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#
# fields is a package for analysis of spatial data written for
# the R software environment.
# Copyright (C) 2024 Colorado School of Mines
# 1500 Illinois St., Golden, CO 80401
# Contact: Douglas Nychka, douglasnychka@gmail.com,
#
# 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 the R software environment if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
# or see http://www.r-project.org/Licenses/GPL-2
##END HEADER
"predictSurfaceSE"<- function( object,...){
UseMethod("predictSurfaceSE")
}
"predictSurfaceSE.default" <-
function(object, grid.list = NULL,
extrap = FALSE, chull.mask = NA, nx = 80, ny = 80,
xy = c(1,2), verbose = FALSE,
ZGrid=NULL, just.fixed=FALSE, ...) {
# create a default grid if it is not passed
if (is.null(grid.list)) {
# NOTE:
# without grid.list
# default is 80X80 grid on first two variables
# rest are set to median value of the x's
grid.list <- fields.x.to.grid(object$x, nx = nx, ny = ny,
xy = xy)
}
# do some checks on Zgrid if passed and also reshape as a matrix
# rows index grid locations and columns are the covariates
# (as Z in predict).
# if ZGrid is NULL just returns that back
Z<- unrollZGrid( grid.list, ZGrid)
# Convert grid.list to the full set of locations
xg <- make.surface.grid(grid.list)
# NOTE: the predict function called will need to do some internal the checks
# whether the evaluation of a large number of grid points (xg) makes sense.
if( verbose){
print( dim( xg))
print( dim( Z))
}
#
# Next call is fragile as it assumes the predictSE method includes
# a Z argument (even if it will often just be NULL )
out0<- predictSE(object, xg, Z=Z, ...)
# coerce back into image format
out <- as.surface( xg, out0)
#
# if extrapolate is FALSE set all values outside convex hull to NA
if (!extrap) {
if( is.null( object$x)){
stop("need and x matrix in object")
}
if (is.na(chull.mask)) {
chull.mask <- unique.matrix(object$x[, xy])
}
out$z[!in.poly(xg[, xy], xp = chull.mask, convex.hull = TRUE)] <- NA
}
#
return(out)
}
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