rendering quarto html (pdf took too long)

.Rhistory

@@ -1,122 +1,3 @@
-species <- unique(data$SPECIES_CD)
-for (i in species) {
-# Subset data for the current species
-species_data <- filter(data, SPECIES_CD == i)
-# format indicator object -----------------------------
-datdata <- species_data$YEAR
-inddata <- data.frame(species_data$density)
-labs <- c(i, "Density", "")
-indnames <- data.frame(matrix(labs, nrow = 3, byrow = F))
-s <- list(labels = indnames, indicators = inddata, datelist = datdata)
-class(s) <- "indicatordata"
-# save and plot -----------------------------------------
-plotIndicatorTimeSeries(s)
-inddata <- s
-save(inddata, file = paste("indicator_objects/RUVdensity_", j, "_", i, ".RData", sep = ""))
-}
-}
-calibrated = read.csv("indicator_data/RVC/calibrated_species.csv")
-prico = readRDS("indicator_data/RVC/prico_2001_2021_calibrated.rds")
-sttstj = readRDS("indicator_data/RVC/sttstj_2001_2021_calibrated.rds")
-stx = readRDS("indicator_data/RVC/stx_2001_2021_calibrated.rds")
-## Make a list of species
-## You can use full scientific names, common names, or
-## species codes (first 3 letters of genus, and first 4 of species)
-## Only scientific names are case-sensitive
-spcs = c("OCY CHRY", "LUT ANAL", "BAL VETU", "EPI GUTT", "SPA AURO", "SPA VIRI")
-regions = c("PRICO","STTSTJ","STX")
-for(j in regions) {
-# call data for the current region
-dat = switch(j,
-"PRICO" = prico,
-"STTSTJ" = sttstj,
-"STX" = stx)
-## Calculate statistics for entire sampling domain
-ddens = getDomainDensity(dat, species = spcs)
-# Convert SPECIES_CD to factor to ensure correct ordering in plots
-ddens$SPECIES_CD <- factor(ddens$SPECIES_CD)
-species <- unique(ddens$SPECIES_CD)
-for (i in species) {
-# Subset data for the current species
-species_data <- filter(ddens, SPECIES_CD == i)
-# format indicator object -----------------------------
-datdata <- species_data$YEAR
-inddata <- data.frame(species_data$density)
-labs <- c(i, "Density", "")
-indnames <- data.frame(matrix(labs, nrow = 3, byrow = F))
-s <- list(labels = indnames, indicators = inddata, datelist = datdata)
-class(s) <- "indicatordata"
-# save and plot -----------------------------------------
-plotIndicatorTimeSeries(s)
-inddata <- s
-save(inddata, file = paste("indicator_objects/RUVdensity_", j, "_", i, ".RData", sep = ""))
-}
-}
-library(rvc)
-calibrated = read.csv("indicator_data/RVC/calibrated_species.csv")
-prico = readRDS("indicator_data/RVC/prico_2001_2021_calibrated.rds")
-sttstj = readRDS("indicator_data/RVC/sttstj_2001_2021_calibrated.rds")
-stx = readRDS("indicator_data/RVC/stx_2001_2021_calibrated.rds")
-## Make a list of species
-## You can use full scientific names, common names, or
-## species codes (first 3 letters of genus, and first 4 of species)
-## Only scientific names are case-sensitive
-spcs = c("OCY CHRY", "LUT ANAL", "BAL VETU", "EPI GUTT", "SPA AURO", "SPA VIRI")
-regions = c("PRICO","STTSTJ","STX")
-for(j in regions) {
-# call data for the current region
-dat = switch(j,
-"PRICO" = prico,
-"STTSTJ" = sttstj,
-"STX" = stx)
-## Calculate statistics for entire sampling domain
-ddens = getDomainDensity(dat, species = spcs)
-# Convert SPECIES_CD to factor to ensure correct ordering in plots
-ddens$SPECIES_CD <- factor(ddens$SPECIES_CD)
-species <- unique(ddens$SPECIES_CD)
-for (i in species) {
-# Subset data for the current species
-species_data <- filter(ddens, SPECIES_CD == i)
-# format indicator object -----------------------------
-datdata <- species_data$YEAR
-inddata <- data.frame(species_data$density)
-labs <- c(i, "Density", "")
-indnames <- data.frame(matrix(labs, nrow = 3, byrow = F))
-s <- list(labels = indnames, indicators = inddata, datelist = datdata)
-class(s) <- "indicatordata"
-# save and plot -----------------------------------------
-plotIndicatorTimeSeries(s)
-inddata <- s
-save(inddata, file = paste("indicator_objects/RUVdensity_", j, "_", i, ".RData", sep = ""))
-}
-}
-for(j in regions) {
-# call data for the current region
-dat = switch(j,
-"PRICO" = prico,
-"STTSTJ" = sttstj,
-"STX" = stx)
-## Calculate statistics for entire sampling domain
-ddens = getDomainDensity(dat, species = spcs)
-# Convert SPECIES_CD to factor to ensure correct ordering in plots
-ddens$SPECIES_CD <- factor(ddens$SPECIES_CD)
-species <- unique(ddens$SPECIES_CD)
-for (i in species) {
-# Subset data for the current species
-species_data <- filter(ddens, SPECIES_CD == i)
-# format indicator object -----------------------------
-datdata <- species_data$YEAR
-inddata <- data.frame(species_data$density)
-labs <- c(j, paste("Density", i), "")
-indnames <- data.frame(matrix(labs, nrow = 3, byrow = F))
-s <- list(labels = indnames, indicators = inddata, datelist = datdata)
-class(s) <- "indicatordata"
-# save and plot -----------------------------------------
-plotIndicatorTimeSeries(s)
-inddata <- s
-save(inddata, file = paste("indicator_objects/RUVdensity_", j, "_", i, ".RData", sep = ""))
-}
-}
 load("~/My Github Projects/Caribbean-ESR/indicator_objects/RUVdensity_PRICO_BAL VETU.RData")
 load("~/My Github Projects/Caribbean-ESR/indicator_objects/RUVdensity_PRICO_BAL VETU.RData")
 test = readRDS("indicator_objects/RUVdensity_PRICO_BAL VETU.RData")
@@ -510,3 +391,122 @@ install.packages("ncdf4")
 library(ncdf4)
 nc_data = nc_open("../../../Downloads/0190272/2.2/data/0-data/2006-2010.S_density/Year-2006-04.S_density.nc")
 View(nc_data)
+library(plotTimeSeries)
+library(spam)
+load("../indicator_objects/OceanNAICS.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, plotrownum = 2, trendAnalysis = F, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/gini.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, plotrownum = 2, trendAnalysis = F, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/NCRMP_coral_cover_richness.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+plotIndicatorTimeSeries(inddata, trendAnalysis = T)
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/OA.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/DegreeHeatingWeeks.RData")
+plotIndicatorTimeSeries(ind, trendAnalysis = F)
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/OceanNAICS.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, plotrownum = 2, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:8, plotrownum = 2, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:8, plotrownum = 3, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/OA.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+plotIndicatorTimeSeries(inddata, trendAnalysis = T)
+load("../indicator_objects/ACEindex.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/ACEindex.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/OA.RData")
+load("../indicator_objects/ACEindex.RData")
+load("../indicator_objects/turbidity.RData")
+load("../indicator_objects/turbidity.RData")
+load("../indicator_objects/turbidity.RData")
+load("../indicator_objects/ACEindex.RData")
+plotIndicatorTimeSeries(ind, trendAnalysis = F)
+plotIndicatorTimeSeries(ind, trendAnalysis = T)
+load("../indicator_objects/turbidity.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 1, trendAnalysis = T)
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T)
+load("../indicator_objects/beach_litter_un_carib.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/marine_debris.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+load("../indicator_objects/carib_Chl.RData")
+plotIndicatorTimeSeries(ind, trendAnalysis = F)
+load("../indicator_objects/earthquakes.RData")
+plotIndicatorTimeSeries(ind, trendAnalysis = F)
+plotIndicatorTimeSeries(ind, trendAnalysis = T)
+load("../indicator_objects/disturbance.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = F)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, trendAnalysis = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/Sargassum.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = T)
+load("../indicator_objects/sargassum_innundation_monthly_mean_hu.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, sublabel = T, trendAnalysis = T)
+load("../indicator_objects/hotel_occupancy_rates_USVI_and_PR).RData")
+load("../indicator_objects/hotel_occupancy_rates_USVI_and_PR.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, sublabel = T, trendAnalysis = T)
+load("../indicator_objects/hotel_occupancy.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, sublabel = T, trendAnalysis = T)
+load("../indicator_objects/OA.RData")
+plotIndicatorTimeSeries(inddata, trendAnalysis = T)
+load("../indicator_objects/fish_density.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/fish_density.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/NCRMP_coral_cover_richness.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:6, sublabel = T, trendAnalysis = F)
+load("../indicator_objects/coral_spprichness_cover.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:4, sublabel = T, trendAnalysis = F)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:4, sublabel = T, trendAnalysis = T)
+load("../indicator_objects/Carib_SST.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/total_landings.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:9, plotrownum = 3, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, plotrownum = 3, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, plotcolnum = 3, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, hgtadj = 5, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/total_landings.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, , trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/total_landings.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/gini.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/total_rec_catch.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, , trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, widadj = 4, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, widadj = 10, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/DegreeHeatingWeeks.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, trendAnalysis = T, sublabel = T, anom = stmon)
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, trendAnalysis = T, sublabel = T, anom = stmon)
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, trendAnalysis = T, sublabel = T, anom = mon)
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, trendAnalysis = T, sublabel = T, dateformat = "%Y%M")
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, trendAnalysis = T, sublabel = T, dateformat = "%Y%m")
+plotIndicatorTimeSeries(ind, coltoplot = 1:2, trendAnalysis = T, sublabel = T, dateformat = "%Y%m", plotrownum = 2, plotcolnum = 1)
+load("../indicator_objects/turbidity.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, dateformat = "%m%-%Y")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, dateformat = "%m-%Y")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, dateformat = "%m-%Y", sublabel = T)
+load("../indicator_objects/Carib_SST.RData")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, plotrownum = 2, trendAnalysis = T, sublabel = T, dateformat = "%m-%Y")
+plotIndicatorTimeSeries(ind, coltoplot = 1:3, trendAnalysis = T, sublabel = T, dateformat = "%m-%Y")
+load("../indicator_objects/carib_Chl.RData")
+plotIndicatorTimeSeries(ind, trendAnalysis = F, dateformat = "%m-%Y")
+plotIndicatorTimeSeries(ind, trendAnalysis = T, dateformat = "%m-%Y")
+load("../indicator_objects/sargassum_innundation_monthly_mean_hu.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:3, sublabel = T, trendAnalysis = T, dateformat = "%Y%b")
+load("../indicator_objects/hotel_occupancy_rates_USVI_and_PR.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, sublabel = T, trendAnalysis = T, dateformat = "%Y%b")
+load("../indicator_objects/hotel_occupancy.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:2, sublabel = T, trendAnalysis = T, dateformat = "%Y%b")
+load("../indicator_objects/landings.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:6, trendAnalysis = T, sublabel = T)
+load("../indicator_objects/total_landings.RData")
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, plotrownum = 3, plotcolnum = 3, trendAnalysis = T, sublabel = T)

.quarto/cites/index.json

@@ -1 +1 @@
-{"index.qmd":[],"OA.qmd":[],"Report_book_files\\Report4.qmd":[],"Report_book_files\\FMP_objectives.qmd":[],"Report_book_files\\Discussion_material.qmd":[],"Report_book_files\\Risk_indicators.qmd":[],"Lab-report\\OA.qmd":[],"Report_book_files\\Performance_indicators.qmd":[],"Report_book_files\\Intro_text.qmd":[]}
+{"Report_book_files\\Discussion_material.qmd":[],"OA.qmd":[],"Report_book_files\\Intro_text.qmd":[],"index.qmd":[],"Report_book_files\\FMP_objectives.qmd":[],"Report_book_files\\Performance_indicators.qmd":[],"Report_book_files\\Risk_indicators.qmd":[],"Report_book_files\\Report4.qmd":[],"Lab-report\\OA.qmd":[]}

.quarto/xref/40871caf

@@ -1 +1 @@
-{"headings":["executive-summary"],"entries":[],"options":{"chapters":true}}
+{"entries":[],"options":{"chapters":true},"headings":["executive-summary"]}

Report_book_files/Performance_indicators.qmd

@@ -26,7 +26,7 @@ plotIndicatorTimeSeries(inddata, coltoplot = 1:6, trendAnalysis = T, sublabel =
 
 ```{r, message = FALSE, warnings = FALSE}
 load("../indicator_objects/total_landings.RData")
-plotIndicatorTimeSeries(inddata, coltoplot = 1:9, trendAnalysis = T, sublabel = T)
+plotIndicatorTimeSeries(inddata, coltoplot = 1:9, plotrownum = 3, plotcolnum = 3, trendAnalysis = T, sublabel = T)
 ```
 
 ```{r}