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sst_plot.r.Rout
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sst_plot.r.Rout
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R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
>
> ## preparation
> library(aceecostats)
> library(raster)
Loading required package: sp
> library(feather)
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:raster’:
intersect, select, union
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
>
> ## local path to required cache files
> datapath <- "/mnt/acebulk"
>
> ## date range for the sparkline
> sparkline_domain <- aceecostats:::mk_sparkline_domain()
>
> outpdf <- "inst/workflow/graphics/sst_density001.pdf"
>
> ras <- raster(file.path(datapath, "sst_raster.grd"))
> ## cell_tab <- read_feather(file.path(datapath, "sst_cell_tab.feather"))
> summ_tab <- read_feather(file.path(datapath, "sst_summ_tab.feather"))
> raw_tab <- read_feather(file.path(datapath, "sst_raw_tab.feather"))
> varlabel <- function(ttext) {
+ bquote(.(ttext)~ "SST" ~ (degree*C))
+ }
>
>
> # ## here Continent just means High Latitude
> # summ_tab$Zone[summ_tab$Zone == "Continent"] <- "High-Latitude"
> # raw_tab$Zone[raw_tab$Zone == "Continent"] <- "High-Latitude"
>
> seclab <- 28
> min_max <- c(-2, 30)
> usr <- c(-5, 100, -5, 6e9)
> dolog <- ""
>
>
> lwdths <- c(6,4,2,1)
> lcols <- grey(seq(1, 0, length = length(unique(alldecades)) + 2))[-c(1, 2)]
>
> dplot <- T
>
> op1 <- options(scipen = -1)
> if (dplot) pdf(outpdf)
> den.range <- c(0, 1.5)
> seas <- "Summer"
> zone <- "High-Latitude"
> ll <- list()
> for (seas in c( "Summer", "Winter")) {
+ for (zone in c("High-Latitude", "Mid-Latitude")) {
+
+ layout(layout_m())
+ op <- par(mar=c(0,0,0,0), oma=c(2.5, 0.95, 0.5, 0.5), tcl=0.2, cex=1.25, mgp=c(3, 0.25, 0), cex.axis=0.75, col="gray40", col.axis="gray40", fg="gray40")
+ ## DENSITY PLOTS
+ for (sector in c("Atlantic", "Indian", "EastPacific", "WestPacific")) {
+ #this_area <- dplyr::filter(total_areas, Zone == zone & SectorName == sector)
+ #den.range <- c(0, this_area$area_max)
+ titletext<- paste(seas, zone)
+ asub <- dplyr::filter(raw_tab, SectorName == sector & Zone == zone & Season == seas)
+ if (nrow(asub) < 10) {
+ dummyplot()
+ dummyplot()
+ next;
+ }
+ plot(min_max, den.range, type = "n", axes = FALSE, xlab = "", ylab = "")
+ polygon(expand.grid(x = usr[1:2], y = usr[3:4])[c(1, 2, 4, 3), ], col = paste0(sector_colour(sector),40))
+ if (sector %in% c("Atlantic", "EastPacific")) mtext("density", side = 2)
+
+ for (k in seq_along(lcols)) {
+ vals_wgt <- asub %>% filter(decade == decselect(k)) %>% dplyr::select(min, area)
+ if (nrow(vals_wgt) < 1 | all(is.na(vals_wgt$min))) next
+ dens.df <- aceecostats:::do_density(vals_wgt$min, w = vals_wgt$area)
+ lines(dens.df, col=lcols[k], lwd=lwdths[k])
+
+ }
+ axis(2, at = c(0.25, 0.5, 0.75, 1), cex.axis = 0.5, las = 1, mgp = c(3, -1, 0))
+
+ #axis(2, cex.axis = 0.5, las = 1, mgp = c(3, -1, 0))
+ box()
+ mtext(side=1, varlabel(titletext) ,outer =TRUE, line=1.5, cex=1)
+
+ plot(min_max, den.range, type = "n", axes = FALSE, xlab = "", ylab = , log = dolog)
+ polygon(expand.grid(x = usr[1:2], y = usr[3:4])[c(1, 2, 4, 3), ], col = paste0(sector_colour(sector),40))
+ if (grepl("Pacific", sector)) axis(1)
+ if (sector %in% c("Atlantic", "EastPacific")) mtext("density", side = 2)
+ text(seclab[1], den.range[2]*0.9, lab = sector_name(sector), cex=0.5)
+
+ for (k in seq_along(lcols)) {
+ vals_wgt <- asub %>% filter(decade == decselect(k)) %>% dplyr::select(max, area)
+ if (nrow(vals_wgt) < 1 | all(is.na(vals_wgt$max))) next;
+ #dens.df <- do_hist(vals_wgt$max, w = vals_wgt$area)
+ dens.df <- aceecostats:::do_density(vals_wgt$max, w = vals_wgt$area)
+ lines(dens.df, col=lcols[k], lwd=lwdths[k])
+ }
+ #axis(2, at = c(0.25, 0.5, 0.75, 1), cex.axis = 0.5, las = 1, mgp = c(3, -1, 0))
+
+ #axis(2, cex.axis = 0.5, las = 1, mgp = c(3, -1.95, 0))
+ box()
+ mtext(side=1, varlabel(titletext) ,outer =TRUE, line=1.5, cex=1)
+
+ }
+ mtext(side=1, varlabel(titletext) ,outer =T, line=1.5, cex=1)
+ ## SPARKLINES
+ for (sector in c("Atlantic", "Indian", "EastPacific", "WestPacific")) {
+ asub <- dplyr::filter(summ_tab, SectorName == sector & Zone == zone & Season == seas)
+ if (nrow(asub) < 10) {
+ dummyplot()
+ dummyplot()
+ next;
+ }
+
+ ## get the shoulder season
+ shouldersub <- dplyr::filter(summ_tab, SectorName == sector & Zone == zone & Season == c(Summer = "Autumn", Winter = "Spring")[seas])
+ sparkline_range <- range(c(asub$min, shouldersub$min))
+ plot(sparkline_domain, sparkline_range, type = "n", axes = FALSE, xlab = "", ylab = "")
+ segmentlines(cbind(asub$date, asub$min), col = lcols[asub$decade])
+ ## do the shoulder season
+ segmentlines(cbind(shouldersub$date, shouldersub$min), col = lcols[shouldersub$decade], lty = 2)
+ abline(h = mean(asub$min))
+ textheadtail(asub$date, asub$min)
+
+ sparkline_range <- range(c(asub$max, shouldersub$max))
+ plot(sparkline_domain, sparkline_range, type = "n", axes = FALSE, xlab = "", ylab = "")
+ segmentlines(cbind(asub$date, asub$max), col = lcols[asub$decade])
+ abline(h = mean(asub$max))
+ textheadtail(asub$date, asub$max)
+ ## do the shoulder season
+ segmentlines(cbind(shouldersub$date, shouldersub$max), col = lcols[shouldersub$decade], lty = 2)
+
+ }
+ par(op)
+
+ }}
There were 50 or more warnings (use warnings() to see the first 50)
> options(op1)
> if (dplot) dev.off()
null device
1
>
>
>
> proc.time()
user system elapsed
50.064 31.916 81.981