fold: Tensor folding of 2D DelayedArray

In rikenbit/DelayedTensor: R package for sparse and out-of-core arithmetic and decomposition of Tensor

Tensor folding of 2D DelayedArray

Description

General folding of a 2D DelayedArray into a higher-order DelayedArray(Tensor). This is designed to be the inverse function to unfold, with the same ordering of the indices. This amounts to following: if we were to unfold a Tensor using a set of row_idx and col_idx, then we can fold the resulting matrix back into the original Tensor using the same row_idx and col_idx.

Usage

fold(mat, row_idx = NULL, col_idx = NULL, modes = NULL)

## S4 method for signature 'DelayedArray'
fold(mat, row_idx, col_idx, modes)

Arguments

mat	DelayedArray object (only 2D)
row_idx	the indices of the modes that are mapped onto the row space
col_idx	the indices of the modes that are mapped onto the column space
modes	the modes of the output DelayedArray

Details

This function is an extension of the fold by DelayedArray.

Value

DelayedArray object with modes given by modes

References

T. Kolda, B. Bader, "Tensor decomposition and applications". SIAM Applied Mathematics and Applications 2009.

See Also

unfold, k_fold, unmatvec, rs_fold, cs_fold

Examples

library("DelayedRandomArray")
darr <- RandomUnifArray(c(2,3,4))
matT3 <- DelayedTensor::unfold(darr, row_idx=2, col_idx=c(3,1))
identical(
    as.array(DelayedTensor::fold(matT3, row_idx=2,col_idx=c(3,1),
        modes=c(2,3,4))),
    as.array(darr))

rikenbit/DelayedTensor documentation built on Jan. 30, 2023, 6:15 p.m.