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report4_SAG.r
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library(icesTAF)
library(icesFO)
library(sf)
library(ggplot2)
library(dplyr)
## Run utilies
source("bootstrap/utilities.r")
# set values for automatic naming of files:
cap_year <- 2022
cap_month <- "October"
ecoreg_code <- "GS"
##########
#Load data
##########
trends <- read.taf("model/trends.csv")
catch_current <- read.taf("model/catch_current.csv")
catch_trends <- read.taf("model/catch_trends.csv")
#error with number of columns, to check
clean_status <- read.taf("data/clean_status.csv")
###########
## 3: SAG #
###########
#~~~~~~~~~~~~~~~#
# A. Trends by guild
#~~~~~~~~~~~~~~~#
unique(trends$FisheriesGuild)
# 1. Demersal
#~~~~~~~~~~~
plot_stock_trends(trends, guild="demersal", cap_year , cap_month , return_data = FALSE)
ggplot2::ggsave(file_name(cap_year,ecoreg_code,"SAG_Trends_demersal", ext = "png", dir = "report"), width = 178, height = 130, units = "mm", dpi = 300)
dat <- plot_stock_trends(trends, guild="demersal", cap_year , cap_month , return_data = TRUE)
write.taf(dat, file =file_name(cap_year,ecoreg_code,"SAG_Trends_demersal", ext = "csv", dir = "report"))
# 2. Pelagic
#~~~~~~~~~~~
plot_stock_trends(trends, guild="pelagic", cap_year, cap_month , return_data = FALSE)
ggplot2::ggsave(file_name(cap_year,ecoreg_code,"SAG_Trends_pelagic", ext = "png", dir = "report"), width = 178, height = 130, units = "mm", dpi = 300)
dat <- plot_stock_trends(trends, guild="pelagic", cap_year, cap_month , return_data = TRUE)
write.taf(dat,file =file_name(cap_year,ecoreg_code,"SAG_Trends_pelagic", ext = "csv", dir = "report"))
unique(trends$FisheriesGuild)
# 3. Crustacean
#~~~~~~~~~~~
# plot_stock_trends(trends, guild="crustacean", cap_year , cap_month ,return_data = FALSE )
# ggplot2::ggsave(file_name(cap_year,ecoreg_code,"SAG_Trends_crustacean", ext = "png"), path = "report/", width = 178, height = 130, units = "mm", dpi = 300)
#
# dat <- plot_stock_trends(trends, guild="crustacean", cap_year , cap_month , return_data = TRUE)
# write.taf(dat, file =file_name(cap_year,ecoreg_code,"SAG_Trends_crustacean", ext = "csv"), dir = "report" )
#~~~~~~~~~~~~~~~~~~~~~~~~~#
# Ecosystem Overviews plot
#~~~~~~~~~~~~~~~~~~~~~~~~~#
guild <- read.taf("model/guild.csv")
trends2 <- trends %>% filter (StockKeyLabel %in% c("aru.27.5a14",
# "bli.27.5a14",
# "cod.2127.1f14",
# "ghl.27.561214",
"her.27.1-24a514a",
"mac.27.nea",
"reb.2127.dp"
# "reg.27.561214",
# "usk.27.5a14"
))
trends2 <- trends2 [,-1]
colnames(trends2) <- c("FisheriesGuild", "Year", "Metric", "Value")
trends3 <- trends2%>% filter(Metric == "F_FMSY")
trends3 <- trends3 %>% filter(Year > 1960)
# guild2 <- guild %>% filter(Metric == "F_FMSY")
plot_guild_trends(trends3, cap_year, cap_month,return_data = FALSE )
# guild2 <- guild2 %>% filter(FisheriesGuild != "MEAN")
# plot_guild_trends(guild2, cap_year , cap_month,return_data = FALSE )
ggplot2::ggsave(paste0(cap_year, "_", ecoreg_code, "_EO_SAG_GuildTrends_F.png"), path = "report/", width = 178, height = 130, units = "mm", dpi = 300)
# ggplot2::ggsave("2019_BtS_EO_GuildTrends_noMEAN_F.png", path = "report/", width = 178, height = 130, units = "mm", dpi = 300)
trends3 <- trends2 %>% filter(Metric == "SSB_MSYBtrigger")
# guild2 <- guild %>% filter(Metric == "SSB_MSYBtrigger")
# guild3 <- guild2 %>% dplyr::filter(FisheriesGuild != "MEAN")
trends3 <- trends3 %>% filter(Year > 1960)
plot_guild_trends(trends3, cap_year, cap_month,return_data = FALSE )
ggplot2::ggsave(paste0(cap_year, "_", ecoreg_code, "_EO_SAG_GuildTrends_SSB_1960.png"), path = "report/", width = 178, height = 130, units = "mm", dpi = 300)
# ggplot2::ggsave(paste0(year_cap, "_", ecoreg, "_EO_SAG_GuildTrends_SSB_1900.png"), path = "report/", width = 178, height = 130, units = "mm", dpi = 300)
dat <- plot_guild_trends(trends2, cap_year, cap_month ,return_data = TRUE)
write.taf(dat, file =paste0(cap_year, "_", ecoreg_code, "_EO_SAG_GuildTrends.csv"), dir = "report" )
# dat <- trends2[,1:2]
# dat <- unique(dat)
# dat <- dat %>% filter(FisheriesGuild != "MEAN")
# colnames(dat) <- c("StockKeyLabel", "Year")
# dat2 <- sid %>% select(c(StockKeyLabel, StockKeyDescription))
# dat <- left_join(dat,dat2)
# write.taf(dat, file =paste0(year_cap, "_", ecoreg_code, "_EO_SAG_SpeciesGuildList.csv"), dir = "report", quote = TRUE )
#~~~~~~~~~~~~~~~#
# B.Current catches
#~~~~~~~~~~~~~~~#
## Bar plots are not in order, check!!
# 1. Demersal
#~~~~~~~~~~~
bar <- plot_CLD_bar(catch_current, guild = "demersal", caption = T, cap_year , cap_month , return_data = FALSE)
# bar <- plot_CLD_bar(catch_current, guild = "demersal", caption = T, cap_year = 2019, cap_month = "September", return_data = FALSE)
bar_dat <- plot_CLD_bar(catch_current, guild = "demersal", caption = T, cap_year , cap_month , return_data = TRUE)
write.taf(bar_dat, file =file_name(cap_year,ecoreg_code,"SAG_Current_demersal", ext = "csv", dir = "report"))
catch_current <- unique(catch_current)
kobe <- plot_kobe(catch_current, guild = "demersal", caption = T, cap_year , cap_month , return_data = FALSE)
#kobe_dat is just like bar_dat with one less variable
#kobe_dat <- plot_kobe(catch_current, guild = "Demersal", caption = T, cap_year = 2019, cap_month = "September", return_data = TRUE)
png(file_name(cap_year,ecoreg_code,"SAG_Current_demersal", ext = "png", dir = "report"),
width = 131.32,
height = 88.9,
units = "mm",
res = 300)
p1_plot<-gridExtra::grid.arrange(kobe,
bar, ncol = 2,
respect = TRUE, top = "demersal")
dev.off()
# 2. Pelagic
#~~~~~~~~~~~
bar <- plot_CLD_bar(catch_current, guild = "pelagic", caption = T, cap_year, cap_month , return_data = FALSE)
bar_dat <- plot_CLD_bar(catch_current, guild = "pelagic", caption = T, cap_year , cap_month , return_data = TRUE)
write.taf(bar_dat, file =file_name(cap_year,ecoreg_code,"SAG_Current_pelagic", ext = "csv", dir = "report"))
kobe <- plot_kobe(catch_current, guild = "pelagic", caption = T, cap_year , cap_month, return_data = FALSE)
png(file_name(cap_year,ecoreg_code,"SAG_Current_pelagic", ext = "png", dir = "report"),
width = 131.32,
height = 88.9,
units = "mm",
res = 300)
p1_plot<-gridExtra::grid.arrange(kobe,
bar, ncol = 2,
respect = TRUE, top = "pelagic")
dev.off()
# 2. Crustacean
#~~~~~~~~~~~
# bar <- plot_CLD_bar(catch_current, guild = "crustacean", caption = T, cap_year, cap_month , return_data = FALSE)
# bar_dat <- plot_CLD_bar(catch_current, guild = "crustacean", caption = T, cap_year , cap_month , return_data = TRUE)
# write.taf(bar_dat, file =file_name(cap_year,ecoreg_code,"SAG_Current_crustacean", ext = "csv"), dir = "report")
# kobe <- plot_kobe(catch_current, guild = "crustacean", caption = T, cap_year , cap_month , return_data = FALSE)
# png(file_name(cap_year,ecoreg_code,"SAG_Current_crustacean", ext = "png"),
# width = 131.32,
# height = 88.9,
# units = "mm",
# res = 300)
# p1_plot<-gridExtra::grid.arrange(kobe,
# bar, ncol = 2,
# respect = TRUE, top = "crustacean")
# dev.off()
# 6. All
#~~~~~~~~~~~
bar <- plot_CLD_bar(catch_current, guild = "All", caption = T, cap_year , cap_month , return_data = FALSE)
bar_dat <- plot_CLD_bar(catch_current, guild = "All", caption = T, cap_year , cap_month , return_data = TRUE)
write.taf(bar_dat, file =file_name(cap_year,ecoreg_code,"SAG_Current_all", ext = "csv", dir = "report" ))
top_10 <- bar_dat %>% top_n(10, total)
bar <- plot_CLD_bar(top_10, guild = "All", caption = TRUE, cap_year = 2020, cap_month = "September", return_data = FALSE)
# top_10 <- unique(top_10)
kobe <- plot_kobe(top_10, guild = "All", caption = T, cap_year, cap_month , return_data = FALSE)
png(file_name(cap_year,ecoreg_code,"SAG_Current_all", ext = "png", dir = "report"),
width = 137.32,
height = 88.9,
units = "mm",
res = 300)
p1_plot<-gridExtra::grid.arrange(kobe,
bar, ncol = 2,
respect = TRUE, top = "All stocks top 10")
dev.off()
#~~~~~~~~~~~~~~~#
# C. Discards
#~~~~~~~~~~~~~~~#
# No discards at all
# discardsA <- plot_discard_trends(catch_trends, 2022, cap_year , cap_month )
#
# dat <- plot_discard_trends(catch_trends, 2022, cap_year , cap_month , return_data = TRUE)
# write.taf(dat, file =file_name(cap_year,ecoreg_code,"SAG_Discards_trends", ext = "csv", dir = "report" ))
#
# catch_trends2 <- catch_trends %>% filter(discards > 0)
# discardsB <- plot_discard_current(catch_trends3, year,position_letter = "b)", cap_year , cap_month , caption = FALSE)
#
# discardsC <- plot_discard_current(catch_trends, 2021,position_letter = "c)", cap_year, cap_month )
#
# dat <- plot_discard_current(catch_trends, 2021, cap_year, cap_month , return_data = TRUE)
# write.taf(dat, file =file_name(cap_year,ecoreg_code,"SAG_Discards_current", ext = "csv"), dir = "report" )
#
# cowplot::plot_grid(discardsA, discardsC, align = "h", nrow = 1, rel_widths = 1, rel_heights = 1)
# ggplot2::ggsave(file_name(cap_year,ecoreg_code,"_FO_SAG_Discards", ext = "png"), path = "report/", width = 220.32, height = 88.9, units = "mm", dpi = 300)
# png("report/2019_BI_FO_Figure7.png",
# width = 137.32,
# height = 88.9,
# units = "mm",
# res = 300)
# p1_plot<-gridExtra::grid.arrange(discardsA,
# discardsB, ncol = 2,
# respect = TRUE)
# dev.off()
#~~~~~~~~~~~~~~~#
#D. ICES pies
#~~~~~~~~~~~~~~~#
plot_status_prop_pies(clean_status, cap_month,cap_year)
# will make qual_green just green
unique(clean_status$StockSize)
clean_status$StockSize <- gsub("qual_GREEN", "GREEN", clean_status$StockSize)
unique(clean_status$FishingPressure)
clean_status$FishingPressure <- gsub("qual_RED", "RED", clean_status$FishingPressure)
# plot_status_prop_pies(clean_status, "September", "2019")
plot_status_prop_pies(clean_status, cap_month,cap_year)
ggplot2::ggsave(file_name(cap_year,ecoreg_code,"SAG_ICESpies", ext = "png", dir = "report"), width = 178, height = 178, units = "mm", dpi = 300)
dat <- plot_status_prop_pies(clean_status, cap_month,cap_year, return_data = TRUE)
write.taf(dat, file= file_name(cap_year,ecoreg_code,"SAG_ICESpies", ext = "csv", dir = "report"))
#~~~~~~~~~~~~~~~#
#E. GES pies
#~~~~~~~~~~~~~~~#
#Need to change order and fix numbers
plot_GES_pies(clean_status, catch_current, cap_month,cap_year)
ggplot2::ggsave(file_name(cap_year,ecoreg_code,"SAG_GESpies", ext = "png", dir = "report"), width = 178, height = 178, units = "mm", dpi = 300)
dat <- plot_GES_pies(clean_status, catch_current, cap_month,cap_year, return_data = TRUE)
write.taf(dat, file= file_name(cap_year,ecoreg_code,"SAG_GESpies", ext = "csv", dir = "report"))
#~~~~~~~~~~~~~~~#
#F. ANNEX TABLE
#~~~~~~~~~~~~~~~#
dat <- format_annex_table(clean_status, 2022)
dat <- read.taf("report/2022_GS_FO_annex_table.csv")
format_annex_table_html(dat,ecoreg_code,cap_year)
write.taf(dat, file = file_name(cap_year,ecoreg_code,"annex_table", ext = "csv", dir = "report"), quote=TRUE)
# This annex table has to be edited by hand,
# For SBL and GES only one values is reported,
# the one in PA for SBL and the one in MSY for GES