# code used to generate stats and figures for St Anns Bank assessment
# this is the main calling program
# new comment
year.assessment = 2016
p = aegis::aegis_parameters( DS="mpa", yrs=1999:year.assessment )
p$stmv_local_modelengine = "gam"
p = aegis::aegis_parameters( p=p, DS="stmv" )
polys = mpa.db( p=p, DS="polygons.redo" ) # obtain and save a local cache of polygons of the mpa/aoi
# polys = mpa.db( p=p, DS="polygons" )
# 1. close-up map of area of interest:
figure.mpa.closeup(p)
# 2. map of area of interest:
figure.mpa.aoi(p )
# 3. survey.db trawl data summaries
pdf( file=file.path(p$project.outdir.root, "trawl.time.density.pdf") )
ss = survey.db( p=p, DS="set.base" )
dscols = c( snowcrab="green", groundfish="orange" )
plot( jitter( dyear) ~ jitter(yr), ss, pch=".", col=dscols[ss$data.source], xlab="Year", ylab="Fractional year", cex=1.5 )
dev.off()
pdf( file=file.path(p$project.outdir.root, "maps", "trawl.spatial.density.pdf") )
ss = survey.db( p=p, DS="set.base" )
dscols = c( snowcrab="green", groundfish="orange" )
figure.trawl.density(p=p, ss=ss, dscols=dscols )
dev.off()
# 4. net mensuration related figures
p$scanmar.dir = file.path( project.datadirectory("aegis"), "data", "nets", "Scanmar" )
p$marport.dir = file.path( project.datadirectory("aegis"), "data", "nets", "Marport" )
netmensuration.figures( DS="all", p=p, outdir=p$project.outdir.root ) # for latex a copy here
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