tnpy.tsdrg.Node
4.1. tnpy.tsdrg.Node#
- class tnpy.tsdrg.Node(node_id, left=None, right=None, *args, **kwargs)[source]#
Bases:
quimb.tensor.tensor_core.Tensor
The node of binary tree, while data structure is inherited from
quimb.Tensor
.- Parameters
- __init__(node_id, left=None, right=None, *args, **kwargs)[source]#
The node of binary tree, while data structure is inherited from
quimb.Tensor
.- Parameters
node_id (int) – An integer ID of this node.
left (Optional[tnpy.tsdrg.Node]) – The left child node. Default None.
right (Optional[tnpy.tsdrg.Node]) – The right child node. Default None.
*args – Arguments to initialize
quimb.Tensor
.**kwargs – Keywords to initialize
quimb.Tensor
.
Methods
__init__
(node_id[, left, right])The node of binary tree, while data structure is inherited from
quimb.Tensor
.add_owner
(tn, tid)Add
tn
as owner of this Tensor - it's tag and ind maps will be updated whenever this tensor is retagged or reindexed.add_tag
(tag)Add a tag to this tensor.
almost_equals
(other, **kwargs)Check if this tensor is almost the same as another.
astype
(dtype[, inplace])Change the type of this tensor to
dtype
.astype_
(dtype, *[, inplace])bonds
(other)Return a tuple of the shared indices between this tensor and
other
.check_owners
()Check if this tensor is 'owned' by any alive TensorNetworks.
collapse_repeated
([inplace])Take the diagonals of any repeated indices, such that each index only appears once.
collapse_repeated_
(*[, inplace])conj
([inplace])Conjugate this tensors data (does nothing to indices).
conj_
(*[, inplace])contract
(*[, output_inds, get, backend, ...])Efficiently contract multiple tensors, combining their tags.
copy
([deep, virtual])Copy this tensor.
direct_product
(T2[, sum_inds, inplace])Direct product of two Tensors.
direct_product_
(T2[, sum_inds, inplace])distance
(tnB[, xAA, xAB, xBB, method])Compute the Frobenius norm distance between two tensor networks:
draw
(*args, **kwargs)Plot a graph of this tensor and its indices.
drop_tags
([tags])Drop certain tags, defaulting to all, from this tensor.
entropy
(left_inds[, method])Return the entropy associated with splitting this tensor according to
left_inds
.expand_ind
(ind, size)Inplace increase the size of the dimension of
ind
, the new array entries will be filled with zeros.filter_bonds
(other)Sort this tensor's indices into a list of those that it shares and doesn't share with another tensor.
flip
(ind[, inplace])Reverse the axis on this tensor corresponding to
ind
.flip_
(ind, *[, inplace])fuse
(fuse_map[, inplace])Combine groups of indices into single indices.
fuse_
(fuse_map, *[, inplace])gate
(G, ind[, inplace])Gate this tensor - contract a matrix into one of its indices without changing its indices.
gate_
(G, ind, *[, inplace])graph
(*args, **kwargs)Plot a graph of this tensor and its indices.
ind_size
(ind)Return the size of dimension corresponding to
ind
.inner_inds
()iscomplex
()isel
(selectors[, inplace])Select specific values for some dimensions/indices of this tensor, thereby removing them.
isel_
(selectors, *[, inplace])largest_element
()Return the largest element, in terms of absolute magnitude, of this tensor.
max_dim
()Return the maximum size of any dimension, or 1 if scalar.
modify
(**kwargs)Overwrite the data of this tensor in place.
multiply_index_diagonal
(ind, x[, inplace])Multiply this tensor by 1D array
x
as if it were a diagonal tensor being contracted into indexind
.multiply_index_diagonal_
(ind, x, *[, inplace])new_bond
(T2[, size, name, axis1, axis2])Inplace addition of a new bond between tensors
T1
andT2
.new_ind
(name[, size, axis])Inplace add a new index - a named dimension.
new_ind_with_identity
(name, left_inds, ...)Inplace add a new index, where the newly stacked array entries form the identity from
left_inds
toright_inds
.norm
()Frobenius norm of this tensor:
normalize
([inplace])normalize_
(*[, inplace])randomize
([dtype, inplace])Randomize the entries of this tensor.
randomize_
([dtype, inplace])reindex
(index_map[, inplace])Rename the indices of this tensor, optionally in-place.
reindex_
(index_map, *[, inplace])remove_owner
(tn)Remove TensorNetwork
tn
as an owner of this Tensor.retag
(retag_map[, inplace])Rename the tags of this tensor, optionally, in-place.
retag_
(retag_map, *[, inplace])shared_bond_size
(other)Get the total size of the shared index(es) with
other
.singular_values
(left_inds[, method])Return the singular values associated with splitting this tensor according to
left_inds
.split
(left_inds[, method, get, absorb, ...])Decompose this tensor into two tensors.
squeeze
([include, inplace])Drop any singlet dimensions from this tensor.
squeeze_
([include, inplace])sum_reduce
(ind[, inplace])Sum over index
ind
, removing it from this tensor.sum_reduce_
(ind, *[, inplace])symmetrize
(ind1, ind2[, inplace])Hermitian symmetrize this tensor for indices
ind1
andind2
.to_dense
(*inds_seq[, to_qarray])Convert this Tensor into an dense array, with a single dimension for each of inds in
inds_seqs
.trace
(left_inds, right_inds[, ...])Trace index or indices
left_inds
withright_inds
, removing them.transpose
(*output_inds[, inplace])Transpose this tensor - permuting the order of both the data and the indices.
transpose_
(*output_inds[, inplace])transpose_like
(other[, inplace])Transpose this tensor to match the indices of
other
, allowing for one index to be different.transpose_like_
(other, *[, inplace])unfuse
(unfuse_map, shape_map[, inplace])Reshape single indices into groups of multiple indices
unfuse_
(unfuse_map, shape_map, *[, inplace])unitize
([left_inds, inplace, method])Make this tensor unitary (or isometric) with respect to
left_inds
.unitize_
([left_inds, inplace, method])Attributes
H
Conjugate this tensors data (does nothing to indices).
data
dtype
inds
left_inds
ndim
owners
shape
size
tags
- __init__(node_id, left=None, right=None, *args, **kwargs)[source]#
The node of binary tree, while data structure is inherited from
quimb.Tensor
.- Parameters
node_id (int) – An integer ID of this node.
left (Optional[tnpy.tsdrg.Node]) – The left child node. Default None.
right (Optional[tnpy.tsdrg.Node]) – The right child node. Default None.
*args – Arguments to initialize
quimb.Tensor
.**kwargs – Keywords to initialize
quimb.Tensor
.
- property node_id: int#
- property left: tnpy.tsdrg.Node | None#
- property right: tnpy.tsdrg.Node | None#
- property is_leaf: bool#