R6 Class for Sparse Matricized Tensors (Sptenmat)

A sparse matricization of an Sptensor: the nonzeros of the tensor mapped to (row, column) coordinates of the unfolding defined by rdims/cdims, mirroring the MATLAB Tensor Toolbox sptenmat.

Usage

sptenmat(x, rdims = NULL, cdims = NULL)

Arguments

x: An Sptensor.
rdims: Modes mapped to matrix rows.
cdims: Modes mapped to matrix columns.

Value

An Sptenmat object.

Public fields

subs: Two-column integer matrix of (row, col) coordinates
vals: Numeric vector of nonzero values
rdims: Tensor modes mapped to matrix rows
cdims: Tensor modes mapped to matrix columns
tsize: Dimensions of the original tensor

Methods

`Sptenmat$new()`

Initialize a new Sptenmat from a sparse tensor

Usage

Sptenmat$new(x = NULL, rdims = NULL, cdims = NULL)

Arguments

x: An Sptensor.
rdims: Modes mapped to rows.
cdims: Modes mapped to columns (defaults to the remaining modes in ascending order).

Returns

A new Sptenmat object

`Sptenmat$dim()`

Matrix dimensions of the unfolding

Usage

Sptenmat$dim()

Returns

Integer vector c(nrow, ncol)

`Sptenmat$print()`

Print the Sptenmat object

Usage

Sptenmat$print(...)

Arguments

...: Additional arguments

Returns

Invisible self

`Sptenmat$as_matrix()`

Convert to a dense matrix

Usage

Sptenmat$as_matrix()

Returns

A dense matrix of the unfolding

`Sptenmat$clone()`

The objects of this class are cloneable with this method.

Usage

Sptenmat$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

S <- sptenrand(c(4, 3, 2), 5)
A <- sptenmat(S, rdims = 1)