Merge pull request #108 from NOAA-EDAB/dev

updated ecodata data and plot functions

NAMESPACE

@@ -13,6 +13,7 @@ export(plot_blue_runner)
 export(plot_bottom_temp)
 export(plot_bottom_temp_comp)
 export(plot_bottom_temp_glorys)
+export(plot_bottom_temp_seasonal_gridded)
 export(plot_calanus_stage)
 export(plot_ch_bay_sal)
 export(plot_ch_bay_temp)

R/plot_bennet.R

@@ -1,9 +1,10 @@
-#' plot Bennet indicator
+#' plot Bennett indicator
 #'
 #' Stacked bar charts of price and volume components of revenue by feeding guild.
 #'
 #' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
 #' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland")
+#' @param plottype Character string. Which plot ("revenue", "??","???)
 #'
 #' @return ggplot object
 #'
@@ -12,7 +13,8 @@
 #'
 
 plot_bennet <- function(shadedRegion = NULL,
-                              report="MidAtlantic") {
+                        report="MidAtlantic",
+                        plottype="revenue") {
 
   # generate plot setup list (same for all plot functions)
   setup <- ecodata::plot_setup(shadedRegion = shadedRegion,

R/plot_bottom_temp_seasonal_gridded.r

@@ -0,0 +1,111 @@
+#' plot bottom temperature seasonal gridded data
+#'
+#' plots bottom_temp_seasonal_gridded data set
+#'
+#' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10), passed from plot function
+#' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland"), passed from plot function
+#'
+#'
+#' @return ggplot object
+#'
+#' @export
+
+plot_bottom_temp_seasonal_gridded <- function(shadedRegion = NULL,
+                                              report = "MidAtlantic") {
+
+
+  setup <- ecodata::plot_setup(shadedRegion = shadedRegion,
+                               report=report)
+
+  if (report == "MidAtlantic") {
+    filterEPUs <- c("MAB")
+
+    xmin = -77
+    xmax = -66
+    ymin = 35.5
+    ymax = 43
+    xlims <- c(xmin, xmax)
+    ylims <- c(ymin, ymax)
+
+
+  } else {
+    filterEPUs <- c("GB", "GOM")
+    # Set lat/lon window for maps
+    xmin = -73
+    xmax = -65
+    ymin = 39
+    ymax = 45
+    xlims <- c(xmin, xmax)
+    ylims <- c(ymin, ymax)
+  }
+
+
+  #EPU shapefile
+  ne_epu_sf <- ecodata::epu_sf |>
+    dplyr::filter(EPU %in% filterEPUs)
+
+
+  fix <- ecodata::bottom_temp_seasonal_gridded |>
+    dplyr::filter(Time == max(Time)) |>
+    dplyr::select(-Time) |>
+    dplyr::as_tibble() |>
+    dplyr::rename(Var = Season) |>
+    dplyr::mutate(Var = factor(Var, levels = c("winter","spring","summer","fall")))
+
+
+  p <- ggplot2::ggplot(data = fix)+
+    ggplot2::geom_tile(ggplot2::aes(x = Longitude, y = Latitude, fill = Value)) +
+    #ggplot2::coord_sf(xlim = xlims, ylim = ylims) +
+
+    #ggplot2::geom_sf(data = ecodata::coast, size = setup$map.lwd) +
+    #ggplot2::geom_sf(data = ne_epu_sf, fill = "transparent", size = setup$map.lwd) +
+    ggplot2::facet_wrap(Var~.)+
+    ecodata::theme_map() +
+    #ggplot2::scale_fill_viridis_c(option = 'A',name = 'Bottom \n Temp')+
+    ggplot2::ggtitle('Seasonal Mean Bottom Temperature')+
+    ggplot2::xlab("Longitude") +
+    ggplot2::ylab("Latitude") +
+    ggplot2::theme(panel.border = ggplot2::element_rect(colour = "black", fill=NA, linewidth=0.75),
+                   legend.key = ggplot2::element_blank(),
+                   axis.title = ggplot2::element_text(size = 11),
+                   strip.background = ggplot2::element_blank(),
+                   strip.text=ggplot2::element_text(hjust=0),
+                   axis.text = ggplot2::element_text(size = 8),
+                   axis.title.y = ggplot2::element_text(angle = 90))+
+    ecodata::theme_title() +
+    ecodata::theme_ts()
+
+
+  return(p)
+}
+
+attr(plot_bottom_temp_seasonal_gridded,"report") <- c("MidAtlantic","NewEngland")
+
+
+
+# p <-
+#   ggplot2::ggplot() +
+#   ggplot2::geom_tile(data = sst, ggplot2::aes(x = Longitude, y = Latitude,fill = Value)) +
+#   ggplot2::geom_sf(data = ecodata::coast, size = setup$map.lwd) +
+#   ggplot2::geom_sf(data = ne_epu_sf, fill = "transparent", size = setup$map.lwd) +
+#   ggplot2::scale_fill_gradient2(name = "Temp.\nAnomaly (C)",
+#                                 low = scales::muted("blue"),
+#                                 mid = "white",
+#                                 high = scales::muted("red"),
+#                                 limits = c(-5,5),
+#                                 labels = c("<-5", "-2", "0", "2", ">5")) +
+#   ggplot2::coord_sf(xlim = xlims, ylim = ylims) +
+#   ggplot2::facet_wrap(Season~.) +
+#   ecodata::theme_map() +
+#   ggplot2::ggtitle("SST anomaly") +
+#   ggplot2::xlab("Longitude") +
+#   ggplot2::ylab("Latitude") +
+#   ggplot2::theme(panel.border = ggplot2::element_rect(colour = "black", fill=NA, size=0.75),
+#                  legend.key = ggplot2::element_blank(),
+#                  axis.title = ggplot2::element_text(size = 11),
+#                  strip.background = ggplot2::element_blank(),
+#                  strip.text=ggplot2::element_text(hjust=0),
+#                  axis.text = ggplot2::element_text(size = 8),
+#                  axis.title.y = ggplot2::element_text(angle = 90))+
+#
+#    ecodata::theme_title()

R/plot_ch_bay_sal.R

@@ -40,7 +40,7 @@ plot_ch_bay_sal <- function(shadedRegion = NULL,
     ggplot2::geom_ribbon(ggplot2::aes(x = Time, ymin = minLTA, ymax = maxLTA), fill = "grey", alpha = 0.5)+
 
     ggplot2::geom_line(ggplot2::aes(x = Time, y = YearLTA, color= "Long Term Average 2010-2020")) +
-    ggplot2::geom_line(ggplot2::aes(x = Time, y = Year, color = "Daily 2022")) +
+    ggplot2::geom_line(ggplot2::aes(x = Time, y = Year, color = "Daily (Current Year)")) +
     ggplot2::ylab("Salinity") +
     ggplot2::ggtitle("Chesapeake Bay Salinity") +
     ggplot2::theme(legend.position = "bottom",

R/plot_gsi.R

@@ -4,15 +4,16 @@
 #'
 #' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
 #' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland")
-#'
+#' @param varName Character string. Which variable to plot ("gsi","westgsi")
 #' @return ggplot object
 #'
 #'
 #' @export
 #'
 
 plot_gsi <- function(shadedRegion = NULL,
-                              report="MidAtlantic") {
+                     report="MidAtlantic",
+                     varName = "gsi") {
 
   # generate plot setup list (same for all plot functions)
   setup <- ecodata::plot_setup(shadedRegion = shadedRegion,
@@ -26,12 +27,18 @@ plot_gsi <- function(shadedRegion = NULL,
     filterEPUs <- c("GB", "GOM")
   }
 
+  if (varName == "gsi") {
+    var <- "gulf stream index"
+  } else {
+    var <- "western gulf stream index"
+  }
   # optional code to wrangle ecodata object prior to plotting
   # e.g., calculate mean, max or other needed values to join below
 
 
 
   fix <- ecodata::gsi  |>
+    dplyr::filter(Var == var) |>
     dplyr::mutate(Year = floor(Time)) |>
     dplyr::group_by(Year) |>
     dplyr::summarise(Value = mean(Value)) |>
@@ -50,7 +57,7 @@ plot_gsi <- function(shadedRegion = NULL,
         ymin = -Inf, ymax = Inf) +
     ggplot2::geom_point()+
     ggplot2::geom_line()+
-    ggplot2::ggtitle("Gulf Stream Index")+
+    ggplot2::ggtitle(stringr::str_to_title(var))+
     ggplot2::ylab("Anomaly")+
     ggplot2::xlab(ggplot2::element_blank())+
     ecodata::geom_gls()+
@@ -75,3 +82,4 @@ plot_gsi <- function(shadedRegion = NULL,
 
 
 attr(plot_gsi,"report") <- c("MidAtlantic","NewEngland")
+attr(plot_gsi,"varName") <- c("gsi","westgsi")

R/plot_hms_landings.R

@@ -80,6 +80,12 @@ plot_hms_landings <- function(shadedRegion = NULL,
 
     return(p)
 
+
+}
+
+attr(plot_hms_landings,"varName") <- c("Landings","Revenue")
+attr(plot_hms_landings,"report") <- c("MidAtlantic","NewEngland")
+
   # Paste commented original plot code chunk for reference
   #Get data for plotting
   # ## Apex pred
@@ -120,4 +126,3 @@ plot_hms_landings <- function(shadedRegion = NULL,
   # p1
   #
 
-}

R/plot_productivity_anomaly.R

@@ -103,7 +103,7 @@ plot_productivity_anomaly <- function(shadedRegion = NULL,
     p <- plot_stackbarcpts_single(YEAR = bar_dat$Time,
                                     var2bar = bar_dat$Var,
                                     x = bar_dat$Value,
-                                    titl = paste0(EPU, "from survey data"),
+                                    titl = paste0(EPU, " from survey data"),
                                     xlab = "",
                                     ylab = "Small fish per large fish biomass (anomaly)",
                                     height = 5.5,

R/plot_thermal_habitiat_persistence.R

@@ -1,6 +1,6 @@
 #' plot thermal habitat persistence
 #'
-#' plots thermal_habitat_persistence data set.
+#' plots thermal_habitat_persistence data set. Current SOE Year only
 #'
 #' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
 #' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland")
@@ -12,7 +12,8 @@
 #'
 
 plot_thermal_habitat_persistence <- function(shadedRegion = NULL,
-                                      report="MidAtlantic") {
+                                             report="MidAtlantic",
+                                             year = NULL) {
 
   # generate plot setup list (same for all plot functions)
   setup <- ecodata::plot_setup(shadedRegion = shadedRegion,
@@ -25,10 +26,15 @@ plot_thermal_habitat_persistence <- function(shadedRegion = NULL,
     filterEPUs <- c("GB","GOM")
   }
 
+  if (is.null(year)) {
+    # current SOE report year
+    Yr <- setup$shadedRegion[2]
+  }
   # optional code to wrangle ecodata object prior to plotting
   # e.g., calculate mean, max or other needed values to join below
   fix <- ecodata::thermal_habitat_persistence |>
-    dplyr::mutate(Var = paste0(Var,"\u00B0C"))
+    dplyr::mutate(Var = paste0(Var,"\u00B0C")) |>
+    dplyr::filter(Time == Yr)
 
   # neus_map  <- ggplot2::map_data('worldHires',region = 'USA')
   legendTitle <- unique(fix$Units)

R/plot_wind_occupancy.R

@@ -33,31 +33,31 @@ plot_wind_occupancy <- function(shadedRegion = NULL,
                        ifelse(wind1$Trend == "neg",
                               "$\\searrow$",
                               " "))
-  wind2<-wind1 %>% dplyr::select(Area, Season, Species, trend)
+  wind2<-wind1 |> dplyr::select(Area, Season, Species, trend)
   names<-c("Area", "Season", "Species", "trend")
   bnew<-c("Area.1", "Season.1", "Species.1", "trend.1")
   cnew<-c("Area.2", "Season.2", "Species.2", "trend.2")
   dnew<-c("Area.3", "Season.3", "Species.3", "trend.3")
   enew<-c("Area.4", "Season.4", "Species.4", "trend.4")
-  a<-wind2 %>% dplyr::filter(Area == "Existing-North")
-  b<-wind2 %>% dplyr::filter(Area == "Proposed-North") %>%
+  a<-wind2 |> dplyr::filter(Area == "Existing-North")
+  b<-wind2 |> dplyr::filter(Area == "Proposed-North") |>
     dplyr::rename_at(dplyr::vars(names), ~ bnew)
-  c<-wind2 %>% dplyr::filter(Area == "Existing-Mid")%>%
+  c<-wind2 |> dplyr::filter(Area == "Existing-Mid")|>
     dplyr::rename_at(dplyr::vars(names), ~ cnew)
-  d<-wind2 %>% dplyr::filter(Area == "Proposed-Mid")%>%
+  d<-wind2 |> dplyr::filter(Area == "Proposed-Mid")|>
     dplyr::rename_at(dplyr::vars(names), ~ dnew)
-  e<-wind2 %>% dplyr::filter(Area == "Existing-South")%>%
+  e<-wind2 |> dplyr::filter(Area == "Existing-South")|>
     dplyr::rename_at(dplyr::vars(names), ~ enew)
-  all<- a %>% cbind(b,c,d,e) %>%
+  all<- a |> cbind(b,c,d,e) |>
     dplyr::select(2:4,7:8,11:12,15:16,19:20)
 
   tab <- kableExtra::kable(all, escape = FALSE,
                     col.names = c("Season", "Species", "Trend", "Species", "Trend", "Species","Trend", "Species","Trend", "Species", "Trend"),
                     caption = "Species with highest probability of occupancy species each season and area, with observed trends",
-                    booktabs = T) %>%
+                    booktabs = T) |>
     kableExtra::add_header_above(c(" " = 1, "Existing - North" = 2, "Proposed - North" = 2,
                                    "Existing - Mid" = 2, "Proposed - Mid" = 2,
-                                   "Existing - South" = 2)) %>%
+                                   "Existing - South" = 2)) |>
     kableExtra::kable_styling(latex_options = c("hold_position", "scale_down"))
 
     return(tab)