The HTML UI application demonstrates defining a Shiny user-interface using a standard HTML page rather than a ui.R script. To run the example type:
> library(shiny)
> runExample("08_html")
#### www/index.html
<html>
<head>
<script src="shared/jquery.js" type="text/javascript"></script>
<script src="shared/shiny.js" type="text/javascript"></script>
<link rel="stylesheet" type="text/css" href="shared/shiny.css"/>
</head>
<body>
<h1>HTML UI</h1>
<p>
<label>Distribution type:</label><br />
<select name="dist">
<option value="norm">Normal</option>
<option value="unif">Uniform</option>
<option value="lnorm">Log-normal</option>
<option value="exp">Exponential</option>
</select>
</p>
<p>
<label>Number of observations:</label><br />
<input type="number" name="n" value="500" min="1" max="1000" />
</p>
<pre id="summary" class="shiny-text-output"></pre>
<div id="plot" class="shiny-plot-output"
style="width: 100%; height: 400px"></div>
<div id="table" class="shiny-html-output"></div>
</body>
</html>
#### server.R
library(shiny)
# Define server logic for random distribution application
shinyServer(function(input, output) {
# Reactive function to generate the requested distribution. This is
# called whenever the inputs change. The output functions defined
# below then all used the value computed from this function
data <- reactive(function() {
dist <- switch(input$dist,
norm = rnorm,
unif = runif,
lnorm = rlnorm,
exp = rexp,
rnorm)
dist(as.integer(input$n))
})
# Generate a plot of the data. Also uses the inputs to build the
# plot label. Note that the dependencies on both the inputs and
# the data reactive function are both tracked, and all functions
# are called in the sequence implied by the dependency graph
output$plot <- reactivePlot(function() {
dist <- input$dist
n <- input$n
hist(data(),
main=paste('r', dist, '(', n, ')', sep=''))
})
# Generate a summary of the data
output$summary <- reactivePrint(function() {
summary(data())
})
# Generate an HTML table view of the data
output$table <- reactiveTable(function() {
data.frame(x=data())
})
})