R Under development (unstable) (2024-10-08 r87214 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> suppressMessages(library(LatticeKrig))
> 
> #######################################################
> # Define two useful predict functions. 
> #######################################################
> predict.surfaceGrid<- function(object,x){
+   interp.surface( object, x)
+ }
> # this is a simple function that just returns the constant value
> # object$value
> predict.CONSTANT<- function(object,x){
+   rep( object$value, nrow(x))
+ }
> ### first compare the stationsry case to its equivalent parameterization as
> ### a nonstationary model but where parameters are constant. 
> 
> ############# 1-d case first
> 
> a.wghtObject<- list(value = 4.5)
> class( a.wghtObject )<-"CONSTANT"
> 
> alphaTemp<-c(.75, .2, .05)
> alphaObject<- NULL
> for( k in 1:3){
+   temp<- list( value = alphaTemp[k])
+   class( temp )<-"CONSTANT"
+   alphaObject<- c( alphaObject, list( temp))
+ }
> 
> LKinfo0<- LKrigSetup( rbind(-1,1), NC=4,
+                       LKGeometry="LKInterval",
+                       nlevel=3, a.wght=4.5, alpha=alphaTemp )
> #NOTE can reuse predict objects because they are constants not related to 
> # locations
> LKinfoTEST1<- LKrigSetup( rbind(-1,1), NC=4,
+                           LKGeometry="LKInterval",
+                           nlevel=3, 
+                           a.wghtObject = a.wghtObject,
+                           alphaObject = alphaObject ) 
> xGrid<- cbind(seq( -1,1,length.out= 20))
> for( k in 1:3){
+   s0<-  spind2full(LKrigSAR( LKinfo0, k))
+   s1<-  spind2full(LKrigSAR( LKinfoTEST1, k))
+   test.for.zero( s0,s1, tag="1-d SAR Levels")
+ }
Testing:  1-d SAR Levels
PASSED test at tolerance  1e-08
Testing:  1-d SAR Levels
PASSED test at tolerance  1e-08
Testing:  1-d SAR Levels
PASSED test at tolerance  1e-08
> p0<- LKrig.precision( LKinfo0)       
> p1<- LKrig.precision( LKinfoTEST1)
> test.for.zero( p0@entries, p1@entries, tag="1-d SAR Precision")
Testing:  1-d SAR Precision
PASSED test at tolerance  1e-08
> 
> ############# 2-d case
> 
> 
> # spatial domain    
> sDomain<- rbind( c(-1,-1),
+                  c(1,1))
> 
> alphaTemp<-c(.75, .2, .05)
> alphaTemp<-rep( 1, 3)
> # To get started compare stationary model specified two ways
> LKinfo0<- LKrigSetup( sDomain, NC=3,
+                       NC.buffer=2,
+                       nlevel=3, a.wght=4.5, alpha=alphaTemp )
> a.wghtObject<- list(value = 4.5)
> class( a.wghtObject )<-"CONSTANT"
> 
> 
> alphaObject<- NULL
> for( k in 1:3){
+   temp<- list( value = alphaTemp[k])
+   class( temp )<-"CONSTANT"
+   alphaObject<- c( alphaObject, list( temp))
+ }
> LKinfoTEST1<- LKrigSetup( sDomain,  NC=3, nlevel=3,
+                           NC.buffer=2,
+                           a.wghtObject = a.wghtObject,
+                           alpha = alphaTemp )
> LKinfoTEST2<- LKrigSetup( sDomain,  NC=3, nlevel=3,
+                           NC.buffer=2,
+                           a.wghtObject = a.wghtObject,
+                           alphaObject = alphaObject )
> 
> p0<- LKrig.precision( LKinfo0)       
> p1<- LKrig.precision( LKinfoTEST1)
> p2<- LKrig.precision( LKinfoTEST2) 
> test.for.zero( p0@entries, p1@entries, tag="2-d precision alpha constant")
Testing:  2-d precision alpha constant
PASSED test at tolerance  1e-08
> test.for.zero( p1@entries, p2@entries, tag="2-d precision alphaObject")
Testing:  2-d precision alphaObject
PASSED test at tolerance  1e-08
> 
> b0<- LKrig.basis( rbind( c(.2,.8)), LKinfo0)
> b1<- LKrig.basis( rbind( c(.2,.8)), LKinfoTEST1)
> b2<- LKrig.basis( rbind( c(.2,.8)), LKinfoTEST2)
> test.for.zero( b0,b1, tag="2-d basis alpha constant")
Testing:  2-d basis alpha constant
PASSED test at tolerance  1e-08
> test.for.zero( b1,b2,tag="2-d basis alphaObject")
Testing:  2-d basis alphaObject
PASSED test at tolerance  1e-08
> 
> 
> 
> proc.time()
   user  system elapsed 
   3.60    0.15    3.68