library(shiny)

display_as_int <- function(input){
    return (format(round(input, 0), nsmall = 0))
}

data <- read.csv("history.csv") #returns a dataframe object
data <- data[order(data$year),] #resort by ascending year

# Define UI for app that draws a histogram ----
ui <- fluidPage(

  # App title ----
  titlePanel("Hello Shiny!"),

  # Sidebar layout with input and output definitions ----
  sidebarLayout(

    # Sidebar panel for inputs ----
    sidebarPanel(

      # Input: Slider for the number of bins ----
      sliderInput(inputId = "starting_sum",
                  label = "Starting Sum in Portfolio:",
                  min   = 100000,
                  max   = 1000000,
                  step  = 25000,
                  value = 100000),
      sliderInput(inputId = "monthly_draw",
                  label = "Monthly Withdrawals:",
                  min   = 0,
                  max   = 10000,
                  step  = 1000,
                  value = 1000),
      sliderInput(inputId = "monthly_increase",
                  label = "Monthly Withdrawals Increase per Year (%):",
                  min   = 0,
                  max   = 10,
                  step  = 1,
                  value = 0),
      sliderInput(inputId = "draw_years",
                  label = "Years of Withdrawal:",
                  min   = 10,
                  max   = 40,
                  step  = 1,
                  value = 10),
      checkboxInput("do_shuffle", 
                  label = "Shuffle Returns", 
                  value = FALSE)
    ),

    # Main panel for displaying outputs ----
    mainPanel(

      # Output: Histogram ----
      plotOutput(outputId = "distPlot"),

      # Output: Text
      verbatimTextOutput("summary_info")

    )
  )
)

# Define server logic required to draw a histogram ----
server <- function(input, output) {
  ret_sum    <- 0
  ret_sq_sum <- 0
  fail_count <- 0
  # Histogram of the Old Faithful Geyser Data ----
  # with requested number of bins
  # This expression that generates a histogram is wrapped in a call
  # to renderPlot to indicate that:
  #
  # 1. It is "reactive" and therefore should be automatically
  #    re-executed when inputs (input$bins) change
  # 2. Its output type is a plot
  output$distPlot <- renderPlot({
    # Init global vars
    ret_sum    <<- 0
    ret_sq_sum <<- 0
    fail_count <<- 0

    #Empty plot
    plot(NULL, xlim=c(0, input$draw_years), ylim=c(-1000000,10000000), 
                      ylab="Portfolio $", xlab="Years")

    #pre assign empty vector
    sum     <- vector(mode="numeric", input$draw_years+1)
    #calculate how many widnows of X years we have in the return dataset
    nsims   <- max(data$year)-min(data$year)-input$draw_years
    #Color palette
    palette <- colorRampPalette(c("white", "#75AADC"))
    palette <- palette(nsims)

    #Simulate
    if (!input$do_shuffle){
        returns <- data$return
    } else {
        returns <- sample(data$return)
    }

    for (isim in seq(1, nsims)) {
        sum[1] <- input$starting_sum
        for (iyear in seq(1, input$draw_years)) {
            sum[iyear+1] <- sum[iyear]
            ret <- returns[0+iyear+isim]
            draw <- input$monthly_draw*(1+input$monthly_increase/100)**(iyear-1)
            for (imonth in seq(1, 12)) {
                sum[iyear+1] <- (sum[iyear+1]-draw)*
                (1.0+ret/100/12)
            }
        }
        #Plot
        years <- seq(0, input$draw_years)
        #Double plotting for outline
        lines(years, sum, col = "black", lwd=3)
        lines(years, sum, col = palette[isim], lwd=2)

        #Store Values
        final <- tail(sum, n=1)
        ret_sum    <<- ret_sum + final #<< makes it so these variables update in other blocks too
        ret_sq_sum <<- ret_sq_sum + final*final
        if (final <=0){
            fail_count <<- fail_count + 1
        }
        lines(years, sum*0, col = "black", lwd=3, lty="dashed")
    }
    output$summary_info <- renderText({
      final_draw <- input$monthly_draw*(1+input$monthly_increase/100)**(input$draw_years)
      nsims <- max(data$year)-min(data$year)-input$draw_years
      avg <- ret_sum/nsims
      sd  <- sqrt((ret_sq_sum/nsims)-(ret_sum/nsims)**2)
      fail_perc <- fail_count/nsims * 100
      paste("Monthly Withdrawals at End of Period ", 
            display_as_int(final_draw), "\n",
            "Average Portfolio Value and SD ", 
            display_as_int(avg/1000), " k ", display_as_int(sd/1000), " k", "\n",
            "Failed Portfolios ", fail_count, " ", display_as_int(fail_perc), "%",
            sep="")
    })
    
  })

}

# Create Shiny app ----
shinyApp(ui = ui, server = server)