unfold-methods | R Documentation |

Unfolds the tensor into a matrix, with the modes in `rs`

onto the rows
and modes in `cs`

onto the columns. Note that `c(rs,cs)`

must have the same elements (order doesn't matter) as `dim(darr)`

.
Within the rows and columns, the order of the unfolding is determined
by the order of the modes.
This convention is consistent with Kolda and Bader (2009).

unfold(darr, row_idx, col_idx) ## S4 method for signature 'DelayedArray' unfold(darr, row_idx, col_idx)

`darr` |
DelayedArray object |

`row_idx` |
the indices of the modes to map onto the row space |

`col_idx` |
the indices of the modes to map onto the column space |

This function is an extension of the `unfold`

by DelayedArray.

For Row Space Unfolding or m-mode Unfolding,
see `rs_unfold`

.
For Column Space Unfolding or matvec,
see `cs_unfold`

.

`vec`

returns the vectorization of the tensor.

2D DelayedArray with `prod(row_idx)`

rows and `prod(col_idx)`

columns

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

`k_unfold`

, `matvec`

,
`rs_unfold`

, `cs_unfold`

library("DelayedRandomArray") darr <- RandomUnifArray(c(2,3,4)) unfold(darr, row_idx=2, col_idx=c(3,1))

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.