https://github.com/cran/tgp
Tip revision: 80903f05d1487ec1898b1c7a022ac9d9db75720c authored by Robert B. Gramacy on 24 October 2008, 00:00:00 UTC
version 2.1-5
version 2.1-5
Tip revision: 80903f0
print.tgp.R
#*******************************************************************************
#
# 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)
#
#*******************************************************************************
## print.tgp
##
## generic print method for tgp-class objects
## (doesn't do much now except list the fields of the tgp-class list
"print.tgp" <-
function(x, ...)
{
cat("\nThis is a 'tgp' class object. ",
"It is basically a list with the following entries:\n", fill=TRUE)
print(names(x), quote=FALSE)
cat("\nSee ?btgp for an explanation of the individual entries. ",
"See plot.tgp and tgp.trees for help with visualization.\n", fill=TRUE)
cat("The $trace field, if it exists, is of class 'tgptraces'",
"and has its own print statement\n", fill=TRUE)
}
## print.tgptraces
##
## generic print method for tgptraces-class objects
## describes the contents of each field in the list, as well as
## sub-fields where appropriate. Some fields may be empty, or have
## sub-fields which depend on the type of analysis, and this
## is indicated
"print.tgptraces" <-
function(x, ...)
{
cat("\nThis 'tgptraces'-class object contains traces of the parameters\n")
cat("to a tgp model. Access is as a list:\n\n")
## info about XX
cat(paste("1.) $XX contains the traces of GP parameters for ",
length(x$XX), " predictive\n", sep=""))
cat(" locations\n\n")
if(length(x$XX) > 0) {
if(length(x$XX) == 1) { cat(paste("\n$XX[[1]]" , sep="")) }
else { cat(paste(" Each of $XX[[1]] ... $XX[[", length(x$XX), "]]", sep="")) }
cat(paste(" is a data frame with the\n columns representing GP parameters:\n\n",
sep=""))
print(names(x$XX[[1]]), quote=FALSE)
} else
cat(" ** The $XX list is empty because XX=NULL, or T-B=0\n")
## info about hierarchial params
cat("\n2.) $hier has a trace of the hierarchical params:\n", sep="", fill=TRUE)
if(!is.null(names(x$hier)))
print(names(x$hier), quote=FALSE)
else
cat(" ** $hier is empty because T-B=0\n")
## info about linarea
cat("\n3.) $linarea has a trace of areas under the LLM. It is a \n")
cat(" data frame with columns:\n\n")
cat(" count: number of booleans b=0, indicating LLM\n")
cat(" la: area of domain under LLM\n")
cat(" ba: area of domain under LLM weighed by dim\n")
if(length(x$linarea) <= 0) {
cat("\n ** $linarea is empty since you fit a model which \n")
cat(" ** either forced the LLM (btlm, blm), or disallowed\n")
cat(" ** it (bgp, btgp)\n")
}
## info about parts
cat("\n4.) $parts contains all of the partitions visited. Use the\n")
cat(" tgp.plot.parts.[1d,2d] functions for visuals\n")
if(length(x$parts) <= 0) {
cat("\n ** $parts is empty since you fit a non-treed model\n")
}
## info about posts
cat("\n5.) $post is a data frame with columns showing the following:\n")
cat(" log posterior ($lpost), tree height ($height) and leaves\n")
cat(" ($leaves), IS weights ($w), tempered log posterior ($tlpost),\n")
cat(" inv-temp ($itemp), and weights adjusted for ESS ($wlambda)\n")
if(is.null(x$post))
cat("\n ** $posts is empty since T-B=0\n")
## info about ZZ
cat("\n6.) $preds is a list containing data.frames for samples from\n")
cat(" the posterior predictive distributions data (X) locations\n")
cat(" (if pred.n=TRUE: $Zp, $Zp.km, $Zp.ks2) and (XX) locations\n")
cat(" (if XX != NULL: $ZZ, $ZZ.km, $ZZ.ks2), with $Ds2x when\n")
cat(" input argument ds2x=TRUE, and $improv when improv=TRUE\n\n")
if(length(x$preds) <= 0) {
cat(" ** $preds is empty because pred.n=FALSE and XX=NULL, or T-B=0\n\n")
}
}