textFunctionInput.md

title: "Recursive Shiny Module for Functionals" author: "Keon-Woong Moon" date: "2017-11-03" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{textFunctinoInput} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}

There are many functions that takes a function as an input : Functionals. To handle a functional in a shiny app, you have to make a shiny module that allows recursive call. I have included an recursive shiny module textFunction in my package ggplotAssist. The UI of textFunction shiny module is textFunctionInput and the server function is textFunction. I also included two toy shiny apps to demonstrate the recursive shiny module.

Prerequisite

You have to install the developmental version of R package editData from github.

#install.packages("devtools")
devtools::install_github("cardiomoon/editData")

Install package

You have to install the developmental version of ggplotAssist package from github.

devtools::install_github("cardiomoon/ggplotAssist")

Example 1

After install the package ggplotAssist, you can run the first example app by the following R code.

shiny::runApp(system.file('textFunctionExample',package='ggplotAssist'))

Enter element_text() in the textInput(1).

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You can select font family(2) or colour(3). You can enter size(4). To adjust margin, enter margin() at the margin textInput(5).

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You can adjust dimensions of each margin(6,7) or ajdust default units of dimension(8). You can see the resultant R code for this function(arrow).

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Example 2

You can use textFunctionInput as a selectInput. Please run the second example app by the following R code.

shiny::runApp(system.file('textFunctionExample2',package='ggplotAssist'))

Select guide_colorbar() among the selectInput(arrow).

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You can enter title(9) or select title.position(10). You can set the title.theme by enter element_text() in the textInput(11).

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You can adjust font family(12) or font face(13). Also you can set the margin by entering margin() in the textInput(14).

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You can see the source R code at the github page of package ggplotAssist: https://github.com/cardiomoon/ggplotAssist.



cardiomoon/ggplotAssist documentation built on May 28, 2019, 7:14 p.m.