library(stockassessment)

oldwd<-setwd("data")

  cn<-read.ices("cn.dat")
  cw<-read.ices("cw.dat")
  dw<-read.ices("dw.dat")
  lw<-read.ices("lw.dat")
  mo<-read.ices("mo.dat")
  nm<-read.ices("nm.dat")
  pf<-read.ices("pf.dat")
  pm<-read.ices("pm.dat")
  sw<-read.ices("sw.dat")
  lf<-read.ices("lf.dat")
  surveys<-read.ices("survey.dat")
  #surveys[1:2]<-lapply(surveys[1:2], function(x)x*1000)

  patch<-function(x,with,ally=sort(c(1940:1949,as.integer(rownames(surveys[[3]])), as.integer(rownames(x))))){
    ret<-matrix(NA,ncol=ncol(x),nrow=length(ally))
    rownames(ret)<-ally
    colnames(ret)<-colnames(x)
    idx<-as.integer(ally)%in%as.integer(rownames(x))
    ret[idx,]<-x
    ret[!idx,]<-do.call(rbind, rep(list(with), sum(!idx)) )
    ret  
  }

  cn <- patch(cn,colMeans(cn))
  cn[as.integer(rownames(cn))%in%(1945:2008),]<-NA
  cw <- patch(cw,colMeans(cw))
  dw <- patch(dw,colMeans(dw))
  lw <- patch(lw,colMeans(lw))
  mo <- patch(mo,colMeans(mo))
  nm <- patch(nm,colMeans(nm))
  pf <- patch(pf,colMeans(pf))
  pm <- patch(pm,colMeans(pm))
  sw <- patch(sw,colMeans(sw))
  lf <- patch(lf,colMeans(lf))

setwd(oldwd)

dat<-setup.sam.data(surveys=surveys,
                    residual.fleet=cn, 
                    prop.mature=mo, 
                    stock.mean.weight=sw, 
                    catch.mean.weight=cw, 
                    dis.mean.weight=dw, 
                    land.mean.weight=lw,
                    prop.f=pf, 
                    prop.m=pm, 
                    natural.mortality=nm, 
                    land.frac=lf)


save(dat, file="run/data.RData")