On Wed, Feb 11, 2009 at 1:32 PM, cruz <crua...@gmail.com> wrote:
> Hi,
>
> I have a big matrix X with M rows and N columns that I want to filter
> it into smaller ones with m (<M) rows and N columns.
> The filter rule is based on the values of each columns, i.e.
>
> X looks like this:
> column name: a, b, c, d, ... etc
>
> a b c d ...
> 1 2 3 4 ...
> 5 6 7 8 ...
> 9 8 7 6 ...
> ... ... ... ...
>
> The filter rule with the result that I want is:
>
> X[X$a<5 & X$b<5 & X$c<5 & X$d<5 ...etc ,]
> X[X$a<5 & X$b<5 & X$c<5 & X$d>=5 ...etc ,]
> X[X$a<5 & X$b<5 & X$c>=5 & X$d<5 ...etc ,]
> ... ... ...
> ...
>
> with all the possible combinations which is 2^M
>
> I try to use multiple for loops to separate it:
>
> for (i in 1:2)
> for (j in 1:2)
> for (k in 1:2)
> ... ...
> assign(paste(i,j,k,...,sep="")), X[if (i==1) paste("X$a<5")
> else paste("X$a>=5") & if (i==1) paste("X$b<5") else paste("X$b>=5") &
> ..., ])
>
> # there might be syntax errors, I just want to clearly describe my problem
>
> Since paste("X$a>=5") gives type of character; whereas the type of
> X$a>=5 should be logical.
>
> How can I do this?
>
> All thoughts are greatly appreciated.
>
> Many Thanks,
> cruz
>
Assuming that I understood your data structure correctly, that all
columns should be tested in your filter, and that exactly one column
should not match the condition, the following should work:
##sample data
X<-matrix(sample(1:200,10000,replace=T),nrow=100)
colnames(X)<-1:100
### Filter function - modify to suit your purpose
filterFunction<-function(n,data){
filteredData<-data[rowSums(data>=199)==1&(data[,n]>=199),,drop=FALSE]
if(nrow(filteredData)==0){
filteredData<-"NoMatchingRows"
}
return(filteredData)
}
names<-colnames(X)
lapply(as.list(names),filterFunction,X)
Hope it helps.
Best regards,
Gustaf
--
Gustaf Rydevik, M.Sci.
tel: +46(0)703 051 451
address:Essingetorget 40,112 66 Stockholm, SE
skype:gustaf_rydevik
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