#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#


##Adding a save button.

## Suppose we have found a data set we like, and want  to use/save elsewhere.  For a complex app, this could be used
## to record user feedback or something.  Note that because you are allowing an external user to write things to your
## server space, this involves some possible risks--they could try to fill up your computer's memory and crash your system.
##
##
##  To do this, we have to consider a  couple things--what is it we want to save? How do we want to save it? And 
## should we try to simply 'log' information to an existing file, or completely overwrite things.
##
##  for the moment, let's say we want to create a logging file that simply adds the information in the summary table  column freq to an
## existing .csv file.  This is pretty straightforward to do with the append=T argument of write.csv.
##
## To do this, we need to:
## 1. create an action button in the interface. (this is already done, using actionButton()).
## 2. create code that responds to an update in the action button (using ObserveEvent() in the server, have the first argument refer to the 
##   button label, and the second argument a code block specified in {} that is the code you want to execute.
## 3. Have this code write a file consisting of the summary of the data you output in the previous tutorial.  You can recalculate 
##   the summary within this ObserveEvent code.
##  4. Challenge: make the summary table reactive, so that the table gets calculated as its own reactive data, and then this table gets
##    used both to display the table and to save the table out.     

library(shiny)
library(ggplot2)

# Define UI for application that draws a histogram
ui <- fluidPage(
  
  
  # Application title
  titlePanel("Random distribution generation"),
  
  # Sidebar with a slider input for number of bins 
  sidebarLayout(
    sidebarPanel(
      sliderInput("bins",                        "Number of bins:",
                  min = 1,
                  max = 50,
                  value = 30),
      selectInput("type",label="Select form of distribution",
                  choices=c("normal","uniform")),
      numericInput("number","Number of samples",500,min=100,max=10000,step=100,width='100%'),
      
      
      tags$a("Link to wikipedia",href="http://en.wikipedia.org"),
      tags$p(),
      tags$hr(),
      tags$a( tags$img(src="https://upload.wikimedia.org/wikipedia/en/c/c9/Michigan_Technological_University_logo.svg"),
              href="http://mtu.edu"),
      ),
    
    # Show a plot of the generated distribution
    mainPanel(
      h1("Histograms"),
      plotOutput("distPlot"),
      plotOutput("distPlot2",width=400, height=400),
      actionButton("save","Save table to log file"),
      tableOutput("table"),
      h3("Overview in text:"),
      textOutput("textdesc")
    )
  )
)

server <- function(input, output,session) {
  data <- reactive(
    {
      
      if( input$type=="normal")
      {
        x    <-  rnorm(input$number)  
        updateNumericInput(session,"bins",value=25)
      }else if(input$type=="uniform")
      {
        x    <-  runif(input$number) 
        updateNumericInput(session,"bins",value=10)
      }
      
      x
    }
    
  )
  
  
  
  output$distPlot <- renderPlot({
    x <- data()
    
    # draw the histogram with the specified number of bins
    a <- as.data.frame(x) |> ggplot(aes(x=x)) +geom_histogram(bins=input$bins,fill="orange2",color="black") + theme_bw()
    print(a)
  })
  
  
  
  output$distPlot2 <- renderPlot({
    x <- data()
    # draw the histogram with the specified number of bins
    b <- as.data.frame(x) |> ggplot(aes(sample=x)) + geom_qq() + theme_bw()
    print(b)
  })
  
  
  
  
  
  output$table<- renderTable({
    x <- data()
    as.data.frame(summary(as.data.frame(x)))
  })
  
  output$textdesc <- renderText(
    paste("using ",input$type," distribution with a mean of ", round(mean(data()),3),
          " and standard devation of",round(sd(data()),3),"\n")
  )
  
}



# Run the application 
shinyApp(ui = ui, server = server)