#******************************************************************************* 
#
# 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)
#
#*******************************************************************************


"check.matrix" <- 
function(X, Z=NULL)
{
  ## format X
  if(is.null(X)) return(NULL)
  n <- dim(X)[1]
  if(is.null(n)) { n <- length(X); X <- matrix(X, nrow=n) }
  X <- as.matrix(X)
  
  ## if a Z is provided to go along with X
  if(!is.null(Z)) {
    
    ## format Z
    Z <- as.vector(matrix(Z, ncol=1)[,1])
    if(length(Z) != n) stop("mismatched row dimension in X and Z")
    
    ## calculate locations of NAs NaNs and Infs in Z
    nna <- (1:n)[!is.na(Z) == 1]
    nnan <- (1:n)[!is.nan(Z) == 1]
    ninf <- (1:n)[!is.infinite(Z) == 1]
    if(length(nna) < n) warning(paste(n-length(nna), "NAs removed from input vector"))
    if(length(nnan) < n) warning(paste(n-length(nnan), "NaNs removed from input vector"))
    if(length(ninf) < n) warning(paste(n-length(ninf), "Infs removed from input vector"))
    
    neitherZ <- intersect(nna, intersect(nnan, ninf))
  } else neitherZ <- (1:n)
  
  ## calculate row locations of NAs NaNs and Infs in X
  nna <- (1:n)[apply(!is.na(X), 1, prod) == 1]
  nnan <- (1:n)[apply(!is.nan(X), 1, prod) == 1]
  ninf <- (1:n)[apply(!is.infinite(X), 1, prod) == 1]
  if(length(nna) < n) warning(paste(n-length(nna), "NAs removed from input matrix"))
  if(length(nnan) < n) warning(paste(n-length(nnan), "NaNs removed from input matrix"))
  if(length(ninf) < n) warning(paste(n-length(ninf), "Infs removed from input matrix"))
  neitherX <- intersect(nna, intersect(nnan, ninf))
  
  ## combine good X and Z rows
  neither <- intersect(neitherZ, neitherX)
  X <- matrix(X[neither,], nrow=length(neither))
  Z <- Z[neither]
  
  return(list(X=X, Z=Z))
}