R Under development (unstable) (2024-08-21 r87038 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.

> library(testthat)
>  Sys.setenv('OMP_THREAD_LIMIT'=2)
>  library(rlibkriging)

Attaching package: 'rlibkriging'

The following objects are masked from 'package:base':

    load, save

> 
> ##library(rlibkriging, lib.loc="bindings/R/Rlibs")
> ##library(testthat)
> 
> context("increment Kriging")
> 
> f <- function(X) apply(X, 1,
+                        function(x)
+                          prod(
+                            sin(2*pi*
+                                  ( x * (seq(0,1,l=1+length(x))[-1])^2 )
+                            )))
> n <- 1000
> d <- 3
> set.seed(1234)
> X <- matrix(runif(n*d),ncol=d)
> y <- f(X)+rnorm(1000,0,0.1)
> r = NULL
> try( r <- NuggetKriging(y, X, "gauss","constant",FALSE,"none","LL", parameters=list(theta = matrix(.5,ncol=3), beta = matrix(0.01), nugget=0.1^2, sigma2=0.09)) )
> 
> no = floor(n*0.7)
> try( ro <- NuggetKriging(y[1:no], X[1:no,], "gauss","constant",FALSE,"none","LL", parameters=list(theta = matrix(.5,ncol=3), beta = matrix(0.01), nugget=0.1^2, sigma2=0.09)) )
> # update with new points, compute LL but no fit (since optim=none)
> ro$update(y[(no+1):n],X[(no+1):n,], refit=TRUE)
> 
> test_that(desc="Updated (no refit) Kriging equals Kriging with all data",
+           expect_equal(ro$T(), r$T(), tol=1e-5))
Test passed 🌈
> 
> # m1 = microbenchmark::microbenchmark(
> #   r <- Kriging(y, X, "gauss","constant",FALSE,"none","LL", parameters=list(theta = matrix(.5,ncol=3), beta = matrix(0.01))),
> #   times=100
> # )
> # 
> # m2 = microbenchmark::microbenchmark(
> #   {
> #     ro <- Kriging(y[1:no], X[1:no,], "gauss","constant",FALSE,"none","LL", parameters=list(theta = matrix(.5,ncol=3), beta = matrix(0.01)))
> #     ro$update(y[(no+1):n], X[(no+1):n,], refit=FALSE)
> #   },
> #   times=100
> # )
> 
> proc.time()
   user  system elapsed 
   1.90    0.34    2.25