#_____________________________________________________________________________________________________________________________
# load packages
library(data.table)
library(magrittr)
library(r4ss)

#_____________________________________________________________________________________________________________________________
# define paths
    proj_dir = this.path::this.proj()
    dir_model = paste0(proj_dir,"/stock-synthesis-models/")

#_____________________________________________________________________________________________________________________________
# get a vector of directories for models that have produced stock synthesis output
    all_dirs = list.files(dir_model,recursive = TRUE)
    # only keep model directories that contain a Report.sso file
    all_dirs = all_dirs[grep("/Report.sso",all_dirs,fixed=TRUE)]
    all_dirs = gsub("Report.sso","",all_dirs,fixed=TRUE)

#_____________________________________________________________________________________________________________________________
# extract output from models
  output = SSgetoutput(dirvec=paste0(dir_model,all_dirs))
  names(output) = gsub("/","",all_dirs)

  # since we ran models with different steepness values lets get the steepness value that corresponds to each model
  model_steepness = sapply(output,function(x)x[["parameters"]]["SR_BH_steep","Value"])

  # we want to build a shiny app that shows the stock recruit curve for each model so we will need to extract the corresponding data
  # expected stock recruit relationship (srr)
  expected_srr_dt.list = as.list(rep(NA,length(all_dirs)))
  for(i in seq_along(expected_srr_dt.list)){
    expected_srr_dt.list[[i]] = as.data.table(output[[i]]$SPAWN_RECR_CURVE) %>%
                       .[,model_name:=names(output[i])] %>%
                       .[,.(model_name,SSB,Recruitment)] %>%
                       setnames(.,c("SSB","Recruitment"),c("ssb","rec_actual"))
  }
  expected_srr_dt = rbindlist(expected_srr_dt.list)
  fwrite(expected_srr_dt,file=paste0(proj_dir,"shiny/shiny-data/expected_srr.csv"))

  # annual estimated recruitments and corresponding spawning biomass
  est_recruit_dt.list = as.list(rep(NA,length(all_dirs)))
  for(i in seq_along(est_recruit_dt.list)){
    est_recruit_dt.list[[i]] = as.data.table(output[[i]]$recruit) %>%
                       .[,model_name:=names(output[i])] %>%
                       .[era=="Main"] %>%
                       .[,.(model_name,Yr,SpawnBio,pred_recr)] %>%
                       setnames(.,c("Yr","SpawnBio","pred_recr"),c("yr","ssb","rec_estimated"))
  }
  est_recruit_dt = rbindlist(est_recruit_dt.list)
  fwrite(est_recruit_dt,file=paste0(proj_dir,"shiny/shiny-data/est_recruit.csv"))
  
#_____________________________________________________________________________________________________________________________
# make summary files to run the shiny app from
  summary_dt = data.table(model_name=names(output),steepness=model_steepness)
  fwrite(summary_dt,file=paste0(proj_dir,"shiny/shiny-data/summary.csv"))

library(shinydashboard)
library(shinyWidgets)

css <- htmltools::HTML(
    "#summarytable > .dataTables_wrapper.no-footer > .dataTables_scroll > .dataTables_scrollBody {
        transform:rotateX(180deg);
    }
    #summarytable > .dataTables_wrapper.no-footer > .dataTables_scroll > .dataTables_scrollBody table{
        transform:rotateX(180deg);
    }"
)

ui = shinydashboard::dashboardPage(
  header = shinydashboard::dashboardHeader(title="Shiny demo"),
  sidebar = shinydashboard::dashboardSidebar(
    br(),
    br(),
    sidebarMenu(id="sidebarmenu",
      menuItem("Introduction", tabName="introduction"),
      menuItem("Summary table", tabName="table"),
      menuItem("Stock-recruit relationship (SRR)", tabName="srr_plots")
    ),

    # Only show these on the plotting tabs - not Introduction and Summary table tabs
    conditionalPanel(condition="input.sidebarmenu == 'srr_plots'",
      # srr-show-est
      switchInput(
      inputId = "srr_show_est",  
      label = "Show estimated recruitment",
      value=TRUE,
      onLabel = "TRUE",
      offLabel = "FALSE",
      onStatus = "success", 
      offStatus = "danger"),
      # srr-est-type
      awesomeRadio(
      inputId = "srr_est_type",  
      label = "Plot estimated recruitment as:",
      choices=c("Path","Points","Both"),
      selected = "Path")
    ),
    br(),
    br(),
    tags$footer(
      div(style="text-align:center",
        tags$p("version 0.0.1"),
        tags$p(paste("Copyright", format(Sys.time(),"%Y"), "NOAA Fisheries, PIFSC Stock Assessment Group"))
      )
    )
  ), # End of sidebar

  body = shinydashboard::dashboardBody(
    tags$head(tags$style(HTML('.wrapper {height: auto !important; position:relative; overflow-x:hidden; overflow-y:hidden}') )),
    tags$head(tags$style(css)),
    # Start of main tab stuff
    tabItems(
      # **** Introduction ****
      tabItem(tabName="introduction", h2("Introduction"),
        fluidRow(column(12, includeMarkdown("./introduction_index.md")))
      ), # End of introduction tab

      # **** Summary table ****
      tabItem(tabName="table", h2("Summary table"),
        fluidRow(box(title="Model metrics", collapsed=FALSE, solidHeader=TRUE, collapsible=TRUE, status="primary", width=12,
         DT::dataTableOutput("summarytable")))
      ), # End of table tab

      # **** Stock recruitment plots ****
      tabItem(tabName="srr_plots", h2("Stock-recruitment plots"),
        fluidRow(
          box(title="Stock-recruitment relationship (SRR)", solidHeader=TRUE, collapsible=TRUE, collapsed=FALSE, status="primary", width=12,
            p("Select at least one model."),
            plotOutput("srr_plots", height="auto"))
        )
      ) # End of srr_plots tab
    ) # End of tabItems
  ) # End of dashboardBody
)

library(data.table)
library(magrittr)
library(ggplot2)
library(viridis)

server = function(input, output){
  # pixel height for each panel. i.e row height when plotting by species
  height_per_panel = 350

  # load data needed for shiny app
    summary_dt = fread(file="./shiny-data/summary.csv")

  ref_table_reduced = summary_dt %>%
                as.data.frame(.)

  output$summarytable = DT::renderDataTable({
    summary_df = summary_dt %>%
                 as.data.frame(.,stringsAsFactors=FALSE)
    summary_DT = DT::datatable(summary_df, filter = 'top',rownames=FALSE,
    options = list(scrollX = TRUE, search = list(regex = TRUE, caseInsensitive = FALSE),pageLength = 25))
    return(summary_DT)
  })
  outputOptions(output, "summarytable", suspendWhenHidden = FALSE)

  filtered_id = reactive({
    req(input$summarytable_rows_selected)
    keep_models = c(ref_table_reduced[input$summarytable_rows_selected, ]$model_name)
    return(keep_models)  
  })

  # define plots
  output$srr_plots = renderPlot({
    input_models = unique(filtered_id())
    if(length(input_models) < 1 ){
      return(warning("Please select at least one model."))
    }

    expected_srr_dt = fread(file="./shiny-data/expected_srr.csv") %>%
                      .[model_name %in% input_models]
    est_recruit_dt = fread(file="./shiny-data/est_recruit.csv") %>%
                      .[model_name %in% input_models]

    p = expected_srr_dt %>%
      ggplot() +
            ylim(0,NA) +
            xlab("Spawning biomass (SSB)") +
            ylab("Recruitment") +
            geom_path(aes(x=ssb,y=rec_actual,group=model_name,color=model_name),linewidth=1.5)

      if(input$srr_show_est == "TRUE")
      {
        if(input$srr_est_type == "Path"){
            p = p + geom_line(data=est_recruit_dt,aes(x=ssb,y=rec_estimated,group=model_name,color=model_name),alpha=0.5)
        } else if(input$srr_est_type == "Points"){
            p = p + geom_point(data=est_recruit_dt,aes(x=ssb,y=rec_estimated,group=model_name,fill=model_name),shape=21,cex=3)
        } else {
            p = p + geom_line(data=est_recruit_dt,aes(x=ssb,y=rec_estimated,group=model_name,color=model_name),alpha=0.5)
            p = p + geom_point(data=est_recruit_dt,aes(x=ssb,y=rec_estimated,group=model_name,fill=model_name),shape=21,cex=3)
        }
      }
      
    
      p = p + viridis::scale_color_viridis("Model",begin = 0.1,end = 0.8,direction = 1,option = "H",discrete=TRUE) +
            viridis::scale_fill_viridis("Model",begin = 0.1,end = 0.8,direction = 1,option = "H",discrete=TRUE) +
            theme(panel.background = element_rect(fill = "white", color = "black", linetype = "solid"),
                            panel.grid.major = element_line(color = 'gray70',linetype = "dotted"), 
                            panel.grid.minor = element_line(color = 'gray70',linetype = "dotted"),
                            strip.background =element_rect(fill="white"),
                            legend.key = element_rect(fill = "white"))
            
    return(p)
  },
  height=function(){
    return((height_per_panel*1.5))
  })
}