if(typeof(x) %in% c("expression","symbol"))

          x<-eval(x, design$variables)

      else {

          if(is.data.frame(x) && any(sapply(x,is.factor))){

              xx<-lapply(x, function(xi) {if (is.factor(xi)) 0+(outer(xi,levels(xi),"==")) else xi})

              cols<-sapply(xx,NCOL)

              scols<-c(0,cumsum(cols))

              cn<-character(sum(cols))

              for(i in 1:length(xx))

                  cn[scols[i]+1:cols[i]]<-paste(names(x)[i],levels(x[[i]]),sep="")

              x<-matrix(nrow=NROW(xx[[1]]),ncol=sum(cols))

              for(i in 1:length(xx)){

                  x[,scols[i]+1:cols[i]]<-xx[[i]]

              }

              colnames(x)<-cn

          }

      }

  } 

  x<-as.matrix(x)

  if (na.rm){

    nas<-rowSums(is.na(x))

    design<-design[nas==0,]

    x<-x[nas==0,,drop=FALSE]

  }

  wts<-design$repweights

  scale<-design$scale

  rscales<-design$rscales

  if (!is.null(rho)) .NotYetUsed("rho")

  if (!design$combined.weights)

    pw<-design$pweights

  else

    pw<-1

  rval<-colSums(design$pweights*x)/sum(design$pweights)

  if (getOption("survey.drop.replicates") && !is.null(design$selfrep) && all(design$selfrep)){

    v<-matrix(0,length(rval),length(rval))

    repmeans<-NULL

  } else {

  if (inherits(wts, "repweights_compressed")){

    repmeans<-matrix(ncol=NCOL(x), nrow=ncol(wts$weights))

    for(i in 1:ncol(wts$weights)){

      wi<-wts$weights[wts$index,i]

      repmeans[i,]<-t(colSums(wi*x*pw)/sum(pw*wi))

    }

  } else {

    repmeans<-matrix(data=as.numeric(NA), ncol=NCOL(x), nrow=ncol(wts))

    for(i in 1:ncol(wts)){

      repmeans[i,]<-t(colSums(wts[,i]*x*pw)/sum(pw*wts[,i]))

    }

  }

  repmeans<-drop(repmeans)

  v <- svrVar(repmeans, scale, rscales,mse=design$mse, coef=rval)

}

# this is easy to fix, but for now...

return(v)

  attr(rval,"var") <-v

  attr(rval, "statistic")<-"mean"

  if (return.replicates){

    attr(repmeans,"scale")<-design$scale

    attr(repmeans,"rscales")<-design$rscales

    attr(repmeans,"mse")<-design$mse

    rval<-list(mean=rval, replicates=repmeans)

  }

  if (is.character(deff) || deff){

      nobs<-length(design$pweights)

      npop<-sum(design$pweights)

      vsrs<-unclass(svyvar(x,design,na.rm=na.rm, return.replicates=FALSE,estimate.only=TRUE))/length(design$pweights)

      if (deff!="replace")

        vsrs<-vsrs*(npop-nobs)/npop

      attr(rval,"deff") <- v/vsrs

  }

  class(rval)<-"svrepstat"

  rval

}

source("harness.R")

for (s in c("alabama", "california", "acs3yr" )) { 

  svydata <- readRDS(paste0(s,".rds"))

  names(svydata) <- tolower(names(svydata))

  print("loaded")

  svydsgn <- svrepdesign(

      weight = ~pwgtp ,

      repweights = 'pwgtp[1-9]' ,

      scale = 4 / 80 ,

      rscales = rep( 1 , 80 ) ,

      mse = TRUE ,

      data = svydata) 

  print("initialized")

  for (r in 1:5) {

    timing <- system.time({

      agep <- svymean(~agep, svydsgn, se=TRUE)

      print(agep)

      print(relp)

    })[[3]]

    log.result("survey", sys, conf, s, r, timing)

    clearResultRecycler()

  }

}