add plot_forage_index file

R/plot_forage_index.R

@@ -0,0 +1,115 @@
+#' plot forage index
+#'
+#' Description should be here. This needs to be reworked to uncouple GB and GOM
+#'
+#' @param EPUs Character string. Which SOE report ("GB","MAB")
+#' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot
+#' @param shade.fill Character string. Color of shaded region. (Default = "lightgrey)
+#' @param shade.alpha Numeric scalar. Alpha of shaded region (Default = 0.5)
+#'
+#' @return ggplot object
+#'
+#'
+#' @export
+#'
+
+plot_forage_index <- function(EPUs="MAB",
+                              shadedRegion=c(2012,2022),
+                              shade.fill="lightgrey",
+                              shade.alpha=0.3) {
+
+
+  x.shade.min <- shadedRegion[1]
+  x.shade.max <- shadedRegion[2]
+
+  if (EPUs == "GB") {
+    filterEPUs <- c("GOM", "GB")
+  } else {
+    filterEPUs <- EPUs
+  }
+
+
+  fix<- ecodata::forage_index %>%
+    dplyr::filter(Var %in% c("Fall Forage Fish Biomass Estimate",
+                             "Spring Forage Fish Biomass Estimate"),
+                  EPU %in% filterEPUs) %>%
+    dplyr::group_by(EPU) %>%
+    dplyr::summarise(max = max(Value))
+
+  p <- ecodata::forage_index %>%
+    dplyr::filter(Var %in% c("Fall Forage Fish Biomass Estimate",
+                             "Fall Forage Fish Biomass Estimate SE",
+                             "Spring Forage Fish Biomass Estimate",
+                             "Spring Forage Fish Biomass Estimate SE"),
+                  EPU %in% filterEPUs) %>%
+    dplyr::group_by(EPU) %>%
+    tidyr::separate(Var, into = c("Season", "A", "B", "C", "D", "Var")) %>%
+    dplyr::mutate(Var = tidyr::replace_na(Var, "Mean")) %>% #,
+                  #max = as.numeric(Value)) %>%
+    tidyr::pivot_wider(names_from = Var, values_from = Value) %>%
+    dplyr::left_join(fix) %>%
+    dplyr::mutate(#Value = Value/resca,
+      Mean = as.numeric(Mean),
+      #max = as.numeric(Value),
+      Mean = Mean/max,
+      SE = SE/max,
+      Upper = Mean + SE,
+      Lower = Mean - SE) %>%
+    ggplot2::ggplot(aes(x = Time, y = Mean, group = Season))+
+    ggplot2::annotate("rect", fill = shade.fill, alpha = shade.alpha,
+        xmin = x.shade.min , xmax = x.shade.max,
+        ymin = -Inf, ymax = Inf) +
+    ggplot2::geom_ribbon(aes(ymin = Lower, ymax = Upper, fill = Season), alpha = 0.5)+
+    ggplot2::geom_point()+
+    ggplot2::geom_line()+
+    ggplot2::ggtitle("")+
+    ggplot2::ylab(expression("Relative forage biomass"))+
+    ggplot2::xlab(element_blank())+
+    ggplot2::facet_wrap(.~EPU)+
+    ecodata::geom_gls()+
+    ecodata::theme_ts()+
+    ecodata::theme_facet()+
+    ecodata::theme_title()
+
+    if (EPUs == "GB") {
+      p <- p +
+        ggplot2::theme(legend.position = "bottom",
+                       legend.title = element_blank())
+
+    }
+
+    return(p)
+
+  # ecodata::forage_index %>%
+  #   dplyr::filter(Var %in% c("Fall Forage Fish Biomass Estimate",
+  #                            "Fall Forage Fish Biomass Estimate SE",
+  #                            "Spring Forage Fish Biomass Estimate",
+  #                            "Spring Forage Fish Biomass Estimate SE"),
+  #                 EPU == "MAB") %>%
+  #   tidyr::separate(Var, into = c("Season", "A", "B", "C", "D", "Var")) %>%
+  #   dplyr::mutate(Var = replace_na(Var, "Mean"),
+  #                 max = as.numeric(resca)) %>%
+  #   tidyr::pivot_wider(names_from = Var, values_from = Value) %>%
+  #   dplyr::mutate(#Value = Value/resca,
+  #     Mean = as.numeric(Mean),
+  #     Mean = Mean/max,
+  #     SE = SE/max,
+  #     Upper = Mean + SE,
+  #     Lower = Mean - SE) %>%
+  #   ggplot2::ggplot(aes(x = Time, y = Mean, group = Season))+
+  #   ggplot2::annotate("rect", fill = shade.fill, alpha = shade.alpha,
+  #                     xmin = x.shade.min , xmax = x.shade.max,
+  #                     ymin = -Inf, ymax = Inf) +
+  #   ggplot2::geom_ribbon(aes(ymin = Lower, ymax = Upper, fill = Season), alpha = 0.5)+
+  #   ggplot2::geom_point()+
+  #   ggplot2::geom_line()+
+  #   ggplot2::ggtitle("Forage Biomass Index")+
+  #   ggplot2::ylab(expression("Relative forage biomass"))+
+  #   ggplot2::xlab(element_blank())+
+  #   ecodata::geom_gls()+
+  #   ecodata::theme_ts()+
+  #   ecodata::theme_title()
+  #
+  #
+
+}