inst/Frameworks/LFA3438Framework/LFA34-38Framework/17.CPUEextended.r
In LobsterScience/bio.lobster: Lobster Stock Assessment Tools for DFO Maritimes
require(bio.lobster)
require(bio.utilities)
p = bio.lobster::load.environment()
la()
assessment.year = 2018 ########### check the year ############### !!!!!!!!!!!
p$syr = 1989
p$yrs = p$syr:(p$current.assessment.year-1)
figdir = file.path(project.datadirectory("bio.lobster"),"figures","LFA3438Framework2019")
p$lfas = c("34", "35", "36", "38") # specify lfas for data summary
p$subareas = c("34", "35", "36", "38") # specify lfas for data summary
lS<-lobster.db('process.logs')
lS = subset(lS,SYEAR<2019)
H = lobster.db('historic.cpue')
H$CPUE = H$LBSPTRAP/2.2046
lobster.db('process.vlog')
V = vlog
V$SYEAR = as.numeric(year(V$FDATE))
V$SYEAR = year(V$FDATE)
V$MONTH = month(V$FDATE)
ii = which(V$MONTH>8)
V$SYEAR[ii] = V$SYEAR[ii]+1
##LFA 34
H34 = aggregate(CPUE~LFA+SYEAR+SDATE,data=subset(H, LFA==34 & SYEAR<1960),FUN=mean)
H34 = H34[order(H34$SDATE),]
names(H34) = c('LFA','SYEAR','SDATE','CPUE')
aH34 = aggregate(cbind(CPUE,SDATE)~LFA+SYEAR,data=subset(H, LFA==34 & SYEAR<1960),FUN=mean)
V34 = aggregate(cbind(W_KG,N_TRP)~LFA+SYEAR+FDATE, data=subset(V,LFA==34), FUN=sum)
V34$CPUE = V34$W_KG / V34$N_TRP
V34$W_KG = V34$N_TRP = NULL
names(V34) = c('LFA','SYEAR','SDATE','CPUE')
#kludge
V34$SYEAR[which(abs(V34$SYEAR-year(V34$SDATE))< -1)] = 1991
aV34 = aggregate(cbind(W_KG,N_TRP)~LFA+SYEAR, data=subset(V,LFA==34), FUN=sum)
aV34$CPUE = aV34$W_KG / aV34$N_TRP
aV34$W_KG = aV34$N_TRP = NULL
names(aV34) = c('LFA','SYEAR','CPUE')
aaV34 = aggregate(FDATE~LFA+SYEAR, data=subset(V,LFA==34), FUN=mean)
names(aaV34)[3] = 'SDATE'
aV34 = merge(aV34,aaV34)
L34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+DATE_FISHED, data=subset(lS,LFA==34), FUN=sum)
L34$CPUE = L34$WEIGHT_KG / L34$NUM_OF_TRAPS
L34$WEIGHT_KG = L34$NUM_OF_TRAPS = NULL
names(L34) = c('LFA','SYEAR','SDATE','CPUE')
aL34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA==34), FUN=sum)
aL34$CPUE = aL34$WEIGHT_KG / aL34$NUM_OF_TRAPS
aL34$WEIGHT_KG = aL34$NUM_OF_TRAPS = NULL
names(aL34) = c('LFA','SYEAR','CPUE')
aaL34 = aggregate(DATE_FISHED~LFA+SYEAR, data=subset(lS,LFA==34), FUN=mean)
names(aaL34)[3] = 'SDATE'
aL34 = merge(aL34,aaL34)
b34 = as.data.frame(rbind(rbind(H34,V34),L34))
bb34 = as.data.frame(rbind(rbind(aH34,aV34),aL34))
yy = unique(a34$SYEAR)
bb34$SDATE = as.POSIXct(paste(bb34$SYEAR,'01','01',sep="-"))
with(b34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5)))
for(i in yy){
with(subset(b34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(bb34,SYEAR<1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
with(subset(bb34,SYEAR>1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
#################
##LFA 35 not enough data to make it worth it
##LFA 38
H34 = aggregate(CPUE~LFA+SYEAR+SDATE,data=subset(H, LFA==38 & SYEAR<1960),FUN=mean)
H34 = H34[order(H34$SDATE),]
names(H34) = c('LFA','SYEAR','SDATE','CPUE')
aH34 = aggregate(cbind(CPUE,SDATE)~LFA+SYEAR,data=subset(H, LFA==38 & SYEAR<1960),FUN=mean)
#kludge
L34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+DATE_FISHED, data=subset(lS,LFA==38), FUN=sum)
L34$CPUE = L34$WEIGHT_KG / L34$NUM_OF_TRAPS
L34$WEIGHT_KG = L34$NUM_OF_TRAPS = NULL
names(L34) = c('LFA','SYEAR','SDATE','CPUE')
aL34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA==38), FUN=sum)
aL34$CPUE = aL34$WEIGHT_KG / aL34$NUM_OF_TRAPS
aL34$WEIGHT_KG = aL34$NUM_OF_TRAPS = NULL
names(aL34) = c('LFA','SYEAR','CPUE')
aaL34 = aggregate(DATE_FISHED~LFA+SYEAR, data=subset(lS,LFA==38), FUN=mean)
names(aaL34)[3] = 'SDATE'
aL34 = merge(aL34,aaL34)
a34 = as.data.frame(rbind(H34,L34))
aa34 = as.data.frame(rbind(aH34,aL34))
yy = unique(a34$SYEAR)
aa34$SDATE = as.POSIXct(paste(aa34$SYEAR,'01','01',sep="-"))
with(a34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5)))
for(i in yy){
with(subset(a34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(aa34,SYEAR<1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
with(subset(aa34,SYEAR>1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
###plots
lS<-lobster.db('process.logs')
lS = subset(lS,SYEAR<2019)
lS$SDATE = as.POSIXct(lS$DATE_FISHED)
ade = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+SDATE, data=subset(lS,LFA %in% c(35,36)), FUN=sum)
ade$CPUE = ade$WEIGHT_KG/ade$NUM_OF_TRAPS
adem = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA %in% c(35,36)), FUN=sum)
adem$CPUE = adem$WEIGHT_KG/adem$NUM_OF_TRAPS
adem$SDATE = as.POSIXct(paste(adem$SYEAR,'01','01',sep="-"))
xlims=c(min(b34$SDATE),max(b34$SDATE))
lfa = c(34,35,36,38)
fpf1 = file.path(project.figuredirectory('bio.lobster'),"LFA3438Framework2019")
pdf(file.path( fpf1,paste0("CPUERawHistoric.pdf")),8,11)
par(mfrow=c(length(lfa),1),mar=c(0,0,0,0),omi=c(0.5,1,0.5,0.5),las=1)
for(j in 1:length(lfa)){
if(lfa[j] == 34){
with(b34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims))
yy = unique(bb34$SYEAR)
for(i in yy){
with(subset(b34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(bb34,SYEAR<1970),points(CPUE~SDATE,pch=21,bg='red',type='b'))
with(subset(bb34,SYEAR>1970),points(CPUE~SDATE,pch=21,bg='red',type='b'))
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
if(lfa[j]== 38){
with(a34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims))
yy = unique(aa34$SYEAR)
for(i in yy){
with(subset(a34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(aa34,SYEAR<1970),points(CPUE~SDATE, pch=21,bg='red',type='b'))
with(subset(aa34,SYEAR>1970),points(CPUE~SDATE, pch=21,bg='red',type='b'))
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
if(lfa[j] %in% c(35, 36)){
yy = unique(subset(ade,LFA==lfa[j])$SYEAR)
plot(CPUE~SDATE,subset(ade,LFA==lfa[j]),type='n',ylim=c(0,max(ade$CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims)
for(i in yy){
lines(CPUE~SDATE,subset(ade,LFA==lfa[j]& SYEAR==i),type='l',col=rgb(0,0,0,0.5))
}
lines(CPUE~SDATE,subset(adem,LFA==lfa[j]),type='b',pch=21,bg='red')
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
}
mtext("CPUE (kg/TH)", 2, 3, outer = T, cex = 1.5,las=0)
dev.off()
#####cpue v modelled resutls
cp = read.csv(file.path(project.datadirectory('bio.lobster'),'analysis','LFA34-38','indicators','CPUEmodelindex.csv'))
ll = unique(cp$LFA)
fpf1 = file.path(project.figuredirectory('bio.lobster'),"LFA3438Framework2019")
pdf(file.path( fpf1,paste0("CPUEAnnualModel1.pdf")),8,11)
par(mfrow=c(length(ll),1),mar=c(0,0,0,0),omi=c(0.5,1,0.5,0.5),las=1)
xlims=c(min(cp$YEAR), max(cp$YEAR))
ylims=c(1.8,max(cp$ub)*1.1)
for(i in ll){
c5 = subset(cp,LFA==i)
with(c5, plot(YEAR, mu, xlab='Year',ylab='Modelled CPUE' ,type='b' , xlim=xlims,ylim=ylims,pch=21,bg='red'))
with(c5, arrows(YEAR,y0=lb,y1=ub,length=0))
text(min(cp$YEAR,na.rm=T),max(cp$ub,na.rm=T)*.8,paste("LFA",i),cex=2,pos=4)
}
dev.off()
LobsterScience/bio.lobster documentation built on Feb. 14, 2025, 3:28 p.m.
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require(bio.lobster)
require(bio.utilities)
p = bio.lobster::load.environment()
la()
assessment.year = 2018 ########### check the year ############### !!!!!!!!!!!
p$syr = 1989
p$yrs = p$syr:(p$current.assessment.year-1)
figdir = file.path(project.datadirectory("bio.lobster"),"figures","LFA3438Framework2019")
p$lfas = c("34", "35", "36", "38") # specify lfas for data summary
p$subareas = c("34", "35", "36", "38") # specify lfas for data summary
lS<-lobster.db('process.logs')
lS = subset(lS,SYEAR<2019)
H = lobster.db('historic.cpue')
H$CPUE = H$LBSPTRAP/2.2046
lobster.db('process.vlog')
V = vlog
V$SYEAR = as.numeric(year(V$FDATE))
V$SYEAR = year(V$FDATE)
V$MONTH = month(V$FDATE)
ii = which(V$MONTH>8)
V$SYEAR[ii] = V$SYEAR[ii]+1
##LFA 34
H34 = aggregate(CPUE~LFA+SYEAR+SDATE,data=subset(H, LFA==34 & SYEAR<1960),FUN=mean)
H34 = H34[order(H34$SDATE),]
names(H34) = c('LFA','SYEAR','SDATE','CPUE')
aH34 = aggregate(cbind(CPUE,SDATE)~LFA+SYEAR,data=subset(H, LFA==34 & SYEAR<1960),FUN=mean)
V34 = aggregate(cbind(W_KG,N_TRP)~LFA+SYEAR+FDATE, data=subset(V,LFA==34), FUN=sum)
V34$CPUE = V34$W_KG / V34$N_TRP
V34$W_KG = V34$N_TRP = NULL
names(V34) = c('LFA','SYEAR','SDATE','CPUE')
#kludge
V34$SYEAR[which(abs(V34$SYEAR-year(V34$SDATE))< -1)] = 1991
aV34 = aggregate(cbind(W_KG,N_TRP)~LFA+SYEAR, data=subset(V,LFA==34), FUN=sum)
aV34$CPUE = aV34$W_KG / aV34$N_TRP
aV34$W_KG = aV34$N_TRP = NULL
names(aV34) = c('LFA','SYEAR','CPUE')
aaV34 = aggregate(FDATE~LFA+SYEAR, data=subset(V,LFA==34), FUN=mean)
names(aaV34)[3] = 'SDATE'
aV34 = merge(aV34,aaV34)
L34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+DATE_FISHED, data=subset(lS,LFA==34), FUN=sum)
L34$CPUE = L34$WEIGHT_KG / L34$NUM_OF_TRAPS
L34$WEIGHT_KG = L34$NUM_OF_TRAPS = NULL
names(L34) = c('LFA','SYEAR','SDATE','CPUE')
aL34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA==34), FUN=sum)
aL34$CPUE = aL34$WEIGHT_KG / aL34$NUM_OF_TRAPS
aL34$WEIGHT_KG = aL34$NUM_OF_TRAPS = NULL
names(aL34) = c('LFA','SYEAR','CPUE')
aaL34 = aggregate(DATE_FISHED~LFA+SYEAR, data=subset(lS,LFA==34), FUN=mean)
names(aaL34)[3] = 'SDATE'
aL34 = merge(aL34,aaL34)
b34 = as.data.frame(rbind(rbind(H34,V34),L34))
bb34 = as.data.frame(rbind(rbind(aH34,aV34),aL34))
yy = unique(a34$SYEAR)
bb34$SDATE = as.POSIXct(paste(bb34$SYEAR,'01','01',sep="-"))
with(b34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5)))
for(i in yy){
with(subset(b34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(bb34,SYEAR<1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
with(subset(bb34,SYEAR>1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
#################
##LFA 35 not enough data to make it worth it
##LFA 38
H34 = aggregate(CPUE~LFA+SYEAR+SDATE,data=subset(H, LFA==38 & SYEAR<1960),FUN=mean)
H34 = H34[order(H34$SDATE),]
names(H34) = c('LFA','SYEAR','SDATE','CPUE')
aH34 = aggregate(cbind(CPUE,SDATE)~LFA+SYEAR,data=subset(H, LFA==38 & SYEAR<1960),FUN=mean)
#kludge
L34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+DATE_FISHED, data=subset(lS,LFA==38), FUN=sum)
L34$CPUE = L34$WEIGHT_KG / L34$NUM_OF_TRAPS
L34$WEIGHT_KG = L34$NUM_OF_TRAPS = NULL
names(L34) = c('LFA','SYEAR','SDATE','CPUE')
aL34 = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA==38), FUN=sum)
aL34$CPUE = aL34$WEIGHT_KG / aL34$NUM_OF_TRAPS
aL34$WEIGHT_KG = aL34$NUM_OF_TRAPS = NULL
names(aL34) = c('LFA','SYEAR','CPUE')
aaL34 = aggregate(DATE_FISHED~LFA+SYEAR, data=subset(lS,LFA==38), FUN=mean)
names(aaL34)[3] = 'SDATE'
aL34 = merge(aL34,aaL34)
a34 = as.data.frame(rbind(H34,L34))
aa34 = as.data.frame(rbind(aH34,aL34))
yy = unique(a34$SYEAR)
aa34$SDATE = as.POSIXct(paste(aa34$SYEAR,'01','01',sep="-"))
with(a34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5)))
for(i in yy){
with(subset(a34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(aa34,SYEAR<1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
with(subset(aa34,SYEAR>1970),points(CPUE~SDATE, col='red',pch=16,type='b'))
###plots
lS<-lobster.db('process.logs')
lS = subset(lS,SYEAR<2019)
lS$SDATE = as.POSIXct(lS$DATE_FISHED)
ade = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR+SDATE, data=subset(lS,LFA %in% c(35,36)), FUN=sum)
ade$CPUE = ade$WEIGHT_KG/ade$NUM_OF_TRAPS
adem = aggregate(cbind(WEIGHT_KG,NUM_OF_TRAPS)~LFA+SYEAR, data=subset(lS,LFA %in% c(35,36)), FUN=sum)
adem$CPUE = adem$WEIGHT_KG/adem$NUM_OF_TRAPS
adem$SDATE = as.POSIXct(paste(adem$SYEAR,'01','01',sep="-"))
xlims=c(min(b34$SDATE),max(b34$SDATE))
lfa = c(34,35,36,38)
fpf1 = file.path(project.figuredirectory('bio.lobster'),"LFA3438Framework2019")
pdf(file.path( fpf1,paste0("CPUERawHistoric.pdf")),8,11)
par(mfrow=c(length(lfa),1),mar=c(0,0,0,0),omi=c(0.5,1,0.5,0.5),las=1)
for(j in 1:length(lfa)){
if(lfa[j] == 34){
with(b34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims))
yy = unique(bb34$SYEAR)
for(i in yy){
with(subset(b34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(bb34,SYEAR<1970),points(CPUE~SDATE,pch=21,bg='red',type='b'))
with(subset(bb34,SYEAR>1970),points(CPUE~SDATE,pch=21,bg='red',type='b'))
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
if(lfa[j]== 38){
with(a34,plot(CPUE~SDATE,type='n',ylim=c(0,max(CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims))
yy = unique(aa34$SYEAR)
for(i in yy){
with(subset(a34,SYEAR==i),lines(CPUE~SDATE, col=rgb(0,0,0,0.5)))
}
with(subset(aa34,SYEAR<1970),points(CPUE~SDATE, pch=21,bg='red',type='b'))
with(subset(aa34,SYEAR>1970),points(CPUE~SDATE, pch=21,bg='red',type='b'))
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
if(lfa[j] %in% c(35, 36)){
yy = unique(subset(ade,LFA==lfa[j])$SYEAR)
plot(CPUE~SDATE,subset(ade,LFA==lfa[j]),type='n',ylim=c(0,max(ade$CPUE,na.rm=T)),col=rgb(0,0,0,0.5),xlim=xlims)
for(i in yy){
lines(CPUE~SDATE,subset(ade,LFA==lfa[j]& SYEAR==i),type='l',col=rgb(0,0,0,0.5))
}
lines(CPUE~SDATE,subset(adem,LFA==lfa[j]),type='b',pch=21,bg='red')
text(min(b34$SDATE,na.rm=T),max(b34$CPUE,na.rm=T)*.8,paste("LFA",lfa[j]),cex=2,pos=4)
}
}
mtext("CPUE (kg/TH)", 2, 3, outer = T, cex = 1.5,las=0)
dev.off()
#####cpue v modelled resutls
cp = read.csv(file.path(project.datadirectory('bio.lobster'),'analysis','LFA34-38','indicators','CPUEmodelindex.csv'))
ll = unique(cp$LFA)
fpf1 = file.path(project.figuredirectory('bio.lobster'),"LFA3438Framework2019")
pdf(file.path( fpf1,paste0("CPUEAnnualModel1.pdf")),8,11)
par(mfrow=c(length(ll),1),mar=c(0,0,0,0),omi=c(0.5,1,0.5,0.5),las=1)
xlims=c(min(cp$YEAR), max(cp$YEAR))
ylims=c(1.8,max(cp$ub)*1.1)
for(i in ll){
c5 = subset(cp,LFA==i)
with(c5, plot(YEAR, mu, xlab='Year',ylab='Modelled CPUE' ,type='b' , xlim=xlims,ylim=ylims,pch=21,bg='red'))
with(c5, arrows(YEAR,y0=lb,y1=ub,length=0))
text(min(cp$YEAR,na.rm=T),max(cp$ub,na.rm=T)*.8,paste("LFA",i),cex=2,pos=4)
}
dev.off()
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