute(
490	!	plot_call + expand_limits(y = c(0, 1.1)),
491	!	env = list(plot_call = plot_call)
492		)
493		}
494
495	!	if (counts) {
496	!	plot_call <- substitute(
497	!	expr = plot_call +
498	!	geom_text(
499	!	data = ANL2,
500	!	aes(label = ns, x = x_cl, y = ns, group = resp_cl),
501	!	col = "white",
502	!	vjust = "middle",
503	!	hjust = "middle",
504	!	position = position_anl2_value
505		) +
506	!	geom_text(
507	!	data = ANL3, aes(label = ns, x = x_cl, y = anl3_y),
508	!	hjust = hjust_value,
509	!	vjust = vjust_value,
510	!	position = position_anl3_value
511		),
512	!	env = list(
513	!	plot_call = plot_call,
514	!	x_cl = x_cl,
515	!	resp_cl = resp_cl,
516	!	hjust_value = if (swap_axes) "left" else "middle",
517	!	vjust_value = if (swap_axes) "middle" else -1,
518	!	position_anl2_value = if (!freq) quote(position_fill(0.5)) else quote(position_stack(0.5)), # nolint: line_length.
519	!	anl3_y = if (!freq) 1.1 else as.name("ns"),
520	!	position_anl3_value = if (!freq) "fill" else "stack"
521		)
522		)
523		}
524
525	!	if (swap_axes) {
526	!	plot_call <- substitute(plot_call + coord_flip(), env = list(plot_call = plot_call))
527		}
528
529	!	facet_cl <- facet_ggplot_call(row_facet_name, col_facet_name)
530
531	!	if (!is.null(facet_cl)) {
532	!	plot_call <- substitute(expr = plot_call + facet_cl, env = list(plot_call = plot_call, facet_cl = facet_cl))
533		}
534
535	!	dev_ggplot2_args <- teal.widgets::ggplot2_args(
536	!	labs = list(
537	!	x = varname_w_label(x, ANL),
538	!	y = varname_w_label(resp_var, ANL, prefix = "Proportion of "),
539	!	fill = varname_w_label(resp_var, ANL)
540		),
541	!	theme = list(legend.position = "bottom")
542		)
543
544	!	if (rotate_xaxis_labels) {
545	!	dev_ggplot2_args$theme[["axis.text.x"]] <- quote(element_text(angle = 45, hjust = 1))
546		}
547
548	!	all_ggplot2_args <- teal.widgets::resolve_ggplot2_args(
549	!	user_plot = ggplot2_args,
550	!	module_plot = dev_ggplot2_args
551		)
552
553	!	parsed_ggplot2_args <- teal.widgets::parse_ggplot2_args(
554	!	all_ggplot2_args,
555	!	ggtheme = ggtheme
556		)
557
558	!	plot_call <- substitute(expr = {
559	!	plot <- plot_call + labs + ggthemes + themes
560	!	}, env = list(
561	!	plot_call = plot_call,
562	!	labs = parsed_ggplot2_args$labs,
563	!	themes = parsed_ggplot2_args$theme,
564	!	ggthemes = parsed_ggplot2_args$ggtheme
565		))
566
567	!	teal.code::eval_code(qenv, plot_call)
568		})
569
570	!	decorated_output_plot_q <- srv_decorate_teal_data(
571	!	id = "decorator",
572	!	data = output_q,
573	!	decorators = select_decorators(decorators, "plot"),
574	!	expr = print(plot)
575		)
576
577	!	plot_r <- reactive(req(decorated_output_plot_q())[["plot"]])
578
579		# Insert the plot into a plot_with_settings module from teal.widgets
580	!	pws <- teal.widgets::plot_with_settings_srv(
581	!	id = "myplot",
582	!	plot_r = plot_r,
583	!	height = plot_height,
584	!	width = plot_width
585		)
586
587		# Render R code.
588	!	source_code_r <- reactive(teal.code::get_code(req(decorated_output_plot_q())))
589
590	!	teal.widgets::verbatim_popup_srv(
591	!	id = "rcode",
592	!	verbatim_content = source_code_r,
593	!	title = "Show R Code for Response"
594		)
595
596		### REPORTER
597	!	if (with_reporter) {
598	!	card_fun <- function(comment, label) {
599	!	card <- teal::report_card_template(
600	!	title = "Response Plot",
601	!	label = label,
602	!	with_filter = with_filter,
603	!	filter_panel_api = filter_panel_api
604		)
605	!	card$append_text("Plot", "header3")
606	!	card$append_plot(plot_r(), dim = pws$dim())
607	!	if (!comment == "") {
608	!	card$append_text("Comment", "header3")
609	!	card$append_text(comment)
610		}
611	!	card$append_src(source_code_r())
612	!	card
613		}
614	!	teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
615		}
616		###
617		})
618		}

1		#' `teal` module: File viewer
2		#'
3		#' The file viewer module provides a tool to view static files.
4		#' Supported formats include text formats, `PDF`, `PNG` `APNG`,
5		#' `JPEG` `SVG`, `WEBP`, `GIF` and `BMP`.
6		#'
7		#' @inheritParams teal::module
8		#' @inheritParams shared_params
9		#' @param input_path (`list`) of the input paths, optional. Each element can be:
10		#'
11		#' Paths can be specified as absolute paths or relative to the running directory of the application.
12		#' Default to the current working directory if not supplied.
13		#'
14		#' @inherit shared_params return
15		#'
16		#' @examplesShinylive
17		#' library(teal.modules.general)
18		#' interactive <- function() TRUE
19		#' {{ next_example }}
20		#' @examples
21		#' data <- teal_data()
22		#' data <- within(data, {
23		#' data <- data.frame(1)
24		#' })
25		#'
26		#' app <- init(
27		#' data = data,
28		#' modules = modules(
29		#' tm_file_viewer(
30		#' input_path = list(
31		#' folder = system.file("sample_files", package = "teal.modules.general"),
32		#' png = system.file("sample_files/sample_file.png", package = "teal.modules.general"),
33		#' txt = system.file("sample_files/sample_file.txt", package = "teal.modules.general"),
34		#' url = "https://fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
35		#' )
36		#' )
37		#' )
38		#' )
39		#' if (interactive()) {
40		#' shinyApp(app$ui, app$server)
41		#' }
42		#'
43		#' @export
44		#'
45		tm_file_viewer <- function(label = "File Viewer Module",
46		input_path = list("Current Working Directory" = ".")) {
47	!	message("Initializing tm_file_viewer")
48
49		# Normalize the parameters
50	!	if (length(label) == 0 \|\| identical(label, "")) label <- " "
51	!	if (length(input_path) == 0 \|\| identical(input_path, "")) input_path <- list()
52
53		# Start of assertions
54	!	checkmate::assert_string(label)
55
56	!	checkmate::assert(
57	!	checkmate::check_list(input_path, types = "character", min.len = 0),
58	!	checkmate::check_character(input_path, min.len = 1)
59		)
60	!	if (length(input_path) > 0) {
61	!	valid_url <- function(url_input, timeout = 2) {
62	!	con <- try(url(url_input), silent = TRUE)
63	!	check <- suppressWarnings(try(open.connection(con, open = "rt", timeout = timeout), silent = TRUE)[1])
64	!	try(close.connection(con), silent = TRUE)
65	!	is.null(check)
66		}
67	!	idx <- vapply(input_path, function(x) file.exists(x) \|\| valid_url(x), logical(1))
68
69	!	if (!all(idx)) {
70	!	warning(
71	!	paste0(
72	!	"Non-existent file or url path. Please provide valid paths for:\n",
73	!	paste0(input_path[!idx], collapse = "\n")
74		)
75		)
76		}
77	!	input_path <- input_path[idx]
78		} else {
79	!	warning(
80	!	"No file or url paths were provided."
81		)
82		}
83		# End of assertions
84
85		# Make UI args
86	!	args <- as.list(environment())
87
88	!	ans <- module(
89	!	label = label,
90	!	server = srv_viewer,
91	!	server_args = list(input_path = input_path),
92	!	ui = ui_viewer,
93	!	ui_args = args,
94	!	datanames = NULL
95		)
96	!	attr(ans, "teal_bookmarkable") <- FALSE
97	!	ans
98		}
99
100		# UI function for the file viewer module
101		ui_viewer <- function(id, ...) {
102	!	args <- list(...)
103	!	ns <- NS(id)
104
105	!	tagList(
106	!	include_css_files("custom"),
107	!	teal.widgets::standard_layout(
108	!	output = tags$div(
109	!	uiOutput(ns("output"))
110		),
111	!	encoding = tags$div(
112	!	class = "file_viewer_encoding",
113	!	tags$label("Encodings", class = "text-primary"),
114	!	shinyTree::shinyTree(
115	!	ns("tree"),
116	!	dragAndDrop = FALSE,
117	!	sort = FALSE,
118	!	wholerow = TRUE,
119	!	theme = "proton",
120	!	multiple = FALSE
121		)
122		)
123		)
124		)
125		}
126
127		# Server function for the file viewer module
128		srv_viewer <- function(id, input_path) {
129	!	moduleServer(id, function(input, output, session) {
130	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
131
132	!	temp_dir <- tempfile()
133	!	if (!dir.exists(temp_dir)) {
134	!	dir.create(temp_dir, recursive = TRUE)
135		}
136	!	addResourcePath(basename(temp_dir), temp_dir)
137
138	!	test_path_text <- function(selected_path, type) {
139	!	out <- tryCatch(
140	!	expr = {
141	!	if (type != "url") {
142	!	selected_path <- normalizePath(selected_path, winslash = "/")
143		}
144	!	readLines(con = selected_path)
145		},
146	!	error = function(cond) FALSE,
147	!	warning = function(cond) {
148	!	`if`(grepl("^incomplete final line found on", cond[[1]]), suppressWarnings(eval(cond[[2]])), FALSE)
149		}
150		)
151		}
152
153	!	handle_connection_type <- function(selected_path) {
154	!	file_extension <- tools::file_ext(selected_path)
155	!	file_class <- suppressWarnings(file(selected_path))
156	!	close(file_class)
157
158	!	output_text <- test_path_text(selected_path, type = class(file_class)[1])
159
160	!	if (class(file_class)[1] == "url") {
161	!	list(selected_path = selected_path, output_text = output_text)
162		} else {
163	!	file.copy(normalizePath(selected_path, winslash = "/"), temp_dir)
164	!	selected_path <- file.path(basename(temp_dir), basename(selected_path))
165	!	list(selected_path = selected_path, output_text = output_text)
166		}
167		}
168
169	!	display_file <- function(selected_path) {
170	!	con_type <- handle_connection_type(selected_path)
171	!	file_extension <- tools::file_ext(selected_path)
172	!	if (file_extension %in% c("png", "apng", "jpg", "jpeg", "svg", "gif", "webp", "bmp")) {
173	!	tags$img(src = con_type$selected_path, alt = "file does not exist")
174	!	} else if (file_extension == "pdf") {
175	!	tags$embed(
176	!	class = "embed_pdf",
177	!	src = con_type$selected_path
178		)
179	!	} else if (!isFALSE(con_type$output_text[1])) {
180	!	tags$pre(paste0(con_type$output_text, collapse = "\n"))
181		} else {
182	!	tags$p("Please select a supported format.")
183		}
184		}
185
186	!	tree_list <- function(file_or_dir) {
187	!	nested_list <- lapply(file_or_dir, function(path) {
188	!	file_class <- suppressWarnings(file(path))
189	!	close(file_class)
190	!	if (class(file_class)[[1]] != "url") {
191	!	isdir <- file.info(path)$isdir
192	!	if (!isdir) {
193	!	structure(path, ancestry = path, sticon = "file")
194		} else {
195	!	files <- list.files(path, full.names = TRUE, include.dirs = TRUE)
196	!	out <- lapply(files, function(x) tree_list(x))
197	!	out <- unlist(out, recursive = FALSE)
198	!	if (length(files) > 0) names(out) <- basename(files)
199	!	out
200		}
201		} else {
202	!	structure(path, ancestry = path, sticon = "file")
203		}
204		})
205
206	!	missing_labels <- if (is.null(names(nested_list))) seq_along(nested_list) else which(names(nested_list) == "")
207	!	names(nested_list)[missing_labels] <- file_or_dir[missing_labels]
208	!	nested_list
209		}
210
211	!	output$tree <- shinyTree::renderTree({
212	!	if (length(input_path) > 0) {
213	!	tree_list(input_path)
214		} else {
215	!	list("Empty Path" = NULL)
216		}
217		})
218
219	!	output$output <- renderUI({
220	!	validate(
221	!	need(
222	!	length(shinyTree::get_selected(input$tree)) > 0,
223	!	"Please select a file."
224		)
225		)
226
227	!	obj <- shinyTree::get_selected(input$tree, format = "names")[[1]]
228	!	repo <- attr(obj, "ancestry")
229	!	repo_collapsed <- if (length(repo) > 1) paste0(repo, collapse = "/") else repo
230	!	is_not_named <- file.exists(file.path(c(repo_collapsed, obj[1])))[1]
231
232	!	if (is_not_named) {
233	!	selected_path <- do.call("file.path", as.list(c(repo, obj[1])))
234		} else {
235	!	if (length(repo) == 0) {
236	!	selected_path <- do.call("file.path", as.list(attr(input$tree[[obj[1]]], "ancestry")))
237		} else {
238	!	selected_path <- do.call("file.path", as.list(attr(input$tree[[repo]][[obj[1]]], "ancestry")))
239		}
240		}
241
242	!	validate(
243	!	need(
244	!	!isTRUE(file.info(selected_path)$isdir) && length(selected_path) > 0,
245	!	"Please select a single file."
246		)
247		)
248	!	display_file(selected_path)
249		})
250
251	!	onStop(function() {
252	!	removeResourcePath(basename(temp_dir))
253	!	unlink(temp_dir)
254		})
255		})
256		}

1		#' `teal` module: Scatterplot matrix
2		#'
3		#' Generates a scatterplot matrix from selected `variables` from datasets.
4		#' Each plot within the matrix represents the relationship between two variables,
5		#' providing the overview of correlations and distributions across selected data.
6		#'
7		#' @note For more examples, please see the vignette "Using scatterplot matrix" via
8		#' `vignette("using-scatterplot-matrix", package = "teal.modules.general")`.
9		#'
10		#' @inheritParams teal::module
11		#' @inheritParams tm_g_scatterplot
12		#' @inheritParams shared_params
13		#'
14		#' @param variables (`data_extract_spec` or `list` of multiple `data_extract_spec`)
15		#' Specifies plotting variables from an incoming dataset with filtering and selecting. In case of
16		#' `data_extract_spec` use `select_spec(..., ordered = TRUE)` if plot elements should be
17		#' rendered according to selection order.
18		#'
19		#' @inherit shared_params return
20		#'
21		#' @section Decorating Module:
22		#'
23		#' This module generates the following objects, which can be modified in place using decorators:
24		#' - `plot` (`trellis` - output of `lattice::splom`)
25		#'
26		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
27		#' The name of this list corresponds to the name of the output to which the decorator is applied.
28		#' See code snippet below:
29		#'
30		#' ```
31		#' tm_g_scatterplotmatrix(
32		#' ..., # arguments for module
33		#' decorators = list(
34		#' plot = teal_transform_module(...) # applied to the `plot` output
35		#' )
36		#' )
37		#' ```
38		#'
39		#' For additional details and examples of decorators, refer to the vignette
40		#' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
41		#'
42		#' @examplesShinylive
43		#' library(teal.modules.general)
44		#' interactive <- function() TRUE
45		#' {{ next_example }}
46		#' @examples
47		#' # general data example
48		#' data <- teal_data()
49		#' data <- within(data, {
50		#' countries <- data.frame(
51		#' id = c("DE", "FR", "IT", "ES", "PT", "GR", "NL", "BE", "LU", "AT"),
52		#' government = factor(
53		#' c(2, 2, 2, 1, 2, 2, 1, 1, 1, 2),
54		#' labels = c("Monarchy", "Republic")
55		#' ),
56		#' language_family = factor(
57		#' c(1, 3, 3, 3, 3, 2, 1, 1, 3, 1),
58		#' labels = c("Germanic", "Hellenic", "Romance")
59		#' ),
60		#' population = c(83, 67, 60, 47, 10, 11, 17, 11, 0.6, 9),
61		#' area = c(357, 551, 301, 505, 92, 132, 41, 30, 2.6, 83),
62		#' gdp = c(3.4, 2.7, 2.1, 1.4, 0.3, 0.2, 0.7, 0.5, 0.1, 0.4),
63		#' debt = c(2.1, 2.3, 2.4, 2.6, 2.3, 2.4, 2.3, 2.4, 2.3, 2.4)
64		#' )
65		#' sales <- data.frame(
66		#' id = 1:50,
67		#' country_id = sample(
68		#' c("DE", "FR", "IT", "ES", "PT", "GR", "NL", "BE", "LU", "AT"),
69		#' size = 50,
70		#' replace = TRUE
71		#' ),
72		#' year = sort(sample(2010:2020, 50, replace = TRUE)),
73		#' venue = sample(c("small", "medium", "large", "online"), 50, replace = TRUE),
74		#' cancelled = sample(c(TRUE, FALSE), 50, replace = TRUE),
75		#' quantity = rnorm(50, 100, 20),
76		#' costs = rnorm(50, 80, 20),
77		#' profit = rnorm(50, 20, 10)
78		#' )
79		#' })
80		#' join_keys(data) <- join_keys(
81		#' join_key("countries", "countries", "id"),
82		#' join_key("sales", "sales", "id"),
83		#' join_key("countries", "sales", c("id" = "country_id"))
84		#' )
85		#'
86		#' app <- init(
87		#' data = data,
88		#' modules = modules(
89		#' tm_g_scatterplotmatrix(
90		#' label = "Scatterplot matrix",
91		#' variables = list(
92		#' data_extract_spec(
93		#' dataname = "countries",
94		#' select = select_spec(
95		#' label = "Select variables:",
96		#' choices = variable_choices(data[["countries"]]),
97		#' selected = c("area", "gdp", "debt"),
98		#' multiple = TRUE,
99		#' ordered = TRUE,
100		#' fixed = FALSE
101		#' )
102		#' ),
103		#' data_extract_spec(
104		#' dataname = "sales",
105		#' filter = filter_spec(
106		#' label = "Select variable:",
107		#' vars = "country_id",
108		#' choices = value_choices(data[["sales"]], "country_id"),
109		#' selected = c("DE", "FR", "IT", "ES", "PT", "GR", "NL", "BE", "LU", "AT"),
110		#' multiple = TRUE
111		#' ),
112		#' select = select_spec(
113		#' label = "Select variables:",
114		#' choices = variable_choices(data[["sales"]], c("quantity", "costs", "profit")),
115		#' selected = c("quantity", "costs", "profit"),
116		#' multiple = TRUE,
117		#' ordered = TRUE,
118		#' fixed = FALSE
119		#' )
120		#' )
121		#' )
122		#' )
123		#' )
124		#' )
125		#' if (interactive()) {
126		#' shinyApp(app$ui, app$server)
127		#' }
128		#'
129		#' @examplesShinylive
130		#' library(teal.modules.general)
131		#' interactive <- function() TRUE
132		#' {{ next_example }}
133		#' @examples
134		#' # CDISC data example
135		#' data <- teal_data()
136		#' data <- within(data, {
137		#' ADSL <- teal.data::rADSL
138		#' ADRS <- teal.data::rADRS
139		#' })
140		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
141		#'
142		#' app <- init(
143		#' data = data,
144		#' modules = modules(
145		#' tm_g_scatterplotmatrix(
146		#' label = "Scatterplot matrix",
147		#' variables = list(
148		#' data_extract_spec(
149		#' dataname = "ADSL",
150		#' select = select_spec(
151		#' label = "Select variables:",
152		#' choices = variable_choices(data[["ADSL"]]),
153		#' selected = c("AGE", "RACE", "SEX"),
154		#' multiple = TRUE,
155		#' ordered = TRUE,
156		#' fixed = FALSE
157		#' )
158		#' ),
159		#' data_extract_spec(
160		#' dataname = "ADRS",
161		#' filter = filter_spec(
162		#' label = "Select endpoints:",
163		#' vars = c("PARAMCD", "AVISIT"),
164		#' choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
165		#' selected = "INVET - END OF INDUCTION",
166		#' multiple = TRUE
167		#' ),
168		#' select = select_spec(
169		#' label = "Select variables:",
170		#' choices = variable_choices(data[["ADRS"]]),
171		#' selected = c("AGE", "AVAL", "ADY"),
172		#' multiple = TRUE,
173		#' ordered = TRUE,
174		#' fixed = FALSE
175		#' )
176		#' )
177		#' )
178		#' )
179		#' )
180		#' )
181		#' if (interactive()) {
182		#' shinyApp(app$ui, app$server)
183		#' }
184		#'
185		#' @export
186		#'
187		tm_g_scatterplotmatrix <- function(label = "Scatterplot Matrix",
188		variables,
189		plot_height = c(600, 200, 2000),
190		plot_width = NULL,
191		pre_output = NULL,
192		post_output = NULL,
193		transformators = list(),
194		decorators = list()) {
195	!	message("Initializing tm_g_scatterplotmatrix")
196
197		# Normalize the parameters
198	!	if (inherits(variables, "data_extract_spec")) variables <- list(variables)
199
200		# Start of assertions
201	!	checkmate::assert_string(label)
202	!	checkmate::assert_list(variables, types = "data_extract_spec")
203
204	!	checkmate::assert_numeric(plot_height, len = 3, any.missing = FALSE, finite = TRUE)
205	!	checkmate::assert_numeric(plot_height[1], lower = plot_height[2], upper = plot_height[3], .var.name = "plot_height")
206	!	checkmate::assert_numeric(plot_width, len = 3, any.missing = FALSE, null.ok = TRUE, finite = TRUE)
207	!	checkmate::assert_numeric(
208	!	plot_width[1],
209	!	lower = plot_width[2], upper = plot_width[3], null.ok = TRUE, .var.name = "plot_width"
210		)
211
212	!	checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
213	!	checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
214
215	!	assert_decorators(decorators, "plot")
216		# End of assertions
217
218		# Make UI args
219	!	args <- as.list(environment())
220
221	!	ans <- module(
222	!	label = label,
223	!	server = srv_g_scatterplotmatrix,
224	!	ui = ui_g_scatterplotmatrix,
225	!	ui_args = args,
226	!	server_args = list(
227	!	variables = variables,
228	!	plot_height = plot_height,
229	!	plot_width = plot_width,
230	!	decorators = decorators
231		),
232	!	transformators = transformators,
233	!	datanames = teal.transform::get_extract_datanames(variables)
234		)
235	!	attr(ans, "teal_bookmarkable") <- TRUE
236	!	ans
237		}
238
239		# UI function for the scatterplot matrix module
240		ui_g_scatterplotmatrix <- function(id, ...) {
241	!	args <- list(...)
242	!	is_single_dataset_value <- teal.transform::is_single_dataset(args$variables)
243	!	ns <- NS(id)
244	!	teal.widgets::standard_layout(
245	!	output = teal.widgets::white_small_well(
246	!	textOutput(ns("message")),
247	!	tags$br(),
248	!	teal.widgets::plot_with_settings_ui(id = ns("myplot"))
249		),
250	!	encoding = tags$div(
251		### Reporter
252	!	teal.reporter::simple_reporter_ui(ns("simple_reporter")),
253		###
254	!	tags$label("Encodings", class = "text-primary"),
255	!	teal.transform::datanames_input(args$variables),
256	!	teal.transform::data_extract_ui(
257	!	id = ns("variables"),
258	!	label = "Variables",
259	!	data_extract_spec = args$variables,
260	!	is_single_dataset = is_single_dataset_value
261		),
262	!	tags$hr(),
263	!	ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(args$decorators, "plot")),
264	!	teal.widgets::panel_group(
265	!	teal.widgets::panel_item(
266	!	title = "Plot settings",
267	!	sliderInput(
268	!	ns("alpha"), "Opacity:",
269	!	min = 0, max = 1,
270	!	step = .05, value = .5, ticks = FALSE
271		),
272	!	sliderInput(
273	!	ns("cex"), "Points size:",
274	!	min = 0.2, max = 3,
275	!	step = .05, value = .65, ticks = FALSE
276		),
277	!	checkboxInput(ns("cor"), "Add Correlation", value = FALSE),
278	!	radioButtons(
279	!	ns("cor_method"), "Select Correlation Method",
280	!	choiceNames = c("Pearson", "Kendall", "Spearman"),
281	!	choiceValues = c("pearson", "kendall", "spearman"),
282	!	inline = TRUE
283		),
284	!	checkboxInput(ns("cor_na_omit"), "Omit Missing Values", value = TRUE)
285		)
286		)
287		),
288	!	forms = tagList(
289	!	teal.widgets::verbatim_popup_ui(ns("rcode"), "Show R code")
290		),
291	!	pre_output = args$pre_output,
292	!	post_output = args$post_output
293		)
294		}
295
296		# Server function for the scatterplot matrix module
297		srv_g_scatterplotmatrix <- function(id,
298		data,
299		reporter,
300		filter_panel_api,
301		variables,
302		plot_height,
303		plot_width,
304		decorators) {
305	!	with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
306	!	with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
307	!	checkmate::assert_class(data, "reactive")
308	!	checkmate::assert_class(isolate(data()), "teal_data")
309	!	moduleServer(id, function(input, output, session) {
310	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
311
312	!	selector_list <- teal.transform::data_extract_multiple_srv(
313	!	data_extract = list(variables = variables),
314	!	datasets = data,
315	!	select_validation_rule = list(
316	!	variables = ~ if (length(.) <= 1) "Please select at least 2 columns."
317		)
318		)
319
320	!	iv_r <- reactive({
321	!	iv <- shinyvalidate::InputValidator$new()
322	!	teal.transform::compose_and_enable_validators(iv, selector_list)
323		})
324
325	!	anl_merged_input <- teal.transform::merge_expression_srv(
326	!	datasets = data,
327	!	selector_list = selector_list
328		)
329
330	!	anl_merged_q <- reactive({
331	!	req(anl_merged_input())
332	!	data() %>%
333	!	teal.code::eval_code(as.expression(anl_merged_input()$expr))
334		})
335
336	!	merged <- list(
337	!	anl_input_r = anl_merged_input,
338	!	anl_q_r = anl_merged_q
339		)
340
341		# plot
342	!	output_q <- reactive({
343	!	teal::validate_inputs(iv_r())
344
345	!	qenv <- merged$anl_q_r()
346	!	ANL <- qenv[["ANL"]]
347
348	!	cols_names <- merged$anl_input_r()$columns_source$variables
349	!	alpha <- input$alpha
350	!	cex <- input$cex
351	!	add_cor <- input$cor
352	!	cor_method <- input$cor_method
353	!	cor_na_omit <- input$cor_na_omit
354
355	!	cor_na_action <- if (isTruthy(cor_na_omit)) {
356	!	"na.omit"
357		} else {
358	!	"na.fail"
359		}
360
361	!	teal::validate_has_data(ANL, 10)
362	!	teal::validate_has_data(ANL[, cols_names, drop = FALSE], 10, complete = TRUE, allow_inf = FALSE)
363
364		# get labels and proper variable names
365	!	varnames <- varname_w_label(cols_names, ANL, wrap_width = 20)
366
367		# check character columns. If any, then those are converted to factors
368	!	check_char <- vapply(ANL[, cols_names], is.character, logical(1))
369	!	if (any(check_char)) {
370	!	qenv <- teal.code::eval_code(
371	!	qenv,
372	!	substitute(
373	!	expr = ANL <- ANL[, cols_names] %>%
374	!	dplyr::mutate_if(is.character, as.factor) %>%
375	!	droplevels(),
376	!	env = list(cols_names = cols_names)
377		)
378		)
379		} else {
380	!	qenv <- teal.code::eval_code(
381	!	qenv,
382	!	substitute(
383	!	expr = ANL <- ANL[, cols_names] %>%
384	!	droplevels(),
385	!	env = list(cols_names = cols_names)
386		)
387		)
388		}
389
390
391		# create plot
392	!	if (add_cor) {
393	!	shinyjs::show("cor_method")
394	!	shinyjs::show("cor_use")
395	!	shinyjs::show("cor_na_omit")
396
397	!	qenv <- teal.code::eval_code(
398	!	qenv,
399	!	substitute(
400	!	expr = {
401	!	plot <- lattice::splom(
402	!	ANL,
403	!	varnames = varnames_value,
404	!	panel = function(x, y, ...) {
405	!	lattice::panel.splom(x = x, y = y, ...)
406	!	cpl <- lattice::current.panel.limits()
407	!	lattice::panel.text(
408	!	mean(cpl$xlim),
409	!	mean(cpl$ylim),
410	!	get_scatterplotmatrix_stats(
411	!	x,
412	!	y,
413	!	.f = stats::cor.test,
414	!	.f_args = list(method = cor_method, na.action = cor_na_action)
415		),
416	!	alpha = 0.6,
417	!	fontsize = 18,
418	!	fontface = "bold"
419		)
420		},
421	!	pch = 16,
422	!	alpha = alpha_value,
423	!	cex = cex_value
424		)
425		},
426	!	env = list(
427	!	varnames_value = varnames,
428	!	cor_method = cor_method,
429	!	cor_na_action = cor_na_action,
430	!	alpha_value = alpha,
431	!	cex_value = cex
432		)
433		)
434		)
435		} else {
436	!	shinyjs::hide("cor_method")
437	!	shinyjs::hide("cor_use")
438	!	shinyjs::hide("cor_na_omit")
439	!	qenv <- teal.code::eval_code(
440	!	qenv,
441	!	substitute(
442	!	expr = {
443	!	plot <- lattice::splom(
444	!	ANL,
445	!	varnames = varnames_value,
446	!	pch = 16,
447	!	alpha = alpha_value,
448	!	cex = cex_value
449		)
450		},
451	!	env = list(varnames_value = varnames, alpha_value = alpha, cex_value = cex)
452		)
453		)
454		}
455	!	qenv
456		})
457
458	!	decorated_output_q <- srv_decorate_teal_data(
459	!	id = "decorator",
460	!	data = output_q,
461	!	decorators = select_decorators(decorators, "plot"),
462	!	expr = print(plot)
463		)
464
465	!	plot_r <- reactive(req(decorated_output_q())[["plot"]])
466
467		# Insert the plot into a plot_with_settings module
468	!	pws <- teal.widgets::plot_with_settings_srv(
469	!	id = "myplot",
470	!	plot_r = plot_r,
471	!	height = plot_height,
472	!	width = plot_width
473		)
474
475		# show a message if conversion to factors took place
476	!	output$message <- renderText({
477	!	req(iv_r()$is_valid())
478	!	req(selector_list()$variables())
479	!	ANL <- merged$anl_q_r()[["ANL"]]
480	!	cols_names <- unique(unname(do.call(c, merged$anl_input_r()$columns_source)))
481	!	check_char <- vapply(ANL[, cols_names], is.character, logical(1))
482	!	if (any(check_char)) {
483	!	is_single <- sum(check_char) == 1
484	!	paste(
485	!	"Character",
486	!	ifelse(is_single, "variable", "variables"),
487	!	paste0("(", paste(cols_names[check_char], collapse = ", "), ")"),
488	!	ifelse(is_single, "was", "were"),
489	!	"converted to",
490	!	ifelse(is_single, "factor.", "factors.")
491		)
492		} else {
493		""
494		}
495		})
496
497		# Render R code.
498	!	source_code_r <- reactive(teal.code::get_code(req(decorated_output_q())))
499
500	!	teal.widgets::verbatim_popup_srv(
501	!	id = "rcode",
502	!	verbatim_content = source_code_r,
503	!	title = "Show R Code for Scatterplotmatrix"
504		)
505
506		### REPORTER
507	!	if (with_reporter) {
508	!	card_fun <- function(comment, label) {
509	!	card <- teal::report_card_template(
510	!	title = "Scatter Plot Matrix",
511	!	label = label,
512	!	with_filter = with_filter,
513	!	filter_panel_api = filter_panel_api
514		)
515	!	card$append_text("Plot", "header3")
516	!	card$append_plot(plot_r(), dim = pws$dim())
517	!	if (!comment == "") {
518	!	card$append_text("Comment", "header3")
519	!	card$append_text(comment)
520		}
521	!	card$append_src(source_code_r())
522	!	card
523		}
524	!	teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
525		}
526		###
527		})
528		}
529
530		#' Get stats for x-y pairs in scatterplot matrix
531		#'
532		#' Uses [stats::cor.test()] per default for all numerical input variables and converts results
533		#' to character vector.
534		#' Could be extended if different stats for different variable types are needed.
535		#' Meant to be called from [lattice::panel.text()].
536		#'
537		#' Presently we need to use a formula input for `stats::cor.test` because
538		#' `na.fail` only gets evaluated when a formula is passed (see below).
539		#' ```
540		#' x = c(1,3,5,7,NA)
541		#' y = c(3,6,7,8,1)
542		#' stats::cor.test(x, y, na.action = "na.fail")
543		#' stats::cor.test(~ x + y, na.action = "na.fail")
544		#' ```
545		#'
546		#' @param x,y (`numeric`) vectors of data values. `x` and `y` must have the same length.
547		#' @param .f (`function`) function that accepts x and y as formula input `~ x + y`.
548		#' Default `stats::cor.test`.
549		#' @param .f_args (`list`) of arguments to be passed to `.f`.
550		#' @param round_stat (`integer(1)`) optional, number of decimal places to use when rounding the estimate.
551		#' @param round_pval (`integer(1)`) optional, number of decimal places to use when rounding the p-value.
552		#'
553		#' @return Character with stats. For [stats::cor.test()] correlation coefficient and p-value.
554		#'
555		#' @examples
556		#' set.seed(1)
557		#' x <- runif(25, 0, 1)
558		#' y <- runif(25, 0, 1)
559		#' x[c(3, 10, 18)] <- NA
560		#'
561		#' get_scatterplotmatrix_stats(x, y, .f = stats::cor.test, .f_args = list(method = "pearson"))
562		#' get_scatterplotmatrix_stats(x, y, .f = stats::cor.test, .f_args = list(
563		#' method = "pearson",
564		#' na.action = na.fail
565		#' ))
566		#'
567		#' @export
568		#'
569		get_scatterplotmatrix_stats <- function(x, y,
570		.f = stats::cor.test,
571		.f_args = list(),
572		round_stat = 2,
573		round_pval = 4) {
574	6x	if (is.numeric(x) && is.numeric(y)) {
575	3x	stat <- tryCatch(do.call(.f, c(list(~ x + y), .f_args)), error = function(e) NA)
576
577	3x	if (anyNA(stat)) {
578	1x	return("NA")
579	2x	} else if (all(c("estimate", "p.value") %in% names(stat))) {
580	2x	return(paste(
581	2x	c(
582	2x	paste0(names(stat$estimate), ":", round(stat$estimate, round_stat)),
583	2x	paste0("P:", round(stat$p.value, round_pval))
584		),
585	2x	collapse = "\n"
586		))
587		} else {
588	!	stop("function not supported")
589		}
590		} else {
591	3x	if ("method" %in% names(.f_args)) {
592	3x	if (.f_args$method == "pearson") {
593	1x	return("cor:-")
594		}
595	2x	if (.f_args$method == "kendall") {
596	1x	return("tau:-")
597		}
598	1x	if (.f_args$method == "spearman") {
599	1x	return("rho:-")
600		}
601		}
602	!	return("-")
603		}
604		}

1		#' Shared parameters documentation
2		#'
3		#' Defines common arguments shared across multiple functions in the package
4		#' to avoid repetition by using `inheritParams`.
5		#'
6		#' @param plot_height (`numeric`) optional, specifies the plot height as a three-element vector of
7		#' `value`, `min`, and `max` intended for use with a slider UI element.
8		#' @param plot_width (`numeric`) optional, specifies the plot width as a three-element vector of
9		#' `value`, `min`, and `max` for a slider encoding the plot width.
10		#' @param rotate_xaxis_labels (`logical`) optional, whether to rotate plot X axis labels. Does not
11		#' rotate by default (`FALSE`).
12		#' @param ggtheme (`character`) optional, `ggplot2` theme to be used by default. Defaults to `"gray"`.
13		#' @param ggplot2_args (`ggplot2_args`) object created by [teal.widgets::ggplot2_args()]
14		#' with settings for the module plot.
15		#' The argument is merged with options variable `teal.ggplot2_args` and default module setup.
16		#'
17		#' For more details see the vignette: `vignette("custom-ggplot2-arguments", package = "teal.widgets")`
18		#' @param basic_table_args (`basic_table_args`) object created by [teal.widgets::basic_table_args()]
19		#' with settings for the module table.
20		#' The argument is merged with options variable `teal.basic_table_args` and default module setup.
21		#'
22		#' For more details see the vignette: `vignette("custom-basic-table-arguments", package = "teal.widgets")`
23		#' @param pre_output (`shiny.tag`) optional, text or UI element to be displayed before the module's output,
24		#' providing context or a title.
25		#' with text placed before the output to put the output into context. For example a title.
26		#' @param post_output (`shiny.tag`) optional, text or UI element to be displayed after the module's output,
27		#' adding context or further instructions. Elements like `shiny::helpText()` are useful.
28		#' @param alpha (`integer(1)` or `integer(3)`) optional, specifies point opacity.
29		#' - When the length of `alpha` is one: the plot points will have a fixed opacity.
30		#' - When the length of `alpha` is three: the plot points opacity are dynamically adjusted based on
31		#' vector of `value`, `min`, and `max`.
32		#' @param size (`integer(1)` or `integer(3)`) optional, specifies point size.
33		#' - When the length of `size` is one: the plot point sizes will have a fixed size.
34		#' - When the length of `size` is three: the plot points size are dynamically adjusted based on
35		#' vector of `value`, `min`, and `max`.
36		#' @param decorators `r lifecycle::badge("experimental")`
37		#' (`list` of `teal_transform_module`, named `list` of `teal_transform_module`) optional,
38		#' decorator for tables or plots included in the module output reported.
39		#' When a named list of `teal_transform_module`, the decorators are applied to the respective output objects.
40		#'
41		#' Otherwise, the decorators are applied to all objects, which is equivalent as using the name `default`.
42		#'
43		#' See section "Decorating Module" below for more details.
44		#'
45		#' @return Object of class `teal_module` to be used in `teal` applications.
46		#'
47		#' @name shared_params
48		#' @keywords internal
49		NULL
50
51		#' Add labels for facets to a `ggplot2` object
52		#'
53		#' Enhances a `ggplot2` plot by adding labels that describe
54		#' the faceting variables along the x and y axes.
55		#'
56		#' @param p (`ggplot2`) object to which facet labels will be added.
57		#' @param xfacet_label (`character`) Label for the facet along the x-axis.
58		#' If `NULL`, no label is added. If a vector, labels are joined with " & ".
59		#' @param yfacet_label (`character`) Label for the facet along the y-axis.
60		#' Similar behavior to `xfacet_label`.
61		#'
62		#' @return Returns `grid` or `grob` object (to be drawn with `grid.draw`)
63		#'
64		#' @examples
65		#' library(ggplot2)
66		#' library(grid)
67		#'
68		#' p <- ggplot(mtcars) +
69		#' aes(x = mpg, y = disp) +
70		#' geom_point() +
71		#' facet_grid(gear ~ cyl)
72		#'
73		#' xfacet_label <- "cylinders"
74		#' yfacet_label <- "gear"
75		#' res <- add_facet_labels(p, xfacet_label, yfacet_label)
76		#' grid.newpage()
77		#' grid.draw(res)
78		#'
79		#' grid.newpage()
80		#' grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label))
81		#' grid.newpage()
82		#' grid.draw(add_facet_labels(p, xfacet_label, yfacet_label = NULL))
83		#' grid.newpage()
84		#' grid.draw(add_facet_labels(p, xfacet_label = NULL, yfacet_label = NULL))
85		#'
86		#' @export
87		#'
88		add_facet_labels <- function(p, xfacet_label = NULL, yfacet_label = NULL) {
89	!	checkmate::assert_class(p, classes = "ggplot")
90	!	checkmate::assert_character(xfacet_label, null.ok = TRUE, min.len = 1)
91	!	checkmate::assert_character(yfacet_label, null.ok = TRUE, min.len = 1)
92	!	if (is.null(xfacet_label) && is.null(yfacet_label)) {
93	!	return(ggplotGrob(p))
94		}
95	!	grid::grid.grabExpr({
96	!	g <- ggplotGrob(p)
97
98		# we are going to replace these, so we make sure they have nothing in them
99	!	checkmate::assert_class(g$grobs[[grep("xlab-t", g$layout$name, fixed = TRUE)]], "zeroGrob")
100	!	checkmate::assert_class(g$grobs[[grep("ylab-r", g$layout$name, fixed = TRUE)]], "zeroGrob")
101
102	!	xaxis_label_grob <- g$grobs[[grep("xlab-b", g$layout$name, fixed = TRUE)]]
103	!	xaxis_label_grob$children[[1]]$label <- paste(xfacet_label, collapse = " & ")
104	!	yaxis_label_grob <- g$grobs[[grep("ylab-l", g$layout$name, fixed = TRUE)]]
105	!	yaxis_label_grob$children[[1]]$label <- paste(yfacet_label, collapse = " & ")
106	!	yaxis_label_grob$children[[1]]$rot <- 270
107
108	!	top_height <- if (is.null(xfacet_label)) 0 else grid::unit(2, "line")
109	!	right_width <- if (is.null(yfacet_label)) 0 else grid::unit(2, "line")
110
111	!	grid::grid.newpage()
112	!	grid::pushViewport(grid::plotViewport(margins = c(0, 0, top_height, right_width), name = "ggplot"))
113	!	grid::grid.draw(g)
114	!	grid::upViewport(1)
115
116		# draw x facet
117	!	if (!is.null(xfacet_label)) {
118	!	grid::pushViewport(grid::viewport(
119	!	x = 0, y = grid::unit(1, "npc") - top_height, width = grid::unit(1, "npc"),
120	!	height = top_height, just = c("left", "bottom"), name = "topxaxis"
121		))
122	!	grid::grid.draw(xaxis_label_grob)
123	!	grid::upViewport(1)
124		}
125
126		# draw y facet
127	!	if (!is.null(yfacet_label)) {
128	!	grid::pushViewport(grid::viewport(
129	!	x = grid::unit(1, "npc") - grid::unit(as.numeric(right_width) / 2, "line"), y = 0, width = right_width,
130	!	height = grid::unit(1, "npc"), just = c("left", "bottom"), name = "rightyaxis"
131		))
132	!	grid::grid.draw(yaxis_label_grob)
133	!	grid::upViewport(1)
134		}
135		})
136		}
137
138		#' Call a function with a character vector for the `...` argument
139		#'
140		#' @param fun (`character`) Name of a function where the `...` argument shall be replaced by values from `str_args`.
141		#' @param str_args (`character`) A character vector that the function shall be executed with
142		#'
143		#' @return
144		#' Value of call to `fun` with arguments specified in `str_args`.
145		#'
146		#' @keywords internal
147		call_fun_dots <- function(fun, str_args) {
148	!	do.call("call", c(list(fun), lapply(str_args, as.name)), quote = TRUE)
149		}
150
151		#' Generate a string for a variable including its label
152		#'
153		#' @param var_names (`character`) Name of variable to extract labels from.
154		#' @param dataset (`dataset`) Name of analysis dataset.
155		#' @param prefix,suffix (`character`) String to paste to the beginning/end of the variable name with label.
156		#' @param wrap_width (`numeric`) Number of characters to wrap original label to. Defaults to 80.
157		#'
158		#' @return (`character`) String with variable name and label.
159		#'
160		#' @keywords internal
161		#'
162		varname_w_label <- function(var_names,
163		dataset,
164		wrap_width = 80,
165		prefix = NULL,
166		suffix = NULL) {
167	!	add_label <- function(var_names) {
168	!	label <- vapply(
169	!	dataset[var_names], function(x) {
170	!	attr_label <- attr(x, "label")
171	!	`if`(is.null(attr_label), "", attr_label)
172		},
173	!	character(1)
174		)
175
176	!	if (length(label) == 1 && !is.na(label) && !identical(label, "")) {
177	!	paste0(prefix, label, " [", var_names, "]", suffix)
178		} else {
179	!	var_names
180		}
181		}
182
183	!	if (length(var_names) < 1) {
184	!	NULL
185	!	} else if (length(var_names) == 1) {
186	!	stringr::str_wrap(add_label(var_names), width = wrap_width)
187	!	} else if (length(var_names) > 1) {
188	!	stringr::str_wrap(vapply(var_names, add_label, character(1)), width = wrap_width)
189		}
190		}
191
192		# see vignette("ggplot2-specs", package="ggplot2")
193		shape_names <- c(
194		"circle", paste("circle", c("open", "filled", "cross", "plus", "small")), "bullet",
195		"square", paste("square", c("open", "filled", "cross", "plus", "triangle")),
196		"diamond", paste("diamond", c("open", "filled", "plus")),
197		"triangle", paste("triangle", c("open", "filled", "square")),
198		paste("triangle down", c("open", "filled")),
199		"plus", "cross", "asterisk"
200		)
201
202		#' Get icons to represent variable types in dataset
203		#'
204		#' @param var_type (`character`) of R internal types (classes).
205		#' @return (`character`) vector of HTML icons corresponding to data type in each column.
206		#' @keywords internal
207		variable_type_icons <- function(var_type) {
208	!	checkmate::assert_character(var_type, any.missing = FALSE)
209
210	!	class_to_icon <- list(
211	!	numeric = "arrow-up-1-9",
212	!	integer = "arrow-up-1-9",
213	!	logical = "pause",
214	!	Date = "calendar",
215	!	POSIXct = "calendar",
216	!	POSIXlt = "calendar",
217	!	factor = "chart-bar",
218	!	character = "keyboard",
219	!	primary_key = "key",
220	!	unknown = "circle-question"
221		)
222	!	class_to_icon <- lapply(class_to_icon, function(icon_name) toString(icon(icon_name, lib = "font-awesome")))
223
224	!	unname(vapply(
225	!	var_type,
226	!	FUN.VALUE = character(1),
227	!	FUN = function(class) {
228	!	if (class == "") {
229	!	class
230	!	} else if (is.null(class_to_icon[[class]])) {
231	!	class_to_icon[["unknown"]]
232		} else {
233	!	class_to_icon[[class]]
234		}
235		}
236		))
237		}
238
239		#' Include `CSS` files from `/inst/css/` package directory to application header
240		#'
241		#' `system.file` should not be used to access files in other packages, it does
242		#' not work with `devtools`. Therefore, we redefine this method in each package
243		#' as needed. Thus, we do not export this method
244		#'
245		#' @param pattern (`character`) optional, regular expression to match the file names to be included.
246		#'
247		#' @return HTML code that includes `CSS` files.
248		#' @keywords internal
249		#'
250		include_css_files <- function(pattern = "*") {
251	!	css_files <- list.files(
252	!	system.file("css", package = "teal.modules.general", mustWork = TRUE),
253	!	pattern = pattern, full.names = TRUE
254		)
255	!	if (length(css_files) == 0) {
256	!	return(NULL)
257		}
258	!	singleton(tags$head(lapply(css_files, includeCSS)))
259		}
260
261		#' JavaScript condition to check if a specific tab is active
262		#'
263		#' @param id (`character(1)`) the id of the tab panel with tabs.
264		#' @param name (`character(1)`) the name of the tab.
265		#' @return JavaScript expression to be used in `shiny::conditionalPanel()` to determine
266		#' if the specified tab is active.
267		#' @keywords internal
268		#'
269		is_tab_active_js <- function(id, name) {
270		# supporting the bs3 and higher version at the same time
271	!	sprintf(
272	!	"$(\"#%1$s > li.active\").text().trim() == '%2$s' \|\| $(\"#%1$s > li a.active\").text().trim() == '%2$s'",
273	!	id, name
274		)
275		}
276
277		#' Assert single selection on `data_extract_spec` object
278		#' Helper to reduce code in assertions
279		#' @noRd
280		#'
281		assert_single_selection <- function(x,
282		.var.name = checkmate::vname(x)) { # nolint: object_name.
283	104x	if (any(vapply(x, function(.x) .x$select$multiple, logical(1)))) {
284	4x	stop("'", .var.name, "' should not allow multiple selection")
285		}
286	100x	invisible(TRUE)
287		}
288
289		#' Wrappers around `srv_transform_teal_data` that allows to decorate the data
290		#' @inheritParams teal::srv_transform_teal_data
291		#' @param expr (`expression` or `reactive`) to evaluate on the output of the decoration.
292		#' When an expression it must be inline code. See [within()]
293		#' Default is `NULL` which won't evaluate any appending code.
294		#' @param expr_is_reactive (`logical(1)`) whether `expr` is a reactive expression
295		#' that skips defusing the argument.
296		#' @details
297		#' `srv_decorate_teal_data` is a wrapper around `srv_transform_teal_data` that
298		#' allows to decorate the data with additional expressions.
299		#' When original `teal_data` object is in error state, it will show that error
300		#' first.
301		#'
302		#' @keywords internal
303		srv_decorate_teal_data <- function(id, data, decorators, expr, expr_is_reactive = FALSE) {
304	!	checkmate::assert_class(data, classes = "reactive")
305	!	checkmate::assert_list(decorators, "teal_transform_module")
306	!	checkmate::assert_flag(expr_is_reactive)
307
308	!	missing_expr <- missing(expr)
309	!	if (!missing_expr && !expr_is_reactive) {
310	!	expr <- dplyr::enexpr(expr) # Using dplyr re-export to avoid adding rlang to Imports
311		}
312
313	!	moduleServer(id, function(input, output, session) {
314	!	decorated_output <- srv_transform_teal_data("inner", data = data, transformators = decorators)
315
316	!	reactive({
317	!	data_out <- try(data(), silent = TRUE)
318	!	if (inherits(data_out, "qenv.error")) {
319	!	data()
320		} else {
321		# ensure original errors are displayed and `eval_code` is never executed with NULL
322	!	req(data(), decorated_output())
323	!	if (missing_expr) {
324	!	decorated_output()
325	!	} else if (expr_is_reactive) {
326	!	teal.code::eval_code(decorated_output(), expr())
327		} else {
328	!	teal.code::eval_code(decorated_output(), expr)
329		}
330		}
331		})
332		})
333		}
334
335		#' @rdname srv_decorate_teal_data
336		#' @details
337		#' `ui_decorate_teal_data` is a wrapper around `ui_transform_teal_data`.
338		#' @keywords internal
339		ui_decorate_teal_data <- function(id, decorators, ...) {
340	!	teal::ui_transform_teal_data(NS(id, "inner"), transformators = decorators, ...)
341		}
342
343		#' Internal function to check if decorators is a valid object
344		#' @noRd
345		check_decorators <- function(x, names = NULL) { # nolint: object_name.
346
347	5x	check_message <- checkmate::check_list(x, names = "named")
348
349	5x	if (!is.null(names)) {
350	5x	if (isTRUE(check_message)) {
351	5x	if (length(names(x)) != length(unique(names(x)))) {
352	!	check_message <- sprintf(
353	!	"The `decorators` must contain unique names from these names: %s.",
354	!	paste(names, collapse = ", ")
355		)
356		}
357		} else {
358	!	check_message <- sprintf(
359	!	"The `decorators` must be a named list from these names: %s.",
360	!	paste(names, collapse = ", ")
361		)
362		}
363		}
364
365	5x	if (!isTRUE(check_message)) {
366	!	return(check_message)
367		}
368
369	5x	valid_elements <- vapply(
370	5x	x,
371	5x	checkmate::test_class,
372	5x	classes = "teal_transform_module",
373	5x	FUN.VALUE = logical(1L)
374		)
375
376	5x	if (all(valid_elements)) {
377	5x	return(TRUE)
378		}
379
380	!	"Make sure that the named list contains 'teal_transform_module' objects created using `teal_transform_module()`."
381		}
382		#' Internal assertion on decorators
383		#' @noRd
384		assert_decorators <- checkmate::makeAssertionFunction(check_decorators)
385
386		#' Subset decorators based on the scope
387		#'
388		#' @param scope (`character`) a character vector of decorator names to include.
389		#' @param decorators (named `list`) of list decorators to subset.
390		#'
391		#' @return Subsetted list with all decorators to include.
392		#' It can be an empty list if none of the scope exists in `decorators` argument.
393		#' @keywords internal
394		select_decorators <- function(decorators, scope) {
395	!	checkmate::assert_character(scope, null.ok = TRUE)
396	!	if (scope %in% names(decorators)) {
397	!	decorators[scope]
398		} else {
399	!	list()
400		}
401		}

1		#' `teal` module: Data table viewer
2		#'
3		#' Module provides a dynamic and interactive way to view `data.frame`s in a `teal` application.
4		#' It uses the `DT` package to display data tables in a paginated, searchable, and sortable format,
5		#' which helps to enhance data exploration and analysis.
6		#'
7		#' The `DT` package has an option `DT.TOJSON_ARGS` to show `Inf` and `NA` in data tables.
8		#' Configure the `DT.TOJSON_ARGS` option via
9		#' `options(DT.TOJSON_ARGS = list(na = "string"))` before running the module.
10		#' Note though that sorting of numeric columns with `NA`/`Inf` will be lexicographic not numerical.
11		#'
12		#' @inheritParams teal::module
13		#' @inheritParams shared_params
14		#' @param variables_selected (`named list`) Character vectors of the variables (i.e. columns)
15		#' which should be initially shown for each dataset.
16		#' Names of list elements should correspond to the names of the datasets available in the app.
17		#' If no entry is specified for a dataset, the first six variables from that
18		#' dataset will initially be shown.
19		#' @param datasets_selected (`character`) `r lifecycle::badge("deprecated")` A vector of datasets which should be
20		#' shown and in what order. Use `datanames` instead.
21		#' @param dt_args (`named list`) Additional arguments to be passed to [DT::datatable()]
22		#' (must not include `data` or `options`).
23		#' @param dt_options (`named list`) The `options` argument to `DT::datatable`. By default
24		#' `list(searching = FALSE, pageLength = 30, lengthMenu = c(5, 15, 30, 100), scrollX = TRUE)`
25		#' @param server_rendering (`logical`) should the data table be rendered server side
26		#' (see `server` argument of [DT::renderDataTable()])
27		#'
28		#' @inherit shared_params return
29		#'
30		#' @examplesShinylive
31		#' library(teal.modules.general)
32		#' interactive <- function() TRUE
33		#' {{ next_example }}
34		#' @examples
35		#' # general data example
36		#' data <- teal_data()
37		#' data <- within(data, {
38		#' require(nestcolor)
39		#' iris <- iris
40		#' })
41		#'
42		#' app <- init(
43		#' data = data,
44		#' modules = modules(
45		#' tm_data_table(
46		#' variables_selected = list(
47		#' iris = c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width", "Species")
48		#' ),
49		#' dt_args = list(caption = "IRIS Table Caption")
50		#' )
51		#' )
52		#' )
53		#' if (interactive()) {
54		#' shinyApp(app$ui, app$server)
55		#' }
56		#'
57		#' @examplesShinylive
58		#' library(teal.modules.general)
59		#' interactive <- function() TRUE
60		#' {{ next_example }}
61		#' @examples
62		#' # CDISC data example
63		#' data <- teal_data()
64		#' data <- within(data, {
65		#' require(nestcolor)
66		#' ADSL <- teal.data::rADSL
67		#' })
68		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
69		#'
70		#' app <- init(
71		#' data = data,
72		#' modules = modules(
73		#' tm_data_table(
74		#' variables_selected = list(ADSL = c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "SEX")),
75		#' dt_args = list(caption = "ADSL Table Caption")
76		#' )
77		#' )
78		#' )
79		#' if (interactive()) {
80		#' shinyApp(app$ui, app$server)
81		#' }
82		#'
83		#' @export
84		#'
85		tm_data_table <- function(label = "Data Table",
86		variables_selected = list(),
87		datasets_selected = deprecated(),
88		datanames = if (missing(datasets_selected)) "all" else datasets_selected,
89		dt_args = list(),
90		dt_options = list(
91		searching = FALSE,
92		pageLength = 30,
93		lengthMenu = c(5, 15, 30, 100),
94		scrollX = TRUE
95		),
96		server_rendering = FALSE,
97		pre_output = NULL,
98		post_output = NULL,
99		transformators = list()) {
100	!	message("Initializing tm_data_table")
101
102		# Start of assertions
103	!	checkmate::assert_string(label)
104
105	!	checkmate::assert_list(variables_selected, min.len = 0, types = "character", names = "named")
106	!	if (length(variables_selected) > 0) {
107	!	lapply(seq_along(variables_selected), function(i) {
108	!	checkmate::assert_character(variables_selected[[i]], min.chars = 1, min.len = 1)
109	!	if (!is.null(names(variables_selected[[i]]))) {
110	!	checkmate::assert_names(names(variables_selected[[i]]))
111		}
112		})
113		}
114	!	if (!missing(datasets_selected)) {
115	!	lifecycle::deprecate_soft(
116	!	when = "0.4.0",
117	!	what = "tm_data_table(datasets_selected)",
118	!	with = "tm_data_table(datanames)",
119	!	details = 'Use tm_data_table(datanames = "all") to keep the previous behavior and avoid this warning.',
120		)
121		}
122	!	checkmate::assert_character(datanames, min.len = 0, min.chars = 1, null.ok = TRUE)
123	!	checkmate::assert(
124	!	checkmate::check_list(dt_args, len = 0),
125	!	checkmate::check_subset(names(dt_args), choices = names(formals(DT::datatable)))
126		)
127	!	checkmate::assert_list(dt_options, names = "named")
128	!	checkmate::assert_flag(server_rendering)
129	!	checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
130	!	checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
131
132		# End of assertions
133
134	!	ans <- module(
135	!	label,
136	!	server = srv_page_data_table,
137	!	ui = ui_page_data_table,
138	!	datanames = datanames,
139	!	server_args = list(
140	!	datanames = if (is.null(datanames)) "all" else datanames,
141	!	variables_selected = variables_selected,
142	!	dt_args = dt_args,
143	!	dt_options = dt_options,
144	!	server_rendering = server_rendering
145		),
146	!	ui_args = list(
147	!	pre_output = pre_output,
148	!	post_output = post_output
149		),
150	!	transformators = transformators
151		)
152	!	attr(ans, "teal_bookmarkable") <- TRUE
153	!	ans
154		}
155
156		# UI page module
157		ui_page_data_table <- function(id, pre_output = NULL, post_output = NULL) {
158	!	ns <- NS(id)
159
160	!	tagList(
161	!	include_css_files("custom"),
162	!	teal.widgets::standard_layout(
163	!	output = teal.widgets::white_small_well(
164	!	fluidRow(
165	!	column(
166	!	width = 12,
167	!	checkboxInput(
168	!	ns("if_distinct"),
169	!	"Show only distinct rows:",
170	!	value = FALSE
171		)
172		)
173		),
174	!	fluidRow(
175	!	class = "mb-8",
176	!	column(
177	!	width = 12,
178	!	uiOutput(ns("dataset_table"))
179		)
180		)
181		),
182	!	pre_output = pre_output,
183	!	post_output = post_output
184		)
185		)
186		}
187
188		# Server page module
189		srv_page_data_table <- function(id,
190		data,
191		datanames,
192		variables_selected,
193		dt_args,
194		dt_options,
195		server_rendering) {
196	!	checkmate::assert_class(data, "reactive")
197	!	checkmate::assert_class(isolate(data()), "teal_data")
198	!	moduleServer(id, function(input, output, session) {
199	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
200
201	!	if_filtered <- reactive(as.logical(input$if_filtered))
202	!	if_distinct <- reactive(as.logical(input$if_distinct))
203
204	!	datanames <- Filter(function(name) {
205	!	is.data.frame(isolate(data())[[name]])
206	!	}, if (identical(datanames, "all")) names(isolate(data())) else datanames)
207
208
209	!	output$dataset_table <- renderUI({
210	!	do.call(
211	!	tabsetPanel,
212	!	c(
213	!	list(id = session$ns("dataname_tab")),
214	!	lapply(
215	!	datanames,
216	!	function(x) {
217	!	dataset <- isolate(data()[[x]])
218	!	choices <- names(dataset)
219	!	labels <- vapply(
220	!	dataset,
221	!	function(x) ifelse(is.null(attr(x, "label")), "", attr(x, "label")),
222	!	character(1)
223		)
224	!	names(choices) <- ifelse(
225	!	is.na(labels) \| labels == "",
226	!	choices,
227	!	paste(choices, labels, sep = ": ")
228		)
229	!	variables_selected <- if (!is.null(variables_selected[[x]])) {
230	!	variables_selected[[x]]
231		} else {
232	!	utils::head(choices)
233		}
234	!	tabPanel(
235	!	title = x,
236	!	column(
237	!	width = 12,
238	!	div(
239	!	class = "mt-4",
240	!	ui_data_table(
241	!	id = session$ns(x),
242	!	choices = choices,
243	!	selected = variables_selected
244		)
245		)
246		)
247		)
248		}
249		)
250		)
251		)
252		})
253
254	!	lapply(
255	!	datanames,
256	!	function(x) {
257	!	srv_data_table(
258	!	id = x,
259	!	data = data,
260	!	dataname = x,
261	!	if_filtered = if_filtered,
262	!	if_distinct = if_distinct,
263	!	dt_args = dt_args,
264	!	dt_options = dt_options,
265	!	server_rendering = server_rendering
266		)
267		}
268		)
269		})
270		}
271
272		# UI function for the data_table module
273		ui_data_table <- function(id, choices, selected) {
274	!	ns <- NS(id)
275
276	!	if (!is.null(selected)) {
277	!	all_choices <- choices
278	!	choices <- c(selected, setdiff(choices, selected))
279	!	names(choices) <- names(all_choices)[match(choices, all_choices)]
280		}
281
282	!	tagList(
283	!	teal.widgets::get_dt_rows(ns("data_table"), ns("dt_rows")),
284	!	fluidRow(
285	!	teal.widgets::optionalSelectInput(
286	!	ns("variables"),
287	!	"Select variables:",
288	!	choices = choices,
289	!	selected = selected,
290	!	multiple = TRUE,
291	!	width = "100%"
292		)
293		),
294	!	fluidRow(
295	!	DT::dataTableOutput(ns("data_table"), width = "100%")
296		)
297		)
298		}
299
300		# Server function for the data_table module
301		srv_data_table <- function(id,
302		data,
303		dataname,
304		if_filtered,
305		if_distinct,
306		dt_args,
307		dt_options,
308		server_rendering) {
309	!	moduleServer(id, function(input, output, session) {
310	!	iv <- shinyvalidate::InputValidator$new()
311	!	iv$add_rule("variables", shinyvalidate::sv_required("Please select valid variable names"))
312	!	iv$add_rule("variables", shinyvalidate::sv_in_set(
313	!	set = names(isolate(data())[[dataname]]), message_fmt = "Not all selected variables exist in the data"
314		))
315	!	iv$enable()
316
317	!	data_table_data <- reactive({
318	!	df <- data()[[dataname]]
319
320	!	teal::validate_has_data(df, min_nrow = 1L, msg = paste("data", dataname, "is empty"))
321
322	!	teal.code::eval_code(
323	!	data(),
324	!	substitute(
325	!	expr = {
326	!	variables <- vars
327	!	dataframe_selected <- if (if_distinct) {
328	!	dplyr::count(dataname, dplyr::across(dplyr::all_of(variables)))
329		} else {
330	!	dataname[variables]
331		}
332	!	dt_args <- args
333	!	dt_args$options <- dt_options
334	!	if (!is.null(dt_rows)) {
335	!	dt_args$options$pageLength <- dt_rows
336		}
337	!	dt_args$data <- dataframe_selected
338	!	table <- do.call(DT::datatable, dt_args)
339		},
340	!	env = list(
341	!	dataname = as.name(dataname),
342	!	if_distinct = if_distinct(),
343	!	vars = input$variables,
344	!	args = dt_args,
345	!	dt_options = dt_options,
346	!	dt_rows = input$dt_rows
347		)
348		)
349		)
350		})
351
352	!	output$data_table <- DT::renderDataTable(server = server_rendering, {
353	!	teal::validate_inputs(iv)
354	!	req(data_table_data())[["table"]]
355		})
356		})
357		}

1		#' `teal` module: Cross-table
2		#'
3		#' Generates a simple cross-table of two variables from a dataset with custom
4		#' options for showing percentages and sub-totals.
5		#'
6		#' @inheritParams teal::module
7		#' @inheritParams shared_params
8		#' @param x (`data_extract_spec` or `list` of multiple `data_extract_spec`)
9		#' Object with all available choices with pre-selected option for variable X - row values.
10		#' In case of `data_extract_spec` use `select_spec(..., ordered = TRUE)` if table elements should be
11		#' rendered according to selection order.
12		#' @param y (`data_extract_spec` or `list` of multiple `data_extract_spec`)
13		#' Object with all available choices with pre-selected option for variable Y - column values.
14		#'
15		#' `data_extract_spec` must not allow multiple selection in this case.
16		#' @param show_percentage (`logical(1)`)
17		#' Indicates whether to show percentages (relevant only when `x` is a `factor`).
18		#' Defaults to `TRUE`.
19		#' @param show_total (`logical(1)`)
20		#' Indicates whether to show total column.
21		#' Defaults to `TRUE`.
22		#'
23		#' @note For more examples, please see the vignette "Using cross table" via
24		#' `vignette("using-cross-table", package = "teal.modules.general")`.
25		#'
26		#' @inherit shared_params return
27		#'
28		#' @section Decorating Module:
29		#'
30		#' This module generates the following objects, which can be modified in place using decorators:
31		#' - `table` (`ElementaryTable` - output of `rtables::build_table`)
32		#'
33		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
34		#' The name of this list corresponds to the name of the output to which the decorator is applied.
35		#' See code snippet below:
36		#'
37		#' ```
38		#' tm_t_crosstable(
39		#' ..., # arguments for module
40		#' decorators = list(
41		#' table = teal_transform_module(...) # applied to the `table` output
42		#' )
43		#' )
44		#' ```
45		#' For additional details and examples of decorators, refer to the vignette
46		#' `vignette("decorate-modules-output", package = "teal")` or the [`teal::teal_transform_module()`] documentation.
47		#'
48		#' @examplesShinylive
49		#' library(teal.modules.general)
50		#' interactive <- function() TRUE
51		#' {{ next_example }}
52		#' @examples
53		#' # general data example
54		#' data <- teal_data()
55		#' data <- within(data, {
56		#' mtcars <- mtcars
57		#' for (v in c("cyl", "vs", "am", "gear")) {
58		#' mtcars[[v]] <- as.factor(mtcars[[v]])
59		#' }
60		#' mtcars[["primary_key"]] <- seq_len(nrow(mtcars))
61		#' })
62		#' join_keys(data) <- join_keys(join_key("mtcars", "mtcars", "primary_key"))
63		#'
64		#' app <- init(
65		#' data = data,
66		#' modules = modules(
67		#' tm_t_crosstable(
68		#' label = "Cross Table",
69		#' x = data_extract_spec(
70		#' dataname = "mtcars",
71		#' select = select_spec(
72		#' label = "Select variable:",
73		#' choices = variable_choices(data[["mtcars"]], c("cyl", "vs", "am", "gear")),
74		#' selected = c("cyl", "gear"),
75		#' multiple = TRUE,
76		#' ordered = TRUE,
77		#' fixed = FALSE
78		#' )
79		#' ),
80		#' y = data_extract_spec(
81		#' dataname = "mtcars",
82		#' select = select_spec(
83		#' label = "Select variable:",
84		#' choices = variable_choices(data[["mtcars"]], c("cyl", "vs", "am", "gear")),
85		#' selected = "vs",
86		#' multiple = FALSE,
87		#' fixed = FALSE
88		#' )
89		#' )
90		#' )
91		#' )
92		#' )
93		#' if (interactive()) {
94		#' shinyApp(app$ui, app$server)
95		#' }
96		#'
97		#' @examplesShinylive
98		#' library(teal.modules.general)
99		#' interactive <- function() TRUE
100		#' {{ next_example }}
101		#' @examples
102		#' # CDISC data example
103		#' data <- teal_data()
104		#' data <- within(data, {
105		#' ADSL <- teal.data::rADSL
106		#' })
107		#' join_keys(data) <- default_cdisc_join_keys[names(data)]
108		#'
109		#' app <- init(
110		#' data = data,
111		#' modules = modules(
112		#' tm_t_crosstable(
113		#' label = "Cross Table",
114		#' x = data_extract_spec(
115		#' dataname = "ADSL",
116		#' select = select_spec(
117		#' label = "Select variable:",
118		#' choices = variable_choices(data[["ADSL"]], subset = function(data) {
119		#' idx <- !vapply(data, inherits, logical(1), c("Date", "POSIXct", "POSIXlt"))
120		#' return(names(data)[idx])
121		#' }),
122		#' selected = "COUNTRY",
123		#' multiple = TRUE,
124		#' ordered = TRUE,
125		#' fixed = FALSE
126		#' )
127		#' ),
128		#' y = data_extract_spec(
129		#' dataname = "ADSL",
130		#' select = select_spec(
131		#' label = "Select variable:",
132		#' choices = variable_choices(data[["ADSL"]], subset = function(data) {
133		#' idx <- vapply(data, is.factor, logical(1))
134		#' return(names(data)[idx])
135		#' }),
136		#' selected = "SEX",
137		#' multiple = FALSE,
138		#' fixed = FALSE
139		#' )
140		#' )
141		#' )
142		#' )
143		#' )
144		#' if (interactive()) {
145		#' shinyApp(app$ui, app$server)
146		#' }
147		#'
148		#' @export
149		#'
150		tm_t_crosstable <- function(label = "Cross Table",
151		x,
152		y,
153		show_percentage = TRUE,
154		show_total = TRUE,
155		pre_output = NULL,
156		post_output = NULL,
157		basic_table_args = teal.widgets::basic_table_args(),
158		transformators = list(),
159		decorators = list()) {
160	!	message("Initializing tm_t_crosstable")
161
162		# Normalize the parameters
163	!	if (inherits(x, "data_extract_spec")) x <- list(x)
164	!	if (inherits(y, "data_extract_spec")) y <- list(y)
165
166		# Start of assertions
167	!	checkmate::assert_string(label)
168	!	checkmate::assert_list(x, types = "data_extract_spec")
169
170	!	checkmate::assert_list(y, types = "data_extract_spec")
171	!	assert_single_selection(y)
172
173	!	checkmate::assert_flag(show_percentage)
174	!	checkmate::assert_flag(show_total)
175	!	checkmate::assert_multi_class(pre_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
176	!	checkmate::assert_multi_class(post_output, c("shiny.tag", "shiny.tag.list", "html"), null.ok = TRUE)
177	!	checkmate::assert_class(basic_table_args, classes = "basic_table_args")
178
179	!	assert_decorators(decorators, "table")
180		# End of assertions
181
182		# Make UI args
183	!	ui_args <- as.list(environment())
184
185	!	server_args <- list(
186	!	label = label,
187	!	x = x,
188	!	y = y,
189	!	basic_table_args = basic_table_args,
190	!	decorators = decorators
191		)
192
193	!	ans <- module(
194	!	label = label,
195	!	server = srv_t_crosstable,
196	!	ui = ui_t_crosstable,
197	!	ui_args = ui_args,
198	!	server_args = server_args,
199	!	transformators = transformators,
200	!	datanames = teal.transform::get_extract_datanames(list(x = x, y = y))
201		)
202	!	attr(ans, "teal_bookmarkable") <- TRUE
203	!	ans
204		}
205
206		# UI function for the cross-table module
207		ui_t_crosstable <- function(id, x, y, show_percentage, show_total, pre_output, post_output, ...) {
208	!	args <- list(...)
209	!	ns <- NS(id)
210	!	is_single_dataset <- teal.transform::is_single_dataset(x, y)
211
212	!	join_default_options <- c(
213	!	"Full Join" = "dplyr::full_join",
214	!	"Inner Join" = "dplyr::inner_join",
215	!	"Left Join" = "dplyr::left_join",
216	!	"Right Join" = "dplyr::right_join"
217		)
218
219	!	teal.widgets::standard_layout(
220	!	output = teal.widgets::white_small_well(
221	!	textOutput(ns("title")),
222	!	teal.widgets::table_with_settings_ui(ns("table"))
223		),
224	!	encoding = tags$div(
225		### Reporter
226	!	teal.reporter::simple_reporter_ui(ns("simple_reporter")),
227		###
228	!	tags$label("Encodings", class = "text-primary"),
229	!	teal.transform::datanames_input(list(x, y)),
230	!	teal.transform::data_extract_ui(ns("x"), label = "Row values", x, is_single_dataset = is_single_dataset),
231	!	teal.transform::data_extract_ui(ns("y"), label = "Column values", y, is_single_dataset = is_single_dataset),
232	!	teal.widgets::optionalSelectInput(
233	!	ns("join_fun"),
234	!	label = "Row to Column type of join",
235	!	choices = join_default_options,
236	!	selected = join_default_options[1],
237	!	multiple = FALSE
238		),
239	!	tags$hr(),
240	!	teal.widgets::panel_group(
241	!	teal.widgets::panel_item(
242	!	title = "Table settings",
243	!	checkboxInput(ns("show_percentage"), "Show column percentage", value = show_percentage),
244	!	checkboxInput(ns("show_total"), "Show total column", value = show_total)
245		)
246		),
247	!	ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(args$decorators, "table"))
248		),
249	!	forms = tagList(
250	!	teal.widgets::verbatim_popup_ui(ns("rcode"), "Show R code")
251		),
252	!	pre_output = pre_output,
253	!	post_output = post_output
254		)
255		}
256
257		# Server function for the cross-table module
258		srv_t_crosstable <- function(id, data, reporter, filter_panel_api, label, x, y, basic_table_args, decorators) {
259	!	with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
260	!	with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
261	!	checkmate::assert_class(data, "reactive")
262	!	checkmate::assert_class(isolate(data()), "teal_data")
263	!	moduleServer(id, function(input, output, session) {
264	!	teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.general")
265
266	!	selector_list <- teal.transform::data_extract_multiple_srv(
267	!	data_extract = list(x = x, y = y),
268	!	datasets = data,
269	!	select_validation_rule = list(
270	!	x = shinyvalidate::sv_required("Please define column for row variable."),
271	!	y = shinyvalidate::sv_required("Please define column for column variable.")
272		)
273		)
274
275	!	iv_r <- reactive({
276	!	iv <- shinyvalidate::InputValidator$new()
277	!	iv$add_rule("join_fun", function(value) {
278	!	if (!identical(selector_list()$x()$dataname, selector_list()$y()$dataname)) {
279	!	if (!shinyvalidate::input_provided(value)) {
280	!	"Please select a joining function."
281		}
282		}
283		})
284	!	teal.transform::compose_and_enable_validators(iv, selector_list)
285		})
286
287	!	observeEvent(
288	!	eventExpr = {
289	!	req(!is.null(selector_list()$x()) && !is.null(selector_list()$y()))
290	!	list(selector_list()$x(), selector_list()$y())
291		},
292	!	handlerExpr = {
293	!	if (identical(selector_list()$x()$dataname, selector_list()$y()$dataname)) {
294	!	shinyjs::hide("join_fun")
295		} else {
296	!	shinyjs::show("join_fun")
297		}
298		}
299		)
300
301	!	merge_function <- reactive({
302	!	if (is.null(input$join_fun)) {
303	!	"dplyr::full_join"
304		} else {
305	!	input$join_fun
306		}
307		})
308
309	!	anl_merged_input <- teal.transform::merge_expression_srv(
310	!	datasets = data,
311	!	selector_list = selector_list,
312	!	merge_function = merge_function
313		)
314
315	!	anl_merged_q <- reactive({
316	!	req(anl_merged_input())
317	!	data() %>%
318	!	teal.code::eval_code(as.expression(anl_merged_input()$expr))
319		})
320
321	!	merged <- list(
322	!	anl_input_r = anl_merged_input,
323	!	anl_q_r = anl_merged_q
324		)
325
326	!	output_q <- reactive({
327	!	teal::validate_inputs(iv_r())
328	!	ANL <- merged$anl_q_r()[["ANL"]]
329
330		# As this is a summary
331	!	x_name <- as.vector(merged$anl_input_r()$columns_source$x)
332	!	y_name <- as.vector(merged$anl_input_r()$columns_source$y)
333
334	!	teal::validate_has_data(ANL, 3)
335	!	teal::validate_has_data(ANL[, c(x_name, y_name)], 3, complete = TRUE, allow_inf = FALSE)
336
337	!	is_allowed_class <- function(x) is.numeric(x) \|\| is.factor(x) \|\| is.character(x) \|\| is.logical(x)
338	!	validate(need(
339	!	all(vapply(ANL[x_name], is_allowed_class, logical(1))),
340	!	"Selected row variable has an unsupported data type."
341		))
342	!	validate(need(
343	!	is_allowed_class(ANL[[y_name]]),
344	!	"Selected column variable has an unsupported data type."
345		))
346
347	!	show_percentage <- input$show_percentage
348	!	show_total <- input$show_total
349
350	!	plot_title <- paste(
351	!	"Cross-Table of",
352	!	paste0(varname_w_label(x_name, ANL), collapse = ", "),
353	!	"(rows)", "vs.",
354	!	varname_w_label(y_name, ANL),
355	!	"(columns)"
356		)
357
358	!	labels_vec <- vapply(
359	!	x_name,
360	!	varname_w_label,
361	!	character(1),
362	!	ANL
363		)
364
365	!	teal.code::eval_code(
366	!	merged$anl_q_r(),
367	!	substitute(
368	!	expr = {
369	!	title <- plot_title
370		},
371	!	env = list(plot_title = plot_title)
372		)
373		) %>%
374	!	teal.code::eval_code(
375	!	substitute(
376	!	expr = {
377	!	table <- basic_tables %>%
378	!	split_call %>% # styler: off
379	!	rtables::add_colcounts() %>%
380	!	tern::analyze_vars(
381	!	vars = x_name,
382	!	var_labels = labels_vec,
383	!	na.rm = FALSE,
384	!	denom = "N_col",
385	!	.stats = c("mean_sd", "median", "range", count_value)
386		)
387		},
388	!	env = list(
389	!	basic_tables = teal.widgets::parse_basic_table_args(
390	!	basic_table_args = teal.widgets::resolve_basic_table_args(basic_table_args)
391		),
392	!	split_call = if (show_total) {
393	!	substitute(
394	!	expr = rtables::split_cols_by(
395	!	y_name,
396	!	split_fun = rtables::add_overall_level(label = "Total", first = FALSE)
397		),
398	!	env = list(y_name = y_name)
399		)
400		} else {
401	!	substitute(rtables::split_cols_by(y_name), env = list(y_name = y_name))
402		},
403	!	x_name = x_name,
404	!	labels_vec = labels_vec,
405	!	count_value = ifelse(show_percentage, "count_fraction", "count")
406		)
407		)
408		) %>%
409	!	teal.code::eval_code(
410	!	substitute(
411	!	expr = {
412	!	ANL <- tern::df_explicit_na(ANL)
413	!	table <- rtables::build_table(lyt = table, df = ANL[order(ANL[[y_name]]), ])
414		},
415	!	env = list(y_name = y_name)
416		)
417		)
418		})
419
420	!	decorated_output_q <- srv_decorate_teal_data(
421	!	id = "decorator",
422	!	data = output_q,
423	!	decorators = select_decorators(decorators, "table"),
424	!	expr = table
425		)
426
427	!	output$title <- renderText(req(decorated_output_q())[["title"]])
428
429	!	table_r <- reactive({
430	!	req(iv_r()$is_valid())
431	!	req(decorated_output_q())[["table"]]
432		})
433
434	!	teal.widgets::table_with_settings_srv(
435	!	id = "table",
436	!	table_r = table_r
437		)
438
439		# Render R code.
440	!	source_code_r <- reactive(teal.code::get_code(req(decorated_output_q())))
441
442	!	teal.widgets::verbatim_popup_srv(
443	!	id = "rcode",
444	!	verbatim_content = source_code_r,
445	!	title = "Show R Code for Cross-Table"
446		)
447
448		### REPORTER
449	!	if (with_reporter) {
450	!	card_fun <- function(comment, label) {
451	!	card <- teal::report_card_template(
452	!	title = "Cross Table",
453	!	label = label,
454	!	with_filter = with_filter,
455	!	filter_panel_api = filter_panel_api
456		)
457	!	card$append_text("Table", "header3")
458	!	card$append_table(table_r())
459	!	if (!comment == "") {
460	!	card$append_text("Comment", "header3")
461	!	card$append_text(comment)
462		}
463	!	card$append_src(source_code_r())
464	!	card
465		}
466	!	teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
467		}
468		###
469		})
470		}

1		#' `teal` module: Outliers analysis
2		#'
3		#' Module to analyze and identify outliers using different methods
4		#' such as IQR, Z-score, and Percentiles, and offers visualizations including
5		#' box plots, density plots, and cumulative distribution plots to help interpret the outliers.
6		#'
7		#' @inheritParams teal::module
8		#' @inheritParams shared_params
9		#'
10		#' @param outlier_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
11		#' Specifies variable(s) to be analyzed for outliers.
12		#' @param categorical_var (`data_extract_spec` or `list` of multiple `data_extract_spec`) optional,
13		#' specifies the categorical variable(s) to split the selected outlier variables on.
14		#' @param ggplot2_args `r roxygen_ggplot2_args_param("Boxplot", "Density Plot", "Cumulative Distribution Plot")`
15		#'
16		#' @inherit shared_params return
17		#'
18		#' @section Decorating Module:
19		#'
20		#' This module generates the following objects, which can be modified in place using decorators:
21		#' - `box_plot` (`ggplot2`)
22		#' - `density_plot` (`ggplot2`)
23		#' - `cumulative_plot` (`ggplot2`)
24		#' - `table` (`listing_df` created with [rlistings::as_listing()])
25		#'
26		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
27		#' The name of this list corresponds to the name of the output to which the decorator is applied.
28		#' See code snippet below:
29		#'
30		#' ```
31		#' tm_outliers(
32		#' ..., # arguments for module
33		#' decorators = list(
34		#' box_plot = teal_transform_module(...), # applied only to `box_plot` output
35		#' density_plot = teal_transform_module(...), # applied only to `density_plot` output
36		#' cumulative_plot = teal_transform_module(...), # applied only to `cumulative_plot` output
37		#' table = teal_transform_module(...) # applied only to `table` output
38		#' )
39		#' )
40		#' ```

1		#' `teal` module: Variable browser
2		#'
3		#' Module provides provides a detailed summary and visualization of variable distributions
4		#' for `data.frame` objects, with interactive features to customize analysis.
5		#'
6		#' Numeric columns with fewer than 30 distinct values can be treated as either discrete
7		#' or continuous with a checkbox allowing users to switch how they are treated(if < 6 unique values
8		#' then the default is discrete, otherwise it is continuous).
9		#'
10		#' @inheritParams teal::module
11		#' @inheritParams shared_params
12		#' @param parent_dataname (`character(1)`) string specifying a parent dataset.
13		#' If it exists in `datanames` then an extra checkbox will be shown to
14		#' allow users to not show variables in other datasets which exist in this `dataname`.
15		#' This is typically used to remove `ADSL` columns in `CDISC` data.
16		#' In non `CDISC` data this can be ignored. Defaults to `"ADSL"`.
17		#' @param datasets_selected (`character`) `r lifecycle::badge("deprecated")` vector of datasets to show, please
18		#' use the `datanames` argument.
19		#'
20		#' @inherit shared_params return
21		#'
22		#' @examplesShinylive
23		#' library(teal.modules.general)
24		#' interactive <- function() TRUE
25		#' {{ next_example }}
26		# nolint start: line_length_linter.
27		#' @examples
28		# nolint end: line_length_linter.
29		#' # general data example
30		#' data <- teal_data()
31		#' data <- within(data, {
32		#' iris <- iris
33		#' mtcars <- mtcars
34		#' women <- women
35		#' faithful <- faithful
36		#' CO2 <- CO2
37		#' })
38		#'
39		#' app <- init(
40		#' data = data,

1		#' `teal` module: Missing data analysis
2		#'
3		#' This module analyzes missing data in `data.frame`s to help users explore missing observations and
4		#' gain insights into the completeness of their data.
5		#' It is useful for clinical data analysis within the context of `CDISC` standards and
6		#' adaptable for general data analysis purposes.
7		#'
8		#' @inheritParams teal::module
9		#' @inheritParams shared_params
10		#' @param parent_dataname (`character(1)`) Specifies the parent dataset name. Default is `ADSL` for `CDISC` data.
11		#' If provided and exists, enables additional analysis "by subject". For non-`CDISC` data, this parameter can be
12		#' ignored.
13		# nolint start: line_length.
14		#' @param ggtheme (`character`) optional, specifies the default `ggplot2` theme for plots. Defaults to `classic`.
15		#' @param ggplot2_args `r roxygen_ggplot2_args_param("Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject")`
16		# nolint end: line_length.
17		#'
18		#' @inherit shared_params return
19		#'
20		#' @section Decorating Module:
21		#'
22		#' This module generates the following objects, which can be modified in place using decorators:
23		#' - `summary_plot` (`grob` created with [ggplot2::ggplotGrob()])
24		#' - `combination_plot` (`grob` created with [ggplot2::ggplotGrob()])
25		#' - `by_subject_plot` (`ggplot2`)
26		#' - `table` (`listing_df` created with [rlistings::as_listing()])
27		#'
28		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
29		#' The name of this list corresponds to the name of the output to which the decorator is applied.
30		#' See code snippet below:
31		#'
32		#' ```
33		#' tm_missing_data(
34		#' ..., # arguments for module
35		#' decorators = list(
36		#' summary_plot = teal_transform_module(...), # applied only to `summary_plot` output
37		#' combination_plot = teal_transform_module(...), # applied only to `combination_plot` output
38		#' by_subject_plot = teal_transform_module(...), # applied only to `by_subject_plot` output
39		#' table = teal_transform_module(...) # applied only to `table` output
40		#' )

1		#' `teal` module: Distribution analysis
2		#'
3		#' Module is designed to explore the distribution of a single variable within a given dataset.
4		#' It offers several tools, such as histograms, Q-Q plots, and various statistical tests to
5		#' visually and statistically analyze the variable's distribution.
6		#'
7		#' @inheritParams teal::module
8		#' @inheritParams teal.widgets::standard_layout
9		#' @inheritParams shared_params
10		#'
11		#' @param dist_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
12		#' Variable(s) for which the distribution will be analyzed.
13		#' @param strata_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
14		#' Categorical variable used to split the distribution analysis.
15		#' @param group_var (`data_extract_spec` or `list` of multiple `data_extract_spec`)
16		#' Variable used for faceting plot into multiple panels.
17		#' @param freq (`logical`) optional, whether to display frequency (`TRUE`) or density (`FALSE`).
18		#' Defaults to density (`FALSE`).
19		#' @param bins (`integer(1)` or `integer(3)`) optional, specifies the number of bins for the histogram.
20		#' - When the length of `bins` is one: The histogram bins will have a fixed size based on the `bins` provided.
21		#' - When the length of `bins` is three: The histogram bins are dynamically adjusted based on vector of `value`, `min`,
22		#' and `max`.
23		#' Defaults to `c(30L, 1L, 100L)`.
24		#'
25		#' @param ggplot2_args `r roxygen_ggplot2_args_param("Histogram", "QQplot")`
26		#'
27		#' @inherit shared_params return
28		#'
29		#' @section Decorating Module:
30		#'
31		#' This module generates the following objects, which can be modified in place using decorators::
32		#' - `histogram_plot` (`ggplot2`)
33		#' - `qq_plot` (`ggplot2`)
34		#' - `summary_table` (`listing_df` created with [rlistings::as_listing()])
35		#' - `test_table` (`listing_df` created with [rlistings::as_listing()])
36		#'
37		#' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
38		#' The name of this list corresponds to the name of the output to which the decorator is applied.
39		#' See code snippet below:
40		#'