def ghost_to_view(self, idxs):
""" This maps the index from the current ghost shape of the view to the view shape.
:param list idxs_in: list of indices to be transformed
.. note:: no slicing is admitted here. Preprocess ``idxs`` with :py:meth:`expand_idxs` if slicing is required.
"""
if self.maps[self.view]['Q'] != None:
return tuple([(i if i < N else N - 1) for i, N in zip(
self.ghost_to_extended(idxs), self.get_view_shape())])
else:
idxs = idxfold(self.get_view_shape(),
idxunfold(self.get_ghost_shape(), idxs))
return tuple(idxs)
def __getitem__(self, idxs):
""" Get item function
:param tuple,int idxs: ((i_1,..,i_d),(j_1,..,j_d)) with respect to the unfolded mode sizes
:returns: item at that position
"""
if not self.init:
raise NameError(
"TensorToolbox.QTTmat.__getitem__: QTT not initialized correctly"
)
# Check for out of bounds
if any(map(operator.ge, idxs[0], self.get_full_nrows())) or any(
map(operator.ge, idxs[1], self.get_full_ncols())):
raise NameError(
"TensorToolbox.QTTmat.__getitem__: Index out of bounds")
# Compute the index of the folding representation from the unfolded index
return TTmat.__getitem__(
self, (idxfold(self.get_nrows(),
idxunfold(self.get_full_nrows(), idxs[0])),
idxfold(self.get_ncols(),
idxunfold(self.get_full_ncols(), idxs[1]))))
def view_to_ghost(self, idxs):
""" This maps the index from the view to the ghost shape.
:param list idxs: list of indices to be transformed
.. note:: no slicing is admitted here. Preprocess ``idxs`` with :py:meth:`expand_idxs` if slicing is required.
.. note:: this returns an error if the ghost shape is obtained by quantics folding, because the one view index can be pointing to many indices in the folding.
"""
if self.maps[self.view]['Q'] != None:
raise NotImplemented(
"This operation is undefined because one view idx can point to many q indices"
)
else:
return idxfold(self.get_ghost_shape(),
idxunfold(self.get_view_shape(), idxs))
def __getitem__(self, idxs):
""" Get item function: indexes are entered in with respect to the unfolded mode sizes.
"""
if not self.init:
raise NameError(
"TensorToolbox.QTTvec.__getitem__: QTT not initialized correctly"
)
# Check whether index out of bounds
if any(map(operator.ge, idxs, self.get_global_shape())):
raise NameError(
"TensorToolbox.QTTvec.__getitem__: Index out of bounds")
# Compute the index of the folding representation from the unfolded representation
return TTvec.__getitem__(
self,
idxfold(self.shape(), idxunfold(self.get_global_shape(), idxs)))
def full_to_q(self, idxs):
return idxfold(self.get_q_shape(), idxunfold(self.shape(), idxs))
def q_to_full(self, idxs):
return idxfold(self.shape(), idxunfold(self.get_q_shape(), idxs))
def ghost_to_extended(self, idxs):
return idxfold(self.get_extended_shape(),
idxunfold(self.get_ghost_shape(), idxs))