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xchen::TensorArray< T, dims > Class Template Reference

A multi-array, with the same shape in each direction. More...

#include <TensorArray.H>

List of all members.

Public Methods
	TensorArray ()
	construct an empty tensor array.
	TensorArray (int sz,...)
	1st arg is array size in dimension 'dims-1'. Assuming list has 'dims' args.
	TensorArray (int *sz)
	array size in dimension 'd' is sz[d]. Assuming 'dims' sizes given.
	TensorArray (MyType const &)
	An exact copy of the given array.
	TensorArray (MyType const &, int d, int s, int e)
	An exact copy of the subarray, specified as: d:[s, e).
	TensorArray (MyType const &, int *start, int *end)
	An exact copy of the subarray, specified as: [start[], end[]).
	TensorArray (TensorArray< T, dims+1 > const &rhs, int d, int s)
	Construct from a slice from an array of SuperType(one dimension higher).
	~TensorArray ()
TensorArray &	Transform (xchen::Transform const &)
	Assume the element type can be transformed.
void	Clear ()
	Delete all elements to become an empty array.
bool	Empty () const
	return true if empty array.
void	PopFront (int i=0)
	erase the front elements of each row in i dir.
void	PopBack (int i=0)
	erase the back elements of each row in i dir.
void	Insert (linear_iterator itr, T const &val)
	Insert before the linear iterator(point to the inserted afterward).++(size_at_last_dimension).
void	Insert (int dir, int before)
	Insert 'before' at each row of the dir. ++(size_at_dir). Uninitialized.
void	SetN (int N)
	Set reserved subdivision depth to N.
void	InsertMiddlePoints (bool average=true)
	set sbd_dpth to 1 if 0. insert uninitualized or average value inbetween eles(rows). dec sbd_dpth.
void	Averaging ()
	Averaging each hyper-cube cells into its lowerleft corner. dec sz in each dir by one.
TensorArray &	operator= (const TensorArray &rhs)
	An exact copy of rhs, except the capacity.
int	GetSize (int dir=0) const
	get array size in direction 'dir'.
void	GetSize (int *Sz) const
	Sz[d] <-- array size of dir 'd'.
int	GetTotalSize () const
	Get total elements in the multi-array.
void	Reserve (int newCapacity,...)
	reserve at least 'newCapacity' for dir 'dims-1', and so on...
void	Reserve (int *newCapacity)
	reserve at least newCapacity[d] for dir 'd'.
void	Resize (int newSz,...)
	expand(no initialization) or cut to 'newSz' for dir 'dims-1', and so on...
void	Resize (int *newSz)
	expand(no initialization) or cut to 'Sz[d]' for dir 'd'.
void	ResizeOneDirection (int i, int new_sz)
	resize direction i.
void	CopyExtend (int left,...)
	ArgList: left,right, left',right'... Copy-Expand two ends left and right times at dir dims-1, etc.
void	CopyExtend (int *rightleft)
	Right-copy-expand 'rightleft[0]' and Left-copy-expand 'rightleft[1]' eles at dir 0, etc.
void	CopyExtendAtDirection (int i, int left, int right)
	Left-Copy extend the left end point left times at dir i, and Right-Copy....
void	ExtendAtDirection (int i, int left, int right)
	Left extend the left end point left times at dir i, and Right extend....
void	Extend (int left,...)
	ArgList: left,right, ... Expand two ends left and right times at dir dims-1, and so on.
void	Extend (int *rightleft)
	Right-expand 'rightleft[0]' and Left-expand 'rightleft[1]' eles at dir 0, etc. No initialization.
slc_iterator	SliceIterate (int dir=0, int start=0, int end=0)
	end=0 defaults to size().
linear_iterator	LinearIterate (int dir, int start, int len)
	Subarray is dir:[start, start+len).
linear_iterator	LinearIterate (int *start=0, int *end=0)
	1D iterate the specified subarray
linear_iterator	Begin ()
	Begin 1D iteration of the array.
linear_iterator	End ()
	End 1D iteration of the array.
linear_riterator	LinearReverseIterate (int dir, int start, int len)
	Subarray is dir:[start, start+len).
linear_riterator	LinearReverseIterate (int *start=0, int *end=0)
	reverse version.
linear_riterator	Rbegin ()
	reverse version.
linear_riterator	Rend ()
	reverse version.
row_iterator	RowIterate (int row_d, int subarray_d, int start, int len)
	Subarray is subarray_d:[start, start+len).
row_iterator	RowIterate (int d=0, int *start=0, int *end=0)
	Iterate the subarray row by row.
row_riterator	RowReverseIterate (int r_d, int sub_d, int start, int L)
	Subarray is sub_d:[start, start+L).
row_riterator	RowReverseIterate (int d=0, int *start=0, int *end=0)
	Iterate the subarray row by row.
idx_op_ret_t	operator[] (int i)
	Used for operations [][]..[].
T &	operator[] (Vector< int, dims >const &i)
	Vector indexing operation.
ListAssignmentCheckSzRt< T, linear_iterator >	operator= (T)
	Assignment from a list.
T const &	GetElement (int *idx) const
	Assume idx of len dims. idx[0] is lowest index.
T const &	GetElement (int i,...) const
	Assume argLst of len dims. First arg is highest index.
void	PrintShape () const
	Output size and capacity of each direction.
Friends
class	TensorArray< T, dims-1 >
ostream &	operator<< (ostream &os, const TensorArray &)

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Detailed Description

template<typename T, int dims>
class xchen::TensorArray< T, dims >

A multi-array, with the same shape in each direction.

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Constructor & Destructor Documentation

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (    )  [inline]

construct an empty tensor array.

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  int    sz, ...    )  [inline, explicit]

1st arg is array size in dimension 'dims-1'. Assuming list has 'dims' args.

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  int *    sz )  [inline, explicit]

array size in dimension 'd' is sz[d]. Assuming 'dims' sizes given.

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  MyType const &    )  [inline]

An exact copy of the given array.

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  MyType const &   , int    d, int    s, int    e )  [inline]

An exact copy of the subarray, specified as: d:[s, e).

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  MyType const &   , int *    start, int *    end )  [inline]

An exact copy of the subarray, specified as: [start[], end[]).

template<typename T, int dims> xchen::TensorArray< T, dims >::TensorArray (  TensorArray< T, dims+1 > const &    rhs, int    d, int    s )  [inline]

Construct from a slice from an array of SuperType(one dimension higher).

template<typename T, int dims> xchen::TensorArray< T, dims >::~TensorArray (    )  [inline]

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Member Function Documentation

template<typename T, int dims> void xchen::TensorArray< T, dims >::Averaging (    )

Averaging each hyper-cube cells into its lowerleft corner. dec sz in each dir by one.

template<typename T, int dims> linear_iterator xchen::TensorArray< T, dims >::Begin (    )  [inline]

Begin 1D iteration of the array.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Clear (    )  [inline]

Delete all elements to become an empty array.

template<typename T, int dims> void xchen::TensorArray< T, dims >::CopyExtend (  int *    rightleft )  [inline]

Right-copy-expand 'rightleft[0]' and Left-copy-expand 'rightleft[1]' eles at dir 0, etc.

template<typename T, int dims> void xchen::TensorArray< T, dims >::CopyExtend (  int    left, ...    )  [inline]

ArgList: left,right, left',right'... Copy-Expand two ends left and right times at dir dims-1, etc.

template<typename T, int dims> void xchen::TensorArray< T, dims >::CopyExtendAtDirection (  int    i, int    left, int    right )  [inline]

Left-Copy extend the left end point left times at dir i, and Right-Copy....

template<typename T, int dims> bool xchen::TensorArray< T, dims >::Empty (    )  const [inline]

return true if empty array.

template<typename T, int dims> linear_iterator xchen::TensorArray< T, dims >::End (    )  [inline]

End 1D iteration of the array.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Extend (  int *    rightleft )  [inline]

Right-expand 'rightleft[0]' and Left-expand 'rightleft[1]' eles at dir 0, etc. No initialization.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Extend (  int    left, ...    )  [inline]

ArgList: left,right, ... Expand two ends left and right times at dir dims-1, and so on.

template<typename T, int dims> void xchen::TensorArray< T, dims >::ExtendAtDirection (  int    i, int    left, int    right )  [inline]

Left extend the left end point left times at dir i, and Right extend....

template<typename T, int dims> T const & xchen::TensorArray< T, dims >::GetElement (  int    i, ...    )  const

Assume argLst of len dims. First arg is highest index.

template<typename T, int dims> T const & xchen::TensorArray< T, dims >::GetElement (  int *    idx )  const

Assume idx of len dims. idx[0] is lowest index.

template<typename T, int dims> void xchen::TensorArray< T, dims >::GetSize (  int *    Sz )  const [inline]

Sz[d] <-- array size of dir 'd'.

template<typename T, int dims> int xchen::TensorArray< T, dims >::GetSize (  int    dir = 0 )  const [inline]

get array size in direction 'dir'.

template<typename T, int dims> int xchen::TensorArray< T, dims >::GetTotalSize (    )  const [inline]

Get total elements in the multi-array.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Insert (  int    dir, int    before )

Insert 'before' at each row of the dir. ++(size_at_dir). Uninitialized.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Insert (  linear_iterator    itr, T const &    val )

Insert before the linear iterator(point to the inserted afterward).++(size_at_last_dimension).

template<typename T, int dims> void xchen::TensorArray< T, dims >::InsertMiddlePoints (  bool    average = true )

set sbd_dpth to 1 if 0. insert uninitualized or average value inbetween eles(rows). dec sbd_dpth.

template<typename T, int dims> linear_iterator xchen::TensorArray< T, dims >::LinearIterate (  int *    start = 0, int *    end = 0 )  [inline]

1D iterate the specified subarray

template<typename T, int dims> TensorArray< T, dims >::linear_iterator xchen::TensorArray< T, dims >::LinearIterate (  int    dir, int    start, int    len )  [inline]

Subarray is dir:[start, start+len).

template<typename T, int dims> linear_riterator xchen::TensorArray< T, dims >::LinearReverseIterate (  int *    start = 0, int *    end = 0 )  [inline]

reverse version.

template<typename T, int dims> TensorArray< T, dims >::linear_riterator xchen::TensorArray< T, dims >::LinearReverseIterate (  int    dir, int    start, int    len )  [inline]

Subarray is dir:[start, start+len).

template<typename T, int dims> ListAssignmentCheckSzRt< T, typename TensorArray< T, dims >::linear_iterator > xchen::TensorArray< T, dims >::operator= (  T    )

Assignment from a list.

template<typename T, int dims> TensorArray< T, dims > & xchen::TensorArray< T, dims >::operator= (  const TensorArray< T, dims > &    rhs )

An exact copy of rhs, except the capacity.

template<typename T, int dims> T & xchen::TensorArray< T, dims >::operator[] (  Vector< int, dims >const &    i )  [inline]

Vector indexing operation.

template<typename T, int dims> TensorArrayIndexOperatorTraits< T, dims >::ReturnType xchen::TensorArray< T, dims >::operator[] (  int    i )  [inline]

Used for operations [][]..[].

template<typename T, int dims> void xchen::TensorArray< T, dims >::PopBack (  int    i = 0 )

erase the back elements of each row in i dir.

template<typename T, int dims> void xchen::TensorArray< T, dims >::PopFront (  int    i = 0 )

erase the front elements of each row in i dir.

template<typename T, int dims> void xchen::TensorArray< T, dims >::PrintShape (    )

Output size and capacity of each direction.

template<typename T, int dims> linear_riterator xchen::TensorArray< T, dims >::Rbegin (    )  [inline]

reverse version.

template<typename T, int dims> linear_riterator xchen::TensorArray< T, dims >::Rend (    )  [inline]

reverse version.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Reserve (  int *    newCapacity )

reserve at least newCapacity[d] for dir 'd'.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Reserve (  int    newCapacity, ...    )  [inline]

reserve at least 'newCapacity' for dir 'dims-1', and so on...

template<typename T, int dims> void xchen::TensorArray< T, dims >::Resize (  int *    newSz )

expand(no initialization) or cut to 'Sz[d]' for dir 'd'.

template<typename T, int dims> void xchen::TensorArray< T, dims >::Resize (  int    newSz, ...    )  [inline]

expand(no initialization) or cut to 'newSz' for dir 'dims-1', and so on...

template<typename T, int dims> void xchen::TensorArray< T, dims >::ResizeOneDirection (  int    i, int    new_sz )

resize direction i.

template<typename T, int dims> row_iterator xchen::TensorArray< T, dims >::RowIterate (  int    d = 0, int *    start = 0, int *    end = 0 )  [inline]

Iterate the subarray row by row.

template<typename T, int dims> TensorArray< T, dims >::row_iterator xchen::TensorArray< T, dims >::RowIterate (  int    row_d, int    subarray_d, int    start, int    len )  [inline]

Subarray is subarray_d:[start, start+len).

template<typename T, int dims> row_riterator xchen::TensorArray< T, dims >::RowReverseIterate (  int    d = 0, int *    start = 0, int *    end = 0 )  [inline]

Iterate the subarray row by row.

template<typename T, int dims> TensorArray< T, dims >::row_riterator xchen::TensorArray< T, dims >::RowReverseIterate (  int    r_d, int    sub_d, int    start, int    L )  [inline]

Subarray is sub_d:[start, start+L).

template<typename T, int dims> void xchen::TensorArray< T, dims >::SetN (  int    N )  [inline]

Set reserved subdivision depth to N.

template<typename T, int dims> slc_iterator xchen::TensorArray< T, dims >::SliceIterate (  int    dir = 0, int    start = 0, int    end = 0 )  [inline]

end=0 defaults to size().

template<typename T, int dims> TensorArray< T, dims > & xchen::TensorArray< T, dims >::Transform (  xchen::Transform const &    )  [inline]

Assume the element type can be transformed.

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Friends And Related Function Documentation

template<typename T, int dims> ostream& operator<< (  ostream &    os, const TensorArray< T, dims > &    _ar )  [friend]

template<typename T, int dims> friend class TensorArray< T, dims-1 > [friend]

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The documentation for this class was generated from the following file:

• TensorArray.H

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