Provides methods to manipulate and store sparse tensors. Tensors are multidimensional generalizations of matrices (two dimensional) and vectors (one dimensional).
tensorr
provides methods to manipulate and store sparse tensors. Tensors are multi-dimensional generalizations of matrices (two dimensional) and vectors (one dimensional).
It has three main goals:
The development version of tensorr is available on github.
devtools::install_github("zamorarr/tensorr")
See the introduction vignette for a comprehensive overview. To create a sparse tensor you have to provide the non-zero values, subscripts to the non-zero values, and the overall dimensions of the tensor.
library(tensorr)subs <- list(c(1,1,1), c(1,1,2))vals <- c(10, 20)dims <- c(2,2,2)x <- sptensor(subs, vals, dims)x#> subs: <1,1,1> <1,1,2>#> vals: 10 20
Many of the dense and sparse implementation ideas were adpated from:
For a review on tensors, see:
NEWS.md
file to track changes to the package.