TuckerTensorTrain.concatenate

static t3toolbox.tucker_tensor_train.TuckerTensorTrain.concatenate(xx)

def concatenate(
        xx: Sequence['TuckerTensorTrain'],
) -> 'TuckerTensorTrain':

Concatenates TuckerTensorTrain segments.

Parameters:

xx (Sequence[TuckerTensorTrain]) – TuckerTensorTrain segments to be concatenated

Returns:

Concatenated TuckerTensorTrain.

Return type:

TuckerTensorTrain

Raises:

ValueError – If segments have incompatible leading and trailing TT ranks. I.e., if x[ii].tt_ranks[-1] != x[ii+1].tt_ranks[0].

See also

TuckerTensorTrain.segment()

Examples

>>> import numpy as np
>>> import t3toolbox.tucker_tensor_train as t3
>>> np.random.seed(0)
>>> randn = np.random.randn
>>> tk = (randn(4,14), randn(5,15), randn(6,16), randn(7,17), randn(8,18), randn(9,19))
>>> tt = (randn(2,4,3), randn(3,5,2), randn(2,6,2), randn(2,7,3), (randn(3,8,4)), (randn(4,9,1)))
>>> x = t3.TuckerTensorTrain(tk[:3], tt[:3])
>>> y = t3.TuckerTensorTrain(tk[3:4], tt[3:4])
>>> z = t3.TuckerTensorTrain(tk[4:], tt[4:])
>>> xyz = t3.TuckerTensorTrain.concatenate([x, y, z])
>>> xyz2 = t3.TuckerTensorTrain(tk, tt)              # the same train, built in one piece
>>> print(np.allclose(xyz.to_dense(), xyz2.to_dense()))
True