Merge pull request #223 from NOAA-EDAB/plot_fix_jc

Plot adjustments: cold pool, bottom temp, bennet, and commercial_div

R/plot_bennet.R

@@ -71,11 +71,11 @@ plot_bennet <- function(shadedRegion = NULL,
                         ymin = -Inf, ymax = Inf)+
       ggplot2::geom_bar(data = indicators, ggplot2::aes(x = Time, y = Value, fill = Guild), stat="identity")+
       #ggplot2::scale_fill_manual(name = "Indicators", values = Guild) +
-      ggplot2::geom_line(data = indicators, ggplot2::aes(x = Time, y = component, color = "$"))+
+      ggplot2::geom_line(data = indicators, ggplot2::aes(x = Time, y = component, color = "$"), linewidth = 0.7)+
       ggplot2::scale_x_continuous(breaks = seq(1980, 2020, by = 5), expand = c(0.01, 0.01)) +
       ggplot2::facet_grid(EPU~Var, scales = "free")+
       ggplot2::scale_colour_grey(name ="Component") +
-      ggplot2::ggtitle("Bennet Indicator")+
+      ggplot2::ggtitle(paste0("Bennet Indicator \n",EPU))+
       ggplot2::labs(y=paste0("Million USD (", bennet_year, ")")) +
 
       ggplot2::xlab(ggplot2::element_blank())+
@@ -114,9 +114,9 @@ plot_bennet <- function(shadedRegion = NULL,
                         ymin = -Inf, ymax = Inf)+
       ggplot2::geom_bar(data = indicators, ggplot2::aes(x = Time, y = Value, fill = Var), stat="identity")+
       ggplot2::scale_fill_manual(name = "Indicators", values = ind_fill) +
-      ggplot2::geom_line(data = revchange, ggplot2::aes(x = Time, y = Value, color = "$"))+
+      ggplot2::geom_line(data = revchange, ggplot2::aes(x = Time, y = Value, color = "$"), linewidth = 0.7)+
       ggplot2::scale_colour_grey(name ="Revenue Change") +
-      ggplot2::ggtitle("Bennet Indicator")+
+      ggplot2::ggtitle(paste0("Bennet Indicator \n",EPU))+
       ggplot2::labs(y=paste0("Million USD (", bennet_year, ")")) +
       ggplot2::scale_x_continuous(breaks = seq(1980, 2020, by = 5), expand = c(0.01, 0.01)) +
       #::scale_y_continuous(breaks = seq(y.lim[1], y.lim[2], by = 100),
@@ -157,9 +157,9 @@ plot_bennet <- function(shadedRegion = NULL,
                         ymin = -Inf, ymax = Inf)+
       ggplot2::geom_bar(data = indicators, ggplot2::aes(x = Time, y = Value, fill = Var), stat="identity")+
       ggplot2::scale_fill_manual(name = "Indicators", values = ind_fill) +
-      ggplot2::geom_line(data = revchange, ggplot2::aes(x = Time, y = Value, color = "$"))+
+      ggplot2::geom_line(data = revchange, ggplot2::aes(x = Time, y = Value, color = "$"), linewidth = 0.7)+
       ggplot2::scale_colour_grey(name ="Revenue Change") +
-      ggplot2::ggtitle("Bennet Indicator")+
+      ggplot2::ggtitle(paste0("Bennet Indicator \n",EPU))+
       ggplot2::labs(y=paste0("Million USD (", bennet_year, ")")) +
       ggplot2::scale_x_continuous(breaks = seq(1980, 2015, by = 10), expand = c(0.01, 0.01)) +
       #ggplot2::scale_y_continuous(breaks = seq(y.lim[1], y.lim[2], by = 100),

R/plot_bottom_temp_model_anom.R

@@ -7,6 +7,7 @@
 #' @param varName Character string. Which variable ("seasonal", "annual")
 #' @param EPU Character string. Which EPU for New England report ("GB", "GOM") Mid will always be MAB
 #' @param n Numeric scalar. Number of years used (from most recent year) to estimate short term trend . Default = 0 (No trend calculated)
+#' @param source character vector. Which source data should be plotted (e.g. 'GLORYS','MOM6')
 #'
 #' @return ggplot object
 #'
@@ -16,6 +17,7 @@ plot_bottom_temp_model_anom <- function(shadedRegion=NULL,
                                   report="MidAtlantic",
                                   varName="seasonal",
                                   EPU="MAB",
+                                  source = 'GLORYS',
                                   n = 0) {
 
   setup <- ecodata::plot_setup(shadedRegion = shadedRegion,
@@ -32,7 +34,7 @@ plot_bottom_temp_model_anom <- function(shadedRegion=NULL,
 
 
   fix <- ecodata::bottom_temp_model_anom |>
-    dplyr::filter((Source == "GLORYS" & Time >= 1993) | (Source == "ROMS") | (Source == 'MOM6') ) |>
+    dplyr::filter(Source %in% source) |>
     dplyr::filter(EPU %in% filterEPUs) |>
     dplyr::mutate(Time = as.numeric(Time),
                   Var = stringr::str_to_title(stringr::str_extract(Var,"Winter|Spring|Summer|Fall|Annual"))) |>
@@ -109,3 +111,4 @@ plot_bottom_temp_model_anom <- function(shadedRegion=NULL,
 attr(plot_bottom_temp_model_anom,"EPU") <- c("MAB","GB","GOM")
 attr(plot_bottom_temp_model_anom,"report") <- c("MidAtlantic","NewEngland")
 attr(plot_bottom_temp_model_anom, "varName") <- c("seasonal", "annual")
+attr(plot_bottom_temp_model_anom, "source") <- c("GLORYS", "MOM6")

R/plot_cold_pool.R

@@ -4,18 +4,24 @@
 #'
 #' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
 #' @param report Character string. Which SOE report ("MidAtlantic" only, default)
-#' @param varName Character string. Which plot (NULL, "cold_pool", "persistence","extent")
+#' @param varName Character string. Which variable to plot (NULL, "cold_pool", "persistence","extent"). NULL plots all three.
 #' @param n Numeric scalar. Number of years used (from most recent year) to estimate short term trend . Default = 0 (No trend calculated)
 #'
 #' @return ggplot object
 #'
 #'
 #' @export
 #'
+#'
+
+# removed temporarily from params documentation, add back later:
+# @param source character vector. Which source data should be plotted (e.g. 'GLORYS','MOM6')
+
 
 plot_cold_pool <- function(shadedRegion = NULL,
                            report="MidAtlantic",
                            varName = NULL,
+                           #source = 'GLORYS',
                            n = 0) {
 
   # generate plot setup list (same for all plot functions)
@@ -39,6 +45,7 @@ plot_cold_pool <- function(shadedRegion = NULL,
 
   cpdup <- ecodata::cold_pool |>
     dplyr::group_by(Time, Var, EPU) |>
+    #dplyr::filter(Source %in% source) |>
     dplyr::mutate(duplicated = dplyr::n()>1) |>
     dplyr::ungroup()
 
@@ -67,16 +74,16 @@ plot_cold_pool <- function(shadedRegion = NULL,
     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_line(ggplot2::aes(x = Time, y = Value), size = setup$lwd) +
-    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value, shape = Source), size = setup$pcex) +
+    ggplot2::geom_line(ggplot2::aes(x = Time, y = Value), size = setup$lwd) + #, color = Source
+    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value, shape = Source), size = setup$pcex) + #color = Source
     ggplot2::scale_shape_manual(values = c(16, 1))+
     ggplot2::theme(legend.position = "none")+
     # ggplot2::geom_ribbon(aes(x = Time, ymin = Lower, ymax = Upper), fill = "gray")+
     ggplot2::geom_hline(ggplot2::aes(yintercept = 0))+
     ecodata::geom_gls(ggplot2::aes(x = Time, y = Value))+
     ecodata::geom_lm(n=n, ggplot2::aes(x = Time, y = Value))+
     #ecodata::geom_lm(aes(x = Time, y = Value, group = Var))+
-    ggplot2::ylab(bquote("Cold Pool Index, " ~ (x^{-1}))) +
+    ggplot2::ylab(bquote("Cold Pool Index, (\u00B0C)" ~ (x^{-1}))) +
     #ggplot2::scale_y_reverse()+
     ggplot2::xlab("")+
     ecodata::theme_ts()+
@@ -85,7 +92,8 @@ plot_cold_pool <- function(shadedRegion = NULL,
     ggplot2::annotate("text", x = 1990, y = -2.5, label = "Warmer",size = 4, colour = "red")
 
 
-
+  #Cold Pool Extent units originall number of cells. Assuming 111km/deg to convert to area
+  #One cell is 9.25^2 or 85.5 km2
 
   ei<- cpts |>
     dplyr::filter(stringr::str_detect(Var, pattern = "extent")) |>
@@ -99,24 +107,24 @@ plot_cold_pool <- function(shadedRegion = NULL,
     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_line(ggplot2::aes(x = Time, y = Value), size = setup$lwd) +
-    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value, shape = Source), size = setup$pcex) +
+    ggplot2::geom_line(ggplot2::aes(x = Time, y = Value*85.5), size = setup$lwd) + #, color = Source
+    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value*85.5, shape = Source), size = setup$pcex) + #color = Source
     ggplot2::scale_shape_manual(values = c(16, 1))+
     ggplot2::theme(legend.position = "none")+
     ggplot2::geom_hline(ggplot2::aes(yintercept = 0))+
-    ecodata::geom_gls(ggplot2::aes(x = Time, y = Value))+
-    ecodata::geom_lm(n=n, ggplot2::aes(x = Time, y = Value))+
+    ecodata::geom_gls(ggplot2::aes(x = Time, y = Value*85.5))+
+    ecodata::geom_lm(n=n, ggplot2::aes(x = Time, y = Value*85.5))+
     #ecodata::geom_lm(aes(x = Time, y = Value, group = Var))+
-    ggplot2::ylab("Spatial Extent Index") +
+    ggplot2::ylab(bquote("Spatial Extent Index, " ~ (km^{2}))) +
     ggplot2::xlab("")+
     ecodata::theme_ts()+
     ecodata::theme_title()+
     # ggplot2::annotate("segment", x = 2025, xend = 2025, y = 0.05, yend = 50,
     #          colour = "blue", size = 0.70, arrow = arrow())+
     # ggplot2::annotate("segment", x = 2025, xend = 2025, y = -0.05, yend = -250,
     #          colour = "red", size = 0.70, arrow = arrow())+
-    ggplot2::annotate("text", x = 1990, y = 125, label = "Larger",size = 4, colour = "blue")+
-    ggplot2::annotate("text", x = 1990, y = -350, label = "Smaller",size = 4, colour = "red")
+    ggplot2::annotate("text", x = 1990, y = Inf,vjust = 1.5, label = "Larger",size = 4, colour = "blue")+
+    ggplot2::annotate("text", x = 1990, y = -Inf,vjust = -1.5, label = "Smaller",size = 4, colour = "red")
 
 
   pi<- cpts |>
@@ -131,15 +139,15 @@ plot_cold_pool <- function(shadedRegion = NULL,
     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_line(ggplot2::aes(x = Time, y = Value), size = setup$lwd) +
-    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value, shape = Source), size = setup$pcex) +
+    ggplot2::geom_line(ggplot2::aes(x = Time, y = Value), size = setup$lwd) + #, color = Source
+    ggplot2::geom_point(ggplot2::aes(x = Time, y = Value, shape = Source), size = setup$pcex) + #color = Source
     ggplot2::scale_shape_manual(values = c(16, 1))+
     ggplot2::theme(legend.position = "none")+
     ggplot2::geom_hline(ggplot2::aes(yintercept = 0))+
     ecodata::geom_gls(ggplot2::aes(x = Time, y = Value))+
     ecodata::geom_lm(n=n, ggplot2::aes(x = Time, y = Value))+
     #ecodata::geom_lm(aes(x = Time, y = Value, group = Var))+
-    ggplot2::ylab("Persistence Index") +
+    ggplot2::ylab("Persistence Index (months)") +
     ggplot2::xlab("")+
     ecodata::theme_ts()+
     ecodata::theme_title()+
@@ -169,7 +177,7 @@ plot_cold_pool <- function(shadedRegion = NULL,
 
 attr(plot_cold_pool,"report") <- c("MidAtlantic","NewEngland")
 attr(plot_cold_pool,"varName") <- c("cold_pool", "persistence","extent")
-
+#attr(plot_cold_pool, "source") <- c("GLORYS", "MOM6")
 
 
   # Paste commented original plot code chunk for reference

R/plot_commercial_div.R

@@ -45,10 +45,10 @@ plot_commercial_div <- function(shadedRegion = NULL,
                     expression("Effective Shannon"))
 
   if(varName=="Fleet count"){
-    ylim_fc <- c(min(comm_div[comm_div$Var == "Fleet count",]$Value, na.rm = TRUE) - 10,
-                 max(comm_div[comm_div$Var == "Fleet count",]$Value, na.rm = TRUE) + 10 )
+    ylim_fc <- c(min(comm_div[comm_div$Var == "Fleet count" & comm_div$EPU == setup$region_abbr ,]$Value, na.rm = TRUE) *0.95,
+                 max(comm_div[comm_div$Var == "Fleet count"& comm_div$EPU == setup$region_abbr,]$Value, na.rm = TRUE) *1.05 )
   }else if(varName=="Fleet diversity in revenue"){
-    ylim_fc <- c(0, max(comm_div[comm_div$Var == "Fleet diversity in revenue",]$Value) + 3 )
+    ylim_fc <- c(0, max(comm_div[comm_div$Var == "Fleet diversity in revenue" & comm_div$EPU == setup$region_abbr,]$Value) *1.1 )
   }else{
     ylim_fc <- c(NA, NA)
   }