CODEWITHSUNDEEP
rmatrixtriangular
Student
Student

Reputation: 353

Reading a symmetric matrix from file that omits upper triangular part

Using R, what is the best way to read a symmetric matrix from a file that omits the upper triangular part. For example,

1.000
.505  1.000
.569  .422  1.000
.602  .467  .926  1.000
.621  .482  .877  .874  1.000
.603  .450  .878  .894  .937  1.000

I have tried read.table, but haven't been successful.

Upvotes: 2

Views: 4750

Answers (5)

nisetama
nisetama

Reputation: 8863

This won't work in the OP's case because the diagonal was 1, but if the diagonal is zero or missing, then you can use as.dist%>%as.matrix to copy the lower diagonal to the upper diagonal and set the diagonal to zero:

input=" Pop0    Pop1    Pop2
Pop0
Pop1    0.015
Pop2    0.079   0.083
Pop3    0.014   0.016   0.073"

as.matrix(as.dist(cbind(read.table(text=input,fill=T),NA)))

Result:

      Pop0  Pop1  Pop2  Pop3
Pop0 0.000 0.015 0.079 0.014
Pop1 0.015 0.000 0.083 0.016
Pop2 0.079 0.083 0.000 0.073
Pop3 0.014 0.016 0.073 0.000

In my case the input had column names, so read.table(fill=T) was automatically able to determine the number of columns and IRTFM's trick of specifying col.names=1:4 was not neeeded.

Upvotes: 0

Blue Magister
Blue Magister

Reputation: 13363

I copied your text, and then used tt <- file('clipboard','rt') to import it. For a standard file:

tt <- file("yourfile.txt",'rt')
a <- readLines(tt)
b <- strsplit(a,"  ") #insert delimiter here; can use regex
b <- lapply(b,function(x) {
  x <- as.numeric(x)
  length(x) <- max(unlist(lapply(b,length))); 
  return(x)
})
b <- do.call(rbind,b)
b[is.na(b)] <- 0
#kinda kludgy way to get the symmetric matrix
b <- b + t(b) - diag(b[1,1],nrow=dim(b)[1],ncol=dim(b)[2]

Upvotes: 3

IRTFM
IRTFM

Reputation: 263342

Here's a read.table and loopless and *apply-less solution:

txt <- "1.000
.505  1.000
.569  .422  1.000
.602  .467  .926  1.000
.621  .482  .877  .874  1.000
.603  .450  .878  .894  .937  1.000"
 # Could use clipboard or read this from a file as well.
mat <- data.matrix( read.table(text=txt, fill=TRUE, col.names=paste("V", 1:6))  )
mat[upper.tri(mat)] <- t(mat)[upper.tri(mat)]
> mat
        V1    V2    V3    V4    V5    V6 
[1,] 1.000 0.505 0.569 0.602 0.621 0.603
[2,] 0.505 1.000 0.422 0.467 0.482 0.450
[3,] 0.569 0.422 1.000 0.926 0.877 0.878
[4,] 0.602 0.467 0.926 1.000 0.874 0.894
[5,] 0.621 0.482 0.877 0.874 1.000 0.937
[6,] 0.603 0.450 0.878 0.894 0.937 1.000

Upvotes: 15

Sven Hohenstein
Sven Hohenstein

Reputation: 81693

Here is an approach which also works if the dimensions of the matrix are unknown.

# read file as a vector
mat <- scan("file.txt", what = numeric())

# calculate the number of columns (and rows)
ncol <- (sqrt(8 * length(mat) + 1) - 1) / 2

# index of the diagonal values
diag_idx <- cumsum(seq.int(ncol))

# generate split index
split_idx <- cummax(sequence(seq.int(ncol)))
split_idx[diag_idx] <- split_idx[diag_idx] - 1

# split vector into list of rows
splitted_rows <- split(mat, f = split_idx)

# generate matrix
mat_full <- suppressWarnings(do.call(rbind, splitted_rows))
mat_full[upper.tri(mat_full)] <- t(mat_full)[upper.tri(mat_full)]


   [,1]  [,2]  [,3]  [,4]  [,5]  [,6]
0 1.000 0.505 0.569 0.602 0.621 0.603
1 0.505 1.000 0.422 0.467 0.482 0.450
2 0.569 0.422 1.000 0.926 0.877 0.878
3 0.602 0.467 0.926 1.000 0.874 0.894
4 0.621 0.482 0.877 0.874 1.000 0.937
5 0.603 0.450 0.878 0.894 0.937 1.000

Upvotes: 1

Tyler Rinker
Tyler Rinker

Reputation: 109864

I'm posting but I like Blue Magister's approach wat better. But maybe there's something in this that's of use.

mat <- readLines(n=6)
1.000
.505  1.000
.569  .422  1.000
.602  .467  .926  1.000
.621  .482  .877  .874  1.000
.603  .450  .878  .894  .937  1.000

nmat <- lapply(mat, function(x) unlist(strsplit(x, "\\s+")))
lens <- sapply(nmat, length)
dlen <- max(lens) -lens
bmat <- lapply(seq_along(nmat), function(i) {
    as.numeric(c(nmat[[i]], rep(NA, dlen[i])))
})
mat <- do.call(rbind, bmat)
mat[upper.tri(mat)] <- t(mat)[upper.tri(mat)]
mat

Upvotes: 1

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