Running ‘allier.R’
  Comparing ‘allier.Rout’ to ‘allier.Rout.save’ ... OK
  Running ‘blockkr.R’
  Comparing ‘blockkr.Rout’ to ‘blockkr.Rout.save’ ... OK
  Running ‘covtable.R’
  Comparing ‘covtable.Rout’ to ‘covtable.Rout.save’ ... OK
  Running ‘cv.R’
  Comparing ‘cv.Rout’ to ‘cv.Rout.save’ ... OK
  Running ‘cv3d.R’
  Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ... OK
  Running ‘fit.R’
  Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
  Running ‘krige0.R’ [5s/11s]
  Comparing ‘krige0.Rout’ to ‘krige0.Rout.save’ ... OK
  Running ‘line.R’
  Comparing ‘line.Rout’ to ‘line.Rout.save’ ... OK
  Running ‘merge.R’
  Comparing ‘merge.Rout’ to ‘merge.Rout.save’ ... OK
  Running ‘na.action.R’
  Comparing ‘na.action.Rout’ to ‘na.action.Rout.save’ ... OK
  Running ‘rings.R’
  Comparing ‘rings.Rout’ to ‘rings.Rout.save’ ... OK
  Running ‘sim.R’
  Comparing ‘sim.Rout’ to ‘sim.Rout.save’ ... OK
  Running ‘stars.R’ [0m/89m]
  Running ‘variogram.R’
Running the tests in ‘tests/stars.R’ failed.
Complete output:
  > Sys.setenv(TZ = "UTC")
  > 
  > Sys.unsetenv("KMP_DEVICE_THREAD_LIMIT")
  > Sys.unsetenv("KMP_ALL_THREADS")
  > Sys.unsetenv("KMP_TEAMS_THREAD_LIMIT")
  > Sys.unsetenv("OMP_THREAD_LIMIT")
  > 
  > # 0. using sp:
  > 
  > suppressPackageStartupMessages(library(sp))
  > demo(meuse, ask = FALSE)
  
  
  	demo(meuse)
  	---- ~~~~~
  
  > require(sp)
  
  > crs = CRS("EPSG:28992")
  
  > data("meuse")
  
  > coordinates(meuse) <- ~x+y
  
  > proj4string(meuse) <- crs
  
  > data("meuse.grid")
  
  > coordinates(meuse.grid) <- ~x+y
  
  > gridded(meuse.grid) <- TRUE
  
  > proj4string(meuse.grid) <- crs
  
  > data("meuse.riv")
  
  > meuse.riv <- SpatialPolygons(list(Polygons(list(Polygon(meuse.riv)),"meuse.riv")))
  
  > proj4string(meuse.riv) <- crs
  
  > data("meuse.area")
  
  > meuse.area = SpatialPolygons(list(Polygons(list(Polygon(meuse.area)), "area")))
  
  > proj4string(meuse.area) <- crs
  > suppressPackageStartupMessages(library(gstat))
  > v = variogram(log(zinc)~1, meuse)
  > (v.fit = fit.variogram(v, vgm(1, "Sph", 900, 1)))
    model      psill    range
  1   Nug 0.05066243   0.0000
  2   Sph 0.59060780 897.0209
  > k_sp = krige(log(zinc)~1, meuse[-(1:5),], meuse[1:5,], v.fit)
  [using ordinary kriging]
  > k_sp_grd = krige(log(zinc)~1, meuse, meuse.grid, v.fit)
  [using ordinary kriging]
  > 
  > # 1. using sf:
  > suppressPackageStartupMessages(library(sf))
  > demo(meuse_sf, ask = FALSE, echo = FALSE)
  > # reloads meuse as data.frame, so
  > demo(meuse, ask = FALSE)
  
  
  	demo(meuse)
  	---- ~~~~~
  
  > require(sp)
  
  > crs = CRS("EPSG:28992")
  
  > data("meuse")
  
  > coordinates(meuse) <- ~x+y
  
  > proj4string(meuse) <- crs
  
  > data("meuse.grid")
  
  > coordinates(meuse.grid) <- ~x+y
  
  > gridded(meuse.grid) <- TRUE
  
  > proj4string(meuse.grid) <- crs
  
  > data("meuse.riv")
  
  > meuse.riv <- SpatialPolygons(list(Polygons(list(Polygon(meuse.riv)),"meuse.riv")))
  
  > proj4string(meuse.riv) <- crs
  
  > data("meuse.area")
  
  > meuse.area = SpatialPolygons(list(Polygons(list(Polygon(meuse.area)), "area")))
  
  > proj4string(meuse.area) <- crs
  > 
  > v = variogram(log(zinc)~1, meuse_sf)
  > (v.fit = fit.variogram(v, vgm(1, "Sph", 900, 1)))
    model      psill    range
  1   Nug 0.05066243   0.0000
  2   Sph 0.59060780 897.0209
  > k_sf = krige(log(zinc)~1, meuse_sf[-(1:5),], meuse_sf[1:5,], v.fit)
  [using ordinary kriging]
  > 
  > all.equal(k_sp, as(k_sf, "Spatial"), check.attributes = FALSE)
  [1] TRUE
  > all.equal(k_sp, as(k_sf, "Spatial"), check.attributes = TRUE)
  [1] "Attributes: < Component \"bbox\": Attributes: < Component \"dimnames\": Component 1: 2 string mismatches > >"  
  [2] "Attributes: < Component \"coords\": Attributes: < Component \"dimnames\": Component 2: 2 string mismatches > >"
  [3] "Attributes: < Component \"coords.nrs\": Numeric: lengths (2, 0) differ >"                                      
  > 
  > # 2. using stars for grid:
  > 
  > suppressPackageStartupMessages(library(stars))
  > st = st_as_stars(meuse.grid)
  > st_crs(st)
  Coordinate Reference System:
    User input: Amersfoort / RD New 
    wkt:
  PROJCRS["Amersfoort / RD New",
      BASEGEOGCRS["Amersfoort",
          DATUM["Amersfoort",
              ELLIPSOID["Bessel 1841",6377397.155,299.1528128,
                  LENGTHUNIT["metre",1]]],
          PRIMEM["Greenwich",0,
              ANGLEUNIT["degree",0.0174532925199433]],
          ID["EPSG",4289]],
      CONVERSION["RD New",
          METHOD["Oblique Stereographic",
              ID["EPSG",9809]],
          PARAMETER["Latitude of natural origin",52.1561605555556,
              ANGLEUNIT["degree",0.0174532925199433],
              ID["EPSG",8801]],
          PARAMETER["Longitude of natural origin",5.38763888888889,
              ANGLEUNIT["degree",0.0174532925199433],
              ID["EPSG",8802]],
          PARAMETER["Scale factor at natural origin",0.9999079,
              SCALEUNIT["unity",1],
              ID["EPSG",8805]],
          PARAMETER["False easting",155000,
              LENGTHUNIT["metre",1],
              ID["EPSG",8806]],
          PARAMETER["False northing",463000,
              LENGTHUNIT["metre",1],
              ID["EPSG",8807]]],
      CS[Cartesian,2],
          AXIS["easting (X)",east,
              ORDER[1],
              LENGTHUNIT["metre",1]],
          AXIS["northing (Y)",north,
              ORDER[2],
              LENGTHUNIT["metre",1]],
      USAGE[
          SCOPE["Engineering survey, topographic mapping."],
          AREA["Netherlands - onshore, including Waddenzee, Dutch Wadden Islands and 12-mile offshore coastal zone."],
          BBOX[50.75,3.2,53.7,7.22]],
      ID["EPSG",28992]]
  > 
  > # compare inputs:
  > sp = as(st, "Spatial")
  > fullgrid(meuse.grid) = TRUE
  > all.equal(sp, meuse.grid["dist"], check.attributes = FALSE)
  [1] "Names: Lengths (5, 1) differ (string compare on first 1)"
  [2] "Names: 1 string mismatch"                                
  > all.equal(sp, meuse.grid["dist"], check.attributes = TRUE, use.names = FALSE)
  [1] "Names: Lengths (5, 1) differ (string compare on first 1)"                                      
  [2] "Names: 1 string mismatch"                                                                      
  [3] "Attributes: < Component 3: Names: 1 string mismatch >"                                         
  [4] "Attributes: < Component 3: Length mismatch: comparison on first 1 components >"                
  [5] "Attributes: < Component 3: Component 1: Mean relative difference: 1.08298 >"                   
  [6] "Attributes: < Component 4: Attributes: < Component 2: names for current but not for target > >"
  [7] "Attributes: < Component 4: Attributes: < Component 3: names for current but not for target > >"
  > 
  > # kriging:
  > st_crs(st) = st_crs(meuse_sf) = NA # GDAL roundtrip messes them up!
  > k_st = if (Sys.getenv("USER") == "travis") {
  + 	try(krige(log(zinc)~1, meuse_sf, st, v.fit))
  + } else {
  + 	krige(log(zinc)~1, meuse_sf, st, v.fit)
  + }
  [using ordinary kriging]
  > k_st
  stars object with 2 dimensions and 2 attributes
  attribute(s):
                  Min.   1st Qu.    Median      Mean   3rd Qu.      Max. NA's
  var1.pred  4.7765547 5.2376293 5.5728839 5.7072287 6.1717619 7.4399911 5009
  var1.var   0.0854949 0.1372864 0.1621838 0.1853319 0.2116152 0.5002756 5009
  dimension(s):
    from  to offset delta x/y
  x    1  78 178440    40 [x]
  y    1 104 333760   -40 [y]
  > 
  > # handle factors, when going to stars?
  > k_sp_grd$cls = cut(k_sp_grd$var1.pred, c(0, 5, 6, 7, 8, 9))
  > st_as_stars(k_sp_grd)
  stars object with 2 dimensions and 3 attributes
  attribute(s):
     var1.pred       var1.var          cls      
   Min.   :4.777   Min.   :0.0855   (0,5]: 316  
   1st Qu.:5.238   1st Qu.:0.1373   (5,6]:1778  
   Median :5.573   Median :0.1622   (6,7]: 962  
   Mean   :5.707   Mean   :0.1853   (7,8]:  47  
   3rd Qu.:6.172   3rd Qu.:0.2116   (8,9]:   0  
   Max.   :7.440   Max.   :0.5003   NA's :5009  
   NA's   :5009    NA's   :5009                 
  dimension(s):
    from  to offset delta              refsys x/y
  x    1  78 178440    40 Amersfoort / RD New [x]
  y    1 104 333760   -40 Amersfoort / RD New [y]
  > if (require(raster, quietly = TRUE)) {
  +  print(st_as_stars(raster::stack(k_sp_grd))) # check
  +  print(all.equal(st_redimension(st_as_stars(k_sp_grd)), st_as_stars(raster::stack(k_sp_grd)), check.attributes=FALSE))
  + }
  stars object with 3 dimensions and 1 attribute
  attribute(s):
                  Min.   1st Qu. Median     Mean  3rd Qu.     Max.  NA's
  var1.pred  0.0854949 0.2116778      2 2.710347 5.237542 7.439991 15027
  dimension(s):
       from  to offset delta              refsys                          values
  x       1  78 178440    40 Amersfoort / RD New                            NULL
  y       1 104 333760   -40 Amersfoort / RD New                            NULL
  band    1   3     NA    NA                  NA var1.pred, var1.var , cls      
       x/y
  x    [x]
  y    [y]
  band    
  [1] TRUE
  > 
  > suppressPackageStartupMessages(library(spacetime))
  > 
  > tm = as.POSIXct("2019-02-25 15:37:24 CET")
  > n = 4
  > s = stars:::st_stars(list(foo = array(1:(n^3), rep(n,3))),
  + stars:::create_dimensions(list(
  +   x = stars:::create_dimension(from = 1, to = n, offset = 10, delta = 0.5),
  +   y = stars:::create_dimension(from = 1, to = n, offset = 0, delta = -0.7),
  +   time = stars:::create_dimension(values = tm + 1:n)),
  +   raster = stars:::get_raster(dimensions = c("x", "y")))
  +   )
  > s
  stars object with 3 dimensions and 1 attribute
  attribute(s):
       Min. 1st Qu. Median Mean 3rd Qu. Max.
  foo     1   16.75   32.5 32.5   48.25   64
  dimension(s):
       from to                  offset  delta  refsys x/y
  x       1  4                      10    0.5      NA [x]
  y       1  4                       0   -0.7      NA [y]
  time    1  4 2019-02-25 15:37:25 UTC 1 secs POSIXct    
  > 
  > as.data.frame(s)
         x     y                time foo
  1  10.25 -0.35 2019-02-25 15:37:25   1
  2  10.75 -0.35 2019-02-25 15:37:25   2
  3  11.25 -0.35 2019-02-25 15:37:25   3
  4  11.75 -0.35 2019-02-25 15:37:25   4
  5  10.25 -1.05 2019-02-25 15:37:25   5
  6  10.75 -1.05 2019-02-25 15:37:25   6
  7  11.25 -1.05 2019-02-25 15:37:25   7
  8  11.75 -1.05 2019-02-25 15:37:25   8
  9  10.25 -1.75 2019-02-25 15:37:25   9
  10 10.75 -1.75 2019-02-25 15:37:25  10
  11 11.25 -1.75 2019-02-25 15:37:25  11
  12 11.75 -1.75 2019-02-25 15:37:25  12
  13 10.25 -2.45 2019-02-25 15:37:25  13
  14 10.75 -2.45 2019-02-25 15:37:25  14
  15 11.25 -2.45 2019-02-25 15:37:25  15
  16 11.75 -2.45 2019-02-25 15:37:25  16
  17 10.25 -0.35 2019-02-25 15:37:26  17
  18 10.75 -0.35 2019-02-25 15:37:26  18
  19 11.25 -0.35 2019-02-25 15:37:26  19
  20 11.75 -0.35 2019-02-25 15:37:26  20
  21 10.25 -1.05 2019-02-25 15:37:26  21
  22 10.75 -1.05 2019-02-25 15:37:26  22
  23 11.25 -1.05 2019-02-25 15:37:26  23
  24 11.75 -1.05 2019-02-25 15:37:26  24
  25 10.25 -1.75 2019-02-25 15:37:26  25
  26 10.75 -1.75 2019-02-25 15:37:26  26
  27 11.25 -1.75 2019-02-25 15:37:26  27
  28 11.75 -1.75 2019-02-25 15:37:26  28
  29 10.25 -2.45 2019-02-25 15:37:26  29
  30 10.75 -2.45 2019-02-25 15:37:26  30
  31 11.25 -2.45 2019-02-25 15:37:26  31
  32 11.75 -2.45 2019-02-25 15:37:26  32
  33 10.25 -0.35 2019-02-25 15:37:27  33
  34 10.75 -0.35 2019-02-25 15:37:27  34
  35 11.25 -0.35 2019-02-25 15:37:27  35
  36 11.75 -0.35 2019-02-25 15:37:27  36
  37 10.25 -1.05 2019-02-25 15:37:27  37
  38 10.75 -1.05 2019-02-25 15:37:27  38
  39 11.25 -1.05 2019-02-25 15:37:27  39
  40 11.75 -1.05 2019-02-25 15:37:27  40
  41 10.25 -1.75 2019-02-25 15:37:27  41
  42 10.75 -1.75 2019-02-25 15:37:27  42
  43 11.25 -1.75 2019-02-25 15:37:27  43
  44 11.75 -1.75 2019-02-25 15:37:27  44
  45 10.25 -2.45 2019-02-25 15:37:27  45
  46 10.75 -2.45 2019-02-25 15:37:27  46
  47 11.25 -2.45 2019-02-25 15:37:27  47
  48 11.75 -2.45 2019-02-25 15:37:27  48
  49 10.25 -0.35 2019-02-25 15:37:28  49
  50 10.75 -0.35 2019-02-25 15:37:28  50
  51 11.25 -0.35 2019-02-25 15:37:28  51
  52 11.75 -0.35 2019-02-25 15:37:28  52
  53 10.25 -1.05 2019-02-25 15:37:28  53
  54 10.75 -1.05 2019-02-25 15:37:28  54
  55 11.25 -1.05 2019-02-25 15:37:28  55
  56 11.75 -1.05 2019-02-25 15:37:28  56
  57 10.25 -1.75 2019-02-25 15:37:28  57
  58 10.75 -1.75 2019-02-25 15:37:28  58
  59 11.25 -1.75 2019-02-25 15:37:28  59
  60 11.75 -1.75 2019-02-25 15:37:28  60
  61 10.25 -2.45 2019-02-25 15:37:28  61
  62 10.75 -2.45 2019-02-25 15:37:28  62
  63 11.25 -2.45 2019-02-25 15:37:28  63
  64 11.75 -2.45 2019-02-25 15:37:28  64
  > plot(s, col = sf.colors(), axes = TRUE)
  > (s.stfdf = as(s, "STFDF"))
  An object of class "STFDF"
  Slot "data":
     foo
  1    1
  2    2
  3    3
  4    4
  5    5
  6    6
  7    7
  8    8
  9    9
  10  10
  11  11
  12  12
  13  13
  14  14
  15  15
  16  16
  17  17
  18  18
  19  19
  20  20
  21  21
  22  22
  23  23
  24  24
  25  25
  26  26
  27  27
  28  28
  29  29
  30  30
  31  31
  32  32
  33  33
  34  34
  35  35
  36  36
  37  37
  38  38
  39  39
  40  40
  41  41
  42  42
  43  43
  44  44
  45  45
  46  46
  47  47
  48  48
  49  49
  50  50
  51  51
  52  52
  53  53
  54  54
  55  55
  56  56
  57  57
  58  58
  59  59
  60  60
  61  61
  62  62
  63  63
  64  64
  
  Slot "sp":
  Object of class SpatialPixels
  Grid topology:
    cellcentre.offset cellsize cells.dim
  x             10.25      0.5         4
  y             -2.45      0.7         4
  SpatialPoints:
            x     y
   [1,] 10.25 -0.35
   [2,] 10.75 -0.35
   [3,] 11.25 -0.35
   [4,] 11.75 -0.35
   [5,] 10.25 -1.05
   [6,] 10.75 -1.05
   [7,] 11.25 -1.05
   [8,] 11.75 -1.05
   [9,] 10.25 -1.75
  [10,] 10.75 -1.75
  [11,] 11.25 -1.75
  [12,] 11.75 -1.75
  [13,] 10.25 -2.45
  [14,] 10.75 -2.45
  [15,] 11.25 -2.45
  [16,] 11.75 -2.45
  Coordinate Reference System (CRS) arguments: NA 
  
  Slot "time":
                      timeIndex
  2019-02-25 15:37:25         1
  2019-02-25 15:37:26         2
  2019-02-25 15:37:27         3
  2019-02-25 15:37:28         4
  
  Slot "endTime":
  [1] "2019-02-25 15:37:26 UTC" "2019-02-25 15:37:27 UTC"
  [3] "2019-02-25 15:37:28 UTC" "2019-02-25 15:37:29 UTC"
  
  > stplot(s.stfdf, scales = list(draw = TRUE))
  > 
  > (s2 = st_as_stars(s.stfdf))
  stars object with 3 dimensions and 1 attribute
  attribute(s):
       Min. 1st Qu. Median Mean 3rd Qu. Max.
  foo     1   16.75   32.5 32.5   48.25   64
  dimension(s):
       from to                  offset  delta  refsys x/y
  x       1  4                      10    0.5      NA [x]
  y       1  4               -1.11e-16   -0.7      NA [y]
  time    1  4 2019-02-25 15:37:25 UTC 1 secs POSIXct    
  > plot(s2, col = sf.colors(), axes = TRUE)
  > all.equal(s, s2, check.attributes = FALSE)
  [1] TRUE
  > 
  > # multiple simulations:
  > data(meuse, package = "sp")
  > data(meuse.grid, package = "sp")
  > coordinates(meuse.grid) <- ~x+y
  > gridded(meuse.grid) <- TRUE
  > meuse.grid = st_as_stars(meuse.grid)
  > meuse_sf = st_as_sf(meuse, coords = c("x", "y"))
  > g = gstat(NULL, "zinc", zinc~1, meuse_sf, model = vgm(1, "Exp", 300), nmax = 10)
  > g = gstat(g, "lead", lead~1, meuse_sf, model = vgm(1, "Exp", 300), nmax = 10, fill.cross = TRUE)
  > set.seed(123)
  > ## IGNORE_RDIFF_BEGIN
  > (p = predict(g, meuse.grid, nsim = 5))
  drawing 5 multivariate GLS realisations of beta...