rShiny Selecting between different plotting packages - r

Question

I have a task where i need to build an rShiny app that allows the user to choose which kind of R plotting package is used in-order to display a plot.
Currently the only way i have gotten it to work (semi-decently) is using package specific functions for each package on the server side and using a series of conditional panels on the UI side.
However the problem is that when the user enters the page for the first time then all plots are initialized. Second problem is when the user changes some plot input values and after that chooses another package then the old plot will be displayed until a new plot is created.
Questions:
Is this the only available approach?
I feel that there must be a way to use reactive functions for the package selection?
I feel that it should be possible to use a single rShiny's htmlOutput (or something similar) in the ui and therefore not needing the switchPanel?
I have created a small app to demonstrate my current implementation and both problems:
server.R
library(shiny)
#library(devtools)
#install_github("ramnathv/rCharts")
library(rCharts)
shinyServer(function(input, output) {
names(iris) = gsub("\\.", "", names(iris))
#Render the Generic plot
output$GenericPlot <- renderPlot({
data = iris[0:input$variable,]
plot(data$SepalLength ~ data$SepalWidth)
})
#Render the Polychart plot
output$PolychartPlot <- renderChart({
plotData <- rPlot(SepalLength ~ SepalWidth, data = iris[0:input$variable,], color = 'Species', type = 'point')
plotData$addParams(dom = 'PolychartPlot')
return(plotData)
})
#Render the NDV3 plot
output$NDV3Plot <- renderChart({
plotData <- nPlot(SepalLength ~ SepalWidth, data = iris[0:input$variable,], group = 'Species', type = 'scatterChart')
plotData$addParams(dom = 'NDV3Plot')
return(plotData)
})
})
ui.R
library(shiny)
library(rCharts)
shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("lib", label = "Library:",
choices = list("Generic", "rCharts Polychart", "rCharts NDV3"),
selected = "Generic"
),
numericInput("variable", "Observations:",
min = 5,
max = 150,
value = 10
)
),
mainPanel(
conditionalPanel(
condition = "input.lib == 'Generic'",
h3("Generic plot"),
plotOutput("GenericPlot")
),
conditionalPanel(
condition = "input.lib == 'rCharts Polychart'",
h3("rCharts Polychart plot"),
showOutput("PolychartPlot", "polycharts")
),
conditionalPanel(
condition = "input.lib == 'rCharts NDV3'",
h3("rCharts NDV3 plot"),
showOutput("NDV3Plot", "nvd3")
)
)
)
))
The final version will use a different dataset and more charting packages. The provided code is more of a toy example, with most of the stuff stripped out.

Answer 1

Make a single part in the output part of the app that includes some logic based on the input. For example,
library(shiny)
library(ggplot2)
data(cars)
server <- function(input, output) {output$plot<- renderPlot({
if (input$lib == "base") {
p <- plot(cars$speed, cars$dist)
} else if (input$lib == "ggplot") {
p <- ggplot(cars, aes(x = speed, y = dist)) + geom_point()
}
p
})
}
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("lib", "Library: ", choices = list("base", "ggplot"),
selected = "base")
),
mainPanel(plotOutput("plot"))
)
)
shinyApp(ui = ui, server = server)
This provides one plot and as soon as I change the lib option it regenerates.

Answer 2

Found a solution to my problem. The solution is basically to use uiOutput() in the ui.R and move the plotOutput(), showOutput() methods to the server.R.
The solution based on iacobus code:
ui.R
library(shiny)
library(rCharts)
shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("lib", "Library: ", choices = list("base", "ggplot", "Polychart"),
selected = "base")
),
mainPanel(uiOutput("plot"))
)
))
server.R
library(shiny)
library(ggplot2)
library(rCharts)
data(cars)
server <- function(input, output) {
output$plot<- renderUI({
if (input$lib == "base") {
plotOutput("base")
} else if (input$lib == "ggplot") {
plotOutput("ggplot")
} else if (input$lib == "Polychart") {
showOutput("polychart", "polycharts")
}
})
output$base <- renderPlot({
plot(cars$speed, cars$dist)
})
output$ggplot <- renderPlot({
ggplot(cars, aes(x = speed, y = dist)) + geom_point()
})
output$polychart <- renderChart({
p <- rPlot(speed ~ dist, data = cars, type = "point")
p$addParams(dom = 'plot')
p
})
}
The difficulty arose for me, because i assumed that plotOutput(), showOutput() etc methods can only be used in the ui.R. This however is not the case.
EDIT:
It turned out that this was not enough for pollyCharts to work properly along with other rCharts packages.
instead i am using renderUI and rCharts $show to display the chart inline. The following link was helpful for me: https://github.com/ramnathv/rCharts/issues/373. In the ui i'm using htmlOutput