R/smart_plots.R

In d-lorenz/smartR: Spatial Management and Assessment of Demersal Resources for Trawl Fisheries

# SmartR Plots ----

## Pre-Sim - Production Index x Year Boxplot ----
ggplot_prodIndBoxplot <- function(df_ProdInde) {
  return(
    suppressMessages(
      ggplot(
        df_ProdInde,
        aes_(
          x = ~Year, y = ~Production,
          group = ~Year
        )
      ) +
        geom_boxplot() +
        geom_jitter(
          data = df_ProdInde,
          aes_(
            x = ~Year, y = ~Production,
            group = ~Year,
            color = ~Year
          ),
          size = 1, shape = 19, alpha = 0.25,
          height = 0, width = 0.25
        ) +
        ggtitle("Production Index") +
        ylab("Index Value") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Pre-Sim - Effort Index x Year Boxplot ----
ggplot_effoIndBoxplot <- function(df_EffoInde) {
  return(
    suppressMessages(
      ggplot(
        df_EffoInde,
        aes_(
          x = ~Year, y = ~EffInd,
          group = ~Year
        )
      ) +
        geom_boxplot() +
        geom_jitter(
          data = df_EffoInde,
          aes_(
            x = ~Year, y = ~EffInd,
            group = ~Year,
            color = ~Year
          ),
          size = 1, shape = 19, alpha = 0.25,
          height = 0, width = 0.25
        ) +
        ggtitle("Effort Index") +
        ylab("Index Value") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Pre-Sim - Days at Sea x Year Boxplot ----
ggplot_seaDaysBoxplot <- function(df_seaDays) {
  return(
    suppressMessages(
      ggplot(
        df_seaDays,
        aes_(
          x = ~Year, y = ~Freq,
          group = ~Year
        )
      ) +
        geom_boxplot() +
        geom_jitter(
          data = df_seaDays,
          aes_(
            x = ~Year, y = ~Freq,
            group = ~Year,
            color = ~Year
          ),
          size = 1, shape = 19, alpha = 0.25,
          height = 0, width = 0.25
        ) +
        ggtitle("Days at Sea") +
        ylab("Index Value") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}


## Economy - Spatial Regression scatter plot ----
ggplot_spatialRegression <- function(df_spatialIn, reg_spatialOut) {
  df_spatialIn$Response <- df_spatialIn$EffInd * reg_spatialOut$coefficients[1] + df_spatialIn$Loa * reg_spatialOut$coefficients[2]
  return(
    suppressMessages(
      ggplot(df_spatialIn, aes_(x = ~Response, y = ~SpatialCost)) +
        geom_point() +
        stat_smooth(method = "lm", col = "Firebrick") +
        ggtitle("Spatial Based Cost Regression") +
        scale_x_continuous("Spatial Index", breaks = pretty(df_spatialIn$Response, 4)) +
        scale_y_continuous("Spatial Cost", breaks = pretty(df_spatialIn$SpatialCost, 10)) +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}


## Economy - Effort Regression scatter plot ----
ggplot_effortRegression <- function(df_effortIn, reg_effortOut) {
  df_effortIn$Response <- reg_effortOut$coefficients[1] * df_effortIn$Freq + reg_effortOut$coefficients[2] * df_effortIn$Loa + reg_effortOut$coefficients[3] * df_effortIn$Kw
  return(
    suppressMessages(
      ggplot(df_effortIn, aes_(x = ~Response, y = ~EffortCost)) +
        geom_point() +
        stat_smooth(method = "lm", col = "Firebrick") +
        ggtitle("Effort Based Cost Regression") +
        scale_x_continuous("Effort Index", breaks = pretty(df_effortIn$Response, 4)) +
        scale_y_continuous("Effort Cost", breaks = pretty(df_effortIn$EffortCost, 10)) +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}


## Economy - Production Regression scatter plot ----
ggplot_productionRegression <- function(df_productionIn, reg_productionOut) {
  df_productionIn$Response <- reg_productionOut$coefficients[1] * df_productionIn$Production
  return(
    suppressMessages(
      ggplot(df_productionIn, aes_(x = ~Response, y = ~ProductionCost)) +
        geom_point() +
        stat_smooth(method = "lm", col = "Firebrick") +
        ggtitle("Production Based Cost Regression") +
        scale_x_continuous("Production Index", breaks = pretty(df_productionIn$Response, 4)) +
        scale_y_continuous("", breaks = pretty(df_productionIn$ProductionCost, 10)) +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 18),
          axis.text.x = element_text(size = 10),
          axis.title.x = element_text(size = 12),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 12),
          axis.ticks.y = element_blank()
        )
    )
  )
}


## Production - Betas x FG Boxplot ----
ggplot_betasBoxplot <- function(df_YearFGprod, int_hline) {
  return(
    suppressMessages(
      ggplot(
        df_YearFGprod,
        aes_(
          x = ~FishGround, y = ~Productivity,
          group = ~FishGround
        )
      ) +
        geom_boxplot() +
        geom_jitter(
          data = df_YearFGprod,
          aes_(
            x = ~FishGround, y = ~Productivity,
            # fill = ~Productivity,
            group = ~FishGround,
            color = ~Year
          ),
          size = 2, shape = 19, alpha = 0.6,
          height = 0
        ) +
        geom_hline(yintercept = int_hline, color = "firebrick", linetype = "dashed") +
        theme_tufte(base_size = 14, ticks = F) +
        xlab("Fishing Ground") +
        theme(legend.position = "right")
    )
  )
}

## Fleet Register - Plot Dispatch ----
ggplot_registerDispatch <- function(curRegister, selPlot) {
  suppressWarnings(
    switch(selPlot,
           "Summary" = grid.arrange(ggplot_registerMainGear(df_Register = curRegister),
                                    ggplot_registerSecGear(df_Register = curRegister),
                                    ggplot_registerHullMaterial(df_Register = curRegister[!is.na(curRegister$Hull.Material), ]),
                                    ggplot_registerConstYear(df_Register = curRegister),
                                    ggplot_registerLoa(df_Register = curRegister),
                                    ggplot_registerMainPower(df_Register = curRegister),
                                    layout_matrix = rbind(c(1, 2, 3), c(4, 5, 6))
           ),
           "Main Gear" = print(ggplot_registerMainGear(df_Register = curRegister)),
           "Secondary Gear" = print(ggplot_registerSecGear(df_Register = curRegister)),
           "Hull Material" = print(ggplot_registerHullMaterial(df_Register = curRegister[!is.na(curRegister$Hull.Material), ])),
           "Construction Year" = print(ggplot_registerConstYear(df_Register = curRegister)),
           "Length Over All" = print(ggplot_registerLoa(df_Register = curRegister)),
           "Main Power" = print(ggplot_registerMainPower(df_Register = curRegister))
    )
  )
}


## Fleet Register - Main Gear ----
ggplot_registerMainGear <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_bar(
          data = df_Register,
          mapping = aes_(~Gear.Main.Code)
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        ggtitle("Main Gear") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 8, angle = 90),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Fleet Register - Secondary Gear ----
ggplot_registerSecGear <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_bar(
          data = df_Register,
          mapping = aes_(~Gear.Sec.Code)
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        ggtitle("Secondary Gear") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 8, angle = 90),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Fleet Register - Hull Material ----
ggplot_registerHullMaterial <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_bar(
          data = df_Register,
          mapping = aes_(~factor(Hull.Material,
                                 levels = c(1, 2, 3, 4, 5),
                                 labels = c("Wood", "Metal", "Plastic", "Other", "Unknown")
          ))
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        ggtitle("Hull Material") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 10, angle = 90),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Fleet Register - Construction Year ----
ggplot_registerConstYear <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_histogram(
          data = df_Register,
          mapping = aes_(~Construction.Year),
          bins = 100
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        scale_x_continuous(
          breaks = pretty(df_Register$Construction.Year),
          limits = range(pretty(df_Register$Construction.Year))
        ) +
        ggtitle("Construction Year") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 8),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Fleet Register - Length Over All ----
ggplot_registerLoa <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_histogram(
          data = df_Register,
          mapping = aes_(~Loa),
          bins = 100
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        scale_x_continuous(
          breaks = pretty(df_Register$Loa),
          limits = range(pretty(df_Register$Loa))
        ) +
        ggtitle("Length Over All") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 8),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Fleet Register - Main Engine Power ----
ggplot_registerMainPower <- function(df_Register) {
  return(
    suppressMessages(
      ggplot() +
        geom_histogram(
          data = df_Register,
          mapping = aes_(~Power.Main),
          bins = 100
        ) +
        theme_tufte(base_size = 14, ticks = F) +
        scale_x_continuous(
          breaks = pretty(df_Register$Power.Main),
          limits = range(pretty(df_Register$Power.Main))
        ) +
        ggtitle("Main Engine Power (Kw)") +
        theme(
          legend.position = "none",
          plot.title = element_text(size = 14),
          axis.text.x = element_text(size = 8),
          axis.title = element_blank(),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Production Total path ----
ggplot_TotalProduction <- function(df_Prod) {
  return(
    suppressMessages(
      ggplot() +
        geom_line(data = df_Prod, mapping = aes_(x = ~Year, y = ~Production)) +
        ylab("Kilogram") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          axis.text.x = element_text(size = 10),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        )
    )
  )
}

## Production by Fishing Ground path ----
ggplot_FGProduction <- function(df_FGProd) {
  return(
    suppressMessages(
      ggplot() +
        geom_line(
          data = df_FGProd,
          mapping = aes_(
            x = ~Year, y = ~Production,
            color = ~FishGround, group = ~FishGround
          )
        ) +
        ylab("Kilogram") +
        theme_tufte(base_size = 14, ticks = F) +
        scale_color_manual(values = colorRampPalette(brewer.pal(8, "Accent"))(length(unique(df_FGProd$FishGround)))) +
        theme(
          legend.position = "bottom",
          axis.text.x = element_text(size = 10),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.y = element_text(size = 10),
          axis.ticks.y = element_blank()
        ) +
        labs(color = "Fishing Ground")
    )
  )
}

## MCMC Survivors * quarter ----
set_ggSurvLine <- function(df_surv) {
  tmpPlot <- suppressMessages(
    ggplot(data = df_surv, aes_(x = ~Catch, y = ~Qty, group = ~Birth, color = ~Birth)) +
      geom_line() +
      scale_x_discrete(drop = FALSE) +
      theme_tufte(base_size = 14, ticks = F) +
      annotate("text", x = Inf, y = Inf, hjust = 1, vjust = 1, family = "serif", label = "Survivors") +
      theme(
        legend.position = "none",
        axis.text.x = element_text(size = 5, angle = 90),
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 5),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      )
  )
  if (length(unique(df_surv$Birth)) <= 12) {
    tmpPlot <- tmpPlot + scale_color_brewer(palette = "Paired")
  } else {
    outPal <- rainbow(length(unique(df_surv$Birth)))
    tmpPlot <- tmpPlot + scale_colour_manual(values = outPal)
  }
  return(tmpPlot)
}

## MCMC Catch * Quarters ----
set_ggCatchLine <- function(df_birth) {
  tmpPlot <- suppressMessages(
    ggplot() +
      geom_line(data = df_birth, aes_(x = ~Catch, y = ~Qty, group = ~Birth, color = ~Birth)) +
      theme_tufte(base_size = 14, ticks = F) +
      scale_x_discrete(drop = FALSE) +
      annotate("text", x = Inf, y = Inf, hjust = 1, vjust = 1, family = "serif", label = "Catches") +
      theme(
        legend.position = "none",
        legend.title = element_blank(),
        legend.text = element_text(size = 10),
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 5, angle = 45),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 5),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      )
  )
  
  if (length(unique(df_birth$Birth)) <= 12) {
    tmpPlot <- tmpPlot + scale_color_brewer(palette = "Paired")
  } else {
    outPal <- rainbow(length(unique(df_birth$Birth)))
    tmpPlot <- tmpPlot + scale_colour_manual(values = outPal)
  }
  return(tmpPlot)
}

## MCMC Quarters Histogram ----
set_ggHistBirth <- function(df_mix, df_grow) {
  tmpPlot <- suppressMessages(
    ggplot(
      data = df_mix,
      mapping = aes_(
        x = ~CatcDate, y = ~Length,
        color = ~factor(Birth)
      )
    ) +
      geom_jitter(size = 0.05, height = 0, width = 0.9, alpha = 0.4) +
      scale_x_discrete(drop = FALSE) +
      geom_line(
        data = df_grow,
        mapping = aes_(x = ~Date, y = ~Length, group = ~Birth),
        linetype = 2
      ) +
      guides(colour = guide_legend(override.aes = list(
        size = 2.5,
        alpha = 0.9,
        fill = NA
      ))) +
      theme_tufte(base_size = 14, ticks = FALSE) +
      theme(
        legend.position = "bottom",
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 8, angle = 90),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 8),
        axis.title.y = element_text(size = 8),
        legend.key = element_blank()
      )
  )
  if (length(unique(df_mix$Birth)) <= 12) {
    tmpPlot <- tmpPlot + scale_color_brewer(name = "Year of Birth", palette = "Paired")
  } else {
    outPal <- rainbow(length(unique(df_mix$Birth)))
    tmpPlot <- tmpPlot + scale_colour_manual(values = outPal)
  }
  return(tmpPlot)
}

## MCMC Cohort Summary Table ----
set_tblCohoStat <- function(df_coho) {
  cohSliTheme <- gridExtra::ttheme_default(
    core = list(fg_params = list(cex = 0.4)),
    colhead = list(fg_params = list(cex = 0.5)),
    rowhead = list(fg_params = list(cex = 0.4))
  )
  return(tableGrob(round(df_coho, 2), theme = cohSliTheme, rows = NULL))
}

## MCMC Age-Length Table ----
set_tblAgeLength <- function(df_mix) {
  ageLenTheme <- gridExtra::ttheme_default(
    core = list(fg_params = list(cex = 0.4)),
    colhead = list(fg_params = list(cex = 0.5)),
    rowhead = list(fg_params = list(cex = 0.3))
  )
  return(tableGrob(table(round(df_mix$Length), df_mix$Age), theme = ageLenTheme))
}

## MCMC Plot Age-Length ----
set_ggAgeLength <- function(df_mix, mixPalette) {
  return(
    suppressMessages(
      ggplot() +
        scale_x_continuous("Age", breaks = 0:max(ceiling(df_mix$Age))) +
        scale_y_continuous("Length", breaks = pretty(df_mix$Length, 10)) +
        geom_point(data = df_mix, aes_(x = ~AgeNF, y = ~Length, color = ~factor(Age)), size = 0.3) +
        geom_point(data = df_mix, aes_(x = ~Age, y = ~Length, fill = ~factor(Age)), shape = 21, color = "grey20", size = 1.2) +
        scale_color_manual(values = mixPalette) +
        scale_fill_manual(values = mixPalette) +
        theme_tufte(base_size = 14, ticks = FALSE) +
        theme(
          legend.position = "none",
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.x = element_text(size = 8),
          axis.title.x = element_text(size = 8),
          axis.text.y = element_text(size = 8),
          axis.title.y = element_text(size = 8)
        )
    )
  )
}

## MCMC Chains Boxplot Sigma ----
set_ggSigmaBox <- function(df_sigma, sigPalette, numCoho) {
  cohoVari <- melt(sqrt(df_sigma))
  names(cohoVari) <- c("Iter", "Cohort", "Value")
  cohoVari$Cohort <- factor(as.numeric(cohoVari$Cohort), levels = 1:numCoho)
  stsVari <- boxplot.stats(cohoVari$Value)$stats ## from: http://stackoverflow.com/questions/21533158/remove-outliers-fully-from-multiple-boxplots-made-with-ggplot2-in-r-and-display
  cohoVariGG <- suppressMessages(
    ggplot(cohoVari, aes_(x = ~Cohort, y = ~Value, fill = ~Cohort)) +
      geom_boxplot(alpha = 0.6, outlier.color = "grey30", outlier.size = 0.35, notch = TRUE) +
      ggtitle("SD") +
      scale_x_discrete(labels = 0:(numCoho - 1)) +
      scale_fill_manual(values = sigPalette) +
      theme_tufte(base_size = 14, ticks = FALSE) +
      theme(
        legend.position = "none",
        title = element_text(size = 9),
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 8),
        axis.title.x = element_text(size = 8),
        axis.text.y = element_text(size = 8),
        axis.title.y = element_blank()
      ) +
      coord_cartesian(ylim = c(stsVari[2] / 2, max(stsVari) * 1.25)) ## from: http://stackoverflow.com/questions/21533158/remove-outliers-fully-from-multiple-boxplots-made-with-ggplot2-in-r-and-display
  )
  return(cohoVariGG)
}

## MCMC Chains Boxplot Tau ----
set_ggTausBox <- function(df_taus, tauPalette, numCoho) {
  cohoPreci <- melt(df_taus)
  names(cohoPreci) <- c("Iter", "Cohort", "Value")
  cohoPreci$Cohort <- factor(as.numeric(cohoPreci$Cohort), levels = 1:(numCoho))
  stsPreci <- boxplot.stats(cohoPreci$Value)$stats ## from: http://stackoverflow.com/questions/21533158/remove-outliers-fully-from-multiple-boxplots-made-with-ggplot2-in-r-and-display
  
  cohoPreciGG <- suppressMessages(
    ggplot(cohoPreci, aes_(x = ~Cohort, y = ~Value, fill = ~Cohort)) +
      geom_boxplot(alpha = 0.6, outlier.color = "grey30", outlier.size = 0.35, notch = TRUE) +
      ggtitle("Precision") +
      scale_x_discrete(labels = 0:(numCoho - 1)) +
      scale_fill_manual(values = tauPalette) +
      theme_tufte(base_size = 14, ticks = FALSE) +
      theme(
        legend.position = "none",
        title = element_text(size = 9),
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 8),
        axis.title.x = element_text(size = 8),
        axis.text.y = element_text(size = 8),
        axis.title.y = element_blank()
      ) +
      coord_cartesian(ylim = c(stsPreci[2] / 2, max(stsPreci) * 1.25)) ## from: http://stackoverflow.com/questions/21533158/remove-outliers-fully-from-multiple-boxplots-made-with-ggplot2-in-r-and-display
  )
  
  return(cohoPreciGG)
}

## MCMC Chains Traceplot ----
set_ggChainTrace <- function(df_LK) {
  return(
    suppressMessages(
      ggplot(
        data = df_LK,
        mapping = aes_(x = ~Iter, y = ~Value, color = ~factor(Chain))
      ) +
        geom_line(alpha = 0.7) +
        facet_wrap(~Parameter, nrow = 3, ncol = 1, scales = "free", strip.position = "left") +
        scale_color_brewer(palette = "Dark2", "Chain") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          title = element_text(size = 10),
          legend.position = "right",
          legend.title = element_text(size = 7),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.x = element_text(size = 6),
          axis.title.x = element_blank(),
          axis.text.y = element_text(size = 6),
          axis.title.y = element_blank(),
          axis.ticks.y = element_blank()
        ) +
        guides(colour = guide_legend(override.aes = list(
          size = 3,
          alpha = 0.9,
          fill = NA
        )))
    )
  )
}

## MCMC Chains Scatterplot ----
set_ggChainScatter <- function(gg_DFscat, meanL, meanK) {
  return(
    suppressMessages(
      ggplot() +
        geom_point(
          data = gg_DFscat,
          mapping = aes_(x = ~Linf, y = ~Kappa, color = ~factor(Chain)),
          size = 0.25, alpha = 0.25
        ) +
        annotate("point",
                 x = meanL, y = meanK, color = "goldenrod1",
                 shape = 42, size = 12, alpha = 0.9
        ) +
        annotate("text",
                 x = Inf, y = Inf,
                 label = paste("LHat = ", round(meanL, 2),
                               "\nKHat = ", round(meanK, 3),
                               sep = ""
                 ),
                 hjust = 1, vjust = 1, color = "goldenrod1", fontface = "bold"
        ) +
        scale_color_brewer(palette = "Dark2", "Chain") +
        theme_tufte(base_size = 14, ticks = F) +
        theme(
          legend.position = "none",
          legend.title = element_text(size = 9),
          panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
          axis.text.x = element_text(size = 6),
          axis.title.x = element_text(size = 8),
          axis.text.y = element_text(size = 6),
          axis.title.y = element_text(size = 8),
          axis.ticks.y = element_blank()
        ) +
        guides(colour = guide_legend(override.aes = list(
          size = 3,
          alpha = 0.9,
          fill = NA
        )))
    )
  )
}

## Length Frequency Distribution Histogram ----
set_ggHistLfdTot <- function(inLfd) {
  suppressMessages(ggplot(inLfd, aes_(x = ~Length, y = ~..count.., fill = ~factor(1))) +
                     geom_histogram(bins = 50, alpha = 0.7, col = "grey10") +
                     # annotate("text", x = 0, y = Inf, hjust = 0, vjust = 1,
                     #          family="serif", label = "Absolute frequency of \nlength values") +
                     geom_vline(xintercept = mean(inLfd$Length), col = "grey90", lwd = 0.6, lty = 2) +
                     scale_x_continuous(breaks = pretty(inLfd$Length, 10)) +
                     theme_tufte(base_size = 14, ticks = F) +
                     theme(
                       legend.position = "none",
                       panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
                       axis.text.x = element_text(size = 8),
                       axis.title.x = element_text(size = 10),
                       axis.text.y = element_text(size = 8),
                       axis.title.y = element_blank(),
                       axis.ticks.y = element_blank()
                     ))
}

## UTC Coverage Histogram ----
set_ggHistUtcTot <- function(inLfd) {
  suppressMessages(
    ggplot(data.frame(UTC = unique(inLfd$UTC)), aes_(x = ~UTC, y = ~..count.., fill = ~factor(1))) +
      geom_histogram(bins = 100, alpha = 0.7) +
      annotate("text",
               x = -Inf, y = Inf, hjust = 0, vjust = 1,
               family = "serif", label = "Time coverage"
      ) +
      theme_tufte(base_size = 14, ticks = F) +
      theme(
        legend.position = "none",
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 8, angle = 45),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 8),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      ) +
      scale_x_chron(n = 10)
  )
}

## UTC split Dot Chart ----
set_ggDotUtcSplit <- function(inLfd) {
  sampPunch <- melt(table(inLfd$Year, inLfd$Month))
  names(sampPunch) <- c("Year", "Month", "Frequency")
  sampPunch$Year <- factor(sampPunch$Year, levels = sort(unique(sampPunch$Year), decreasing = TRUE))
  suppressMessages(
    ggplot(sampPunch, aes_(x = ~Month, y = ~Year, size = ~log10(Frequency), color = ~factor(1))) +
      geom_point() +
      scale_y_discrete(breaks = unique(sampPunch$Year), expand = c(0.1, 0.1)) +
      theme_tufte(base_size = 14, ticks = F) +
      theme(
        legend.position = "none",
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 8),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 8),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      )
  )
}

## UTC LFD Histogram ----
set_ggHistUtcLfd <- function(inLfd) {
  suppressMessages(
    ggplot(inLfd, aes_(x = ~Length, y = ~..count.., fill = ~factor(1))) +
      geom_histogram(bins = 30, alpha = 0.7) +
      facet_grid(Year ~ Month, switch = "y") +
      theme_few() +
      scale_x_continuous(breaks = pretty(inLfd$Length, 5)) +
      theme(
        legend.position = "none",
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 6),
        strip.text.x = element_text(size = 8),
        axis.title.x = element_text(size = 10),
        axis.text.y = element_blank(),
        strip.text.y = element_text(size = 10),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      )
  )
}

## Medits Index DotChart ----
ggplot_meditsIndex <- function(inMedits) {
  suppressMessages(
    ggplot() +
      geom_point(data = inMedits, mapping = aes_(x = ~Class, y = ~Stratum, size = ~Index, colour = ~Zeros, shape = ~Zeros)) +
      theme_tufte(base_size = 14, ticks = F) +
      scale_x_continuous(breaks = pretty(inMedits$Class, 10)) +
      scale_color_wsj(guide = FALSE) +
      scale_shape_cleveland(guide = FALSE) +
      facet_grid(Year ~ .) +
      theme(
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 6),
        strip.text.x = element_text(size = 8),
        axis.title.x = element_text(size = 10),
        axis.text.y = element_text(size = 8),
        strip.text.y = element_text(size = 10),
        axis.title.y = element_text(size = 10),
        axis.ticks.y = element_blank()
      )
  )
}


## Year LFD Histogram ----
set_ggHistYearLfd <- function(inLfd) {
  suppressMessages(
    ggplot(inLfd, aes_(x = ~Length, y = ~..count.., fill = ~factor(1))) +
      geom_histogram(bins = 60, alpha = 0.7) +
      facet_grid(Year ~ ., switch = "y") +
      theme_few() +
      scale_x_continuous(breaks = pretty(inLfd$Length, 5)) +
      theme(
        legend.position = "none",
        panel.grid = element_line(size = 0.25, linetype = 2, colour = "grey20"),
        axis.text.x = element_text(size = 6),
        strip.text.x = element_text(size = 8),
        axis.title.x = element_text(size = 10),
        axis.text.y = element_blank(),
        strip.text.y = element_text(size = 10),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank()
      )
  )
}

## Abundance Frequency Table ----
set_spatAbbTbl <- function(inSpat) {
  out_FgTbl <- data.frame(
    FG = inSpat$FG,
    AbsFreq = inSpat$Freq,
    RelFreq = inSpat$relFreq
  )
  
  fgAbbTheme <- gridExtra::ttheme_default(
    core = list(fg_params = list(cex = 0.4)),
    colhead = list(fg_params = list(cex = 0.6)),
    rowhead = list(fg_params = list(cex = 0.4))
  )
  
  return(tableGrob(out_FgTbl, theme = fgAbbTheme))
}

## Abundance Absolute Frequency Bars ----
set_spatAbsFreq <- function(inSpat) {
  suppressMessages(
    ggplot(inSpat, aes_(x = ~FG, y = ~Freq)) +
      theme_tufte(base_size = 14, ticks = F) +
      geom_bar(width = 0.45, fill = "gray35", stat = "identity") +
      scale_y_continuous(breaks = pretty(inSpat$Freq, n = 5)) +
      ggtitle("Absolute number of obsevartions\nin each fishing ground") +
      annotate("text",
               x = 1:nrow(inSpat), y = inSpat$Freq + max(inSpat$Freq) / 20,
               hjust = 0.5, family = "serif", size = 3,
               label = ifelse(inSpat$Freq == 0, "", inSpat$Freq)
      ) +
      theme(
        legend.position = "none",
        plot.title = element_text(size = 6),
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        axis.title = element_blank(),
        axis.text.x = element_text(size = 5),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 5),
        axis.title.y = element_blank()
      )
  )
}

## Abundance Relative Frequency Bars ----
set_spatRelFreq <- function(inSpat) {
  suppressMessages(
    ggplot(inSpat, aes_(x = ~FG, y = ~relFreq)) +
      theme_tufte(base_size = 14, ticks = F) +
      geom_bar(width = 0.45, fill = "gray35", stat = "identity") +
      scale_y_continuous(breaks = pretty(inSpat$relFreq, n = 5)) +
      ggtitle("Relative number of obsevartions\nin each fishing ground") +
      annotate("text",
               x = 1:nrow(inSpat), y = inSpat$relFreq + max(inSpat$relFreq) / 20,
               hjust = 0.5, family = "serif", size = 3,
               label = ifelse(inSpat$relFreq == 0, "", inSpat$relFreq)
      ) +
      theme(
        legend.position = "none",
        panel.grid = element_line(size = 0.05, linetype = 2, colour = "grey20"),
        plot.title = element_text(size = 6),
        axis.title = element_blank(),
        axis.text.x = element_text(size = 5),
        axis.title.x = element_blank(),
        axis.text.y = element_text(size = 5),
        axis.title.y = element_blank()
      )
  )
}


### Single Species Assessment ####

ggplot_SSBsingle <- function(choSpecie, assData) {
  suppressMessages(
    ggplot(data = assData, aes_(x = ~Year, y = ~SSB)) +
      geom_point() +
      geom_line() +
      geom_ribbon(aes(ymin = assData$Lower, ymax = assData$Upper),
                  linetype = 2, alpha = 0.1
      ) +
      ggtitle(paste(choSpecie, "- Stock SSB")) +
      theme_tufte(base_size = 14, ticks = F) +
      ylab("SSB (t)") +
      theme(
        legend.position = "none",
        plot.title = element_text(size = 18),
        axis.text.x = element_text(size = 10),
        axis.title.x = element_text(size = 12),
        panel.grid = element_line(size = 0.5, linetype = 2, colour = "grey20"),
        axis.text.y = element_text(size = 12),
        axis.ticks.y = element_blank()
      )
  )
}

ggplot_OPSsingle <- function(choSpecie, assData) {
  suppressMessages(
    ggplot(assData$obsSAA, aes_(x = ~Year, y = ~Index, colour = ~Age, group = ~Age)) +
      geom_errorbar(aes_(ymin = ~Lower, ymax = ~Upper),
                    colour = "black", width = .1
      ) +
      geom_point(size = 1) +
      geom_line(data = assData$predSAA, aes_(x = ~Year, y = ~Index, colour = ~Age, group = ~Age)) +
      facet_wrap(~Age, nrow = 2, scales = "free_y") +
      ggtitle(paste(choSpecie, "- Survey Index - Observed VS Predicted")) +
      theme_tufte(base_size = 14, ticks = F) +
      ylab("Survey Index") +
      theme(
        legend.position = "none",
        plot.title = element_text(size = 16),
        axis.text.x = element_text(size = 10),
        axis.title.x = element_text(size = 12),
        panel.grid = element_line(size = 0.25, linetype = 2, colour = "grey20"),
        axis.text.y = element_text(size = 10),
        axis.ticks.y = element_blank()
      )
  )
}

ggplot_OPCsingle <- function(choSpecie, assData) {
  suppressMessages(
    ggplot(data = assData) +
      geom_point(mapping = aes_(x = ~Age, y = ~obsCAA, color = ~factor(Age)), size = 3) +
      geom_line(mapping = aes_(x = ~Age, y = ~predCAA)) +
      ggtitle(paste(choSpecie, "- Catch At Age - Observed VS Predicted")) +
      theme_tufte(base_size = 14, ticks = F) +
      ylab("Frequency") +
      theme(
        legend.position = "none",
        plot.title = element_text(size = 16),
        axis.text.x = element_text(size = 10),
        axis.title.x = element_text(size = 12),
        panel.grid = element_line(size = 0.5, linetype = 2, colour = "grey20"),
        axis.text.y = element_text(size = 10),
        axis.ticks.y = element_blank()
      )
  )
}


ggplot_TCsingle <- function(choSpecie, assData) {
  suppressMessages(
    ggplot(data = assData, aes_(x = ~Year, y = ~Catch/1000)) +
      geom_errorbar(aes_(ymin = ~Lower/1000, ymax = ~Upper/1000), colour = "black", width = 0.1) +
      geom_point() +
      geom_line() +
      ggtitle(paste(choSpecie, "- Total Catch")) +
      theme_tufte(base_size = 14, ticks = F) +
      ylab("Catch (t)") +
      theme(
        legend.position = "none",
        plot.title = element_text(size = 18),
        axis.text.x = element_text(size = 10),
        axis.title.x = element_text(size = 12),
        panel.grid = element_line(size = 0.5, linetype = 2, colour = "grey20"),
        axis.text.y = element_text(size = 12),
        axis.ticks.y = element_blank()
      )
  )
}