#
# 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/
#

library("shiny")
library("deSolve")
library("cowplot")
library("ggplot2")
library("tidyverse")
library("ggrepel")
#library("highcharter")
library("shinydashboard")

## Create an SIR function
sir <- function(time, state, parameters) {
  with(as.list(c(state, parameters)), {
    dS <- -beta * S * I
    dI <-  beta * S * I - gamma * I
    dR <-                 gamma * I
    dV <- 0
    return(list(c(dS, dI, dR, dV)))
  })
}

# Define UI for application that draws a histogram
ui <- dashboardPage(
  dashboardHeader(disable = TRUE),
  dashboardSidebar(
    sliderInput(
      "connum",
      "Basic reproductive number (R0, antal personer):",
      min = .5,
      max = 20,
      value = 5
    ),
    sliderInput(
      "pinf",
      "Antal inficerede ved start:",
      min = 1,
      max = 50,
      value = 2
    ),
    sliderInput(
      "pvac",
      "Andel vaccinerede + tidligere immune (%):",
      min = 0,
      max = 100,
      value = 75
    ),
    sliderInput(
      "vaceff",
      "Vaccineeffektivitet (%):",
      min = 0,
      max = 100,
      value = 85
    ),
    sliderInput(
      "infper",
      "Infektionsperiode (dage):",
      min = 1,
      max = 30,
      value = 7
    ),
    sliderInput(
      "timeframe",
      "Tidsperiode (dage):",
      min = 1,
      max = 400,
      value = 200
    )
    
  ),
  dashboardBody(
    tags$head(tags$style(HTML('
                              /* main sidebar 
                              .skin-blue .main-sidebar {
                              background-color: #808080;
                              } */

                              /* body */
                              .content-wrapper, .right-side {
                              background-color: #fffff8;
                              }
                              
                              '))),
        
    #    mainPanel(
    fluidRow(plotOutput("distPlot")),
    br(),
    fluidRow(
      # Dynamic valueBoxes
      valueBoxOutput("progressBox", width = 6),
      valueBoxOutput("approvalBox", width = 6),
      valueBoxOutput("BRRBox", width = 6),
      valueBoxOutput("HIBox", width = 6)
      
    ),
    br(),
    br()
  )
  #  )
)

# Define server logic required to draw a histogram
server <- function(input, output) {
  # Create reactive input
  popsize <- 5700000
  dataInput <- reactive({
    init       <-
      c(
        S = 1 - input$pinf / popsize - input$pvac / 100 * input$vaceff / 100,
        I = input$pinf / popsize,
        R = 0,
        V = input$pvac / 100 * input$vaceff / 100
      )
    ## beta: infection parameter; gamma: recovery parameter
    parameters <-
      c(beta = input$connum * 1 / input$infper,
        # * (1 - input$pvac/100*input$vaceff/100),
        gamma = 1 / input$infper)
    ## Time frame
    times      <- seq(0, input$timeframe, by = .2)
    
    ## Solve using ode (General Solver for Ordinary Differential Equations)
    out <-
      ode(
        y = init,
        times = times,
        func = sir,
        parms = parameters
      )
    
    #    out
    as.data.frame(out)
  })
  
  output$distPlot <- renderPlot({
    out <-
      dataInput() %>%
      gather(key, value, -time) %>%
      mutate(
        id = row_number(),
        key2 = recode(
          key,
          S = "Modtagelige (S)",
          I = "Inficerede (I)",
          R = "Sygdomsramte (R)",
          V = "Vaccinerede + tidligere immune"
        ),
        keyleft = recode(
          key,
          S = "Modtagelige (S)",
          I = "",
          R = "",
          V = "Vaccinerede + tidligere immune"
        ),
        keyright = recode(
          key,
          S = "",
          I = "Inficerede (I)",
          R = "Sygdomsramte (R)",
          V = ""
        )
      )
    
    ggplot(data = out,
           aes(
             x = time,
             y = value,
             group = key2,
             col = key2,
             label = key2,
             data_id = id
           )) + # ylim(0, 1) +
      ylab("Procent af hele befolkningen") + xlab("Tid (dage)") +
      geom_line(size = 2) +
      geom_text_repel(
        data = subset(out, time == max(time)),
        aes(label = keyright),
        size = 6,
        segment.size  = 0.2,
        segment.color = "grey50",
        nudge_x = 0,
        hjust = 1,
        direction = "y"
      ) +
      geom_text_repel(
        data = subset(out, time == min(time)),
        aes(label = keyleft),
        size = 6,
        segment.size  = 0.2,
        segment.color = "grey50",
        nudge_x = 0,
        hjust = 0,
        direction = "y"
      ) +
      theme(legend.position = "none") +
      scale_colour_manual(values = c("red", "green4", "black", "blue")) +
      scale_y_continuous(labels = scales::percent, limits = c(0, 1)) +
      theme(
        rect=element_rect(size=0),
        legend.position="none",
        panel.background=element_rect(fill="transparent", colour=NA),
        plot.background=element_rect(fill="transparent", colour=NA),
        legend.key = element_rect(fill = "transparent", colour = "transparent")
      )
    
  })
  
  output$progressBox <- renderValueBox({
    valueBox(
      dataInput() %>% filter(time == max(time)) %>% select(R) %>% mutate(R = round(100 *
                                                                                     R, 2)) %>% paste0("%"),
      "Andel af hele populationen ramt af sygdommen",
      icon = icon("thumbs-up", lib = "glyphicon"),
      color = "black"
    )
  })
  
  output$approvalBox <- renderValueBox({
    valueBox(
      paste0(round(
        100 * (
          dataInput() %>% filter(row_number() == n()) %>% mutate(res = (R + I) / (S + I + R)) %>% pull("res")
        ), 2
      ), "%"),
      "Andel af de modtagelige, der bliver ramt af sygdommen",
      icon = icon("thermometer-full"),
      color = "black"
    )
  })
  
  
  # Mangler af gange med N
  output$BRRBox <- renderValueBox({
    valueBox(
      paste0(round(input$connum *
                     ((1 - input$pvac / 100 * input$vaceff / 100)
                     )
                   , 2), ""),
      "Effektiv R0 (for populationen ved udbrudsstart, når immune er taget i betragtning)",
      icon = icon("arrows-alt"),
      color = "red"
    )
  })
  
  # Mangler af gange med N
  output$HIBox <- renderValueBox({
    valueBox(
      paste0(round(100 * (
        1 -
          1 / (input$connum)
      ), 2), "%"),
      "Andel af befolkningen, der skal være immune for at opnå flokimmunitet ved udbrudsstart",
      icon = icon("medkit"),
      color = "blue"
    )
  })
  
}

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