#!/usr/bin/env Rscript

library(shiny)
library(shinyBS)

getwd()
setwd("~/git/LSHTM_analysis/scripts/plotting")
getwd()
source("Header_TT.R")

drug = 'streptomycin'
gene = 'gid'

source("../functions/bp_subcolours.R")
source("get_plotting_dfs.R")

cat(paste0("Variables imported:"
           , "\ndrug:", drug
           , "\ngene:", gene))

# sanity checks
str(df)
#===========================================================
# Define UI for application that draws a histogram
wide_ui <- 
  fillPage(
  #fluidPage(
  #titlePanel("Mtb target: gid"),
  # sidebarLayout(
  #  sidebarPanel(),
    bsTooltip("wide graph", "Really wide graph","right", options = list(container = "body")),
    
    mainPanel(
      plotOutput("widePlot", click = "plot_click", width = "100%"),
#      uiOutput("uiExample")
    verbatimTextOutput("info_pos"),
    tableOutput("info")

      )
  #  )
  )

# Define server logic required to draw a histogram
wide_plot_server <- function(input, output, session) {
  
  output$widePlot <- renderPlot({

    # axis label size
    my_xaxls = 12
    my_yaxls = 20
    
    # axes text size
    my_xaxts = 18
    my_yaxts = 20
    
    #title_ps = "Protein stability (DUET)"
    
    g = ggplot(subcols_df_ps, aes(x = factor(position, ordered = T)))
    g + geom_bar(aes(fill = group), colour = "grey") +
      scale_fill_manual( values = subcols_ps
                         , guide = "none") +
      theme( axis.text.x = element_text(size = my_xaxls
                                        , angle = 90
                                        , hjust = 1
                                        , vjust = 0.4)
             , axis.text.y = element_text(size = my_yaxls 
                                          , angle = 0
                                          , hjust = 1
                                          , vjust = 0)
             , axis.title.x = element_text(size = my_xaxts)
             , axis.title.y = element_text(size = my_yaxts ) ) +
      labs(title = ""
           #title = title_ps
           , x = "Position"
           , y = "Frequency")
}, width = "auto")
  
#output$info_pos <- renderText({paste("Clicked Position", "\nx=", input$plot_click$x, "\ny=", input$plot_click$y)})

#   
# output$info_pos <- renderText({paste("Clicked Position",
#                                      "\nx=",
#                                      #round(as.numeric(input$plot_click$x, digits = 0)),
#                                      ceiling(as.numeric(input$plot_click$x)),
#                                      "\ny=",
#                                      #round(as.numeric(input$plot_click$y, digits = 0))
#                                      ceiling(as.numeric(input$plot_click$y))
#                                      )})

# output$info <-renderTable({
#     nearPoints(
#       subcols_df_ps,
#       input$plot_click,
#       xvar = "position",
#       yvar = "pos_count")
#   })
 
 #output$info <- renderTable(xtable::xtable(subcols_df_ps[]))

#############################################################
# upos <- unique(subcols_df_ps$position)
# upos <- upos[order(upos)]
# x <- ceiling(as.numeric(input$plot_click$x))
# x_mod = upos[x]   

output$info_pos <- renderText({paste("Clicked Position",
                                     "\nx=",
                                     ceiling(as.numeric(input$plot_click$x)),
                                     "\ny=",
                                     ceiling(as.numeric(input$plot_click$y))
)})

  ##magic happens here##
  output$info <- renderTable({
    upos <- unique(subcols_df_ps$position)
    upos <- upos[order(upos)]
    x_pos <- upos[ceiling(as.numeric(input$plot_click$x))]
    subcols_df_ps[subcols_df_ps$position == x_pos,]
  })
  
############################################################
}

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