clus_explorer: CLUS Explorer

#' page_dashboard_forestry UI Function
#'
#' @description A shiny Module.
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
#' @noRd
#'
#' @importFrom shiny NS tagList
mod_page_dashboard_forestry_ui <- function(id){
  ns <- NS(id)
  tagList(
    tabsetPanel(
      tabPanel(
        "Harvest Flow",
        plotlyOutput(outputId = ns("harvestAreaPlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff'),
        plotlyOutput(outputId = ns("harvestVolumePlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff')
      ),
      tabPanel(
        "Transition Harvest",
        plotlyOutput(outputId = ns("managedAreaPlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff'),
        plotlyOutput(outputId = ns("managedVolumePlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff')
      ),
      tabPanel(
        "Harvest Age",
        plotlyOutput(outputId = ns("harvestAgePlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff')
      ),
      tabPanel(
        "Available THLB",
        plotlyOutput(outputId = ns("availableTHLBPlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff')
      ),
      tabPanel(
        "Growingstock",
        plotlyOutput(outputId = ns("growingStockPlot"), height = "400px") %>%
          withSpinner(color = '#ecf0f5', color.background = '#ffffff')
      )
    )
  )
}

#' page_dashboard_forestry Server Functions
#'
#' @noRd
mod_page_dashboard_forestry_server <- function(id, reportList){
  moduleServer( id, function(input, output, session){
    ns <- session$ns

    if (nrow(reportList()$harvest) > 0) {

      output$harvestAreaPlot <- renderPlotly ({
        withProgress(message = 'Making Plots', value = 0.1, {

          data <-
            reportList()$harvest[, sum(area), by = c("scenario", "timeperiod")]
          data$scenario <-
            reorder(data$scenario, data$V1, function(x)
              - max(x))
          data[, timeperiod := as.integer(timeperiod)]
          p <- ggplot (data, aes (x = timeperiod, y = V1, fill = scenario)) +
            geom_area(position = "identity", aes(alpha = scenario)) +
            xlab ("Future year") +
            ylab ("Area Harvested (ha)") +
            scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
            scale_y_continuous(
              labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
            ) +
            scale_alpha_discrete(range = c(0.4, 0.8)) +
            scale_fill_grey(start = 0.8, end = 0.2) +
            theme_bw()
          ggplotly(p)
        })
      })

      output$harvestAgePlot <- renderPlotly ({
        withProgress(message = 'Making Plots', value = 0.1, {
          data <- reportList()$harvest
          data <-
            data[, lapply(.SD, FUN = weighted.mean, x = age), by = c("scenario", "timeperiod"), .SDcols =
                   'age']
          #data$scenario <- reorder(data$scenario, data$V1, function(x) -max(x) )
          data[, timeperiod := as.integer(timeperiod)]
          p <- ggplot (data, aes (x = timeperiod, y = age, fill = scenario)) +
            geom_area(position = "identity", aes(alpha = scenario)) +
            xlab ("Future year") +
            ylab ("Average Harvest Age (yrs)") +
            scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
            scale_y_continuous(
              labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
            ) +
            scale_alpha_discrete(range = c(0.4, 0.8)) +
            scale_fill_grey(start = 0.8, end = 0.2) +
            theme_bw()
          ggplotly(p)
        })
      })

      output$harvestVolumePlot <- renderPlotly ({
        data <-
          reportList()$harvest[, sum(volume), by = c("scenario", "timeperiod")]
        data$scenario <-
          reorder(data$scenario, data$V1, function(x)
            - max(x))
        data[, timeperiod := as.integer(timeperiod)]
        p <- ggplot (data, aes (x = timeperiod, y = V1, fill = scenario)) +
          geom_area(position = "identity", aes(alpha = scenario)) +
          xlab ("Future year") +
          ylab ("Volume Harvested (m3)") +
          scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
          scale_y_continuous(
            labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
          ) +
          scale_alpha_discrete(range = c(0.4, 0.8)) +
          scale_fill_grey(start = 0.8, end = 0.2) +
          theme_bw()
        ggplotly(p)
      })

      output$managedAreaPlot <- renderPlotly ({
        data <-
          reportList()$harvest[, sum(transition_area), by = c("scenario", "timeperiod")]
        data$scenario <-
          reorder(data$scenario, data$V1, function(x)
            - max(x))
        data[, timeperiod := as.integer(timeperiod)]
        p <- ggplot (data, aes (x = timeperiod, y = V1, fill = scenario)) +
          geom_area(position = "identity", aes(alpha = scenario)) +
          xlab ("Future year") +
          ylab ("Managed Area Harvested (ha)") +
          scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
          scale_y_continuous(
            labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
          ) +
          scale_alpha_discrete(range = c(0.4, 0.8)) +
          scale_fill_grey(start = 0.8, end = 0.2) +
          theme_bw()
        ggplotly(p)
      })

      output$managedVolumePlot <- renderPlotly ({
        data <-
          reportList()$harvest[, sum(transition_volume), by = c("scenario", "timeperiod")]
        data$scenario <-
          reorder(data$scenario, data$V1, function(x)
            - max(x))
        data[, timeperiod := as.integer(timeperiod)]
        p <- ggplot (data, aes (x = timeperiod, y = V1, fill = scenario)) +
          geom_area(position = "identity", aes(alpha = scenario)) +
          xlab ("Future year") +
          ylab ("Managed Volume Harvested (m3)") +
          scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
          scale_y_continuous(
            labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
          ) +
          scale_alpha_discrete(range = c(0.4, 0.8)) +
          scale_fill_grey(start = 0.8, end = 0.2) +
          theme_bw()
        ggplotly(p)
      })

      output$availableTHLBPlot <- renderPlotly ({
        data <-
          reportList()$harvest[, sum(avail_thlb), by = c("scenario", "timeperiod")]
        data$scenario <-
          reorder(data$scenario, data$V1, function(x)
            - max(x))
        data[, timeperiod := as.integer(timeperiod)]
        p <- ggplot (data, aes (x = timeperiod, y = V1, fill = scenario)) +
          geom_area(position = "identity", aes(alpha = scenario)) +
          xlab ("Future year") +
          ylab ("Available THLB (ha)") +
          scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
          scale_y_continuous(
            labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
          ) +
          scale_alpha_discrete(range = c(0.4, 0.8)) +
          scale_fill_grey(start = 0.8, end = 0.2) +
          theme_bw()
        ggplotly(p)
      })
    }

    if (nrow(reportList()$growingstock) > 0) {
      output$growingStockPlot <- renderPlotly ({
        data <- reportList()$growingstock
        data$scenario <-
          reorder(data$scenario, data$growingstock, function(x)
            - max(x))
        p <-
          ggplot(data, aes (x = timeperiod, y = growingstock, fill = scenario)) +
          geom_area(position = "identity", aes(alpha = scenario)) +
          xlab ("Future year") +
          ylab ("Growing Stock (m3)") +
          scale_x_continuous(breaks = seq(0, max(data$timeperiod), by = 10)) +
          scale_y_continuous(
            labels = scales::comma_format(big.mark = ",", decimal.mark = ".")
          ) +
          scale_alpha_discrete(range = c(0.4, 0.8)) +
          scale_fill_grey(start = 0.8, end = 0.2) +
          theme_bw()
        ggplotly(p)
      })
    }

  })
}