
## BART: Bayesian Additive Regression Trees
## Copyright (C) 2017 Robert McCulloch and Rodney Sparapani

## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.

## This program 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 General Public License for more details.

## You should have received a copy of the GNU General Public License
## along with this program; if not, a copy is available at
## https://www.R-project.org/Licenses/GPL-2

predict.lbart <- function(object, newdata, mc.cores=getOption('mc.cores', 1L),
                          openmp=(mc.cores.openmp()>0),
                          probs=c(0.025, 0.975), ...) {
    if(class(newdata)[1] == "data.frame") newdata=bartModelMatrix(newdata)
    ##if(class(newdata) != "matrix") stop("newdata must be a matrix")

    p <- length(object$treedraws$cutpoints)

    if(p!=ncol(newdata))
        stop(paste0('The number of columns in newdata must be equal to ', p))

    if(.Platform$OS.type == "unix") mc.cores.detected <- detectCores()
    else mc.cores.detected <- NA

    if(!is.na(mc.cores.detected) && mc.cores>mc.cores.detected) mc.cores <- mc.cores.detected

    if(.Platform$OS.type != "unix" || openmp || mc.cores==1) call <- pwbart
    else call <- mc.pwbart

    ##return(call(newdata, object$treedraws, mc.cores=mc.cores, mu=object$binaryOffset, ...))
    if(length(object$binaryOffset)==0) object$binaryOffset=object$offset

    pred <- list(yhat.test=call(newdata, object$treedraws, mc.cores=mc.cores,
                                mu=object$binaryOffset, ...))

    pred$prob.test <- plogis(pred$yhat.test)
    pred$prob.test.mean <- apply(pred$prob.test, 2, mean)
    pred$prob.test.lower <- apply(pred$prob.test, 2, quantile,
                                  probs=min(probs))
    pred$prob.test.upper <- apply(pred$prob.test, 2, quantile,
                                  probs=max(probs))
    pred$binaryOffset <- object$binaryOffset
    attr(pred, 'class') <- 'lbart'

    return(pred)
}

