Last updated on 2025-11-15 03:50:51 CET.
| Package | ERROR | WARN | NOTE | OK |
|---|---|---|---|---|
| gstat | 2 | 11 | ||
| hexbin | 2 | 11 | ||
| intervals | 13 | |||
| lwgeom | 5 | 8 | ||
| s2 | 2 | 3 | 8 | |
| sf | 1 | 7 | 5 | |
| sp | 3 | 10 | ||
| spacetime | 13 | |||
| stars | 13 | |||
| trajectories | 7 | 6 | ||
| units | 13 | |||
| vardiag | 2 | 11 |
Current CRAN status: ERROR: 2, OK: 11
Version: 2.1-4
Check: tests
Result: ERROR
Running ‘allier.R’ [2s/10s]
Comparing ‘allier.Rout’ to ‘allier.Rout.save’ ... OK
Running ‘blockkr.R’ [2s/11s]
Comparing ‘blockkr.Rout’ to ‘blockkr.Rout.save’ ... OK
Running ‘covtable.R’ [2s/13s]
Comparing ‘covtable.Rout’ to ‘covtable.Rout.save’ ... OK
Running ‘cv.R’ [3s/11s]
Comparing ‘cv.Rout’ to ‘cv.Rout.save’ ... OK
Running ‘cv3d.R’ [3s/16s]
Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ... OK
Running ‘fit.R’ [2s/14s]
Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
Running ‘krige0.R’ [4s/14s]
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’ [39s/121s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ... OK
Running ‘variogram.R’ [3s/18s]
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/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"))
+ }
OMP: Warning #96: Cannot form a team with 24 threads, using 2 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 2.1-4
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’ ... 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’
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’ [90m/68m]
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’ [0m/22m]
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
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20 20
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27 27
28 28
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30 30
31 31
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33 33
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36 36
37 37
38 38
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40 40
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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...
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"))
+ }
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: NOTE: 2, OK: 11
Version: 1.28.5
Check: re-building of vignette outputs
Result: NOTE
Note: skipping ‘hexagon_binning.Rnw’ due to unavailable dependencies:
'marray'
Flavors: r-release-macos-arm64, r-release-macos-x86_64
Current CRAN status: OK: 13
Current CRAN status: NOTE: 5, OK: 8
Version: 0.2-14
Check: tests
Result: NOTE
Running ‘azimuth.R’
Comparing ‘azimuth.Rout’ to ‘azimuth.Rout.save’ ... OK
Running ‘dist.R’
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘geod.R’
Comparing ‘geod.Rout’ to ‘geod.Rout.save’ ... OK
Running ‘perimeter.R’
Comparing ‘perimeter.Rout’ to ‘perimeter.Rout.save’ ...9c9
< [1] 176215.7 149266.8 199587.9 375136.8 263512.7
---
> [1] 176214.9 149265.4 199586.8 375137.8 263512.6
12c12
< [1] 176215.7 149266.8 199587.9 375136.8 263512.7
---
> [1] 176214.9 149265.4 199586.8 375137.8 263512.6
Running ‘testthat.R’
Comparing ‘testthat.Rout’ to ‘testthat.Rout.save’ ... OK
Running ‘twkb.R’
Comparing ‘twkb.Rout’ to ‘twkb.Rout.save’ ... OK
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.2-14
Check: installed package size
Result: NOTE
installed size is 24.4Mb
sub-directories of 1Mb or more:
libs 24.2Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: WARN: 2, NOTE: 3, OK: 8
Version: 1.1.9
Check: compiled code
Result: WARN
File ‘s2/libs/s2.so’:
Found ‘__ZNSt3__14cerrE’, possibly from ‘std::cerr’ (C++)
Object: ‘../tools/dist/lib/libabsl_flags_config.a’
Found ‘___assert_rtn’, possibly from ‘assert’ (C)
Objects: ‘../tools/dist/lib/libabsl_base.a’,
‘../tools/dist/lib/libabsl_cord.a’,
‘../tools/dist/lib/libabsl_cord_internal.a’,
‘../tools/dist/lib/libabsl_cordz_handle.a’,
‘../tools/dist/lib/libabsl_cordz_info.a’,
‘../tools/dist/lib/libabsl_crc_cord_state.a’,
‘../tools/dist/lib/libabsl_crc_internal.a’,
‘../tools/dist/lib/libabsl_flags_internal.a’,
‘../tools/dist/lib/libabsl_flags_reflection.a’,
‘../tools/dist/lib/libabsl_graphcycles_internal.a’,
‘../tools/dist/lib/libabsl_int128.a’,
‘../tools/dist/lib/libabsl_kernel_timeout_internal.a’,
‘../tools/dist/lib/libabsl_log_globals.a’,
‘../tools/dist/lib/libabsl_log_internal_format.a’,
‘../tools/dist/lib/libabsl_log_internal_globals.a’,
‘../tools/dist/lib/libabsl_log_internal_log_sink_set.a’,
‘../tools/dist/lib/libabsl_log_internal_message.a’,
‘../tools/dist/lib/libabsl_log_internal_proto.a’,
‘../tools/dist/lib/libabsl_malloc_internal.a’,
‘../tools/dist/lib/libabsl_raw_hash_set.a’,
‘../tools/dist/lib/libabsl_raw_logging_internal.a’,
‘../tools/dist/lib/libabsl_status.a’,
‘../tools/dist/lib/libabsl_str_format_internal.a’,
‘../tools/dist/lib/libabsl_strings.a’,
‘../tools/dist/lib/libabsl_strings_internal.a’,
‘../tools/dist/lib/libabsl_symbolize.a’,
‘../tools/dist/lib/libabsl_synchronization.a’,
‘../tools/dist/lib/libabsl_time.a’,
‘../tools/dist/lib/libabsl_time_zone.a’
Found ‘___stderrp’, possibly from ‘stderr’ (C)
Objects: ‘../tools/dist/lib/libabsl_log_internal_globals.a’,
‘../tools/dist/lib/libabsl_str_format_internal.a’
Found ‘__exit’, possibly from ‘_exit’ (C), ‘_Exit’ (C)
Object: ‘../tools/dist/lib/libabsl_log_internal_message.a’
Found ‘_abort’, possibly from ‘abort’ (C)
Objects: ‘../tools/dist/lib/libabsl_log_internal_message.a’,
‘../tools/dist/lib/libabsl_raw_logging_internal.a’
Found ‘_exit’, possibly from ‘exit’ (C)
Object: ‘../tools/dist/lib/libabsl_flags_reflection.a’
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs nor [v]sprintf.
See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-release-macos-arm64, r-release-macos-x86_64
Version: 1.1.9
Check: installed package size
Result: NOTE
installed size is 39.5Mb
sub-directories of 1Mb or more:
libs 38.4Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: ERROR: 1, NOTE: 7, OK: 5
Version: 1.0-22
Check: tests
Result: NOTE
Running ‘aggregate.R’ [1s/1s]
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ... OK
Running ‘cast.R’ [2s/2s]
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’ [1s/1s]
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’ [1s/1s]
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’ [3s/4s]
Comparing ‘dplyr.Rout’ to ‘dplyr.Rout.save’ ... OK
Running ‘empty.R’ [1s/1s]
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘full.R’ [1s/2s]
Comparing ‘full.Rout’ to ‘full.Rout.save’ ... OK
Running ‘gdal_geom.R’ [2s/2s]
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ... OK
Running ‘geos.R’ [19s/20s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ... OK
Running ‘graticule.R’ [3s/4s]
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’ [1s/2s]
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘maps.R’ [2s/2s]
Comparing ‘maps.Rout’ to ‘maps.Rout.save’ ... OK
Running ‘plot.R’ [6s/7s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’ [2s/4s]
Comparing ‘read.Rout’ to ‘read.Rout.save’ ... OK
Running ‘roundtrip.R’ [2s/3s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘s2.R’ [2s/3s]
Comparing ‘s2.Rout’ to ‘s2.Rout.save’ ... OK
Running ‘sample.R’ [1s/1s]
Comparing ‘sample.Rout’ to ‘sample.Rout.save’ ... OK
Running ‘sfc.R’ [10s/13s]
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ...547a548,551
> The following object is masked from 'package:testthat':
>
> matches
>
Running ‘sfg.R’ [1s/1s]
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘spatstat.R’ [3s/4s]
Comparing ‘spatstat.Rout’ to ‘spatstat.Rout.save’ ... OK
Running ‘stars.R’ [3s/5s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ... OK
Running ‘testthat.R’ [14s/18s]
Running ‘units.R’ [1s/1s]
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’ [1s/1s]
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0-22
Check: tests
Result: NOTE
Running ‘aggregate.R’
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ... OK
Running ‘cast.R’ [4s/14s]
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’ [7s/20s]
Comparing ‘dplyr.Rout’ to ‘dplyr.Rout.save’ ... OK
Running ‘empty.R’
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘full.R’
Comparing ‘full.Rout’ to ‘full.Rout.save’ ... OK
Running ‘gdal_geom.R’ [4s/11s]
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ...244,248c244,248
< [1,] 1760242094 0.114
< [2,] 946426033 0.061
< [3,] 2202239126 0.143
< [4,] 1074338664 0.070
< [5,] 2352518951 0.153
---
> [1,] 1760230516 0.114
> [2,] 946417787 0.061
> [3,] 2202223078 0.143
> [4,] 1074332698 0.070
> [5,] 2352528086 0.153
Running ‘geos.R’ [56s/155s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ...13,22c13,22
< [1,] 0.00 0.00 25652.42 440561.04 299772.09 361529.39 419671.11
< [2,] 0.00 0.00 0.00 409428.55 268944.32 332589.77 388544.57
< [3,] 25652.42 0.00 0.00 367555.46 227017.50 290297.11 346667.96
< [4,] 440561.04 409428.55 367555.46 0.00 67226.88 45537.78 0.00
< [5,] 299772.09 268944.32 227017.50 67226.88 0.00 0.00 46527.48
< [6,] 361529.39 332589.77 290297.11 45537.78 0.00 0.00 30213.34
< [7,] 419671.11 388544.57 346667.96 0.00 46527.48 30213.34 0.00
< [8,] 384592.69 354294.05 312350.59 16130.19 11926.78 0.00 0.00
< [9,] 262354.14 231217.46 189310.29 140455.85 0.00 64606.20 119563.76
< [10,] 71139.12 41943.86 0.00 330751.41 190182.42 252372.08 309862.03
---
> [1,] 0.00 0.00 25651.99 440561.48 299772.34 361529.73 419671.66
> [2,] 0.00 0.00 0.00 409429.44 268945.05 332590.52 388545.58
> [3,] 25651.99 0.00 0.00 367556.52 227018.38 290298.04 346669.14
> [4,] 440561.48 409429.44 367556.52 0.00 67226.86 45537.62 0.00
> [5,] 299772.34 268945.05 227018.38 67226.86 0.00 0.00 46527.56
> [6,] 361529.73 332590.52 290298.04 45537.62 0.00 0.00 30213.17
> [7,] 419671.66 388545.58 346669.14 0.00 46527.56 30213.17 0.00
> [8,] 384593.29 354295.06 312351.76 16130.19 11926.86 0.00 0.00
> [9,] 262353.97 231217.73 189310.73 140455.97 0.00 64606.27 119564.00
> [10,] 71138.53 41943.71 0.00 330752.58 190183.42 252373.26 309863.33
24,33c24,33
< [1,] 384592.69 262354.14 71139.12
< [2,] 354294.05 231217.46 41943.86
< [3,] 312350.59 189310.29 0.00
< [4,] 16130.19 140455.85 330751.41
< [5,] 11926.78 0.00 190182.42
< [6,] 0.00 64606.20 252372.08
< [7,] 0.00 119563.76 309862.03
< [8,] 0.00 85533.06 275389.73
< [9,] 85533.06 0.00 152488.90
< [10,] 275389.73 152488.90 0.00
---
> [1,] 384593.29 262353.97 71138.53
> [2,] 354295.06 231217.73 41943.71
> [3,] 312351.76 189310.73 0.00
> [4,] 16130.19 140455.97 330752.58
> [5,] 11926.86 0.00 190183.42
> [6,] 0.00 64606.27 252373.26
> [7,] 0.00 119564.00 309863.33
> [8,] 0.00 85533.33 275391.07
> [9,] 85533.33 0.00 152489.45
> [10,] 275391.07 152489.45 0.00
Running ‘graticule.R’ [7s/26s]
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘maps.R’ [5s/12s]
Comparing ‘maps.Rout’ to ‘maps.Rout.save’ ... OK
Running ‘plot.R’ [15s/43s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’ [9s/23s]
Comparing ‘read.Rout’ to ‘read.Rout.save’ ... OK
Running ‘roundtrip.R’ [4s/13s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘s2.R’ [4s/13s]
Comparing ‘s2.Rout’ to ‘s2.Rout.save’ ... OK
Running ‘sample.R’
Comparing ‘sample.Rout’ to ‘sample.Rout.save’ ... OK
Running ‘sfc.R’ [27s/72s]
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ...614c614
< Bounding box: xmin: 406261.8 ymin: 48374.95 xmax: 3052888 ymax: 1044157
---
> Bounding box: xmin: 406265 ymin: 48359.7 xmax: 3052877 ymax: 1044143
629,633c629,633
< 1 10 1364 0 19 A 4 #fb80724d MULTIPOLYGON (((1270815 913...
< 2 10 542 3 12 A 4 #fb80724d MULTIPOLYGON (((1340555 959...
< 3 208 3616 6 260 A 5 #80b1d34d MULTIPOLYGON (((1570591 910...
< 4 123 830 2 145 A 10 #bc80bd4d MULTIPOLYGON (((2881208 948...
< 5 1066 1606 3 1197 A 8 #fccde54d MULTIPOLYGON (((2525701 911...
---
> 1 10 1364 0 19 A 4 #fb80724d MULTIPOLYGON (((1270813 913...
> 2 10 542 3 12 A 4 #fb80724d MULTIPOLYGON (((1340553 959...
> 3 208 3616 6 260 A 5 #80b1d34d MULTIPOLYGON (((1570586 910...
> 4 123 830 2 145 A 10 #bc80bd4d MULTIPOLYGON (((2881206 948...
> 5 1066 1606 3 1197 A 8 #fccde54d MULTIPOLYGON (((2525700 911...
635,638c635,638
< 7 115 350 2 139 A 10 #bc80bd4d MULTIPOLYGON (((2881208 948...
< 8 254 594 2 371 A 9 #d9d9d94d MULTIPOLYGON (((2717989 951...
< 9 748 1190 2 844 A 8 #fccde54d MULTIPOLYGON (((2203890 914...
< 10 160 2038 5 176 A 5 #80b1d34d MULTIPOLYGON (((1697623 911...
---
> 7 115 350 2 139 A 10 #bc80bd4d MULTIPOLYGON (((2881206 948...
> 8 254 594 2 371 A 9 #d9d9d94d MULTIPOLYGON (((2717988 951...
> 9 748 1190 2 844 A 8 #fccde54d MULTIPOLYGON (((2203888 914...
> 10 160 2038 5 176 A 5 #80b1d34d MULTIPOLYGON (((1697618 911...
721c721
< Bounding box: xmin: 1216510 ymin: 935867 xmax: 1428880 ymax: 1031510
---
> Bounding box: xmin: 1216510 ymin: 935852 xmax: 1428880 ymax: 1031490
724,728c724,728
< POINT (1264559 935867)
< POINT (1256623 949384)
< POINT (1222665 972639)
< POINT (1333530 968278)
< POINT (1310838 958645)
---
> POINT (1264558 935852)
> POINT (1256623 949369)
> POINT (1222665 972624)
> POINT (1333528 968263)
> POINT (1310837 958630)
738c738
< Bounding box: xmin: -81.6893 ymin: 36.2492 xmax: -80.914 ymax: 36.5726
---
> Bounding box: xmin: -81.6893 ymin: 36.2491 xmax: -80.914 ymax: 36.5726
Running ‘sfg.R’
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘spatstat.R’ [8s/20s]
Comparing ‘spatstat.Rout’ to ‘spatstat.Rout.save’ ... OK
Running ‘stars.R’ [8s/18s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ... OK
Running ‘testthat.R’ [43s/95s]
Running ‘units.R’
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.0-22
Check: tests
Result: NOTE
Running ‘aggregate.R’
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ... OK
Running ‘cast.R’
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’
Comparing ‘dplyr.Rout’ to ‘dplyr.Rout.save’ ... OK
Running ‘empty.R’
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘full.R’
Comparing ‘full.Rout’ to ‘full.Rout.save’ ... OK
Running ‘gdal_geom.R’
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ...244,248c244,248
< [1,] 1760242094 0.114
< [2,] 946426033 0.061
< [3,] 2202239126 0.143
< [4,] 1074338664 0.070
< [5,] 2352518951 0.153
---
> [1,] 1760230516 0.114
> [2,] 946417787 0.061
> [3,] 2202223078 0.143
> [4,] 1074332698 0.070
> [5,] 2352528086 0.153
Running ‘geos.R’ [37s/37s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ...13,22c13,22
< [1,] 0.00 0.00 25652.42 440561.04 299772.09 361529.39 419671.11
< [2,] 0.00 0.00 0.00 409428.55 268944.32 332589.77 388544.57
< [3,] 25652.42 0.00 0.00 367555.46 227017.50 290297.11 346667.96
< [4,] 440561.04 409428.55 367555.46 0.00 67226.88 45537.78 0.00
< [5,] 299772.09 268944.32 227017.50 67226.88 0.00 0.00 46527.48
< [6,] 361529.39 332589.77 290297.11 45537.78 0.00 0.00 30213.34
< [7,] 419671.11 388544.57 346667.96 0.00 46527.48 30213.34 0.00
< [8,] 384592.69 354294.05 312350.59 16130.19 11926.78 0.00 0.00
< [9,] 262354.14 231217.46 189310.29 140455.85 0.00 64606.20 119563.76
< [10,] 71139.12 41943.86 0.00 330751.41 190182.42 252372.08 309862.03
---
> [1,] 0.00 0.00 25651.99 440561.48 299772.34 361529.73 419671.66
> [2,] 0.00 0.00 0.00 409429.44 268945.05 332590.52 388545.58
> [3,] 25651.99 0.00 0.00 367556.52 227018.38 290298.04 346669.14
> [4,] 440561.48 409429.44 367556.52 0.00 67226.86 45537.62 0.00
> [5,] 299772.34 268945.05 227018.38 67226.86 0.00 0.00 46527.56
> [6,] 361529.73 332590.52 290298.04 45537.62 0.00 0.00 30213.17
> [7,] 419671.66 388545.58 346669.14 0.00 46527.56 30213.17 0.00
> [8,] 384593.29 354295.06 312351.76 16130.19 11926.86 0.00 0.00
> [9,] 262353.97 231217.73 189310.73 140455.97 0.00 64606.27 119564.00
> [10,] 71138.53 41943.71 0.00 330752.58 190183.42 252373.26 309863.33
24,33c24,33
< [1,] 384592.69 262354.14 71139.12
< [2,] 354294.05 231217.46 41943.86
< [3,] 312350.59 189310.29 0.00
< [4,] 16130.19 140455.85 330751.41
< [5,] 11926.78 0.00 190182.42
< [6,] 0.00 64606.20 252372.08
< [7,] 0.00 119563.76 309862.03
< [8,] 0.00 85533.06 275389.73
< [9,] 85533.06 0.00 152488.90
< [10,] 275389.73 152488.90 0.00
---
> [1,] 384593.29 262353.97 71138.53
> [2,] 354295.06 231217.73 41943.71
> [3,] 312351.76 189310.73 0.00
> [4,] 16130.19 140455.97 330752.58
> [5,] 11926.86 0.00 190183.42
> [6,] 0.00 64606.27 252373.26
> [7,] 0.00 119564.00 309863.33
> [8,] 0.00 85533.33 275391.07
> [9,] 85533.33 0.00 152489.45
> [10,] 275391.07 152489.45 0.00
Running ‘graticule.R’
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘maps.R’
Comparing ‘maps.Rout’ to ‘maps.Rout.save’ ... OK
Running ‘plot.R’ [10s/11s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’
Comparing ‘read.Rout’ to ‘read.Rout.save’ ... OK
Running ‘roundtrip.R’
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘s2.R’
Comparing ‘s2.Rout’ to ‘s2.Rout.save’ ... OK
Running ‘sample.R’
Comparing ‘sample.Rout’ to ‘sample.Rout.save’ ... OK
Running ‘sfc.R’ [15s/15s]
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ...614c614
< Bounding box: xmin: 406261.8 ymin: 48374.95 xmax: 3052888 ymax: 1044157
---
> Bounding box: xmin: 406265 ymin: 48359.7 xmax: 3052877 ymax: 1044143
629,633c629,633
< 1 10 1364 0 19 A 4 #fb80724d MULTIPOLYGON (((1270815 913...
< 2 10 542 3 12 A 4 #fb80724d MULTIPOLYGON (((1340555 959...
< 3 208 3616 6 260 A 5 #80b1d34d MULTIPOLYGON (((1570591 910...
< 4 123 830 2 145 A 10 #bc80bd4d MULTIPOLYGON (((2881208 948...
< 5 1066 1606 3 1197 A 8 #fccde54d MULTIPOLYGON (((2525701 911...
---
> 1 10 1364 0 19 A 4 #fb80724d MULTIPOLYGON (((1270813 913...
> 2 10 542 3 12 A 4 #fb80724d MULTIPOLYGON (((1340553 959...
> 3 208 3616 6 260 A 5 #80b1d34d MULTIPOLYGON (((1570586 910...
> 4 123 830 2 145 A 10 #bc80bd4d MULTIPOLYGON (((2881206 948...
> 5 1066 1606 3 1197 A 8 #fccde54d MULTIPOLYGON (((2525700 911...
635,638c635,638
< 7 115 350 2 139 A 10 #bc80bd4d MULTIPOLYGON (((2881208 948...
< 8 254 594 2 371 A 9 #d9d9d94d MULTIPOLYGON (((2717989 951...
< 9 748 1190 2 844 A 8 #fccde54d MULTIPOLYGON (((2203890 914...
< 10 160 2038 5 176 A 5 #80b1d34d MULTIPOLYGON (((1697623 911...
---
> 7 115 350 2 139 A 10 #bc80bd4d MULTIPOLYGON (((2881206 948...
> 8 254 594 2 371 A 9 #d9d9d94d MULTIPOLYGON (((2717988 951...
> 9 748 1190 2 844 A 8 #fccde54d MULTIPOLYGON (((2203888 914...
> 10 160 2038 5 176 A 5 #80b1d34d MULTIPOLYGON (((1697618 911...
721c721
< Bounding box: xmin: 1216510 ymin: 935867 xmax: 1428880 ymax: 1031510
---
> Bounding box: xmin: 1216510 ymin: 935852 xmax: 1428880 ymax: 1031490
724,728c724,728
< POINT (1264559 935867)
< POINT (1256623 949384)
< POINT (1222665 972639)
< POINT (1333530 968278)
< POINT (1310838 958645)
---
> POINT (1264558 935852)
> POINT (1256623 949369)
> POINT (1222665 972624)
> POINT (1333528 968263)
> POINT (1310837 958630)
738c738
< Bounding box: xmin: -81.6893 ymin: 36.2492 xmax: -80.914 ymax: 36.5726
---
> Bounding box: xmin: -81.6893 ymin: 36.2491 xmax: -80.914 ymax: 36.5726
Running ‘sfg.R’
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘spatstat.R’
Comparing ‘spatstat.Rout’ to ‘spatstat.Rout.save’ ... OK
Running ‘stars.R’
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ...282c282,285
< "nodata_value": 0
---
> "nodata_value": 0,
> "structural_info": {
> "COMPRESSOR": "{ \"blocksize\": 0, \"clevel\": 5, \"cname\": \"lz4\", \"id\": \"blosc\", \"shuffle\": 1 }"
> }
Running ‘testthat.R’ [20s/24s]
Running ‘units.R’
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.0-22
Check: tests
Result: NOTE
Running ‘aggregate.R’ [1s/1s]
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ... OK
Running ‘cast.R’ [1s/1s]
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’ [1s/1s]
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’ [1s/1s]
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’ [1s/1s]
Comparing ‘dplyr.Rout’ to ‘dplyr.Rout.save’ ...125a126
> [1] 4
Running ‘empty.R’ [1s/1s]
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘full.R’ [1s/1s]
Comparing ‘full.Rout’ to ‘full.Rout.save’ ... OK
Running ‘gdal_geom.R’ [1s/1s]
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ... OK
Running ‘geos.R’ [10s/11s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ... OK
Running ‘graticule.R’ [2s/2s]
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’ [1s/1s]
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘maps.R’ [1s/1s]
Comparing ‘maps.Rout’ to ‘maps.Rout.save’ ... OK
Running ‘plot.R’ [4s/4s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’ [1s/1s]
Comparing ‘read.Rout’ to ‘read.Rout.save’ ...187,189c187,254
< Warning message:
< In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
< there is no package called 'RSQLite'
---
> Simple feature collection with 155 features and 13 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 178605 ymin: 329714 xmax: 181390 ymax: 333611
> CRS: NA
> First 3 features:
> ogc_fid cadmium copper lead zinc elev dist om ffreq soil lime
> 1 1 11.7 85 299 1022 7.909 0.00135803 13.6 1 1 1
> 2 2 8.6 81 277 1141 6.983 0.01222430 14.0 1 1 1
> 3 3 6.5 68 199 640 7.800 0.10302900 13.0 1 1 1
> landuse dist.m GEOMETRY
> 1 Ah 50 POINT (181072 333611)
> 2 Ah 30 POINT (181025 333558)
> 3 Ah 150 POINT (181165 333537)
> Simple feature collection with 100 features and 15 fields
> Geometry type: MULTIPOLYGON
> Dimension: XY
> Bounding box: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
> CRS: NA
> First 3 features:
> ogc_fid area perimeter cnty_ cnty_id name fips fipsno cress_id bir74
> 1 1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091
> 2 2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487
> 3 3 0.143 1.630 1828 1828 Surry 37171 37171 86 3188
> sid74 nwbir74 bir79 sid79 nwbir79 GEOMETRY
> 1 1 10 1364 0 19 MULTIPOLYGON (((-81.47276 3...
> 2 0 10 542 3 12 MULTIPOLYGON (((-81.23989 3...
> 3 5 208 3616 6 260 MULTIPOLYGON (((-80.45634 3...
> Integer64 values larger than 9.0072e+15 lost significance after conversion to double;
> use argument int64_as_string = TRUE to import them lossless, as character
> Simple feature collection with 1 feature and 2 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 0 ymin: 1 xmax: 0 ymax: 1
> CRS: NA
> a bigint GEOMETRY
> 1 1 4.611686e+18 POINT (0 1)
> Simple feature collection with 1 feature and 2 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 0 ymin: 1 xmax: 0 ymax: 1
> CRS: NA
> a bigint GEOMETRY
> 1 1 4611686018427387904 POINT (0 1)
> Simple feature collection with 10 features and 2 fields
> Geometry type: LINESTRING
> Dimension: XY
> Bounding box: xmin: 645003 ymin: 4822568 xmax: 748805.6 ymax: 4992001
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Geometry
> 1 1 Unknown LINESTRING (668540.7 485826...
> Simple feature collection with 8101 features and 6 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 319224 ymin: 3934674 xmax: 1308585 ymax: 5214373
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Peoples LocalCounc County Region Geometry
> 1 1 Brozolo 435 1 0 0 POINT (427002.8 4996361)
> Simple feature collection with 10 features and 2 fields
> Geometry type: MULTIPOLYGON
> Dimension: XY
> Bounding box: xmin: 378359.8 ymin: 4198234 xmax: 1211486 ymax: 5036803
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Geometry
> 1 1 VENETO MULTIPOLYGON (((752912.3 50...
Running ‘roundtrip.R’ [1s/1s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘s2.R’ [1s/1s]
Comparing ‘s2.Rout’ to ‘s2.Rout.save’ ... OK
Running ‘sample.R’ [0s/1s]
Comparing ‘sample.Rout’ to ‘sample.Rout.save’ ... OK
Running ‘sfc.R’ [6s/6s]
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ... OK
Running ‘sfg.R’ [0s/0s]
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘spatstat.R’ [2s/2s]
Comparing ‘spatstat.Rout’ to ‘spatstat.Rout.save’ ... OK
Running ‘stars.R’ [2s/2s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ...282c282,285
< "nodata_value": 0
---
> "nodata_value": 0,
> "structural_info": {
> "COMPRESSOR": "{ \"blocksize\": 0, \"clevel\": 5, \"cname\": \"lz4\", \"id\": \"blosc\", \"shuffle\": 1 }"
> }
Running ‘testthat.R’ [8s/8s]
Running ‘units.R’ [1s/1s]
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’ [0s/0s]
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Flavor: r-release-macos-arm64
Version: 1.0-22
Check: tests
Result: NOTE
Running ‘aggregate.R’ [1s/1s]
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ... OK
Running ‘cast.R’ [2s/2s]
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’ [1s/1s]
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’ [1s/2s]
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’ [3s/5s]
Comparing ‘dplyr.Rout’ to ‘dplyr.Rout.save’ ... OK
Running ‘empty.R’ [1s/2s]
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘full.R’ [1s/2s]
Comparing ‘full.Rout’ to ‘full.Rout.save’ ... OK
Running ‘gdal_geom.R’ [2s/3s]
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ... OK
Running ‘geos.R’ [21s/67s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ... OK
Running ‘graticule.R’ [3s/6s]
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’ [1s/2s]
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘maps.R’ [2s/3s]
Comparing ‘maps.Rout’ to ‘maps.Rout.save’ ... OK
Running ‘plot.R’ [8s/15s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’ [2s/3s]
Comparing ‘read.Rout’ to ‘read.Rout.save’ ...187,189c187,254
< Warning message:
< In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
< there is no package called 'RSQLite'
---
> Simple feature collection with 155 features and 13 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 178605 ymin: 329714 xmax: 181390 ymax: 333611
> CRS: NA
> First 3 features:
> ogc_fid cadmium copper lead zinc elev dist om ffreq soil lime
> 1 1 11.7 85 299 1022 7.909 0.00135803 13.6 1 1 1
> 2 2 8.6 81 277 1141 6.983 0.01222430 14.0 1 1 1
> 3 3 6.5 68 199 640 7.800 0.10302900 13.0 1 1 1
> landuse dist.m GEOMETRY
> 1 Ah 50 POINT (181072 333611)
> 2 Ah 30 POINT (181025 333558)
> 3 Ah 150 POINT (181165 333537)
> Simple feature collection with 100 features and 15 fields
> Geometry type: MULTIPOLYGON
> Dimension: XY
> Bounding box: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
> CRS: NA
> First 3 features:
> ogc_fid area perimeter cnty_ cnty_id name fips fipsno cress_id bir74
> 1 1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091
> 2 2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487
> 3 3 0.143 1.630 1828 1828 Surry 37171 37171 86 3188
> sid74 nwbir74 bir79 sid79 nwbir79 GEOMETRY
> 1 1 10 1364 0 19 MULTIPOLYGON (((-81.47276 3...
> 2 0 10 542 3 12 MULTIPOLYGON (((-81.23989 3...
> 3 5 208 3616 6 260 MULTIPOLYGON (((-80.45634 3...
> Integer64 values larger than 9.0072e+15 lost significance after conversion to double;
> use argument int64_as_string = TRUE to import them lossless, as character
> Simple feature collection with 1 feature and 2 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 0 ymin: 1 xmax: 0 ymax: 1
> CRS: NA
> a bigint GEOMETRY
> 1 1 4.611686e+18 POINT (0 1)
> Simple feature collection with 1 feature and 2 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 0 ymin: 1 xmax: 0 ymax: 1
> CRS: NA
> a bigint GEOMETRY
> 1 1 4611686018427387904 POINT (0 1)
> Simple feature collection with 10 features and 2 fields
> Geometry type: LINESTRING
> Dimension: XY
> Bounding box: xmin: 645003 ymin: 4822568 xmax: 748805.6 ymax: 4992001
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Geometry
> 1 1 Unknown LINESTRING (668540.7 485826...
> Simple feature collection with 8101 features and 6 fields
> Geometry type: POINT
> Dimension: XY
> Bounding box: xmin: 319224 ymin: 3934674 xmax: 1308585 ymax: 5214373
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Peoples LocalCounc County Region Geometry
> 1 1 Brozolo 435 1 0 0 POINT (427002.8 4996361)
> Simple feature collection with 10 features and 2 fields
> Geometry type: MULTIPOLYGON
> Dimension: XY
> Bounding box: xmin: 378359.8 ymin: 4198234 xmax: 1211486 ymax: 5036803
> Projected CRS: WGS 84 / UTM zone 32N
> First 1 features:
> PK_UID Name Geometry
> 1 1 VENETO MULTIPOLYGON (((752912.3 50...
Running ‘roundtrip.R’ [2s/3s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘s2.R’ [2s/3s]
Comparing ‘s2.Rout’ to ‘s2.Rout.save’ ... OK
Running ‘sample.R’ [1s/1s]
Comparing ‘sample.Rout’ to ‘sample.Rout.save’ ... OK
Running ‘sfc.R’ [11s/18s]
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ... OK
Running ‘sfg.R’ [1s/1s]
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘spatstat.R’ [3s/5s]
Comparing ‘spatstat.Rout’ to ‘spatstat.Rout.save’ ... OK
Running ‘stars.R’ [3s/5s]
Comparing ‘stars.Rout’ to ‘stars.Rout.save’ ...282c282,285
< "nodata_value": 0
---
> "nodata_value": 0,
> "structural_info": {
> "COMPRESSOR": "{ \"blocksize\": 0, \"clevel\": 5, \"cname\": \"lz4\", \"id\": \"blosc\", \"shuffle\": 1 }"
> }
Running ‘testthat.R’ [15s/24s]
Running ‘units.R’ [1s/1s]
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’ [1s/1s]
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Flavor: r-release-macos-x86_64
Version: 1.0-22
Check: installed package size
Result: NOTE
installed size is 81.8Mb
sub-directories of 1Mb or more:
doc 12.6Mb
libs 64.5Mb
sqlite 1.5Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.0-22
Check: tests
Result: ERROR
Running 'aggregate.R' [2s]
Comparing 'aggregate.Rout' to 'aggregate.Rout.save' ... OK
Running 'cast.R' [2s]
Comparing 'cast.Rout' to 'cast.Rout.save' ... OK
Running 'crs.R' [2s]
Comparing 'crs.Rout' to 'crs.Rout.save' ... OK
Running 'dist.R' [2s]
Comparing 'dist.Rout' to 'dist.Rout.save' ... OK
Running 'dplyr.R' [5s]
Comparing 'dplyr.Rout' to 'dplyr.Rout.save' ... OK
Running 'empty.R' [1s]
Comparing 'empty.Rout' to 'empty.Rout.save' ... OK
Running 'full.R' [2s]
Comparing 'full.Rout' to 'full.Rout.save' ... OK
Running 'gdal_geom.R' [2s]
Comparing 'gdal_geom.Rout' to 'gdal_geom.Rout.save' ... OK
Running 'geos.R' [38s]
Comparing 'geos.Rout' to 'geos.Rout.save' ... OK
Running 'graticule.R' [5s]
Comparing 'graticule.Rout' to 'graticule.Rout.save' ... OK
Running 'grid.R' [2s]
Comparing 'grid.Rout' to 'grid.Rout.save' ... OK
Running 'maps.R' [3s]
Comparing 'maps.Rout' to 'maps.Rout.save' ... OK
Running 'plot.R' [12s]
Comparing 'plot.Rout' to 'plot.Rout.save' ... OK
Running 'read.R' [4s]
Comparing 'read.Rout' to 'read.Rout.save' ... OK
Running 'roundtrip.R' [3s]
Comparing 'roundtrip.Rout' to 'roundtrip.Rout.save' ... OK
Running 's2.R' [3s]
Comparing 's2.Rout' to 's2.Rout.save' ... OK
Running 'sample.R' [1s]
Comparing 'sample.Rout' to 'sample.Rout.save' ... OK
Running 'sfc.R' [17s]
Comparing 'sfc.Rout' to 'sfc.Rout.save' ... OK
Running 'sfg.R' [1s]
Comparing 'sfg.Rout' to 'sfg.Rout.save' ... OK
Running 'spatstat.R' [6s]
Comparing 'spatstat.Rout' to 'spatstat.Rout.save' ... OK
Running 'stars.R' [6s]
Running 'testthat.R' [36s]
Running 'units.R' [1s]
Comparing 'units.Rout' to 'units.Rout.save' ... OK
Running 'wkb.R' [2s]
Comparing 'wkb.Rout' to 'wkb.Rout.save' ... OK
Running the tests in 'tests/stars.R' failed.
Complete output:
> suppressPackageStartupMessages(library(sf))
>
> tif = system.file("tif/geomatrix.tif", package = "sf")
>
> gdal_metadata(tif)
[1] "AREA_OR_POINT=Point"
> gdal_metadata(tif, NA_character_)
[1] "IMAGE_STRUCTURE" "DERIVED_SUBDATASETS" ""
> try(gdal_metadata(tif, "wrongDomain"))
Error in gdal_metadata(tif, "wrongDomain") :
domain_item[1] not found in available metadata domains
> gdal_metadata(tif, c("IMAGE_STRUCTURE"))
$INTERLEAVE
[1] "BAND"
attr(,"class")
[1] "gdal_metadata"
> try(length(gdal_metadata(tif, c("DERIVED_SUBDATASETS")))) # fails on Fedora 26
[1] 2
>
> if (require(stars, quietly = TRUE)) {
+ tif = system.file("tif/geomatrix.tif", package = "sf")
+ r = read_stars(tif)
+ d = (st_dimensions(r))
+ gt = c(1841001.75, 1.5, -5, 1144003.25, -5, -1.5)
+ x1 = st_as_sfc(d, as_points = TRUE, use_cpp = TRUE, geotransform = gt)
+ x2 = st_as_sfc(d, as_points = TRUE, use_cpp = FALSE, geotransform = gt)
+ print(identical(x1, x2))
+ y1 = st_as_sfc(d, as_points = FALSE, use_cpp = TRUE, geotransform = gt)
+ y2 = st_as_sfc(d, as_points = FALSE, use_cpp = FALSE, geotransform = gt)
+ print(identical(y1, y2))
+
+ # rectilinear grid:
+ m = matrix(1:20, nrow = 5, ncol = 4)
+ x = c(0,0.5,1,2,4,5)
+ y = c(0.3,0.5,1,2,2.2)
+ r = st_as_stars(list(m = m), dimensions = st_dimensions(x = x, y = y, .raster = c("x", "y")))
+ print(st_as_sfc(st_dimensions(r), as_points = TRUE))
+ print(st_as_sfc(st_dimensions(r), as_points = FALSE))
+
+ # curvilinear grid:
+ lon = st_as_stars(matrix(1:5, 4, 5, byrow = TRUE))
+ lat = st_as_stars(matrix(1:4, 4, 5))
+ ll = c(X1 = lon, X2 = lat)
+ curv = st_as_stars(st_as_stars(t(m)), curvilinear = setNames(ll, c("X1", "X2")))
+ print(st_as_sfc(st_dimensions(curv), as_points = TRUE))
+ print(st_as_sfc(st_dimensions(curv), as_points = FALSE))
+
+ demo(nc, echo = FALSE, ask = FALSE)
+ print(x <- st_rasterize(nc)) # default grid:
+ print(p <- st_as_sf(x, as_points = FALSE)) # polygonize: follow raster boundaries
+ print(p <- st_as_sf(x, as_points = FALSE, use_integer = TRUE)) # polygonize integers: follow raster boundaries
+ print(try(p <- st_as_sf(x, as_points = TRUE))) # polygonize: contour, requies GDAL >= 2.4.0
+ if (utils::packageVersion("stars") >= "0.2-1") {
+ write_stars(read_stars(tif), tempfile(fileext = ".tif"))
+ write_stars(read_stars(tif, proxy = TRUE), tempfile(fileext = ".tif"))
+ write_stars(read_stars(tif, proxy = TRUE), tempfile(fileext = ".tif"), chunk_size = c(200,200))
+ na.tif = read_stars(system.file("tif/na.tif", package = "stars"))
+ write_stars(na.tif, "na.tif")
+ write_stars(na.tif, "na.tif", NA_value = -999)
+ na.tif = read_stars(system.file("tif/na.tif", package = "stars"), NA_value = -999)
+ write_stars(na.tif, "na.tif")
+ write_stars(na.tif, "na.tif", NA_value = -999)
+ na.tif = read_stars(system.file("tif/na.tif", package = "stars"), NA_value = -999, proxy = TRUE)
+ write_stars(na.tif, "na.tif")
+ write_stars(na.tif, "na.tif", NA_value = -999)
+ }
+ # https://github.com/mtennekes/tmap/issues/368
+ if (utils::packageVersion("stars") > "0.4-0") {
+ lc = system.file('tif/lc.tif', package = 'stars')
+ if (lc != "") {
+ r = read_stars(lc, RAT = "Land Cover Class")
+ r <- droplevels(r)
+ }
+ }
+ }
[1] TRUE
[1] TRUE
Geometry set for 20 features
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 0.25 ymin: 0.4 xmax: 4.5 ymax: 2.1
CRS: NA
First 5 geometries:
POINT (0.25 0.4)
POINT (0.75 0.4)
POINT (1.5 0.4)
POINT (3 0.4)
POINT (4.5 0.4)
Geometry set for 20 features
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 0 ymin: 0.3 xmax: 5 ymax: 2.2
CRS: NA
First 5 geometries:
POLYGON ((0 0.3, 0.5 0.3, 0.5 0.5, 0 0.5, 0 0.3))
POLYGON ((0.5 0.3, 1 0.3, 1 0.5, 0.5 0.5, 0.5 0...
POLYGON ((1 0.3, 2 0.3, 2 0.5, 1 0.5, 1 0.3))
POLYGON ((2 0.3, 4 0.3, 4 0.5, 2 0.5, 2 0.3))
POLYGON ((4 0.3, 5 0.3, 5 0.5, 4 0.5, 4 0.3))
Geometry set for 20 features
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 1 ymin: 1 xmax: 5 ymax: 4
Geodetic CRS: WGS 84 (CRS84)
First 5 geometries:
POINT (1 1)
POINT (1 2)
POINT (1 3)
POINT (1 4)
POINT (2 1)
Geometry set for 20 features
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 0.5 ymin: 0.5 xmax: 5.5 ymax: 4.5
Geodetic CRS: WGS 84 (CRS84)
First 5 geometries:
POLYGON ((0.5 0.5, 0.5 1.5, 1.5 1.5, 1.5 0.5, 0...
POLYGON ((0.5 1.5, 0.5 2.5, 1.5 2.5, 1.5 1.5, 0...
POLYGON ((0.5 2.5, 0.5 3.5, 1.5 3.5, 1.5 2.5, 0...
POLYGON ((0.5 3.5, 0.5 4.5, 1.5 4.5, 1.5 3.5, 0...
POLYGON ((1.5 0.5, 1.5 1.5, 2.5 1.5, 2.5 0.5, 1...
stars object with 2 dimensions and 12 attributes
attribute(s):
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
AREA 0.042 0.108 0.142 1.451932e-01 0.181 0.241 30904
PERIMETER 0.999 1.461 1.716 1.786110e+00 2.004 3.640 30904
CNTY_ 1825.000 1907.000 1989.000 1.998403e+03 2085.000 2241.000 30904
CNTY_ID 1825.000 1907.000 1989.000 1.998403e+03 2085.000 2241.000 30904
FIPSNO 37001.000 37049.000 37101.000 3.710042e+04 37153.000 37199.000 30904
CRESS_ID 1.000 25.000 51.000 5.071206e+01 77.000 100.000 30904
BIR74 248.000 1323.000 2648.000 3.791637e+03 4139.000 21588.000 30904
SID74 0.000 3.000 5.000 7.891985e+00 10.000 44.000 30904
NWBIR74 1.000 297.000 844.000 1.246210e+03 1396.000 8027.000 30904
BIR79 319.000 1606.000 3108.000 4.852046e+03 5400.000 30757.000 30904
SID79 0.000 3.000 6.000 9.584098e+00 13.000 57.000 30904
NWBIR79 3.000 360.000 1058.000 1.604642e+03 1524.000 11631.000 30904
dimension(s):
from to offset delta refsys point x/y
x 1 461 -84.32 0.01925 NAD27 FALSE [x]
y 1 141 36.59 -0.01925 NAD27 FALSE [y]
Simple feature collection with 34097 features and 12 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: -84.32385 ymin: 33.87563 xmax: -75.45034 ymax: 36.58965
Geodetic CRS: NAD27
First 10 features:
AREA PERIMETER CNTY_ CNTY_ID FIPSNO CRESS_ID BIR74 SID74 NWBIR74 BIR79
1 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
2 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
3 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
4 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
5 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
6 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
7 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
8 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
9 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
10 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
SID79 NWBIR79 geometry
1 0 19 POLYGON ((-81.66757 36.5896...
2 0 19 POLYGON ((-81.64833 36.5896...
3 0 19 POLYGON ((-81.62908 36.5896...
4 0 19 POLYGON ((-81.60983 36.5896...
5 0 19 POLYGON ((-81.59058 36.5896...
6 0 19 POLYGON ((-81.57133 36.5896...
7 0 19 POLYGON ((-81.55208 36.5896...
8 0 19 POLYGON ((-81.53283 36.5896...
9 0 19 POLYGON ((-81.51359 36.5896...
10 0 19 POLYGON ((-81.49434 36.5896...
Simple feature collection with 34097 features and 12 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: -84.32385 ymin: 33.87563 xmax: -75.45034 ymax: 36.58965
Geodetic CRS: NAD27
First 10 features:
AREA PERIMETER CNTY_ CNTY_ID FIPSNO CRESS_ID BIR74 SID74 NWBIR74 BIR79
1 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
2 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
3 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
4 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
5 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
6 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
7 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
8 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
9 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
10 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
SID79 NWBIR79 geometry
1 0 19 POLYGON ((-81.66757 36.5896...
2 0 19 POLYGON ((-81.64833 36.5896...
3 0 19 POLYGON ((-81.62908 36.5896...
4 0 19 POLYGON ((-81.60983 36.5896...
5 0 19 POLYGON ((-81.59058 36.5896...
6 0 19 POLYGON ((-81.57133 36.5896...
7 0 19 POLYGON ((-81.55208 36.5896...
8 0 19 POLYGON ((-81.53283 36.5896...
9 0 19 POLYGON ((-81.51359 36.5896...
10 0 19 POLYGON ((-81.49434 36.5896...
Simple feature collection with 34097 features and 12 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: -84.31423 ymin: 33.88525 xmax: -75.45997 ymax: 36.58003
Geodetic CRS: NAD27
First 10 features:
AREA PERIMETER CNTY_ CNTY_ID FIPSNO CRESS_ID BIR74 SID74 NWBIR74 BIR79
1 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
2 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
3 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
4 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
5 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
6 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
7 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
8 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
9 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
10 0.114 1.442 1825 1825 37009 5 1091 1 10 1364
SID79 NWBIR79 geometry
1 0 19 POINT (-81.65795 36.58003)
2 0 19 POINT (-81.6387 36.58003)
3 0 19 POINT (-81.61945 36.58003)
4 0 19 POINT (-81.6002 36.58003)
5 0 19 POINT (-81.58096 36.58003)
6 0 19 POINT (-81.56171 36.58003)
7 0 19 POINT (-81.54246 36.58003)
8 0 19 POINT (-81.52321 36.58003)
9 0 19 POINT (-81.50396 36.58003)
10 0 19 POINT (-81.48471 36.58003)
>
> r = gdal_read(tif)
> gt = c(0,1,0,0,0,1)
> gdal_inv_geotransform(gt)
[1] 0 1 0 0 0 1
> rc = expand.grid(x=1:3, y = 1:3)
> #(xy = xy_from_colrow(rc, gt))
> #xy_from_colrow(xy, gt, inverse = TRUE)
> crs <- gdal_crs(tif)
>
> try(gdal_metadata("foo"))
[1] NA
> gdal_metadata(tif)
[1] "AREA_OR_POINT=Point"
>
> if (require(stars, quietly = TRUE)) {
+ p = normalizePath(system.file("nc/ones.zarr.zip", package = "sf"))
+ z = paste0('ZARR:/vsizip/"', p, '"/ones.zarr')
+ gdal_utils("mdiminfo", z)
+ cat("\n")
+ print(read_stars(z, normalize_path = FALSE))
+ print(read_mdim(z, normalize_path = FALSE))
+ }
failed to open ZARR:/vsizip/"D:\RCompile\CRANpkg\lib\4.4\sf\nc\ones.zarr.zip"/ones.zarr
Error: Error opening data source
In addition: Warning message:
In CPL_gdalmdiminfo(source, options, oo, config_options) :
GDAL Error 1: Decompressor blosc not handled
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: NOTE: 3, OK: 10
Version: 2.2-0
Check: installed package size
Result: NOTE
installed size is 9.2Mb
sub-directories of 1Mb or more:
doc 7.6Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: NOTE: 13
Version: 0.6-8
Check: DESCRIPTION meta-information
Result: NOTE
Missing dependency on R >= 4.2.0 because package code uses the pipe
placeholder syntax added in R 4.2.0.
File(s) using such syntax:
‘prcomp.Rd’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64
Version: 0.6-8
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘starsdata’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.6-8
Check: installed package size
Result: NOTE
installed size is 6.9Mb
sub-directories of 1Mb or more:
doc 2.9Mb
nc 1.7Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: NOTE: 7, OK: 6
Version: 0.2-9
Check: for unstated dependencies in ‘demo’
Result: NOTE
'::' or ':::' import not declared from: ‘devtools’
'library' or 'require' calls not declared from:
‘XML’ ‘devtools’ ‘jsonlite’ ‘ks’ ‘maps’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 0.2-9
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘taxidata’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: NOTE: 2, OK: 11
Version: 0.2-1
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Edzer Pebesma <edzer.pebesma@uni-muenster.de>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Ernst",
family = "Glatzer",
role = "aut",
email = "ernst.glatzer@wu-wien.ac.at"),
person(given = "Edzer",
family = "Pebesma",
role = "cre",
email = "edzer.pebesma@uni-muenster.de"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc