Create a VizModules Figure Builder Application

Build the multi-panel Figure Builder Shiny application as a returnable object. The app lets users add any VizModules plot module to a free-form A4 canvas, drag and resize each plot, filter each plot's data independently, label panels automatically, and export the whole figure as a single editable SVG (or bundle every plot's source data, HTML plot, and statistics into one .zip).

Usage

figureBuilderApp(
  data_list = NULL,
  module_registry = NULL,
  title = "VizModules Figure Builder",
  return_components = FALSE
)

Arguments

data_list: An optional named list of data frames that seed the dataset registry. If NULL (the default), the bundled example datasets (plus a sales_by_region summary suited to the pie plot) are used. At least one element is required. An element is either a data frame, or a named list of data frames for a module that needs companion tables (the ComplexHeatmap module's list(matrix = , column_annotations = )); in the latter case only the primary table is filtered and shown in the panel's table pane.
module_registry: An optional named list describing the plot modules to offer. If NULL (the default), all bundled VizModules modules are offered, each opening on the same example figure as in moduleGalleryApp(). Each entry is itself a list with components: label (character, shown in the picker), dataset (character, the dataset name its defaults were written for), inputs_ui, output_ui, and server_fn (the module's three functions), and defaults (a named list of input defaults applied only when dataset is the chosen dataset). An entry may also carry primary.table, naming which table of a multi-table dataset gets filtered (the first by default); its presence is also what marks the module as able to take a multi-table dataset at all, so modules without it are handed the primary table alone and any dataset stays usable with any module. See figureBuilderServer() for the vector_svg hook that lets a non-plotly module take part in the SVG figure export.
title: A character string used as the page title and header (default: "VizModules Figure Builder").
return_components: Logical. When FALSE (the default) a shiny::shinyApp() object is returned. When TRUE a named list with ui and server elements is returned instead, which is convenient for deployment scripts that need an explicit shinyApp(ui, server) call.

Value

Either a shiny::shinyApp() object, or (when return_components = TRUE) a list with elements ui and server.

Details

Datasets are supplied via data_list and seed the "Add Plot" dialog; users can also upload additional datasets (CSV, TSV, or tab-delimited TXT) at runtime. The set of available plot modules is controlled by module_registry, so the app can be extended with custom wrapper modules without editing the package.

This is the recommended way to launch a standalone Figure Builder. Internally it is a thin wrapper around the figureBuilderUI() / figureBuilderServer() Shiny module, so the same builder can be embedded inside a larger app (and instantiated more than once) by calling those two functions directly. It is also the Figure Builder tab of moduleGalleryApp().

Author

Jared Andrews

Examples

library(VizModules)

# Launch with the bundled example datasets and all modules:
app <- figureBuilderApp()
if (interactive()) runApp(app)

# Launch with your own datasets:
app2 <- figureBuilderApp(data_list = list("iris" = iris, "mtcars" = mtcars))
if (interactive()) runApp(app2)

# Return the UI and server separately (e.g. for a deployment app.R):
parts <- figureBuilderApp(return_components = TRUE)
if (interactive()) shinyApp(parts$ui, parts$server)