R/figure.timeseries.bycatch.r

In jae0/snowcrab: Snow crab assessment suite using aegis* and associated projects and data streams.

  figure.timeseries.bycatch = function(p, outdir, species,  plotyears, type='mass', all.areas=T, graphic='pdf', plotmethod="default",
    regions = c("cfanorth", "cfasouth", "cfa4x"),  region_label = c("N-ENS", "S-ENS", "4X")  ) {

    outdir=file.path(p$annual.results, "timeseries", "survey")

    if (!all.areas) {
      # not for default method .. only for lattice-based stuff
      regions = c("cfasouth", "cfanorth" )
      region_label = c("S-ENS", "N-ENS")
    }  
    
    n.region_label = length(region_label)
    n.regions = length(regions)
 
    spcd = groundfish_survey_db( DS="spcodes")
    tdb = snowcrab.timeseries.db( DS="biologicals", p=p )
    if(missing(species)){
      cat = snowcrab.db( DS="cat.initial" )
      species = unique(cat$spec)
    }
    v = paste("ms", type, species,sep='.')
    spcd = subset(spcd,code%in%species)
    if (missing(plotyears)) plotyears = unique(tdb$year)
 
    for(i in 1:length(v)){

      td = tdb[ which( tdb$variable == v[i] & tdb$year%in%plotyears) ,]
      td = td[ order(td$region, td$year) , ]
      td$region = factor(td$region, levels=regions, labels =region_label)
      td = td[(which(!is.na(td$region))), ]

      common = spcd$comm[which(spcd$code==species[i])]

      ylim='NULL'
      ylim[2]=max(td$ub,na.rm=T)*1.05
      ylim[1]=0
      xlim=range(td$year); xlim[1]=xlim[1]; xlim[2]=xlim[2]

      xlabels = seq(min(xlim), max(xlim), 1)
      ylabels = pretty(ylim,8)

      dir.create( outdir, recursive=T, showWarnings=F )
      fn = file.path( outdir, paste( v[i], graphic,  sep="." ) )
      cex.main = 1.4
      cex.lab = 1
      cex.axis = 0.2

      if (plotmethod=="default") {
        require(ggplot2)
 
        color_map = c("#E69F00", "#56B4E9",  "#CC79A7" )

        out = ggplot(td, aes(x=year, y=mean, fill=region, colour=region)) +
          geom_line( alpha=0.9, linewidth=1.2 ) +
          geom_point(aes(shape=region), size=3, alpha=0.7 ) +
          geom_errorbar(aes(ymin=lb,ymax=ub), linewidth=0.8, alpha=0.8, width=0.3)  +
          labs(x=NULL, y=NULL) +
          # labs(x="Year", y="", size = rel(1.5)) +
          scale_colour_manual(values=color_map) +
          scale_fill_manual(values=color_map) +
          scale_shape_manual(values = c(15, 17, 19)) +
          theme_light( base_size = 22) + 
          theme( legend.position="inside", legend.position.inside=c(0.1, 0.9), legend.title=element_blank()) 

          # scale_y_continuous( limits=c(0, 300) )  
          ggsave(filename=fn, plot=out, device="pdf", width=12, height = 8)

        print( fn )
      }

      if (plotmethod=="lattice") {
              
        if(graphic=='png') Cairo( file=fn, type="png", bg="white",  units="in", width=5, height=6, dpi=350 )
        if(graphic=='pdf') pdf(file=fn, width=5, height=6, bg='white')
        if(graphic=='R') plot.new()

          setup.lattice.options()
          pl = xyplot( mean~year|region, data=td, ub=td$ub, lb=td$lb,
                layout=c(1,n.region_label),
                par.strip.text=list(
                  plot.symbol=list(col='black', fill='darkgrey', cex=0.75, pch=21),
                  axis.text=list(cex=0.7),
                  par.main.text=list(cex=1),
                  layout.heights=list(strip=1, panel=1, main=0.5),
                  strip.background=list(col='lightgrey')),
                  #xlim=xlim,
                  ylim=(c(as.numeric(ylim[1]), as.numeric(ylim[2]))),
                  scales=list(y=list(at=ylabels, labels=ylabels, cex=0.65), x=list(at=xlabels, labels=xlabels, rot=50, cex=0.65)),
                    main=paste(capwords(common,T,F),"Biomass"), xlab=list("Year", cex=1), ylab=list("Geometric mean kg / km^2", cex=1),
                    #cex.lab=cex.lab,
                    cex.axis=cex.axis,
                    cex.main = cex.main,
                    panel = function(x, y, subscripts, ub, lb, ...) {
                  larrows(x, lb[subscripts], x, ub[subscripts], angle = 90, code = 3, length=0.05)
                  panel.xyplot(x, y, type="b", lty=1, lwd=1.5, pch=21, fill='darkgrey', col="black", ...)
                  panel.abline(h=median(y), col="gray", ...)
              }
            )

          print(pl)
          if(graphic!='R') dev.off()
          print(fn)
        }
      #cmd( "convert   -trim -quality 9  -geometry 200% -frame 2% -mattecolor white -antialias ", paste(fn, "pdf", sep="."),  paste(fn, "png", sep=".") )
    }
  return("Done")
}