#******************************************************************************* 
#
# Bayesian Regression and Adaptive Sampling with Gaussian Process Trees
# Copyright (C) 2005, University of California
# 
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
# 
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# Lesser General Public License for more details.
# 
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
#
# Questions? Contact Robert B. Gramacy (rbgramacy@ams.ucsc.edu)
#
#*******************************************************************************

"tgp.choose.as" <-
function(out, as)
{
  # choose AS stats to plot
  if(is.null(as)) {
     X <- rbind(out$X, out$XX)
     criteria <- c(out$Zp.q, out$ZZ.q)
     name <- "error"
  } else {
     X <- out$XX
     criteria <- out$ZZ.q
     name <- "ALM stats"
     if(as == "alc") {
       if(is.null(out$Ds2x)) cat("NOTICE: out$Ds2x is NULL, using ALM\n")
       else { criteria <- out$Ds2x; name <- "ALC stats" }
     } else if(as == "ego") {
       if(is.null(out$ego)) cat("NOTICE: out$ego is NULL, using ALM\n")
       else { criteria <- out$ego; name <- "EGO stats" }
     }
  }

  return(list(X=X, criteria=criteria, name=name))
}