TTSVD

# Import statement

from hottbox.algorithms.decomposition import TTSVD

class TTSVD(verbose=False)

Tensor Train Decomposition.

Parameters

verbosebool

Attributes

name	Name of the decomposition

converged

Methods

copy(self)	Copy of the Decomposition as a new object
decompose(self, tensor, rank[, keep_meta])	Performs TT-SVD on the tensor with respect to the specified rank

plot

copy(self)

Copy of the Decomposition as a new object

decompose(self, tensor, rank, keep_meta=0)

Performs TT-SVD on the tensor with respect to the specified rank

Parameters

tensorTensor

Multidimensional data to be decomposed

ranktuple

Desired tt-rank for the given tensor

keep_metaint

Keep meta information about modes of the given tensor. 0 - the output will have default values for the meta data 1 - keep only mode names 2 - keep mode names and indices

Returns

tensor_ttTensorTT

Tensor train representation of the tensor

Notes

Reshaping of the data is performed with respect to the FORTRAN ordering. This makes it easy to compare results with the MATLAB implementation by Oseledets. This doesn’t really matter (apart from time it takes to compute), as long as we do exactly the opposite for the reconstruction

property name

Name of the decomposition

Returns

decomposition_namestr