Running ‘allier.R’ [2s/2s]
  Comparing ‘allier.Rout’ to ‘allier.Rout.save’ ... OK
  Running ‘blockkr.R’ [2s/2s]
  Comparing ‘blockkr.Rout’ to ‘blockkr.Rout.save’ ... OK
  Running ‘covtable.R’ [2s/2s]
  Comparing ‘covtable.Rout’ to ‘covtable.Rout.save’ ... OK
  Running ‘cv.R’ [3s/3s]
  Comparing ‘cv.Rout’ to ‘cv.Rout.save’ ... OK
  Running ‘cv3d.R’ [2s/2s]
  Comparing ‘cv3d.Rout’ to ‘cv3d.Rout.save’ ... OK
  Running ‘fit.R’ [2s/2s]
  Comparing ‘fit.Rout’ to ‘fit.Rout.save’ ... OK
  Running ‘krige0.R’ [5s/5s]
  Comparing ‘krige0.Rout’ to ‘krige0.Rout.save’ ... OK
  Running ‘line.R’ [3s/3s]
  Comparing ‘line.Rout’ to ‘line.Rout.save’ ... OK
  Running ‘merge.R’ [2s/2s]
  Comparing ‘merge.Rout’ to ‘merge.Rout.save’ ... OK
  Running ‘na.action.R’ [2s/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/1s]
  Comparing ‘sim.Rout’ to ‘sim.Rout.save’ ... OK
  Running ‘unproj.R’ [3s/3s]
  Comparing ‘unproj.Rout’ to ‘unproj.Rout.save’ ...5c5
< rgdal: version: 1.2-16, (SVN revision 701)
---
> rgdal: version: 1.2-5, (SVN revision 648)
7,10c7,9
<  Loaded GDAL runtime: GDAL 2.2.2, released 2017/09/15
<  Path to GDAL shared files: /usr/share/gdal/2.2
<  GDAL binary built with GEOS: TRUE 
<  Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
---
>  Loaded GDAL runtime: GDAL 2.1.0, released 2016/04/25
>  Path to GDAL shared files: /usr/share/gdal/2.1
>  Loaded PROJ.4 runtime: Rel. 4.9.2, 08 September 2015, [PJ_VERSION: 492]
12c11
<  Linking to sp version: 1.2-5 
---
>  Linking to sp version: 1.2-3 
82c81
< Spam version 2.1-1 (2017-07-02) is loaded.
---
> Spam version 1.4-0 (2016-08-29) is loaded.
  Running ‘variogram.R’ [3s/3s]
  Comparing ‘variogram.Rout’ to ‘variogram.Rout.save’ ... OK
  Running ‘vdist.R’ [2s/2s]
  Comparing ‘vdist.Rout’ to ‘vdist.Rout.save’ ... OK
  Running ‘windst.R’ [2s/2s]
Running the tests in ‘tests/windst.R’ failed.
Complete output:
  > library(sp)
  > library(spacetime)
  > library(gstat)
  > 
  > 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(rgdal) && require(maps)) {
  + proj4string(pts) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
  + utm29 = CRS("+proj=utm +zone=29 +datum=WGS84 +ellps=WGS84")
  + pts = spTransform(pts, utm29)
  + # note the t() in:
  + w = STFDF(pts, wind$time, data.frame(values = as.vector(t(velocities))))
  + 
  + library(mapdata)
  + library(maptools)
  + m = map2SpatialLines(
  +     map("worldHires", xlim = c(-11,-5.4), ylim = c(51,55.5), plot=F))
  + proj4string(m) = "+proj=longlat +datum=WGS84 +ellps=WGS84"
  + m = spTransform(m, utm29)
  + 
  + # setup grid
  + grd = SpatialPixels(SpatialPoints(makegrid(m, n = 300)),
  + 	proj4string = proj4string(m))
  + # grd$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)
  + }
  Loading required package: rgdal
  rgdal: version: 1.2-16, (SVN revision 701)
   Geospatial Data Abstraction Library extensions to R successfully loaded
   Loaded GDAL runtime: GDAL 2.2.2, released 2017/09/15
   Path to GDAL shared files: /usr/share/gdal/2.2
   GDAL binary built with GEOS: TRUE 
   Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
   Path to PROJ.4 shared files: (autodetected)
   Linking to sp version: 1.2-5 
  Loading required package: maps
  Checking rgeos availability: TRUE
  
   *** caught segfault ***
  address 0x2, cause 'memory not mapped'
  
  Traceback:
   1: .External("mergeXts", all = all[1:2], fill = fill, setclass = setclass,     symnames = symnames, suffixes = suffixes, retside = retside,     env = new.env(), tzone = tzone, ..., PACKAGE = "xts")
   2: merge.xts(..., all = all, fill = fill, suffixes = suffixes)
   3: cbind(deparse.level, ...)
   4: cbind(x@time, 1:nrow(x@time))
   5: w[, "1961-04"]
   6: w[, "1961-04"]
  An irrecoverable exception occurred. R is aborting now ...
  Segmentation fault