| tensorSparse | R Documentation |
Compute the tensor product of two vectors, matrices or arrays which may be sparse or non-sparse.
tensorSparse(A, B, alongA = integer(0), alongB = integer(0))
A, B |
Vectors, matrices, three-dimensional arrays,
or objects of class |
alongA |
Integer vector specifying the dimensions of |
alongB |
Integer vector specifying the dimensions of |
This function is a generalisation, to sparse arrays, of the function
tensor in the tensor package.
tensorSparse has the same syntax and interpretation
as tensor.
For example, if A and B are matrices, then
tensor(A,B,2,1) is the matrix product A %*% B
while tensor(A,B,2,2) is A %*% t(B).
This function tensorSparse handles
sparse vectors (class "sparseVector" in the Matrix package),
sparse matrices (class "sparseMatrix" in the Matrix
package) and sparse three-dimensional arrays (class
"sparse3Darray" in the spatstat.sparse package)
in addition to the usual vectors, matrices and arrays.
The result is a sparse object if at least one of A and B
is sparse. Otherwise, if neither A nor B is sparse, then the
result is computed using tensor.
The main limitation is that the result cannot have more than 3 dimensions (because sparse arrays with more than 3 dimensions are not yet supported).
Either a scalar, a vector, a matrix, an array,
a sparse vector (class "sparseVector" in the Matrix package),
a sparse matrix (class "sparseMatrix" in the Matrix
package) or a sparse three-dimensional array (class
"sparse3Darray" in the spatstat.sparse package).
.
sparse3Darray,
aperm.sparse3Darray
M <- sparse3Darray(i=1:4, j=sample(1:4, replace=TRUE),
k=c(1,2,1,2), x=1:4, dims=c(5,5,2))
A <- tensorSparse(M, M, 1:2, 2:1)
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