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<h1><img src="../../../../boost.png" align="middle" />Overview of Tensor, Matrix- and Vector Types </h1>
<div class="toc" id="toc"></div>

<dl>
<dt>Contents:</dt>
<dd><a href="#vectors">Vectors</a></dd>
<dd><a href="#vector_proxies">Vector Proxies</a></dd>
<dd><a href="#matrices">Matrices</a></dd>
<dd><a href="#matrix_proxies">Matrix Proxies</a></dd>
<dd><a href="#tensors">Tensors</a></dd>
<dd><a href="#storage_layout">Special Storage Layouts</a></dd>
</dl>


<h2>Notation</h2>

<table style="border: none;" summary="notation">
<tr><td><code>T</code></td> 
<td>is the data type. For general linear algebra operations this will be a real type e.g. <code>double</code>, ...</td></tr>
<tr><td><code>F</code></td> 
<td>is the orientation type, either
<code>row_major</code> or <code>column_major</code> for matrices and <code>first_order</code> or <code>last_order</code> for tensors</td></tr> 
<tr><td><code>A, IA, TA</code></td> <td>is an array storage type, e.g. <code>std::vector,
bounded_array, unbounded_array, ...</code></td></tr>
<tr><td><code>TRI</code></td> 
<td>is a triangular functor: <code>lower,
unit_lower, strict_lower, upper, unit_upper,
strict_upper</code></td></tr>
<tr><td><code>M, N, K</code></td> 
<td>are unsigned integer sizes 
(<code>std::size_t</code>)</td></tr>
<tr><td><code>IB</code></td> 
<td>is an index base
(<code>std::size_t</code>)</td></tr>
<tr><td><code>VEC</code></td> 
<td>is any vector type</td></tr>
<tr><td><code>MAT</code> </td>
<td>is any matrix type</td></tr>
<tr><td><code>TEN</code> </td>
<td>is any tensor type</td></tr>
<tr><td><code>[...]</code></td> 
<td>denote optional arguments - for more details
look at the section "storage layout".</td></tr>
</table>

<h2><a id="vectors">Vectors</a></h2>
<table border="1" summary="vector types">
<thead>
<tr>
<th width="30%">Definition</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>vector&lt;T [, A]&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>a dense vector of values of type <code>T</code> of variable
size. A storage type <code>A</code> can be specified
which defaults to <code>unbounded_array</code>.
Elements are constructed by <code>A</code>, which need not initialise their value.</td>

</tr>
<tr>
<td><code>bounded_vector&lt;T, N&gt;<br />&nbsp;&nbsp; v;</code></td>
<td>a dense vector of values of type <code>T</code> of variable size but with maximum
<code>N</code>. The default constructor creates <code>v</code>
with size <code>N</code>.
Elements are constructed by the storage type <code>bounded_array</code>, which need not initialise their value.</td>
</tr>
<tr>
<td><code>c_vector&lt;T, M&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>a dense vector of values of type <code>T</code> with the given size.
The data is stored as an ordinary C++ array <code>T
data_[M]</code></td>
</tr>
<tr>
<td><code>zero_vector&lt;T&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>the zero vector of type <code>T</code> with the given
size.</td>
</tr>
<tr>
<td><code>unit_vector&lt;T&gt;<br />&nbsp;&nbsp; v(size,&nbsp;index);</code></td>
<td>the unit vector of type <code>T</code> with the given size. The
vector is zero other then a single specified element.
<br/><code>index</code> should be less than <code>size</code>.</td>
</tr>
<tr>
<td><code>mapped_vector&lt;T [, S]&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>a sparse vector of values of type <code>T</code> of variable
size. The sparse storage type <code>S</code> can be <code>std::map&lt;size_t,
T&gt;</code> or <code>map_array&lt;size_t, T&gt;</code>.</td>
</tr>
<tr>
<td><code>compressed_vector&lt;T [,IB, IA, TA]&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>a sparse vector of values of type <code>T</code> of variable
size. The non zero values are stored as two seperate arrays - an
index array and a value array. The index array is always sorted and
there is at most one entry for each index.</td>
</tr>
<tr>
<td><code>coordinate_vector&lt;T [,IB, IA, TA]&gt;<br />&nbsp;&nbsp; v(size);</code></td>
<td>a sparse vector of values of type <code>T</code> of variable
size. The non zero values are stored as two seperate arrays - an
index array and a value array. The arrays may be out of order with
multiple entries for each vector element. If there are multiple
values for the same index the sum of these values is the real
value.</td>
</tr>
</tbody>
</table>
<p><em>Note:</em> the default types are defined in
<code>boost/numeric/ublas/fwd.hpp</code>.</p>

<h2><a id="vector_proxies">Vector Proxies</a></h2>

<table border="1" summary="vector proxies">
<thead>
<tr>
<th width="30%">Definition</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>vector_range&lt;VEC&gt;<br />&nbsp;&nbsp; vr(v, range);</code></td>
<td>a vector referencing a continuous subvector of elements of
vector <code>v</code> containing all elements specified by
<code>range</code>.</td>
</tr>
<tr>
<td><code>vector_slice&lt;VEC&gt;<br />&nbsp;&nbsp; vs(v, slice);</code></td>
<td>a vector referencing a non continuous subvector of elements of
vector <code>v</code> containing all elements specified by
<code>slice</code>.</td>
</tr>
<tr>
<td><code>matrix_row&lt;MAT&gt;<br />&nbsp;&nbsp; vr(m, index);</code></td>
<td>a vector referencing the <code>index</code>-th row of matrix
<code>m</code></td>
</tr>
<tr>
<td><code>matrix_column&lt;MAT&gt;<br />&nbsp;&nbsp; vc(m, index);</code></td>
<td>a vector referencing the <code>index</code>-th column of matrix
<code>m</code></td>
</tr>
</tbody>
</table>

<h2><a id="matrices">Matrices</a></h2>

<table border="1" summary="matrix types">
<thead>
<tr>
<th width="30%">Definition</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>matrix&lt;T [, F, A]&gt;<br />&nbsp;&nbsp; m(size1, size2);</code></td>
<td>a dense matrix of values of type <code>T</code> of variable
size.  A storage type <code>A</code> can be specified
which defaults to <code>unbounded_array</code>.
The orientation functor <code>F</code> defaults to
<code>row_major</code>.
Elements are constructed by <code>A</code>, which need not initialise their value.</td>
</tr>
<tr>
<td><code>bounded_matrix&lt;T, M, N [, F]&gt;<br />&nbsp;&nbsp; m;</code></td>
<td>a dense matrix of type <code>T</code> with variable size with maximum <code>M</code>-by-<code>N</code>. The orientation functor <code>F</code>
defaults to <code>row_major</code>. The default constructor creates
<code>m</code> with size <code>M</code>-by-<code>N</code>.
Elements are constructed by the storage type <code>bounded_array</code>, which need not initialise their value.</td>
</tr>
<tr>
<td><code>c_matrix&lt;T, M, N&gt;<br />&nbsp;&nbsp; m(size1, size2);</code></td>
<td>a dense matrix of values of type <code>T</code> with the given size.
The data is stored as an ordinary C++ array <code>T
data_[N][M]</code></td>
</tr>
<tr>
<td><code>vector_of_vector&lt;T [, F, A]&gt;<br />&nbsp;&nbsp; m(size1,
size2);</code></td>
<td>a dense matrix of values of type <code>T</code> with the given size.
The data is stored as a vector of vectors. The orientation
<code>F</code> defaults to <code>row_major</code>. The storage
type <code>S</code> defaults to
<code>unbounded_array&lt;unbounded_array&lt;T&gt;&nbsp;&gt;</code></td>
</tr>
<tr>
<td><code>zero_matrix&lt;T&gt;<br />&nbsp;&nbsp; m(size1, size2);</code></td>
<td>a zero matrix of type <code>T</code> with the given size.</td>
</tr>
<tr>
<td><code>identity_matrix&lt;T&gt;<br />&nbsp;&nbsp; m(size1, size2);</code></td>
<td>an identity matrix of type <code>T</code> with the given size.
The values are <code>v(i,j) = (i==j)?T(1):T()</code>.</td>
</tr>
<tr>
<td><code>scalar_matrix&lt;T&gt;<br />&nbsp;&nbsp; m(size1, size2,
value);</code></td>
<td>a matrix of type <code>T</code> with the given size that has the
value <code>value</code> everywhere.</td>
</tr>
<tr>
<td><code>triangular_matrix&lt;T [, TRI, F, A]&gt;<br />&nbsp;&nbsp;
m(size);</code></td>
<td>a triangular matrix of values of type <code>T</code> of
variable size. Only the nonzero elements are stored in the given
order <code>F</code>. ("triangular packed storage") The triangular
type <code>F</code> defaults to <code>lower</code>, the orientation
type <code>F</code> defaults to <code>row_major</code>.</td>
</tr>
<tr>
<td><code>banded_matrix&lt;T [, F, A]&gt;<br />&nbsp;&nbsp; m(size1, size2, n_lower,
n_upper);</code></td>
<td>a banded matrix of values of type <code>T</code> of variable
size with <code>n_lower</code> sub diagonals and
<code>n_upper</code> super diagonals. Only the nonzero elements are
stored in the given order <code>F</code>. ("packed storage")</td>
</tr>
<tr>
<td><code>symmetric_matrix&lt;T [, TRI, F, A]&gt;<br />&nbsp;&nbsp;
m(size);</code></td>
<td>a symmetric matrix of values of type <code>T</code> of
variable size. Only the given triangular matrix is stored in the
given order <code>F</code>.</td>
</tr>
<tr>
<td><code>hermitian_matrix&lt;T [, TRI, F, A]&gt;<br />&nbsp;&nbsp;
m(size);</code></td>
<td>a hermitian matrix of values of type <code>T</code> of
variable size. Only the given triangular matrix is stored using
the order <code>F</code>.</td>
</tr>
<tr>
<td><code>mapped_matrix&lt;T, [F, S]&gt;<br />&nbsp;&nbsp; m(size1, size2 [,
non_zeros]);</code></td>
<td>a sparse matrix of values of type <code>T</code> of variable
size. The sparse storage type <code>S</code> can be either <code>std::map&lt;size_t,
std::map&lt;size_t, T&gt;&nbsp;&gt;</code> or
<code>map_array&lt;size_t, map_array&lt;size_t,
T&gt;&nbsp;&gt;</code>.</td>
</tr>
<tr>
<td><code>sparse_vector_of_sparse_vector&lt;T, [F, C]&gt;<br />&nbsp;&nbsp; m(size1,
size2 [, non_zeros]);</code></td>
<td>a sparse matrix of values of type <code>T</code> of variable
size.</td>
</tr>
<tr>
<td><code>compressed_matrix&lt;T, [F, IB, IA, TA]&gt;<br />&nbsp;&nbsp; m(size1,
size2 [, non_zeros]);</code></td>
<td>a sparse matrix of values of type <code>T</code> of variable
size. The values are stored in compressed row/column storage.</td>
</tr>
<tr>
<td><code>coordinate_matrix&lt;T, [F, IB, IA, TA]&gt;<br />&nbsp;&nbsp; m(size1,
size2 [, non_zeros]);</code></td>
<td>a sparse matrix of values of type <code>T</code> of variable
size. The values are stored in 3 parallel array as triples (i, j,
value). More than one value for each pair of indices is possible,
the real value is the sum of all.</td>
</tr>
<tr>
<td><code>generalized_vector_of_vector&lt;T, F, A&gt;<br />&nbsp;&nbsp; m(size1,
size2 [, non_zeros]);</code></td>
<td>a sparse matrix of values of type <code>T</code> of variable
size. The values are stored as a vector of sparse vectors, e.g.
<code>generalized_vector_of_vector&lt;double, row_major,
unbounded_array&lt;coordinate_vector&lt;double&gt;&nbsp;&gt;&nbsp;&gt;</code></td>
</tr>
</tbody>
</table>
<p><em>Note:</em> the default types are defined in
<code>boost/numeric/ublas/fwd.hpp</code>.</p>

<h2><a id="matrix_proxies">Matrix Proxies</a></h2>

<table border="1" summary="matrix proxies">
<thead>
<tr>
<th width="30%">Definition</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>triangular_adaptor&lt;MAT, TRI&gt;<br />&nbsp;&nbsp; ta(m);</code></td>
<td>a triangular matrix referencing a selection of elements of the
matrix <code>m</code>.</td>
</tr>
<tr>
<td><code>symmetric_adaptor&lt;MAT, TRI&gt;<br />&nbsp;&nbsp; sa(m);</code></td>
<td>a symmetric matrix referencing a selection of elements of the
matrix <code>m</code>.</td>
</tr>
<tr>
<td><code>hermitian_adaptor&lt;MAT, TRI&gt;<br />&nbsp;&nbsp; ha(m);</code></td>
<td>a hermitian matrix referencing a selection of elements of the
matrix <code>m</code>.</td>
</tr>
<tr>
<td><code>banded_adaptor&lt;MAT&gt;<br />&nbsp;&nbsp; ba(m, n_lower,
n_upper);</code></td>
<td>a banded matrix referencing a selection of elements of the
matrix <code>m</code>.</td>
</tr>
<tr>
<td><code>matrix_range&lt;MAT, TRI&gt;<br />&nbsp;&nbsp; mr(m, range1,
range2);</code></td>
<td>a matrix referencing a submatrix of elements in the matrix
<code>m</code>.</td>
</tr>
<tr>
<td><code>matrix_slice&lt;MAT, TRI&gt;<br />&nbsp;&nbsp; ms(m, slice1,
slice2);</code></td>
<td>a matrix referencing a non continues submatrix of elements in
the matrix <code>m</code>.</td>
</tr>
</tbody>
</table>


<h2><a id="tensors">Tensors</a></h2>

<table border="1" summary="tensor types">
<thead>
<tr>
<th width="10%">Definition</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td><code>tensor&lt;T [, F, A]&gt;<br />&nbsp;&nbsp; t(size1, size2, ... );</code></td>
<td>a dense matrix of values of type <code>T</code> of variable
size. A storage type <code>A</code> can be specified
which defaults to <code>std::vector&lt;T&gt;</code>.
The orientation type <code>F</code> defaults to
<code>first_order</code>.
Elements are constructed by <code>A</code>, which need not initialise their value.</td>
</tr>
</tbody>
</table>


<h2><a id="storage_layout">Special Storage Layouts</a></h2>


<p>The library supports conventional dense, packed and basic sparse
vector and matrix storage layouts. The description of the most
common constructions of vectors and matrices comes next.</p>

<table border="1" summary="storage layouts">
<tbody>
<tr>
<th width="30%">Construction</th>
<th>Comment</th>
</tr>
<tr>
<td><code>vector&lt;T,<br />
&nbsp;std::vector&lt;T&gt; &gt;<br />
&nbsp;&nbsp;v (size)</code></td>
<td>a dense vector, storage is provided by a standard
vector.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>vector&lt;T,<br />
&nbsp;unbounded_array&lt;T&gt; &gt;<br />
&nbsp;&nbsp;v (size)</code></td>
<td>a dense vector, storage is provided by a heap-based
array.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>vector&lt;T,<br />
&nbsp;bounded_array&lt;T, N&gt; &gt;<br />
&nbsp;&nbsp;v (size)</code></td>
<td>a dense vector, storage is provided by a stack-based
array.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>mapped_vector&lt;T,<br />
&nbsp;std::map&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;v (size, non_zeros)</code></td>
<td>a sparse vector, storage is provided by a standard
map.</td>
</tr>
<tr>
<td><code>mapped_vector&lt;T,<br />
&nbsp;map_array&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;v (size, non_zeros)</code></td>
<td>a sparse vector, storage is provided by a map
array.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;row_major,<br />
&nbsp;std::vector&lt;T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is row major, storage is
provided by a standard vector.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;column_major,<br />
&nbsp;std::vector&lt;T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is column major, storage
is provided by a standard vector.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;row_major,<br />
&nbsp;unbounded_array&lt;T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is row major, storage is
provided by a heap-based array.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;column_major,<br />
&nbsp;unbounded_array&lt;T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is column major, storage
is provided by a heap-based array.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;row_major,<br />
&nbsp;bounded_array&lt;T, N1 * N2&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is row major, storage is
provided by a stack-based array.</td>
</tr>
<tr>
<td><code>matrix&lt;T,<br />
&nbsp;column_major,<br />
&nbsp;bounded_array&lt;T, N1 * N2&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2)</code></td>
<td>a dense matrix, orientation is column major, storage
is provided by a stack-based array.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>triangular_matrix&lt;T,<br />
&nbsp;row_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed triangular matrix, orientation is row
major.</td>
</tr>
<tr>
<td><code>triangular_matrix&lt;T,<br />
&nbsp;column_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed triangular matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>banded_matrix&lt;T,<br />
&nbsp;row_major, A&gt;<br />
&nbsp;&nbsp;m (size1, size2, lower, upper)</code></td>
<td>a packed banded matrix, orientation is row
major.</td>
</tr>
<tr>
<td><code>banded_matrix&lt;T,<br />
&nbsp;column_major, A&gt;<br />
&nbsp;&nbsp;m (size1, size2, lower, upper)</code></td>
<td>a packed banded matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>symmetric_matrix&lt;T,<br />
&nbsp;row_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed symmetric matrix, orientation is row
major.</td>
</tr>
<tr>
<td><code>symmetric_matrix&lt;T,<br />
&nbsp;column_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed symmetric matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>hermitian_matrix&lt;T,<br />
&nbsp;row_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed hermitian matrix, orientation is row
major.</td>
</tr>
<tr>
<td><code>hermitian_matrix&lt;T,<br />
&nbsp;column_major, F, A&gt;<br />
&nbsp;&nbsp;m (size)</code></td>
<td>a packed hermitian matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>mapped_matrix&lt;T,<br />
&nbsp;row_major,<br />
&nbsp;std::map&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a sparse matrix, orientation is row major, storage
is provided by a standard map.</td>
</tr>
<tr>
<td><code>mapped_matrix&lt;T,<br />
&nbsp;column_major,<br />
&nbsp;std::map&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a sparse matrix, orientation is column major,
storage is provided by a standard map.</td>
</tr>
<tr>
<td><code>mapped_matrix&lt;T,<br />
&nbsp;row_major,<br />
&nbsp;map_array&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a sparse matrix, orientation is row major, storage
is provided by a map array.</td>
</tr>
<tr>
<td><code>mapped_matrix&lt;T,<br />
&nbsp;column_major,<br />
&nbsp;map_array&lt;std::size_t, T&gt; &gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a sparse matrix, orientation is column major,
storage is provided by a map array.</td>
</tr>
<tr>
<td><code>compressed_matrix&lt;T,<br />
&nbsp;row_major&gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a compressed matrix, orientation is row major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>compressed_matrix&lt;T,<br />
&nbsp;column_major&gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a compressed matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>coordinate_matrix&lt;T,<br />
&nbsp;row_major&gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a coordinate matrix, orientation is row major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
<tr>
<td><code>coordinate_matrix&lt;T,<br />
&nbsp;column_major&gt;<br />
&nbsp;&nbsp;m (size1, size2, non_zeros)</code></td>
<td>a coordinate matrix, orientation is column
major.<br />
The storage layout usually is BLAS compliant.</td>
</tr>
</tbody>
</table>

<hr />
<p>Copyright (&copy;) 2000-2004 Joerg Walter, Mathias Koch, Gunter
Winkler, Michael Stevens<br />
   Use, modification and distribution are subject to the
   Boost Software License, Version 1.0.
   (See accompanying file LICENSE_1_0.txt
   or copy at <a href="http://www.boost.org/LICENSE_1_0.txt">
      http://www.boost.org/LICENSE_1_0.txt
   </a>).
</p>
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