609 lines
20 KiB
HTML
609 lines
20 KiB
HTML
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"HTML Tidy for Linux/x86 (vers 1st March 2004), see www.w3.org" />
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<meta name="GENERATOR" content="Quanta Plus" />
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<link rel="stylesheet" href="../../../../boost.css" type="text/css"/>
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<script type="text/javascript" src="js/jquery-1.3.2.min.js" async="async" ></script>
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<script type="text/javascript" src="js/jquery.toc-gw.js" async="async" ></script>
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<title>Types Overview</title>
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</head>
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<body>
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<h1><img src="../../../../boost.png" align="middle" />Overview of Tensor, Matrix- and Vector Types </h1>
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<div class="toc" id="toc"></div>
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<dl>
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<dt>Contents:</dt>
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<dd><a href="#vectors">Vectors</a></dd>
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<dd><a href="#vector_proxies">Vector Proxies</a></dd>
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<dd><a href="#matrices">Matrices</a></dd>
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<dd><a href="#matrix_proxies">Matrix Proxies</a></dd>
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<dd><a href="#tensors">Tensors</a></dd>
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<dd><a href="#storage_layout">Special Storage Layouts</a></dd>
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</dl>
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<h2>Notation</h2>
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<table style="border: none;" summary="notation">
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<tr><td><code>T</code></td>
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<td>is the data type. For general linear algebra operations this will be a real type e.g. <code>double</code>, ...</td></tr>
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<tr><td><code>F</code></td>
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<td>is the orientation type, either
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<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>
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<tr><td><code>A, IA, TA</code></td> <td>is an array storage type, e.g. <code>std::vector,
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bounded_array, unbounded_array, ...</code></td></tr>
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<tr><td><code>TRI</code></td>
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<td>is a triangular functor: <code>lower,
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unit_lower, strict_lower, upper, unit_upper,
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strict_upper</code></td></tr>
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<tr><td><code>M, N, K</code></td>
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<td>are unsigned integer sizes
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(<code>std::size_t</code>)</td></tr>
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<tr><td><code>IB</code></td>
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<td>is an index base
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(<code>std::size_t</code>)</td></tr>
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<tr><td><code>VEC</code></td>
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<td>is any vector type</td></tr>
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<tr><td><code>MAT</code> </td>
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<td>is any matrix type</td></tr>
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<tr><td><code>TEN</code> </td>
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<td>is any tensor type</td></tr>
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<tr><td><code>[...]</code></td>
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<td>denote optional arguments - for more details
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look at the section "storage layout".</td></tr>
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</table>
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<h2><a id="vectors">Vectors</a></h2>
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<table border="1" summary="vector types">
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<thead>
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<tr>
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<th width="30%">Definition</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><code>vector<T [, A]><br /> v(size);</code></td>
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<td>a dense vector of values of type <code>T</code> of variable
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size. A storage type <code>A</code> can be specified
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which defaults to <code>unbounded_array</code>.
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Elements are constructed by <code>A</code>, which need not initialise their value.</td>
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</tr>
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<tr>
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<td><code>bounded_vector<T, N><br /> v;</code></td>
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<td>a dense vector of values of type <code>T</code> of variable size but with maximum
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<code>N</code>. The default constructor creates <code>v</code>
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with size <code>N</code>.
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Elements are constructed by the storage type <code>bounded_array</code>, which need not initialise their value.</td>
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</tr>
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<tr>
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<td><code>c_vector<T, M><br /> v(size);</code></td>
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<td>a dense vector of values of type <code>T</code> with the given size.
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The data is stored as an ordinary C++ array <code>T
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data_[M]</code></td>
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</tr>
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<tr>
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<td><code>zero_vector<T><br /> v(size);</code></td>
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<td>the zero vector of type <code>T</code> with the given
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size.</td>
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</tr>
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<tr>
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<td><code>unit_vector<T><br /> v(size, index);</code></td>
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<td>the unit vector of type <code>T</code> with the given size. The
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vector is zero other then a single specified element.
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<br/><code>index</code> should be less than <code>size</code>.</td>
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</tr>
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<tr>
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<td><code>mapped_vector<T [, S]><br /> v(size);</code></td>
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<td>a sparse vector of values of type <code>T</code> of variable
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size. The sparse storage type <code>S</code> can be <code>std::map<size_t,
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T></code> or <code>map_array<size_t, T></code>.</td>
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</tr>
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<tr>
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<td><code>compressed_vector<T [,IB, IA, TA]><br /> v(size);</code></td>
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<td>a sparse vector of values of type <code>T</code> of variable
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size. The non zero values are stored as two seperate arrays - an
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index array and a value array. The index array is always sorted and
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there is at most one entry for each index.</td>
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</tr>
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<tr>
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<td><code>coordinate_vector<T [,IB, IA, TA]><br /> v(size);</code></td>
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<td>a sparse vector of values of type <code>T</code> of variable
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size. The non zero values are stored as two seperate arrays - an
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index array and a value array. The arrays may be out of order with
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multiple entries for each vector element. If there are multiple
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values for the same index the sum of these values is the real
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value.</td>
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</tr>
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</tbody>
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</table>
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<p><em>Note:</em> the default types are defined in
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<code>boost/numeric/ublas/fwd.hpp</code>.</p>
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<h2><a id="vector_proxies">Vector Proxies</a></h2>
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<table border="1" summary="vector proxies">
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<thead>
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<tr>
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<th width="30%">Definition</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><code>vector_range<VEC><br /> vr(v, range);</code></td>
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<td>a vector referencing a continuous subvector of elements of
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vector <code>v</code> containing all elements specified by
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<code>range</code>.</td>
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</tr>
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<tr>
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<td><code>vector_slice<VEC><br /> vs(v, slice);</code></td>
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<td>a vector referencing a non continuous subvector of elements of
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vector <code>v</code> containing all elements specified by
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<code>slice</code>.</td>
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</tr>
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<tr>
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<td><code>matrix_row<MAT><br /> vr(m, index);</code></td>
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<td>a vector referencing the <code>index</code>-th row of matrix
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<code>m</code></td>
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</tr>
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<tr>
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<td><code>matrix_column<MAT><br /> vc(m, index);</code></td>
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<td>a vector referencing the <code>index</code>-th column of matrix
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<code>m</code></td>
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</tr>
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</tbody>
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</table>
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<h2><a id="matrices">Matrices</a></h2>
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<table border="1" summary="matrix types">
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<thead>
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<tr>
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<th width="30%">Definition</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><code>matrix<T [, F, A]><br /> m(size1, size2);</code></td>
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<td>a dense matrix of values of type <code>T</code> of variable
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size. A storage type <code>A</code> can be specified
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which defaults to <code>unbounded_array</code>.
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The orientation functor <code>F</code> defaults to
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<code>row_major</code>.
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Elements are constructed by <code>A</code>, which need not initialise their value.</td>
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</tr>
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<tr>
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<td><code>bounded_matrix<T, M, N [, F]><br /> m;</code></td>
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<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>
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defaults to <code>row_major</code>. The default constructor creates
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<code>m</code> with size <code>M</code>-by-<code>N</code>.
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Elements are constructed by the storage type <code>bounded_array</code>, which need not initialise their value.</td>
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</tr>
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<tr>
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<td><code>c_matrix<T, M, N><br /> m(size1, size2);</code></td>
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<td>a dense matrix of values of type <code>T</code> with the given size.
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The data is stored as an ordinary C++ array <code>T
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data_[N][M]</code></td>
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</tr>
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<tr>
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<td><code>vector_of_vector<T [, F, A]><br /> m(size1,
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size2);</code></td>
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<td>a dense matrix of values of type <code>T</code> with the given size.
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The data is stored as a vector of vectors. The orientation
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<code>F</code> defaults to <code>row_major</code>. The storage
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type <code>S</code> defaults to
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<code>unbounded_array<unbounded_array<T> ></code></td>
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</tr>
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<tr>
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<td><code>zero_matrix<T><br /> m(size1, size2);</code></td>
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<td>a zero matrix of type <code>T</code> with the given size.</td>
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</tr>
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<tr>
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<td><code>identity_matrix<T><br /> m(size1, size2);</code></td>
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<td>an identity matrix of type <code>T</code> with the given size.
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The values are <code>v(i,j) = (i==j)?T(1):T()</code>.</td>
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</tr>
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<tr>
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<td><code>scalar_matrix<T><br /> m(size1, size2,
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value);</code></td>
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<td>a matrix of type <code>T</code> with the given size that has the
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value <code>value</code> everywhere.</td>
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</tr>
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<tr>
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<td><code>triangular_matrix<T [, TRI, F, A]><br />
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m(size);</code></td>
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<td>a triangular matrix of values of type <code>T</code> of
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variable size. Only the nonzero elements are stored in the given
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order <code>F</code>. ("triangular packed storage") The triangular
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type <code>F</code> defaults to <code>lower</code>, the orientation
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type <code>F</code> defaults to <code>row_major</code>.</td>
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</tr>
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<tr>
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<td><code>banded_matrix<T [, F, A]><br /> m(size1, size2, n_lower,
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n_upper);</code></td>
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<td>a banded matrix of values of type <code>T</code> of variable
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size with <code>n_lower</code> sub diagonals and
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<code>n_upper</code> super diagonals. Only the nonzero elements are
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stored in the given order <code>F</code>. ("packed storage")</td>
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</tr>
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<tr>
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<td><code>symmetric_matrix<T [, TRI, F, A]><br />
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m(size);</code></td>
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<td>a symmetric matrix of values of type <code>T</code> of
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variable size. Only the given triangular matrix is stored in the
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given order <code>F</code>.</td>
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</tr>
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<tr>
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<td><code>hermitian_matrix<T [, TRI, F, A]><br />
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m(size);</code></td>
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<td>a hermitian matrix of values of type <code>T</code> of
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variable size. Only the given triangular matrix is stored using
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the order <code>F</code>.</td>
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</tr>
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<tr>
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<td><code>mapped_matrix<T, [F, S]><br /> m(size1, size2 [,
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non_zeros]);</code></td>
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<td>a sparse matrix of values of type <code>T</code> of variable
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size. The sparse storage type <code>S</code> can be either <code>std::map<size_t,
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std::map<size_t, T> ></code> or
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<code>map_array<size_t, map_array<size_t,
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T> ></code>.</td>
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</tr>
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<tr>
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<td><code>sparse_vector_of_sparse_vector<T, [F, C]><br /> m(size1,
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size2 [, non_zeros]);</code></td>
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<td>a sparse matrix of values of type <code>T</code> of variable
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size.</td>
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</tr>
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<tr>
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<td><code>compressed_matrix<T, [F, IB, IA, TA]><br /> m(size1,
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size2 [, non_zeros]);</code></td>
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<td>a sparse matrix of values of type <code>T</code> of variable
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size. The values are stored in compressed row/column storage.</td>
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</tr>
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<tr>
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<td><code>coordinate_matrix<T, [F, IB, IA, TA]><br /> m(size1,
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size2 [, non_zeros]);</code></td>
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<td>a sparse matrix of values of type <code>T</code> of variable
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size. The values are stored in 3 parallel array as triples (i, j,
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value). More than one value for each pair of indices is possible,
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the real value is the sum of all.</td>
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</tr>
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<tr>
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<td><code>generalized_vector_of_vector<T, F, A><br /> m(size1,
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size2 [, non_zeros]);</code></td>
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<td>a sparse matrix of values of type <code>T</code> of variable
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size. The values are stored as a vector of sparse vectors, e.g.
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<code>generalized_vector_of_vector<double, row_major,
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unbounded_array<coordinate_vector<double> > ></code></td>
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</tr>
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</tbody>
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</table>
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<p><em>Note:</em> the default types are defined in
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<code>boost/numeric/ublas/fwd.hpp</code>.</p>
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<h2><a id="matrix_proxies">Matrix Proxies</a></h2>
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<table border="1" summary="matrix proxies">
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<thead>
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<tr>
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<th width="30%">Definition</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><code>triangular_adaptor<MAT, TRI><br /> ta(m);</code></td>
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<td>a triangular matrix referencing a selection of elements of the
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matrix <code>m</code>.</td>
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</tr>
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<tr>
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<td><code>symmetric_adaptor<MAT, TRI><br /> sa(m);</code></td>
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<td>a symmetric matrix referencing a selection of elements of the
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matrix <code>m</code>.</td>
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</tr>
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<tr>
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<td><code>hermitian_adaptor<MAT, TRI><br /> ha(m);</code></td>
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<td>a hermitian matrix referencing a selection of elements of the
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matrix <code>m</code>.</td>
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</tr>
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<tr>
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<td><code>banded_adaptor<MAT><br /> ba(m, n_lower,
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n_upper);</code></td>
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<td>a banded matrix referencing a selection of elements of the
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matrix <code>m</code>.</td>
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</tr>
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<tr>
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<td><code>matrix_range<MAT, TRI><br /> mr(m, range1,
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range2);</code></td>
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<td>a matrix referencing a submatrix of elements in the matrix
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<code>m</code>.</td>
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</tr>
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<tr>
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<td><code>matrix_slice<MAT, TRI><br /> ms(m, slice1,
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slice2);</code></td>
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<td>a matrix referencing a non continues submatrix of elements in
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the matrix <code>m</code>.</td>
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</tr>
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</tbody>
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</table>
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<h2><a id="tensors">Tensors</a></h2>
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<table border="1" summary="tensor types">
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<thead>
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<tr>
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<th width="10%">Definition</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><code>tensor<T [, F, A]><br /> t(size1, size2, ... );</code></td>
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<td>a dense matrix of values of type <code>T</code> of variable
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size. A storage type <code>A</code> can be specified
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which defaults to <code>std::vector<T></code>.
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The orientation type <code>F</code> defaults to
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<code>first_order</code>.
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Elements are constructed by <code>A</code>, which need not initialise their value.</td>
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</tr>
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</tbody>
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</table>
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<h2><a id="storage_layout">Special Storage Layouts</a></h2>
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<p>The library supports conventional dense, packed and basic sparse
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vector and matrix storage layouts. The description of the most
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common constructions of vectors and matrices comes next.</p>
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<table border="1" summary="storage layouts">
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<tbody>
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<tr>
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<th width="30%">Construction</th>
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<th>Comment</th>
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</tr>
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<tr>
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<td><code>vector<T,<br />
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std::vector<T> ><br />
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v (size)</code></td>
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<td>a dense vector, storage is provided by a standard
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vector.<br />
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The storage layout usually is BLAS compliant.</td>
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</tr>
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<tr>
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<td><code>vector<T,<br />
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unbounded_array<T> ><br />
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v (size)</code></td>
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<td>a dense vector, storage is provided by a heap-based
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array.<br />
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The storage layout usually is BLAS compliant.</td>
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</tr>
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<tr>
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<td><code>vector<T,<br />
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bounded_array<T, N> ><br />
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v (size)</code></td>
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<td>a dense vector, storage is provided by a stack-based
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array.<br />
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The storage layout usually is BLAS compliant.</td>
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</tr>
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<tr>
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<td><code>mapped_vector<T,<br />
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std::map<std::size_t, T> ><br />
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v (size, non_zeros)</code></td>
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<td>a sparse vector, storage is provided by a standard
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map.</td>
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</tr>
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<tr>
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<td><code>mapped_vector<T,<br />
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map_array<std::size_t, T> ><br />
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v (size, non_zeros)</code></td>
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<td>a sparse vector, storage is provided by a map
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array.</td>
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</tr>
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<tr>
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<td><code>matrix<T,<br />
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row_major,<br />
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std::vector<T> ><br />
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m (size1, size2)</code></td>
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<td>a dense matrix, orientation is row major, storage is
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provided by a standard vector.</td>
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</tr>
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<tr>
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<td><code>matrix<T,<br />
|
|
column_major,<br />
|
|
std::vector<T> ><br />
|
|
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<T,<br />
|
|
row_major,<br />
|
|
unbounded_array<T> ><br />
|
|
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<T,<br />
|
|
column_major,<br />
|
|
unbounded_array<T> ><br />
|
|
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<T,<br />
|
|
row_major,<br />
|
|
bounded_array<T, N1 * N2> ><br />
|
|
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<T,<br />
|
|
column_major,<br />
|
|
bounded_array<T, N1 * N2> ><br />
|
|
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<T,<br />
|
|
row_major, F, A><br />
|
|
m (size)</code></td>
|
|
<td>a packed triangular matrix, orientation is row
|
|
major.</td>
|
|
</tr>
|
|
<tr>
|
|
<td><code>triangular_matrix<T,<br />
|
|
column_major, F, A><br />
|
|
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<T,<br />
|
|
row_major, A><br />
|
|
m (size1, size2, lower, upper)</code></td>
|
|
<td>a packed banded matrix, orientation is row
|
|
major.</td>
|
|
</tr>
|
|
<tr>
|
|
<td><code>banded_matrix<T,<br />
|
|
column_major, A><br />
|
|
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<T,<br />
|
|
row_major, F, A><br />
|
|
m (size)</code></td>
|
|
<td>a packed symmetric matrix, orientation is row
|
|
major.</td>
|
|
</tr>
|
|
<tr>
|
|
<td><code>symmetric_matrix<T,<br />
|
|
column_major, F, A><br />
|
|
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<T,<br />
|
|
row_major, F, A><br />
|
|
m (size)</code></td>
|
|
<td>a packed hermitian matrix, orientation is row
|
|
major.</td>
|
|
</tr>
|
|
<tr>
|
|
<td><code>hermitian_matrix<T,<br />
|
|
column_major, F, A><br />
|
|
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<T,<br />
|
|
row_major,<br />
|
|
std::map<std::size_t, T> ><br />
|
|
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<T,<br />
|
|
column_major,<br />
|
|
std::map<std::size_t, T> ><br />
|
|
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<T,<br />
|
|
row_major,<br />
|
|
map_array<std::size_t, T> ><br />
|
|
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<T,<br />
|
|
column_major,<br />
|
|
map_array<std::size_t, T> ><br />
|
|
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<T,<br />
|
|
row_major><br />
|
|
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<T,<br />
|
|
column_major><br />
|
|
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<T,<br />
|
|
row_major><br />
|
|
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<T,<br />
|
|
column_major><br />
|
|
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 (©) 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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