R Under development (unstable) (2024-06-26 r86840 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # > # 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 sreg and related functions > > suppressMessages(library(fields)) > #options(echo=FALSE) > > test.for.zero.flag<- 1 > > > > # simple covariance function for implementation > exp_cov <- function(dist){ + sigma2<-1 + covariance <- sigma2* exp(-dist / 10) # 10 is arbitrary + return(covariance) + } > > # ----------------------------- > # Define grid and observations > # ----------------------------- > > m<- 10 > n<- 11 > nx<- m > ny<- n > M<- 15 > dx<- 1 > dy<- 1 > sigma2<-2.0 > np<-3 > > > # first a case where all obs in same grid box. > # addition of "dx" also tests that this works when grid is not just integers > # set dx=1 for the most basic case > dx<- .5 > s0<- rbind( + c(5.1,6.2), + c(5.1,6.5), + c( 5.85,6.45) + ) > s0<- s0*dx > > test0<- offGridWeights( s0, list( x= (1:m)*dx, y=(1:n)*dx), + aRange=10*dx, sigma2=sigma2, + Covariance="Exponential", + np=2, + debug=TRUE) [1] 2 Found 1 grid box(es) containing more than 1 obs location > # explicit nearest neighbors in this case > sTmp<- cbind( rep(4:7,4), rep(5:8,each=4) ) > sGrid<- sTmp*dx > > # check that same grid being used by function > test.for.zero(sGrid, cbind(test0$gridX[,1], test0$gridY[,1]) ) PASSED test at tolerance 1e-08 > > S21 <- 2.0* exp( -rdist( s0, sGrid)/(10*dx)) > S11 <- 2.0* exp( -rdist( sGrid , sGrid)/(10*dx) ) > S22 <- 2.0* exp( -rdist( s0, s0)/(10*dx)) > # local weights applied for prediction > Btest<- S21%*% solve( S11) > # find indices for neigborhood > sIndex<- sTmp[,1] + (sTmp[,2]-1)*m > # Kriging weights > Bfull<- spam2full(test0$B[,sIndex]) > test.for.zero( Bfull, Btest) PASSED test at tolerance 1e-08 > # standard error matrix > # note that transpsoe also taken so SEtest%*%t( SEtest) = cov matrix > SEtest<- t(chol(S22 - S21%*% solve( S11)%*%t(S21) )) > SEfull <- spam2full(test0$SE) > test.for.zero( SEfull, SEtest) PASSED test at tolerance 1e-08 > > > # now test several observation locations > > dx<- .45 > s<- rbind( + c(5.1,6.2), + c(7.1,7.2), + c(5.1,6.5), + c(8.5,4.4), + c( 5.85,6.45), + c(7.3,7.4) + ) > s<- s * dx > # Note s0 from above is s[c(1,3,5),] > ind1<- c(1,3,5) > > sTmp<- cbind( rep(4:7,4), rep(5:8,each=4) ) > sGrid<- sTmp*dx > sIndex<- sTmp[,1] + (sTmp[,2]-1)*m > > S21<- 2.0* exp( -rdist( s[ind1,], sGrid)/(10*dx) ) > S11<- 2.0* exp( -rdist( sGrid , sGrid)/(10*dx) ) > S22<- 2.0* exp( -rdist( s[ind1,], s[ind1,])/(10*dx) ) > > sparseObj<- offGridWeights( s, list( x= (1:m)*dx, y=(1:n)*dx), + aRange=(10*dx), sigma2=sigma2, + Covariance="Exponential", + np=2, + debug=TRUE) [1] 2 Found 2 grid box(es) containing more than 1 obs location > > test.for.zero( sparseObj$Sigma21Star[ind1,], S21 ) PASSED test at tolerance 1e-08 > test.for.zero( sparseObj$Sigma11Inv, solve(S11) ) PASSED test at tolerance 1e-08 > > Btest<- S21%*% solve( S11) > look2<- spam2full( sparseObj$B) > test.for.zero( Btest,look2[ind1, sIndex] ) PASSED test at tolerance 1e-08 > > > SEfull<- spam2full( sparseObj$SE) > SE2full<- (SEfull)%*%t(SEfull) > test.for.zero(diag( SE2full), sparseObj$predictionVariance ) PASSED test at tolerance 1e-08 > > SEtest<- t(chol(S22 - S21%*%solve( S11)%*%t( S21) )) > test.for.zero(SEtest, SEfull[ind1, ind1] ) PASSED test at tolerance 1e-08 > > # check that debug FALSE also works > > sparseObj1<- offGridWeights( s, list( x= (1:m)*dx, y=(1:n)*dx), + aRange=(10*dx), sigma2=sigma2, + Covariance="Exponential", + np=2, + debug=FALSE) [1] 2 Found 2 grid box(es) containing more than 1 obs location > > test.for.zero( sparseObj$B, sparseObj1$B) PASSED test at tolerance 1e-08 > test.for.zero( sparseObj$SE, sparseObj1$SE) PASSED test at tolerance 1e-08 > > cat("all done with off grid weight tests part 2", fill=TRUE) all done with off grid weight tests part 2 > > > proc.time() user system elapsed 0.51 0.15 0.60