inst/Frameworks/LFA41Framework/16.refpoints.r
In LobsterScience/bio.lobster: Lobster Stock Assessment Tools for DFO Maritimes
#Old reference levels on new indicators
#RV survey
#40% of median catch 1983-1994
#50% median value of 1995-2009
require(bio.lobster)
p = bio.lobster::load.environment()
require(bio.polygons)
p$libs = NULL
require(PBSmapping)
require(bio.lobster)
require(bio.utilities)
la()
fp = file.path(project.datadirectory('bio.lobster'),'analysis')
figfp = file.path(project.figuredirectory('bio.lobster'))
outref = list()
RR95=list()
RR75 = list()
#logbook data
lobster.db('logs41') #make sure to do a database recapture through logs41.redo before moving on
logs41 = rename.df(logs41,c('FV_FISHED_DATETIME'),c('DATE_FISHED'))
logs41$yr = year(logs41$DATE_FISHED) #2002 to present
ziff41$yr = year(ziff41$DATE_FISHED) #1995 to 2001
ziff41$DDLON = ziff41$DDLON * -1
off41$yr = year(off41$DATE_FISHED) #1981 to 1994
logs41$OFFAREA = NULL
#oct16-oct15 fishing year until 2005 switch to Jan 1 to Dec 31MOnt
a41 = rbind(off41,ziff41,logs41)
a41$fishingYear = sapply(a41$DATE_FISHED,offFishingYear)
a41 = makePBS(a41,polygon=FALSE)
a41$ADJCATCH = a41$ADJCATCH / 2.2 #convert to kgs
TOTALLAND = aggregate(ADJCATCH~fishingYear,data=a41,FUN=sum)
TOTALLAND = rename.df(TOTALLAND,'fishingYear','yr')
#boundaries for fishing data
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
#prune landings to SURVEY
b = find.bio.gis('strat.gf',return.one.match=F)
b = read.table(b)
names(b) <- c('X','Y','PID')
b = within(b,{POS <- ave(PID,list(PID),FUN=seq_along)})
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = subset(b,SID %in% c(1,2))
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
a = merge(TOTALLAND,La,'yr')
RVPropLand = (a[,3]/a[,2])
###DFO RV survey
load(file.path(fp,'stratified.summer.LFA41.restratified.length.all.not.sexed.rdata'))
all.out = out
load(file.path(fp,'stratified.summer.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
a = merge(all.out,out,by='yr')
median(a$w.Yst.y/a$w.Yst.x) #0.876 proportion of total weight that comprises commercial animals....assuming constant over time....
ao = all.out[,c('yr','w.Yst')]
ao$w.Yst = ao$w.Yst * 0.876
ao$w.Yst[ao$yr %in% out$yr] <- out$w.Yst[which(!is.na(out$yr))]
#ao is full time series of biomasses
require(bcp)
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPDFORefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1970
p$time.series.end.year = 2015
p$reference.start.year=1970
p$reference.end.year=2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$add.primary.line=F
p$return.running=T
p$ylim = c(0,3.5)
bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
outbref[[1]] = bref
#based on bcp
lb = median(subset(ao,yr %in% 1970:1999,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2000:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1970:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'DFORefpointsNewArea.png'))
#relative F DFO summer
aa = merge(ao,La,by='yr')
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,13)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2000)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[1]] = quantile(aa$relF[ii],0.75)
RR95[[1]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFDFOSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings / aa$mean/1000
t = which(!is.finite(aa$relF))
aa$mean[t] = 0.001
aa$relF = aa$landings / aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataDFOSurvey.png'))
####################
###Georges
#####################
load(file.path(fp,'stratified.georges.Georges.Canada.base.length.all.not.sexed.rdata'))
aout = out
aout = aout[,c('yr','w.Yst')]
load(file.path(fp,'stratified.georges.Georges.Canada.base.length.83-300.male&female.sexed.rdata'))
out = subset(out,yr>=2007)
out = out[,c('yr','w.Yst')]
aa=merge(out,aout,all.x=T,by='yr')
sum(aa[,2])/sum(aa[,3]) #0.872 commercial
aout$w.Yst = aout$w.Yst * 0.872
aout$w.Yst[aout$yr %in% out$yr] <- out$w.Yst
ao = aout
require(bcp)
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPGeorgesRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1987
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,1.2)
p$return.running=T
outbref[[2]] = bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
#based on bcp
lb = median(subset(ao,yr %in% 1987:1999,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2000:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1987:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'GeorgesRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
b = file.path(project.datadirectory('bio.polygons'),'data','Science','PED','GeorgesBankStrata.rdata')
load(b)
d = joinPolys(LFA41,out,'INT')
attr(d,'projection') <- "LL"
d = joinPolys(d,operation='UNION')
d = subset(d,SID==1)
b = findPolys(completeFun(a41,c('X','Y')),d)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
a = merge(TOTALLAND,La,'yr')
GBPropLand = (a[,3]/a[,2])
aa = merge(ao,La,by='yr')
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1987
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,6)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2000)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[2]] = quantile(aa$relF[ii],0.75)
RR95[[2]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFGeorgesSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings / aa$mean/1000
t = which(!is.finite(aa$relF))
aa$mean[t] = 0.001
aa$relF = aa$landings / aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataGeorgesSurvey.png'))
#######################
###Spring
########################
require(bcp)
load(file.path(fp,'stratified.nefsc.spring.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
ao = out[,c('yr','w.Yst')]
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPSpringRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1969
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,38)
p$return.running=T
outbref[[3]]= bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
lb = median(subset(ao,yr %in% 1969:2000,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2001:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1969:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'SpringRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
a = importShapefile(find.bio.gis('BTS_Strata'),readDBF=T)
l = attributes(a)$PolyData[,c('PID','STRATA')]
a = merge(a,l,by='PID',all.x=T)
# addPolys(a,border='red')
b = subset(a,STRATA %in% c(1160, 1170, 1180, 1190, 1200, 1210, 1220, 1290, 1300, 1340, 1360))
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
aa = merge(ao,La,by='yr')
a = merge(TOTALLAND,La,'yr')
NPropLand = (a[,3]/a[,2])
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = F
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,2)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2001)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[3]] = quantile(aa$relF[ii],0.75)
RR95[[3]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFSpringSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings/aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataSpringSurvey.png'))
#########################################################3
#Fall
load(file.path(fp,'stratified.nefsc.fall.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
ao = out[,c('yr','w.Yst')]
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPAutumnRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1969
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,20)
p$return.running=T
outbref[[4]] = bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
lb = median(subset(ao,yr %in% 1969:2000,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2001:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1969:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'AutumnRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
a = importShapefile(find.bio.gis('BTS_Strata'),readDBF=T)
l = attributes(a)$PolyData[,c('PID','STRATA')]
a = merge(a,l,by='PID',all.x=T)
# addPolys(a,border='red')
b = subset(a,STRATA %in% c(1160, 1170, 1180, 1190, 1200, 1210, 1220, 1290, 1300, 1340, 1360))
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
aa = merge(ao,La,by='yr')
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,2)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2001)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[4]] = quantile(aa$relF[ii],0.75)
RR95[[4]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFAutumnSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings/aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataAutumnSurvey.png'))
save(outbref,file=file.path(project.datadirectory('bio.lobster'),'analysis','RunningMedians.Rdata'))
RVPropLand
GBPropLand
NPropLand
LobsterScience/bio.lobster documentation built on Feb. 14, 2025, 3:28 p.m.
R Package Documentation
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#Old reference levels on new indicators
#RV survey
#40% of median catch 1983-1994
#50% median value of 1995-2009
require(bio.lobster)
p = bio.lobster::load.environment()
require(bio.polygons)
p$libs = NULL
require(PBSmapping)
require(bio.lobster)
require(bio.utilities)
la()
fp = file.path(project.datadirectory('bio.lobster'),'analysis')
figfp = file.path(project.figuredirectory('bio.lobster'))
outref = list()
RR95=list()
RR75 = list()
#logbook data
lobster.db('logs41') #make sure to do a database recapture through logs41.redo before moving on
logs41 = rename.df(logs41,c('FV_FISHED_DATETIME'),c('DATE_FISHED'))
logs41$yr = year(logs41$DATE_FISHED) #2002 to present
ziff41$yr = year(ziff41$DATE_FISHED) #1995 to 2001
ziff41$DDLON = ziff41$DDLON * -1
off41$yr = year(off41$DATE_FISHED) #1981 to 1994
logs41$OFFAREA = NULL
#oct16-oct15 fishing year until 2005 switch to Jan 1 to Dec 31MOnt
a41 = rbind(off41,ziff41,logs41)
a41$fishingYear = sapply(a41$DATE_FISHED,offFishingYear)
a41 = makePBS(a41,polygon=FALSE)
a41$ADJCATCH = a41$ADJCATCH / 2.2 #convert to kgs
TOTALLAND = aggregate(ADJCATCH~fishingYear,data=a41,FUN=sum)
TOTALLAND = rename.df(TOTALLAND,'fishingYear','yr')
#boundaries for fishing data
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
#prune landings to SURVEY
b = find.bio.gis('strat.gf',return.one.match=F)
b = read.table(b)
names(b) <- c('X','Y','PID')
b = within(b,{POS <- ave(PID,list(PID),FUN=seq_along)})
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = subset(b,SID %in% c(1,2))
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
a = merge(TOTALLAND,La,'yr')
RVPropLand = (a[,3]/a[,2])
###DFO RV survey
load(file.path(fp,'stratified.summer.LFA41.restratified.length.all.not.sexed.rdata'))
all.out = out
load(file.path(fp,'stratified.summer.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
a = merge(all.out,out,by='yr')
median(a$w.Yst.y/a$w.Yst.x) #0.876 proportion of total weight that comprises commercial animals....assuming constant over time....
ao = all.out[,c('yr','w.Yst')]
ao$w.Yst = ao$w.Yst * 0.876
ao$w.Yst[ao$yr %in% out$yr] <- out$w.Yst[which(!is.na(out$yr))]
#ao is full time series of biomasses
require(bcp)
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPDFORefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1970
p$time.series.end.year = 2015
p$reference.start.year=1970
p$reference.end.year=2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$add.primary.line=F
p$return.running=T
p$ylim = c(0,3.5)
bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
outbref[[1]] = bref
#based on bcp
lb = median(subset(ao,yr %in% 1970:1999,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2000:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1970:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'DFORefpointsNewArea.png'))
#relative F DFO summer
aa = merge(ao,La,by='yr')
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,13)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2000)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[1]] = quantile(aa$relF[ii],0.75)
RR95[[1]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFDFOSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings / aa$mean/1000
t = which(!is.finite(aa$relF))
aa$mean[t] = 0.001
aa$relF = aa$landings / aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataDFOSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr,ylim=c(0,12))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataDFOSurvey.png'))
####################
###Georges
#####################
load(file.path(fp,'stratified.georges.Georges.Canada.base.length.all.not.sexed.rdata'))
aout = out
aout = aout[,c('yr','w.Yst')]
load(file.path(fp,'stratified.georges.Georges.Canada.base.length.83-300.male&female.sexed.rdata'))
out = subset(out,yr>=2007)
out = out[,c('yr','w.Yst')]
aa=merge(out,aout,all.x=T,by='yr')
sum(aa[,2])/sum(aa[,3]) #0.872 commercial
aout$w.Yst = aout$w.Yst * 0.872
aout$w.Yst[aout$yr %in% out$yr] <- out$w.Yst
ao = aout
require(bcp)
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPGeorgesRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1987
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,1.2)
p$return.running=T
outbref[[2]] = bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
#based on bcp
lb = median(subset(ao,yr %in% 1987:1999,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2000:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1987:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'GeorgesRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
b = file.path(project.datadirectory('bio.polygons'),'data','Science','PED','GeorgesBankStrata.rdata')
load(b)
d = joinPolys(LFA41,out,'INT')
attr(d,'projection') <- "LL"
d = joinPolys(d,operation='UNION')
d = subset(d,SID==1)
b = findPolys(completeFun(a41,c('X','Y')),d)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
a = merge(TOTALLAND,La,'yr')
GBPropLand = (a[,3]/a[,2])
aa = merge(ao,La,by='yr')
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1987
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,6)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2000)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[2]] = quantile(aa$relF[ii],0.75)
RR95[[2]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFGeorgesSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings / aa$mean/1000
t = which(!is.finite(aa$relF))
aa$mean[t] = 0.001
aa$relF = aa$landings / aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataGeorgesSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr,ylims=c(0,6))
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataGeorgesSurvey.png'))
#######################
###Spring
########################
require(bcp)
load(file.path(fp,'stratified.nefsc.spring.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
ao = out[,c('yr','w.Yst')]
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPSpringRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1969
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,38)
p$return.running=T
outbref[[3]]= bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
lb = median(subset(ao,yr %in% 1969:2000,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2001:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1969:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'SpringRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
a = importShapefile(find.bio.gis('BTS_Strata'),readDBF=T)
l = attributes(a)$PolyData[,c('PID','STRATA')]
a = merge(a,l,by='PID',all.x=T)
# addPolys(a,border='red')
b = subset(a,STRATA %in% c(1160, 1170, 1180, 1190, 1200, 1210, 1220, 1290, 1300, 1340, 1360))
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
aa = merge(ao,La,by='yr')
a = merge(TOTALLAND,La,'yr')
NPropLand = (a[,3]/a[,2])
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = F
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,2)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2001)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[3]] = quantile(aa$relF[ii],0.75)
RR95[[3]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFSpringSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings/aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataSpringSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataSpringSurvey.png'))
#########################################################3
#Fall
load(file.path(fp,'stratified.nefsc.fall.LFA41.restratified.length.83-300.male&female.sexed.rdata'))
ao = out[,c('yr','w.Yst')]
h = subset(ao,w.Yst>0) #need to remove the zeros for bcp to function correctly
b = bcp(log(h$w.Yst),w0 = 0.2, p0 = 0.05)
plot(b,xaxlab=h$yr,xlab='Year')
savePlot(file.path(figfp,'BCPAutumnRefpointsNewArea.png'))
p=list()
p$add.reference.lines = FALSE
p$user.defined.references=NULL
p$time.series.start.year = 1969
p$time.series.end.year = 2015
p$metric = 'weights' #weights
p$measure = 'stratified.total' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'DFOrestratRefLines.png'
p$l.reference.start.year = 1983
p$l.reference.end.year = 2015
p$lref = 0.4*median(out$n.yst[which(out$yr %in% p$l.reference.start.year:p$l.reference.end.year)])
p$u.reference.start.year = 1983
p$u.reference.end.year = 2015
p$uref = median(out$n.yst[which(out$yr %in% 1995:2015)])
p$y.maximum = NULL # NULL # if ymax is too high for one year
p$show.truncated.numbers = F #if using ymax and want to show the numbers that are cut off as values on figure
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=T
p$ylim = c(0,20)
p$return.running=T
outbref[[4]] = bref= figure.stratified.analysis(x=ao,out.dir = 'bio.lobster', p=p,save=F)
lb = median(subset(ao,yr %in% 1969:2000,select=w.Yst)[,1])/1000
ub = median(subset(ao,yr %in% 2001:2015,select=w.Yst)[,1])/1000 * 0.4
nub = median(subset(ao,yr %in% 1969:2015,select=w.Yst)[,1])/1000
llb = ao$w.Yst[which(ao$w.Yst>0)]
llb = median(sort(llb)[1:5])/1000
abline(h=llb,col='orange',lwd=2)
abline(h=lb,col='blue',lwd=2)
abline(h=ub,col='green',lwd=2)
abline(h=nub,col='purple',lwd=2)
savePlot(file.path(figfp,'AutumnRefpointsNewArea.png'))
#polygon for landings
LFA41 = read.csv(file.path( project.datadirectory("bio.lobster"), "data","maps","LFA41Offareas.csv"))
LFA41 = joinPolys(as.PolySet(LFA41),operation='UNION')
LFA41 = subset(LFA41,SID==1)
attr(LFA41,'projection') <- 'LL'
a = importShapefile(find.bio.gis('BTS_Strata'),readDBF=T)
l = attributes(a)$PolyData[,c('PID','STRATA')]
a = merge(a,l,by='PID',all.x=T)
# addPolys(a,border='red')
b = subset(a,STRATA %in% c(1160, 1170, 1180, 1190, 1200, 1210, 1220, 1290, 1300, 1340, 1360))
b = joinPolys(b,operation='UNION')
b = joinPolys(b,LFA41,'INT')
b = findPolys(completeFun(a41,c('X','Y')),b)$EID
aS = subset(a41,EID %in% b)
La = aggregate(ADJCATCH~fishingYear,data=aS,FUN=sum)
La$landings = La$ADJCATCH / 1000
La = rename.df(La,'fishingYear','yr')
aa = merge(ao,La,by='yr')
###relative F
aa$relF = aa$landings / aa$w.Yst
t = which(is.finite(aa$relF))
p$add.reference.lines = FALSE
p$time.series.start.year = 1981
p$time.series.end.year = 2015
p$metric = 'relF' #weights
p$measure = '' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = 'relFSummerRV.png'
p$ylim = c(0,2)
p$legend = FALSE
p$running.median = T
p$running.length = 3
p$running.mean = F #can only have rmedian or rmean
p$error.polygon=F
p$error.bars=F
p$return.running=T
ii = which(aa$yr<2001)
ii = intersect(t,ii)
ap = median(aa$relF[ii])
apt = median(aa$relF[t])
RR75[[4]] = quantile(aa$relF[ii],0.75)
RR95[[4]] = quantile(aa$relF[ii],0.95)
rref= figure.stratified.analysis(x=aa,out.dir = 'bio.lobster', p=p,save=F)
abline(h=ap,col='blue',lwd=2)
abline(h=apt,col='purple',lwd=2)
savePlot(file.path(project.figuredirectory('bio.lobster'),'relFAutumnSurvey.png'))
#HCR plots
aa = merge(bref,aa,by='yr')
aa$relF = aa$landings/aa$mean/1000
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=lb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=lb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRLongTermDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=ub,LRP=llb,RR=ap,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbDataAutumnSurvey.png'))
hcrPlot(B=aa$mean,mF=aa$relF,USR=nub,LRP=llb,RR=apt,yrs=aa$yr)
savePlot(file.path(project.figuredirectory('bio.lobster'),'HCRllbLongTermDataAutumnSurvey.png'))
save(outbref,file=file.path(project.datadirectory('bio.lobster'),'analysis','RunningMedians.Rdata'))
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