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#
# fields is a package for analysis of spatial data written for
# the R software environment.
# Copyright (C) 2022 Colorado School of Mines
# 1500 Illinois St., Golden, CO 80401
# Contact: Douglas Nychka, douglasnychka@gmail.edu,
#
# 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
##END HEADER
# test of rdist.near
suppressMessages(library(fields))
options(echo=FALSE)
test.for.zero.flag<- 1
set.seed(123)
x1<- matrix( runif(2*20), ncol=2)
x2<- matrix( runif(2*10), ncol=2)
fields.rdist.near( x1,x2, delta=.75)-> look
temp<- matrix( NA, nrow(x1),nrow(x2))
temp[ look$ind] <- look$ra
temp2<- rdist( x1, x2)
temp2[ temp2> .75] <- NA
temp[ is.na( temp)]<- 0
temp2[ is.na( temp2)]<- 0
test.for.zero( temp, temp2)
# test of constructing covariance matrix
# and also versions of Wendland function
# default taper is wendland k=2.
DD<- rdist( x1,x2)
temp<- Wendland2.2(DD, aRange=.8)
temp2<- Wendland( DD, aRange=.8, dimension=2, k=2)
test.for.zero( temp, temp2)
stationary.taper.cov( x1,x2, Taper="Wendland2.2",
Taper.args= list( aRange=.8), spam.format=FALSE )-> look
temp0<- look
stationary.taper.cov( x1,x2, Taper="Wendland2.2",
Taper.args= list( aRange=.8), spam.format=TRUE )-> look
temp1<- spam2full( look)
test.for.zero( temp1, temp0)
stationary.taper.cov( x1,x2, Taper="Wendland",
Taper.args= list( aRange=.8, k=2, dimension=2),
spam.format=TRUE )-> look
temp1b<- spam2full( look)
temp2<- Wendland2.2(DD, aRange=.8) * Exponential(DD)
temp3<- wendland.cov(x1,x2, k=2, aRange=.8) * Exponential(DD)
temp4<- Wendland(DD, k=2, dimension=2, aRange=.8)* Exponential(DD)
test.for.zero( temp1, temp0, rel=FALSE)
test.for.zero( temp1b, temp0, rel=FALSE)
test.for.zero( temp2, temp0, rel=FALSE)
test.for.zero( temp2, temp3,rel=FALSE)
test.for.zero( temp2, temp4,rel=FALSE)
set.seed( 256)
rv<- runif( nrow(x2))
# test of multiply
stationary.taper.cov( x1, x2, C= rv)-> look
temp2<-stationary.taper.cov( x1,x2)
spam2full(temp2)%*%(rv)-> look2
test.for.zero( look, look2)
#
set.seed( 123)
temp<- matrix( 1:48, ncol=6, nrow=8)
temp[ sample( 1:48, 20)] <- 0
as.spam( temp)-> temp2
test.for.zero( spam2full(temp2), temp )
spam2spind( temp2)-> temp3
test.for.zero( spind2full( temp3), temp)
test.for.zero( spind2spam( temp3),temp2)
# test that ordering works
MM<- nrow( temp3$ind)
ix<- sample( 1:MM,MM)
# shuffle temp3
temp3$ind<- temp3$ind[ix,]
temp3$ra<- temp3$ra[ix]
test.for.zero( spind2spam( temp3),temp2)
# temp<- temp[1:4, 1:5] for help file
#
set.seed( 234)
CC<- matrix( rnorm( 64), 8,8)
A<- ( CC)%*% t(CC)
as.spam( A)-> As
test.for.zero( solve( As), solve( A))
set.seed( 233)
CC<- diag( 1, 8)
CC[4,1:8] <- rnorm(8)
CC[7,1:8] <- rnorm(8)
A<- ( CC)%*% t(CC)
as.spam( A)-> As
test.for.zero( solve( As), solve( A))
data( ozone2)
x<- ozone2$lon.lat
y<- ozone2$y[16,]
Krig(x,y, cov.function = "stationary.taper.cov", aRange=1.5,
give.warnings=FALSE,
cov.args= list( spam.format=FALSE,
Taper.args= list( dimension=2, aRange=2.0,k=3) ) ) -> out1
Krig(x,y, cov.function = "stationary.taper.cov", lambda=2.0, aRange=1.5,
cov.args= list( spam.format=TRUE,
Taper.args= list( aRange=2.0,k=3, dimension=2) )
) -> out2
temp1<- predict( out1,lambda=2.0)
temp2<- predict( out2)
test.for.zero( temp1, temp2)
cat( "All done with SPAM tests", fill=TRUE)
options(echo=TRUE)
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