<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> <meta http-equiv="X-UA-Compatible" content="IE=9"/> <meta name="generator" content="Doxygen 1.8.5"/> <title>Eigen: Redux.h Source File</title> <link href="tabs.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="jquery.js"></script> <script type="text/javascript" src="dynsections.js"></script> <link href="navtree.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtree.js"></script> <script type="text/javascript"> $(document).ready(initResizable); $(window).load(resizeHeight); </script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/search.js"></script> <script type="text/javascript"> $(document).ready(function() { searchBox.OnSelectItem(0); }); </script> <link href="doxygen.css" rel="stylesheet" type="text/css" /> <link href="eigendoxy.css" rel="stylesheet" type="text/css"> <!-- --> <script type="text/javascript" src="eigen_navtree_hacks.js"></script> <!-- <script type="text/javascript"> --> <!-- </script> --> </head> <body> <div id="top"><!-- do not remove this div, it is closed by doxygen! --> <!-- <a name="top"></a> --> <div id="titlearea"> <table cellspacing="0" cellpadding="0"> <tbody> <tr style="height: 56px;"> <td id="projectlogo"><img alt="Logo" src="Eigen_Silly_Professor_64x64.png"/></td> <td style="padding-left: 0.5em;"> <div id="projectname"><a href="http://eigen.tuxfamily.org">Eigen</a>  <span id="projectnumber">3.2.0</span> </div> </td> <td> <div id="MSearchBox" class="MSearchBoxInactive"> <span class="left"> <img id="MSearchSelect" src="search/mag_sel.png" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" alt=""/> <input type="text" id="MSearchField" value="Search" accesskey="S" onfocus="searchBox.OnSearchFieldFocus(true)" onblur="searchBox.OnSearchFieldFocus(false)" onkeyup="searchBox.OnSearchFieldChange(event)"/> </span><span class="right"> <a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a> </span> </div> </td> </tr> </tbody> </table> </div> <!-- end header part --> <!-- Generated by Doxygen 1.8.5 --> <script type="text/javascript"> var searchBox = new SearchBox("searchBox", "search",false,'Search'); </script> </div><!-- top --> <div id="side-nav" class="ui-resizable side-nav-resizable"> <div id="nav-tree"> <div id="nav-tree-contents"> <div id="nav-sync" class="sync"></div> </div> </div> <div id="splitbar" style="-moz-user-select:none;" class="ui-resizable-handle"> </div> </div> <script type="text/javascript"> $(document).ready(function(){initNavTree('Redux_8h_source.html','');}); </script> <div id="doc-content"> <!-- window showing the filter options --> <div id="MSearchSelectWindow" onmouseover="return searchBox.OnSearchSelectShow()" onmouseout="return searchBox.OnSearchSelectHide()" onkeydown="return searchBox.OnSearchSelectKey(event)"> <a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Classes</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Typedefs</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Friends</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(9)"><span class="SelectionMark"> </span>Groups</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(10)"><span class="SelectionMark"> </span>Pages</a></div> <!-- iframe showing the search results (closed by default) --> <div id="MSearchResultsWindow"> <iframe src="javascript:void(0)" frameborder="0" name="MSearchResults" id="MSearchResults"> </iframe> </div> <div class="header"> <div class="headertitle"> <div class="title">Redux.h</div> </div> </div><!--header--> <div class="contents"> <div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div> <div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// for linear algebra.</span></div> <div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">//</span></div> <div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr></span></div> <div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment">// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com></span></div> <div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment">//</span></div> <div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div> <div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div> <div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div> <div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div> <div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#ifndef EIGEN_REDUX_H</span></div> <div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor"></span><span class="preprocessor">#define EIGEN_REDUX_H</span></div> <div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor"></span></div> <div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">namespace </span>Eigen { </div> <div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div> <div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">namespace </span>internal {</div> <div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div> <div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment">// TODO</span></div> <div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment">// * implement other kind of vectorization</span></div> <div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment">// * factorize code</span></div> <div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div> <div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment">/***************************************************************************</span></div> <div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment">* Part 1 : the logic deciding a strategy for vectorization and unrolling</span></div> <div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment">***************************************************************************/</span></div> <div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div> <div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword">struct </span>redux_traits</div> <div class="line"><a name="l00028"></a><span class="lineno"> 28</span> {</div> <div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">public</span>:</div> <div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  PacketSize = packet_traits<typename Derived::Scalar>::size,</div> <div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  InnerMaxSize = int(Derived::IsRowMajor)</div> <div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  ? Derived::MaxColsAtCompileTime</div> <div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  : Derived::MaxRowsAtCompileTime</div> <div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  };</div> <div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div> <div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  MightVectorize = (int(Derived::Flags)&<a class="code" href="group__flags.html#gaafbee24aed0aa204db61f7fce3334329">ActualPacketAccessBit</a>)</div> <div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  && (functor_traits<Func>::PacketAccess),</div> <div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  MayLinearVectorize = MightVectorize && (int(Derived::Flags)&<a class="code" href="group__flags.html#gab9799bf6feed77fc9fce0136ee55b99c">LinearAccessBit</a>),</div> <div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  MaySliceVectorize = MightVectorize && <span class="keywordtype">int</span>(InnerMaxSize)>=3*PacketSize</div> <div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  };</div> <div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div> <div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">public</span>:</div> <div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal)</div> <div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  : int(MaySliceVectorize) ? int(SliceVectorizedTraversal)</div> <div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  : int(DefaultTraversal)</div> <div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  };</div> <div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div> <div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="keyword">public</span>:</div> <div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  Cost = ( Derived::SizeAtCompileTime == <a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a></div> <div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  || Derived::CoeffReadCost == <a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a></div> <div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  || (Derived::SizeAtCompileTime!=1 && functor_traits<Func>::Cost == <a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a>)</div> <div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  ) ? <a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a></div> <div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  : Derived::SizeAtCompileTime * Derived::CoeffReadCost</div> <div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  + (Derived::SizeAtCompileTime-1) * functor_traits<Func>::Cost,</div> <div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  UnrollingLimit = EIGEN_UNROLLING_LIMIT * (<span class="keywordtype">int</span>(Traversal) == int(DefaultTraversal) ? 1 : int(PacketSize))</div> <div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  };</div> <div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div> <div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="keyword">public</span>:</div> <div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  Unrolling = Cost != <a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a> && Cost <= UnrollingLimit</div> <div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  ? CompleteUnrolling</div> <div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  : NoUnrolling</div> <div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  };</div> <div class="line"><a name="l00068"></a><span class="lineno"> 68</span> };</div> <div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div> <div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment">/***************************************************************************</span></div> <div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment">* Part 2 : unrollers</span></div> <div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment">***************************************************************************/</span></div> <div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div> <div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment">/*** no vectorization ***/</span></div> <div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div> <div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived, <span class="keywordtype">int</span> Start, <span class="keywordtype">int</span> Length></div> <div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="keyword">struct </span>redux_novec_unroller</div> <div class="line"><a name="l00078"></a><span class="lineno"> 78</span> {</div> <div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  HalfLength = Length/2</div> <div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  };</div> <div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div> <div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div> <div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Derived &mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  {</div> <div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordflow">return</span> func(redux_novec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),</div> <div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  redux_novec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func));</div> <div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  }</div> <div class="line"><a name="l00090"></a><span class="lineno"> 90</span> };</div> <div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div> <div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived, <span class="keywordtype">int</span> Start></div> <div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="keyword">struct </span>redux_novec_unroller<Func, Derived, Start, 1></div> <div class="line"><a name="l00094"></a><span class="lineno"> 94</span> {</div> <div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  outer = Start / Derived::InnerSizeAtCompileTime,</div> <div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  inner = Start % Derived::InnerSizeAtCompileTime</div> <div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  };</div> <div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div> <div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div> <div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Derived &mat, <span class="keyword">const</span> Func&)</div> <div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div> <div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">return</span> mat.coeffByOuterInner(outer, inner);</div> <div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div> <div class="line"><a name="l00106"></a><span class="lineno"> 106</span> };</div> <div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div> <div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment">// This is actually dead code and will never be called. It is required</span></div> <div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment">// to prevent false warnings regarding failed inlining though</span></div> <div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment">// for 0 length run() will never be called at all.</span></div> <div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived, <span class="keywordtype">int</span> Start></div> <div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="keyword">struct </span>redux_novec_unroller<Func, Derived, Start, 0></div> <div class="line"><a name="l00113"></a><span class="lineno"> 113</span> {</div> <div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Derived&, <span class="keyword">const</span> Func&) { <span class="keywordflow">return</span> Scalar(); }</div> <div class="line"><a name="l00116"></a><span class="lineno"> 116</span> };</div> <div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div> <div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment">/*** vectorization ***/</span></div> <div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div> <div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived, <span class="keywordtype">int</span> Start, <span class="keywordtype">int</span> Length></div> <div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="keyword">struct </span>redux_vec_unroller</div> <div class="line"><a name="l00122"></a><span class="lineno"> 122</span> {</div> <div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  PacketSize = packet_traits<typename Derived::Scalar>::size,</div> <div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  HalfLength = Length/2</div> <div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  };</div> <div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div> <div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits<Scalar>::type PacketScalar;</div> <div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div> <div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE PacketScalar run(<span class="keyword">const</span> Derived &mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div> <div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">return</span> func.packetOp(</div> <div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),</div> <div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  redux_vec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func) );</div> <div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  }</div> <div class="line"><a name="l00137"></a><span class="lineno"> 137</span> };</div> <div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div> <div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived, <span class="keywordtype">int</span> Start></div> <div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="keyword">struct </span>redux_vec_unroller<Func, Derived, Start, 1></div> <div class="line"><a name="l00141"></a><span class="lineno"> 141</span> {</div> <div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  index = Start * packet_traits<typename Derived::Scalar>::size,</div> <div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  outer = index / int(Derived::InnerSizeAtCompileTime),</div> <div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  inner = index % int(Derived::InnerSizeAtCompileTime),</div> <div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  alignment = (Derived::Flags & <a class="code" href="group__flags.html#ga972a2dcb6603215fa53e0b9e82051426">AlignedBit</a>) ? <a class="code" href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371ad5380ca00f3d74b38593adf8a0d06d3e">Aligned</a> : <a class="code" href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371afeaf599f3da3693d2ab4a7cc48a19437">Unaligned</a></div> <div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  };</div> <div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div> <div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits<Scalar>::type PacketScalar;</div> <div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div> <div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE PacketScalar run(<span class="keyword">const</span> Derived &mat, <span class="keyword">const</span> Func&)</div> <div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div> <div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">return</span> mat.template packetByOuterInner<alignment>(outer, inner);</div> <div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  }</div> <div class="line"><a name="l00156"></a><span class="lineno"> 156</span> };</div> <div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div> <div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="comment">/***************************************************************************</span></div> <div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment">* Part 3 : implementation of all cases</span></div> <div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="comment">***************************************************************************/</span></div> <div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div> <div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived,</div> <div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordtype">int</span> Traversal = redux_traits<Func, Derived>::Traversal,</div> <div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordtype">int</span> Unrolling = redux_traits<Func, Derived>::Unrolling</div> <div class="line"><a name="l00165"></a><span class="lineno"> 165</span> ></div> <div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="keyword">struct </span>redux_impl;</div> <div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div> <div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="keyword">struct </span>redux_impl<Func, Derived, DefaultTraversal, NoUnrolling></div> <div class="line"><a name="l00170"></a><span class="lineno"> 170</span> {</div> <div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Index Index;</div> <div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Derived& mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  {</div> <div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  eigen_assert(mat.rows()>0 && mat.cols()>0 && <span class="stringliteral">"you are using an empty matrix"</span>);</div> <div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  Scalar res;</div> <div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  res = mat.coeffByOuterInner(0, 0);</div> <div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">for</span>(Index i = 1; i < mat.innerSize(); ++i)</div> <div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  res = func(res, mat.coeffByOuterInner(0, i));</div> <div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">for</span>(Index i = 1; i < mat.outerSize(); ++i)</div> <div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordflow">for</span>(Index j = 0; j < mat.innerSize(); ++j)</div> <div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  res = func(res, mat.coeffByOuterInner(i, j));</div> <div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordflow">return</span> res;</div> <div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  }</div> <div class="line"><a name="l00185"></a><span class="lineno"> 185</span> };</div> <div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div> <div class="line"><a name="l00187"></a><span class="lineno"> 187</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="keyword">struct </span>redux_impl<Func,Derived, DefaultTraversal, CompleteUnrolling></div> <div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  : <span class="keyword">public</span> redux_novec_unroller<Func,Derived, 0, Derived::SizeAtCompileTime></div> <div class="line"><a name="l00190"></a><span class="lineno"> 190</span> {};</div> <div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div> <div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="keyword">struct </span>redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling></div> <div class="line"><a name="l00194"></a><span class="lineno"> 194</span> {</div> <div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits<Scalar>::type PacketScalar;</div> <div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Index Index;</div> <div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div> <div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keyword">static</span> Scalar run(<span class="keyword">const</span> Derived& mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div> <div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keyword">const</span> Index size = mat.size();</div> <div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  eigen_assert(size && <span class="stringliteral">"you are using an empty matrix"</span>);</div> <div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">const</span> Index packetSize = packet_traits<Scalar>::size;</div> <div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">const</span> Index alignedStart = internal::first_aligned(mat);</div> <div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  alignment = bool(Derived::Flags & <a class="code" href="group__flags.html#ga54c3b872f5a14e7e0d3d6539b704ea67">DirectAccessBit</a>) || bool(Derived::Flags & <a class="code" href="group__flags.html#ga972a2dcb6603215fa53e0b9e82051426">AlignedBit</a>)</div> <div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  ? <a class="code" href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371ad5380ca00f3d74b38593adf8a0d06d3e">Aligned</a> : <a class="code" href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371afeaf599f3da3693d2ab4a7cc48a19437">Unaligned</a></div> <div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  };</div> <div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keyword">const</span> Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);</div> <div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">const</span> Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);</div> <div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keyword">const</span> Index alignedEnd2 = alignedStart + alignedSize2;</div> <div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keyword">const</span> Index alignedEnd = alignedStart + alignedSize;</div> <div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  Scalar res;</div> <div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">if</span>(alignedSize)</div> <div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  {</div> <div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  PacketScalar packet_res0 = mat.template packet<alignment>(alignedStart);</div> <div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keywordflow">if</span>(alignedSize>packetSize) <span class="comment">// we have at least two packets to partly unroll the loop</span></div> <div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  {</div> <div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  PacketScalar packet_res1 = mat.template packet<alignment>(alignedStart+packetSize);</div> <div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordflow">for</span>(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize)</div> <div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  {</div> <div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(index));</div> <div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment>(index+packetSize));</div> <div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div> <div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div> <div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  packet_res0 = func.packetOp(packet_res0,packet_res1);</div> <div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">if</span>(alignedEnd>alignedEnd2)</div> <div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(alignedEnd2));</div> <div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div> <div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  res = func.predux(packet_res0);</div> <div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div> <div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">for</span>(Index index = 0; index < alignedStart; ++index)</div> <div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  res = func(res,mat.coeff(index));</div> <div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div> <div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">for</span>(Index index = alignedEnd; index < size; ++index)</div> <div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  res = func(res,mat.coeff(index));</div> <div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  }</div> <div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordflow">else</span> <span class="comment">// too small to vectorize anything.</span></div> <div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="comment">// since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize.</span></div> <div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div> <div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  res = mat.coeff(0);</div> <div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">for</span>(Index index = 1; index < size; ++index)</div> <div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  res = func(res,mat.coeff(index));</div> <div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  }</div> <div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div> <div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">return</span> res;</div> <div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  }</div> <div class="line"><a name="l00248"></a><span class="lineno"> 248</span> };</div> <div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div> <div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="keyword">struct </span>redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling></div> <div class="line"><a name="l00252"></a><span class="lineno"> 252</span> {</div> <div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits<Scalar>::type PacketScalar;</div> <div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Index Index;</div> <div class="line"><a name="l00256"></a><span class="lineno"> 256</span> </div> <div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">static</span> Scalar run(<span class="keyword">const</span> Derived& mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  {</div> <div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  eigen_assert(mat.rows()>0 && mat.cols()>0 && <span class="stringliteral">"you are using an empty matrix"</span>);</div> <div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keyword">const</span> Index innerSize = mat.innerSize();</div> <div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">const</span> Index outerSize = mat.outerSize();</div> <div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  packetSize = packet_traits<Scalar>::size</div> <div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  };</div> <div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keyword">const</span> Index packetedInnerSize = ((innerSize)/packetSize)*packetSize;</div> <div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  Scalar res;</div> <div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">if</span>(packetedInnerSize)</div> <div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  {</div> <div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  PacketScalar packet_res = mat.template packet<Unaligned>(0,0);</div> <div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">for</span>(Index j=0; j<outerSize; ++j)</div> <div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keywordflow">for</span>(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize))</div> <div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned>(j,i));</div> <div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div> <div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  res = func.predux(packet_res);</div> <div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordflow">for</span>(Index j=0; j<outerSize; ++j)</div> <div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keywordflow">for</span>(Index i=packetedInnerSize; i<innerSize; ++i)</div> <div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  res = func(res, mat.coeffByOuterInner(j,i));</div> <div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  }</div> <div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordflow">else</span> <span class="comment">// too small to vectorize anything.</span></div> <div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="comment">// since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize.</span></div> <div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  {</div> <div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  res = redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>::run(mat, func);</div> <div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  }</div> <div class="line"><a name="l00284"></a><span class="lineno"> 284</span> </div> <div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">return</span> res;</div> <div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  }</div> <div class="line"><a name="l00287"></a><span class="lineno"> 287</span> };</div> <div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div> <div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="keyword">struct </span>redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling></div> <div class="line"><a name="l00291"></a><span class="lineno"> 291</span> {</div> <div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> Derived::Scalar Scalar;</div> <div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> packet_traits<Scalar>::type PacketScalar;</div> <div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keyword">enum</span> {</div> <div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  PacketSize = packet_traits<Scalar>::size,</div> <div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  Size = Derived::SizeAtCompileTime,</div> <div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  VectorizedSize = (Size / PacketSize) * PacketSize</div> <div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  };</div> <div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Derived& mat, <span class="keyword">const</span> Func& func)</div> <div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div> <div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  eigen_assert(mat.rows()>0 && mat.cols()>0 && <span class="stringliteral">"you are using an empty matrix"</span>);</div> <div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));</div> <div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">if</span> (VectorizedSize != Size)</div> <div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  res = func(res,redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));</div> <div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">return</span> res;</div> <div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  }</div> <div class="line"><a name="l00307"></a><span class="lineno"> 307</span> };</div> <div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div> <div class="line"><a name="l00309"></a><span class="lineno"> 309</span> } <span class="comment">// end namespace internal</span></div> <div class="line"><a name="l00310"></a><span class="lineno"> 310</span> </div> <div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="comment">/***************************************************************************</span></div> <div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment">* Part 4 : public API</span></div> <div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="comment">***************************************************************************/</span></div> <div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div> <div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div> <div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="keyword">template</span><<span class="keyword">typename</span> Func></div> <div class="line"><a name="l00325"></a><span class="lineno"> 325</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::result_of<Func(typename internal::traits<Derived>::Scalar)>::type</div> <div class="line"><a name="l00326"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a64248a8479a46b78fa5b19702aa5d212"> 326</a></span> <a class="code" href="classEigen_1_1DenseBase.html">DenseBase<Derived>::redux</a>(<span class="keyword">const</span> Func& func) <span class="keyword">const</span></div> <div class="line"><a name="l00327"></a><span class="lineno"> 327</span> {</div> <div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> internal::remove_all<typename Derived::Nested>::type ThisNested;</div> <div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> internal::redux_impl<Func, ThisNested></div> <div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  ::run(derived(), func);</div> <div class="line"><a name="l00331"></a><span class="lineno"> 331</span> }</div> <div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div> <div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00337"></a><span class="lineno"> 337</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00338"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#add6cb2d85282829eb9adc9565ce784d6"> 338</a></span> <a class="code" href="classEigen_1_1DenseBase.html#add6cb2d85282829eb9adc9565ce784d6">DenseBase<Derived>::minCoeff</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">return</span> this->redux(Eigen::internal::scalar_min_op<Scalar>());</div> <div class="line"><a name="l00341"></a><span class="lineno"> 341</span> }</div> <div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div> <div class="line"><a name="l00346"></a><span class="lineno"> 346</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00347"></a><span class="lineno"> 347</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00348"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a878f0dae18b28d8158c5f1c232edced2"> 348</a></span> <a class="code" href="classEigen_1_1DenseBase.html#a878f0dae18b28d8158c5f1c232edced2">DenseBase<Derived>::maxCoeff</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00349"></a><span class="lineno"> 349</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">return</span> this->redux(Eigen::internal::scalar_max_op<Scalar>());</div> <div class="line"><a name="l00351"></a><span class="lineno"> 351</span> }</div> <div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div> <div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00358"></a><span class="lineno"> 358</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00359"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a3a3b3fb530d3364ecef0bf9c9daf0983"> 359</a></span> <a class="code" href="classEigen_1_1DenseBase.html#a3a3b3fb530d3364ecef0bf9c9daf0983">DenseBase<Derived>::sum</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00360"></a><span class="lineno"> 360</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">if</span>(SizeAtCompileTime==0 || (SizeAtCompileTime==<a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a> && size()==0))</div> <div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">return</span> Scalar(0);</div> <div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">return</span> this->redux(Eigen::internal::scalar_sum_op<Scalar>());</div> <div class="line"><a name="l00364"></a><span class="lineno"> 364</span> }</div> <div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div> <div class="line"><a name="l00370"></a><span class="lineno"> 370</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00371"></a><span class="lineno"> 371</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00372"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a0af2b3991862a079e3efaef3e4d17d96"> 372</a></span> <a class="code" href="classEigen_1_1DenseBase.html#a0af2b3991862a079e3efaef3e4d17d96">DenseBase<Derived>::mean</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">return</span> Scalar(this->redux(Eigen::internal::scalar_sum_op<Scalar>())) / Scalar(this->size());</div> <div class="line"><a name="l00375"></a><span class="lineno"> 375</span> }</div> <div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div> <div class="line"><a name="l00384"></a><span class="lineno"> 384</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00385"></a><span class="lineno"> 385</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a6bdcbfa7e3b07d3246ad80de7170b0f5"> 386</a></span> <a class="code" href="classEigen_1_1DenseBase.html#a6bdcbfa7e3b07d3246ad80de7170b0f5">DenseBase<Derived>::prod</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">if</span>(SizeAtCompileTime==0 || (SizeAtCompileTime==<a class="code" href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Dynamic</a> && size()==0))</div> <div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">return</span> Scalar(1);</div> <div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">return</span> this->redux(Eigen::internal::scalar_product_op<Scalar>());</div> <div class="line"><a name="l00391"></a><span class="lineno"> 391</span> }</div> <div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div> <div class="line"><a name="l00399"></a><span class="lineno"> 399</span> <span class="keyword">template</span><<span class="keyword">typename</span> Derived></div> <div class="line"><a name="l00400"></a><span class="lineno"> 400</span> EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits<Derived>::Scalar</div> <div class="line"><a name="l00401"></a><span class="lineno"><a class="line" href="classEigen_1_1MatrixBase.html#a71696dd0adbf4731561fd60e55c3a96e"> 401</a></span> <a class="code" href="classEigen_1_1MatrixBase.html#a71696dd0adbf4731561fd60e55c3a96e">MatrixBase<Derived>::trace</a>()<span class="keyword"> const</span></div> <div class="line"><a name="l00402"></a><span class="lineno"> 402</span> <span class="keyword"></span>{</div> <div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keywordflow">return</span> derived().diagonal().sum();</div> <div class="line"><a name="l00404"></a><span class="lineno"> 404</span> }</div> <div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div> <div class="line"><a name="l00406"></a><span class="lineno"> 406</span> } <span class="comment">// end namespace Eigen</span></div> <div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div> <div class="line"><a name="l00408"></a><span class="lineno"> 408</span> <span class="preprocessor">#endif // EIGEN_REDUX_H</span></div> <div class="ttc" id="classEigen_1_1DenseBase_html_a0af2b3991862a079e3efaef3e4d17d96"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a0af2b3991862a079e3efaef3e4d17d96">Eigen::DenseBase::mean</a></div><div class="ttdeci">Scalar mean() const </div><div class="ttdef"><b>Definition:</b> Redux.h:372</div></div> <div class="ttc" id="classEigen_1_1DenseBase_html_add6cb2d85282829eb9adc9565ce784d6"><div class="ttname"><a href="classEigen_1_1DenseBase.html#add6cb2d85282829eb9adc9565ce784d6">Eigen::DenseBase::minCoeff</a></div><div class="ttdeci">internal::traits< Derived >::Scalar minCoeff() const </div><div class="ttdef"><b>Definition:</b> Redux.h:338</div></div> <div class="ttc" id="classEigen_1_1DenseBase_html_a6bdcbfa7e3b07d3246ad80de7170b0f5"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a6bdcbfa7e3b07d3246ad80de7170b0f5">Eigen::DenseBase::prod</a></div><div class="ttdeci">Scalar prod() const </div><div class="ttdef"><b>Definition:</b> Redux.h:386</div></div> <div class="ttc" id="group__enums_html_gga456ac33d49271d3e2c371351cd1d6371afeaf599f3da3693d2ab4a7cc48a19437"><div class="ttname"><a href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371afeaf599f3da3693d2ab4a7cc48a19437">Eigen::Unaligned</a></div><div class="ttdef"><b>Definition:</b> Constants.h:192</div></div> <div class="ttc" id="namespaceEigen_html_adc9da5be31bdce40c25a92c27999c0e3"><div class="ttname"><a href="namespaceEigen.html#adc9da5be31bdce40c25a92c27999c0e3">Eigen::Dynamic</a></div><div class="ttdeci">const int Dynamic</div><div class="ttdef"><b>Definition:</b> Constants.h:21</div></div> <div class="ttc" id="classEigen_1_1DenseBase_html_a878f0dae18b28d8158c5f1c232edced2"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a878f0dae18b28d8158c5f1c232edced2">Eigen::DenseBase::maxCoeff</a></div><div class="ttdeci">internal::traits< Derived >::Scalar maxCoeff() const </div><div class="ttdef"><b>Definition:</b> Redux.h:348</div></div> <div class="ttc" id="classEigen_1_1DenseBase_html"><div class="ttname"><a href="classEigen_1_1DenseBase.html">Eigen::DenseBase</a></div><div class="ttdoc">Base class for all dense matrices, vectors, and arrays. </div><div class="ttdef"><b>Definition:</b> DenseBase.h:41</div></div> <div class="ttc" id="classEigen_1_1MatrixBase_html_a71696dd0adbf4731561fd60e55c3a96e"><div class="ttname"><a href="classEigen_1_1MatrixBase.html#a71696dd0adbf4731561fd60e55c3a96e">Eigen::MatrixBase::trace</a></div><div class="ttdeci">Scalar trace() const </div><div class="ttdef"><b>Definition:</b> Redux.h:401</div></div> <div class="ttc" id="group__flags_html_gaafbee24aed0aa204db61f7fce3334329"><div class="ttname"><a href="group__flags.html#gaafbee24aed0aa204db61f7fce3334329">Eigen::ActualPacketAccessBit</a></div><div class="ttdeci">const unsigned int ActualPacketAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:92</div></div> <div class="ttc" id="classEigen_1_1DenseBase_html_a3a3b3fb530d3364ecef0bf9c9daf0983"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a3a3b3fb530d3364ecef0bf9c9daf0983">Eigen::DenseBase::sum</a></div><div class="ttdeci">Scalar sum() const </div><div class="ttdef"><b>Definition:</b> Redux.h:359</div></div> <div class="ttc" id="group__flags_html_gab9799bf6feed77fc9fce0136ee55b99c"><div class="ttname"><a href="group__flags.html#gab9799bf6feed77fc9fce0136ee55b99c">Eigen::LinearAccessBit</a></div><div class="ttdeci">const unsigned int LinearAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:117</div></div> <div class="ttc" id="group__enums_html_gga456ac33d49271d3e2c371351cd1d6371ad5380ca00f3d74b38593adf8a0d06d3e"><div class="ttname"><a href="group__enums.html#gga456ac33d49271d3e2c371351cd1d6371ad5380ca00f3d74b38593adf8a0d06d3e">Eigen::Aligned</a></div><div class="ttdef"><b>Definition:</b> Constants.h:194</div></div> <div class="ttc" id="group__flags_html_ga54c3b872f5a14e7e0d3d6539b704ea67"><div class="ttname"><a href="group__flags.html#ga54c3b872f5a14e7e0d3d6539b704ea67">Eigen::DirectAccessBit</a></div><div class="ttdeci">const unsigned int DirectAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:142</div></div> <div class="ttc" id="group__flags_html_ga972a2dcb6603215fa53e0b9e82051426"><div class="ttname"><a href="group__flags.html#ga972a2dcb6603215fa53e0b9e82051426">Eigen::AlignedBit</a></div><div class="ttdeci">const unsigned int AlignedBit</div><div class="ttdef"><b>Definition:</b> Constants.h:147</div></div> </div><!-- fragment --></div><!-- contents --> </div><!-- doc-content --> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="navelem"><a class="el" href="dir_e49d68e3078f12dfcf157021597ad168.html">Eigen</a></li><li class="navelem"><a class="el" href="dir_64b228556dc7f9fe757d43bb57fbfc24.html">src</a></li><li class="navelem"><a class="el" href="dir_55812ea607075be3acfc18281a2aed64.html">Core</a></li><li class="navelem"><b>Redux.h</b></li> <li class="footer">Generated on Mon Oct 28 2013 11:04:25 for Eigen by <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.5 </li> </ul> </div> <!-- Piwik --> <!-- <script type="text/javascript"> var pkBaseURL = (("https:" == document.location.protocol) ? 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