[Traminer-users] seqrplot: Error in plot.new() : figure margins too large
Alexis Gabadinho
Alexis.Gabadinho at unige.ch
Wed Mar 9 16:27:53 CET 2011
Dear Jane,
I tried to reproduce the problem by creating an artificial sequence data
set and a clustering variable with the same characteristics as yours:
library(TraMineR)
co.fac <- rep(paste("Gr",1:8, sep=""), 1000)
ex <- seqgen(4000, 120, 1:10)
Org.seq <- seqdef(ex)
## mean time plot
seqmtplot(Org.seq, group=co.fac)
The code above works perfectly both on Linux (R 2.10) and Windows (R
2.12). You can try it on your computer. If you get an error with this
code, could you tell me which R and TraMineR versions you use ?
Moreover I see an error in your "seqrplot" code :
seqrplot(Org.seq, group = co.fac, co.fac, border=NA)
You have to provide a distance matrix (created with "seqdist()") for
plotting representative sequences, and instead you pass "co.fac" again.
Your code should look like this (replace "my.dist.matrix" by the name of
your distance matrix):
seqrplot(Org.seq, group = co.fac, dist.matrix= my.dist.matrix , border=NA)
Sometimes, if a graphic window is open and an error occurs with the
plotting function, you have to close the graphic window before running
the corrected code again.
Let me know if this is the solution to your problem.
Best,
Alexis.
Le 08. 03. 11 21:08, Jane K. Ohgami a écrit :
>
> I am new to TraMineR and have what is probably a very basic question
> regarding plot/graphing commands for cluster analysis.
> I am analyzing career transitions and my data set consists of
>
> [>] 3842 sequences with 10 distinct events/states
> [>] 2590 distinct sequences
> [>] min/max sequence length: 120/120
>
> Trying to exercise the following syntax:
> seqmtplot(Org.seq, group = co.fac, border=NA) or
> seqrplot(Org.seq, group = co.fac, co.fac, border=NA)
>
> I get the following error message:
> >Error in plot.new() : figure margins too large
>
> I have unsuccessfully tried to adjust for this so would appreciate any
> suggestions. Basically I need to figure out how my 8 clusters break
> down. Any suggestions/advice would be greatly appreciated. Thank you!
>
>
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