Reference documentation for deal.II version 9.2.0
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Namespaces | |
internal | |
Classes | |
struct | ReturnType |
struct | ReturnType< 0, T > |
struct | ValueType |
struct | ValueType< const T > |
struct | ValueType< const T[N]> |
struct | ValueType< T[N]> |
Functions | |
template<int index, int rank, typename T > | |
constexpr internal::ReorderedIndexView< index, rank, T > | reordered_index_view (T &t) |
template<int rank, typename T , typename ArrayType > | |
constexpr ReturnType< rank, T >::value_type & | extract (T &t, const ArrayType &indices) |
template<int no_contr, int rank_1, int rank_2, int dim, typename T1 , typename T2 , typename T3 > | |
constexpr void | contract (T1 &result, const T2 &left, const T3 &right) |
template<int rank_1, int rank_2, int dim, typename T1 , typename T2 , typename T3 , typename T4 > | |
constexpr T1 | contract3 (const T2 &left, const T3 &middle, const T4 &right) |
This namespace is a collection of algorithms working on generic tensorial objects (of arbitrary rank).
The rationale to implement such functionality in a generic fashion in a separate namespace is
A tensorial object has the notion of a rank and allows a rank-times recursive application of the index operator, e.g., if t
is a tensorial object of rank 4, the following access is valid:
deal.II has its own implementation for tensorial objects such as ::Tensor<rank, dim, Number> and SymmetricTensor<rank, dim, Number>
The methods and algorithms implemented in this namespace, however, are fully generic. More precisely, it can operate on nested c-style arrays, or on class types T
with a minimal interface that provides a local alias value_type
and an index operator operator[](unsigned int)
that returns a (const or non-const) reference of value_type
:
This namespace provides primitives for access, reordering and contraction of such objects.
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constexpr |
Provide a "tensorial view" to a reference t
of a tensor object of rank rank
in which the index index
is shifted to the end. As an example consider a tensor of 5th order in dim=5 space dimensions that can be accessed through 5 recursive operator[]()
invocations:
Index 1 (the 2nd index, count starts at 0) can now be shifted to the end via
The usage of the Tensor type was solely for the sake of an example. The mechanism implemented by this function is available for fairly general tensorial types T
.
The purpose of this reordering facility is to be able to contract over an arbitrary index of two (or more) tensors:
operator[](unsigned int)
and an alias value_type
describing its return value.index | The index to be shifted to the end. Indices are counted from 0, thus the valid range is \(0\le\text{index}<\text{rank}\). |
rank | Rank of the tensorial object t |
T | A tensorial object of rank rank . T must provide a local alias value_type and an index operator operator[]() that returns a (const or non-const) reference of value_type . |
Definition at line 192 of file tensor_accessors.h.
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constexpr |
Return a reference (const or non-const) to a subobject of a tensorial object t
of type T
, as described by an array type ArrayType
object indices
. For example:
This is equivalent to tensor[0][1][2][3][4] = 42.
.
T | A tensorial object of rank rank . T must provide a local alias value_type and an index operator operator[]() that returns a (const or non-const) reference of value_type . Further, its tensorial rank must be equal or greater than rank . |
ArrayType | An array like object, such as std::array, or TableIndices that stores at least rank indices that can be accessed via operator[](). |
Definition at line 226 of file tensor_accessors.h.
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inlineconstexpr |
This function contracts two tensorial objects left
and right
and stores the result in result
. The contraction is done over the last no_contr
indices of both tensorial objects:
\[ \text{result}_{i_1,..,i_{r1},j_1,..,j_{r2}} = \sum_{k_1,..,k_{\text{no\_contr}}} \text{left}_{i_1,..,i_{r1},k_1,..,k_{\text{no\_contr}}} \text{right}_{j_1,..,j_{r2},k_1,..,k_{\text{no\_contr}}} \]
Calling this function is equivalent of writing the following low level code:
with r = rank_1 + rank_2 - 2 * no_contr, l = rank_1 - no_contr, l1 = rank_1, and c = no_contr.
T1
, T2
, and T3
must have rank rank_1 + rank_2 - 2 * no_contr, rank_1, or rank_2, respectively. Obviously, no_contr must be less or equal than rank_1 and rank_2.Definition at line 281 of file tensor_accessors.h.
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constexpr |
Full contraction of three tensorial objects:
\[ \sum_{i_1,..,i_{r1},j_1,..,j_{r2}} \text{left}_{i_1,..,i_{r1}} \text{middle}_{i_1,..,i_{r1},j_1,..,j_{r2}} \text{right}_{j_1,..,j_{r2}} \]
Calling this function is equivalent of writing the following low level code:
T2
, T3
, and T4
must have rank rank_1, rank_1 + rank_2, and rank_3, respectively. T1
must be a scalar type.Definition at line 335 of file tensor_accessors.h.