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scale_releases_1to1.R
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################################################################################
############ GoM-ATL scaled red snapper release file for CMS ################
############ M. Karnauskas Sep 12, 2019 ################
#
# code takes output from independent regional maps for GoM and Atl
# scales release files according to ratios reported in surveys done in both basins
# for use in full GoM-Atl simulation
################################################################################
rm(list=ls())
if (!"maps" %in% installed.packages()) install.packages("maps", repos='http://cran.us.r-project.org')
library(maps)
source("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/findMinDepth.R")
### Step 1: import independent maps and scale them to known ratios calculated above
# load data ----------------------------------------------------------
load("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/GOMreleaseForScaling.RData")
GOM <- matfinGOM
load("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/ATLreleaseForScaling.RData")
ATL <- matS
# check how many millions of particles present in each file ----------
sum(GOM$V5)/10^5
sum(ATL$V5)/10^5
areaGOM <- length(unique(paste(GOM$V2, GOM$V3)))
areaATL <- length(unique(paste(ATL$V2, ATL$V3)))
areaGOM
areaATL
arearat <- areaGOM/areaATL
arearat
# calculate constants for scaling -------------------------------------
const_scaler <- sum(GOM$V5)/sum(ATL$V5)
const_scaler
unscaled <- rbind(GOM, ATL)
dim(unscaled)
GOMsc <- GOM
ATLsc <- ATL
GOMsc$V5 <- round(GOMsc$V5 * 10)
ATLsc$V5 <- round(ATLsc$V5 * 10 * const_scaler / arearat)
scaled <- rbind(GOMsc, ATLsc)
dim(scaled)
which(scaled$V5==0)
par(mfrow=c(1,2), mex=0.8)
barplot(c(sum(GOM$V5), sum(ATL$V5)), names.arg=c("GoM", "Atl"), main="unscaled", ylab=""); abline(0,0)
barplot(c(sum(GOMsc$V5), sum(ATLsc$V5)), names.arg=c("GoM", "Atl"), main="scaled", ylab=""); abline(0,0)
# check ratios -----------------------------------------
(sum(GOMsc$V5)) / (sum(ATLsc$V5))
arearat
(sum(GOM$V5)) / (sum(ATL$V5))
# plot results to check --------------------------------
#par(mfrow=c(1,2))
dev.off()
par(mar = c(5, 7, 1, 1))
sc2 <- scaled[which(scaled$V6==2013 & scaled$V7==6 & scaled$V8==27),]
x <- sc2$V5 / 130
pos <- c(0.005, 0.05, 0.1, 0.2, 0.5, 1, 2, 4, 5, 10, 20, 50, 100, 1000)
a <- floor(min(x))
b <- max((x)-a)*1.03
pind <- round((x-a)/b*100+1); print(min(pind)); print(max(pind))
cols <- c(rainbow(30, start=0.82, end=0.99), rainbow(70, start=0.01, end=0.17))[100:1]
map('state', fill = 1, interior=F, col = gray(0.85), ylim=c(22.5, 35), xlim=c(-88,-76))
#mtext(side = 1, line = 2.5, "longitude")
#mtext(side = 2, line = 2.5, "latitude")
points(sc2$V2, sc2$V3, col=cols[pind], pch=15, cex=0.5)
#box(); axis(1); axis(2, las = 2)
xloc <- seq(-86, -78, length.out=100)
for (j in 1:100) { polygon(c(xloc[j], xloc[j+1],xloc[j+1], xloc[j]), c(23.0,23.0,23.4,23.4), col=cols[j], border=NA) }
w <- which.min(abs(((max(x)-min(x))/6) - pos))
if(-pos[w]<min(x)) { xx <- seq(0, max(x), pos[w]); xx <- xx[xx>min(x)] } else { xx <- c(seq(-pos[w], min(x), -pos[w]), seq(0, max(x), pos[w])) }
text(xloc[round((xx-a)/b*100+1)], y=22.75, xx, pos=2)
text(-82, 24.25, "relative index of spawning output", pos = 1)
degs = seq(88, 76, -2)
a = sapply(degs, function(x) bquote(.(x)*degree ~ W))
axis(1, at = -degs, lab=do.call(expression, a))
degs = seq(24, 34, 2)
a = sapply(degs, function(x) bquote(.(x)*degree ~ N))
axis(2, at = degs, lab=do.call(expression, a), las = 2)
box()
#mtext(side=3, line=1.5, "scaled fecundity map", cex=1.3, font=2)
sc3 <- unscaled[which(unscaled$V6==2013 & unscaled$V7==6 & unscaled$V8==27),]
x <- sc3$V5 / 100
pos <- c(0.005, 0.05, 0.1, 0.2, 0.5, 1, 2, 4, 5, 10, 20, 50, 100, 1000)
a <- floor(min(x))
b <- max((x)-a)*1.03
pind <- round((x-a)/b*100+1); print(min(pind)); print(max(pind))
cols <- c(rainbow(30, start=0.82, end=0.99), rainbow(70, start=0.01, end=0.17))[100:1]
map('state', fill = 1, interior=F, col = gray(0.95), ylim=c(23.0, 35), xlim=c(-88,-76))
points(sc3$V2, sc3$V3, col=cols[pind], pch=15, cex=0.8)
box(); axis(1); axis(2)
xloc <- seq(-86, -78, length.out=100)
for (j in 1:100) { polygon(c(xloc[j], xloc[j+1],xloc[j+1], xloc[j]), c(23.5,23.5,24.0,24.0), col=cols[j], border=NA) }
w <- which.min(abs(((max(x)-min(x))/6) - pos))
if(-pos[w]<min(x)) { xx <- seq(0, max(x), pos[w]); xx <- xx[xx>min(x)] } else { xx <- c(seq(-pos[w], min(x), -pos[w]), seq(0, max(x), pos[w])) }
text(xloc[round((xx-a)/b*100+1)], y=23.2, xx, pos=2)
mtext(side=3, line=1.5, "unscaled fecundity map", cex=1.3, font=2)
# reduce number of particles ----------------------------------
min(scaled$V5); max(scaled$V5); mean(scaled$V5); sum(scaled$V5)
dim(scaled)
scaled$V5 <- round(scaled$V5/1000) # 200 for large, 1000 for small
min(scaled$V5); max(scaled$V5); mean(scaled$V5); sum(scaled$V5)
table(scaled$V5==0)
scaled <- scaled[(scaled$V5>0),]
dim(scaled)
min(scaled$V5); max(scaled$V5); mean(scaled$V5); sum(scaled$V5)
# check particle reduction -------------------------------------
sc2 <- scaled[which(scaled$V6==2013 & scaled$V7==7 & scaled$V8==27),]
x <- sc2$V5
pos <- c(0.005, 0.05, 0.1, 0.2, 0.5, 1, 2, 4, 5, 20, 50, 100, 200, 500, 1000)
a <- floor(min(x))
b <- max((x)-a)*1.03
pind <- round((x-a)/b*100+1); print(min(pind)); print(max(pind))
cols <- c(rainbow(30, start=0.82, end=0.99), rainbow(70, start=0.01, end=0.17))[100:1]
map('state', fill = 1, interior=F, col = gray(0.95), ylim=c(23.0, 35), xlim=c(-88,-76))
points(sc2$V2, sc2$V3, col=cols[pind], pch=15, cex=0.8)
box(); axis(1); axis(2)
xloc <- seq(-86, -78, length.out=100)
for (j in 1:100) { polygon(c(xloc[j], xloc[j+1],xloc[j+1], xloc[j]), c(23.5,23.5,24.0,24.0), col=cols[j], border=NA) }
w <- which.min(abs(((max(x)-min(x))/6) - pos))
if(-pos[w]<min(x)) { xx <- seq(0, max(x), pos[w]); xx <- xx[xx>min(x)] } else { xx <- c(seq(-pos[w], min(x), -pos[w]), seq(0, max(x), pos[w])) }
text(xloc[round((xx-a)/b*100+1)], y=23.2, xx, pos=2)
mtext(side=3, line=1.5, "scaled fecundity map", cex=1.3, font=2)
#scaledfin <- scaled
dim(scaled)
setwd("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes")
d <- read.table("bad.csv", sep = ",", header = F)
d$V4 <- d$V3
d$V3 <- paste0(round(d$V1, 4), "_", round(d$V2, 4))
scaled$V10 <- paste0(round(scaled$V2, 4), "_", round(scaled$V3, 4))
prob <- which(scaled$V10 %in% d$V3)
prob2 <- which(scaled$V10 == d$V3[3])
scaledfin <- c()
for (y in 2019) {
scaled2 <- scaled
scaled2$V6 <- y
scaledfin <- rbind(scaledfin, scaled2) }
dim(scaledfin)/5
dim(scaled)
sum(scaledfin$V5)
head(scaledfin)
scaledfin <- scaledfin[-10]
head(scaledfin)
table(scaledfin$V1)
table(scaledfin$V2)
table(scaledfin$V3)
table(scaledfin$V4)
table(scaledfin$V5)
table(scaledfin$V6)
table(scaledfin$V7)
table(scaledfin$V8)
table(scaledfin$V9)
table(scaledfin$V10)
setwd("C:/Users/mandy.karnauskas/Desktop/RS_FATEproject/MASTER_codes/")
nests <- c("nest_1_SABGOM.nc", "nest_2_SABGOM.nc",
"nest_1_AtlMercator.nc",
"nest_1_20080501000000_HYCOM150.nc",
"nest_1_hycomGOM90pt1.nc", "nest_1_hycomGOM32pt5.nc", "nest_2_GLBHYCOMsmall.nc")
d2 <- findMinDepth(scaledfin$V2, scaledfin$V3, nests)
plot(-d2, -scaledfin$V4)
abline(1,1)
table(scaledfin$V4 < d2)
#plot(-d2[1:100], type = "l")
#lines(-scaledfin$V4[1:100], col = 2)
scaledfin$V4 <- round(d2 - 10)
table(scaledfin$V4)
scaledfin$V4[which(scaledfin$V4 > 50)] <- 50
table(scaledfin$V4)
table(scaledfin$V4[prob])
scaledfin$V4[prob] <- scaledfin$V4[prob] - 10
table(scaledfin$V4[prob])
table(scaledfin$V4 < d2)
table(scaledfin$V4[prob2])
scaledfin$V4[prob2] <- scaledfin$V4[prob2] - 10
table(scaledfin$V4[prob2])
scaledfin$V4[which(scaledfin$V4 <= 0)] <- 1
table(scaledfin$V4)
plot(-d2, -scaledfin$V4, pch = 19, cex = 2, col = "#FF000002")
abline(1,1)
# final check ----------------------------------
tapply(scaledfin$V5, scaledfin$V1 > 77, sum)
ga <- tapply(scaledfin$V5, scaledfin$V1 > 77, sum)
ga[1] / ga[2] # 2.079171 for small; 2.10428 for large
arearat
sum(scaledfin$V5) # 43404 per year for small; 224604 for large
table(scaledfin$V6) # 22938 per year for small; 34058 for large
head(scaledfin)
# save output -------------------------------------------
write.table(scaledfin, file="scaledGOMATLrel2019.txt", sep="\t", col.names=F, row.names=F)
# the end -----------------------
# plot release file by date --------------------------------------
datelist <- unique(paste(scaled$V7, "_", scaled$V8, sep=""))
datelist1 <- sort((unique(paste(scaled$V7, ".", sprintf("%02d", scaled$V8), sep=""))))
datelist <- datelist[order(as.numeric(datelist1))]
dev.off()
par(mfrow=c(4, 6), mex=0.5)
x <- scaled$V5
pos <- c(0.005, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 40, 100, 500, 1000)
a <- floor(min(x))
b <- max((x)-a)*1.03
cols <- c(rainbow(30, start=0.82, end=0.99), rainbow(70, start=0.01, end=0.17))[100:1]
for (i in 1:length(datelist)) {
sc2 <- scaled[which(scaled$V6==2017 & scaled$V7==strsplit(datelist[i], "_")[[1]][1] & scaled$V8==strsplit(datelist[i], "_")[[1]][2]),]
x1 <- sc2$V5
pind <- round((x1-a)/b*100+1); print(min(pind)); print(max(pind))
map('state', fill = 1, interior=F, col = gray(0.95), ylim=c(23.0, 35), xlim=c(-89,-77))
points(sc2$V2, sc2$V3, col=cols[pind], pch=15, cex=0.8)
box(); axis(1); axis(2)
xloc <- seq(-86, -78, length.out=100)
for (j in 1:100) { polygon(c(xloc[j], xloc[j+1],xloc[j+1], xloc[j]), c(23.5,23.5,24.0,24.0), col=cols[j], border=NA) }
w <- 11 # w <- which.min(abs(((max(x)-min(x))/6) - pos))
if(-pos[w]<min(x)) { xx <- seq(0, max(x), pos[w]); xx <- xx[xx>min(x)] } else { xx <- c(seq(-pos[w], min(x), -pos[w]), seq(0, max(x), pos[w])) }
#text(xloc[round((xx-a)/b*100+1)], y=23.2, xx, pos=2)
mtext(side=3, line=1.5, paste(month.abb[as.numeric(strsplit(datelist[i], "_")[[1]][1])], strsplit(datelist[i], "_")[[1]][2]), cex=1, font=2)
}
################################ END #######################################