Last updated on 2025-01-31 01:48:27 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.1-2 | 18.71 | 189.44 | 208.15 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 2.1-2 | 15.70 | 128.06 | 143.76 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.1-2 | 326.63 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 2.1-2 | OK | ||||
| r-devel-windows-x86_64 | 2.1-2 | 34.00 | 250.00 | 284.00 | NOTE | |
| r-patched-linux-x86_64 | 2.1-2 | 23.47 | 177.67 | 201.14 | OK | |
| r-release-linux-x86_64 | 2.1-2 | 21.56 | 175.99 | 197.55 | OK | |
| r-release-macos-arm64 | 2.1-2 | 107.00 | OK | |||
| r-release-macos-x86_64 | 2.1-2 | 221.00 | OK | |||
| r-release-windows-x86_64 | 2.1-2 | 36.00 | 251.00 | 287.00 | OK | |
| r-oldrel-macos-arm64 | 2.1-2 | 126.00 | OK | |||
| r-oldrel-macos-x86_64 | 2.1-2 | 242.00 | OK | |||
| r-oldrel-windows-x86_64 | 2.1-2 | 36.00 | 277.00 | 313.00 | OK |
Version: 2.1-2
Check: for unstated dependencies in ‘demo’
Result: NOTE
'library' or 'require' calls not declared from:
‘RColorBrewer’ ‘geoR’ ‘ggplot2’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 2.1-2
Check: tests
Result: NOTE
Running ‘allier.R’ [1s/27s]
Comparing ‘allier.Rout’ to ‘allier.Rout.save’ ... OK
Running ‘blockkr.R’ [1s/2s]
Comparing ‘blockkr.Rout’ to ‘blockkr.Rout.save’ ... OK
Running ‘covtable.R’ [1s/1s]
Comparing ‘covtable.Rout’ to ‘covtable.Rout.save’ ... OK
Running ‘cv.R’ [2s/2s]
Comparing ‘cv.Rout’ to ‘cv.Rout.save’ ...68c68
< Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190976
---
> Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190977
Running ‘cv3d.R’ [2s/2s]
Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ...14c14
< 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.501 3rd Qu.: 0.8508
---
> 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.500 3rd Qu.: 0.8508
17,22c17,22
< Min. :-5.1678 Min. : 1.0 Min. :0.00678 Min. :0.0034
< 1st Qu.:-1.8749 1st Qu.:13.2 1st Qu.:0.23966 1st Qu.:0.2466
< Median : 0.2453 Median :25.5 Median :0.48668 Median :0.4525
< Mean : 0.0167 Mean :25.5 Mean :0.49966 Mean :0.4969
< 3rd Qu.: 2.0201 3rd Qu.:37.8 3rd Qu.:0.74730 3rd Qu.:0.7394
< Max. : 7.3541 Max. :50.0 Max. :0.98754 Max. :0.9872
---
> Min. :-5.168 Min. : 1.0 Min. :0.0068 Min. :0.0034
> 1st Qu.:-1.875 1st Qu.:13.2 1st Qu.:0.2397 1st Qu.:0.2466
> Median : 0.245 Median :25.5 Median :0.4867 Median :0.4525
> Mean : 0.017 Mean :25.5 Mean :0.4997 Mean :0.4969
> 3rd Qu.: 2.020 3rd Qu.:37.8 3rd Qu.:0.7473 3rd Qu.:0.7394
> Max. : 7.354 Max. :50.0 Max. :0.9875 Max. :0.9872
24,29c24,29
< Min. :0.00164
< 1st Qu.:0.18646
< Median :0.44850
< Mean :0.47142
< 3rd Qu.:0.72403
< Max. :0.99420
---
> Min. :0.0016
> 1st Qu.:0.1865
> Median :0.4485
> Mean :0.4714
> 3rd Qu.:0.7240
> Max. :0.9942
Running ‘fit.R’ [1s/2s]
Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
Running ‘krige0.R’ [3s/4s]
Comparing ‘krige0.Rout’ to ‘krige0.Rout.save’ ... OK
Running ‘line.R’ [2s/2s]
Comparing ‘line.Rout’ to ‘line.Rout.save’ ... OK
Running ‘merge.R’ [1s/2s]
Comparing ‘merge.Rout’ to ‘merge.Rout.save’ ... OK
Running ‘na.action.R’ [1s/2s]
Comparing ‘na.action.Rout’ to ‘na.action.Rout.save’ ... OK
Running ‘rings.R’ [2s/2s]
Comparing ‘rings.Rout’ to ‘rings.Rout.save’ ... OK
Running ‘sim.R’ [1s/2s]
Comparing ‘sim.Rout’ to ‘sim.Rout.save’ ... OK
Running ‘stars.R’ [14s/23s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ...196,201c196,201
< 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
---
> Min. :4.777 Min. :0.085 (0,5]: 316
> 1st Qu.:5.238 1st Qu.:0.137 (5,6]:1778
> Median :5.573 Median :0.162 (6,7]: 962
> Mean :5.707 Mean :0.185 (7,8]: 47
> 3rd Qu.:6.172 3rd Qu.:0.212 (8,9]: 0
> Max. :7.440 Max. :0.500 NA's :5009
Running ‘unproj.R’ [4s/7s]
Comparing ‘unproj.Rout’ to ‘unproj.Rout.save’ ... OK
Running ‘variogram.R’ [2s/3s]
Comparing ‘variogram.Rout’ to ‘variogram.Rout.save’ ... OK
Running ‘vdist.R’ [1s/2s]
Comparing ‘vdist.Rout’ to ‘vdist.Rout.save’ ... OK
Running ‘windst.R’ [8s/12s]
Comparing ‘windst.Rout’ to ‘windst.Rout.save’ ... OK
Flavor: r-devel-linux-x86_64-debian-clang
Version: 2.1-2
Check: tests
Result: ERROR
Running ‘allier.R’ [1s/2s]
Comparing ‘allier.Rout’ to ‘allier.Rout.save’ ... OK
Running ‘blockkr.R’ [1s/1s]
Comparing ‘blockkr.Rout’ to ‘blockkr.Rout.save’ ... OK
Running ‘covtable.R’ [1s/1s]
Comparing ‘covtable.Rout’ to ‘covtable.Rout.save’ ... OK
Running ‘cv.R’ [1s/1s]
Comparing ‘cv.Rout’ to ‘cv.Rout.save’ ...68c68
< Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190976
---
> Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190977
Running ‘cv3d.R’ [1s/1s]
Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ...14c14
< 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.501 3rd Qu.: 0.8508
---
> 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.500 3rd Qu.: 0.8508
17,22c17,22
< Min. :-5.1678 Min. : 1.0 Min. :0.00678 Min. :0.0034
< 1st Qu.:-1.8749 1st Qu.:13.2 1st Qu.:0.23966 1st Qu.:0.2466
< Median : 0.2453 Median :25.5 Median :0.48668 Median :0.4525
< Mean : 0.0167 Mean :25.5 Mean :0.49966 Mean :0.4969
< 3rd Qu.: 2.0201 3rd Qu.:37.8 3rd Qu.:0.74730 3rd Qu.:0.7394
< Max. : 7.3541 Max. :50.0 Max. :0.98754 Max. :0.9872
---
> Min. :-5.168 Min. : 1.0 Min. :0.0068 Min. :0.0034
> 1st Qu.:-1.875 1st Qu.:13.2 1st Qu.:0.2397 1st Qu.:0.2466
> Median : 0.245 Median :25.5 Median :0.4867 Median :0.4525
> Mean : 0.017 Mean :25.5 Mean :0.4997 Mean :0.4969
> 3rd Qu.: 2.020 3rd Qu.:37.8 3rd Qu.:0.7473 3rd Qu.:0.7394
> Max. : 7.354 Max. :50.0 Max. :0.9875 Max. :0.9872
24,29c24,29
< Min. :0.00164
< 1st Qu.:0.18646
< Median :0.44850
< Mean :0.47142
< 3rd Qu.:0.72403
< Max. :0.99420
---
> Min. :0.0016
> 1st Qu.:0.1865
> Median :0.4485
> Mean :0.4714
> 3rd Qu.:0.7240
> Max. :0.9942
Running ‘fit.R’ [1s/1s]
Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
Running ‘krige0.R’ [2s/3s]
Comparing ‘krige0.Rout’ to ‘krige0.Rout.save’ ... OK
Running ‘line.R’ [1s/2s]
Comparing ‘line.Rout’ to ‘line.Rout.save’ ... OK
Running ‘merge.R’ [1s/1s]
Comparing ‘merge.Rout’ to ‘merge.Rout.save’ ... OK
Running ‘na.action.R’ [1s/1s]
Comparing ‘na.action.Rout’ to ‘na.action.Rout.save’ ... OK
Running ‘rings.R’ [1s/1s]
Comparing ‘rings.Rout’ to ‘rings.Rout.save’ ... OK
Running ‘sim.R’ [1s/1s]
Comparing ‘sim.Rout’ to ‘sim.Rout.save’ ... OK
Running ‘stars.R’ [8s/10s]
Running ‘unproj.R’ [3s/4s]
Comparing ‘unproj.Rout’ to ‘unproj.Rout.save’ ... OK
Running ‘variogram.R’ [1s/1s]
Comparing ‘variogram.Rout’ to ‘variogram.Rout.save’ ... OK
Running ‘vdist.R’ [1s/1s]
Comparing ‘vdist.Rout’ to ‘vdist.Rout.save’ ... OK
Running ‘windst.R’ [3s/5s]
Running the tests in ‘tests/stars.R’ failed.
Complete output:
> Sys.setenv(TZ = "UTC")
>
> # 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")))
+ )
Error in `/.difftime`(diff(range(ud)), mean(ud)) :
second argument of / cannot be a "difftime" object
Calls: <Anonymous> ... <Anonymous> -> regular_intervals -> isTRUE -> /.difftime
Execution halted
Running the tests in ‘tests/windst.R’ failed.
Complete output:
> suppressPackageStartupMessages(library(sp))
> suppressPackageStartupMessages(library(spacetime))
> suppressPackageStartupMessages(library(gstat))
> suppressPackageStartupMessages(library(stars))
>
> data(wind)
> wind.loc$y = as.numeric(char2dms(as.character(wind.loc[["Latitude"]])))
> wind.loc$x = as.numeric(char2dms(as.character(wind.loc[["Longitude"]])))
> coordinates(wind.loc) = ~x+y
> proj4string(wind.loc) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
>
> wind$time = ISOdate(wind$year+1900, wind$month, wind$day)
> wind$jday = as.numeric(format(wind$time, '%j'))
> stations = 4:15
> windsqrt = sqrt(0.5148 * wind[stations]) # knots -> m/s
> Jday = 1:366
> daymeans = colMeans(
+ sapply(split(windsqrt - colMeans(windsqrt), wind$jday), colMeans))
> meanwind = lowess(daymeans ~ Jday, f = 0.1)$y[wind$jday]
> velocities = apply(windsqrt, 2, function(x) { x - meanwind })
> # match order of columns in wind to Code in wind.loc;
> # convert to utm zone 29, to be able to do interpolation in
> # proper Euclidian (projected) space:
> pts = coordinates(wind.loc[match(names(wind[4:15]), wind.loc$Code),])
> pts = SpatialPoints(pts)
> if (require(sp, quietly = TRUE) && require(maps, quietly = TRUE)) {
+ proj4string(pts) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
+ utm29 = "+proj=utm +zone=29 +datum=WGS84 +ellps=WGS84"
+ pts = as(st_transform(st_as_sfc(pts), utm29), "Spatial")
+ # note the t() in:
+ w = STFDF(pts, wind$time, data.frame(values = as.vector(t(velocities))))
+
+ library(mapdata)
+ mp = map("worldHires", xlim = c(-11,-5.4), ylim = c(51,55.5), plot=FALSE)
+ sf = st_transform(st_as_sf(mp, fill = FALSE), utm29)
+ m = as(sf, "Spatial")
+
+ # setup grid
+ grd = SpatialPixels(SpatialPoints(makegrid(m, n = 300)),
+ proj4string = m@proj4string)
+ # grd$t = rep(1, nrow(grd))
+ #coordinates(grd) = ~x1+x2
+ #gridded(grd)=TRUE
+
+ # select april 1961:
+ w = w[, "1961-04"]
+
+ covfn = function(x, y = x) {
+ du = spDists(coordinates(x), coordinates(y))
+ t1 = as.numeric(index(x)) # time in seconds
+ t2 = as.numeric(index(y)) # time in seconds
+ dt = abs(outer(t1, t2, "-"))
+ # separable, product covariance model:
+ 0.6 * exp(-du/750000) * exp(-dt / (1.5 * 3600 * 24))
+ }
+
+ n = 10
+ tgrd = seq(min(index(w)), max(index(w)), length=n)
+ pred = krige0(sqrt(values)~1, w, STF(grd, tgrd), covfn)
+ layout = list(list("sp.points", pts, first=F, cex=.5),
+ list("sp.lines", m, col='grey'))
+ wind.pr0 = STFDF(grd, tgrd, data.frame(var1.pred = pred))
+
+ v = vgmST("separable",
+ space = vgm(1, "Exp", 750000),
+ time = vgm(1, "Exp", 1.5 * 3600 * 24),
+ sill = 0.6)
+ wind.ST = krigeST(sqrt(values)~1, w, STF(grd, tgrd), v)
+
+ all.equal(wind.pr0, wind.ST)
+
+ # stars:
+ df = data.frame(a = rep(NA, 324*10))
+ s = STF(grd, tgrd)
+ newd = addAttrToGeom(s, df)
+ wind.sta = krigeST(sqrt(values)~1, st_as_stars(w), st_as_stars(newd), v)
+ # 1
+ plot(stars::st_as_stars(wind.ST), breaks = "equal", col = sf.colors())
+ # 2
+ stplot(wind.ST)
+ # 3
+ plot(wind.sta, breaks = "equal", col = sf.colors())
+ st_as_stars(wind.ST)[[1]][1:3,1:3,1]
+ (wind.sta)[[1]][1:3,1:3,1]
+ st_bbox(wind.sta)
+ bbox(wind.ST)
+ all.equal(wind.sta, stars::st_as_stars(wind.ST), check.attributes = FALSE)
+
+ # 4: roundtrip wind.sta->STFDF->stars
+ rt = stars::st_as_stars(as(wind.sta, "STFDF"))
+ plot(rt, breaks = "equal", col = sf.colors())
+ # 5:
+ stplot(as(wind.sta, "STFDF"))
+ st_bbox(rt)
+
+ # 6:
+ stplot(as(st_as_stars(wind.ST), "STFDF"))
+ }
Error in `/.difftime`(diff(range(ud)), mean(ud)) :
second argument of / cannot be a "difftime" object
Calls: krigeST ... create_dimension -> regular_intervals -> isTRUE -> /.difftime
In addition: Warning message:
In krigeST(sqrt(values) ~ 1, w, STF(grd, tgrd), v) :
The spatio-temporal variogram model does not carry the strongly recommended attribute 'temporal unit'.
The unit 'secs' has been assumed. krigeST could not check whether the temporal distances between locations and in the variogram coincide.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.1-2
Check: tests
Result: ERROR
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’ ...68c68
< Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190976
---
> Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190977
Running ‘cv3d.R’
Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ...14c14
< 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.501 3rd Qu.: 0.8508
---
> 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.500 3rd Qu.: 0.8508
17,22c17,22
< Min. :-5.1678 Min. : 1.0 Min. :0.00678 Min. :0.0034
< 1st Qu.:-1.8749 1st Qu.:13.2 1st Qu.:0.23966 1st Qu.:0.2466
< Median : 0.2453 Median :25.5 Median :0.48668 Median :0.4525
< Mean : 0.0167 Mean :25.5 Mean :0.49966 Mean :0.4969
< 3rd Qu.: 2.0201 3rd Qu.:37.8 3rd Qu.:0.74730 3rd Qu.:0.7394
< Max. : 7.3541 Max. :50.0 Max. :0.98754 Max. :0.9872
---
> Min. :-5.168 Min. : 1.0 Min. :0.0068 Min. :0.0034
> 1st Qu.:-1.875 1st Qu.:13.2 1st Qu.:0.2397 1st Qu.:0.2466
> Median : 0.245 Median :25.5 Median :0.4867 Median :0.4525
> Mean : 0.017 Mean :25.5 Mean :0.4997 Mean :0.4969
> 3rd Qu.: 2.020 3rd Qu.:37.8 3rd Qu.:0.7473 3rd Qu.:0.7394
> Max. : 7.354 Max. :50.0 Max. :0.9875 Max. :0.9872
24,29c24,29
< Min. :0.00164
< 1st Qu.:0.18646
< Median :0.44850
< Mean :0.47142
< 3rd Qu.:0.72403
< Max. :0.99420
---
> Min. :0.0016
> 1st Qu.:0.1865
> Median :0.4485
> Mean :0.4714
> 3rd Qu.:0.7240
> Max. :0.9942
Running ‘fit.R’
Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
Running ‘krige0.R’
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’ [22s/28s]
Running ‘unproj.R’
Comparing ‘unproj.Rout’ to ‘unproj.Rout.save’ ... OK
Running ‘variogram.R’
Comparing ‘variogram.Rout’ to ‘variogram.Rout.save’ ... OK
Running ‘vdist.R’
Comparing ‘vdist.Rout’ to ‘vdist.Rout.save’ ... OK
Running ‘windst.R’
Running the tests in ‘tests/stars.R’ failed.
Complete output:
> Sys.setenv(TZ = "UTC")
>
> # 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")))
+ )
Error in `/.difftime`(diff(range(ud)), mean(ud)) :
second argument of / cannot be a "difftime" object
Calls: <Anonymous> ... <Anonymous> -> regular_intervals -> isTRUE -> /.difftime
Execution halted
Running the tests in ‘tests/windst.R’ failed.
Complete output:
> suppressPackageStartupMessages(library(sp))
> suppressPackageStartupMessages(library(spacetime))
> suppressPackageStartupMessages(library(gstat))
> suppressPackageStartupMessages(library(stars))
>
> data(wind)
> wind.loc$y = as.numeric(char2dms(as.character(wind.loc[["Latitude"]])))
> wind.loc$x = as.numeric(char2dms(as.character(wind.loc[["Longitude"]])))
> coordinates(wind.loc) = ~x+y
> proj4string(wind.loc) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
>
> wind$time = ISOdate(wind$year+1900, wind$month, wind$day)
> wind$jday = as.numeric(format(wind$time, '%j'))
> stations = 4:15
> windsqrt = sqrt(0.5148 * wind[stations]) # knots -> m/s
> Jday = 1:366
> daymeans = colMeans(
+ sapply(split(windsqrt - colMeans(windsqrt), wind$jday), colMeans))
> meanwind = lowess(daymeans ~ Jday, f = 0.1)$y[wind$jday]
> velocities = apply(windsqrt, 2, function(x) { x - meanwind })
> # match order of columns in wind to Code in wind.loc;
> # convert to utm zone 29, to be able to do interpolation in
> # proper Euclidian (projected) space:
> pts = coordinates(wind.loc[match(names(wind[4:15]), wind.loc$Code),])
> pts = SpatialPoints(pts)
> if (require(sp, quietly = TRUE) && require(maps, quietly = TRUE)) {
+ proj4string(pts) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
+ utm29 = "+proj=utm +zone=29 +datum=WGS84 +ellps=WGS84"
+ pts = as(st_transform(st_as_sfc(pts), utm29), "Spatial")
+ # note the t() in:
+ w = STFDF(pts, wind$time, data.frame(values = as.vector(t(velocities))))
+
+ library(mapdata)
+ mp = map("worldHires", xlim = c(-11,-5.4), ylim = c(51,55.5), plot=FALSE)
+ sf = st_transform(st_as_sf(mp, fill = FALSE), utm29)
+ m = as(sf, "Spatial")
+
+ # setup grid
+ grd = SpatialPixels(SpatialPoints(makegrid(m, n = 300)),
+ proj4string = m@proj4string)
+ # grd$t = rep(1, nrow(grd))
+ #coordinates(grd) = ~x1+x2
+ #gridded(grd)=TRUE
+
+ # select april 1961:
+ w = w[, "1961-04"]
+
+ covfn = function(x, y = x) {
+ du = spDists(coordinates(x), coordinates(y))
+ t1 = as.numeric(index(x)) # time in seconds
+ t2 = as.numeric(index(y)) # time in seconds
+ dt = abs(outer(t1, t2, "-"))
+ # separable, product covariance model:
+ 0.6 * exp(-du/750000) * exp(-dt / (1.5 * 3600 * 24))
+ }
+
+ n = 10
+ tgrd = seq(min(index(w)), max(index(w)), length=n)
+ pred = krige0(sqrt(values)~1, w, STF(grd, tgrd), covfn)
+ layout = list(list("sp.points", pts, first=F, cex=.5),
+ list("sp.lines", m, col='grey'))
+ wind.pr0 = STFDF(grd, tgrd, data.frame(var1.pred = pred))
+
+ v = vgmST("separable",
+ space = vgm(1, "Exp", 750000),
+ time = vgm(1, "Exp", 1.5 * 3600 * 24),
+ sill = 0.6)
+ wind.ST = krigeST(sqrt(values)~1, w, STF(grd, tgrd), v)
+
+ all.equal(wind.pr0, wind.ST)
+
+ # stars:
+ df = data.frame(a = rep(NA, 324*10))
+ s = STF(grd, tgrd)
+ newd = addAttrToGeom(s, df)
+ wind.sta = krigeST(sqrt(values)~1, st_as_stars(w), st_as_stars(newd), v)
+ # 1
+ plot(stars::st_as_stars(wind.ST), breaks = "equal", col = sf.colors())
+ # 2
+ stplot(wind.ST)
+ # 3
+ plot(wind.sta, breaks = "equal", col = sf.colors())
+ st_as_stars(wind.ST)[[1]][1:3,1:3,1]
+ (wind.sta)[[1]][1:3,1:3,1]
+ st_bbox(wind.sta)
+ bbox(wind.ST)
+ all.equal(wind.sta, stars::st_as_stars(wind.ST), check.attributes = FALSE)
+
+ # 4: roundtrip wind.sta->STFDF->stars
+ rt = stars::st_as_stars(as(wind.sta, "STFDF"))
+ plot(rt, breaks = "equal", col = sf.colors())
+ # 5:
+ stplot(as(wind.sta, "STFDF"))
+ st_bbox(rt)
+
+ # 6:
+ stplot(as(st_as_stars(wind.ST), "STFDF"))
+ }
Error in `/.difftime`(diff(range(ud)), mean(ud)) :
second argument of / cannot be a "difftime" object
Calls: krigeST ... create_dimension -> regular_intervals -> isTRUE -> /.difftime
In addition: Warning message:
In krigeST(sqrt(values) ~ 1, w, STF(grd, tgrd), v) :
The spatio-temporal variogram model does not carry the strongly recommended attribute 'temporal unit'.
The unit 'secs' has been assumed. krigeST could not check whether the temporal distances between locations and in the variogram coincide.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 2.1-2
Check: tests
Result: NOTE
Running 'allier.R' [1s]
Comparing 'allier.Rout' to 'allier.Rout.save' ... OK
Running 'blockkr.R' [1s]
Comparing 'blockkr.Rout' to 'blockkr.Rout.save' ... OK
Running 'covtable.R' [1s]
Comparing 'covtable.Rout' to 'covtable.Rout.save' ... OK
Running 'cv.R' [1s]
Comparing 'cv.Rout' to 'cv.Rout.save' ...68c68
< Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190976
---
> Min. :4.644 Min. :0.002371 Min. :4.727 Min. :-0.4190977
Running 'cv3d.R' [2s]
Comparing 'cv3d.Rout' to 'cv3d.Rout.save' ...14c14
< 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.501 3rd Qu.: 0.8508
---
> 3rd Qu.: 0.161 3rd Qu.:0.240 3rd Qu.: 0.500 3rd Qu.: 0.8508
17,22c17,22
< Min. :-5.1678 Min. : 1.0 Min. :0.00678 Min. :0.0034
< 1st Qu.:-1.8749 1st Qu.:13.2 1st Qu.:0.23966 1st Qu.:0.2466
< Median : 0.2453 Median :25.5 Median :0.48668 Median :0.4525
< Mean : 0.0167 Mean :25.5 Mean :0.49966 Mean :0.4969
< 3rd Qu.: 2.0201 3rd Qu.:37.8 3rd Qu.:0.74730 3rd Qu.:0.7394
< Max. : 7.3541 Max. :50.0 Max. :0.98754 Max. :0.9872
---
> Min. :-5.168 Min. : 1.0 Min. :0.0068 Min. :0.0034
> 1st Qu.:-1.875 1st Qu.:13.2 1st Qu.:0.2397 1st Qu.:0.2466
> Median : 0.245 Median :25.5 Median :0.4867 Median :0.4525
> Mean : 0.017 Mean :25.5 Mean :0.4997 Mean :0.4969
> 3rd Qu.: 2.020 3rd Qu.:37.8 3rd Qu.:0.7473 3rd Qu.:0.7394
> Max. : 7.354 Max. :50.0 Max. :0.9875 Max. :0.9872
24,29c24,29
< Min. :0.00164
< 1st Qu.:0.18646
< Median :0.44850
< Mean :0.47142
< 3rd Qu.:0.72403
< Max. :0.99420
---
> Min. :0.0016
> 1st Qu.:0.1865
> Median :0.4485
> Mean :0.4714
> 3rd Qu.:0.7240
> Max. :0.9942
Running 'fit.R' [1s]
Comparing 'fit.Rout' to 'fit.Rout.save' ... OK
Running 'krige0.R' [3s]
Comparing 'krige0.Rout' to 'krige0.Rout.save' ... OK
Running 'line.R' [2s]
Comparing 'line.Rout' to 'line.Rout.save' ... OK
Running 'merge.R' [1s]
Comparing 'merge.Rout' to 'merge.Rout.save' ... OK
Running 'na.action.R' [1s]
Comparing 'na.action.Rout' to 'na.action.Rout.save' ... OK
Running 'rings.R' [1s]
Comparing 'rings.Rout' to 'rings.Rout.save' ... OK
Running 'sim.R' [1s]
Comparing 'sim.Rout' to 'sim.Rout.save' ... OK
Running 'stars.R' [12s]
Comparing 'stars.Rout' to 'stars.Rout.save' ...196,201c196,201
< 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
---
> Min. :4.777 Min. :0.085 (0,5]: 316
> 1st Qu.:5.238 1st Qu.:0.137 (5,6]:1778
> Median :5.573 Median :0.162 (6,7]: 962
> Mean :5.707 Mean :0.185 (7,8]: 47
> 3rd Qu.:6.172 3rd Qu.:0.212 (8,9]: 0
> Max. :7.440 Max. :0.500 NA's :5009
Running 'unproj.R' [3s]
Comparing 'unproj.Rout' to 'unproj.Rout.save' ... OK
Running 'variogram.R' [1s]
Comparing 'variogram.Rout' to 'variogram.Rout.save' ... OK
Running 'vdist.R' [1s]
Comparing 'vdist.Rout' to 'vdist.Rout.save' ... OK
Running 'windst.R' [8s]
Comparing 'windst.Rout' to 'windst.Rout.save' ... OK
Flavor: r-devel-windows-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.