Parameters: |
- A (Candecomp,ndarray,TT) – Available input formats are Candecomp, full tensor in numpy.ndarray, Tensor Train structure (list of cores), list of sparse matrices of sizes (r_{i-1}*r_{i}*nrows x ncols) (used for fast dot product - limited support for other functionalities)
- nrows (list,int) – If int then the row size will be the same in all dimensions, if list then len(nrows) == len(self.TT) (numer of cores) and row size will change for each dimension.
- ncols (list,int) – If int then the column size will be the same in all dimensions, if list then len(ncols) == len(self.TT) (numer of cores) and column size will change for each dimension.
- is_sparse (bool) – [default == False] if True it uses sparsity to accelerate some computations
- sparse_ranks (list) – [default==None] mandatory argument when A is a list of sparse matrices. It contains integers listing the TT-ranks of the matrix.
|