R/diags-SAM.R

In laurieKell/diags: Diagnostics for stock assessment methods

utils::globalVariables(c("name","age"))
utils::globalVariables(c("ddply"))
utils::globalVariables(c("."))
utils::globalVariables(c("rstudent"))
utils::globalVariables(c("lm"))
utils::globalVariables(c("rstandard"))

utils::globalVariables(c("read.table"))
utils::globalVariables(c("diagsFn"))


readSam<-function(file, reduced=FALSE){
  # Function to read a basic fit
  ret<-list()
  parfile<-as.numeric(scan(paste(file,'.par', sep=''), 
                           what='', n=16, quiet=TRUE)[c(6,11,16)])
  ret$nopar<-as.integer(parfile[1])
  ret$nlogl<-parfile[2]
  ret$maxgrad<-parfile[3]
  rep<-scan(paste(file,'.rep', sep=''), quiet=TRUE)
  ret$res<-read.table(paste(file,'.res', sep=''),header=FALSE)
  ret$stateDim<-rep[1]
  ret$years<-rep[-1]
  file<-paste(file,'.cor', sep='')
  lin<-readLines(file)
  ret$npar<-length(lin)-2
  ret$logDetHess<-as.numeric(strsplit(lin[1], '=')[[1]][2])
  sublin<-lapply(strsplit(lin[1:ret$npar+2], ' '),function(x)x[x!=''])
  ret$names<-unlist(lapply(sublin,function(x)x[2]))
  ret$est<-as.numeric(unlist(lapply(sublin,function(x)x[3])))
  ret$std<-as.numeric(unlist(lapply(sublin,function(x)x[4])))
  
  ret$cor<-matrix(NA, ret$npar, ret$npar)
  for(i in 1:ret$npar){
    ret$cor[1:i,i]<-as.numeric(unlist(lapply(sublin[i],
                                             function(x)x[5:(4+i)])))
    ret$cor[i,1:i]<-ret$cor[1:i,i]
  }
  ret$cov<-ret$cor*(ret$std%o%ret$std)
  mslh<-function(name){
    idx<-which(ret$names==name)
    x<-cbind(ret$est[idx], ret$std[idx], ret$est[idx]-2*ret$std[idx], 
             ret$est[idx]+2*ret$std[idx])
    colnames(x)<-c('est', 'std', 'low', 'hig')
    return(x)
  }
  ret$ssb<-mslh('ssb')
  ret$fbar<-mslh('fbar')
  ret$tsb<-mslh('tsb')
  ret$logssb<-mslh('logssb')
  ret$logfbar<-mslh('logfbar')
  ret$logtsb<-mslh('logtsb')
  ret$logscale<-mslh('logScale')
  ret$logFpar<-mslh('logFpar')
  ret$logCatch<-mslh('logCatch')
  x<-mslh('U')
  ret$stateEst<-matrix(x[,1],ncol=ret$stateDim, byrow=TRUE)
  ret$stateStd<-matrix(x[,2],ncol=ret$stateDim, byrow=TRUE)
  ret$stateLow<-matrix(x[,3],ncol=ret$stateDim, byrow=TRUE)
  ret$stateHig<-matrix(x[,4],ncol=ret$stateDim, byrow=TRUE)
  ret$R<-cbind(exp(ret$stateEst[,1]), NA, exp(ret$stateLow[,1]), 
               exp(ret$stateHig[,1]))
  if(reduced){
    ret<-ret[which(!names(ret)%in%c('cov','cor'))]
  }
  return(ret)
}


utils::globalVariables(c("index"))

.diagUsam=function(x){
  sam       =readSam(x)
  res       =sam$res
  names(res)=c("year","name","age","obs","hat","residual")
  
  res=transform(res,roriginal=residual,
                    residual =residual*exp(sam$est[sam$names=="logSdLogObs"])[name])
    
  res=ddply(res,.(name,age),  function(x) transform(x, rstudent =rstudent( lm(obs~0+hat)),
                                                       rstandard=rstandard(lm(obs~0+hat))))
  
  res=ddply(res,.(name,age),  diagsFn)
  
  names(res)[seq(length(names(res)))[names(res)=="obs"]]="index"
  
  res}