It's a pretty inefficient way to do things (e.g. 50000+ iterations [20
seconds] to find a good sample) but if you're not doing this often I
guess you could do something like:
checkNeighborEqual<-function(x){
#assuming the final value is not infinity
return(any(x==c(x[-1],Inf)))
}
#fake data
x<-data.frame('distance'=rep(1:10,3),'angle'=rep(1:5,6),'var3'=rep(1:6,5))
#column that should not have adjacent duplicates
noDupeColumns<-c('angle','var3')
run<-1
while(run==1||any(apply(newX[,noDupeColumns],2,checkNeighborEqual))){
message('Scrambling for the ',run,' time')
newX<-x[sample(1:nrow(x),nrow(x)),]
run<-run+1
}
print(newX)
Scott
Scott Sherrill-Mix
Department of Microbiology
University of Pennsylvania
402B Johnson Pavilion
3610 Hamilton Walk
Philadelphia, PA 19104-6076
On Tue, Aug 11, 2009 at 4:25 PM, Jon Zadra<jr...@virginia.edu> wrote:
> Hi,
>
> I'm trying to randomize a sequence of trials for an experimental design.
> The trials consist of values for each of two factors. As is there are 30
> combinations of the two factors, and I want them to be ordered randomly but
> with the requirement that for one of the factors, the value can never be the
> same as the previous value.
>
> I'm currently randomizing my dataframe by using:
>
> x[sample(1:nrow(x), nrow(x),]
>
> Output example, on rows 2 and 3 the angle value is the same (the situation I
> wish to prevent):
> Distance Angle
> 9 90
> 9 45
> 10 45
> 11 30
> 8 60
> 7 0
> 8 30
> 10 0
> 10 60
> ... ...
>
> Can anyone recommend a simple way to do this? (Bonus if it could be
> implemented for more than a single column!)
>
> Thanks in advance,
>
> Jon
> --
> Jon Zadra
> Department of Psychology
> University of Virginia
> P.O. Box 400400
> Charlottesville VA 22904
> (434) 982-4744
> email: za...@virginia.edu
> <http://www.google.com/calendar/embed?src=jzadra%40gmail.com>
>
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
>
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