plot function template, FWIW

R/plot_function_template.R

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+#' plot <dataset name>
+#'
+#' <Insert description of plot function.>
+#'
+#' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
+#' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland")
+#'
+#' @return ggplot object
+#'
+#'
+#' @export
+#'
+
+plot_function_template <- function(shadedRegion = shadedRegion,
+                              report="MidAtlantic") {
+
+  # generate plot setup list (same for all plot functions)
+  setup <- ecodata::plot_setup(shadedRegion = shadedRegion,
+                               report=report)
+
+  # which report? this may be bypassed for some figures
+  if (report == "MidAtlantic") {
+    filterEPUs <- c("MAB")
+  } else {
+    filterEPUs <- c("GB", "GOM")
+  }
+
+  # optional code to wrangle ecodata object prior to plotting
+  # e.g., calculate mean, max or other needed values to join below
+   fix<- ecodata::dataset |>
+     dplyr::filter(Var %in% c("...",
+                              "..."),
+                   EPU %in% filterEPUs) |>
+     dplyr::group_by(EPU) |>
+     dplyr::summarise(max = max(Value))
+
+  # code for generating plot object p
+  # ensure that setup list objects are called as setup$...
+  # e.g. fill = setup$shade.fill, alpha = setup$shade.alpha,
+  # xmin = setup$x.shade.min , xmax = setup$x.shade.max
+  #
+  p <- ecodata::dataset |>
+    dplyr::filter(Var %in% c("..."),
+                                  EPU == "...") |>
+    #... more dataset wrangling as necessary |>
+    dplyr::left_join(fix) |>
+    dplyr::mutate(#
+      Value = Value,
+      #Mean = as.numeric(Mean),
+      #max = as.numeric(Value),
+      #Mean = Mean/max,
+      #SE = SE/max,
+      Upper = Mean + SE,
+      Lower = Mean - SE) |>
+    ggplot2::ggplot(ggplot2::aes(x = Time, y = Value))+
+    ggplot2::annotate("rect", fill = setup$shade.fill, alpha = setup$shade.alpha,
+        xmin = setup$x.shade.min , xmax = setup$x.shade.max,
+        ymin = -Inf, ymax = Inf) +
+    ggplot2::geom_ribbon(ggplot2::aes(ymin = Lower, ymax = Upper), alpha = 0.5)+
+    ggplot2::geom_point()+
+    ggplot2::geom_line()+
+    ggplot2::ggtitle("")+
+    ggplot2::ylab(expression("Indicator (units)"))+
+    ggplot2::xlab(element_blank())+
+    ggplot2::facet_wrap(.~EPU)+
+    ecodata::geom_gls()+
+    ecodata::theme_ts()+
+    ecodata::theme_facet()+
+    ecodata::theme_title()
+
+   # optional code for New England specific (2 panel) formatting
+    if (report == "NewEngland") {
+      p <- p +
+        ggplot2::theme(legend.position = "bottom",
+                       legend.title = element_blank())
+
+    }
+
+    return(p)
+
+  # Paste commented original plot code chunk for reference
+  # ecodata::dataset |>
+  #   dplyr::filter(Var %in% c("..."),
+  #                 EPU == "...") |>
+  #   ... more dataset wrangling as necessary |>
+  #   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("Title")+
+  #   ggplot2::ylab(expression("Y label"))+
+  #   ggplot2::xlab(element_blank())+
+  #   ecodata::geom_gls()+
+  #   ecodata::theme_ts()+
+  #   ecodata::theme_title()
+  #
+  #
+
+}