Running 'rtop.R' [25s]
  Comparing 'rtop.Rout' to 'rtop.Rout.save' ... OK
  Running 'rtop_sf.R' [179s]
Running the tests in 'tests/rtop_sf.R' failed.
Complete output:
  > ## IGNORE_RDIFF_BEGIN
  > library(rtop)
  > library(sf)
  Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; 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\CRANpkg\lib\4.4\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$AREASQKM
  > predictionLocations = st_read(rpath,"predictionLocations")
  Reading layer `predictionLocations' from data source 
    `D:\RCompile\CRANpkg\lib\4.4\rtop\extdata' using driver `ESRI Shapefile'
  Simple feature collection with 235 features and 5 fields
  Geometry type: POLYGON
  Dimension:     XY
  Bounding box:  xmin: 393416.8 ymin: 454919.1 xmax: 519903.3 ymax: 543984.4
  Projected CRS: Lambert_Conformal_Conic
  > ## IGNORE_RDIFF_END
  > 
  > params = list(gDist = TRUE, cloud = FALSE)
  > # Create a column with the specific runoff:
  > observations$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 
    27.14    0.56   27.73