[R-sig-Geo] spplot question in sp_0.9-98

Mauricio Zambrano-Bigiarini hzambran.newsgroups at gmail.com
Tue Apr 3 20:37:29 CEST 2012 

Dear List,

I just notice an strange behaviour of the 'spplot' function, and I
would like your help to figure out if it is something related to my
system or is something related to the 'spplot' function.

Below goes a reproducible example taken from
http://r-spatial.sourceforge.net/gallery/ :


# fig06.R multi-panel plot, scales + north arrow only in last plot.

----------------------START-----------------------------------

library(sp)
library(lattice) # required for trellis.par.set():
trellis.par.set(sp.theme()) # sets color ramp to bpy.colors()

data(meuse)
coordinates(meuse)=~x+y
data(meuse.riv)
meuse.sr = SpatialPolygons(list(Polygons(list(Polygon(meuse.riv)),"meuse.riv")))
rv = list("sp.polygons", meuse.sr, fill = "lightblue")

## multi-panel plot, scales + north arrow only in last plot:
## using the "which" argument in a layout component
## (if which=4 was set as list component of sp.layout, the river
## would as well be drawn only in that (last) panel)
scale = list("SpatialPolygonsRescale", layout.scale.bar(),
offset = c(180500,329800), scale = 500, fill=c("transparent","black"),
which = 4)
text1 = list("sp.text", c(180500,329900), "0", cex = .5, which = 4)
text2 = list("sp.text", c(181000,329900), "500 m", cex = .5, which = 4)
arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
offset = c(181300,329800),
scale = 400, which = 4)
cuts = c(.2,.5,1,2,5,10,20,50,100,200,500,1000,2000)
spplot(meuse, c("cadmium", "copper", "lead", "zinc"), do.log = TRUE,
key.space = "right", as.table = TRUE,
sp.layout=list(rv, scale, text1, text2, arrow),
main = "Heavy metals (top soil), ppm", cex = .7, cuts = cuts)

----------------------END-----------------------------------


After the last spplot command, I only get one point in the upper left
figure, which is very different from the Figure 6 shown in
http://r-spatial.sourceforge.net/gallery/

In addition, I get the following output after the spplot command:

[1] "#A714EBFF" "#6500FFFF" "#6500FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF"
  [7] "#2400FFFF" "#2400FFFF" "#2400FFFF" "#0000DAFF" "#0000DAFF" "#0000DAFF"
 [13] "#A714EBFF" "#2400FFFF" "#0000DAFF" "#6500FFFF" "#6500FFFF" "#6500FFFF"
 [19] "#6500FFFF" "#A714EBFF" "#6500FFFF" "#2400FFFF" "#2400FFFF" "#0000DAFF"
 [25] "#0000DAFF" "#0000DAFF" "#0000DAFF" "#0000DAFF" "#0000DAFF" "#0000DAFF"
 [31] "#0000DAFF" "#0000DAFF" "#2400FFFF" "#0000DAFF" "#0000DAFF" "#2400FFFF"
 [37] "#6500FFFF" "#6500FFFF" "#6500FFFF" "#A714EBFF" "#2400FFFF" "#0000DAFF"
 [43] "#0000DAFF" "#0000DAFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#0000DAFF"
 [49] "#0000DAFF" "#2400FFFF" "#0000DAFF" "#6500FFFF" "#A714EBFF" "#A714EBFF"
 [55] "#6500FFFF" "#6500FFFF" "#2400FFFF" "#2400FFFF" "#A714EBFF" "#6500FFFF"
 [61] "#6500FFFF" "#6500FFFF" "#6500FFFF" "#6500FFFF" "#6500FFFF" "#6500FFFF"
 [67] "#6500FFFF" "#000086FF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF"
 [73] "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF"
 [79] "#6500FFFF" "#6500FFFF" "#A714EBFF" "#A714EBFF" "#6500FFFF" "#2400FFFF"
 [85] "#0000DAFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#0000DAFF"
 [91] "#0000DAFF" "#2400FFFF" "#2400FFFF" "#000086FF" "#000086FF" "#000033FF"
 [97] "#000086FF" "#000033FF" "#000033FF" "#000033FF" "#000086FF" "#000033FF"
[103] "#000033FF" "#000033FF" "#000033FF" "#000033FF" "#000033FF" "#000033FF"
[109] "#000033FF" "#000033FF" "#000033FF" "#000033FF" "#000033FF" "#000033FF"
[115] "#000033FF" "#000033FF" "#000033FF" "#2400FFFF" "#000033FF" "#000033FF"
[121] "#000033FF" "#000033FF" "#0000DAFF" "#2400FFFF" "#000033FF" "#000033FF"
[127] "#000033FF" "#000033FF" "#000033FF" "#0000DAFF" "#000086FF" "#0000DAFF"
[133] "#000033FF" "#000033FF" "#000086FF" "#000086FF" "#000086FF" "#0000DAFF"
[139] "#0000DAFF" "#0000DAFF" "#0000DAFF" "#000086FF" "#000086FF" "#2400FFFF"
[145] "#2400FFFF" "#2400FFFF" "#2400FFFF" "#2400FFFF" "#0000DAFF" "#0000DAFF"
[151] "#000086FF" "#2400FFFF" "#2400FFFF" "#000086FF" "#2400FFFF" "#FF6798FF"
[157] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#FF6798FF" "#E83EC1FF"
[163] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF"
[169] "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[175] "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[181] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[187] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[193] "#FF6798FF" "#FF6798FF" "#FF916EFF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[199] "#E83EC1FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[205] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FF916EFF" "#FF916EFF" "#FF916EFF"
[211] "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[217] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[223] "#E83EC1FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#E83EC1FF"
[229] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF"
[235] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF"
[241] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[247] "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[253] "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[259] "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#A714EBFF" "#E83EC1FF" "#E83EC1FF"
[265] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[271] "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF"
[277] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#A714EBFF"
[283] "#A714EBFF" "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#E83EC1FF" "#A714EBFF"
[289] "#A714EBFF" "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#E83EC1FF" "#E83EC1FF"
[295] "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#A714EBFF" "#E83EC1FF" "#E83EC1FF"
[301] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#A714EBFF" "#A714EBFF"
[307] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FFBB44FF" "#FFBB44FF"
[313] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF"
[319] "#FF916EFF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FFBB44FF" "#FF916EFF"
[325] "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF"
[331] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[337] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[343] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF916EFF" "#FFBB44FF"
[349] "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#E83EC1FF" "#FF6798FF" "#FF6798FF"
[355] "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FF916EFF"
[361] "#FF6798FF" "#FF916EFF" "#FFBB44FF" "#FFE51AFF" "#FFBB44FF" "#FFBB44FF"
[367] "#FF916EFF" "#FFBB44FF" "#FFE51AFF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF"
[373] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#E83EC1FF"
[379] "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF"
[385] "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF"
[391] "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FF6798FF" "#FF916EFF"
[397] "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF"
[403] "#FFBB44FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[409] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#FF6798FF" "#E83EC1FF"
[415] "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#FF6798FF"
[421] "#FF6798FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[427] "#FF6798FF" "#FFBB44FF" "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF6798FF"
[433] "#FFBB44FF" "#FFBB44FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#E83EC1FF"
[439] "#FF916EFF" "#FF916EFF" "#E83EC1FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF"
[445] "#E83EC1FF" "#E83EC1FF" "#E83EC1FF" "#FF6798FF" "#FF916EFF" "#FF6798FF"
[451] "#FF6798FF" "#FF6798FF" "#FF6798FF" "#FF916EFF" "#FF916EFF" "#FF916EFF"
[457] "#FF916EFF" "#FFBB44FF" "#FF6798FF" "#FF6798FF" "#E83EC1FF" "#FF916EFF"
[463] "#FF916EFF" "#FF6798FF" "#FF916EFF" "#FFFF60FF" "#FFFF60FF" "#FFE51AFF"
[469] "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF"
[475] "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFFF60FF" "#FFE51AFF" "#FFBB44FF"
[481] "#FFFF60FF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFFF60FF" "#FFE51AFF"
[487] "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FFBB44FF"
[493] "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FFBB44FF"
[499] "#FF916EFF" "#FFBB44FF" "#FFBB44FF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF"
[505] "#FFFF60FF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFE51AFF"
[511] "#FFE51AFF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF"
[517] "#FFE51AFF" "#FFFF60FF" "#FFFF60FF" "#FFFF60FF" "#FFE51AFF" "#FFBB44FF"
[523] "#FFE51AFF" "#FFFF60FF" "#FFFF60FF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF"
[529] "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFFF60FF" "#FF916EFF" "#FFE51AFF"
[535] "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFE51AFF"
[541] "#FFE51AFF" "#FFE51AFF" "#FFE51AFF" "#FFFF60FF" "#FFFF60FF" "#FFFF60FF"
[547] "#FFFF60FF" "#FFE51AFF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFE51AFF"
[553] "#FFE51AFF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FFE51AFF" "#FFE51AFF"
[559] "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FF916EFF"
[565] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FF916EFF" "#FF916EFF"
[571] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF"
[577] "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF"
[583] "#FFE51AFF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFE51AFF"
[589] "#FFE51AFF" "#FFBB44FF" "#FF916EFF" "#FF916EFF" "#FF916EFF" "#FFBB44FF"
[595] "#FFBB44FF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#FF916EFF"
[601] "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF"
[607] "#FF916EFF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF" "#FFE51AFF" "#FFE51AFF"
[613] "#FFE51AFF" "#FFBB44FF" "#FFBB44FF" "#FF916EFF" "#FFBB44FF" "#FFBB44FF"
[619] "#FF916EFF" "#FFBB44FF"

-------------------

sessionInfo()
R version 2.14.1 (2011-12-22)
Platform: x86_64-redhat-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_GB.utf8       LC_NUMERIC=C
 [3] LC_TIME=en_GB.utf8        LC_COLLATE=en_GB.utf8
 [5] LC_MONETARY=en_GB.utf8    LC_MESSAGES=en_GB.utf8
 [7] LC_PAPER=C                LC_NAME=C
 [9] LC_ADDRESS=C              LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_GB.utf8 LC_IDENTIFICATION=C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] lattice_0.20-6 sp_0.9-98

loaded via a namespace (and not attached):
[1] grid_2.14.1  tools_2.14.1

-----------


Thanks in advance for any help,


Mauricio Zambrano-Bigiarini

-- 
===========================================
Water Resources Unit
Institute for Environment and Sustainability
Joint Research Centre, European Commission
webinfo    : http://floods.jrc.ec.europa.eu/
===========================================
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and may not in any circumstances be regarded as
stating an official position of the European Commission"
===========================================
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============================================
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