A little different solution, but it gives you the matches and the
columns in a more compact form. You can always take the data and use
it to put into your array.
> # creation of the data matrix
> c1<- c(1,4,3,2,4,1,3,2,4,3)
> c2<- c(2,4,3,4,4,3,4,1,3,2)
> c3<- c(1,3,2,4,4,3,4,4,2,2)
> c4<- c(2,3,2,3,1,3,2,4,4,3)
> c5<- c(1,2,1,1,2,2,2,3,2,1)
> c6<- c(3,2,4,3,1,1,2,3,3,4)
>
>
> X<-cbind(c1,c2,c3,c4,c5,c6)
>
>
>
> # initialize a matrix with T/F for same values
> same <- matrix(FALSE, ncol=ncol(X) / 2, nrow=nrow(X))
> # set the values
> for (i in 1:ncol(same)) same[,i] <- X[, 2*i-1] == X[, 2*i]
>
> # get all possible combinations of numbers for accessing the matrix
> cbn <- combn(ncol(same), 2) # combinations take 2 at a time
> cbn # see what it looks like
[,1] [,2] [,3]
[1,] 1 1 2
[2,] 2 3 3
>
> # use this to interate through using 'lapply' since it returns value
> values <- lapply(1:ncol(cbn), function(.col){ # similar to 'for', but better
+ match <- which(same[, cbn[1, .col]] & same[, cbn[2, .col]])
+ if (length(match) == 0) return(NULL) # no matches
+ # now return the values
+ cbind(LA=X[match, 2 * cbn[1, .col]],
+ LB=X[match, 2 * cbn[2, .col]],
+ col1=cbn[1, .col],
+ col2=cbn[2, .col])
+ })
> X
c1 c2 c3 c4 c5 c6
[1,] 1 2 1 2 1 3
[2,] 4 4 3 3 2 2
[3,] 3 3 2 2 1 4
[4,] 2 4 4 3 1 3
[5,] 4 4 4 1 2 1
[6,] 1 3 3 3 2 1
[7,] 3 4 4 2 2 2
[8,] 2 1 4 4 3 3
[9,] 4 3 2 4 2 3
[10,] 3 2 2 3 1 4
> (values <- do.call('rbind', values))
LA LB col1 col2
[1,] 4 3 1 2
[2,] 3 2 1 2
[3,] 4 2 1 3
[4,] 3 2 2 3
[5,] 4 3 2 3
>
On 10/19/07, Luke Neraas <[EMAIL PROTECTED]> wrote:
> #Hi Jim,
> # here is a simpler version of my puzzle
> # I have added a bit of explanation near the bottom of this puzzle
> # I apologize for the confusion and sloppiness earlier.
>
>
> # I have a question regarding pairwise calculations of a matrix using a
> "for-loop."
> # Below I have a matrix "X" with 6 columns. These are Genotypic data so
> Column1 & Column2 is
> # a unit, Column3 & Column4 is a unit, Column5 & Column6 is a unit,
> # I have a loop designed to calculate the number of times an individual in
> Column"i" & Column"j"
> # has the same value and the same individual has two values that are the
> same in Column"k" & Column"l" .
> # I have another series of code that adds a 2 to a specific location in a
> results data frame called " result.df".
> # I have written a loop that accomplishes this "pair of columns" pairwise
> comparison, but it also compares
> # some of the "pairs of Columns" to themselves. Is there a way to get around
> this?
>
>
> # creation of the data matrix
> c1<- c(1,4,3,2,4,1,3,2,4,3)
> c2<- c(2,4,3,4,4,3,4,1,3,2)
> c3<- c(1,3,2,4,4,3,4,4,2,2)
> c4<- c(2,3,2,3,1,3,2,4,4,3)
> c5<- c(1,2,1,1,2,2,2,3,2,1)
> c6<- c(3,2,4,3,1,1,2,3,3,4)
>
>
> X<-cbind(c1,c2,c3,c4,c5,c6)
>
> X
>
> ## Creation of the result dataframe
> result<- matrix(0,16,2)
> result.df<-data.frame(result)
> result.df[,1] <- c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4)
> result.df[,2] <- c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4)
> names(result.df)[1]<-"L(A)a(ij)"
> names(result.df)[2]<-"L(B)a(kl)"
>
> result.df
>
>
>
> ### The loop written to find Double Homozygotes
>
>
> for (i in seq(1,(ncol(X)-3), by=2)){
> j <- i+1
> for (k in seq(3,(ncol(X)-1), by=2)){
> l <- k+1
>
> match.rows <- ((X [,i] == X [, j] ) & ( X [,k] == X [, l]))
>
> double_homo_i <- X [match.rows, i]
> double_homo_k <- X [match.rows, k]
>
> double_homo<- cbind( double_homo_i, double_homo_k)
> double_homo.df<-data.frame(double_homo,Counts=2)
> names(double_homo.df)[1]<-"L(A)a(ij)"
> names(double_homo.df)[2]<- "L(B)a(kl)"
>
>
> # Below takes the result from each loop and puts in the result.df dataframe.
>
> count<-double_homo.df
>
> almost.df<-aggregate(count$Counts, list(count[,1],count[,2]),
> FUN=sum)
>
> temp<-order(almost.df$Group.1)
> final.df<-almost.df[temp,]
> names(final.df)[1]<-"L(A)a(ij)"
> names(final.df )[2]<-"L(B)a(kl)"
>
> result.df<-merge(result.df,final.df,by=c("L(A)a(ij)","L(B)a(kl)"), all.x=T)
>
> }
> }
>
>
>
> # Below are the result I get with the code above.
>
> result.df
>
>
>
> # L(A)a(ij) L(B)a(kl) C1C2~C3C4 C1C2~C5C6 C3C4~C3C4 C3C4~C5C6
> # 1 1 1 NA NA NA
> NA
> # 2 1 2 NA NA NA
> NA
> # 3 1 3 NA NA NA
> NA
> # 4 1 4 NA NA NA
> NA
> # 5 2 1 NA NA NA
> NA
> # 6 2 2 NA NA 2
> NA
> # 7 2 3 NA NA NA
> NA
> # 8 2 4 NA NA NA
> NA
> # 9 3 1 NA NA NA
> NA
> # 10 3 2 2 NA NA
> 2
> # 11 3 3 NA NA 4
> NA
> # 12 3 4 NA NA NA
> NA
> # 13 4 1 NA NA NA
> NA
> # 14 4 2 NA 2 NA
> NA
> # 15 4 3 2 NA NA
> 2
> # 16 4 4 NA NA 2
> NA
>
> # The first column in result.df is the value of the number (1-4) in a the
> first "column pair" comparison from "X" that has the same value in a row.
> # The second column in result.df is the value of the number (1-4) in a
> "column pair" comparison from "X" that has the same value in a row for that
> # column pair.
> # The third column in result.df has the value 2 added to the data.frame if
> the condition is met.
> # for example in :X" Col1 & Col2 row 3 has a "3 3" and Col3 & Col4 has a "2
> 2" in row three. Therefore the result.df$C1C2~C3C4 has a 2 added to
> # the row where results.df$L(A)a(ij)=3 and results.df$L(B)a(kl)=2.
> # My major problem stems from having "Column pairs" compared to themselves,
> such as result.df$C3C4~C3C4 are the results from
> # X[,3:4] compared to itself.
> # is there way to write the loop so these "Column Pairs" are not compared to
> themselves.
> # Perhaps a change in the code for my loop :
> # for (i in seq(1,(ncol(X)-3), by=2)){
> # j <- i+1
> # for (k in seq(3,(ncol(X)-1), by=2)){
> # l <- k+1
>
>
>
> # Here is the Result I am looking for.
>
> L(A)a(ij) L(B)a(kl) C1C2~C3C4 C1C2~C5C6 C3C4~C5C6
> # 1 1 1 NA NA NA
> # 2 1 2 NA NA NA
> # 3 1 3 NA NA NA
> # 4 1 4 NA NA NA
> # 5 2 1 NA NA NA
> # 6 2 2 NA NA NA
> # 7 2 3 NA NA NA
> # 8 2 4 NA NA NA
> # 9 3 1 NA NA NA
> # 10 3 2 2 NA 2
> # 11 3 3 NA NA NA
> # 12 3 4 NA NA NA
> # 13 4 1 NA NA NA
> # 14 4 2 NA 2 NA
> # 15 4 3 2 NA 2
> # 16 4 4 NA NA NA
>
>
> # Any help or ideas would be greatly appreciated
>
> # Thanks in advance
>
> # Luke Neraas
>
> # [EMAIL PROTECTED]
>
> # University of Alaska Fairbanks
> # School of Fisheries and Ocean Sciences
> # 11120 Glacier Highway
> # UAF Fisheries Division
> # Juneau, AK 99801
>
>
>
>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
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