Making Modules

In formods: 'Shiny' Modules for General Tasks

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Introduction

This vignette will provide an overview of the formods framework for creating reproducable modules that interact with each other. Each module has its own namespace that is mantained by using a module short name as a prefix for functions. For example the figure generation module uses FG. If you want to create a module, please submit an issue at the formods github repository with the following information:

• The short name you intend to use
• A brief description of the module
• A list of modules it depends on

Current modules

The following modules are currently available:

• ASM - App State Management
• DW - Data Wrangling
• FG - Figure Generation
• FM - Formods
• NCA - Non-Compartmental Analysis
• UD - Upload Data

Other short names in use:

• MC - This is a reserved word

Currently in development:

• MB - Model Builder
• CTS - Clinical Trial Simuilations

formods framework

To get started you need to create some template files. The example below assumes you are creating this module for a package called mypackage and that you are running this command in a git repository. Say that this module is used to produce widgets, the short name is MM which stands for My Module:

use_formods(SN          = "MM",
            Module_Name = "My Module",
            element     = "widgets", 
            package     = "mypackage")

This command will create the following files:

• MM_module_components.R - An app that can be used for testing the module and highlighting the different UI elements that are used within the module (found in inst/templates).
• MM_Server.R: A bare bones file containing the expected functions and their minimal inputs. (found in R).
• MM.yaml: This module configuration file contains the the minimal elements expected, but you can add your own fields to suit your modules needs (found in inst/templates).
• MM_funcs.R: This script contains example code for the different elements of the module that can be used in the function examples and also to quickly test the different module functions while you develop them (found in inst/test_apps).
• MM_preload.yaml: This yaml file contains a skeleton of a preload configuration file. This will need to be populated to work with MM_test_mksession() (found in MM_funcs.R) in order to create a testing environment for your module (found in inst/prelaod).

Expected functions

The module template will create a standard set of functions for you. The MM below will be replaced with whatever short name you choose above when you create the templates. These functions can be customized for your specific module. Some are optional and can be deleted. For example the MM_fetch_ds function is only needed if your module creates datasets and provides them for other modules to use (like the DW module exports data views to be used by other modules). The modules are designed to create elements. For example the DW module creates data view elements, the FG module is used to create figure elements, etc.

• MM_Server Shiny server function.
• MM_init_state Creates an empty the formods state for the module.
• MM_fetch_state Each module has a function to fetch the state. Within this function there should be no interactivity. Any access of the elements to the Shiny input should be isolated. Based on differences between the input elements (current state of the app) and the stored app state can be used to trigger different things.
• MM_fetch_code This takes as it's first argument the module state. When called with only this argument it should return a character object containing all of the code needed to generate the elements of this module represented in the app. You can assume that any modules this one depends on will be defined previously. For example the FG module will return only that code associated with generating figures. It will be appended to the code from the UD and DW modules that define loading the dataset and creation of the data views. For modules where no code is generated (e.g. ASM) just return NULL.
• MM_append_report If a module generates reportable outputs, this function will be used to append those outputs to the overall reports generated by formods.
• MM_fetch_ds If a module provides data sets to be used in other modules you need to create this function. For an example see the DW_fetch_ds() in the DW module This function should return at least the following:
  • hasds Boolean variable indicating if the modules currently has any exportable datasets.
  • isgood General return status of the funciton. Set to FALSE if any errors were encoutered.
  • msgs A character vector of any messages to pass back to the user.
  • ds A module can provide multiple datasets. This is a list with the following elements for each dataset:
    • label Text label for the dataset
    • MOD_TYPE Short name for the type of module.
    • id module ID.
    • DS Dataframe containing the actual dataset.
    • DSMETA Metadata describing DS.
    • code Complete code to build dataset.
    • checksum Module checksum.
    • DSchecksum Dataset checksum.
• MM_fetch_mdl If a module provides ODE models to be used in other modules you need to create this function. To see an example of this check out the MB_fetch_mdl() in the MB module This function should return at least the following:
  • hasmdl Boolean variable indicating if the modules currently has any exportable models.
  • isgood General return status of the funciton. Set to FALSE if any errors were encountered.
  • msgs A character vector of any messages to pass back to the user.
  • ts_details List of timescale details
  • mdl A module can provide multiple models. This is a list with the following elements for each model:
    • label Text label for the model.
    • MOD_TYPE Short name for the type of module.
    • id module ID.
    • rx_obj The rxode2 object that holds the model.
    • rx_obj_name The rxode2 object name in generated code.
    • ts_obj The timescale object that holds timescales list.
    • rx_obj_name The timescale object name in generated code.
    • fcn_def Text to define the model
    • MDLMETA Verbose metadata describing model.
    • code Complete code to build the model.
    • checksum Checksum of the module the model came from.
    • MDLchecksum Checksum of the model.
• MM_preload The ASM module provides the ability to load a previous analysis from yaml files. This function is called with the contents of those yaml files to process and load them.
• MM_mk_preload This will create a preload list of the current state of the module.
• MM_test_mksession When testing outside of Shiny it is useful to have a pre-populated session, input, etc. objects with actual data. Each module should have a test_mksession function that populates these objects with useful data. If your module depends on a different module. The function should return the following:
  • isgood Boolean indicating the exit status of the function.
  • msgs Any messages generated when creating the test environment.
  • session The value Shiny session variable (in app) or a list (outside of app) after initialization.
  • input The value of the shiny input at the end of the session initialization.
  • state App state.
  • react_tate`` Thereact_state` components.
• MM_new_element Creates a new module element.
• MM_fetch_current_element Extracts the current element from the state object.
• MM_set_current_element Sets the current element to the provided value.
• MM_del_element Deletes the current active element.

Expected UI components

• ui_mm_compact This is a UI output that contains a compact view of your module that can be called from the main ui functions for the App. It is composed of the individual UI elements that are shown in the MM_module_components.R file. This allows the user a quick way to utilize a model (using the ui_mm_compact), and the ability to customize the module UI by manually arranging the pieces found in MM_module_components.R.

Module interaction

Say you are using the UD module to feed data into the DW module and the user goes back to the upload form and uploads a different data set. This will need to trigger a reset of the Data Wrangling module as well as tell your larger app that something has changed.

Module state and reacting to changes

Changes in module states are detected with the react_state object. For a given module of type "MM" with a module id of "ID" you would detect changes by reacting to react_state[["ID"]] and looking for changes in the checksum element below:

react_state[["ID"]][["MM"]][["checksum"]]

• checksum A checksum that can be used to detect changes in this module. For example in the UD module this will change if the uploaded file or the sheet selected from a currently uploaded file changes.

Helper functions in formods

• FM_le() - Creates log entries (le) that are displayed in the console and recorded in the log file for the current session.
• FM_tc() - This can be used to evaluate code, trap errors, and process results.
• has_changed() - Depreciated see has_updated()
• has_updated() - Used to compare objects to see if they have changed.
• icon_link() - Used to create the ui for a link using an icon.
• is_installed() - Used to test if a package is available.
• is_shiny() - Used to test if a session object is simply a list or a legitimate Shiny session object.
• set_hold() - Used to set a hold on one or more UI elements. This prevents internal updating of that UI element based on the current value in the App.
• fetch_hold() - This will retrieve the hold status of a UI element.
• remove_hold() - This will remove any holds set on a UI element.
• FM_build_comment() - This creates comments from strings so they will form sections when viewed in RStudio.
• FM_add_ui_tooltip() - Attaches a tooltip to a UI element.
• FM_init_state() - Called at the top of your module state initialization function to create a skeleton of a module state that you can then build upon.
• FM_set_notification() - Within you code you can create notifications and attach them to a module state.
• FM_notify() - Used in observeEvent() to show notifications that have not yet been displayed.
• FM_set_mod_state() - Used to save any changes to the module state.
• FM_fetch_mod_state() - Used to get the module state.
• FM_set_ui_msg() - Attach verbose messages or errors that need to be pushed back to the user in the app.
• FM_pretty_sort() - Used as a general sorting function that will try to make the sorted results prettier.
• FM_pause_screen() - Pauses the screen when doing something on the server side that takes a while.
• FM_resume_screen() - Resumes activity (unpauses the screen) when you're done with the pause.
• FM_fetch_data_format() - Creates formatting information for display for a given data frame.

The examples below require a Shiny session variable and a formods state object. Here we create some examples and other objects needed to demonstrate the functions below.

library(formods)
# This creates the state and session objects
sess_res = UD_test_mksession(session=list())
state    = sess_res$state
session  = sess_res$session

# Here we load an example dataset into the df object.
data_file_local =  system.file(package="formods", "test_data", "TEST_DATA.xlsx")
sheet           = "DATA"

df = readxl::read_excel(path=data_file_local, sheet=sheet)

Setting holds on UI elements

The mechanics of the fetch state functions mean that each time a fetch state is called, all of the UI elements in the App are pulled and placed in the app state. This generally works well with some exceptions. The main exception is when you want to have a UI element that changes another UI element. Say for example you have a selection box with a UI id of my_selection. You want that selection to alter a text input with an id of my_text. However if you just poll the ui elements you may update my_text based on changes to my_selection then have those overwritten by the current value of my_text. To prevent this, you need to do two things:

• When processing my_selection you need to set a hold on my_text (done with set_hold()).
• When processing my_text you need to do that only if there is no hold set. This is checked with fetch_hold()

Lastly you need to remove the hold. This is done after the UI has refreshed with the new text value populated in to my_text (with the appropriate reactions set). This is done with an observeEvent that is triggered after everything else (with a priority of -100 below):

remove_hold_listen  <- reactive({
  list(input$my_selection)
})
observeEvent(remove_hold_listen(), {
  # Once the UI has been regenerated we
  # remove any holds for this module
  state = MM_fetch_state(id              = id,
                         input           = input,
                         session         = session,
                         FM_yaml_file    = FM_yaml_file,
                         MOD_yaml_file   = MOD_yaml_file,
                         react_state     = react_state)

  FM_le(state, "removing holds")
  # Removing all holds
  for(hname in names(state[["MM"]][["ui_hold"]])){
    remove_hold(state, session, hname)
  }
}, priority = -100)

The remove_hold_listen object should contain all of the inputs that create holds.

Dataframe formatting information

If you want to tables and pulldown menues based on the types of data in each column you can use the FM_fetch_data_format() function.

hfmt = FM_fetch_data_format(df, state)

# Descriptive headers 
head(as.vector(unlist( hfmt[["col_heads"]])))

# Subtext
head(as.vector(unlist( hfmt[["col_subtext"]])))

The custom headers can be used with the {rhandsontable} package.

hot = rhandsontable::rhandsontable(
  head(df),
  width      = "100%",
  height     = "100%",
  colHeaders = as.vector(unlist(hfmt[["col_heads"]])),
  rowHeaders = NULL
  )

hot

To add subtext to a selection widget in Shiny you need to use the {shinyWidgets} package.

sel_subtext = as.vector(unlist( hfmt[["col_subtext"]]))
library(shinyWidgets)
shinyWidgets::pickerInput(
    inputId    = "select_example",
    choices    = names(df),
    label      = "Select with subtext",
    choicesOpt = list(subtext = sel_subtext))

To alter the formats shown here you need to edit the formods.yaml configuration file and look at the FM$\rightarrow$data_meta section.

Notifications

Notifications are created using the {shinybusy} package and are produced with two different functions: FM_set_notification() and FM_notify(). This is done in a centralized fashion where notifications are added to the state object as user information is processed. This will set a notification called Example Notification. Along with that a timestamp is set:

   state = FM_set_notification(state, "Something happened", "Example Notification")

That timestamp is used to track and prevent the notification from being shown multiple times. Next you need to setup the reactions to display the notifications. Here you can create a reactive expression of the inputs that will lead to a notification:

    toNotify <- reactive({
      list(input$input1,
           input$input2)
    })

Next you use observeEvent() with that reactive expression to trigger notifications. You need to use the fetch state function for that module to get the state object with the notifications. Then FM_notify() will be called an any unprocessed notifications will be displayed:

    observeEvent(toNotify(), {
      state = MM_fetch_state(id              = id,
                             input           = input,
                             session         = session,
                             FM_yaml_file    = FM_yaml_file,
                             MOD_yaml_file   = MOD_yaml_file,
                             react_state     = react_state)

      # Triggering optional notifications
      notify_res =
      FM_notify(state    = state,
                session  = session)
    })

Adding tooltips

Tooltips are created internally using the suggested {prompter} package. To add a tool tip to a ui element you would use the FM_add_ui_tooltip() function. For example to add the tool tip, You need to type harder! to a text input you would do the following:

uiele = shiny::textInput(
          inputId = "some_text", 
          label   = "You need to type harder!")
uiele = FM_add_ui_tooltip(state, uiele, 
      tooltip  = "This is a tooltip",
      position = "left")

Pausing the screen

To pause the screen the {shinybusy} package is also used. This is controlled with two functions: FM_pause_screen() is used to pause the screen and/or update the pause message, and FM_resume_screen() is used end the pause and resume interaction with the user.

FM_pause_screen(state, session)
FM_resume_screen(state, session)

formods state objects

When you create a formods state object it can have the following fields:

• yaml- Contents of the formods configuration file.
• MC - Contents of the module configuration file.
• MM - MM here is the short name of the current module. MOD_TYPE below), this is where you would store any app information. (see below).
• MOD_TYPE - Short name of the module.
• id - ID of the module.
• FM_yaml_file - formods configuration file.
• MOD_yaml_file - Module configuration file.
• notifications - Contains notifications set by the user through FM_set_notification().

App information in MM

This field state$MM is relatively free form but there are some reserved elements. These reserved keyword are:

• button_counters - Counter that tracks button clicks
• ui_hold - List of hold elements that is populated with set_hold()
• isgood - Boolean variable indicating the state of the module.
• ui_msg - Messaages returned to the UI with captured errors populated with FM_set_ui_msg()

Other than those fields you can store whatever else you need for your module.

Checklist

The following is a suggested checkist to go over when making a module:

• Try the following functions with and without content
• MM_mk_preload
• MM_fetch_code

Configuration file

```{css, echo=FALSE} .scroll-100 { max-height: 100px; overflow-y: auto; background-color: inherit; }

# YAML configuration files {.tabset}

```r
yaml= file.path(system.file(package="formods"), "templates", "formods.yaml")
cat(readLines(file.path(system.file(package="formods"), "templates", "formods.yaml")), sep="\n")

#library(shiny)
#library(shinyAce)
# renderUI({
# aceEditor("formods", value=readLines(file.path(system.file(package="formods"), "templates", "formods.yaml")))
# })

# yamls = list(
#   formods.yaml= file.path(system.file(package="formods"), "templates", "formods.yaml"),
#   ASM.yaml    = file.path(system.file(package="formods"), "templates", "ASM.yaml"),
#   DS.yaml     = file.path(system.file(package="formods"), "templates", "DW.yaml") 
#   
# )
# 
# for(yaml in names(yamls)){
# # cat("``` yaml")
#   cat(paste(readLines(file.path(system.file(package="formods"), "templates", "formods.yaml"))), collapse="\n")
# }

formods documentation built on April 12, 2025, 1:57 a.m.