inst/Projects/At Sea Catch Composition/At Sea Catch Composition.r
In LobsterScience/bio.lobster: Lobster Stock Assessment Tools for DFO Maritimes
p = bio.lobster::load.environment()
require(ggplot2)
figdir = file.path(project.datadirectory("bio.lobster","requests","vent"))
dir.create( figdir, recursive = TRUE, showWarnings = FALSE )
png(filename=file.path(figdir, "MapLFA33-34.png"),width=5, height=5, units = "in", res = 800)
LobsterMap('33-34')
dev.off()
#load("C:/bio.data/bio.lobster/data/ODBCDump/atSea.rdata") #Import AtSea data
#lobster.db('atSea.redo')
#lobster.db('atSea.clean.redo')
atSea.clean=lobster.db('atSea.clean')
lfas= c("33", "34")
p$lfas=lfas
a=atSea.clean[atSea.clean$LFA %in% lfas,]
a$yr=year(a$STARTDATE)
b=a[a$yr>2017,]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
#high=124 #define slot
#low=115
l="33-34"
c=b[b$CARLENGTH<=190,]
big=190 #upper bound for hist. Needs to be a multiple of 5
#print(l)
#cu=c[!duplicated(c[,c('TRIPNO')]),]
#cu=cu[cu$WOS %in% c(1:9),]
c=c[c$SEX %in% c(1:3),]
c$SEX[c$SEX==1]="Male"
c$SEX[c$SEX==2]="No Eggs"
c$SEX[c$SEX==3]="Eggs"
c$SEX=factor(c$SEX, levels=c("Eggs", "No Eggs", "Male"))
#Lobster Sizes
png(filename=paste0(figdir,"/Size_Distribution_",l,".png"), width = 150, height = 150, units='mm', res = 600)
#all=hist(c$CARLENGTH, xlim=c(0,big), breaks=seq(0, big, 5), main=paste0("All Lobster LFA",l), col='grey88', xlab="Carapace Length", ylab="Number of Lobster")
ggplot(data = c, aes(x = CARLENGTH, fill = SEX)) +
xlim(40, 170) +
geom_histogram(colour = 'black', binwidth=2, center=1) +
geom_vline(xintercept = 82.5, linetype="dashed", color = "red", size=1) +
scale_fill_manual(values = c("orange1", "deepskyblue1", "palegreen3"), labels= c("Female (Eggs)", "Female (No Eggs)", "Male"), name= "") +
labs( x="Carapace Length (mm)", y= "Number of Lobster") +
ggtitle(paste0("LFAs ",l))+
theme(legend.position = c(0.85, 0.5), plot.title = element_text(hjust = 0.5, size=14, face="bold")) +
theme(axis.line = element_line(colour = "black"))+
theme(panel.background = element_blank()) +
scale_y_continuous(expand = c(0,0.5))
dev.off()
#Ovigerous vs non-Ovigerous
e=c[c$SEX %in% c("No Eggs", "Eggs") & c$CARLENGTH<141,] #Separate female lobster
# Percent Ovigerous
#-------------------------------
berried=data.frame() #all
week=c(1:8)
for (w in week){
gg=e[e$WOS %in% w,]
num.ber=length(gg$EID[gg$SEX=="Eggs"])
num.not=length(gg$EID[gg$SEX=="No Eggs"])
per.ber=num.ber/(num.ber + num.not)*100
output=c(w,per.ber)
berried=rbind(berried, output)
}
names(berried)=c("Week", "All.Percent Berried")
n.berried=data.frame() #north
for (w in week){
g=e[e$area=="north",]
g=g[g$WOS %in% w,]
n.num.ber=length(g$EID[g$SEX=="Eggs"])
n.num.not=length(g$EID[g$SEX=="No Eggs"])
n.per.ber=n.num.ber/(n.num.ber + n.num.not)*100
n.output=c(w,n.per.ber)
n.berried=rbind(n.berried, n.output)
}
names(n.berried)=c("Week", "N.Percent Berried")
c.berried=data.frame() #central
for (w in week){
g=e[e$area=="central",]
g=g[g$WOS %in% w,]
c.num.ber=length(g$EID[g$SEX=="Eggs"])
c.num.not=length(g$EID[g$SEX=="No Eggs"])
c.per.ber=c.num.ber/(c.num.ber + c.num.not)*100
c.output=c(w,c.per.ber)
c.berried=rbind(c.berried, c.output)
}
names(c.berried)=c("Week", "C.Percent Berried")
s.berried=data.frame() #south
for (w in week){
g=e[e$area=="south",]
g=g[g$WOS %in% w,]
s.num.ber=length(g$EID[g$SEX=="Eggs"])
s.num.not=length(g$EID[g$SEX=="No Eggs"])
s.per.ber=s.num.ber/(s.num.ber + s.num.not)*100
s.output=c(w,s.per.ber)
s.berried=rbind(s.berried, s.output)
}
names(s.berried)=c("Week", "S.Percent Berried")
ber=cbind(berried, n.berried[2], c.berried [2], s.berried[2], by=berried$Week)
png(filename=paste0(figdir,"/Percent Berried LFA 27.png"))
plot(berried$Week, berried$`Percent Berried`, main="LFA 27", ylab="% Berried", xlab="Week of Season", col="green", type="n", ylim=c(10, 30))
#points(berried$Week, berried$`Percent Berried`, col="green", pch=16)
#lines(berried$Week, berried$`Percent Berried`, col="green")
points(ber$Week, ber$`N.Percent Berried`, col="red", pch=16)
lines(ber$Week, ber$`N.Percent Berried`, col="red")
points(ber$Week, ber$`C.Percent Berried`, col="blue", pch=16)
lines(ber$Week, ber$`C.Percent Berried`, col="blue")
points(ber$Week, ber$`S.Percent Berried`, col="green", pch=16)
lines(ber$Week, ber$`S.Percent Berried`, col="green")
legend(x = "bottomright", legend = c("North", "Central", "South"),lty = c(1, 1), col = c("red", "blue", "green"), bty="n", pch=16)
dev.off()
# Percent Ovigerous
#-------------------------------
berried=data.frame() #all
week=c(1:8)
for (w in week){
gg=e[e$WOS==w & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
num.ber=length(gg$EID[gg$SEX=="Eggs"])
num.not=length(gg$EID[gg$SEX=="No Eggs"])
per.ber=num.ber/(num.ber + num.not)*100
output=c(w,per.ber)
berried=rbind(berried, output)
}
names(berried)=c("Week", "Sublegal.Percent Berried")
png(filename=paste0(figdir,"/Percent Berried Sublegals.png"))
plot(berried$Week, berried$`Sublegal.Percent Berried`, main="LFA 27 Sublegal(78-82.4mm)", ylab="% Berried", xlab="Week of Season", col="blue", type="l", ylim=c(10, 30))
points(berried$Week, berried$`Sublegal.Percent Berried`, col="green", pch=16)
dev.off()
n.berried=data.frame() #north
for (w in week){
g=e[e$area=="north" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
n.num.ber=length(g$EID[g$SEX=="Eggs"])
n.num.not=length(g$EID[g$SEX=="No Eggs"])
n.per.ber=n.num.ber/(n.num.ber + n.num.not)*100
n.output=c(w,n.per.ber)
n.berried=rbind(n.berried, n.output)
}
names(n.berried)=c("Week", "N.Percent Berried")
c.berried=data.frame() #central
for (w in week){
g=e[e$area=="central" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
c.num.ber=length(g$EID[g$SEX=="Eggs"])
c.num.not=length(g$EID[g$SEX=="No Eggs"])
c.per.ber=c.num.ber/(c.num.ber + c.num.not)*100
c.output=c(w,c.per.ber)
c.berried=rbind(c.berried, c.output)
}
names(c.berried)=c("Week", "C.Percent Berried")
s.berried=data.frame() #south
for (w in week){
g=e[e$area=="south" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
s.num.ber=length(g$EID[g$SEX=="Eggs"])
s.num.not=length(g$EID[g$SEX=="No Eggs"])
s.per.ber=s.num.ber/(s.num.ber + s.num.not)*100
s.output=c(w,s.per.ber)
s.berried=rbind(s.berried, s.output)
}
names(s.berried)=c("Week", "S.Percent Berried")
ber=cbind(berried, n.berried[2], c.berried [2], s.berried[2], by=berried$Week)
png(filename=paste0(figdir,"/Sublegal Percent Berried LFA 27.png"))
plot(berried$Week, berried$`Percent Berried`, main="LFA 27", ylab="% Berried", xlab="Week of Season", col="green", type="n", ylim=c(15, 35))
#points(berried$Week, berried$`Percent Berried`, col="green", pch=16)
#lines(berried$Week, berried$`Percent Berried`, col="green")
points(ber$Week, ber$`N.Percent Berried`, col="red", pch=16)
lines(ber$Week, ber$`N.Percent Berried`, col="red")
points(ber$Week, ber$`C.Percent Berried`, col="blue", pch=16)
lines(ber$Week, ber$`C.Percent Berried`, col="blue")
points(ber$Week, ber$`S.Percent Berried`, col="green", pch=16)
lines(ber$Week, ber$`S.Percent Berried`, col="green")
legend(x = "bottomright", legend = c("North", "Central", "South"),lty = c(1, 1), col = c("red", "blue", "green"), bty="n", pch=16)
dev.off()
#Discards
#---------------------------------------
lfas= c("33", "34")
a=atSea.clean[atSea.clean$LFA %in% lfas,]
a$yr=year(a$STARTDATE)
b=a[a$yr>2009,]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
c=b[b$LFA==l,]
#All Areas
lfas= c("33", "34")
catches=data.frame(matrix(, nrow=length(lfas), ncol=5))
names(catches)=c("LFA","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$LFA=lfas
for (i in 1:length(lfas)){
l=lfas[i]
c=b[b$LFA==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
#discard=rbind(u,berried)
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$LFA==l]=tot-under-o.egg-u.egg
catches$Undersize[catches$LFA==l]=under
catches$Over.Berried[catches$LFA==l]=o.egg
catches$Under.Berried[catches$LFA==l]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("LFA", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("LFA", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
names(catches)=c("LFA", "Legal-Size", "Legal-Size Egged", "Undersize Egged", "Undersize")
bar.p=melt(catches, id.vars="LFA")
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/catch_proportions_33-34.png"),width = 150, height = 150, units='mm', res = 600)
ggplot(bar.p, aes(x = LFA, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="Lobster") +
labs( x="Lobster Fishing Area", y= "% of Catch")
dev.off()
# Discards 27 North vs Central vs South
b=a[a$yr>2009 & a$LFA=="27",]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
c=b
#create North/South index
n.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.North"],div$Y[div$area=="27.North"])==1) #Little River and North
c.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.Central"],div$Y[div$area=="27.Central"])==1) #South Bar to Little River
s.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.South"],div$Y[div$area=="27.South"])==1) #Gabarus to South Bar
c$area=NA
c$area[n.ind]="North"
c$area[c.ind]="Central"
c$area[s.ind]="South"
b=c[!is.na(c$area),]
areas=c("North","Central", "South")
catches=data.frame(matrix(, nrow=length(areas), ncol=5))
names(catches)=c("Area","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$Area=areas
for (i in 1:length(areas)){
l=areas[i]
c=b[b$area==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$Area==l]=tot-under-o.egg-u.egg
catches$Undersize[catches$Area==l]=under
catches$Over.Berried[catches$Area==l]=o.egg
catches$Under.Berried[catches$Area==l]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("Area", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("Area", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
names(catches)=c("Area", "Legal-Size", "Legal-Size Egged", "Undersize Egged", "Undersize")
bar.p=melt(catches, id.vars="Area")
bar.p$Area=factor(bar.p$Area, levels=c("North", "Central", "South"))
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/catch.proportions LFA 27 by Area.png"))
ggplot(bar.p, aes(x = Area, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="") +
labs( x="LFA27 Sub-Area", y= "% of Catch")
dev.off()
# By week
# ----------------------------------
week=c(1:8)
areas=c("North", "South", "Central")
for (aa in areas){
z=b[b$area %in% aa,]
catches=data.frame(matrix(nrow=length(week), ncol=5))
names(catches)=c("Week","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$Week=week
for (i in 1:length(week)){
l=week[i]
c=z[z$WOS == l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$Week==i]=tot-under-o.egg-u.egg
catches$Undersize[catches$Week==i]=under
catches$Over.Berried[catches$Week==i]=o.egg
catches$Under.Berried[catches$Week==i]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("Week", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("Week", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")] #reorder
names(catches)=c("Week", "Legal", "Legal-Size Eggs", "Undersize Eggs", "Undersize")
bar.p=melt(catches, id.vars="Week")
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/weekly.catch.composition.",aa, ".png"))
print(ggplot(bar.p, aes(x = Week, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="Catch Composition") +
labs( title=paste0(aa), x="Week", y= "% of Catch")
)
dev.off()
}
#Vents
#Comparing catch of 50mm (1 15/16") vs 44mm (1 3/4")
#**Number and placement of vents may also differ
l27=b[b$LFA=="27",]
l27=l27[l27$yr>2016,]
big.vent=l27[l27$CAPTAIN %in% c("David Ferguson", "DAVID FERGUSON"),]
big.vent$vent="Big"
small.vent=l27[l27$CAPTAIN %in% c("Raymond Sherwood", "RAYMOND SHERWOOD"),]
small.vent$vent="Small"
escape=rbind(big.vent, small.vent)
biggest=5*(ceiling(max(escape$CARLENGTH)/5))
vents=unique(escape$vent)
escape$size[escape$vent=="Small"]="44mm"
escape$size[escape$vent=="Big"]="50mm"
for (v in vents){
png(filename=paste0(figdir,"/", v, "Vent.png"))
all=hist(escape$CARLENGTH[escape$vent==v], xlim=c(0,biggest), breaks=seq(0, biggest, 2.5), main=paste0(escape$size[escape$vent==v][1], " Vent"),
col='grey88', xlab="Carapace Length", ylab="Number of Lobster")
abline(v = 82.5, col="red", lwd=2, lty=2)
dev.off()
}
#Hist lines
if (plot.hist.line){
png(filename=paste0(figdir,"/","Vent Comparison.png"))
a=hist(escape$CARLENGTH[escape$vent=="Big"],plot=F, breaks=seq(0, biggest, 2.5))
plot(a$mids,a$density,type='l', xlim=c(0,biggest),col='blue', xlab="Carapace Length", ylab="Proportion of Catch",main="Vent Comparison")
b=hist(escape$CARLENGTH[escape$vent=="Small"],plot=F, breaks=seq(0, biggest, 2.5))
lines(b$mids,b$density,type='l',col='red')
abline(v = 82.5, col="grey50", lwd=0.5, lty=2)
legend(x = "topright", legend = c("44mm", "50mm"), inset=0.05,lty = c(1, 1), col = c("red", "blue"), lwd = 2, title="Vent Height")
dev.off()
}
vent.catches=data.frame(matrix(, nrow=length(unique(vents)), ncol=5))
names(vent.catches)=c("Vent","Legal", "Undersize", "Over.Berried", "Under.Berried")
vent.catches$Vent=vents
for (i in 1:length(vents)){
l=vents[i]
c=escape[escape$vent==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
#discard=rbind(u,berried)
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
vent.catches$Legal[vent.catches$Vent==l]=tot-under-o.egg-u.egg
vent.catches$Undersize[vent.catches$Vent==l]=under
vent.catches$Over.Berried[vent.catches$Vent==l]=o.egg
vent.catches$Under.Berried[vent.catches$Vent==l]=u.egg
}
names(vent.catches)=c("Vent", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
vent.catches=vent.catches[, c("Vent", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
vent.catches$Vent[vent.catches$Vent=="Small"]="44mm"
vent.catches$Vent[vent.catches$Vent=="Big"]="50mm"
bar.v=melt(vent.catches, id.vars="Vent")
ggplot(bar.v, aes(x = Vent, y = value, fill = variable)) + geom_col(position="fill")+ scale_y_continuous(labels = scales::percent)
ggplot(bar.v, aes(x = LFA, y = value, fill = variable)) + geom_col(position="fill")+ scale_y_continuous(labels = scales::percent ) + stat_n_text(size = 4)
LobsterScience/bio.lobster documentation built on Feb. 14, 2025, 3:28 p.m.
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p = bio.lobster::load.environment()
require(ggplot2)
figdir = file.path(project.datadirectory("bio.lobster","requests","vent"))
dir.create( figdir, recursive = TRUE, showWarnings = FALSE )
png(filename=file.path(figdir, "MapLFA33-34.png"),width=5, height=5, units = "in", res = 800)
LobsterMap('33-34')
dev.off()
#load("C:/bio.data/bio.lobster/data/ODBCDump/atSea.rdata") #Import AtSea data
#lobster.db('atSea.redo')
#lobster.db('atSea.clean.redo')
atSea.clean=lobster.db('atSea.clean')
lfas= c("33", "34")
p$lfas=lfas
a=atSea.clean[atSea.clean$LFA %in% lfas,]
a$yr=year(a$STARTDATE)
b=a[a$yr>2017,]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
#high=124 #define slot
#low=115
l="33-34"
c=b[b$CARLENGTH<=190,]
big=190 #upper bound for hist. Needs to be a multiple of 5
#print(l)
#cu=c[!duplicated(c[,c('TRIPNO')]),]
#cu=cu[cu$WOS %in% c(1:9),]
c=c[c$SEX %in% c(1:3),]
c$SEX[c$SEX==1]="Male"
c$SEX[c$SEX==2]="No Eggs"
c$SEX[c$SEX==3]="Eggs"
c$SEX=factor(c$SEX, levels=c("Eggs", "No Eggs", "Male"))
#Lobster Sizes
png(filename=paste0(figdir,"/Size_Distribution_",l,".png"), width = 150, height = 150, units='mm', res = 600)
#all=hist(c$CARLENGTH, xlim=c(0,big), breaks=seq(0, big, 5), main=paste0("All Lobster LFA",l), col='grey88', xlab="Carapace Length", ylab="Number of Lobster")
ggplot(data = c, aes(x = CARLENGTH, fill = SEX)) +
xlim(40, 170) +
geom_histogram(colour = 'black', binwidth=2, center=1) +
geom_vline(xintercept = 82.5, linetype="dashed", color = "red", size=1) +
scale_fill_manual(values = c("orange1", "deepskyblue1", "palegreen3"), labels= c("Female (Eggs)", "Female (No Eggs)", "Male"), name= "") +
labs( x="Carapace Length (mm)", y= "Number of Lobster") +
ggtitle(paste0("LFAs ",l))+
theme(legend.position = c(0.85, 0.5), plot.title = element_text(hjust = 0.5, size=14, face="bold")) +
theme(axis.line = element_line(colour = "black"))+
theme(panel.background = element_blank()) +
scale_y_continuous(expand = c(0,0.5))
dev.off()
#Ovigerous vs non-Ovigerous
e=c[c$SEX %in% c("No Eggs", "Eggs") & c$CARLENGTH<141,] #Separate female lobster
# Percent Ovigerous
#-------------------------------
berried=data.frame() #all
week=c(1:8)
for (w in week){
gg=e[e$WOS %in% w,]
num.ber=length(gg$EID[gg$SEX=="Eggs"])
num.not=length(gg$EID[gg$SEX=="No Eggs"])
per.ber=num.ber/(num.ber + num.not)*100
output=c(w,per.ber)
berried=rbind(berried, output)
}
names(berried)=c("Week", "All.Percent Berried")
n.berried=data.frame() #north
for (w in week){
g=e[e$area=="north",]
g=g[g$WOS %in% w,]
n.num.ber=length(g$EID[g$SEX=="Eggs"])
n.num.not=length(g$EID[g$SEX=="No Eggs"])
n.per.ber=n.num.ber/(n.num.ber + n.num.not)*100
n.output=c(w,n.per.ber)
n.berried=rbind(n.berried, n.output)
}
names(n.berried)=c("Week", "N.Percent Berried")
c.berried=data.frame() #central
for (w in week){
g=e[e$area=="central",]
g=g[g$WOS %in% w,]
c.num.ber=length(g$EID[g$SEX=="Eggs"])
c.num.not=length(g$EID[g$SEX=="No Eggs"])
c.per.ber=c.num.ber/(c.num.ber + c.num.not)*100
c.output=c(w,c.per.ber)
c.berried=rbind(c.berried, c.output)
}
names(c.berried)=c("Week", "C.Percent Berried")
s.berried=data.frame() #south
for (w in week){
g=e[e$area=="south",]
g=g[g$WOS %in% w,]
s.num.ber=length(g$EID[g$SEX=="Eggs"])
s.num.not=length(g$EID[g$SEX=="No Eggs"])
s.per.ber=s.num.ber/(s.num.ber + s.num.not)*100
s.output=c(w,s.per.ber)
s.berried=rbind(s.berried, s.output)
}
names(s.berried)=c("Week", "S.Percent Berried")
ber=cbind(berried, n.berried[2], c.berried [2], s.berried[2], by=berried$Week)
png(filename=paste0(figdir,"/Percent Berried LFA 27.png"))
plot(berried$Week, berried$`Percent Berried`, main="LFA 27", ylab="% Berried", xlab="Week of Season", col="green", type="n", ylim=c(10, 30))
#points(berried$Week, berried$`Percent Berried`, col="green", pch=16)
#lines(berried$Week, berried$`Percent Berried`, col="green")
points(ber$Week, ber$`N.Percent Berried`, col="red", pch=16)
lines(ber$Week, ber$`N.Percent Berried`, col="red")
points(ber$Week, ber$`C.Percent Berried`, col="blue", pch=16)
lines(ber$Week, ber$`C.Percent Berried`, col="blue")
points(ber$Week, ber$`S.Percent Berried`, col="green", pch=16)
lines(ber$Week, ber$`S.Percent Berried`, col="green")
legend(x = "bottomright", legend = c("North", "Central", "South"),lty = c(1, 1), col = c("red", "blue", "green"), bty="n", pch=16)
dev.off()
# Percent Ovigerous
#-------------------------------
berried=data.frame() #all
week=c(1:8)
for (w in week){
gg=e[e$WOS==w & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
num.ber=length(gg$EID[gg$SEX=="Eggs"])
num.not=length(gg$EID[gg$SEX=="No Eggs"])
per.ber=num.ber/(num.ber + num.not)*100
output=c(w,per.ber)
berried=rbind(berried, output)
}
names(berried)=c("Week", "Sublegal.Percent Berried")
png(filename=paste0(figdir,"/Percent Berried Sublegals.png"))
plot(berried$Week, berried$`Sublegal.Percent Berried`, main="LFA 27 Sublegal(78-82.4mm)", ylab="% Berried", xlab="Week of Season", col="blue", type="l", ylim=c(10, 30))
points(berried$Week, berried$`Sublegal.Percent Berried`, col="green", pch=16)
dev.off()
n.berried=data.frame() #north
for (w in week){
g=e[e$area=="north" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
n.num.ber=length(g$EID[g$SEX=="Eggs"])
n.num.not=length(g$EID[g$SEX=="No Eggs"])
n.per.ber=n.num.ber/(n.num.ber + n.num.not)*100
n.output=c(w,n.per.ber)
n.berried=rbind(n.berried, n.output)
}
names(n.berried)=c("Week", "N.Percent Berried")
c.berried=data.frame() #central
for (w in week){
g=e[e$area=="central" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
c.num.ber=length(g$EID[g$SEX=="Eggs"])
c.num.not=length(g$EID[g$SEX=="No Eggs"])
c.per.ber=c.num.ber/(c.num.ber + c.num.not)*100
c.output=c(w,c.per.ber)
c.berried=rbind(c.berried, c.output)
}
names(c.berried)=c("Week", "C.Percent Berried")
s.berried=data.frame() #south
for (w in week){
g=e[e$area=="south" & e$CARLENGTH>78 & e$CARLENGTH<82.5,]
g=g[g$WOS %in% w,]
s.num.ber=length(g$EID[g$SEX=="Eggs"])
s.num.not=length(g$EID[g$SEX=="No Eggs"])
s.per.ber=s.num.ber/(s.num.ber + s.num.not)*100
s.output=c(w,s.per.ber)
s.berried=rbind(s.berried, s.output)
}
names(s.berried)=c("Week", "S.Percent Berried")
ber=cbind(berried, n.berried[2], c.berried [2], s.berried[2], by=berried$Week)
png(filename=paste0(figdir,"/Sublegal Percent Berried LFA 27.png"))
plot(berried$Week, berried$`Percent Berried`, main="LFA 27", ylab="% Berried", xlab="Week of Season", col="green", type="n", ylim=c(15, 35))
#points(berried$Week, berried$`Percent Berried`, col="green", pch=16)
#lines(berried$Week, berried$`Percent Berried`, col="green")
points(ber$Week, ber$`N.Percent Berried`, col="red", pch=16)
lines(ber$Week, ber$`N.Percent Berried`, col="red")
points(ber$Week, ber$`C.Percent Berried`, col="blue", pch=16)
lines(ber$Week, ber$`C.Percent Berried`, col="blue")
points(ber$Week, ber$`S.Percent Berried`, col="green", pch=16)
lines(ber$Week, ber$`S.Percent Berried`, col="green")
legend(x = "bottomright", legend = c("North", "Central", "South"),lty = c(1, 1), col = c("red", "blue", "green"), bty="n", pch=16)
dev.off()
#Discards
#---------------------------------------
lfas= c("33", "34")
a=atSea.clean[atSea.clean$LFA %in% lfas,]
a$yr=year(a$STARTDATE)
b=a[a$yr>2009,]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
c=b[b$LFA==l,]
#All Areas
lfas= c("33", "34")
catches=data.frame(matrix(, nrow=length(lfas), ncol=5))
names(catches)=c("LFA","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$LFA=lfas
for (i in 1:length(lfas)){
l=lfas[i]
c=b[b$LFA==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
#discard=rbind(u,berried)
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$LFA==l]=tot-under-o.egg-u.egg
catches$Undersize[catches$LFA==l]=under
catches$Over.Berried[catches$LFA==l]=o.egg
catches$Under.Berried[catches$LFA==l]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("LFA", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("LFA", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
names(catches)=c("LFA", "Legal-Size", "Legal-Size Egged", "Undersize Egged", "Undersize")
bar.p=melt(catches, id.vars="LFA")
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/catch_proportions_33-34.png"),width = 150, height = 150, units='mm', res = 600)
ggplot(bar.p, aes(x = LFA, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="Lobster") +
labs( x="Lobster Fishing Area", y= "% of Catch")
dev.off()
# Discards 27 North vs Central vs South
b=a[a$yr>2009 & a$LFA=="27",]
b=b[is.finite(b$CARLENGTH) & is.finite(b$SEX),]
c=b
#create North/South index
n.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.North"],div$Y[div$area=="27.North"])==1) #Little River and North
c.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.Central"],div$Y[div$area=="27.Central"])==1) #South Bar to Little River
s.ind=which(point.in.polygon(c$X, c$Y,div$X[div$area=="27.South"],div$Y[div$area=="27.South"])==1) #Gabarus to South Bar
c$area=NA
c$area[n.ind]="North"
c$area[c.ind]="Central"
c$area[s.ind]="South"
b=c[!is.na(c$area),]
areas=c("North","Central", "South")
catches=data.frame(matrix(, nrow=length(areas), ncol=5))
names(catches)=c("Area","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$Area=areas
for (i in 1:length(areas)){
l=areas[i]
c=b[b$area==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$Area==l]=tot-under-o.egg-u.egg
catches$Undersize[catches$Area==l]=under
catches$Over.Berried[catches$Area==l]=o.egg
catches$Under.Berried[catches$Area==l]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("Area", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("Area", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
names(catches)=c("Area", "Legal-Size", "Legal-Size Egged", "Undersize Egged", "Undersize")
bar.p=melt(catches, id.vars="Area")
bar.p$Area=factor(bar.p$Area, levels=c("North", "Central", "South"))
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/catch.proportions LFA 27 by Area.png"))
ggplot(bar.p, aes(x = Area, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="") +
labs( x="LFA27 Sub-Area", y= "% of Catch")
dev.off()
# By week
# ----------------------------------
week=c(1:8)
areas=c("North", "South", "Central")
for (aa in areas){
z=b[b$area %in% aa,]
catches=data.frame(matrix(nrow=length(week), ncol=5))
names(catches)=c("Week","Legal", "Undersize", "Over.Berried", "Under.Berried")
catches$Week=week
for (i in 1:length(week)){
l=week[i]
c=z[z$WOS == l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
catches$Legal[catches$Week==i]=tot-under-o.egg-u.egg
catches$Undersize[catches$Week==i]=under
catches$Over.Berried[catches$Week==i]=o.egg
catches$Under.Berried[catches$Week==i]=u.egg
}
library(reshape2)
library(EnvStats)
names(catches)=c("Week", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
catches=catches[, c("Week", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")] #reorder
names(catches)=c("Week", "Legal", "Legal-Size Eggs", "Undersize Eggs", "Undersize")
bar.p=melt(catches, id.vars="Week")
mycolors <- c("green3", "firebrick4", "coral2", "red1")
png(filename=paste0(figdir,"/weekly.catch.composition.",aa, ".png"))
print(ggplot(bar.p, aes(x = Week, y = value, fill = variable)) +
geom_col(position="fill") +
scale_y_continuous(labels = scales::percent) +
scale_fill_manual(values=mycolors, name="Catch Composition") +
labs( title=paste0(aa), x="Week", y= "% of Catch")
)
dev.off()
}
#Vents
#Comparing catch of 50mm (1 15/16") vs 44mm (1 3/4")
#**Number and placement of vents may also differ
l27=b[b$LFA=="27",]
l27=l27[l27$yr>2016,]
big.vent=l27[l27$CAPTAIN %in% c("David Ferguson", "DAVID FERGUSON"),]
big.vent$vent="Big"
small.vent=l27[l27$CAPTAIN %in% c("Raymond Sherwood", "RAYMOND SHERWOOD"),]
small.vent$vent="Small"
escape=rbind(big.vent, small.vent)
biggest=5*(ceiling(max(escape$CARLENGTH)/5))
vents=unique(escape$vent)
escape$size[escape$vent=="Small"]="44mm"
escape$size[escape$vent=="Big"]="50mm"
for (v in vents){
png(filename=paste0(figdir,"/", v, "Vent.png"))
all=hist(escape$CARLENGTH[escape$vent==v], xlim=c(0,biggest), breaks=seq(0, biggest, 2.5), main=paste0(escape$size[escape$vent==v][1], " Vent"),
col='grey88', xlab="Carapace Length", ylab="Number of Lobster")
abline(v = 82.5, col="red", lwd=2, lty=2)
dev.off()
}
#Hist lines
if (plot.hist.line){
png(filename=paste0(figdir,"/","Vent Comparison.png"))
a=hist(escape$CARLENGTH[escape$vent=="Big"],plot=F, breaks=seq(0, biggest, 2.5))
plot(a$mids,a$density,type='l', xlim=c(0,biggest),col='blue', xlab="Carapace Length", ylab="Proportion of Catch",main="Vent Comparison")
b=hist(escape$CARLENGTH[escape$vent=="Small"],plot=F, breaks=seq(0, biggest, 2.5))
lines(b$mids,b$density,type='l',col='red')
abline(v = 82.5, col="grey50", lwd=0.5, lty=2)
legend(x = "topright", legend = c("44mm", "50mm"), inset=0.05,lty = c(1, 1), col = c("red", "blue"), lwd = 2, title="Vent Height")
dev.off()
}
vent.catches=data.frame(matrix(, nrow=length(unique(vents)), ncol=5))
names(vent.catches)=c("Vent","Legal", "Undersize", "Over.Berried", "Under.Berried")
vent.catches$Vent=vents
for (i in 1:length(vents)){
l=vents[i]
c=escape[escape$vent==l,]
u=c[c$CARLENGTH<83 & c$SEX %in% c(1,2),]
u.ber= c[c$SEX=="3" & c$CARLENGTH<83,]
o.ber=c[c$SEX=="3" & c$CARLENGTH>82,]
#discard=rbind(u,berried)
tot=length(c$SEX)
under=(length(u$SEX))
o.egg=length(o.ber$SEX)
u.egg=length(u.ber$SEX)
dc.num=under+u.egg+o.egg
vent.catches$Legal[vent.catches$Vent==l]=tot-under-o.egg-u.egg
vent.catches$Undersize[vent.catches$Vent==l]=under
vent.catches$Over.Berried[vent.catches$Vent==l]=o.egg
vent.catches$Under.Berried[vent.catches$Vent==l]=u.egg
}
names(vent.catches)=c("Vent", "Legal", "Undersize", ">mls w/eggs", "<mls w/eggs")
vent.catches=vent.catches[, c("Vent", "Legal", ">mls w/eggs", "<mls w/eggs", "Undersize")]
vent.catches$Vent[vent.catches$Vent=="Small"]="44mm"
vent.catches$Vent[vent.catches$Vent=="Big"]="50mm"
bar.v=melt(vent.catches, id.vars="Vent")
ggplot(bar.v, aes(x = Vent, y = value, fill = variable)) + geom_col(position="fill")+ scale_y_continuous(labels = scales::percent)
ggplot(bar.v, aes(x = LFA, y = value, fill = variable)) + geom_col(position="fill")+ scale_y_continuous(labels = scales::percent ) + stat_n_text(size = 4)
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