Question

convert S4 DataFrame of Rle objects to sparse matrix

1

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Koen Van den Berge ▴ 180

@koen-van-den-berge-6369

Last seen 6 months ago

Ghent University, Belgium

In the R language, I have an S4 DataFrame consisting of Rle encoded elements.
The data can be simulated using following code

    x = DataFrame(Rle(1:10),Rle(11:20),Rle(21:30))

Now, I want to convert this DataFrame to a sparse matrix from the Matrix package. On a usual data.frame, one can do

    Matrix(x,sparse=TRUE)

However, this does not work for DataFrames, as it gives the following error:

`Error in as.vector(data) : `
 ` no method for coercing this S4 class to a vector`

Also, Matrix(as.data.frame(x)) does not work as it gives the following error:

Error in asMethod(object) : invalid class 'NA' to dup_mMatrix_as_geMatrix

Any ideas on how to convert between data types in a rather efficient way?

Thanks!

s4 • 5.7k views

ADD COMMENT • link updated 9.7 years ago by Michael Lawrence ★ 11k • written 9.7 years ago by Koen Van den Berge ▴ 180

score 2 · Answer 1 · 2015-04-15

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Michael Lawrence ★ 11k

@michael-lawrence-3846

Last seen 3.0 years ago

United States

Direct construction of Matrix objects from data.frame objects does not even work in base R:

> Matrix(as.data.frame(mtcars))
Error in isN0(as(m, "matrix")) : 
  (list) object cannot be coerced to type 'double'

And coercing a DataFrame of Rle objects to a data.frame (and thus the Rle objects to ordinary vectors) defeats the purpose of the run-length encoding.

I know there is at least one RleDataFrame class floating around, and it should probably make its way into S4Vectors.

Once we have that, it would be nice to have a direct, efficient route from a table of Rle objects to a sparse matrix encoding, i.e., one that takes into account the zeros explicitly.

But if you really need this coercion today, and don't mind expanding the Rle objects, then:

> Matrix(as.matrix(as.data.frame(x)))

should do the trick.

ADD COMMENT • link 9.7 years ago Michael Lawrence ★ 11k

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Hi Michael,

The proposed code indeed does work, however it is very inefficient, as you already mention yourself. I was hoping for a more efficient conversion between the two data types. The conversion you propose gives me memory issues for allocating the regular matrix.

ADD REPLY • link 9.7 years ago Koen Van den Berge ▴ 180

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I will work on this.

ADD REPLY • link 9.7 years ago Michael Lawrence ★ 11k

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Is there an answer to this question?

ADD REPLY • link 8.4 years ago John Reid ▴ 20

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Never got around to doing anything here. The S4Vectors package does not depend on Matrix, so I am not sure where this should go, but here is a simple way to go from Rle to Matrix (assuming the DataFrame is called "df"):

setAs("Rle", "Matrix", function(from) {
    rv <- runValue(from)
    nz <- rv != 0
    i <- as.integer(ranges(from)[nz])
    x <- rep(rv[nz], runLength(from)[nz])
    sparseMatrix(i=i, p=c(0L, length(x)), x=x)
})

setAs("DataFrame", "Matrix", function(from) {
    do.call(cbind, lapply(from, as, "Matrix"))
})

as(df, "Matrix")

ADD REPLY • link 8.4 years ago Michael Lawrence ★ 11k

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Thanks for quick response.

ADD REPLY • link 8.4 years ago John Reid ▴ 20

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Just one little bug fix to make sure length is correct if Rle ends with zeros:

#' Convert from Rle to one column matrix
#'
setAs("Rle", "Matrix", function(from) {
    rv <- runValue(from)
    nz <- rv != 0
    i <- as.integer(ranges(from)[nz])
    x <- rep(rv[nz], runLength(from)[nz])
    sparseMatrix(i=i, p=c(0L, length(x)), x=x,
                 dims=c(length(from), 1))
})

#' Convert from DataFrame of Rle to sparse Matrix
#'
setAs("DataFrame", "Matrix", function(from) {
  mat = do.call(cbind, lapply(from, as, "Matrix"))
  colnames(mat) <- colnames(from)
  rownames(mat) <- rownames(from)
  mat
})

ADD REPLY • link 8.4 years ago John Reid ▴ 20