Hi Huapeng,

Firstly, it is worth noting that it is often not recommended to
overlay series with different scales, so you should think about other
ways to present your data.

Secondly, when posting here it is much more helpful to provide the
data in a form that can be copied-and-pasted into R: so rather than
print(mydata), please use dput(mydata).

Regarding the doubleYScale() function from the latticeExtra package,
since you are overlaying grouped plots you should give use.style =
FALSE. Then specify an appropriate par.settings list to the final
plot, which might be
par.settings = simpleTheme(fill = c("dark gray", "light gray",
"white"), col = "black", pch=c(16,17), lty=c(1,2))
I haven't tested this, but I can if you send me your data in a dput() form.

Regarding a composite key, you could construct it using the general
'key' argument described in ?xyplot or if you want two keys in
different positions that would also be possible.

The doubleYScale() function was not really designed for handling such
complex plots... and again, I would encourage you to think about
simpler ways to present your data.

Hope that helps
-Felix


On 4 June 2010 01:48, Chen, Huapeng FOR:EX <huapeng.c...@gov.bc.ca> wrote:
>
> Hello,
>
> I am new to R. I am trying to use “DoubleYScale” to overlay one barchart with 
> a xyplot with two lines. I have two problems. One is that I could not figure 
> out how to custom line (point and line) with “par.settings” and seems to me 
> that whatever “par.settings” I used to custom the barchart was also applied 
> to the xyplot (lines) and I don’t know how to apply par.setting separately to 
> each barchart and xyplot for  my customization.
>
> The other problem is how to add a key for both barchart and xyplot in a 
> meaningful way.
>
> I attached a piece of R code below I have been struggling to get this to 
> work. Your kind help and advice are greatly appreciated.
>
> Thanks,
>
> Huapeng
>
> ###############################################################################################################################################
> dispersal<-barchart(NTLST_Dispersal_VAR_00_08$LDP_PER*100 + 
> NTLST_Dispersal_VAR_00_08$SPP_PER*100 +
>         NTLST_Dispersal_VAR_00_08$SPG_PER*100 ~ 
> NTLST_Dispersal_VAR_00_08$Year | NTLST_Dispersal_VAR_00_08$District,
>         data=NTLST_Dispersal_VAR_00_08,
>         horizontal=FALSE,
>         stack=TRUE,
>         layout=c(5,5),
>         xlab="Year",
>         ylab="%",
>         strip = strip.custom( bg="light gray")
>         #par.settings = simpleTheme(col = c("dark gray", "light gray", 
> "white")),
>         #auto.key=TRUE
>         )
>
>
>
> vars<-xyplot(sqrt(NTLST_Dispersal_VAR_00_08$Infestation_NUM) + 
> NTLST_Dispersal_VAR_00_08$AI  ~ NTLST_Dispersal_VAR_00_08$Year | 
> NTLST_Dispersal_VAR_00_08$District,
> data=NTLST_Dispersal_VAR_00_08,
> layout=c(5,5),
> type="b",
> ylab="Square roots of number of infested cells/Landscape aggregation index"
> #par.settings = simpleTheme(col = c("black", "black"), pch=c(16,17))
> )
>
> doubleYScale(dispersal, vars,add.ylab2 = TRUE,
> #auto.key=list(text=c("LDP","SPP", "SPG","Infestation","Landscape aggregation 
> index"),
> #         points = list(pch=c(16,17)), lines=list(lty=c(1,2)),
> #         rectangles = list(size=1.7,border="black", col=c("black", "light 
> gray", "white")),
> #         space = "right")
> )
>
> update(trellis.last.object(),
> par.settings = simpleTheme(col = c("dark gray", "light gray", 
> "white"),pch=c(16,17),lty=c(1,2)))
> ###########################################################################
>
> ##############################################################################
> A sample of data used
> ########################
>
> District        Year    SPG_PER SPP_PER LDP_PER SPP_LDP_PER     
> Infestation_NUM AI
> DAB     1999    0.446808511     0.205673759     0.34751773      0.553191489   
>   461     48.9143
> DAB     2000    0.480769231     0.192307692     0.326923077     0.519230769   
>   332     37.3591
> DAB     2001    0.366141732     0.212598425     0.421259843     0.633858268   
>   663     37.3418
> DAB     2002    0.663366337     0.222772277     0.113861386     0.336633663   
>   791     41.7671
> DAB     2003    0.553278689     0.178278689     0.268442623     0.446721311   
>   2138    54.333
> DAB     2004    0.799204771     0.115308151     0.085487078     0.200795229   
>   2921    62.5666
> DAB     2005    0.824295011     0.106290672     0.069414317     0.175704989   
>   2783    57.9458
> DAB     2006    0.794520548     0.131506849     0.073972603     0.205479452   
>   2210    50.0829
> DAB     2007    0.77972028      0.148601399     0.071678322     0.22027972    
>   2466    54.0918
> DCC     1999    0.844036697     0.105504587     0.050458716     0.155963303   
>   2077    57.9
> DCC     2000    0.7731569       0.096408318     0.130434783     0.2268431     
>   4294    75.5286
> DCC     2001    0.905714286     0.065714286     0.028571429     0.094285714   
>   4302    74.709
> DCC     2002    0.799256506     0.066914498     0.133828996     0.200743494   
>   6095    80.5838
> DCC     2003    0.896703297     0.065934066     0.037362637     0.103296703   
>   7919    85.7303
> DCC     2004    0.887254902     0.068627451     0.044117647     0.112745098   
>   8516    84.7028
> DCC     2005    0.923728814     0.06779661      0.008474576     0.076271186   
>   7759    79.4637
> DCC     2006    0.941935484     0.04516129      0.012903226     0.058064516   
>   6637    74.5994
> DCC     2007    0.890909091     0.072727273     0.036363636     0.109090909   
>   4288    68.593
> DCH     1999    0.691176471     0.161764706     0.147058824     0.308823529   
>   204     38.2682
> DCH     2000    0.245901639     0.151639344     0.602459016     0.754098361   
>   1099    55.3403
> DCH     2001    0.525316456     0.189873418     0.284810127     0.474683544   
>   1350    52.3413
> DCH     2002    0.326599327     0.111111111     0.562289562     0.673400673   
>   9332    88.5776
> DCH     2003    0.797342193     0.102990033     0.099667774     0.202657807   
>   11416   93.0988
> DCH     2004    0.720430108     0.134408602     0.14516129      0.279569892   
>   13120   94.1959
> DCH     2005    0.773480663     0.066298343     0.160220994     0.226519337   
>   13726   93.0554
> DCH     2006    0.943319838     0.032388664     0.024291498     0.056680162   
>   14393   92.2483
> DCH     2007    0.961038961     0.019480519     0.019480519     0.038961039   
>   13729   90.2417
> DCK     1999    0.611111111     0.055555556     0.333333333     0.388888889   
>   75      64.9573
> DCK     2000    0.48    0.04    0.48    0.52    109     60.2273
> DCK     2001    0.511111111     0.111111111     0.377777778     0.488888889   
>   185     56.1514
> DCK     2002    0.6875  0.09375 0.21875 0.3125  202     65.8192
> DCK     2003    0.649122807     0.052631579     0.298245614     0.350877193   
>   332     61.6667
> DCK     2004    1       0       0       0       315     67.156
> DCK     2005    0.541353383     0.157894737     0.30075188      0.458646617   
>   603     57.967
> DCK     2006    0.685314685     0.111888112     0.202797203     0.314685315   
>   912     59.3861
> DCK     2007    0.9     0.075   0.025   0.1     639     55.8722
> ############################################################################
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Felix Andrews / 安福立
Integrated Catchment Assessment and Management (iCAM) Centre
Fenner School of Environment and Society [Bldg 48a]
The Australian National University
Canberra ACT 0200 Australia
M: +61 410 400 963
T: + 61 2 6125 4670
E: felix.andr...@anu.edu.au
CRICOS Provider No. 00120C
-- 
http://www.neurofractal.org/felix/

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