An Enhanced tensor specifically designed for physical Tensor network simulation. More...

#include <UniTensor.hpp>

Public Member Functions
	UniTensor (const Tensor &in_tensor, const bool &is_diag=false, const cytnx_int64 &rowrank=-1, const std::vector< std::string > &in_labels={}, const std::string &name="")
	Construct a UniTensor from a cytnx::Tensor.

void	Init (const Tensor &in_tensor, const bool &is_diag=false, const cytnx_int64 &rowrank=-1, const std::vector< std::string > &in_labels={}, const std::string &name="")
	Initialize a UniTensor from a cytnx::Tensor.

	UniTensor (const std::vector< Bond > &bonds, const std::vector< std::string > &in_labels={}, const cytnx_int64 &rowrank=-1, const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const bool &is_diag=false, const std::string &name="")
	Construct a UniTensor.

UniTensor &	Init (const std::vector< Bond > &bonds, const std::vector< std::string > &in_labels={}, const cytnx_int64 &rowrank=-1, const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const bool &is_diag=false, const std::string &name="")
	Initialize the UniTensor with the given arguments.

UniTensor &	set_name_ (const std::string &in)
	Set the name of a UniTensor, in-place.

UniTensor &	set_name (const std::string &in)

UniTensor &	set_label_ (const cytnx_int64 &idx, const std::string &new_label)
	Set a new label for bond at the assigned index, in-place.

UniTensor &	set_label_ (const cytnx_int64 &idx, const char *new_label)

UniTensor &	set_label_ (const std::string &old_label, const std::string &new_label)
	set a new label for bond to replace one of the current label, in-place.

UniTensor &	set_label_ (const char *old_label, const std::string &new_label)

UniTensor &	set_label_ (const std::string &old_label, const char *new_label)

UniTensor &	set_label_ (const char old_label, const char new_label)

UniTensor &	set_label (const cytnx_int64 &idx, const std::string &new_label)

UniTensor &	set_label (const cytnx_int64 &idx, const char *new_label)

UniTensor &	set_label (const std::string &old_label, const std::string &new_label)

UniTensor &	set_label (const char *old_label, const std::string &new_label)

UniTensor &	set_label (const std::string &old_label, const char *new_label)

UniTensor &	set_label (const char old_label, const char new_label)

UniTensor &	set_labels (const std::vector< std::string > &new_labels)

UniTensor &	set_labels (const std::initializer_list< char * > &new_labels)

UniTensor &	set_rowrank_ (const cytnx_uint64 &new_rowrank)
	Set the rowrank of the UniTensor.

UniTensor	set_rowrank (const cytnx_uint64 &new_rowrank) const

template<class T >
T &	item ()

Scalar::Sproxy	item () const

cytnx_uint64	Nblocks () const
	Return the number of blocks in the UniTensor.

cytnx_uint64	rank () const
	Return the rank of the UniTensor.

cytnx_uint64	rowrank () const
	Return the row rank of the UniTensor.

unsigned int	dtype () const
	Return the data type of the UniTensor.

int	uten_type () const
	Return the UniTensor type (cytnx::UTenType) of the UniTensor.

bool	is_void () const
	Return whether the UniTensor is uninitialized.

bool	is_scalar () const
	whether the UniTensor is an initialized rank-0 scalar UniTensor

cytnx_uint64	size () const
	Return the total number of logical elements in the UniTensor.

bool	is_empty () const
	whether the UniTensor is initialized and has no logical elements

int	device () const
	Return the device of the UniTensor.

std::string	name () const
	Return the name of the UniTensor.

std::string	dtype_str () const
	Return the data type of the UniTensor in 'string' form.

std::string	device_str () const
	Return the device of the UniTensor in 'string' form.

std::string	uten_type_str () const
	Return the UniTensor type (cytnx::UTenType) of the UniTensor in 'string' form.

bool	is_contiguous () const
	To tell whether the UniTensor is contiguous.

bool	is_diag () const
	To tell whether the UniTensor is in diagonal form.

bool	is_tag () const
	To tell whether the UniTensor is tagged. That is, all of the Bond in the UniTensor is directional (all of them are bondType.BD_KET or bondType.BD_BRA)

std::vector< Symmetry >	syms () const
	Return the symmetry type of the UniTensor.

const bool &	is_braket_form () const
	Check whether the UniTensor is in braket form.

const std::vector< std::string > &	labels () const
	Return the labels of the UniTensor.

cytnx_int64	get_index (std::string label) const
	Get the index of an desired label string.

const std::vector< Bond > &	bonds () const
	Get the bonds of the UniTensor.

const Bond &	bond_ (const cytnx_uint64 &idx) const

Bond &	bond_ (const cytnx_uint64 &idx)

const Bond &	bond_ (const std::string &label) const

Bond &	bond_ (const std::string &label)

Bond	bond (const cytnx_uint64 &idx) const

Bond	bond (const std::string &label) const

std::vector< cytnx_uint64 >	shape () const
	Get the shape of the UniTensor.

std::vector< bool >	signflip () const
	Get the sign information of a fermionic UniTensor.

bool	is_blockform () const
	Check whether the UniTensor is in block form.

UniTensor &	to_ (const int &device)
	move the current UniTensor to the assigned device (inplace).

UniTensor	to (const int &device) const
	move the current UniTensor to the assigned device.

UniTensor	clone () const
	Clone (deep copy) the UniTensor.

UniTensor &	relabel_ (const std::vector< std::string > &new_labels)
	Set new labels for all the bonds.

UniTensor &	relabels_ (const std::vector< std::string > &new_labels)

UniTensor	relabel (const std::vector< std::string > &new_labels) const
	relabel all of the labels in UniTensor.

UniTensor	relabels (const std::vector< std::string > &new_labels) const

UniTensor	relabel (const std::initializer_list< char * > &new_labels) const
	relables all of the labels in UniTensor.

UniTensor	relabels (const std::initializer_list< char * > &new_labels) const

UniTensor &	relabel_ (const std::initializer_list< char * > &new_labels)

UniTensor &	relabels_ (const std::initializer_list< char * > &new_labels)

UniTensor	relabel (const std::vector< std::string > &old_labels, const std::vector< std::string > &new_labels) const
	replace part or all labels by given new labels for the bonds.

UniTensor	relabels (const std::vector< std::string > &old_labels, const std::vector< std::string > &new_labels) const

UniTensor &	relabel_ (const std::vector< std::string > &old_labels, const std::vector< std::string > &new_labels)
	relabel part or all of the labels in UniTensor by given new labels

UniTensor &	relabels_ (const std::vector< std::string > &old_labels, const std::vector< std::string > &new_labels)

UniTensor	relabel (const std::initializer_list< char * > &old_labels, const std::initializer_list< char * > &new_labels) const

UniTensor	relabels (const std::initializer_list< char * > &old_labels, const std::initializer_list< char * > &new_labels) const

UniTensor &	relabel_ (const std::initializer_list< char * > &old_labels, const std::initializer_list< char * > &new_labels)

UniTensor &	relabels_ (const std::initializer_list< char * > &old_labels, const std::initializer_list< char * > &new_labels)

UniTensor	relabel (const cytnx_int64 &inx, const std::string &new_label) const
	rebabel the legs in the UniTensor by given index.

UniTensor &	relabel_ (const cytnx_int64 &inx, const std::string &new_label)
	rebable the legs in the UniTensor by given index.

UniTensor &	relabel_ (const std::string &old_label, const std::string &new_label)
	relabel the legs in the UniTensor by a given label.

UniTensor	relabel (const std::string &old_label, const std::string &new_label) const
	relabel the legs in the UniTensor by a given label.

UniTensor	astype (const unsigned int &dtype) const
	Return a new UniTensor whose elements are casted to a different data type.

UniTensor	permute (const std::vector< cytnx_int64 > &mapper, const cytnx_int64 &rowrank=-1) const
	permute the legs of the UniTensor

UniTensor	permute (const std::vector< std::string > &mapper, const cytnx_int64 &rowrank=-1) const
	permute the legs of the UniTensor by labels

UniTensor	permute (const std::initializer_list< char * > &mapper, const cytnx_int64 &rowrank=-1) const

UniTensor &	permute_ (const std::vector< cytnx_int64 > &mapper, const cytnx_int64 &rowrank=-1)
	permute the legs of the UniTensor, inplacely.

UniTensor &	permute_ (const std::vector< std::string > &mapper, const cytnx_int64 &rowrank=-1)
	permute the legs of the UniTensor, inplacely.

UniTensor	permute_nosignflip (const std::vector< cytnx_int64 > &mapper, const cytnx_int64 &rowrank=-1) const
	permute the legs of the UniTensor without sign flips

UniTensor	permute_nosignflip (const std::vector< std::string > &mapper, const cytnx_int64 &rowrank=-1) const
	permute the legs of the UniTensor by labels without sign flips

UniTensor	permute_nosignflip (const std::initializer_list< char * > &mapper, const cytnx_int64 &rowrank=-1) const

UniTensor &	permute_nosignflip_ (const std::vector< cytnx_int64 > &mapper, const cytnx_int64 &rowrank=-1)
	permute the legs of the UniTensor without fermionic sign flips, inplacely.

UniTensor &	permute_nosignflip_ (const std::vector< std::string > &mapper, const cytnx_int64 &rowrank=-1)
	permute the legs of the UniTensor without fermionic sign flips, inplacely.

UniTensor	twist (const std::string &label) const
	Apply a twist (or braids/self-swap) operation to a given bond; No effect for bosonic tensors; for a fermionic tensor, this means that a signflip occurs for all blocks where the bond has odd fermion parity.

UniTensor	twist (const cytnx_int64 &idx) const
	Apply a twist (or braids/self-swap) operation to a given bond; No effect for bosonic tensors; for a fermionic tensor, this means that a signflip occurs for all blocks where the bond has odd fermion parity.

UniTensor &	twist_ (const std::string &label)
	Inline version.

UniTensor &	twist_ (const cytnx_int64 &idx)
	Inline version.

UniTensor	fermion_twists () const
	Apply twists to all right bonds (>= rowrank) with bond type BD_KET.

UniTensor &	fermion_twists_ ()
	Inline version.

UniTensor	contiguous () const
	Make the UniTensor contiguous by coalescing the memory (storage).

UniTensor &	contiguous_ ()
	Make the UniTensor contiguous by coalescing the memory (storage), inplacely.

UniTensor	apply () const
	Apply fermionic signflips to the UniTensor, such that all elements calling signflip() on the output tensor will result in all elements to be false.

UniTensor &	apply_ ()
	Apply fermionic signflips to the UniTensor, inplacely. Subsequently, all elements returned by signflip() are false.

void	print_diagram (const bool &bond_info=false) const
	Plot the diagram of the UniTensor.

void	print_blocks (const bool &full_info=true) const
	Print all blocks of the UniTensor.

void	print_block (const cytnx_int64 &idx, const bool &full_info=true) const
	Print out the block of the UniTensor with a given block index number.

UniTensor &	group_basis_ ()
	Group the same quantum number basis together.

UniTensor	group_basis () const

template<class T >
T &	at (const std::vector< cytnx_uint64 > &locator)
	Get an element at a specific location.

template<class T >
const T &	at (const std::vector< cytnx_uint64 > &locator) const
	Get an element at a specific location.

template<class T >
const T &	at (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &locator) const

template<class T >
T &	at (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &locator)

const Scalar::Sproxy	at (const std::vector< cytnx_uint64 > &locator) const
	Get an element at a specific location.

Scalar::Sproxy	at (const std::vector< cytnx_uint64 > &locator)
	Get an element at a specific location.

Scalar::Sproxy	at (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &locator)

const Scalar::Sproxy	at (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &locator) const

Tensor	get_block (const cytnx_uint64 &idx=0) const
	Get the block of the UniTensor for a given block index.

Tensor	get_block (const std::vector< cytnx_int64 > &qidx, const bool &force=false) const
	Get the block of the UniTensor for the given quantun indices.

Tensor	get_block (const std::vector< std::string > &labels, const std::vector< cytnx_int64 > &qidx, const bool &force=false) const

Tensor	get_block (const std::initializer_list< cytnx_int64 > &qnum, const bool &force=false) const

Tensor	get_block (const std::vector< cytnx_uint64 > &qnum, const bool &force=false) const

Tensor	get_block (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &qidx, const bool &force=false) const

const Tensor &	get_block_ (const cytnx_uint64 &idx=0) const
	Get the shared view of the block for the given block index.

Tensor &	get_block_ (const cytnx_uint64 &idx=0)

Tensor &	get_block_ (const std::vector< cytnx_int64 > &qidx, const bool &force=false)
	Get the shared view of the block for the given quantum indices.

Tensor	get_block_ (const std::vector< std::string > &labels, const std::vector< cytnx_int64 > &qidx, const bool &force=false)
	Get the shared (data) view of the block for the given quantum indices on given labels.

Tensor &	get_block_ (const std::initializer_list< cytnx_int64 > &qidx, const bool &force=false)

Tensor &	get_block_ (const std::vector< cytnx_uint64 > &qidx, const bool &force=false)

Tensor	get_block_ (const std::vector< std::string > &labels, const std::vector< cytnx_uint64 > &qidx, const bool &force=false)

const Tensor &	get_block_ (const std::vector< cytnx_int64 > &qidx, const bool &force=false) const

const Tensor &	get_block_ (const std::initializer_list< cytnx_int64 > &qidx, const bool &force=false) const

const Tensor &	get_block_ (const std::vector< cytnx_uint64 > &qidx, const bool &force=false) const

std::vector< Tensor >	get_blocks () const
	Get all the blocks of the UniTensor.

const std::vector< Tensor > &	get_blocks_ (const bool &silent=false) const
	Get all the blocks of the UniTensor, inplacely.

std::vector< Tensor > &	get_blocks_ (const bool &silent=false)

UniTensor &	put_block (const Tensor &in, const cytnx_uint64 &idx=0)
	Put the block into the UniTensor with given index.

UniTensor &	put_block (const Tensor &in, const cytnx_uint64 &idx, const bool &force)

UniTensor &	put_block (const Tensor &in_tens, const std::vector< cytnx_int64 > &qidx)
	Put the block into the UniTensor with given quantum number.

UniTensor &	put_block (const Tensor &in_tens, const std::vector< cytnx_int64 > &qidx, const bool &force)

UniTensor &	put_block (Tensor &in, const std::vector< std::string > &lbls, const std::vector< cytnx_int64 > &qidx)
	Put the block into the UniTensor with given quantum indices, will copy the input tensor.

UniTensor &	put_block (Tensor &in, const std::vector< std::string > &lbls, const std::vector< cytnx_int64 > &qidx, const bool &force)

UniTensor &	put_block_ (Tensor &in, const cytnx_uint64 &idx=0)
	Put the block into the UniTensor with given index, inplacely.

UniTensor &	put_block_ (Tensor &in, const std::vector< cytnx_int64 > &qidx)
	Put the block into the UniTensor with given quantum indices, inplacely.

UniTensor &	put_block_ (Tensor &in, const std::vector< cytnx_int64 > &qidx, const bool &force)

UniTensor &	put_block_ (Tensor &in, const std::vector< std::string > &lbls, const std::vector< cytnx_int64 > &qidx)
	Put the block into the UniTensor with given quantum indices, inplacely.

UniTensor &	put_block_ (Tensor &in, const std::vector< std::string > &lbls, const std::vector< cytnx_int64 > &qidx, const bool &force)

UniTensor	get (const std::vector< Accessor > &accessors) const
	get elements using Accessor (C++ API) / slices (python API)

UniTensor	operator[] (const std::vector< cytnx::Accessor > &accessors) const
	get elements using Accessor (C++ API) / slices (python API)

UniTensor	operator[] (const std::initializer_list< cytnx::Accessor > &accessors) const

UniTensor	operator[] (const std::vector< cytnx_int64 > &accessors) const

UniTensor	operator[] (const std::initializer_list< cytnx_int64 > &accessors) const

UniTensor &	set (const std::vector< Accessor > &accessors, const Tensor &rhs)
	set elements using Accessor (C++ API) / slices (python API)

UniTensor &	set (const std::vector< Accessor > &accessors, const UniTensor &rhs)

UniTensor	reshape (const std::vector< cytnx_int64 > &new_shape, const cytnx_uint64 &rowrank=0)
	Reshape the UniTensor.

UniTensor &	reshape_ (const std::vector< cytnx_int64 > &new_shape, const cytnx_uint64 &rowrank=0)
	Reshape the UniTensor, inplacely.

UniTensor	to_dense ()
	Convert the UniTensor to non-diagonal form.

UniTensor &	to_dense_ ()
	Convert the UniTensor to non-diagonal form, inplacely.

void	combineBonds (const std::vector< cytnx_int64 > &indicators, const bool &force, const bool &by_label)

void	combineBonds (const std::vector< std::string > &indicators, const bool &force=false)

void	combineBonds (const std::vector< cytnx_int64 > &indicators, const bool &force=false)

UniTensor &	combineBond_ (const std::vector< std::string > &indicators, const bool &force=false)
	Combine the sevral bonds of the UniTensor, in-place.

UniTensor	combineBond (const std::vector< std::string > &indicators, const bool &force=false) const
	Combine the sevral bonds of the UniTensor, out-of-place.

UniTensor	contract (const UniTensor &inR, const bool &mv_elem_self=false, const bool &mv_elem_rhs=false) const
	Contract the UniTensor with common labels.

bool	same_data (const UniTensor &rhs) const
	Check whether the Blocks address are the same.

UniTensor &	Add_ (const UniTensor &rhs)
	The addition function of the UniTensor.

UniTensor &	Mul_ (const UniTensor &rhs)
	The multiplcation function of the UniTensor.

UniTensor &	Sub_ (const UniTensor &rhs)
	The subtraction function of the UniTensor.

UniTensor &	Div_ (const UniTensor &rhs)
	The division function of the UniTensor.

UniTensor &	Add_ (const Scalar &rhs)
	The addition function for a given scalar.

UniTensor &	Mul_ (const Scalar &rhs)
	The multiplication function for a given scalar.

UniTensor &	Sub_ (const Scalar &rhs)
	The subtraction function for a given scalar.

UniTensor &	Div_ (const Scalar &rhs)
	The division function for a given scalar.

UniTensor	Add (const UniTensor &rhs) const
	The addition function of the UniTensor.

UniTensor	Add (const Scalar &rhs) const
	The addition function for a given scalar.

UniTensor	Mul (const UniTensor &rhs) const
	The multiplication function of the UniTensor.

UniTensor	Mul (const Scalar &rhs) const
	The multiplication function for a given scalar.

UniTensor	Div (const UniTensor &rhs) const
	The division function of the UniTensor.

UniTensor	Div (const Scalar &rhs) const
	The division function for a given scalar.

UniTensor	Sub (const UniTensor &rhs) const
	The subtraction function of the UniTensor.

UniTensor	Sub (const Scalar &rhs) const
	The subtraction function for a given scalar.

Tensor	Norm () const
	Return the norm of the UniTensor.

Scalar	norm () const
	Return the norm of the UniTensor.

UniTensor &	operator+= (const UniTensor &rhs)
	The addition assignment operator of the UniTensor.

UniTensor &	operator-= (const UniTensor &rhs)
	The subtraction assignment operator of the UniTensor.

UniTensor &	operator/= (const UniTensor &rhs)
	The division assignment operator of the UniTensor.

UniTensor &	operator*= (const UniTensor &rhs)
	The multiplication assignment operator of the UniTensor.

UniTensor &	operator+= (const Scalar &rhs)
	The addition assignment operator for a given scalar.

UniTensor &	operator-= (const Scalar &rhs)
	The subtraction assignment operator for a given scalar.

UniTensor &	operator/= (const Scalar &rhs)
	The division assignment operator for a given scalar.

UniTensor &	operator*= (const Scalar &rhs)
	The multiplication assignment operator for a given scalar.

UniTensor	Inv (double clip=-1.) const
	Element-wise (pseudo-)inverse.

UniTensor &	Inv_ (double clip=-1.)
	Element-wise (pseudo-)inverse, inplacely.

UniTensor	Conj () const
	Apply complex conjugate on each entry of the UniTensor.

UniTensor &	Conj_ ()
	Apply complex conjugate on each entry of the UniTensor.

UniTensor	Transpose () const
	Take the transpose of the UniTensor.

UniTensor &	Transpose_ ()
	Take the transpose of the UniTensor, inplacely.

UniTensor	normalize () const
	normalize the current UniTensor instance with 2-norm.

UniTensor &	normalize_ ()
	normalize the UniTensor, inplacely.

UniTensor	Trace (const std::string &a, const std::string &b) const
	Take the partial trace of the UniTensor.

UniTensor	Trace (const cytnx_int64 &a=0, const cytnx_int64 &b=1) const
	Take the partial trace of the UniTensor.

UniTensor &	Trace_ (const std::string &a, const std::string &b)
	Take the partial trace of the UniTensor, inplacely.

UniTensor &	Trace_ (const cytnx_int64 &a=0, const cytnx_int64 &b=1)
	Take the partial trace of the UniTensor, inplacely.

UniTensor	Dagger () const
	Take the conjugate transpose to the UniTensor.

UniTensor &	Dagger_ ()
	Take the conjugate transpose to the UniTensor, inplacely.

UniTensor &	tag_ ()
	Set the UniTensor as a tagged UniTensor, in-place.

UniTensor &	tag ()

UniTensor	Pow (const double &p) const
	Take the power `p` of all elements.

UniTensor &	Pow_ (const double &p)
	Take the power `p` of all elements, inplacely.

bool	elem_exists (const std::vector< cytnx_uint64 > &locator) const
	Given the locator, check if the element exists.

template<class T >
T	get_elem (const std::vector< cytnx_uint64 > &locator) const

template<class T2 >
UniTensor &	set_elem (const std::vector< cytnx_uint64 > &locator, const T2 &rc)

void	Save (const std::string &fname) const
	save a UniTensor to file

void	Save (const char *fname) const
	save a UniTensor to file

UniTensor &	truncate_ (const std::string &label, const cytnx_uint64 &dim)
	truncate bond dimension of the UniTensor by the given bond label and dimension.

UniTensor &	truncate_ (const cytnx_int64 &bond_idx, const cytnx_uint64 &dim)
	truncate bond dimension of the UniTensor by the given bond index and dimension.

UniTensor	truncate (const std::string &label, const cytnx_uint64 &dim) const
	truncate bond dimension of the UniTensor by the given bond label and dimension.

UniTensor	truncate (const cytnx_int64 &bond_idx, const cytnx_uint64 &dim) const
	truncate bond dimension of the UniTensor by the given bond index and dimension.

const std::vector< cytnx_uint64 > &	get_qindices (const cytnx_uint64 &bidx) const
	get the q-indices on each leg for the [bidx]-th block

std::vector< cytnx_uint64 > &	get_qindices (const cytnx_uint64 &bidx)
	get the q-indices on each leg for the [bidx]-th block

const vec2d< cytnx_uint64 > &	get_itoi () const
	get the q-indices on each leg for all the blocks

vec2d< cytnx_uint64 > &	get_itoi ()

UniTensor &	convert_from_ (const UniTensor &rhs, bool force=false, cytnx_double tol=0.)
	Copy data from a UniTensor of different type, in-place.

UniTensor &	convert_from (const UniTensor &rhs, bool force=false, cytnx_double tol=0.)

UniTensor &	normal_ (const double &mean, const double &std, const unsigned int &seed=cytnx::random::__static_random_device())
	Generate a one-bond UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution, inplacely.

UniTensor &	uniform_ (const double &low=0, const double &high=1, const unsigned int &seed=cytnx::random::__static_random_device())
	Generate a UniTensor with all elements are random numbers sampled from a uniform distribution, inplacely.

Static Public Member Functions
static UniTensor	Load (const std::string &fname)
	load a UniTensor from file

static UniTensor	Load (const char *fname)
	load a UniTensor from file

static UniTensor	zeros (const std::vector< cytnx_uint64 > &shape, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Generate a UniTensor with all elements set to zero.

static UniTensor	zeros (std::initializer_list< cytnx_uint64 > shape, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")

static UniTensor	identity (cytnx_uint64 dim, const std::vector< std::string > &in_labels={}, cytnx_bool is_diag=false, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Generate an identity UniTensor with two bonds.

static UniTensor	eye (cytnx_uint64 dim, const std::vector< std::string > &in_labels={}, cytnx_bool is_diag=false, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Generate a 2-bond identity UniTensor.

static UniTensor	ones (const std::vector< cytnx_uint64 > &shape, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Generate a UniTensor with all elements set to one.

static UniTensor	ones (std::initializer_list< cytnx_uint64 > shape, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")

static UniTensor	arange (cytnx_int64 Nelem, const std::vector< std::string > &in_labels={}, const std::string &name="")
	Create a rank-1 UniTensor with incremental unsigned integer elements in the range [0,Nelem).

static UniTensor	arange (cytnx_double start, cytnx_double end, cytnx_double step=1, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Create a rank-1 UniTensor with incremental elements in the range [`start`,`end`) with given step-size `step` between elements.

static UniTensor	linspace (cytnx_double start, cytnx_double end, cytnx_uint64 Nelem, bool endpoint=true, const std::vector< std::string > &in_labels={}, unsigned int dtype=Type.Double, int device=Device.cpu, const std::string &name="")
	Generate a one-bond UniTensor with all elements are evenly spaced numbers over a specified interval.

static UniTensor	normal (const cytnx_uint64 &Nelem, const double &mean, const double &std, const std::vector< std::string > &in_labels={}, const unsigned int &seed=cytnx::random::__static_random_device(), const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const std::string &name="")
	Generate a one-bond UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution.

static UniTensor	normal (const std::vector< cytnx_uint64 > &shape, const double &mean, const double &std, const std::vector< std::string > &in_labels={}, const unsigned int &seed=cytnx::random::__static_random_device(), const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const std::string &name="")
	Generate a UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution.

static UniTensor	uniform (const cytnx_uint64 &Nelem, const double &low, const double &high, const std::vector< std::string > &in_labels={}, const unsigned int &seed=cytnx::random::__static_random_device(), const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const std::string &name="")
	Generate a one-bond UniTensor with all elements are random numbers sampled from a uniform distribution.

static UniTensor	uniform (const std::vector< cytnx_uint64 > &shape, const double &low, const double &high, const std::vector< std::string > &in_labels={}, const unsigned int &seed=cytnx::random::__static_random_device(), const unsigned int &dtype=Type.Double, const int &device=Device.cpu, const std::string &name="")
	Generate a UniTensor with all elements are random numbers sampled from a uniform distribution.

Detailed Description

An Enhanced tensor specifically designed for physical Tensor network simulation.

Constructor & Destructor Documentation

◆ UniTensor() [1/2]

cytnx::UniTensor::UniTensor	(	const Tensor &	in_tensor,
		const bool &	is_diag = `false`,
		const cytnx_int64 &	rowrank = `-1`,
		const std::vector< std::string > &	in_labels = `{}`,
		const std::string &	name = `""`
	)

inlineexplicit

Construct a UniTensor from a cytnx::Tensor.

Parameters

[in]	in_tensor	a cytnx::Tensor
[in]	is_diag	whether the input Tensor `in_tensor` is a diagonal Tensor; this requires the input `in_tensor` to be 1D.
[in]	rowrank	the rowrank of the resulting UniTensor

Note

The constructed UniTensor will have the same rank as the input Tensor, with default labels, and a shared view (shared instance) of interal block as the input Tensor.
The constructed UniTensor is always untagged.

Attention: The internal block of the UniTensor is a referece to the input Tensor. That is, they share the same memory. If the elements of the UniTensor are changed, the original Tensor is also changed and vice-versa. Use Tensor.clone() if a shared view is not desired.

Example:

C++ API:

#include "cytnx.hpp"
#include <iostream>
 
using namespace cytnx;
 
int main(int argc, char* argv[]) {
  Tensor T = zeros({4, 4});
  UniTensor CyT = UniTensor(T, false, 2);  // create un-tagged CyTensor from Tensor
  CyT.print_diagram();
 
  std::cout << "before:" << std::endl;
  std::cout << T << std::endl;
  std::cout << CyT << std::endl;
 
  // Note that it is a shared view, so a change to CyT will affect Tensor T.
  CyT.at<cytnx_double>({0, 0}) = 1.456;
 
  std::cout << "after:" << std::endl;
  std::cout << T << std::endl;
  std::cout << CyT << std::endl;
 
  // If we want a new instance of memery, use clone at initialize:
  std::cout << "[non-share example]" << std::endl;
  UniTensor CyT_nonshare = UniTensor(T.clone(), false, 2);
 
  std::cout << "before:" << std::endl;
  std::cout << T << std::endl;
  std::cout << CyT_nonshare << std::endl;
 
  CyT_nonshare.at<cytnx_double>({1, 1}) = 2.345;
 
  std::cout << "after" << std::endl;
  std::cout << T << std::endl;  // T is unchanged!
  std::cout << CyT_nonshare << std::endl;
 
  return 0;
}

output>

-----------------------
tensor Name :
tensor Rank : 2
block_form  : false
is_diag     : False
on device   : cytnx device: CPU
            -------------
           /             \
     0 ____| 4           |
           |             |
     1 ____| 4           |
           \             /
            -------------
before:

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]


-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



after:

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]


-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



[non-share example]
before:

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]


-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



after

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]


-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 2.34500e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]

Python API:

import sys
from pathlib import Path
home = str(Path.home())
sys.path.append(home + '/Cytnx_lib')
from cytnx import *
 
 
T = zeros([4,4])
CyT = UniTensor(T).set_rowrank_(2) #create un-tagged UniTensor from Tensor
CyT.print_diagram()
 
print("before:")
print(T)
print(CyT)
 
#Note that it is a shared view, so a change to CyT will affect Tensor T.
CyT.set_elem([0,0],1.456)
 
print("after")
print(T)
print(CyT)
 
#If we want a new instance of memery, use clone at initialize:
print("[non-share example]")
CyT_nonshare = UniTensor(T.clone()).set_rowrank_(2)
 
print("before:")
print(T)
print(CyT_nonshare)
 
CyT_nonshare.set_elem([1,1],2.345)
 
print("after")
print(T) # T is unchanged!
print(CyT_nonshare)

output>

-----------------------
tensor Name :
tensor Rank : 2
block_form  : false
is_diag     : False
on device   : cytnx device: CPU
          --------
         /        \
   0 ____| 4      |
         |        |
   1 ____| 4      |
         \        /
          --------
before:

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]




after

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]




[non-share example]
before:

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]




after

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]



-------- start of print ---------
Tensor name:
Tensor name:
is_diag    : False
contiguous : True

Total elem: 16
type  : Double (Float64)
cytnx device: CPU
Shape : (4,4)
[[1.45600e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 2.34500e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]
 [0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 ]]

◆ UniTensor() [2/2]

cytnx::UniTensor::UniTensor	(	const std::vector< Bond > &	bonds,
		const std::vector< std::string > &	in_labels = `{}`,
		const cytnx_int64 &	rowrank = `-1`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const bool &	is_diag = `false`,
		const std::string &	name = `""`
	)

inline

Construct a UniTensor.

Parameters

[in]	bonds	the bond list. Each bond will be deep copy( not a shared view of bond object with input bond)
[in]	in_labels	the labels for each rank(bond)
[in]	rowrank	the rank of physical row space.
[in]	dtype	the data type of the UniTensor. It can be any type defined in cytnx::Type.
[in]	device	the device that the UniTensor is put on. It can be any device defined in cytnx::Device.
[in]	is_diag	if the constructed UniTensor is a diagonal UniTensor. This can only be assigned true when the UniTensor is square and rank-2 UniTensor. The UniTensor must have one in-bond and one out-bond.

Precondition

the bonds cannot contain simutaneously untagged bond(s) and tagged bond(s)
If the bonds are with symmetry (qnums), the symmetry types should be the same across all the bonds.

Member Function Documentation

◆ Add() [1/2]

UniTensor cytnx::UniTensor::Add ( const Scalar & rhs ) const

The addition function for a given scalar.

Given the scalar rhs, it will perform the addition for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to add in the UniTensor.

Returns: UniTensor

Note: Compared to Add_(const Scalar&), this function will create a new UniTensor.

See also: Add_(const Scalar&), Add_(const UniTensor&), Add(const UniTensor&)const, operator+=(const UniTensor&), operator+=(const Scalar&), operator+

◆ Add() [2/2]

UniTensor cytnx::UniTensor::Add ( const UniTensor & rhs ) const

The addition function of the UniTensor.

This is addition function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return a new UniTensor

\[ UT = UT_{self} + UT_2 \]

Perform element-wise addition of two UniTensor.

Parameters

[in] rhs The UniTensor you want to add by.

Returns: UniTensor

Precondition: The two UniTensor need to have same structure.

Note: Compared to Add_(const UniTensor&), this function will create a new UniTensor.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Add_(const UniTensor&), Add_(const Scalar&), Add(const Scalar&)const , operator+=(const UniTensor&), operator+=(const Scalar&), operator+

◆ Add_() [1/2]

UniTensor & cytnx::UniTensor::Add_ ( const Scalar & rhs )

inline

The addition function for a given scalar.

Given the Scalar rhs, it will perform the addition for each element in UniTensor with this Scalar rhs.

Parameters

[in] rhs a Scalar you want to add in the UniTensor.

Returns: UniTensor&

Note: Compared to Add(const Scalar&)const, this is an inplace function.

See also: Add_(const UniTensor&), Add(const UniTensor&)const, Add(const Scalar&)const , operator+=(const UniTensor&), operator+=(const Scalar&), operator+

◆ Add_() [2/2]

UniTensor & cytnx::UniTensor::Add_ ( const UniTensor & rhs )

inline

The addition function of the UniTensor.

This is addition function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return

\[ UT_{self} = UT_{self} + UT_2 \]

Perform element-wise addition of two UniTensor.

Parameters

[in] rhs The UniTensor you want to add by.

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

Note: Compared to Add(const UniTensor&)const, this is an inplace function.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Add_(const Scalar&), Add(const UniTensor&)const, Add(const Scalar&)const , operator+=(const UniTensor&), operator+=(const Scalar&), operator+

◆ apply()

UniTensor cytnx::UniTensor::apply ( ) const

inline

Apply fermionic signflips to the UniTensor, such that all elements calling signflip() on the output tensor will result in all elements to be false.

Warning: Blocks that need to be flipped are copied and inverted. Blocks where no signflip has to be applied remain. Therefore, these correspond to a shared view and changing these blocks on the output tensor will affect the elements of the input tensor as well.

See also: apply_()

◆ apply_()

UniTensor & cytnx::UniTensor::apply_ ( )

inline

Apply fermionic signflips to the UniTensor, inplacely. Subsequently, all elements returned by signflip() are false.

See also: apply()

◆ arange() [1/2]

static UniTensor cytnx::UniTensor::arange	(	cytnx_double	start,
		cytnx_double	end,
		cytnx_double	step = `1`,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Create a rank-1 UniTensor with incremental elements in the range [start,end) with given step-size step between elements.

The elements are start, start + step, start + 2 * step, ... The last element is the largest one that is smaller than end.

Parameters

[in]	start	start value of the range.
[in]	end	end value of the range (exclusive).
[in]	step	step-size between subsequent elements in the range.
[in]	in_labels	the label of the UniTensor.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: arange(const cytnx_double &start, const cytnx_double &end, const cytnx_double &step, const unsigned int &dtype, const int &device)

◆ arange() [2/2]

static UniTensor cytnx::UniTensor::arange	(	cytnx_int64	Nelem,
		const std::vector< std::string > &	in_labels = `{}`,
		const std::string &	name = `""`
	)

inlinestatic

Create a rank-1 UniTensor with incremental unsigned integer elements in the range [0,Nelem).

The elements are 0, 1, 2, ..., Nelem - 1.

Parameters

[in]	Nelem	number of incremental elements.
[in]	in_labels	the label of the UniTensor.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: arange(const cytnx_double &start, const cytnx_double &end, const cytnx_double &step, const std::vector<std::string> &in_labels, const unsigned int &dtype, const int &device, const std::string &name); arange(const cytnx_int64 &Nelem)

◆ astype()

UniTensor cytnx::UniTensor::astype ( const unsigned int & dtype ) const

inline

Return a new UniTensor whose elements are casted to a different data type.

Parameters

[in] new_type the new data type. It an be any type defined in cytnx::Type.

Returns: UniTensor

Attention: If the new_type is same as dtype of the original UniTensor, return self.

◆ at() [1/8]

template<class T >

T & cytnx::UniTensor::at ( const std::vector< cytnx_uint64 > & locator )

inline

Get an element at a specific location.

Parameters

[in] locator the location of the element we want to access.

Note: this API is only for C++.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ at() [2/8]

Scalar::Sproxy cytnx::UniTensor::at ( const std::vector< cytnx_uint64 > & locator )

inline

Get an element at a specific location.

see more information at user guide 6.3.5.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ at() [3/8]

template<class T >

const T & cytnx::UniTensor::at ( const std::vector< cytnx_uint64 > & locator ) const

inline

Get an element at a specific location.

Parameters

[in] locator the location of the element we want to access.

Note: this API is only for C++.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ at() [4/8]

const Scalar::Sproxy cytnx::UniTensor::at ( const std::vector< cytnx_uint64 > & locator ) const

inline

Get an element at a specific location.

see more information at user guide 6.3.5.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ at() [5/8]

template<class T >

T & cytnx::UniTensor::at	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	locator
	)

inline

◆ at() [6/8]

Scalar::Sproxy cytnx::UniTensor::at	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	locator
	)

inline

◆ at() [7/8]

template<class T >

const T & cytnx::UniTensor::at	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	locator
	)		const

inline

◆ at() [8/8]

const Scalar::Sproxy cytnx::UniTensor::at	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	locator
	)		const

inline

◆ bond() [1/2]

Bond cytnx::UniTensor::bond ( const cytnx_uint64 & idx ) const

inline

◆ bond() [2/2]

Bond cytnx::UniTensor::bond ( const std::string & label ) const

inline

◆ bond_() [1/4]

Bond & cytnx::UniTensor::bond_ ( const cytnx_uint64 & idx )

inline

◆ bond_() [2/4]

const Bond & cytnx::UniTensor::bond_ ( const cytnx_uint64 & idx ) const

inline

◆ bond_() [3/4]

Bond & cytnx::UniTensor::bond_ ( const std::string & label )

inline

◆ bond_() [4/4]

const Bond & cytnx::UniTensor::bond_ ( const std::string & label ) const

inline

◆ bonds()

const std::vector< Bond > & cytnx::UniTensor::bonds ( ) const

inline

Get the bonds of the UniTensor.

Returns: std::vector<Bond>

◆ clone()

UniTensor cytnx::UniTensor::clone ( ) const

inline

Clone (deep copy) the UniTensor.

Returns: UniTensor

◆ combineBond()

UniTensor cytnx::UniTensor::combineBond	(	const std::vector< std::string > &	indicators,
		const bool &	force = `false`
	)		const

inline

Combine the sevral bonds of the UniTensor, out-of-place.

Parameters

[in]	indicators	the labels of the legs you want to combine.
[in]	force	If force is true, it will combine the bonds anyway even the direction of the bonds are same. After combining, the direction of the bonds will be set as same as the first bond.

Precondition

The size of indicators need to >= 2.
The UniTensor cannot be diagonal form (that means is_diag cannot be true.)

Returns: UniTensor a new UniTensor with the bonds combined; this UniTensor is unchanged.

See also: combineBond_(const std::vector<std::string> &indicators, const bool &force)

◆ combineBond_()

UniTensor & cytnx::UniTensor::combineBond_	(	const std::vector< std::string > &	indicators,
		const bool &	force = `false`
	)

inline

Combine the sevral bonds of the UniTensor, in-place.

Parameters

[in]	indicators	the labels of the legs you want to combine.
[in]	force	If force is true, it will combine the bonds anyway even the direction of the bonds are same. After combining, the direction of the bonds will be set as same as the first bond.

Precondition

The size of indicators need to >= 2.
The UniTensor cannot be diagonal form (that means is_diag cannot be true.)

Returns: UniTensor& (self)

See also: combineBond(const std::vector<std::string> &indicators, const bool &force) const

◆ combineBonds() [1/3]

void cytnx::UniTensor::combineBonds	(	const std::vector< cytnx_int64 > &	indicators,
		const bool &	force,
		const bool &	by_label
	)

inline

Deprecated:: This function is deprecated. Please use
combineBond_(const std::vector<std::string> &indicators, const bool &force)
instead.

◆ combineBonds() [2/3]

void cytnx::UniTensor::combineBonds	(	const std::vector< cytnx_int64 > &	indicators,
		const bool &	force = `false`
	)

inline

Deprecated:: This function is deprecated. Please use
combineBond_(const std::vector<std::string> &indicators, const bool &force)
instead.

◆ combineBonds() [3/3]

void cytnx::UniTensor::combineBonds	(	const std::vector< std::string > &	indicators,
		const bool &	force = `false`
	)

inline

Deprecated:: This function is deprecated. Please use
combineBond_(const std::vector<std::string> &indicators, const bool &force)
instead.

◆ Conj()

UniTensor cytnx::UniTensor::Conj ( ) const

inline

Apply complex conjugate on each entry of the UniTensor.

Conj() apply complex conjugate on each entry of the UniTensor.

Returns: UniTensor

Note: Compared to Conj_(), this function will create a new object UniTensor.

See also: Conj_()

◆ Conj_()

UniTensor & cytnx::UniTensor::Conj_ ( )

inline

Apply complex conjugate on each entry of the UniTensor.

Conj_() apply complex conjugate on each entry of the UniTensor, inplacely.

Returns: UniTensor

Note: Compared to Conj(), this function is an inplace function.

See also: Conj()

◆ contiguous()

UniTensor cytnx::UniTensor::contiguous ( ) const

inline

Make the UniTensor contiguous by coalescing the memory (storage).

See also: contiguous_()

Warning: If the input tensor is not contiguous, then the data will be stored in new memory; otherwise, the input tensor is returned and no cloning of the data happens.

◆ contiguous_()

UniTensor & cytnx::UniTensor::contiguous_ ( )

inline

Make the UniTensor contiguous by coalescing the memory (storage), inplacely.

See also: contiguous()

◆ contract()

UniTensor cytnx::UniTensor::contract	(	const UniTensor &	inR,
		const bool &	mv_elem_self = `false`,
		const bool &	mv_elem_rhs = `false`
	)		const

inline

Contract the UniTensor with common labels.

This function contract the UniTensor legs with common labels.

Parameters

[in]	inR	The UniTensor you want to contract with.
[in]	mv_elem_self	Whether the self UniTensor need to do contiguous() after the contraction.
[in]	mv_elem_rhs	Whether the rhs UniTensor `inR` need to do contiguous() after the contraction.

Precondition

Two UniTensor need to have same UniTensor type, namely, same UTenType. You cannot contract symmetric to non-symmetric UniTensor.
You cannot contract tagged UniTensor and untagged UniTensor.
For Dense diagonal UniTensor, the type of Bond (bra-ket) should match.
For symmetric UniTensor (UTenType.Block), Symmetry, degeneracy, quantum numbers and Bond type should be consistent.

Returns: UniTensor

See also: uten_type(), linalg::Tensordot

◆ convert_from()

UniTensor & cytnx::UniTensor::convert_from	(	const UniTensor &	rhs,
		bool	force = `false`,
		cytnx_double	tol = `0.`
	)

inline

Deprecated:: This function is deprecated. Please use
convert_from_(const UniTensor &rhs, bool force, cytnx_double tol)
instead.

◆ convert_from_()

UniTensor & cytnx::UniTensor::convert_from_	(	const UniTensor &	rhs,
		bool	force = `false`,
		cytnx_double	tol = `0.`
	)

inline

Copy data from a UniTensor of different type, in-place.

For example, if uTB is a BlockUniTensor and uTD is a DenseUniTensor of the same shape, then uTD.convert_from_(uTB) makes uTD a sparse copy of uTB.

Parameters

[in]	rhs	the UniTensor to copy from
[in]	force	if true, the compatibility of the input and output tensor structure is not checked strictly; elements that do not exist in the output tensor are ignored in the input tensor, even if they are not zero or small.
[in]	tol	applies if a denser UniTensor is converted to a sparser tensor structure; if an element in the output tensor does not exist, the absolute value of the element in the input tensor has to be <= `tol`. Otherwise an error is thrown. This is overwritten by force = true.

Returns: [UniTensor] a reference to this UniTensor

◆ Dagger()

UniTensor cytnx::UniTensor::Dagger ( ) const

inline

Take the conjugate transpose to the UniTensor.

Returns: UniTensor

Note: This function inverts the order of all indices.; Compared to Dagger_(), this function will create a new UniTensor object.; For fermionic UniTensors, the index order is reversed without sign flips.

See also: Dagger_(), Transpose()

◆ Dagger_()

UniTensor & cytnx::UniTensor::Dagger_ ( )

inline

Take the conjugate transpose to the UniTensor, inplacely.

Returns: UniTensor&

Note: This function inverts the order of all indices.; Compared to Dagger(), this is an inplace function.; For fermionic UniTensors, the index order is reversed without sign flips.

See also: Dagger()

◆ device()

int cytnx::UniTensor::device ( ) const

inline

Return the device of the UniTensor.

The function return the device of the UniTensor.

Returns: int

◆ device_str()

std::string cytnx::UniTensor::device_str ( ) const

inline

Return the device of the UniTensor in 'string' form.

Returns: std::string

See also: device()

◆ Div() [1/2]

UniTensor cytnx::UniTensor::Div ( const Scalar & rhs ) const

The division function for a given scalar.

Given the scalar rhs, it will perform the division for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to divide in the UniTensor.

Returns: UniTensor

Note: Compared to Div_(const Scalar&), this function will create a new UniTensor.

See also: Div_(const Scalar&), Div_(const UniTensor&), Div(const UniTensor&)const, operator/=(const UniTensor&), operator/=(const Scalar&), operator/

◆ Div() [2/2]

UniTensor cytnx::UniTensor::Div ( const UniTensor & rhs ) const

The division function of the UniTensor.

This is division function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return a new UniTensor

\[ UT = UT_{self} / UT_2 \]

Perform element-wise division of two UniTensor.

Parameters

[in] rhs the divisor

Returns: UniTensor

Precondition: The two UniTensor need to have same structure.

Note: Compared to Div_(const UniTensor&), this function will create a new UniTensor.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Div_(const UniTensor&), Div_(const Scalar&), Div(const Scalar&)const , operator/=(const UniTensor&), operator/=(const Scalar&), operator/

◆ Div_() [1/2]

UniTensor & cytnx::UniTensor::Div_ ( const Scalar & rhs )

inline

The division function for a given scalar.

Given the scalar rhs, it will perform the division for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to divide in the UniTensor.

Returns: UniTensor&

Note: Compared to Sub(const Scalar&)const, this is an inplace function.

See also: Div_(const UniTensor&), Div(const UniTensor&)const, Div(const Scalar&)const , operator/=(const UniTensor&), operator/=(const Scalar&), operator/

◆ Div_() [2/2]

UniTensor & cytnx::UniTensor::Div_ ( const UniTensor & rhs )

inline

The division function of the UniTensor.

This is division function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return

\[ UT_{self} = UT_{self} / UT_2 \]

Perform element-wise division of two UniTensor.

Parameters

[in] rhs the divisor

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

Note: Compared to Div(const UniTensor&)const, this is an inplace function.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Div_(const Scalar&), Div(const UniTensor&)const, Div(const Scalar&)const , operator/=(const UniTensor&), operator/=(const Scalar&), operator/

◆ dtype()

unsigned int cytnx::UniTensor::dtype ( ) const

inline

Return the data type of the UniTensor.

The function return the data type of the UniTensor.

Returns: unsigned int

◆ dtype_str()

std::string cytnx::UniTensor::dtype_str ( ) const

inline

Return the data type of the UniTensor in 'string' form.

Returns: std::string

See also: dtype()

◆ elem_exists()

bool cytnx::UniTensor::elem_exists ( const std::vector< cytnx_uint64 > & locator ) const

inline

Given the locator, check if the element exists.

Parameters

[in] locator the locator of the element.

Returns: [bool]

Note: Same as at(locator).exists().

◆ eye()

static UniTensor cytnx::UniTensor::eye	(	cytnx_uint64	dim,
		const std::vector< std::string > &	in_labels = `{}`,
		cytnx_bool	is_diag = `false`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Generate a 2-bond identity UniTensor.

Parameters

[in]	dim	the dimension of the diagnal.
[in]	in_labels	the two labels of the UniTensor.
[in]	is_diag	determine if the UniTensor is diagonal or not. Default is false.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

Note: The resulting UniTensor has two bonds. The data is one-dimensional (two-dimensional) if is_diag is true (false).

See also: cytnx::UniTensor::identity

Note: This function is a alias of cytnx::UniTensor::identity().

◆ fermion_twists()

UniTensor cytnx::UniTensor::fermion_twists ( ) const

inline

Apply twists to all right bonds (>= rowrank) with bond type BD_KET.

For bosonic tensors, nothing changes. For fermions, this makes sure that bra- and ket-states can be contracted correctly. For example, a scalar product <A|B> between ket states A and B represented by fermionic tensors with incoming and outgoing legs, can be calculated correctly by contract(Adag.fermion_twists_(), B). This example asumes that Adag is the dagger of A and has rowrank=0, while B has maximal rowrank. Applying fermion_twists_ to B would have no effect in this case and is thus safe to do. Similarly, this can be applied to linear operators. If M is an operator, then its first rowrank indices correspond to ket bonds and are not affected by fermion_twists_. For the remaining bonds, a twist is applied if they are not of type BD_BRA. The combination of this method to bra states, ket states and linear operators in a Hilbert space, together with contractions, ensures that scalar products can be executed as desired.

Warning: The rowrank must be set correctly before applying this method.

◆ fermion_twists_()

UniTensor & cytnx::UniTensor::fermion_twists_ ( )

inline

Inline version.

See also: fermion_twists()

Warning: The rowrank must be set correctly before applying this method.

◆ get()

UniTensor cytnx::UniTensor::get ( const std::vector< Accessor > & accessors ) const

inline

get elements using Accessor (C++ API) / slices (python API)

Parameters

[in] accessors the Accessor (C++ API) / slices (python API) to get the elements.

Returns: [UniTensor]

See also: Tensor::get, UniTensor::operator[]

Note

The return will be a new UniTensor instance, which does not share memory with the current UniTensor.
Equivalently, one can also use the [] operator to access elements.
For diagonal UniTensors, the accessor list can have either one element (to address the diagonal elements), or two elements (in this case, the output will be a non-diagonal UniTensor).

◆ get_block() [1/6]

Tensor cytnx::UniTensor::get_block ( const cytnx_uint64 & idx = 0 ) const

inline

Get the block of the UniTensor for a given block index.

Parameters

[in] idx the index of the block we want to get

Returns: Tensor

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_block() [2/6]

Tensor cytnx::UniTensor::get_block	(	const std::initializer_list< cytnx_int64 > &	qnum,
		const bool &	force = `false`
	)		const

inline

See also: get_block(const std::vector<cytnx_int64> &qnum, const bool &force)const

◆ get_block() [3/6]

Tensor cytnx::UniTensor::get_block	(	const std::vector< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

Get the block of the UniTensor for the given quantun indices.

Parameters

[in]	qidx	input the quantum indices you want to get the corresponding block.
[in]	force	If force is true, it will return the tensor anyway (Even the corresponding block is empty, it will return void type tensor if `force` is set as true. Otherwise, it will trow the exception.)

Returns: Tensor

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_block() [4/6]

Tensor cytnx::UniTensor::get_block	(	const std::vector< cytnx_uint64 > &	qnum,
		const bool &	force = `false`
	)		const

inline

See also: get_block(const std::vector<cytnx_int64> &qnum, const bool &force)const

◆ get_block() [5/6]

Tensor cytnx::UniTensor::get_block	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

◆ get_block() [6/6]

Tensor cytnx::UniTensor::get_block	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

◆ get_block_() [1/10]

Tensor & cytnx::UniTensor::get_block_ ( const cytnx_uint64 & idx = 0 )

inline

See also: get_block_(const cytnx_uint64 &idx) const

Note: This function only works for non-symmetric UniTensor.

◆ get_block_() [2/10]

const Tensor & cytnx::UniTensor::get_block_ ( const cytnx_uint64 & idx = 0 ) const

inline

Get the shared view of the block for the given block index.

Parameters

[in] idx input the index you want to get the corresponding block

Returns: const Tensor&

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_block_() [3/10]

Tensor & cytnx::UniTensor::get_block_	(	const std::initializer_list< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)

inline

See also: get_block_(const std::vector<cytnx_int64> &qidx, const bool &force)

◆ get_block_() [4/10]

const Tensor & cytnx::UniTensor::get_block_	(	const std::initializer_list< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

See also: get_block_(const std::vector<cytnx_int64> &qidx, const bool &force)

◆ get_block_() [5/10]

Tensor & cytnx::UniTensor::get_block_	(	const std::vector< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)

inline

Get the shared view of the block for the given quantum indices.

Parameters

[in]	qidx	input the quantum indices you want to get the corresponding block.
[in]	force	If force is true, it will return the tensor anyway (Even the corresponding block is empty, it will return void type tensor if `force` is set as true. Otherwise, it will trow the exception.)

Returns: Tensor&

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_block_() [6/10]

const Tensor & cytnx::UniTensor::get_block_	(	const std::vector< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

See also: get_block_(const std::vector<cytnx_int64> &qidx, const bool &force)

◆ get_block_() [7/10]

Tensor & cytnx::UniTensor::get_block_	(	const std::vector< cytnx_uint64 > &	qidx,
		const bool &	force = `false`
	)

inline

See also: get_block_(const std::vector<cytnx_int64> &qidx, const bool &force)

◆ get_block_() [8/10]

const Tensor & cytnx::UniTensor::get_block_	(	const std::vector< cytnx_uint64 > &	qidx,
		const bool &	force = `false`
	)		const

inline

See also: get_block_(const std::vector<cytnx_int64> &qidx, const bool &force)

◆ get_block_() [9/10]

Tensor cytnx::UniTensor::get_block_	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force = `false`
	)

inline

Get the shared (data) view of the block for the given quantum indices on given labels.

Parameters

[in]	labels	the labels of the bonds.
[in]	qidx	input the quantum indices you want to get the corresponding block.
[in]	force	If force is true, it will return the tensor anyway (Even the corresponding block is empty, it will return void type tensor if `force` is set as true. Otherwise, it will trow the exception.)

Returns: Tensor&

Note: labels and qidx forming one to one pairs. e.g. it means get qidx[i] qnum at Bond labels[i]. Also note that the return Tensor will have axes in the same order specified by labels.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_block_() [10/10]

Tensor cytnx::UniTensor::get_block_	(	const std::vector< std::string > &	labels,
		const std::vector< cytnx_uint64 > &	qidx,
		const bool &	force = `false`
	)

inline

◆ get_blocks()

std::vector< Tensor > cytnx::UniTensor::get_blocks ( ) const

inline

Get all the blocks of the UniTensor.

get_blocks will return the blocks of the UniTensor. Furthermore,

For symmetric UniTensor, it will call contiguous() and then return the deep copy of blocks.

For non-symmetric UniTensor, it will return the deep copy of blocks.

Returns: std::vector<Tensor>

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_blocks_() [1/2]

std::vector< Tensor > & cytnx::UniTensor::get_blocks_ ( const bool & silent = false )

inline

See also: get_blocks()_

◆ get_blocks_() [2/2]

const std::vector< Tensor > & cytnx::UniTensor::get_blocks_ ( const bool & silent = false ) const

inline

Get all the blocks of the UniTensor, inplacely.

See also: get_blocks()

Parameters

[in] silent whether need to print out the warning messages.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! The reason behind this is that several UniTensors in different permutations can share the same memory. Use signflip() to get the sign structure for each block.

◆ get_elem()

template<class T >

T cytnx::UniTensor::get_elem ( const std::vector< cytnx_uint64 > & locator ) const

inline

Deprecated:: This function is deprecated, please use at() instread.

Note: C++: Deprecated soon, use at()

◆ get_index()

cytnx_int64 cytnx::UniTensor::get_index ( std::string label ) const

inline

Get the index of an desired label string.

Parameters

label Label you want to find

Returns: The index of the label. If not found, return -1

◆ get_itoi() [1/2]

vec2d< cytnx_uint64 > & cytnx::UniTensor::get_itoi ( )

inline

◆ get_itoi() [2/2]

const vec2d< cytnx_uint64 > & cytnx::UniTensor::get_itoi ( ) const

inline

get the q-indices on each leg for all the blocks

Returns: [2d vector]

◆ get_qindices() [1/2]

std::vector< cytnx_uint64 > & cytnx::UniTensor::get_qindices ( const cytnx_uint64 & bidx )

inline

get the q-indices on each leg for the [bidx]-th block

Parameters

bidx	the bidx-th block in current block list.

Returns: [vector]

◆ get_qindices() [2/2]

const std::vector< cytnx_uint64 > & cytnx::UniTensor::get_qindices ( const cytnx_uint64 & bidx ) const

inline

get the q-indices on each leg for the [bidx]-th block

Parameters

bidx	the bidx-th block in current block list.

Returns: [vector]

◆ group_basis()

UniTensor cytnx::UniTensor::group_basis ( ) const

inline

◆ group_basis_()

UniTensor & cytnx::UniTensor::group_basis_ ( )

inline

Group the same quantum number basis together.

If the UniTensor has duplicated quantum number, then this function will group the basis with the same quantum number.

Precondition: The UniTensor must be in block form. That is, the UniTensor is UTenType::Block.

◆ identity()

static UniTensor cytnx::UniTensor::identity	(	cytnx_uint64	dim,
		const std::vector< std::string > &	in_labels = `{}`,
		cytnx_bool	is_diag = `false`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Generate an identity UniTensor with two bonds.

Parameters

[in]	dim	the dimension of the diagnal.
[in]	in_labels	the two labels of the UniTensor.
[in]	is_diag	determine if the UniTensor is diagonal or not. Default is false.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

Note: The resulting UniTensor has two bonds. The data is one-dimensional (two-dimensional) if is_diag is true (false).

◆ Init() [1/2]

UniTensor & cytnx::UniTensor::Init	(	const std::vector< Bond > &	bonds,
		const std::vector< std::string > &	in_labels = `{}`,
		const cytnx_int64 &	rowrank = `-1`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const bool &	is_diag = `false`,
		const std::string &	name = `""`
	)

inline

Initialize the UniTensor with the given arguments.

This is the initial function of the UniTensor. If you want to initialize your UniTensor after declaring just a 'void' UniTensor. You can use this function to initialize it.

Parameters

[in]	bonds	the bond list. Each bond will be deep copy( not a shared view of bond object with input bond)
[in]	in_labels	the labels for each rank(bond)
[in]	rowrank	the rank of physical row space
[in]	dtype	the dtype of the UniTensor. It can be any type defined in cytnx::Type.
[in]	device	the device that the UniTensor is put on. It can be any device defined in cytnx::Device.
[in]	is_diag	if the constructed UniTensor is a diagonal UniTensor. This can only be assigned true when the UniTensor is square, untagged and rank-2 UniTensor.
[in]	name	user specified name of the UniTensor.

Precondition: Please ensure that all of the Bond in bonds should be all symmetric or non-symmetric. You cannot mix them.

See also: UniTensor(const std::vector<Bond> &bonds, const std::vector<std::string> &in_labels, const cytnx_int64 &rowrank, const unsigned int &dtype, const int &device, const bool &is_diag)

◆ Init() [2/2]

void cytnx::UniTensor::Init	(	const Tensor &	in_tensor,
		const bool &	is_diag = `false`,
		const cytnx_int64 &	rowrank = `-1`,
		const std::vector< std::string > &	in_labels = `{}`,
		const std::string &	name = `""`
	)

inline

Initialize a UniTensor from a cytnx::Tensor.

Parameters

[in]	in_tensor	a cytnx::Tensor
[in]	is_diag	whether the input Tensor `in_tensor` is a diagonal Tensor. this requires the input `in_tensor` to be 1D.
[in]	rowrank	the rowrank of the resulting UniTensor.
[in]	name	user-specified name of the UniTensor.

Note

The constructed UniTensor will have the same rank as the input Tensor, with default labels, and a shared view (shared instance) of interal block as the input Tensor.
The constructed UniTensor is always untagged.

Attention: The internal block of the UniTensor is a referece to the input Tensor. That is, they share the same memory. If the elements of the UniTensor are changed, the original Tensor is also changed and vice-versa. Use Tensor.clone() if a shared view is not desired.

See also: UniTensor(const Tensor &, const bool &, const cytnx_int64 &)

◆ Inv()

UniTensor cytnx::UniTensor::Inv ( double clip = -1. ) const

Element-wise (pseudo-)inverse.

This function performs an element-wise inverse with clip. If \( |T_\text{in}[i]| \le \mathrm{clip} \), then the new element is set to zero.

\[ T_\text{out}[i] = \left\{ \begin{array}{ll} 1/(T_\text{in}[i]) & \mathrm{if} \ |T_\text{in}[i]| > \mathrm{clip} \\ 0 & \mathrm{otherwise} \end{array} \right. \]

Parameters

[in] clip elmements with absolute value <= clip are set to zero, corresponding to the pseudo-inverse; default: -1 (no clipping)

Returns: UniTensor

Note

For complex type UniTensors, the norm \( \sqrt{Re^2 + Im^2} \) is used to determine the clip.
If Tin is integer type, it will automatically be promoted to Type.Double.
For symmetric UniTensors, only the elements in the blocks are inverted.

Compared to Inv_(double clip), this function does not modify the input UniTensor but returns a new UniTensor.

See also: Inv_(double clip)

◆ Inv_()

UniTensor & cytnx::UniTensor::Inv_ ( double clip = -1. )

Element-wise (pseudo-)inverse, inplacely.

This function performs an element-wise inverse with clip. If \( |T_\text{in}[i]| \le \mathrm{clip} \), then the new element is set to zero.

\[ T_\text{in}[i] \rightarrow \left\{ \begin{array}{ll} 1/(T_\text{in}[i]) & \mathrm{if} \ |T_\text{in}[i]| > \mathrm{clip} \\ 0 & \mathrm{otherwise} \end{array} \right. \]

Parameters

[in] clip elmements with absolute value <= clip are set to zero, corresponding to the pseudo-inverse; default: -1 (no clipping)

Returns: UniTensor

Note

For complex type UniTensors, the norm \( \sqrt{Re^2 + Im^2} \) is used to determine the clip.
If Tin is integer type, it will automatically be promoted to Type.Double.
For symmetric UniTensors, only the elements in the blocks are inverted.

Compared to UniTensor Inv(const UniTensor &Tin, double clip), this is an inplace function, which modifies the input UniTensor.

See also: Inv(double clip) const

◆ is_blockform()

bool cytnx::UniTensor::is_blockform ( ) const

inline

Check whether the UniTensor is in block form.

This function will check whether the UniTensor is in block form. That is, the uten_type() is UTenType::Block.

◆ is_braket_form()

const bool & cytnx::UniTensor::is_braket_form ( ) const

inline

Check whether the UniTensor is in braket form.

This function will check whether the UniTensor is in braket form. That is,

The bonds order, all of the in-bonds are before out-bonds.
The number of in-bonds is equal to the rowrank.

◆ is_contiguous()

bool cytnx::UniTensor::is_contiguous ( ) const

inline

To tell whether the UniTensor is contiguous.

Returns: bool

See also: contiguous(), contiguous_()

◆ is_diag()

bool cytnx::UniTensor::is_diag ( ) const

inline

To tell whether the UniTensor is in diagonal form.

Returns: bool

◆ is_empty()

bool cytnx::UniTensor::is_empty ( ) const

inline

whether the UniTensor is initialized and has no logical elements

◆ is_scalar()

bool cytnx::UniTensor::is_scalar ( ) const

inline

whether the UniTensor is an initialized rank-0 scalar UniTensor

Returns: [bool] true if the UniTensor has rank 0 and is initialized

◆ is_tag()

bool cytnx::UniTensor::is_tag ( ) const

inline

To tell whether the UniTensor is tagged. That is, all of the Bond in the UniTensor is directional (all of them are bondType.BD_KET or bondType.BD_BRA)

Returns: bool

◆ is_void()

bool cytnx::UniTensor::is_void ( ) const

inline

Return whether the UniTensor is uninitialized.

Returns: bool

◆ item() [1/2]

template<class T >

T & cytnx::UniTensor::item ( )

inline

◆ item() [2/2]

Scalar::Sproxy cytnx::UniTensor::item ( ) const

inline

◆ labels()

const std::vector< std::string > & cytnx::UniTensor::labels ( ) const

inline

Return the labels of the UniTensor.

Returns: std::vector<std::string>

◆ linspace()

static UniTensor cytnx::UniTensor::linspace	(	cytnx_double	start,
		cytnx_double	end,
		cytnx_uint64	Nelem,
		bool	endpoint = `true`,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Generate a one-bond UniTensor with all elements are evenly spaced numbers over a specified interval.

Generate a UniTensor with all elements are evenly spaced numbers over a specified interval. The interval is [start, end] and the number of elements is Nelem.

Parameters

[in]	start	the start of the linspace.
[in]	end	the end of the linspace.
[in]	Nelem	the number of elements.
[in]	endpoint	if `endpoint` is true, the end of linspace is `end`, else the end of linspace is `end` - `step`.
[in]	in_labels	the labels of the UniTensor.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: linspace(const cytnx_double &start, const cytnx_double &end, const cytnx_uint64 &Nelem, const bool &endpoint, const unsigned int &dtype, const int &device)

◆ Load() [1/2]

static UniTensor cytnx::UniTensor::Load ( const char * fname )

static

load a UniTensor from file

Parameters

[in] fname the file name

Returns: the loaded UniTensor

Precondition: The file must be a UniTensor object. That is, the file must be created by UniTensor::Save().

See also: Save(const char* fname) const

◆ Load() [2/2]

static UniTensor cytnx::UniTensor::Load ( const std::string & fname )

static

load a UniTensor from file

Parameters

[in] fname the file name

Returns: the loaded UniTensor

Precondition: The file must be a UniTensor object. That is, the file must be created by UniTensor::Save().

See also: Save(const std::string &fname) const

◆ Mul() [1/2]

UniTensor cytnx::UniTensor::Mul ( const Scalar & rhs ) const

The multiplication function for a given scalar.

Given the scalar rhs, it will perform the multiplication for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to multiply in the UniTensor.

Returns: UniTensor

Note: Compared to Mul_(const Scalar&), this function will create a new UniTensor.

See also: Mul_(const Scalar&), Mul_(const UniTensor&), Mul(const UniTensor&)const, operator*=(const UniTensor&), operator*=(const Scalar&), operator*

◆ Mul() [2/2]

UniTensor cytnx::UniTensor::Mul ( const UniTensor & rhs ) const

The multiplication function of the UniTensor.

This is multiplication function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return a new UniTensor

\[ UT = UT_{self} \times UT_2 \]

Perform element-wise multiplcation of two UniTensor.

Parameters

[in] rhs The UniTensor you want to multiplicate by.

Returns: UniTensor

Precondition: The two UniTensor need to have same structure.

Note: Compared to Mul_(const UniTensor&), this function will create a new UniTensor.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Mul_(const UniTensor&), Mul_(const Scalar&), Mul(const Scalar&)const , operator*=(const UniTensor&), operator*=(const Scalar&), operator*

◆ Mul_() [1/2]

UniTensor & cytnx::UniTensor::Mul_ ( const Scalar & rhs )

inline

The multiplication function for a given scalar.

Given the scalar rhs, it will perform the multiplication for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to multiplicate in the UniTensor.

Returns: UniTensor&

Note: Compared to Mul(const Scalar&)const, this is an inplace function.

See also: Mul_(const UniTensor&), Mul(const UniTensor&)const, Mul(const Scalar&)const , operator*=(const UniTensor&), operator*=(const Scalar&), operator*

◆ Mul_() [2/2]

UniTensor & cytnx::UniTensor::Mul_ ( const UniTensor & rhs )

inline

The multiplcation function of the UniTensor.

This is multiplcation function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return

\[ UT_{self} = UT_{self} \times UT_2 \]

Perform element-wise multiplication of two UniTensor.

Parameters

[in] rhs The UniTensor you want to multiplcate by.

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

Note: Compared to Mul(const UniTensor&)const, this is an inplace function.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Mul_(const Scalar&), Mul(const UniTensor&)const, Mul(const Scalar&)const , operator*=(const UniTensor&), operator*=(const Scalar&), operator*

◆ name()

std::string cytnx::UniTensor::name ( ) const

inline

Return the name of the UniTensor.

Returns: std::string

◆ Nblocks()

cytnx_uint64 cytnx::UniTensor::Nblocks ( ) const

inline

Return the number of blocks in the UniTensor.

Returns: cytnx_uint64

◆ Norm()

Tensor cytnx::UniTensor::Norm ( ) const

inline

Return the norm of the UniTensor.

Norm() return the 2-norm of the UniTensor \(UT\). Namely, it return

\[ ||UT||_2 \]

Returns: Tensor

Deprecated:: Use norm() instead, which returns a Scalar directly.

◆ norm()

Scalar cytnx::UniTensor::norm ( ) const

inline

Return the norm of the UniTensor.

norm() return the 2-norm of the UniTensor \(UT\) as a Scalar carrying the UniTensor's own precision (Float for Float/ComplexFloat input, Double otherwise), so x /= x.norm() stays dtype-preserving rather than promoting a Float UniTensor to Double.

\[ ||UT||_2 \]

Returns: Scalar

◆ normal() [1/2]

static UniTensor cytnx::UniTensor::normal	(	const cytnx_uint64 &	Nelem,
		const double &	mean,
		const double &	std,
		const std::vector< std::string > &	in_labels = `{}`,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const std::string &	name = `""`
	)

static

Generate a one-bond UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution.

Generate a UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution. The mean is mean and the standard deviation is std.

Parameters

[in]	Nelem	the number of elements.
[in]	mean	the mean of the normal distribution.
[in]	std	the standard deviation of the normal distribution.
[in]	in_labels	the labels of the UniTensor.
[in]	seed	the seed of the random generator.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: random::normal(const cytnx_uint64 &Nelem, const double &mean, const double &std, const int &device, const unsigned int &seed, const unsigned int &dtype)

◆ normal() [2/2]

static UniTensor cytnx::UniTensor::normal	(	const std::vector< cytnx_uint64 > &	shape,
		const double &	mean,
		const double &	std,
		const std::vector< std::string > &	in_labels = `{}`,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const std::string &	name = `""`
	)

static

Generate a UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution.

Generate a UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution. The mean is mean and the standard deviation is std.

Parameters

[in]	shape	the shape of the UniTensor.
[in]	mean	the mean of the normal distribution.
[in]	std	the standard deviation of the normal distribution.
[in]	in_labels	the labels of the UniTensor.
[in]	seed	the seed of the random generator.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: random::normal(const std::vector< cytnx_uint64 > &shape, const double &mean, const double &std, const int &device, const unsigned int &seed, const unsigned int &dtype)

◆ normal_()

UniTensor & cytnx::UniTensor::normal_	(	const double &	mean,
		const double &	std,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`
	)

Generate a one-bond UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution, inplacely.

This function provides an inplacely way to generate a UniTensor with all elements are random numbers sampled from a normal (Gaussian) distribution. The mean is mean and the standard deviation is std.

Parameters

[in]	mean	the mean of the normal distribution.
[in]	std	the standard deviation of the normal distribution.
[in]	seed	the seed of the random generator.

See also: random::normal_(UniTensor &in, const double &mean, const double &std, const unsigned int &seed)

◆ normalize()

UniTensor cytnx::UniTensor::normalize ( ) const

inline

normalize the current UniTensor instance with 2-norm.

Returns: UniTensor

Note: Compared to normalize_(), this function will return new UniTensor object.

See also: normalize_()

◆ normalize_()

UniTensor & cytnx::UniTensor::normalize_ ( )

inline

normalize the UniTensor, inplacely.

Returns: UniTensor

Note: Compared to normalize(), this function is inplace function.

See also: normalize()

◆ ones() [1/2]

static UniTensor cytnx::UniTensor::ones	(	const std::vector< cytnx_uint64 > &	shape,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Generate a UniTensor with all elements set to one.

Parameters

[in]	shape	the shape of the UniTensor.
[in]	in_labels	the labels of the UniTensor.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: ones(const std::vector< cytnx_uint64 > &shape, const unsigned int &dtype, const int &device)

◆ ones() [2/2]

static UniTensor cytnx::UniTensor::ones	(	std::initializer_list< cytnx_uint64 >	shape,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

◆ operator*=() [1/2]

UniTensor & cytnx::UniTensor::operator*= ( const Scalar & rhs )

inline

The multiplication assignment operator for a given scalar.

Given the scalar rhs, it will perform the multiplication for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to multiply in the UniTensor.

Returns: UniTensor&

See also: operator*=(const Scalar&), operator*, Mul_(const UniTensor&), Mul_(const Scalar&), Mul(const UniTensor&), Mul(const Scalar&)const

◆ operator*=() [2/2]

UniTensor & cytnx::UniTensor::operator*= ( const UniTensor & rhs )

inline

The multiplication assignment operator of the UniTensor.

This is multiplication assignment operator of the UniTensor. It will perform element-wise multiplication and return

\[ UT *= UT_R \]

Parameters

[in] rhs The UniTensor you want to multilicate by.

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

See also: operator*=(const Scalar&), operator*, Mul_(const UniTensor&), Mul_(const Scalar&), Mul(const UniTensor&), Mul(const Scalar&)const

◆ operator+=() [1/2]

UniTensor & cytnx::UniTensor::operator+= ( const Scalar & rhs )

inline

The addition assignment operator for a given scalar.

Given the scalar rhs, it will perform the addition for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to add in the UniTensor.

Returns: UniTensor&

See also: operator+=(const UniTensor&), operator+, Add_(const UniTensor&), Add_(const Scalar&), Add(const UniTensor&), Add(const Scalar&)const

◆ operator+=() [2/2]

UniTensor & cytnx::UniTensor::operator+= ( const UniTensor & rhs )

inline

The addition assignment operator of the UniTensor.

This is addition assignment operator of the UniTensor. It will perform element-wise addition and return

\[ UT += UT_R \]

Parameters

[in] rhs The UniTensor you want to add by.

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

See also: operator+=(const Scalar&), operator+, Add_(const UniTensor&), Add_(const Scalar&), Add(const UniTensor&), Add(const Scalar&)const

◆ operator-=() [1/2]

UniTensor & cytnx::UniTensor::operator-= ( const Scalar & rhs )

inline

The subtraction assignment operator for a given scalar.

Given the scalar rhs, it will perform the subtraction for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs the subtrahend

Returns: UniTensor&

See also: operator-=(const UniTensor&), operator-, Sub_(const UniTensor&), Sub_(const Scalar&), Sub(const UniTensor&), Sub(const Scalar&)const

◆ operator-=() [2/2]

UniTensor & cytnx::UniTensor::operator-= ( const UniTensor & rhs )

inline

The subtraction assignment operator of the UniTensor.

This is subtraction assignment operator of the UniTensor. It will perform element-wise subtraction and return

\[ UT -= UT_R \]

Parameters

[in] rhs the subtrahend

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

See also: operator-=(const Scalar&), operator-, Sub_(const UniTensor&), Sub_(const Scalar&), Sub(const UniTensor&), Sub(const Scalar&)const

◆ operator/=() [1/2]

UniTensor & cytnx::UniTensor::operator/= ( const Scalar & rhs )

inline

The division assignment operator for a given scalar.

Given the scalar rhs, it will perform the division for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs the divisor

Returns: UniTensor&

See also: operator/=(const UniTensor&), operator/, Div_(const UniTensor&), Div_(const Scalar&), Div(const UniTensor&), Div(const Scalar&)const

◆ operator/=() [2/2]

UniTensor & cytnx::UniTensor::operator/= ( const UniTensor & rhs )

inline

The division assignment operator of the UniTensor.

This is division assignment operator of the UniTensor. It will perform element-wise division and return

\[ UT /= UT_R \]

Parameters

[in] rhs the divisor

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

See also: operator/=(const Scalar&), operator/, Div_(const UniTensor&), Div_(const Scalar&), Div(const UniTensor&), Div(const Scalar&)const

◆ operator[]() [1/4]

UniTensor cytnx::UniTensor::operator[] ( const std::initializer_list< cytnx::Accessor > & accessors ) const

inline

◆ operator[]() [2/4]

UniTensor cytnx::UniTensor::operator[] ( const std::initializer_list< cytnx_int64 > & accessors ) const

inline

◆ operator[]() [3/4]

UniTensor cytnx::UniTensor::operator[] ( const std::vector< cytnx::Accessor > & accessors ) const

inline

get elements using Accessor (C++ API) / slices (python API)

See also: get()

◆ operator[]() [4/4]

UniTensor cytnx::UniTensor::operator[] ( const std::vector< cytnx_int64 > & accessors ) const

inline

◆ permute() [1/3]

UniTensor cytnx::UniTensor::permute	(	const std::initializer_list< char * > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

See also: permute(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank = -1)

Warning: It is recommended to use permute(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead

◆ permute() [2/3]

UniTensor cytnx::UniTensor::permute	(	const std::vector< cytnx_int64 > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

permute the legs of the UniTensor

Parameters

[in]	mapper	the mapper of the permutation by bond indices
[in]	rowrank	the new rowrank after the permutation

Returns: UniTensor

Warning: It is recommended to use permute(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead

◆ permute() [3/3]

UniTensor cytnx::UniTensor::permute	(	const std::vector< std::string > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

permute the legs of the UniTensor by labels

Parameters

[in]	mapper	the mapper of the permutation by labels
[in]	rowrank	the row rank

Returns: UniTensor

◆ permute_() [1/2]

UniTensor & cytnx::UniTensor::permute_	(	const std::vector< cytnx_int64 > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)

inline

permute the legs of the UniTensor, inplacely.

Parameters

[in]	mapper	the mapper of the permutation by labels
[in]	rowrank	the row rank after the permutation

Warning: It is recommended to use permute_(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead

◆ permute_() [2/2]

UniTensor & cytnx::UniTensor::permute_	(	const std::vector< std::string > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)

inline

permute the legs of the UniTensor, inplacely.

Parameters

[in]	mapper	the mapper of the permutation by labels
[in]	rowrank	the row rank after the permutation

See also: permute(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank = -1)

◆ permute_nosignflip() [1/3]

UniTensor cytnx::UniTensor::permute_nosignflip	(	const std::initializer_list< char * > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

See also: permute_nosignflip(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank)

Warning: It is recommended to use permute_nosignflip(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead

◆ permute_nosignflip() [2/3]

UniTensor cytnx::UniTensor::permute_nosignflip	(	const std::vector< cytnx_int64 > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

permute the legs of the UniTensor without sign flips

The indices are permuted, but no fermionic sign flips occur. Use with care! This is usually not intended, since fermionic permutations create sign flips! This should typically only be used to compare tensors in different sign conventions with each other.

Parameters

[in]	mapper	the mapper of the permutation by indices
[in]	rowrank	the new rowrank after the permutation

Returns: UniTensor

Warning: It is recommended to use permute_nosignflip(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead; Usually, the signs should change when permuting a fermionic UniTensor. Use permute instead, unless you are really sure you want to permute without signflips!

◆ permute_nosignflip() [3/3]

UniTensor cytnx::UniTensor::permute_nosignflip	(	const std::vector< std::string > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)		const

inline

permute the legs of the UniTensor by labels without sign flips

The indices are permuted, but no fermionic sign flips occur. Use with care! This is usually not intended, since fermionic permutations create sign flips! This should typically only be used to compare tensors in different sign conventions with each other.

Parameters

[in]	mapper	the mapper of the permutation by labels
[in]	rowrank	the row rank

Returns: UniTensor

Warning: Usually, the signs should change when permuting a fermionic UniTensor. Use permute_ instead, unless you are really sure you want to permute without signflips!

◆ permute_nosignflip_() [1/2]

UniTensor & cytnx::UniTensor::permute_nosignflip_	(	const std::vector< cytnx_int64 > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)

inline

permute the legs of the UniTensor without fermionic sign flips, inplacely.

The indices are permuted, but no fermionic sign flips occur. Use with care! This is usually not intended, since fermionic permutations create sign flips! This should typically only be used to compare tensors in different sign conventions with each other.

Parameters

[in]	mapper	the mapper of the permutation by indices
[in]	rowrank	the row rank after the permutation

Warning: It is recommended to use permute_(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank) instead; Usually, the signs should change when permuting a fermionic UniTensor. Use permute_ instead, unless you are really sure you want to permute without signflips!

◆ permute_nosignflip_() [2/2]

UniTensor & cytnx::UniTensor::permute_nosignflip_	(	const std::vector< std::string > &	mapper,
		const cytnx_int64 &	rowrank = `-1`
	)

inline

permute the legs of the UniTensor without fermionic sign flips, inplacely.

The indices are permuted, but no fermionic sign flips occur. Use with care! This is usually not intended, since fermionic permutations create sign flips! This should typically only be used to compare tensors in different sign conventions with each other.

Parameters

[in]	mapper	the mapper of the permutation by labels
[in]	rowrank	the row rank after the permutation

See also: permute(const std::vector<std::string> &mapper, const cytnx_int64 &rowrank = -1)

Warning: Usually, the signs should change when permuting a fermionic UniTensor. Use permute instead, unless you are really sure you want to permute without signflips!

◆ Pow()

UniTensor cytnx::UniTensor::Pow ( const double & p ) const

Take the power p of all elements.

\[ T_\text{out}[i] = (T_\text{in}[i])^p \]

Parameters

[in] p the power to take

Precondition: If this is a real UniTensor containing negative elements, then p must be an integer.

Note: For symmetric UniTensors, only the elements in the blocks are inverted.

Warning: If p < 0 an inverse has to be taken. If elements could be zero (or close to it), use Inv(double clip) const for a pseudo-inverse instead.; For fermionic UniTensors, the sign structure of the blocks remains unchanged. This way, permute commutes with Pow. This can lead to unexpected behavior since T.Pow(2.0) can differ by signs from T * T.

Note: Compared UniTensor &Pow_(const double &p), this function does not modify the input UniTensor but returns a new UniTensor.

See also: UniTensor &Pow_(const double &p)

◆ Pow_()

UniTensor & cytnx::UniTensor::Pow_ ( const double & p )

Take the power p of all elements, inplacely.

\[ T_\text{in}[i] \rightarrow (T_\text{in}[i])^p \]

Parameters

[in] p the power to take

Precondition: If this is a real UniTensor containing negative elements, then p must be an integer.

Note: For symmetric UniTensors, only the elements in the blocks are inverted.

Warning: If p < 0 an inverse has to be taken. If elements could be zero (or close to it), use Inv_(double clip) for a pseudo-inverse instead.; For fermionic UniTensors, the sign structure of the blocks remains unchanged. This way, permute commutes with Pow_. This can lead to unexpected behavior since T.Pow_(2.0) can differ by signs from T * T.

Note: Compared UniTensor Pow(const double &p) const, this is an inplace function, which modifies the input UniTensor.

See also: UniTensor &Pow(const double &p) const

◆ print_block()

void cytnx::UniTensor::print_block	(	const cytnx_int64 &	idx,
		const bool &	full_info = `true`
	)		const

inline

Print out the block of the UniTensor with a given block index number.

Parameters

[in]	idx	the input index
[in]	full_info	whether need to print the full information of the block

◆ print_blocks()

void cytnx::UniTensor::print_blocks ( const bool & full_info = true ) const

inline

Print all blocks of the UniTensor.

Parameters

[in] full_info whether need to print the full information of the blocks

◆ print_diagram()

void cytnx::UniTensor::print_diagram ( const bool & bond_info = false ) const

inline

Plot the diagram of the UniTensor.

Parameters

[in] bond_info whether need to print the information of the bonds of the UniTensor.

◆ put_block() [1/6]

UniTensor & cytnx::UniTensor::put_block	(	const Tensor &	in,
		const cytnx_uint64 &	idx,
		const bool &	force
	)

inline

Deprecated:: This function is deprecated. Please use
put_block(const Tensor &in, const cytnx_uint64 &idx)
instead.

◆ put_block() [2/6]

UniTensor & cytnx::UniTensor::put_block	(	const Tensor &	in,
		const cytnx_uint64 &	idx = `0`
	)

inline

Put the block into the UniTensor with given index.

Parameters

[in]	in	the block you want to put into UniTensor
[in]	in	the index of the UniTensor you want to put the block `in` in.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block() [3/6]

UniTensor & cytnx::UniTensor::put_block	(	const Tensor &	in_tens,
		const std::vector< cytnx_int64 > &	qidx
	)

inline

Put the block into the UniTensor with given quantum number.

Parameters

[in]	in_tens	the block you want to put into UniTensor
[in]	qidx	the quantum indices of the UniTensor you want to put the block `in_tens` in.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block() [4/6]

UniTensor & cytnx::UniTensor::put_block	(	const Tensor &	in_tens,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force
	)

inline

Deprecated:: This function is deprecated. Please use
put_block(const Tensor &in_tens, const std::vector<cytnx_int64> &qidx)
instead.

◆ put_block() [5/6]

UniTensor & cytnx::UniTensor::put_block	(	Tensor &	in,
		const std::vector< std::string > &	lbls,
		const std::vector< cytnx_int64 > &	qidx
	)

inline

Put the block into the UniTensor with given quantum indices, will copy the input tensor.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block() [6/6]

UniTensor & cytnx::UniTensor::put_block	(	Tensor &	in,
		const std::vector< std::string > &	lbls,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force
	)

inline

Deprecated:: This function is deprecated. Please use
put_block(Tensor &in, const std::vector<std::string> &lbls, const std::vector<cytnx_int64> &qidx)
instead.

◆ put_block_() [1/5]

UniTensor & cytnx::UniTensor::put_block_	(	Tensor &	in,
		const cytnx_uint64 &	idx = `0`
	)

inline

Put the block into the UniTensor with given index, inplacely.

Note: the put block will have shared view with the internal block, i.e. non-clone.

See also: put_block(const Tensor &in, const cytnx_uint64 &idx)

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block_() [2/5]

UniTensor & cytnx::UniTensor::put_block_	(	Tensor &	in,
		const std::vector< cytnx_int64 > &	qidx
	)

inline

Put the block into the UniTensor with given quantum indices, inplacely.

Note: the put block will have shared view with the internal block, i.e. non-clone.

See also: put_block(const Tensor &in, const cytnx_uint64 &idx)

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block_() [3/5]

UniTensor & cytnx::UniTensor::put_block_	(	Tensor &	in,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force
	)

inline

Deprecated:: This function is deprecated. Please use
put_block_(Tensor &in, const std::vector<cytnx_int64> &qidx)
instead.

◆ put_block_() [4/5]

UniTensor & cytnx::UniTensor::put_block_	(	Tensor &	in,
		const std::vector< std::string > &	lbls,
		const std::vector< cytnx_int64 > &	qidx
	)

inline

Put the block into the UniTensor with given quantum indices, inplacely.

Note: the put block will have shared view with the internal block, i.e. non-clone.

Warning: For fermions, the signflip is not included and has to be multiplied by the user! Use signflip() to get the sign, and multiply the block by -1 if the corresponding signflip is true/ODD. The reason behind this is that several UniTensors in different permutations can share the same memory.

◆ put_block_() [5/5]

UniTensor & cytnx::UniTensor::put_block_	(	Tensor &	in,
		const std::vector< std::string > &	lbls,
		const std::vector< cytnx_int64 > &	qidx,
		const bool &	force
	)

inline

Deprecated:: This function is deprecated. Please use
put_block_(Tensor &in, const std::vector<std::string> &lbls, const std::vector<cytnx_int64> &qidx)
instead.

◆ rank()

cytnx_uint64 cytnx::UniTensor::rank ( ) const

inline

Return the rank of the UniTensor.

Returns: cytnx_uint64

◆ relabel() [1/6]

UniTensor cytnx::UniTensor::relabel	(	const cytnx_int64 &	inx,
		const std::string &	new_label
	)		const

inline

rebabel the legs in the UniTensor by given index.

This function will relabel the legs in the UniTensor by a given index. This function will return a new UniTensor with the new label, but the data is still shared with the original UniTensor (that is if you use same_data() to check, it will return true). Compared to set_label(), this function will return a new UniTensor object with different meta data.

Parameters

[in]	inx	a given index
[in]	new_label	the new label of the UniTensor in the index `inx`

Attention: This function will return a new UniTensor with the new label, but the data is still shared with the original UniTensor. That is the meta data of the UniTensor is different, but the internal data is still shared.

See also: set_label(const cytnx_int64 &idx, const std::string &new_label)

◆ relabel() [2/6]

UniTensor cytnx::UniTensor::relabel ( const std::initializer_list< char * > & new_labels ) const

inline

relables all of the labels in UniTensor.

See also: relabel(const std::vector<std::string> &new_labels) const

◆ relabel() [3/6]

UniTensor cytnx::UniTensor::relabel	(	const std::initializer_list< char * > &	old_labels,
		const std::initializer_list< char * > &	new_labels
	)		const

inline

See also: relabel(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels) const

◆ relabel() [4/6]

UniTensor cytnx::UniTensor::relabel	(	const std::string &	old_label,
		const std::string &	new_label
	)		const

inline

relabel the legs in the UniTensor by a given label.

This function will relabel the legs in the UniTensor by a given label. This function will return a new UniTensor with the new label, but the data is still shared with the original UniTensor (that is if you use same_data() to check, it will return true). Compared to set_label(), this function will return a new UniTensor object with different meta data.

Parameters

[in]	old_label	original label you want to replace
[in]	new_label	the new label

Attention: This function will return a new UniTensor with the new label, but the data is still shared with the original UniTensor. That is the meta data of the UniTensor is different, but the internal data is still shared.

See also: set_label(const std::string &old_label, const std::string &new_label)

◆ relabel() [5/6]

UniTensor cytnx::UniTensor::relabel ( const std::vector< std::string > & new_labels ) const

inline

relabel all of the labels in UniTensor.

Parameters

[in] new_labels the new labels for each bond.

Note

the new assign label cannot be the same as the label of any other bonds in the UniTensor. ( cannot have duplicate labels )

Attention: This function will return a new UniTensor with the new label, but the data is still shared with the original UniTensor. That is the meta data of the UniTensor is different, but the internal data is still shared.

◆ relabel() [6/6]

UniTensor cytnx::UniTensor::relabel	(	const std::vector< std::string > &	old_labels,
		const std::vector< std::string > &	new_labels
	)		const

inline

replace part or all labels by given new labels for the bonds.

Parameters

[in]	old_labels	the old labels for each bond.
[in]	new_labels	the new labels for each bond.

Note

the final output UniTensor cannot have duplicate labels.

◆ relabel_() [1/6]

UniTensor & cytnx::UniTensor::relabel_	(	const cytnx_int64 &	inx,
		const std::string &	new_label
	)

inline

rebable the legs in the UniTensor by given index.

This function will relabel the legs in the UniTensor by a given index. This function will alter the label of the UniTensor directly.

Parameters

[in]	inx	a given index
[in]	new_label	the new label of the UniTensor in the index `inx`

See also: set_label(const cytnx_int64 &idx, const std::string &new_label)

◆ relabel_() [2/6]

UniTensor & cytnx::UniTensor::relabel_ ( const std::initializer_list< char * > & new_labels )

inline

See also: relabel_(const std::vector<std::string> &new_labels)

◆ relabel_() [3/6]

UniTensor & cytnx::UniTensor::relabel_	(	const std::initializer_list< char * > &	old_labels,
		const std::initializer_list< char * > &	new_labels
	)

inline

See also: relabel_(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels)

◆ relabel_() [4/6]

UniTensor & cytnx::UniTensor::relabel_	(	const std::string &	old_label,
		const std::string &	new_label
	)

inline

relabel the legs in the UniTensor by a given label.

This function will relabel the legs in the UniTensor by a given label. This function will alter the label of the UniTensor directly.

Parameters

[in]	old_label	original label you want to replace
[in]	new_label	the new label

See also: set_label(const std::string &old_label, const std::string &new_label)

◆ relabel_() [5/6]

UniTensor & cytnx::UniTensor::relabel_ ( const std::vector< std::string > & new_labels )

inline

Set new labels for all the bonds.

Parameters

[in] new_labels the new labels for each bond.

Note

the new assign label cannot be the same as the label of any other bonds in the UniTensor. ( cannot have duplicate labels )
Compared to relabel(const std::vector<std::string> &new_labels) const, this function set the new label to itself.

◆ relabel_() [6/6]

UniTensor & cytnx::UniTensor::relabel_	(	const std::vector< std::string > &	old_labels,
		const std::vector< std::string > &	new_labels
	)

inline

relabel part or all of the labels in UniTensor by given new labels

Parameters

[in]	old_labels	the old labels for each bond.
[in]	new_labels	the new labels for each bond.

Note

the final output UniTensor cannot have duplicate labels.
Compared to relabel(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels) const , this function set the new label(s) to itself.

See also: relabel(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels) const

Attention: This function will return a new UniTensor with the new labels, but the data is still shared with the original UniTensor. That is the meta data of the UniTensor is different, but the internal data is still shared.

◆ relabels() [1/4]

UniTensor cytnx::UniTensor::relabels ( const std::initializer_list< char * > & new_labels ) const

inline

Deprecated:: This function is deprecated. Please use
UniTensor relabel(const std::initializer_list<char *> &new_labels) const
instead.

◆ relabels() [2/4]

UniTensor cytnx::UniTensor::relabels	(	const std::initializer_list< char * > &	old_labels,
		const std::initializer_list< char * > &	new_labels
	)		const

inline

Deprecated:: This function is deprecated. Please use
UniTensor relabel(const std::initializer_list<char *> &old_labels, const std::initializer_list<char *> &new_labels) const
instead.

◆ relabels() [3/4]

UniTensor cytnx::UniTensor::relabels ( const std::vector< std::string > & new_labels ) const

inline

Deprecated:: This function is deprecated. Please use
UniTensor relabel(const std::vector<std::string> &new_labels) const
instead.

◆ relabels() [4/4]

UniTensor cytnx::UniTensor::relabels	(	const std::vector< std::string > &	old_labels,
		const std::vector< std::string > &	new_labels
	)		const

inline

Deprecated:: This function is deprecated. Please use
UniTensor relabel(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels) const
instead.

◆ relabels_() [1/4]

UniTensor & cytnx::UniTensor::relabels_ ( const std::initializer_list< char * > & new_labels )

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::initializer_list<char *> &new_labels)
instead.

◆ relabels_() [2/4]

UniTensor & cytnx::UniTensor::relabels_	(	const std::initializer_list< char * > &	old_labels,
		const std::initializer_list< char * > &	new_labels
	)

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::initializer_list<char *> &old_labels, const std::initializer_list<char *> &new_labels)
instead.

◆ relabels_() [3/4]

UniTensor & cytnx::UniTensor::relabels_ ( const std::vector< std::string > & new_labels )

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::vector<std::string> &new_labels)
instead.

◆ relabels_() [4/4]

UniTensor & cytnx::UniTensor::relabels_	(	const std::vector< std::string > &	old_labels,
		const std::vector< std::string > &	new_labels
	)

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::vector<std::string> &old_labels, const std::vector<std::string> &new_labels)
instead.

◆ reshape()

UniTensor cytnx::UniTensor::reshape	(	const std::vector< cytnx_int64 > &	new_shape,
		const cytnx_uint64 &	rowrank = `0`
	)

inline

Reshape the UniTensor.

Parameters

[in]	new_shape	the new shape you want to reshape to.
[in]	rowrank	the rowrank of the UniTensor after you reshape it.

Note: This function only works for non-symmetric UniTensor. That is, the UniTensor cannot be UTenType::Block.

◆ reshape_()

UniTensor & cytnx::UniTensor::reshape_	(	const std::vector< cytnx_int64 > &	new_shape,
		const cytnx_uint64 &	rowrank = `0`
	)

inline

Reshape the UniTensor, inplacely.

Note: This function only works for non-symmetric UniTensor. That is, the UniTensor cannot be UTenType::Block.

See also: reshape(const std::vector<cytnx_int64> &new_shape, const cytnx_uint64 &rowrank)

◆ rowrank()

cytnx_uint64 cytnx::UniTensor::rowrank ( ) const

inline

Return the row rank of the UniTensor.

Returns: cytnx_uint64

◆ same_data()

bool cytnx::UniTensor::same_data ( const UniTensor & rhs ) const

inline

Check whether the Blocks address are the same.

Returns: bool

◆ Save() [1/2]

void cytnx::UniTensor::Save ( const char * fname ) const

save a UniTensor to file

Save a UniTensor to file. The file extension will be extended as '.cytnx'

Parameters

[in] fname the file name (exclude the file extension).

See also: Load(const char *fname)

◆ Save() [2/2]

void cytnx::UniTensor::Save ( const std::string & fname ) const

save a UniTensor to file

Save a UniTensor to file. The file extension will be extended as '.cytnx'

Parameters

[in] fname the file name (exclude the file extension).

See also: Load(const std::string &fname)

◆ set() [1/2]

UniTensor & cytnx::UniTensor::set	(	const std::vector< Accessor > &	accessors,
		const Tensor &	rhs
	)

inline

set elements using Accessor (C++ API) / slices (python API)

Parameters

[in]	accessors	the Accessor (C++ API) / slices (python API) to set the elements.
[in]	rhs	the tensor containing the values to set.

Returns: [UniTensor]

See also: Tensor::set, UniTensor::operator[], UniTensor::get

Note

The return will be a new UniTensor instance, which does not share memory with the current UniTensor.
Equivalently, one can also use the [] operator to access elements.
For diagonal UniTensors, the accessor list can have either one element (to address the diagonal elements; rhs must be one-dimensional), or two elements (in this case, the output will be a non-diagonal UniTensor; rhs must be two-dimensional).

◆ set() [2/2]

UniTensor & cytnx::UniTensor::set	(	const std::vector< Accessor > &	accessors,
		const UniTensor &	rhs
	)

inline

◆ set_elem()

template<class T2 >

UniTensor & cytnx::UniTensor::set_elem	(	const std::vector< cytnx_uint64 > &	locator,
		const T2 &	rc
	)

inline

Deprecated:: This function is deprecated, please use at() instread.

Note: C++: Deprecated soon, use at()

◆ set_label() [1/6]

UniTensor & cytnx::UniTensor::set_label	(	const char *	old_label,
		const char *	new_label
	)

inline

See also: set_label(const std::string &old_label, const std::string &new_label)

◆ set_label() [2/6]

UniTensor & cytnx::UniTensor::set_label	(	const char *	old_label,
		const std::string &	new_label
	)

inline

See also: set_label(const std::string &old_label, const std::string &new_label)

◆ set_label() [3/6]

UniTensor & cytnx::UniTensor::set_label	(	const cytnx_int64 &	idx,
		const char *	new_label
	)

inline

See also: set_label(const cytnx_int64 &idx, const std::string &new_label)

◆ set_label() [4/6]

UniTensor & cytnx::UniTensor::set_label	(	const cytnx_int64 &	idx,
		const std::string &	new_label
	)

inline

Deprecated:: This function is deprecated. Please use
UniTensor &set_label_(const cytnx_int64 &idx, const std::string &new_label)
instead.

◆ set_label() [5/6]

UniTensor & cytnx::UniTensor::set_label	(	const std::string &	old_label,
		const char *	new_label
	)

inline

See also: set_label(const std::string &old_label, const std::string &new_label)

◆ set_label() [6/6]

UniTensor & cytnx::UniTensor::set_label	(	const std::string &	old_label,
		const std::string &	new_label
	)

inline

Deprecated:: This function is deprecated. Please use
UniTensor &set_label_(const std::string &old_label, const std::string &new_label)
instead.

◆ set_label_() [1/6]

UniTensor & cytnx::UniTensor::set_label_	(	const char *	old_label,
		const char *	new_label
	)

inline

See also: set_label_(const std::string &old_label, const std::string &new_label)

◆ set_label_() [2/6]

UniTensor & cytnx::UniTensor::set_label_	(	const char *	old_label,
		const std::string &	new_label
	)

inline

See also: set_label_(const std::string &old_label, const std::string &new_label)

◆ set_label_() [3/6]

UniTensor & cytnx::UniTensor::set_label_	(	const cytnx_int64 &	idx,
		const char *	new_label
	)

inline

See also: set_label_(const cytnx_int64 &idx, const std::string &new_label)

◆ set_label_() [4/6]

UniTensor & cytnx::UniTensor::set_label_	(	const cytnx_int64 &	idx,
		const std::string &	new_label
	)

inline

Set a new label for bond at the assigned index, in-place.

Parameters

[in]	idx	the index of the bond.
[in]	new_label	the new label that is assign to the bond.

Note

the new assign label cannot be the same as the label of any other bonds in the UniTensor. ( cannot have duplicate labels )
Compared to relabel(const cytnx_int64 &idx, const std::string &new_label) const, this function set the new label and return self.

◆ set_label_() [5/6]

UniTensor & cytnx::UniTensor::set_label_	(	const std::string &	old_label,
		const char *	new_label
	)

inline

See also: set_label_(const std::string &old_label, const std::string &new_label)

◆ set_label_() [6/6]

UniTensor & cytnx::UniTensor::set_label_	(	const std::string &	old_label,
		const std::string &	new_label
	)

inline

set a new label for bond to replace one of the current label, in-place.

Parameters

[in]	old_label	the current label of the bond.
[in]	new_label	the new label that is assign to the bond.

Note

the new assign label cannot be the same as the label of any other bonds in the UniTensor. ( cannot have duplicate labels )
Compared to relabel(const std::string &old_label, const std::string &new_label) const, this function set the new label and return self.

◆ set_labels() [1/2]

UniTensor & cytnx::UniTensor::set_labels ( const std::initializer_list< char * > & new_labels )

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::initializer_list<char *> &new_labels)
instead.

◆ set_labels() [2/2]

UniTensor & cytnx::UniTensor::set_labels ( const std::vector< std::string > & new_labels )

inline

Deprecated:: This function is deprecated. Please use
UniTensor &relabel_(const std::vector<std::string> &new_labels)
instead.

◆ set_name()

UniTensor & cytnx::UniTensor::set_name ( const std::string & in )

inline

Deprecated:: This function is deprecated. Please use set_name_(const std::string &in) instead.

◆ set_name_()

UniTensor & cytnx::UniTensor::set_name_ ( const std::string & in )

inline

Set the name of a UniTensor, in-place.

You can use this function to give a name for the UniTensor.

Parameters

[in] in Input the name you want to set for the UniTensor. It should be a string.

Returns: UniTensor& (self)

◆ set_rowrank()

UniTensor cytnx::UniTensor::set_rowrank ( const cytnx_uint64 & new_rowrank ) const

inline

◆ set_rowrank_()

UniTensor & cytnx::UniTensor::set_rowrank_ ( const cytnx_uint64 & new_rowrank )

inline

Set the rowrank of the UniTensor.

You can use this function to set the row rank of the UniTensor. The row rank is important if you want to use the linear algebra process.

Parameters

[in] new_rowrank the new row rank of the UniTensor

◆ shape()

std::vector< cytnx_uint64 > cytnx::UniTensor::shape ( ) const

inline

Get the shape of the UniTensor.

Returns: std::vector<cytnx_uint64>

◆ signflip()

std::vector< bool > cytnx::UniTensor::signflip ( ) const

inline

Get the sign information of a fermionic UniTensor.

Length is the number of blocks in the UniTensor. If the return is true, the sign of the elements of the corresponding block needs to be flipped.

Returns: std::vector<bool>

◆ size()

cytnx_uint64 cytnx::UniTensor::size ( ) const

inline

Return the total number of logical elements in the UniTensor.

For block UniTensors this is the dense size implied by the bond dimensions, not the number of physically stored block coefficients.

Returns: [cytnx_uint64] 1 for a rank-0 scalar, 0 for a void UniTensor or any zero extent.

◆ Sub() [1/2]

UniTensor cytnx::UniTensor::Sub ( const Scalar & rhs ) const

The subtraction function for a given scalar.

Given the scalar rhs, it will perform the subtraction for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs the subtrahend

Returns: UniTensor

Note: Compared to Sub_(const Scalar&), this function will create a new UniTensor.

See also: Sub_(const Scalar&), Sub_(const UniTensor&), Sub(const UniTensor&)const, operator-=(const UniTensor&), operator-=(const Scalar&), operator-

◆ Sub() [2/2]

UniTensor cytnx::UniTensor::Sub ( const UniTensor & rhs ) const

The subtraction function of the UniTensor.

This is subtraction function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return a new UniTensor

\[ UT = UT_{self} - UT_2 \]

Perform element-wise subtraction of two UniTensor.

Parameters

[in] rhs the subtrahend

Returns: UniTensor

Precondition: The two UniTensor need to have same structure.

Note: Compared to Sub_(const UniTensor&), this function will create a new UniTensor.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Sub_(const UniTensor&), Sub_(const Scalar&), Sub(const Scalar&)const , operator-=(const UniTensor&), operator-=(const Scalar&), operator-

◆ Sub_() [1/2]

UniTensor & cytnx::UniTensor::Sub_ ( const Scalar & rhs )

inline

The subtraction function for a given scalar.

Given the scalar rhs, it will perform the subtraction for each element in UniTensor with this scalar rhs.

Parameters

[in] rhs a scalar you want to subtract in the UniTensor.

Returns: UniTensor&

Note: Compared to Sub(const Scalar&)const, this is an inplace function.

See also: Sub_(const UniTensor&), Sub(const UniTensor&)const, Sub(const Scalar&)const , operator-=(const UniTensor&), operator-=(const Scalar&), operator-

◆ Sub_() [2/2]

UniTensor & cytnx::UniTensor::Sub_ ( const UniTensor & rhs )

inline

The subtraction function of the UniTensor.

This is subtraction function of the UniTensor. Given the UniTensor \( UT_2\) as the argument, it will return

\[ UT_{self} = UT_{self} - UT_2 \]

Perform element-wise subtraction of two UniTensor.

Parameters

[in] rhs the subtrahend

Returns: UniTensor&

Precondition: The two UniTensor need to have same structure.

Note: Compared to Sub(const UniTensor&)const, this is an inplace function.; internal/advanced: not a TN operation; python surface removed per #934; see operator+(const UniTensor&, const UniTensor&) in include/linalg.hpp for the full rationale.

See also: Sub_(const Scalar&), Sub(const UniTensor&)const, Sub(const Scalar&)const , operator-=(const UniTensor&), operator-=(const Scalar&), operator-

◆ syms()

std::vector< Symmetry > cytnx::UniTensor::syms ( ) const

inline

Return the symmetry type of the UniTensor.

We can get the Symmetry structure by calling this function.

Returns: std::vector<Symmetry>

◆ tag()

UniTensor & cytnx::UniTensor::tag ( )

inline

Deprecated:: This function is deprecated. Please use tag_() instead.

◆ tag_()

UniTensor & cytnx::UniTensor::tag_ ( )

inline

Set the UniTensor as a tagged UniTensor, in-place.

This function will set the untagged UniTensor(all of the Bonds are BondType::BD_REG) ) to tagged UniTensor (all of the Bonds are BondType::BD_BRA or BondType::BD_KET). And it will change the UniTensor to bra-ket form. See is_braket_form() for more information.

See also: is_braket_form()

◆ to()

UniTensor cytnx::UniTensor::to ( const int & device ) const

inline

move the current UniTensor to the assigned device.

Warning: if the device-id is the same as current Tensor's device, then return self. otherwise, return a copy of instance that located on the target device.

Parameters

[in] device the device-id(cytnx::Device) that is moving to. It can by any device defined in cytnx::Device.

Returns: UniTensor

See also: to(const int &device)

◆ to_()

UniTensor & cytnx::UniTensor::to_ ( const int & device )

inline

move the current UniTensor to the assigned device (inplace).

Parameters

[in] device the device-id(cytnx::Device) that is moving to. It can by any device defined in cytnx::Device.

See also: to_(const int &device)

◆ to_dense()

UniTensor cytnx::UniTensor::to_dense ( )

inline

Convert the UniTensor to non-diagonal form.

Converts a UniTensor with is_diag = true to one with is_diag = false by expanding each block into a (diagonal) matrix.

Note: If the input tensor is already non-diagonal (is_diag = false), the input is returned. So every manipulation on the returned tensor will change the input tensor. Call clone() on the result if an independent copy is required.

Returns: UniTensor

See also: to_dense_(), is_diag()

◆ to_dense_()

UniTensor & cytnx::UniTensor::to_dense_ ( )

inline

Convert the UniTensor to non-diagonal form, inplacely.

See also: to_dense(), is_diag()

◆ Trace() [1/2]

UniTensor cytnx::UniTensor::Trace	(	const cytnx_int64 &	a = `0`,
		const cytnx_int64 &	b = `1`
	)		const

inline

Take the partial trace of the UniTensor.

Take the partial trace to the UniTensor with the give two labels.

Parameters

[in]	a	label 1
[in]	b	label 2

Returns: UniTensor

Note: Compared to Trace_(), this function will return a new UniTensor object.

See also: Trace_()

◆ Trace() [2/2]

UniTensor cytnx::UniTensor::Trace	(	const std::string &	a,
		const std::string &	b
	)		const

inline

Take the partial trace of the UniTensor.

Take the partial trace to the UniTensor with the give two labels.

Parameters

[in]	a	label 1
[in]	b	label 2

Returns: UniTensor

Note: Compared to Trace_(), this function will return a new UniTensor object.

See also: Trace_()

◆ Trace_() [1/2]

UniTensor & cytnx::UniTensor::Trace_	(	const cytnx_int64 &	a = `0`,
		const cytnx_int64 &	b = `1`
	)

inline

Take the partial trace of the UniTensor, inplacely.

Take the partial trace to the UniTensor with the give two labels.

Parameters

[in]	a	label 1
[in]	b	label 2

Returns: UniTensor&

Note: Compared to Trace(), this is an inplace function.

See also: Trace()

◆ Trace_() [2/2]

UniTensor & cytnx::UniTensor::Trace_	(	const std::string &	a,
		const std::string &	b
	)

inline

Take the partial trace of the UniTensor, inplacely.

Take the partial trace to the UniTensor with the give two labels.

Parameters

[in]	a	label 1
[in]	b	label 2

Returns: UniTensor&

Note: Compared to Trace(), this is an inplace function.

See also: Trace()

◆ Transpose()

UniTensor cytnx::UniTensor::Transpose ( ) const

inline

Take the transpose of the UniTensor.

This function takes the transpose of a UniTensor: 1) The order of the indices is inverted. 2) Incoming legs become outgoing ones, and vice versa. 3) The rowrank is set to rank - old rowrank, such that left indices become right indices and vice versa.

Returns: UniTensor

Note: This function does not only exchange left- and right indices, but inverts the order of all indices.; Compared to Transpose_(), this function will return new UniTensor object.

See also: Transpose_()

◆ Transpose_()

UniTensor & cytnx::UniTensor::Transpose_ ( )

inline

Take the transpose of the UniTensor, inplacely.

Returns: UniTensor

Note: This function inverts the order of all indices.; Compared to Transpose(), this function is an inplace function.

See also: Transpose()

◆ truncate() [1/2]

UniTensor cytnx::UniTensor::truncate	(	const cytnx_int64 &	bond_idx,
		const cytnx_uint64 &	dim
	)		const

inline

truncate bond dimension of the UniTensor by the given bond index and dimension.

Parameters

[in]	bond_idx	the bond index.
[in]	dim	the dimension to be truncated.

Returns: [UniTensor]

Note: Compared to truncate_(const cytnx_int64 &bond_idx, const cytnx_uint64 &dim), this function will return a new UniTensor object.

See also: UniTensor::truncate_(const cytnx_int64 &bond_idx, const cytnx_uint64 &dim)

◆ truncate() [2/2]

UniTensor cytnx::UniTensor::truncate	(	const std::string &	label,
		const cytnx_uint64 &	dim
	)		const

inline

truncate bond dimension of the UniTensor by the given bond label and dimension.

Parameters

[in]	label	the bond label.
[in]	dim	the dimension to be truncated.

Returns: [UniTensor]

Note: Compared to truncate_(const std::string &bond_idx, const cytnx_uint64 &dim), this function will return a new UniTensor object.

See also: UniTensor::truncate_(const std::string &bond_idx, const cytnx_uint64 &dim)

◆ truncate_() [1/2]

UniTensor & cytnx::UniTensor::truncate_	(	const cytnx_int64 &	bond_idx,
		const cytnx_uint64 &	dim
	)

inline

truncate bond dimension of the UniTensor by the given bond index and dimension.

Parameters

[in]	bond_idx	the bond index.
[in]	dim	the dimension to be truncated.

Returns: [UniTensor]

Note: Compared to truncate(const cytnx_int64 &bond_idx, const cytnx_uint64 &dim), this is inplace function and will modify the current UniTensor object.

◆ truncate_() [2/2]

UniTensor & cytnx::UniTensor::truncate_	(	const std::string &	label,
		const cytnx_uint64 &	dim
	)

inline

truncate bond dimension of the UniTensor by the given bond label and dimension.

Parameters

[in]	label	the bond label.
[in]	dim	the dimension to be truncated.

Returns: [UniTensor]

Note: Compared to truncate(const std::string &bond_idx, const cytnx_uint64 &dim), this is inplace function and will modify the current UniTensor object.

◆ twist() [1/2]

UniTensor cytnx::UniTensor::twist ( const cytnx_int64 & idx ) const

inline

Apply a twist (or braids/self-swap) operation to a given bond; No effect for bosonic tensors; for a fermionic tensor, this means that a signflip occurs for all blocks where the bond has odd fermion parity.

Parameters

[in] idx bond index on which the twist shall be applied

Note: This always applies the twist to the bond, ignoring its direction or whether they are incoming or outgoing bonds.

◆ twist() [2/2]

UniTensor cytnx::UniTensor::twist ( const std::string & label ) const

inline

Apply a twist (or braids/self-swap) operation to a given bond; No effect for bosonic tensors; for a fermionic tensor, this means that a signflip occurs for all blocks where the bond has odd fermion parity.

Parameters

[in] label bond label on which the twist shall be applied

Note: This always applies the twist to the bond, ignoring its direction or whether they are incoming or outgoing bonds.

◆ twist_() [1/2]

UniTensor & cytnx::UniTensor::twist_ ( const cytnx_int64 & idx )

inline

Inline version.

Parameters

[in] idx bond index on which the twist shall be applied

See also: twist(const cytnx_int64 &idx)

◆ twist_() [2/2]

UniTensor & cytnx::UniTensor::twist_ ( const std::string & label )

inline

Inline version.

Parameters

[in] label bond label on which the twist shall be applied

See also: twist(const std::string &label)

◆ uniform() [1/2]

static UniTensor cytnx::UniTensor::uniform	(	const cytnx_uint64 &	Nelem,
		const double &	low,
		const double &	high,
		const std::vector< std::string > &	in_labels = `{}`,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const std::string &	name = `""`
	)

static

Generate a one-bond UniTensor with all elements are random numbers sampled from a uniform distribution.

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution. The low bound is low and the high bound is high.

Parameters

[in]	Nelem	the number of elements.
[in]	low	the low bound of the uniform distribution.
[in]	high	the high bound of the uniform distribution.
[in]	in_labels	the labels of the UniTensor.
[in]	seed	the seed of the random generator.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: random::uniform(const cytnx_uint64 &Nelem, const double &low, const double &high, const int &device, const unsigned int &seed, const unsigned int &dtype)

◆ uniform() [2/2]

static UniTensor cytnx::UniTensor::uniform	(	const std::vector< cytnx_uint64 > &	shape,
		const double &	low,
		const double &	high,
		const std::vector< std::string > &	in_labels = `{}`,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`,
		const unsigned int &	dtype = `Type.Double`,
		const int &	device = `Device.cpu`,
		const std::string &	name = `""`
	)

static

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution.

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution. The low bound is low and the high bound is high.

Parameters

[in]	shape	the shape of the UniTensor.
[in]	low	the low bound of the uniform distribution.
[in]	high	the high bound of the uniform distribution.
[in]	in_labels	the labels of the UniTensor.
[in]	seed	the seed of the random generator.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: random::uniform(const std::vector< cytnx_uint64 > &shape, const double &low, const double &high, const int &device, const unsigned int &seed, const unsigned int &dtype)

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution.

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution. The low bound is low and the high bound is high.

Parameters

[in]	shape	the shape of the UniTensor.
[in]	low	the low bound of the uniform distribution.
[in]	high	the high bound of the uniform distribution.
[in]	in_labels	the labels of the UniTensor.
[in]	seed	the seed of the random generator.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: random::uniform(const std::vector< cytnx_uint64 > &shape, const double &low, const double &high, const int &device, const unsigned int &seed, const unsigned int &dtype)

◆ uniform_()

UniTensor & cytnx::UniTensor::uniform_	(	const double &	low = `0`,
		const double &	high = `1`,
		const unsigned int &	seed = `cytnx::random::__static_random_device()`
	)

Generate a UniTensor with all elements are random numbers sampled from a uniform distribution, inplacely.

This function provides an inplacely way to generate a UniTensor with all elements are random numbers sampled from a uniform distribution. The low bound is low and the high bound is high.

Parameters

[in]	low	the low bound of the uniform distribution.
[in]	high	the high bound of the uniform distribution.
[in]	seed	the seed of the random generator.

See also: random::uniform_(UniTensor &in, const double &low, const double &high, const unsigned int &seed)

◆ uten_type()

int cytnx::UniTensor::uten_type ( ) const

inline

Return the UniTensor type (cytnx::UTenType) of the UniTensor.

The function return the UniTensor type of the UniTensor.

Returns: int

See also: uten_type_str()

◆ uten_type_str()

std::string cytnx::UniTensor::uten_type_str ( ) const

inline

Return the UniTensor type (cytnx::UTenType) of the UniTensor in 'string' form.

Returns: std::string

See also: uten_type()

◆ zeros() [1/2]

static UniTensor cytnx::UniTensor::zeros	(	const std::vector< cytnx_uint64 > &	shape,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

Generate a UniTensor with all elements set to zero.

Parameters

[in]	shape	the shape of the UniTensor.
[in]	in_labels	the labels of the UniTensor.
[in]	dtype	the data type of the UniTensor, see cytnx::Type for more information.
[in]	device	the device type of the UniTensor, see cytnx::Device for more information.
[in]	name	the name of the UniTensor.

Returns: [UniTensor]

See also: zeros(const std::vector< cytnx_uint64 > &Nelem, const unsigned int &dtype, const int &device)

◆ zeros() [2/2]

static UniTensor cytnx::UniTensor::zeros	(	std::initializer_list< cytnx_uint64 >	shape,
		const std::vector< std::string > &	in_labels = `{}`,
		unsigned int	dtype = `Type.Double`,
		int	device = `Device.cpu`,
		const std::string &	name = `""`
	)

inlinestatic

The documentation for this class was generated from the following file:

include/UniTensor.hpp

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ UniTensor() [1/2]

Example:

C++ API:

output>

Python API:

output>

◆ UniTensor() [2/2]

Member Function Documentation

◆ Add() [1/2]

◆ Add() [2/2]

◆ Add_() [1/2]

◆ Add_() [2/2]

◆ apply()

◆ apply_()

◆ arange() [1/2]

◆ arange() [2/2]

◆ astype()

◆ at() [1/8]

◆ at() [2/8]

◆ at() [3/8]

◆ at() [4/8]

◆ at() [5/8]

◆ at() [6/8]

◆ at() [7/8]

◆ at() [8/8]

◆ bond() [1/2]

◆ bond() [2/2]

◆ bond_() [1/4]

◆ bond_() [2/4]

◆ bond_() [3/4]

◆ bond_() [4/4]

◆ bonds()

◆ clone()

◆ combineBond()

◆ combineBond_()

◆ combineBonds() [1/3]

◆ combineBonds() [2/3]

◆ combineBonds() [3/3]

◆ Conj()

◆ Conj_()

◆ contiguous()

◆ contiguous_()

◆ contract()

◆ convert_from()

◆ convert_from_()

◆ Dagger()

◆ Dagger_()

◆ device()

◆ device_str()

◆ Div() [1/2]

◆ Div() [2/2]

◆ Div_() [1/2]

◆ Div_() [2/2]

◆ dtype()

◆ dtype_str()

◆ elem_exists()

◆ eye()

◆ fermion_twists()

◆ fermion_twists_()

◆ get()

◆ get_block() [1/6]

◆ get_block() [2/6]

◆ get_block() [3/6]

◆ get_block() [4/6]

◆ get_block() [5/6]

◆ get_block() [6/6]

◆ get_block_() [1/10]

◆ get_block_() [2/10]

◆ get_block_() [3/10]

◆ get_block_() [4/10]

◆ get_block_() [5/10]

◆ get_block_() [6/10]

◆ get_block_() [7/10]

◆ get_block_() [8/10]

◆ get_block_() [9/10]

◆ get_block_() [10/10]