ut3variations_to_t3variations

t3toolbox.backend.ufv_conversions.ut3variations_to_t3variations(x)

def ut3variations_to_t3variations(
        x: typ.Tuple[
            NDArray,                          # tucker_variations,  (d,)+C+(nD, N)
            NDArray,                          # tt_variations,      (d,)+C+(rL, nU, rR)
            typ.Tuple[int, ...],              # shape
            typ.Tuple[                        # (variations up, down, left, right) masks
                NDArray, NDArray, NDArray, NDArray,
            ],
        ],
) -> typ.Union[
    typ.Tuple[typ.Tuple[NDArray, ...], typ.Tuple[NDArray, ...]],  # (tucker_variations, tt_variations), if unstacked
    typ.Tuple,                                                    # else a nested tree (shape stack_shape) of those
]:

Convert uniform UT3Variations .data to ragged T3Variations core-tuples (or a tree, if stacked).

Variations twin of ut3frame_to_t3frame(). The physical mode dim is a prefix (slices [:Ni] from shape); the rank masks scatter, so they extract with np.argwhere (HOST numpy). The variation tt-core H_i has shape (rLi, nUi, rR(i+1)) – left/up/right masks index its three axes.

Parameters:

x (t3toolbox.backend.common.typ.Tuple[NDArray, NDArray, t3toolbox.backend.common.typ.Tuple[int, Ellipsis], t3toolbox.backend.common.typ.Tuple[NDArray, NDArray, NDArray, NDArray]])

Return type:

t3toolbox.backend.common.typ.Union[t3toolbox.backend.common.typ.Tuple[t3toolbox.backend.common.typ.Tuple[NDArray, Ellipsis], t3toolbox.backend.common.typ.Tuple[NDArray, Ellipsis]], t3toolbox.backend.common.typ.Tuple]