###### tags: `R` `shiny` `tabPanel` `magick`
# R Shiny applications
## Add a shinyApp to a presentation
* Adding "runtime: shiny" to the top of the file is needed to run the presentation and interact with the visualisation
---
## Reactive expressions
* reactive expressions come in handy when you want to control the evaluation order in a Shiny app. You can use reactive expressions to stop an expression being updated until you have used a specified controller.
---
## Summary of layouts
* fluidPage() should be used to contain all layout elements except navbarPage()
* sidebarPanel() allows beautifully responsive content to be built
* navbarPage() provides Shiny apps with a horizontal navigation-- allowing you to create multipage dashboards
---
## shinyapps.io
* shinyapps.io is a hosting platform for Shinny apps with deep integration with RStudio.
* While displayed onscreen, Shiny apps consume active hours. The default timeout period is 15 minutes (e.g., every visit to your app consumes a minimum of 15 minutes unless you change that default). A free account has 25 active hours per month.
* Connect RStudio to your shinyapps.io account through the Publishing section of the Global Options screen.
---
## Self-contained shinyApp versus Split-file shiny apps
Self-contained shinyApp
```r!
library(shiny)
shinyApp(
ui=,
server=function(input,output){}
)
```
Split-file shiny apps
ShinyApp
* ui.R
* server.R
* data
* datafile1.csv
* datafile2.csv
* images
* image1.png
* image2.png
Example ui.R
```r!
shinyUI(
fluidPage(
sliderInput(inputId="exponent",label="Exponent", min=1, max=5, value=2))),
plotOutput(outputId="curvePlot")
)
)
```
Example server.R
```r!
shinyServer(function(input,output){
output$curvePlot <- renderPlot(
curve(x^as.numeric(input$exponent), from=-5, to=5)
)
})
```
---
## Upload a text/csv file, an image file and annotate the image using the file
---
ui.R
```r!
library(shiny)
# Define User Interface
shinyUI(fluidPage(
navbarPage(
# App title ----
titlePanel("File Upload"),
# Sidebar layout with input and output definitions ----
sidebarLayout(
sidebarPanel(
# fileinput() function is used to get the file upload contorl option
fileInput(inputId = "file", label = "Upload a text or csv file"),
helpText("Default max. file size is 5MB"),
# Add a horizontal line
tags$hr(),
# Add a level 4 header
h4(helpText("Select the read.table parameters below")),
checkboxInput(inputId = 'header', label = 'Header', value = FALSE),
checkboxInput(inputId = "stringAsFactors", "stringAsFactors", FALSE),
br(),
radioButtons( inputId = 'sep'
,label = 'Separator'
,choices = c(Comma=',',Semicolon=';',Tab='\t', Space='')
,selected = ','),
# Add a horizontal line
tags$hr(),
h4(helpText("Select number of bins for histogram")),
# Input: Slider for the number of bins ----
sliderInput(inputId = "bins",
label = "Number of bins:",
min = 1,
max = 50,
value = 30),
# Add a horizontal line
tags$hr(),
fileInput(inputId = "imported", label = "Upload an image file"),
helpText("Accepting file formats: jpg, png")
),
mainPanel(
uiOutput("tb")
)
)
))
)
```
server.R
```r!
shinyServer(function(input,output){
# This reactive function will take the inputs from ui.R and use them for read.table() to read the data from the file. It returns the dataset in the form of a data.frame.
# To use the input, use input$inputID (e.g., input$file)
# To use the data data.frame, refer it as "data()" rather than "data"
data <- reactive({
file1 <- input$file
if(is.null(file1)){return()}
# file$datapath -> gives the path of the file
read.table( file=file1$datapath
,sep=input$sep
,header = input$header
,stringsAsFactors = input$stringAsFactors)
})
# This reactive output contains the summary of the dataset and display the summary in table format
output$file_1 <- renderTable({
if(is.null(data())){return ()}
input$file
})
# This reactive output contains the summary of the dataset and display the summary in table format
output$file_2 <- renderTable(
input$imported
)
# This reactive output contains the summary of the dataset and display the summary in table format
output$sum <- renderTable({
if(is.null(data())){return ()}
summary(data())
})
# This reactive output contains the dataset and display the dataset in table format
output$table <- renderTable({
if(is.null(data())){return ()}
data()
})
# Make a histogram on column 3 of input data file
output$distPlot <- renderPlot({
# Get column 3
x <- data()[,3]
x <- na.omit(x)
bins <- seq(min(x), max(x), length.out = input$bins + 1)
hist(x
,breaks = bins
, col = "#75AADB"
, border = "black"
,xlab = "Marker measurement"
,main = "Histogram of marker measurement"
,density=TRUE )
})
# Display the uploaded image
output$image <- renderImage({
# The req function makes sure a input was actually selected
req(input$imported)
list(
src = normalizePath(file.path(input$imported$datapath))
,alt = "there should be an image here"
#,width = 400
#,height = 400
)
}, deleteFile = FALSE)
#--------------------------------------------------
# Edit the uploaded image file using magick package
#--------------------------------------------------
loaded_image <- reactive({
# Create pixel coordinates for rectangles
rect_width_half <- 12.5
rect_x_left <- data()[,1] - rect_width_half
rect_x_right <- data()[,1] + rect_width_half
rect_y_top <- data()[,2] - rect_width_half
rect_y_bottom <- data()[,2] + rect_width_half
image <- magick::image_read(req(input$imported$datapath))
magick::image_draw(image=image())
#return(image_drew)
# image <- magick::image_read(req(input$imported$datapath))
# magick::image_draw(image())
# ## Draw rectangles for individual stained cells
# graphics::rect( xleft= rect_x_left
# ,ybottom=rect_y_bottom
# ,xright=rect_x_right
# ,ytop=rect_y_top
# ,col = NA # color(s) to fill or shade the rectangle(s) with. The default NA (or also NULL) means do not fill, i.e., draw transparent rectangles, unless density is specified.
# ,border = "black" # color for rectangle border(s).
# ,lty = par("lty")
# ,lwd = 2)
#grDevices::dev.off()
})
output$image_edited <- renderPlot({
image_ggplot(loaded_image())
})
# The following renderUI is used to dynamically generate the tabsets when the file is loaded. Until the file is loaded, app will not show the tabset.
output$tb <- renderUI({
if(is.null(data()))
h5("Powered by", tags$img(src='RStudio-Ball.png', heigth=200, width=200))
else
tabsetPanel( tabPanel("About file", tableOutput(outputId ="file_1"))
,tabPanel("About image", tableOutput(outputId = "file_2"))
,tabPanel("Data", tableOutput(outputId ="table"))
,tabPanel("Summary", tableOutput(outputId ="sum"))
,tabPanel("Histogram",plotOutput(outputId = "distPlot"))
,tabPanel("Image", imageOutput(outputId = "image"))
,tabPanel("Annotate", imageOutput(outputId = "image_edited"))
)
})
})
```
---
## Errors
```r!
loaded_image <- reactive({
# Create pixel coordinates for rectangles
rect_width_half <- 12.5
rect_x_left <- data()[,1] - rect_width_half
rect_x_right <- data()[,1] + rect_width_half
rect_y_top <- data()[,2] - rect_width_half
rect_y_bottom <- data()[,2] + rect_width_half
image <- magick::image_read(req(input$imported$datapath))
magick::image_draw(image=image)
#return(image_drew)
# image <- magick::image_read(req(input$imported$datapath))
# magick::image_draw(image())
# ## Draw rectangles for individual stained cells
# graphics::rect( xleft= rect_x_left
# ,ybottom=rect_y_bottom
# ,xright=rect_x_right
# ,ytop=rect_y_top
# ,col = NA # color(s) to fill or shade the rectangle(s) with. The default NA (or also NULL) means do not fill, i.e., draw transparent rectangles, unless density is specified.
# ,border = "black" # color for rectangle border(s).
# ,lty = par("lty")
# ,lwd = 2)
#grDevices::dev.off()
})
# Error:
#Listening on http://127.0.0.1:3637
#Warning: Error in grid::grid.newpage: Cannot open a new page on a drawing device
# 174: <Anonymous>
```
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