`tensorly.parafac2_tensor`.parafac2_to_vec

parafac2_to_vec(parafac2_tensor)[source]

Construct a vectorized tensor from a PARAFAC2 decomposition. Uneven slices are padded by zeros.

The decomposition is on the form $(A [B_i] C)$ such that the i-th frontal slice, $X_i$ , of $X$ is given by

$X_i = B_i diag(a_i) C^T,$

where $diag(a_i)$ is the diagonal matrix whose nonzero entries are equal to the $i$ -th row of the $I \times R$ factor matrix $A$ , $B_i$ is a $J_i \times R$ factor matrix such that the cross product matrix $B_{i_1}^T B_{i_1}$ is constant for all $i$ , and $C$ is a $K \times R$ factor matrix. To compute this decomposition, we reformulate the expression for $B_i$ such that

$B_i = P_i B,$

where $P_i$ is a $J_i \times R$ orthogonal matrix and $B$ is a $R \times R$ matrix.

An alternative formulation of the PARAFAC2 decomposition is that the tensor element $X_{ijk}$ is given by

$X_{ijk} = \sum_{r=1}^R A_{ir} B_{ijr} C_{kr},$

with the same constraints hold for $B_i$ as above.

Parameters:	parafac2_tensorParafac2Tensor - (weight, factors, projection_matrices) weights1D array of shape (rank, ) weights of the factors factorsList of factors of the PARAFAC2 decomposition Contains the matrices $A$ , $B$ and $C$ described above projection_matricesList of projection matrices used to create evolving factors.
Returns:	ndarray Full constructed tensor. Uneven slices are padded with zeros.

tensorly.parafac2_tensor.parafac2_to_vec

`tensorly.parafac2_tensor`.parafac2_to_vec