[R] %*% in Matrix objects
Martin Maechler
maechler at stat.math.ethz.ch
Mon Jan 29 09:06:34 CET 2007
>>>>> "Jose" == Jose Quesada <quesada at gmail.com>
>>>>> on Sat, 27 Jan 2007 23:42:34 +0100 writes:
Jose> Hi Martin, Thanks for your detailed answer.
Jose> x <- Matrix(1:12, 3,4, sparse = TRUE)
>> I hope that you are aware of the fact that it's not
>> efficient at all to store a dense matrix (it has *no* 0
>> entry) as a sparse one..
>>
>> and your posting is indeed an incentive for the Matrix
>> developers to improve that part ... ;-)
>>
Jose> Yes, the toy example is not sparse but the actual data
Jose> is, and very large; I'm aware that coercing a dense
Jose> matrix into the Sparse format is not leading to any
Jose> saving (on the contrary). I'm talking about a real
Jose> application with large sparse matrices; from now on,
Jose> I'll post small examples using sparse matrices as well
Jose> to avoid confusion.
ok.
Jose> so I tried
Jose> x = matrix(1:12,3,4)
Jose> x = as(x, "CsparseMatrix")
Jose> xnorms = sqrt(colSums(x^2))
Jose> xnorms = as(xnorms, "CsparseMatrix")
Jose> (xnormed = t(x) * (1/xnorms))
Jose> But now, instead of a warning I get
Jose> "Error: Matrices must have same dimensions in t(x) * (1/xnorms)"
>> yes. And the same happens with traditional matrices -- and well so:
>> For arithmetic with matrices (traditional or "Matrices"),
>>
>> A o B (o in {"+", "*", "^", ....})
>> -----
>>
>> does require that matrices A and B are ``conformable'', i.e.,
>> have exact same dimensions.
>>
>> Only when one of A or B is *not* a matrix,
>> then the usual S-language recycling rules are applied,
>> and that's what you were using in your first example
>> (<Matrix> * <numeric>) above.
>>
Jose> Right. So this means that the * operator is not
Jose> overloaded in Matrix (that is, if I use it, I'll get
Jose> my Matrix coherced to matrix. Is that correct?
no. The "*" is overloaded (read on)
Jose> Does this mean that there is no easy way to do element-by-element
Jose> multiplication without leaving the sparse Matrix format?
No. There is an easy way:
If you multiply (or add or ..) two sparse matrices of matching dim(), the
result will be sparse. Also if use a "scalar" (length-1 vector)
with a Matrix, the result remains sparse (where appropriate) :
> (x <- Matrix(c(0,1,0,0), 3,3))
3 x 3 sparse Matrix of class "dtCMatrix"
[1,] . . .
[2,] 1 . .
[3,] . 1 .
Warning message:
data length [4] is not a sub-multiple or multiple of the number of rows [3] in matrix
> (2 * x) + t(x)
3 x 3 sparse Matrix of class "dgCMatrix"
[1,] . 1 .
[2,] 2 . 1
[3,] . 2 .
> ((2 * x) + t(x)) * t(x)
3 x 3 sparse Matrix of class "dgCMatrix"
[1,] . 1 .
[2,] . . 1
[3,] . . .
What you tried to do, <sparse> * <vector-of-length-gt-1>, will
only result in a sparse matrix in the next version of the Matrix
package.
Jose> I suspect I'm facing the drop=T as before...
>> why??
Jose> Because when I got a row out of a Matrix object, the
Jose> resulting vector is not of class Matrix but numeric,
Jose> and then (<Matrix> * <numeric>) is applied.
Jose> Last, I shouldn't consider myself the most standard
Jose> user of the matrix package, since my lineal algebra is
Jose> really basic. But in any case, you should know that
Jose> your package is being enormously useful for me. Keep
Jose> up the good work. And if I can help by posting my very
Jose> basic questions, I'm glad to help.
Ok, thanks for the flowers :-)
Martin
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