## ui.R ##
library(shinydashboard)

dashboardPage(
  dashboardHeader(),
  dashboardSidebar(),
  dashboardBody()
)


## app.R ##
library(shiny)
library(shinydashboard)
library(bubbles)
library(dplyr)
library(sunburstR)
library(rvest)
library(stringr)
library(tidyr)
library(networkD3)
library(TraMineR)
library(sunburstR)
library(pipeR)

# Define UI
ui <- dashboardPage(skin="blue",
  dashboardHeader(title = tags$a(href='http://sailpoint.com',
        tags$img(src='sailpoint-logo-wh.png', height=35, width=135))),

  ## Sidebar content
  dashboardSidebar(
    sidebarMenu(
      menuItem("Bubble plot", tabName = "bubble", icon = icon("group")),
      menuItem("Sunburst plot", tabName = "sunburst", icon = icon("sun-o")),
      menuItem("Sankey plot", tabName = "plot", icon = icon("tasks"))
    )
  ),

  ## Body content
  dashboardBody(
    tabItems(
      # First tab content
      tabItem(tabName = "bubble",
              fluidRow(
                box(
                  width = 12, status = "info", solidHeader = TRUE,
                  title = "Peer groups by size",
                  bubblesOutput("bubble", width = "100%", height = 600)
                  #plotOutput("bubble_plot", width = "100%", height = 600)
                )
              ),
              fluidRow(
                column(
                  width = 12,
                  offset = 4,
                  box(
                    width = 4, status = "warning", solidHeader = TRUE,
                    height = 200,
                    title = "Number of clusters",
                    sliderInput("slider_bubble", "", 2, 20, 1)
                  )
                )
              )
      ),

      # Second tab content
      tabItem(tabName = "sunburst",
              fluidRow(
                box(
                  width = 12, status = "info", solidHeader = TRUE,
                  title = "School-to-work transition in Northern Ireland",
                  sunburstOutput("sunburst", width = "100%", height = 800)
                )
              )
      ),

      # Third tab content
      tabItem(tabName = "plot",
              fluidRow(
                box(
                  width = 12,
                  status = "info", solidHeader = TRUE,
                  title = "Energy consumption",
                  plotOutput("plot", width = "100%", height = 800)
                )
              )
      )
    )
  )
)

# Server logic
server <- function(input, output, session){
  # output$input <- renderUI({})
  # outputOptions(output, "input", suspendWhenHidden = FALSE)
  # Bubble plot
  output$bubble <- renderBubbles({
      bubbles(value = sqrt(exp(seq(0, as.integer(input$slider_bubble) - 1, by=1))),
            label = letters[1:as.integer(input$slider_bubble)],
            color = paste0("#", lapply(1:as.integer(input$slider_bubble), function(i) paste0(sample(c(0:9,toupper(letters[1:6])), 6 , replace = T),collapse = ''))) %>% unlist())
  })

  # Sunburst plot
  output$sunburst <- renderSunburst({
    # use example from TraMineR vignette
    # data("mvad")
    # mvad.alphab <- c(
    #   "employment", "FE", "HE", "joblessness",
    #   "school", "training"
    # )
    # mvad.seq <- seqdef(mvad, 17:86, xtstep = 6, alphabet = mvad.alphab)
    #
    # # to make this work, we'll compress the sequences with seqdss
    # #   could also aggregate with dply later
    # seqtab( seqdss(mvad.seq), tlim = 0, format = "SPS" ) %>>%
    #   attr("freq") %>>%
    #   (
    #     data.frame(
    #       # appending "-end" is necessary for this to work
    #       sequence = paste0(
    #         gsub(
    #           x = names(.$Freq)
    #           , pattern = "(/[0-9]*)"
    #           , replacement = ""
    #           , perl = T
    #         )
    #         ,"-end"
    #       )
    #       ,freq = as.numeric(.$Freq)
    #       ,stringsAsFactors = FALSE
    #     )
    #   ) %>>%
       sunburst(readRDS("/Users/mohamed.badawy/projects/IAI_exploration/Shiny/sunburst_df.rds"))
  })

  # Sankey plot
  output$sankey <- renderSankeyNetwork({
    # Load energy projection data
    URL <- "https://cdn.rawgit.com/christophergandrud/networkD3/master/JSONdata/energy.json"
    Energy <- jsonlite::fromJSON(URL)

    # Now we have 2 data frames: a 'links' data frame with 3 columns (from, to, value), and a 'nodes' data frame that gives the name of each node.
    #head( Energy$links )
    #head( Energy$nodes )

    # Thus we can plot it
    sankeyNetwork(Links = Energy$links, Nodes = Energy$nodes, Source = "source",
                  Target = "target", Value = "value", NodeID = "name",
                  units = "TWh", fontSize = 12, nodeWidth = 30)
  })

  # test plot
  output$plot <- renderPlot({hist(rnorm(1000))})
}


shinyApp(ui, server)

## app.R ##
library(shiny)
library(shinydashboard)
library(bubbles)
library(dplyr)
library(sunburstR)
library(rvest)
library(stringr)
library(tidyr)
library(networkD3)
library(TraMineR)
library(sunburstR)
library(pipeR)

# Define UI
ui <- dashboardPage(skin="blue",
  dashboardHeader(title = tags$a(href='http://sailpoint.com',
        tags$img(src='sailpoint-logo-wh.png', height=35, width=135))),

  ## Sidebar content
  dashboardSidebar(
    sidebarMenu(
      menuItem("Bubble plot", tabName = "bubble", icon = icon("group")),
      menuItem("Sunburst plot", tabName = "sunburst", icon = icon("sun-o")),
      menuItem("Sankey plot", tabName = "sankey", icon = icon("tasks"))
    )
  ),

  ## Body content
  dashboardBody(
    tabItems(
      # First tab content
      tabItem(tabName = "bubble",
              fluidRow(
                box(
                  width = 12, status = "info", solidHeader = TRUE,
                  title = "Peer groups by size",
                  bubblesOutput("bubble", width = "100%", height = 600)
                  #plotOutput("bubble_plot", width = "100%", height = 600)
                )
              ),
              fluidRow(
                column(
                  width = 12,
                  offset = 4,
                  box(
                    width = 4, status = "warning", solidHeader = TRUE,
                    height = 200,
                    title = "Number of clusters",
                    sliderInput("slider_bubble", "", 2, 20, 1)
                  )
                )
              )
      ),

      # Second tab content
      tabItem(tabName = "sunburst",
              fluidRow(
                box(
                  width = 12, status = "info", solidHeader = TRUE,
                  title = "School-to-work transition in Northern Ireland",
                  sunburstOutput("sunburst", width = "100%", height = 800)
                )
              )
      ),

      # Third tab content
      tabItem(tabName = "sankey",
              fluidRow(
                box(
                  width = 12,
                  status = "info", solidHeader = TRUE,
                  title = "Energy consumption",
                  sankeyNetworkOutput("sankey", width = "100%", height = 800)
                )
              )
      )
    )
  )
)

# Server logic
server <- function(input, output, session){
  # output$input <- renderUI({})
  # outputOptions(output, "input", suspendWhenHidden = FALSE)
  # Bubble plot
  output$bubble <- renderBubbles({
      bubbles(value = sqrt(exp(seq(0, as.integer(input$slider_bubble) - 1, by=1))),
            label = letters[1:as.integer(input$slider_bubble)],
            color = paste0("#", lapply(1:as.integer(input$slider_bubble), function(i) paste0(sample(c(0:9,toupper(letters[1:6])), 6 , replace = T),collapse = ''))) %>% unlist())
  })

  # Sunburst plot
  output$sunburst <- renderSunburst({
    # use example from TraMineR vignette
    # data("mvad")
    # mvad.alphab <- c(
    #   "employment", "FE", "HE", "joblessness",
    #   "school", "training"
    # )
    # mvad.seq <- seqdef(mvad, 17:86, xtstep = 6, alphabet = mvad.alphab)
    #
    # # to make this work, we'll compress the sequences with seqdss
    # #   could also aggregate with dply later
    # seqtab( seqdss(mvad.seq), tlim = 0, format = "SPS" ) %>>%
    #   attr("freq") %>>%
    #   (
    #     data.frame(
    #       # appending "-end" is necessary for this to work
    #       sequence = paste0(
    #         gsub(
    #           x = names(.$Freq)
    #           , pattern = "(/[0-9]*)"
    #           , replacement = ""
    #           , perl = T
    #         )
    #         ,"-end"
    #       )
    #       ,freq = as.numeric(.$Freq)
    #       ,stringsAsFactors = FALSE
    #     )
    #   ) %>>%
       sunburst(readRDS("/Users/mohamed.badawy/projects/IAI_exploration/Shiny/sunburst_df.rds"))
  })

  # Sankey plot
  output$sankey <- renderSankeyNetwork({
    # Load energy projection data
    URL <- "https://cdn.rawgit.com/christophergandrud/networkD3/master/JSONdata/energy.json"
    Energy <- jsonlite::fromJSON(URL)

    # Now we have 2 data frames: a 'links' data frame with 3 columns (from, to, value), and a 'nodes' data frame that gives the name of each node.
    #head( Energy$links )
    #head( Energy$nodes )

    # Thus we can plot it
    sankeyNetwork(Links = Energy$links, Nodes = Energy$nodes, Source = "source",
                  Target = "target", Value = "value", NodeID = "name",
                  units = "TWh", fontSize = 12, nodeWidth = 30)
  })
  }

shinyApp(ui, server)