require(bio.survey)
require(bio.lobster)
require(bio.groundfish)
la()
p = bio.lobster::load.environment()
p$libs = NULL
ff = "LFA34Assessment"
fp1 = file.path(project.datadirectory('bio.lobster'),"analysis",ff)
fpf1 = file.path(project.figuredirectory('bio.lobster'),ff)
p1 = p
p1$yrs = 1969:2019
stratifiedAnalysesBerried = function(p=p1, survey,lfa, fpf = fpf1, fp = fp1,f=ff,ht=ht,wd=wd){
if(survey == 'NEFSC'){
p$years.to.estimate = p$yrs
p$length.based = F
p$size.class= c(120,300)
p$by.sex = T
p$sex = c(3) # male female berried c(1,2,3)
p$bootstrapped.ci=T
p$strata.files.return=F
p$strata.efficiencies=F
p$clusters = c( rep( "localhost", 7) )
p$season =c('spring')# p$series =c('spring');p$series =c('fall')
#Spring restratified to lfa41
p$define.by.polygons = T
p$lobster.subunits=F
p$area = lfa
p$reweight.strata = T #this subsets
p = make.list(list(yrs=p$years.to.estimate),Y=p)
aout= nefsc.analysis(DS='stratified.estimates.redo',p=p)
write.csv(aout,file=file.path(fpf,paste(lfa,'NEFSCSpringberried.csv',sep="-")))
#Figure
p$add.reference.lines = F
p$time.series.start.year = p$years.to.estimate[1]
p$time.series.end.year = p$years.to.estimate[length(p$years.to.estimate)]
p$metric = 'numbers' #weights
p$measure = 'stratified.mean' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = file.path(f,paste(lfa,'NEFSCSpringrestratifiedBerried.png',sep=""))
p$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$error.bars=T
ref.out= figure.stratified.analysis(x=aout,out.dir = 'bio.lobster', p=p,ht=ht,wd=wd)
#Fall restratified to lfa41
p$season =c('fall')
aout= nefsc.analysis(DS='stratified.estimates.redo',p=p)
write.csv(aout,file=file.path(fpf,paste(lfa,'NEFSCfallberried.csv',sep="-")))
#Figure
p$add.reference.lines = F
p$time.series.start.year = p$years.to.estimate[1]
p$time.series.end.year = p$years.to.estimate[length(p$years.to.estimate)]
p$metric = 'numbers' #weights
p$measure = 'stratified.mean' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = file.path(f,paste(lfa,'NEFSCFallrestratifiednumbersBerried.png',sep=""))
p$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$error.bars=T
ref.out= figure.stratified.analysis(x=aout,out.dir = 'bio.lobster', p=p,ht=ht,wd=wd)
}
if(survey=='DFO'){
p$series =c('summer')# p$series =c('georges');p$series =c('fall')
p$define.by.polygons = T
p$lobster.subunits=F
p$area = lfa
p$years.to.estimate = p$yrs[-1]
p$length.based = F
p$by.sex = T
p$sex = c(3)
p$bootstrapped.ci=T
p$strata.files.return=F
p$vessel.correction.fixed=1.2
p$strat = NULL
p$clusters = c( rep( "localhost", 7) )
p$strata.efficiencies = F
p = make.list(list(yrs=p$years.to.estimate),Y=p)
p$reweight.strata = T #this subsets
aout= dfo.rv.analysis(DS='stratified.estimates.redo',p=p)
write.csv(aout,file=file.path(fpf,paste(lfa,'DFOberried.csv',sep="-")))
#Figure
p$add.reference.lines = F
p$time.series.start.year = p$years.to.estimate[1]
p$time.series.end.year = p$years.to.estimate[length(p$years.to.estimate)]
p$metric = 'numbers' #weights
p$measure = 'stratified.mean' #'stratified.total'
p$figure.title = ""
p$reference.measure = 'median' # mean, geomean
p$file.name = p$file.name = file.path(f,paste(lfa,'DFOrestratifiednumbersBerried.png',sep=""))
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
ref.out= figure.stratified.analysis(x=aout,out.dir = 'bio.lobster', p=p,ht=ht,wd=wd)
}
}
stratifiedAnalysesBerried(survey='NEFSC',lfa='LFA34',ht=8,wd=10)
stratifiedAnalysesBerried(survey='DFO',lfa='LFA34',ht=8,wd=10)
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