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post_proc_GoM_ATL.r
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rm(list=ls())
# load libraries --------------------------------------
if (!"ncdf4" %in% installed.packages()) install.packages("ncdf4", repos='http://cran.us.r-project.org')
if (!"sp" %in% installed.packages()) install.packages("sp", repos='http://cran.us.r-project.org')
if (!"maps" %in% installed.packages()) install.packages("maps", repos='http://cran.us.r-project.org')
library(maps)
library(ncdf4)
library(sp)
# specify folder for processing ------------------------
model <- "HYCOM"
spp <- "mutton"
fold <- paste0("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/FINALRUNS_DEC2020/final_for_subsample/", model, "_", spp)
setwd(fold)
if (model == "Mercator") { d <- read.table("C://Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/scaledGOMATLrel20132017.txt") }
if (model == "HYCOM") { nd <- read.table("C://Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/scaledGOMATLrel2019.txt")
d <- rbind(nd, nd, nd, nd, nd); d$V6 <- sort(rep(2015:2019, nrow(nd))) }
if (model == "SABGOM") { d <- read.table("C://Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/scaledGOMATLrel20062010.txt") }
if (model == "Atl-HYCOM") { d <- read.table("C://Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/scaledGOMATLrel200809.txt") }
# concatenate connectivity files -------------------
filelist <- list.files(path = ".", pattern="con_file") # find files
dat <- read.table(filelist[1])
filelist <- filelist[-1]
for (i in filelist) { newdat <- read.table(i); dat <- rbind(dat, newdat) }
colnames(dat) <- c("rel_poly","ret_poly","ret_yr","ret_mo","ret_d","age","ret_dep","rel_yr","rel_mo","rel_d")
################ NEW ##################
#dat <- dat[dat$ret_poly != 77, ]
#dat <- dat[dat$ret_poly != 78, ]
#dat <- dat[dat$ret_poly != 79, ]
##########################################
dat$ret_reg <- "GOM"
dat$ret_reg[which(dat$ret_poly >= 76)] <- "ATL"
dat$rel_reg <- "GOM"
dat$rel_reg[which(dat$rel_poly >= 76)] <- "ATL"
table(dat$rel_reg, dat$ret_reg)
sum(d$V5)
nrow(dat) / sum(d$V5)
# process con file ------------------------------
d$reg <- "GOM"
d$reg[which(d$V1 >= 76)] <- "ATL"
tapply(d$V5, d$reg, sum)
table(dat$rel_reg, dat$ret_reg)
tab <- table(dat$rel_reg, dat$ret_reg)
aa <- tab[1, 1]; aa # 0.8394142 = spawned in ATL, recruited in ATL
ga <- tab[2, 1]; ga # 0.01136878 = spawned in GOM, recruited in ATL
gg <- tab[2, 2]; gg # 0.4308186 = spawned in GOM, recruited in GOM
ag <- tab[1, 2]; ag # 0.0003637645 = spawned in ATL, recruited in GOM
rel <- tapply(d$V5, list(d$reg), sum)
rel
gg / rel[2] * 100 # % Gulf-spawned eggs settling in Gulf
ga / rel[2] * 100 # % Gulf-spawned eggs settling in Atl
aa / rel[1] * 100 # % Atl-spawned eggs settling in Atl
aa / (aa + ga) * 100 # of all recruits in Atlantic, what % came from Atl
ga / (aa + ga) * 100 # of all recruits in Atlantic, what % came from Gulf
ga/ length(which(dat$ret_poly >= 77))*100 # RECORD THIS NUMBER
gomatl <- c(model, spp, ga/ length(which(dat$ret_poly >= 77))*100)
#write.table(matrix(gomatl, 1, 3), file = "C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/FINALRUNS_DEC2020/outputs.txt", append = T, col.names = F)
surv <- table(dat$rel_reg)
surv/rel
#dat <- dat[which(dat$rel_poly>64),]
barplot(table(dat$rel_reg, dat$ret_yr), beside=T)
table(dat$rel_reg, dat$rel_poly) # polygon 68 is first to have successful recruitment to S Atl
(table(dat$rel_reg) / nrow(dat)) * 100
# check particle behaviors ---------------------
rm(list = ls()[-which(ls() %in% c("model", "spp", "fold"))])
getwd()
folder <- "C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/plots/" # folder for final plots
lon <- c()
lat <- c()
dep <- c()
cod <- c()
numlarv <- 500
for (m in 1:length(grep("traj", dir()))) {
nam <- paste("traj_file_", m, ".nc", sep="")
nc <- nc_open(nam, write=FALSE, readunlim=TRUE, verbose=FALSE)
v2 <- nc$var[[2]]
lon1 <- ncvar_get(nc, v2)
lon1[which(lon1>10000)] <- NA
v3 <- nc$var[[3]]
lat1 <- ncvar_get(nc, v3)
lat1[which(lat1>10000)] <- NA
v4 <- nc$var[[4]]
dep1 <- ncvar_get(nc, v4)
dep1[which(dep1>10000)] <- NA
v6 <- nc$var[[6]]
cod1 <- ncvar_get(nc, v6) # 0 can still move; -1 left area; -2 close to land; -3 dead; -4 settled; -5 no oceanographic data
lon <- cbind(lon, lon1)
lat <- cbind(lat, lat1)
dep <- cbind(dep, dep1)
cod <- c(cod, cod1)
nc_close(nc)
}
# check! should have only -4, -1, and 0
table(cod) # 0 can still move; -1 left area; -2 close to land; -3 dead; -4 settled; -5 no oceanographic data
length(which(cod == (-2))) / length(cod) * 100 # percent of particles messed up
hist(dep[2,which(cod==(-1))])
hist(dep[2,])
deplast <- rep(NA, ncol(dep))
for (i in 1:ncol(dep)) { deplast[i] <- dep[max(which(!is.na(dep[, i]))), i] }
hist(deplast[which(cod == (-4))])
mean(deplast[which(cod == (-4))])
deps <- deplast[which(cod == (-4))]
table(deps >= 15 & deps <=45) / length(deps)
bad <- data.frame(cbind(lon[1, which(cod == (-2))]-360, lat[1, which(cod == (-2))]))
bad$V3 <- paste(bad[,1], bad[,2])
matrix(unique(bad$V3))
dev.off()
par(mfrow=c(6,5), mex=0.6)
for (i in 1:30) { hist(dep[i,], breaks=seq(0,100,5)) }
table(dep[2,]==0)/ncol(dep)
#table(dep[2,]<10)/ncol(dep)
#table(dep[2,]>10 & dep[2,]<20)/ncol(dep)
#table(dep[2,]>20 & dep[2,]<30)/ncol(dep)
dev.off()
matplot(-dep[,seq(1, ncol(dep), length.out=100)], col="#FF00FF30", pch=19, type="l",
xlab = "days after spawning", ylab = "depth of particle")
axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
#matplot(-dep, col="#FF00FF30", pch=19, type="l",
# xlab = "days after spawning", ylab = "depth of particle")
#axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
# plot by code number
#par(mfrow=c(4,1), mar = c(4,4,2,1), mgp=c(2.25,1,0))
#matplot(-dep[,which(cod == (0))], col="#FF00FF05", pch=19, type="l", ylim = c(-90, 0),
# xlab = "days after spawning", ylab = "depth of particle", main = "can still move")
#axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
#matplot(-dep[,which(cod == (-1))], col="#FF00FF30", pch=19, type="l", ylim = c(-90, 0),
# xlab = "days after spawning", ylab = "depth of particle", main = "left area")
#axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
matplot(-dep[,which(cod == (-2))], col="#FF00FF30", pch=19, type="l", ylim = c(-90, 0),
xlab = "days after spawning", ylab = "depth of particle", main = "close to land")
axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
#matplot(-dep[,which(cod == (-4))], col="#FF00FF05", pch=19, type="l", ylim = c(-90, 0),
# xlab = "days after spawning", ylab = "depth of particle", main = "settled")
#axis(1, at=1:31, lab=rep("", 31), tck= -0.01)
# end plot -------
#plot(dens, -dep[2,], col="#FF00FF30")
#plot(diam, -dep[2,], col="#FF00FF30")
#min(dens)
#max(dens)
########################## PLOT TRAJECTORIES ###############################
load("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/GEBCO_bathy_hires.RData") # stored GEBCO data and color scheme
numlarv <- 500
# i <- which(cod == (-4))
# la <- rep(NA, length(i))
# for (j in i) { la[j] <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])] }
# maxlat[m] <- mean(la, na.rm=T) }
# 4-panel plot of particle states
dev.off()
png(filename = paste0(folder, "statusCheck-", model, "-", spp, ".png"), units="in", width=8, height=8, pointsize=12, res=72*20)
par(mfrow = c(2, 2), mex = 0.5, mgp = c(1,1,0))
map('usa', xlim=c(-90, -76), ylim=c(23, 35), col=1)
axis(1); axis(2); box(); mtext(side = 3, line = 1, "too close to land")
i <- which(cod == (-2))
k <- i #[seq(1, length(i), length.out=numlarv)]
for (j in k) { lines(lon[,j]-360, lat[,j], col="#FF00FF20")
lo <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
la <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])]
points(lo, la, col="#FF000010", pch=19, cex=1) }
points(lon[1, i]-360, lat[1, i], col = "#00000020", pch = 19)
map('usa', xlim=c(-90, -76), ylim=c(23, 35), col=1)
axis(1); axis(2); box(); mtext(side = 3, line = 1, "left area")
i <- which(cod == (-1)) # -1 left area
k <- i[seq(1, length(i), length.out=numlarv)]
for (j in k) {
points(lon[1,j]-360, lat[1,j], col="#00000050", pch=19, cex=1)
lines(lon[,j]-360, lat[,j], col="#FF00FF20") }
map('usa', xlim=c(-90, -76), ylim=c(23, 35), col=1)
axis(1); axis(2); box(); mtext(side = 3, line = 1, "can still move")
i <- which(cod == (0)) # 0 can still move
k <- i[seq(1, length(i), length.out=numlarv)]
for (j in k) {
lo <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
la <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])]
points(lon[1,j]-360, lat[1,j], col="#00000050", pch=19, cex=1)
lines(lon[,j]-360, lat[,j], col="#FF00FF20")
if (lon[1,j]-360 < (-81.7)) { points(lo, la, col="#00FF0090", pch=19, cex=1.2) } else {
points(lo, la, col="#FF000050", pch=19, cex=1) } }
map('usa', xlim=c(-90, -76), ylim=c(23, 35), col=1)
axis(1); axis(2); box(); mtext(side = 3, line = 1, "settled")
i <- which(cod == (-4)) # -4 settled
k <- i[seq(1, length(i), length.out=numlarv)]
for (j in k) {
lo <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
la <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])]
points(lon[1,j]-360, lat[1,j], col="#00000025", pch=19, cex=1)
lines(lon[,j]-360, lat[,j], col="#FF00FF20")
if (lon[1, j]-360 < (-81.7)) { points(lo, la, col="#00FF0090", pch=19, cex=1) } else {
points(lo, la, col="#FF000050", pch=19, cex=1) } }
# plot all particles spawned in Gulf that settled in Atl ------------------
dev.off()
png(filename = paste0(folder, "GoMtoAtl-", model, "-", spp,".png"), units="in", width=4, height=6, pointsize=12, res=72*20)
par(mar = c(3, 3, 2, 2))
map('usa', xlim=c(-87.75, -75.25), ylim=c(23, 35.75), col=1)
image(x[seq(1, 3360, 5)], y[seq(1, 3360, 5)], z[seq(1, 3360, 5), seq(1, 3360, 5)], col=cols, axes=T, xlab="", ylab="", add=T)
axis(1); axis(2, las = 2); box()
mtext(side = 3, line = 1, paste(model, "-", spp), font = 2, cex = 1.2)
k <- which(cod == (-4))
k <- k[seq(1, length(k), 20)] # change to 2 or 3
for (j in k) {
lo <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
la <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])]
if (lon[1,j]-360 < (-81.7) & lo > (-81.7)) {
points(lon[1,j]-360, lat[1,j], col="#00FF0070", pch=19, cex=0.5)
lines(lon[,j]-360, lat[,j], col="#FFFF0030")
points(lo, la, col="#FF000090", pch=19, cex=0.5) }
}
dev.off()
#abline(v = -81.7)
#le <- length(which(cod == (-4)))
#endlo <- rep(NA, le)
#stalo <- rep(NA, le)
#for (i in 125270:le) {
# j <- which(cod == (-4))[i]
#endlo[i] <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
#stalo[i] <- lon[1, j] - 360 }
#gg <- length(which(stalo < (-81.7) & endlo < (-81.7))); gg
#ga <- length(which(stalo < (-81.7) & endlo >= (-81.7))); ga
#aa <- length(which(stalo >= (-81.7) & endlo >= (-81.7))); aa
#ag <- length(which(stalo >= (-81.7) & endlo < (-81.7))); ag
#aa / (aa + ga)
# all trajectories on one map ---------------------------------
png(filename = paste0(folder, "allTrajectories-", model, "-", spp, ".png"), units="in", width=6, height=9, pointsize=12, res=72*20)
par(mar = c(3, 3, 2, 2))
map('usa', xlim=c(-87.75, -75.25), ylim=c(23, 35.75), col=1)
image(x[seq(1, 3360, 5)], y[seq(1, 3360, 5)], z[seq(1, 3360, 5), seq(1, 3360, 5)], col=cols, axes=T, xlab="", ylab="", add=T)
axis(1); axis(2, las = 2); box()
mtext(side = 3, line = 1, paste(model, "-", spp), font = 2, cex = 1.2)
i <- 1:length(cod)
k <- i[seq(1, length(i), length.out = 100)] # change to 300
for (j in k) { lines(lon[,j]-360, lat[,j], col="#00000030") }
i <- which(cod == (-4))
k <- i[seq(1, length(i), length.out=100)]
for (j in k) {
lo <- lon[!is.na(lon[,j]),j][length(lon[!is.na(lon[,j]),j])] - 360
la <- lat[!is.na(lat[,j]),j][length(lat[!is.na(lat[,j]),j])]
lines(lon[,j]-360, lat[,j], col = "#FF00FF30")
points(lon[1,j]-360, lat[1,j], col="#00000050", pch=19, cex=1)
if (lon[1,j]-360 < (-81.7)) { points(lo, la, col="#FF000050", pch=19, cex=1.2) } else {
points(lo, la, col="#FFFF0050", pch=19, cex=1.2) }
}
legend("topleft", c("release locations", "settlement locations of GoM-spawned larvae", "settlement locations of Atl-spawned larvae",
"all trajectories", "trajectories of successful recruits"),
lty=c(0,0,0,1,1), lwd=c(0,0,0,2,2), col=c(1, 2, 7, 1, 6), pch=c(19, 19, 19, -1, -1), cex=1, y.intersp=1.0, bty="n")
dev.off()
###################### CONNECTIVITY MATRIX ##########################
rm(list = ls()[-which(ls() %in% c("model", "spp", "folder"))])
library(maps)
library(matlab)
############## concatenate files ###################
filelist <- list.files(path = ".", pattern="con_file") # find files
dat <- read.table(filelist[1])
filelist <- filelist[-1]
for (i in filelist) { newdat <- read.table(i); dat <- rbind(dat, newdat) }
colnames(dat) <- c("rel_poly","ret_poly","ret_yr","ret_mo","ret_d","age","ret_dep","rel_yr","rel_mo","rel_d")
#########################################################
d <- read.table("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/CMS_input_files/redSnapperSett_GOM_ATL_hires.xyz", sep="\t")
names(d) <- c("lon", "lat", "pol")
########## plot new grid cells #########################
pols <- unique(d$pol)
tklocs <- c(89.5, 76.5, 95.5, 117.5, 106.5, 41.5)
lablocs <- c(21.0, 59.0, 83.0, 92.5, 101.0, 112.0)
dev.off()
barplot(table(dat$ret_poly))
barplot(table(dat$rel_poly))
barplot(table(dat$ret_yr))
barplot(table(dat$ret_mo))
barplot(table(dat$ret_dep))
barplot(table(dat$age))
# plot for all years together ----------------
con <- dat
colnames(con) <- c("source","sink","yr","mon","day","tim","ret_dep","rel_yr","rel_mo","rel_d")
pollis <- 1:max(d$pol) # list of polygon names
limit <- length(pollis)
png(filename = paste0(folder, "conmatAllYears-", model, "-", spp, ".png"), units="in", width=5, height=5.7, pointsize=12, res=72*20)
nf <- layout(matrix(c(1:2), 2, 1), c(10), c(10, 1.4)) # plot layout -- all years
layout.show(nf)
par(mar=c(4,4,2,2), xpd=F)
con1 <- con # to look at all years together
settle <- matrix(NA, length(pollis), length(pollis))
for (i in 1:length(pollis)) {
a <- which(con1$source==pollis[i])
if(length(a)>0) {
for (j in 1:length(pollis)) { settle[i,j] <- length(which(con1$sink[a]==j)) }
} else { settle[i,] <- 0 } }
settle <- t(settle)
nn <- 300
cl = jet.colors(nn)
image(pollis[42:limit], pollis[42:limit], log(settle[42:limit,42:limit]+1), col=cl, axes=F,
xlab="", ylab="", main = paste(model, "-", spp))
axis(1, at=tklocs, lab=rep("", 6))
axis(2, at=tklocs, lab=rep("", 6))
axis(2, at=lablocs, lab=c("W GOM", "E GOM", "E FL", "GA", "SC", "NC"), tick=F, cex=1, las=2)
axis(1, at=lablocs, lab=c("W GOM", "E GOM", "E FL", "GA", "SC", "NC"), tick=F, cex=1, las=1)
box(); abline(0,1, lty=2)
abline(v=tklocs[2], lty=1); abline(h=tklocs[2], lty=1)
mtext(side=2, line=3.0, "Source Node", font=2)
mtext(side=1, line=2.25, "Receiving Node", font=2)
#### color bar plot
par(mar=c(0,2,0,0))
plot(c(-0.5,1.5), c(1.05,1.18), axes=F, xlab="", ylab="", col="white")
bra <- (seq(-0.5, ceiling(log(max(settle))), (ceiling(log(max(settle)))+0.5)/nn))
i = seq(0,1,1/(nn-1))
rect(i, 1.1, 1.04, 1.12, col = cl, lwd=0, border=cl)
laa <- c(1,10,100) # laa <- seq(0, 60000, 10000)
levs <- (0+i[1:nn]+1/(nn*2))
re <- lm(bra[1:(length(bra)-1)]~levs)
text((log(laa) - re$coef[1])/re$coef[2], 1.07, laa, pos=4, cex=1.2)
text(0.5,1.12, cex=1.2, "number of successful recruits", pos=3)
dev.off()
######### plot layout -- individual years
png(filename = paste0(folder, "conmatByYear-", model, "-", spp, ".png"), units="in", width=13, height=3, pointsize=12, res=72*20)
nf <- layout(matrix(c(1:7, 0, rep(8, 5), 0), 2, 7, byrow=TRUE), c(2, rep(6,5), 3), c(6, 2))
layout.show(nf)
#nf <- layout(matrix(c(1:4, 1, 5:7, 1, 8, 9, 9, rep(10,4)), 4, 4, byrow=TRUE), c(1,rep(7,3)), c(7,7,7,1.5))
#layout.show(nf)
#nf <- layout(matrix(c(1:5, 14, 1, 6:9, 14, 1, 10:13, 14, 1, rep(15,5)), 4, 6, byrow=TRUE), c(1,rep(7,4), 3), c(7,7,7,1.5))
#layout.show(nf)
#### global y label
par(mar=c(0,0,0,3))
plot.new()
mtext(side=2, line=-4, "Source Node", font=2)
#### plot connectivity matrices by year
resmat <- matrix(NA, nrow=13, ncol=5)
limit <- length(pollis)
for (k in unique(con$yr)) {
con1 <- con[which(con$yr == k),]
par(mar=c(3, 3, 2, 2), xpd=F)
settle <- matrix(NA, length(pollis), length(pollis))
for (i in 1:length(pollis)) {
a <- which(con1$source==pollis[i])
if(length(a)>0) {
for (j in 1:length(pollis)) { settle[i,j] <- length(which(con1$sink[a]==j)) }
} else { settle[i,] <- 0 } }
settle <- t(settle)
nn <- 300
cl = jet.colors(nn)
image(pollis[42:limit], pollis[42:limit], log(settle[42:limit,42:limit]+1), col=cl, axes=F, xlab="", ylab="",
main= paste(model, "-", spp, "-", k))
axis(1, at=tklocs, lab=rep("", 6))
axis(2, at=tklocs, lab=rep("", 6))
axis(2, at=lablocs, lab=c("W GOM", "E GOM", "E FL", "GA", "SC", "NC"), tick=F, cex=1, las=2)
axis(1, at=lablocs, lab=c("W GOM", "E GOM", "E FL", "GA", "SC", "NC"), tick=F, cex=1, las=2)
box(); abline(0,1, lty=2)/
abline(v=tklocs[2], lty=1); abline(h=tklocs[2], lty=1)
}
if (length(unique(con$yr)) <= 4) { plot.new() }
if (length(unique(con$yr)) <= 3) { plot.new() }
if (length(unique(con$yr)) <= 2) { plot.new() }
#### color bar plot
par(mar=c(0,2,0,0))
plot(c(1.05,1.18), c(-0.5,1.5), axes=F, xlab="", ylab="", col="white")
bra <- (seq(-0.5, ceiling(log(max(settle))), (ceiling(log(max(settle)))+0.5)/nn))
i = seq(0,1,1/(nn-1))
#rect(1.05, i, 1.1, 1, col = cl, lwd=0, border=cl)
rect(1.11, i, 1.12, 1.3, col = cl, lwd=0, border=cl)
laa <- c(1,10,100,1000) # laa <- seq(0, 60000, 10000)
levs <- (0+i[1:nn]+1/(nn*2))
re <- lm(bra[1:(length(bra)-1)]~levs)
poss <- (log(laa) - re$coef[1])/re$coef[2]
text(1.11, poss, laa, pos=4, cex=1.2)
text(1.115, -0.5, cex=1.1, "number of\nsuccessful\nrecruits", pos=3)
#legend("bottom", "self-recruitment", lwd=1, lty=2, bty="n", cex=1.1)
### global x label
par(mar=c(0,0,3,0))
plot.new()
mtext(side=1, line=-4, "Receiving Node", font=2)
#
dev.off()
# CONNECTIVITY MATRIX - regional summary ---------------------
rm(list = ls()[-which(ls() %in% c("model", "spp", "folder"))])
############## concatenate files ###################
filelist <- list.files(path = ".", pattern="con_file") # find files
dat <- read.table(filelist[1])
filelist <- filelist[-1]
for (i in filelist) { newdat <- read.table(i); dat <- rbind(dat, newdat) }
colnames(dat) <- c("rel_poly","ret_poly","ret_yr","ret_mo","ret_d","age","ret_dep","rel_yr","rel_mo","rel_d")
#########################################################
d <- read.table("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/CMS_input_files/redSnapperSett_GOM_ATL_hires.xyz", sep="\t")
names(d) <- c("lon", "lat", "pol")
for (i in 1) {
pa <- 46:52
bb <- 53:60
ta <- 61:66
sw <- 67:71
dt <- 72:76
sf <- 77:79
ef <- 80:89
ga <- 90:95
sc <- 96:106
nc <- 107:117
labs <- c("Panhandle", "Big Bend", "Central W FL", "SW FL", "Dry Tortugas", "S Florida", "E Florida", "GA", "SC", "NC")
dat$rel <- NA
dat$ret <- NA
dat$rel[which(dat$rel_poly %in% pa)] <- 1
dat$rel[which(dat$rel_poly %in% bb)] <- 2
dat$rel[which(dat$rel_poly %in% ta)] <- 3
dat$rel[which(dat$rel_poly %in% sw)] <- 4
dat$rel[which(dat$rel_poly %in% dt)] <- 5
dat$rel[which(dat$rel_poly %in% sf)] <- 6
dat$rel[which(dat$rel_poly %in% ef)] <- 7
dat$rel[which(dat$rel_poly %in% ga)] <- 8
dat$rel[which(dat$rel_poly %in% sc)] <- 9
dat$rel[which(dat$rel_poly %in% nc)] <- 10
dat$ret[which(dat$ret_poly %in% pa)] <- 1
dat$ret[which(dat$ret_poly %in% bb)] <- 2
dat$ret[which(dat$ret_poly %in% ta)] <- 3
dat$ret[which(dat$ret_poly %in% sw)] <- 4
dat$ret[which(dat$ret_poly %in% dt)] <- 5
dat$ret[which(dat$ret_poly %in% sf)] <- 6
dat$ret[which(dat$ret_poly %in% ef)] <- 7
dat$ret[which(dat$ret_poly %in% ga)] <- 8
dat$ret[which(dat$ret_poly %in% sc)] <- 9
dat$ret[which(dat$ret_poly %in% nc)] <- 10
}
########## plot new grid cells #########################
pols <- 1:10
dev.off()
barplot(table(dat$ret))
barplot(table(dat$rel))
barplot(table(dat$ret_yr))
barplot(table(dat$ret_mo))
barplot(table(dat$ret_dep))
barplot(table(dat$age))
# plot for all years together ----------------
png(filename = paste0(folder, "conmatLoRes-", model, "-", spp, ".png"), units="in", width=6, height=6, pointsize=12, res=72*20)
con <- dat
colnames(con) <- c("rel", "ret", "yr","mon","day","tim","ret_dep","rel_yr","rel_mo","rel_d", "source", "sink")
pollis <- 1:10 # list of polygon names
limit <- length(pollis)
#dev.off()
par(mar=c(8, 7, 2, 1), xpd=F)
con1 <- con # to look at all years together
settle <- matrix(NA, length(pollis), length(pollis))
for (i in 1:length(pollis)) {
a <- which(con1$source==pollis[i])
if(length(a)>0) {
for (j in 1:length(pollis)) { settle[i,j] <- length(which(con1$sink[a]==j)) }
} else { settle[i,] <- 0 } }
settle <- t(settle)
nn <- 300
cl = jet.colors(nn)
image(pollis, pollis[1:9], (settle[, 1:9]), col=cl, axes=F, xlab="", ylab="",
main = paste(model, "-", spp))
axis(1, at=1:10, lab=labs, las = 2)
axis(2, at=1:10, lab=labs, las = 2)
box()
#abline(0,1, lty=2)
abline(v = 5.5, lty=1, col = 0)
abline(h = 5.5, lty=1, col = 0)
txt <- round(settle / sum(sum(settle)) * 100, 1)
for (i in 1:10) {
for (j in 1:10) {
if (txt[i,j] != 0) {
text(i, j, txt[i,j], col = 0) }}}
mtext(side=2, line=6.2, "Source Node", font=2)
mtext(side=1, line=6.2, "Receiving Node", font=2)
dev.off()
# double check calcs
ga <- sum(as.vector(txt[6:10, 1:5]))
aa <- sum(as.vector(txt[6:10, 6:10]))
ga / (ga + aa) # should equal as above