In wStockhausen/rTCSAM2013: Functions to run and plot output from TCSAM2013 models.

knitr::opts_chunk$set(echo=FALSE, error=FALSE, message=FALSE, warning=FALSE,
                      dpi=300,fig.width=6.5,out.width=6.5)

    require(pander);
    require(reshape2);
    require(rTCSAM2013);
    panderOptions("table.caption.prefix","Table ")
    panderOptions("table.split.table",Inf)
    paths<-params$paths;
    obj<-params$obj;
    out.dir<-params$out.dir;
    tblno<-1;

Input model cases

    if (is.null(obj)){
        if (!is.character(paths)){
            cat("'paths' parameter is not a character vector!\n");
            stop();
        }
        obj<-list();
        for (case in names(paths)){
            cat(case,": '",paths[case],"'\n",sep='');
            res<-getResLst(inp.dir=paths[case]);
            if (is.null(res)) {
                #remove path from paths
                paths<-paths[names(paths)!=case];
            } else {
                #add res to obj list
                obj[[case]]<-res;
            }
            rm(res);
        }
    } else {
        obj<-convertToListOfResults(obj);
    }
    cases<-names(obj);
    ncases<-length(cases);

    if (!is.null(paths)){ 
        t<-as.data.frame(list(case=cases, path=getSubPaths(paths,last=3)));
    } else {
        t<-as.data.frame(list(case=cases));
    }
    row.names(t)<-NULL;
    pander(t,caption=paste0(tblno,". Model cases for comparison."));
    tblno<-tblno+1;

Mature biomass-at-mating

    dfr<-getMDFR.PopQuantities(obj,type='MB_yx');
    panderOptions('knitr.auto.asis',FALSE);##need to do this for loops below
    #males
    ddfr<-dcast(dfr[dfr$x=='male',],y~case,value.var='val');
    names(ddfr)[1]<-'year';
    fn<-file.path(out.dir,paste0("RetroModelComparison.MatureBiomassAtMating.csv"));
    write.csv(ddfr,row.names=FALSE,file=fn);
    just<-'l';
    for (i in 1:ncases) just<-paste0(just,'r');
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Estimated MMB-at-mating time (1000's t)."));
    tblno<-tblno+1;
    #females
    ddfr<-dcast(dfr[dfr$x=='female',],y~case,value.var='val');
    names(ddfr)[1]<-'year';
    just<-'l';
    for (i in 1:ncases) just<-paste0(just,'r');
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Estimated MFB-at-mating time (1000's t)."));
    tblno<-tblno+1;
    panderOptions('knitr.auto.asis',TRUE);

Recruitment

    dfr<-getMDFR.PopQuantities(obj,type='R_y');
    panderOptions('knitr.auto.asis',FALSE);##need to do this for loops below
    ddfr<-dcast(dfr,y~case,value.var='val');
    names(ddfr)[1]<-'year';
    fn<-file.path(out.dir,paste0("RetroModelComparison.Recruitment.csv"));
    write.csv(ddfr,row.names=FALSE,file=fn);
    just<-'l';
    for (i in 1:ncases) just<-paste0(just,'r');
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Estimated recruitment (millions)."));
    tblno<-tblno+1;
    panderOptions('knitr.auto.asis',TRUE);

Mature survey biomass

    dfr<-getMDFR.SurveyQuantities(obj,type='MB_yx');
    dfrp<-dcast(dfr,x+y~category+case,value.var='val')
    dfrp<-dfrp[,c(1:3,2+ncases+(1:ncases))];
    names(dfrp)[2:3]<-c('year','observed');
    names(dfrp)[3+(1:ncases)]<-gsub("predicted_","",names(dfrp)[3+(1:ncases)],fixed=TRUE);
    fn<-file.path(out.dir,paste0("RetroModelComparison.MatureSurveyBiomass.csv"));
    write.csv(dfrp,row.names=FALSE,file=fn);
    panderOptions('knitr.auto.asis',FALSE);##need to do this for loops below
    just<-'lr'; for (i in 1:ncases) just<-paste0(just,'r');
    #males
    ddfr<-dfrp[dfrp$x=='male',2:ncol(dfrp)]; rownames(ddfr)<-NULL;
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Estimated mature male survey biomass (1000's t)."));
    tblno<-tblno+1;
    #females
    ddfr<-dfrp[dfrp$x=='female',2:ncol(dfrp)]; rownames(ddfr)<-NULL;
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Estimated mature female survey biomass (1000's t)."));
    tblno<-tblno+1;
    panderOptions('knitr.auto.asis',TRUE);

Retained catch

    dfr<-getMDFR.FisheryQuantities(obj,type='bio.retm');
    dfrp<-dcast(dfr,x+y~category+case,value.var='val')
    dfrp<-dfrp[,c(1:3,2+ncases+(1:ncases))];
    names(dfrp)[2:3]<-c('year','observed');
    names(dfrp)[3+(1:ncases)]<-gsub("predicted_","",names(dfrp)[3+(1:ncases)],fixed=TRUE);
    panderOptions('knitr.auto.asis',FALSE);##need to do this for loops below
    just<-'lr'; for (i in 1:ncases) just<-paste0(just,'r');
    #males
    ddfr<-dfrp[dfrp$x=='male',2:ncol(dfrp)]; rownames(ddfr)<-NULL;
    fn<-file.path(out.dir,paste0("RetroModelComparison.RetainedCatch.csv"));
    write.csv(ddfr,row.names=FALSE,file=fn);
    pandoc.table(ddfr,keep.trailing.zeros=FALSE,justify=just,
           caption=paste0(tblno,". Observed/estimated retained catch (1000's t)."));
    tblno<-tblno+1;
    panderOptions('knitr.auto.asis',TRUE);