pre-release vignettes review

.lintr

@@ -1,5 +1,6 @@
 linters: linters_with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
-  object_usage_linter = NULL
+  object_usage_linter = NULL,
+  object_name_linter = object_name_linter(styles = c("snake_case", "symbols"), regexes = c(ANL = "^ANL_?[0-9]*$", ADaM = "^r?AD[A-Z]{2,3}_?[0-9]*$"))
   )

R/tm_g_response.R

@@ -413,7 +413,6 @@ srv_g_response <- function(id,
           env = list(resp_var = resp_var)
         )
       ) %>%
-        # nolint start
         # rowf and colf will be a NULL if not set by a user
         teal.code::eval_code(
           substitute(
@@ -433,7 +432,6 @@ srv_g_response <- function(id,
             env = list(x_cl = x_cl, rowf = rowf, colf = colf)
           )
         )
-      # nolint end
 
       plot_call <- substitute(
         expr = ggplot(ANL2, aes(x = x_cl, y = ns)) +

vignettes/teal-modules-general.Rmd

@@ -10,25 +10,25 @@ vignette: >
 
 ### Introduction
 
-`teal` is a package that extends the `shiny` framework to build interactive GUI applications using the R programming
-language. `shiny`, and hence `teal`, are implemented to allow the building of large applications by combining small,
-decoupled modules. `teal.modules.general` is a package consisting of a set of modules that are used to build `teal`
-applications. It is "general" in the sense that the intended functions of these modules are more fundamental. This is
-in contrast to the intended functions of its sister package, `teal.modules.clinical`, which is more specialized around
-clinical data. The modules of `teal.modules.general` can be combined with modules of `teal.modules.clinical` and / or
+`teal` extends the `shiny` framework, enabling the creation of interactive GUI applications using the `R`. 
+`shiny`, and `teal`facilitate the development of extensive applications through combining small, decoupled modules. 
+The `teal.modules.general` package consist of collection of modules  essential for developing `teal` applications. 
+It is "general" in the sense that the intended functions of these modules are more fundamental. This contrasts with the more specialized focus on clinical data found in the `teal.modules.clinical` package. 
+The modules from `teal.modules.general`  can be used in conjunction with modules from `teal.modules.clinical` and / or
 other `shiny` modules to build a large `teal` / `shiny` app.
 
+
 The concepts presented here require knowledge about the core features of `teal`, specifically on how to launch a `teal`
 application and how to pass data into it. Therefore, it is highly recommended to refer to the [`README`](https://insightsengineering.github.io/teal/index.html) file and 
 the introductory [vignette](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html) of the `teal` package.
 
-See also `teal.modules.clinical's` [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
+See also `teal.modules.clinical`'s [`README`](https://insightsengineering.github.io/teal.modules.clinical/latest-tag/index.html).
 
 ### Main features
 
 There are five areas of data science that `teal.modules.general` provides tools and solutions (modules) for:
 
-- viewing data in tabular form
+- viewing data in tabular formats
 - visualizing data in plots and graphs
 - viewing data and files in a directory
 - examining missing and extreme values in data
@@ -38,11 +38,13 @@ See [package functions / modules](https://insightsengineering.github.io/teal.mod
 
 ### Example application
 
-A simple application including a `tm_variable_browser` module could look like this:
+A simple application featuring the `tm_variable_browser()` module:
 ```{r, message = FALSE, results = "hide"}
+# load libraries
 library(teal.modules.general)
+library(teal.widgets)
 
-# nolint start
+# teal_data object
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -51,40 +53,42 @@ data <- within(data, {
 datanames <- c("ADSL", "ADTTE")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    tm_variable_browser(
-      label = "Variable browser",
-      ggplot2_args = teal.widgets::ggplot2_args(
-        labs = list(subtitle = "Plot generated by Variable Browser Module")
-      ),
-    )
+# tm_variable_browser module
+tm_variable_browser_module <- tm_variable_browser(
+  label = "Variable browser",
+  ggplot2_args = ggplot2_args(
+    labs = list(subtitle = "Plot generated by Variable Browser Module")
   )
 )
+
+# initialize the app
+app <- init(
+  data = data,
+  modules = modules(tm_variable_browser_module)
+)
 ```
 
 ```{r, eval = FALSE}
 shinyApp(app$ui, app$server)
 ```
 
+<img src="images/app-teal-modules-general.png" style = "display: block; margin: 0px; width: 100%"/>
+
 Let's break the above app into pieces:
+
+1: Load the necessary libraries and data.
 ```r
 library(teal.modules.general)
+library(teal.widgets)
 ```
-The line mentioned above imports the library required for this example and loads data from within that library.
+2: Construct a `teal_data` object containing that will serve as the source of data for the `teal` app. `teal_data` not only encapsulates the data for the app, but it also houses the code required to create the data to maintain reproducibility.
 
-Now, we are building a `teal_data` object that will serve as the source of data for the teal app.
-`teal_data` not only encapsulates the data for the app, but it also houses the code required to create the data to maintain reproducibility.
-To do this, we create an empty `teal_data` object and evaluate code to produce the data within the `teal_data` object,
-so both the code and data are stored together.
+To do this, we create an empty `teal_data` object and evaluate code to produce the data within the `teal_data` object, so both the code and data are stored together.
 
 Following this, we set the `datanames` and `join_keys`.
 
 ```r
-# nolint start
 data <- teal_data()
 data <- within(data, {
   ADSL <- teal.modules.general::rADSL
@@ -93,49 +97,40 @@ data <- within(data, {
 datanames <- c("ADSL", "ADTTE")
 datanames(data) <- datanames
 join_keys(data) <- default_cdisc_join_keys[datanames]
-# nolint end
 ```
 
-There is no need to load `teal` as `teal.modules.general` already depends on it.
+3: Initialize a `teal` application with specified data and modules, in this case, the module: `tm_variable_browser`, datasets:`ADSL` and `ADTTE`.
 
-In the next step, we use `teal` to create `shiny` `ui` and `server` functions so we can launch using `shiny`. The `data`
-argument tells `teal` about the input data - the two datasets `ADSL` and `ADTTE` - and the `modules`
-argument indicates the modules included in the application. Here, we include only one - `tm_variable_browser`.
+`shiny::shinyApp()` use the `ui` and `server` component to initialize the `teal` app.
 
-```{r, results = "hide"}
-app <- teal::init(
-  data = data,
-  modules = teal::modules(
-    tm_variable_browser(
-      # module name to display in the GUI
-      label = "Variable browser",
-      # this argument takes a set of arguments to pass to ggplot2.
-      # the arguments must have the same names as its ggplot2 counterpart, e.g. `subtitle`
-      ggplot2_args = teal.widgets::ggplot2_args(
-        labs = list(subtitle = "Plot generated by Variable Browser Module")
-      ),
-    )
+
+```r
+tm_variable_browser_module <- tm_variable_browser(
+  # module name to display in the GUI
+  label = "Variable browser",
+  # this argument takes a set of arguments to pass to ggplot2.
+  # the arguments must have the same names as its ggplot2 counterpart, e.g. `subtitle`
+  ggplot2_args = ggplot2_args(
+    labs = list(subtitle = "Plot generated by Variable Browser Module")
   )
 )
-```
 
-The `shiny` function `shinyApp` used the `ui` and `server` objects to initialize the `teal` app.
+app <- init(
+  data = data,
+  modules = modules(tm_variable_browser_module)
+)
 
-```{r, eval = FALSE}
-shiny::shinyApp(app$ui, app$server)
+shinyApp(app$ui, app$server)
 ```
 
 In a `teal` app, data and modules are decoupled. In the app above:
 
 - The app developer specified the data and assigned it to the `data` argument.
 - The app developer specified the module and assigned it to the `modules` argument.
-- The `init` function took these arguments and returned a list, which can be demonstrated by running:
+- The `init` function took these arguments and returned a list containing `ui` and `server` object, which can be demonstrated by running:
 
 ```{r, indent = "     "}
 class(app)
-```
-This list contains two R objects named `ui` and `server`.
-```{r, indent = "     "}
 names(app)
 ```