R Under development (unstable) (2023-10-29 r85433 ucrt) -- "Unsuffered Consequences"
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> ## IGNORE_RDIFF_BEGIN
> library(rtop)
> library(sf)
Linking to GEOS 3.11.2, GDAL 3.7.2, PROJ 9.3.0; sf_use_s2() is TRUE
> set.seed(1)
> options(error = recover)
> rpath = system.file("extdata",package="rtop")
> observations = st_read(rpath,"observations")
Reading layer `observations' from data source 
  `D:\RCompile\CRANincoming\R-devel\lib\rtop\extdata' using driver `ESRI Shapefile'
Simple feature collection with 57 features and 7 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 392041.1 ymin: 454983.1 xmax: 512819.5 ymax: 543984.4
Projected CRS: Lambert_Conformal_Conic
> # Create a column with the specific runoff:
> observations$obs = observations$QSUMMER_OB/observations$AREASQKM
> predictionLocations = st_read(rpath,"predictionLocations")
Reading layer `predictionLocations' from data source 
  `D:\RCompile\CRANincoming\R-devel\lib\rtop\extdata' using driver `ESRI Shapefile'
Simple feature collection with 235 features and 5 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 393416.8 ymin: 454919.1 xmax: 519903.3 ymax: 543984.4
Projected CRS: Lambert_Conformal_Conic
> ## IGNORE_RDIFF_END
> 
> params = list(gDist = TRUE, cloud = FALSE)
> # Create a column with the specific runoff:
> observations$obs = observations$QSUMMER_OB/observations$AREASQKM
> # Build an object
> rtopObj = createRtopObject(observations, predictionLocations, 
+                            params = params, formulaString = "obs ~1")
> 
> 
> rtopObj = rtopFitVariogram(rtopObj, iprint = -1)
> 
> # Predicting at prediction locations
> rtopObj = rtopKrige(rtopObj)
[1] "Sampling points from  57 areas"
[1] "Sampled on average 231.88 points from 57 areas"
[1] "Sampling points from  235 areas"
[1] "Sampled on average 210.34 points from 235 areas"
[1] "Creating prediction semivariance matrix. This can take some time."
> 
> # Cross-validation
> rtopObj = rtopKrige(rtopObj,cv=TRUE)
> print(cor(rtopObj$predictions$observed,rtopObj$predictions$var1.pred), 4)
[1] 0.7484
> 
> proc.time()
   user  system elapsed 
  30.75    0.60   31.37