<!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: EigenSolver.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('EigenSolver_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">EigenSolver.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) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk></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_EIGENSOLVER_H</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor"></span><span class="preprocessor">#define EIGEN_EIGENSOLVER_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="preprocessor">#include "./RealSchur.h"</span></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>Eigen { </div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div>
<div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html"> 64</a></span> <span class="keyword">template</span><<span class="keyword">typename</span> _MatrixType> <span class="keyword">class </span><a class="code" href="classEigen_1_1EigenSolver.html">EigenSolver</a></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> {</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">public</span>:</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div>
<div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf"> 69</a></span>  <span class="keyword">typedef</span> _MatrixType <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a>;</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  RowsAtCompileTime = MatrixType::RowsAtCompileTime,</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  ColsAtCompileTime = MatrixType::ColsAtCompileTime,</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  Options = MatrixType::Options,</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  };</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div>
<div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f"> 80</a></span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> MatrixType::Scalar <a class="code" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Scalar</a>;</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structEigen_1_1NumTraits.html">NumTraits<Scalar>::Real</a> RealScalar;</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> MatrixType::Index Index;</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div>
<div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc"> 90</a></span>  <span class="keyword">typedef</span> std::complex<RealScalar> <a class="code" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">ComplexScalar</a>;</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
<div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a62dc35c9c355abf830869b1bad883c74"> 97</a></span>  <span class="keyword">typedef</span> <a class="code" href="classEigen_1_1Matrix.html">Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1></a> <a class="code" href="classEigen_1_1EigenSolver.html#a62dc35c9c355abf830869b1bad883c74">EigenvalueType</a>;</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a50d070013a795db5621119f2b4a3d781"> 104</a></span>  <span class="keyword">typedef</span> <a class="code" href="classEigen_1_1Matrix.html">Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime></a> <a class="code" href="classEigen_1_1EigenSolver.html#a50d070013a795db5621119f2b4a3d781">EigenvectorsType</a>;</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div>
<div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a838424bc2f923e06e7690965bf6d7769"> 113</a></span>  <a class="code" href="classEigen_1_1EigenSolver.html#a838424bc2f923e06e7690965bf6d7769">EigenSolver</a>() : m_eivec(), m_eivalues(), m_isInitialized(false), m_realSchur(), m_matT(), m_tmp() {}</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div>
<div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#af3bf2ce4a17b33b9e298170677f2f0c0"> 121</a></span>  <a class="code" href="classEigen_1_1EigenSolver.html#af3bf2ce4a17b33b9e298170677f2f0c0">EigenSolver</a>(Index size)</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  : m_eivec(size, size),</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  m_eivalues(size),</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  m_isInitialized(false),</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  m_eigenvectorsOk(false),</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  m_realSchur(size),</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  m_matT(size, size), </div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  m_tmp(size)</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  {}</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div>
<div class="line"><a name="l00146"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a8c287af80cfd71517094b75dcad2a31b"> 146</a></span>  <a class="code" href="classEigen_1_1EigenSolver.html#a8c287af80cfd71517094b75dcad2a31b">EigenSolver</a>(<span class="keyword">const</span> <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a>& matrix, <span class="keywordtype">bool</span> computeEigenvectors = <span class="keyword">true</span>)</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  : m_eivec(matrix.rows(), matrix.cols()),</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  m_eivalues(matrix.cols()),</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  m_isInitialized(false),</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  m_eigenvectorsOk(false),</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  m_realSchur(matrix.cols()),</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  m_matT(matrix.rows(), matrix.cols()), </div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  m_tmp(matrix.cols())</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  {</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classEigen_1_1EigenSolver.html#a0e257dae8f1774fdda178482caa65be8">compute</a>(matrix, computeEigenvectors);</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="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="classEigen_1_1EigenSolver.html#a50d070013a795db5621119f2b4a3d781">EigenvectorsType</a> <a class="code" href="classEigen_1_1EigenSolver.html#a3236af3afbc89241aaed4fc868aa8435">eigenvectors</a>() <span class="keyword">const</span>;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
<div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a3b6c3b38f50c2372de195ff955a4e02d"> 198</a></span>  <span class="keyword">const</span> <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a>& <a class="code" href="classEigen_1_1EigenSolver.html#a3b6c3b38f50c2372de195ff955a4e02d">pseudoEigenvectors</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="keyword"> </span>{</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  eigen_assert(m_isInitialized && <span class="stringliteral">"EigenSolver is not initialized."</span>);</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  eigen_assert(m_eigenvectorsOk && <span class="stringliteral">"The eigenvectors have not been computed together with the eigenvalues."</span>);</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">return</span> m_eivec;</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a> <a class="code" href="classEigen_1_1EigenSolver.html#a4140972e2b45343d1ef1793c2824159c">pseudoEigenvalueMatrix</a>() <span class="keyword">const</span>;</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div>
<div class="line"><a name="l00243"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a1165fd63a951c6afaf239174d22e9945"> 243</a></span>  <span class="keyword">const</span> <a class="code" href="classEigen_1_1Matrix.html">EigenvalueType</a>& <a class="code" href="classEigen_1_1EigenSolver.html#a1165fd63a951c6afaf239174d22e9945">eigenvalues</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="keyword"> </span>{</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  eigen_assert(m_isInitialized && <span class="stringliteral">"EigenSolver is not initialized."</span>);</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">return</span> m_eivalues;</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="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="classEigen_1_1EigenSolver.html">EigenSolver</a>& <a class="code" href="classEigen_1_1EigenSolver.html#a0e257dae8f1774fdda178482caa65be8">compute</a>(<span class="keyword">const</span> <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a>& matrix, <span class="keywordtype">bool</span> computeEigenvectors = <span class="keyword">true</span>);</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="group__enums.html#ga51bc1ac16f26ebe51eae1abb77bd037b">ComputationInfo</a> info()<span class="keyword"> const</span></div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="keyword"> </span>{</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  eigen_assert(m_isInitialized && <span class="stringliteral">"EigenSolver is not initialized."</span>);</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">return</span> m_realSchur.<a class="code" href="classEigen_1_1RealSchur.html#a0c06d5c2034ebb329c54235369643ad2">info</a>();</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div>
<div class="line"><a name="l00285"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#ab70fdf436af2c43b7174e2981f618fb3"> 285</a></span>  <a class="code" href="classEigen_1_1EigenSolver.html">EigenSolver</a>& <a class="code" href="classEigen_1_1EigenSolver.html#ab70fdf436af2c43b7174e2981f618fb3">setMaxIterations</a>(Index maxIters)</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>  m_realSchur.<a class="code" href="classEigen_1_1RealSchur.html#adcb20d95f17c74395f9a906e5a72ab6b">setMaxIterations</a>(maxIters);</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  }</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div>
<div class="line"><a name="l00292"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#ab6f0a63ea1d26cef5e748207043eb43e"> 292</a></span>  Index <a class="code" href="classEigen_1_1EigenSolver.html#ab6f0a63ea1d26cef5e748207043eb43e">getMaxIterations</a>()</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  {</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">return</span> m_realSchur.<a class="code" href="classEigen_1_1RealSchur.html#ab6f0a63ea1d26cef5e748207043eb43e">getMaxIterations</a>();</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  }</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span> </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">private</span>:</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordtype">void</span> doComputeEigenvectors();</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keyword">protected</span>:</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a> m_eivec;</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="classEigen_1_1EigenSolver.html#a62dc35c9c355abf830869b1bad883c74">EigenvalueType</a> m_eivalues;</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordtype">bool</span> m_isInitialized;</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordtype">bool</span> m_eigenvectorsOk;</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <a class="code" href="classEigen_1_1RealSchur.html">RealSchur<MatrixType></a> m_realSchur;</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a> m_matT;</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>  <span class="keyword">typedef</span> <a class="code" href="classEigen_1_1Matrix.html">Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1></a> ColumnVectorType;</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  ColumnVectorType m_tmp;</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> </div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType></div>
<div class="line"><a name="l00313"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a4140972e2b45343d1ef1793c2824159c"> 313</a></span> <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a> <a class="code" href="classEigen_1_1EigenSolver.html#a4140972e2b45343d1ef1793c2824159c">EigenSolver<MatrixType>::pseudoEigenvalueMatrix</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  eigen_assert(m_isInitialized && <span class="stringliteral">"EigenSolver is not initialized."</span>);</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  Index n = m_eivalues.rows();</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a> matD = MatrixType::Zero(n,n);</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keywordflow">for</span> (Index i=0; i<n; ++i)</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  {</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">if</span> (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(i)), numext::real(m_eivalues.coeff(i))))</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  matD.coeffRef(i,i) = numext::real(m_eivalues.coeff(i));</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  {</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  matD.template block<2,2>(i,i) << numext::real(m_eivalues.coeff(i)), numext::imag(m_eivalues.coeff(i)),</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  -numext::imag(m_eivalues.coeff(i)), numext::real(m_eivalues.coeff(i));</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  ++i;</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>  }</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> matD;</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span> }</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> <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType></div>
<div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a3236af3afbc89241aaed4fc868aa8435"> 333</a></span> <span class="keyword">typename</span> <a class="code" href="classEigen_1_1Matrix.html">EigenSolver<MatrixType>::EigenvectorsType</a> <a class="code" href="classEigen_1_1EigenSolver.html#a3236af3afbc89241aaed4fc868aa8435">EigenSolver<MatrixType>::eigenvectors</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  eigen_assert(m_isInitialized && <span class="stringliteral">"EigenSolver is not initialized."</span>);</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  eigen_assert(m_eigenvectorsOk && <span class="stringliteral">"The eigenvectors have not been computed together with the eigenvalues."</span>);</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  Index n = m_eivec.cols();</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="classEigen_1_1Matrix.html">EigenvectorsType</a> matV(n,n);</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">for</span> (Index j=0; j<n; ++j)</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  {</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">if</span> (internal::isMuchSmallerThan(numext::imag(m_eivalues.coeff(j)), numext::real(m_eivalues.coeff(j))) || j+1==n)</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  {</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="comment">// we have a real eigen value</span></div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  matV.col(j) = m_eivec.col(j).template cast<ComplexScalar>();</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  matV.col(j).normalize();</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  }</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  {</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="comment">// we have a pair of complex eigen values</span></div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">for</span> (Index i=0; i<n; ++i)</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>  matV.coeffRef(i,j) = <a class="code" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">ComplexScalar</a>(m_eivec.coeff(i,j), m_eivec.coeff(i,j+1));</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  matV.coeffRef(i,j+1) = <a class="code" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">ComplexScalar</a>(m_eivec.coeff(i,j), -m_eivec.coeff(i,j+1));</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  }</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  matV.col(j).normalize();</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  matV.col(j+1).normalize();</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  ++j;</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  }</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  }</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">return</span> matV;</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span> }</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span> <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType></div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span> <a class="code" href="classEigen_1_1EigenSolver.html">EigenSolver<MatrixType></a>& </div>
<div class="line"><a name="l00365"></a><span class="lineno"><a class="line" href="classEigen_1_1EigenSolver.html#a0e257dae8f1774fdda178482caa65be8"> 365</a></span> <a class="code" href="classEigen_1_1EigenSolver.html#a0e257dae8f1774fdda178482caa65be8">EigenSolver<MatrixType>::compute</a>(<span class="keyword">const</span> <a class="code" href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">MatrixType</a>& matrix, <span class="keywordtype">bool</span> computeEigenvectors)</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span> {</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keyword">using</span> std::sqrt;</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keyword">using</span> std::abs;</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  eigen_assert(matrix.cols() == matrix.rows());</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="comment">// Reduce to real Schur form.</span></div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  m_realSchur.compute(matrix, computeEigenvectors);</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">if</span> (m_realSchur.info() == <a class="code" href="group__enums.html#gga51bc1ac16f26ebe51eae1abb77bd037bafdfbdf3247bd36a1f17270d5cec74c9c">Success</a>)</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>  m_matT = m_realSchur.matrixT();</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">if</span> (computeEigenvectors)</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  m_eivec = m_realSchur.matrixU();</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  </div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="comment">// Compute eigenvalues from matT</span></div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  m_eivalues.resize(matrix.cols());</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  Index i = 0;</div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">while</span> (i < matrix.cols()) </div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  {</div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">if</span> (i == matrix.cols() - 1 || m_matT.coeff(i+1, i) == <a class="code" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Scalar</a>(0)) </div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  {</div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  m_eivalues.coeffRef(i) = m_matT.coeff(i, i);</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  ++i;</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  }</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">else</span></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>  <a class="code" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Scalar</a> p = <a class="code" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Scalar</a>(0.5) * (m_matT.coeff(i, i) - m_matT.coeff(i+1, i+1));</div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <a class="code" href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Scalar</a> z = sqrt(abs(p * p + m_matT.coeff(i+1, i) * m_matT.coeff(i, i+1)));</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  m_eivalues.coeffRef(i) = <a class="code" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">ComplexScalar</a>(m_matT.coeff(i+1, i+1) + p, z);</div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  m_eivalues.coeffRef(i+1) = <a class="code" href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">ComplexScalar</a>(m_matT.coeff(i+1, i+1) + p, -z);</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  i += 2;</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  }</div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  }</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  </div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="comment">// Compute eigenvectors.</span></div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">if</span> (computeEigenvectors)</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  doComputeEigenvectors();</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  }</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>  m_isInitialized = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  m_eigenvectorsOk = computeEigenvectors;</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="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span> }</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span> <span class="comment">// Complex scalar division.</span></div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="keyword">template</span><<span class="keyword">typename</span> Scalar></div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span> std::complex<Scalar> cdiv(<span class="keyword">const</span> Scalar& xr, <span class="keyword">const</span> Scalar& xi, <span class="keyword">const</span> Scalar& yr, <span class="keyword">const</span> Scalar& yi)</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span> {</div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keyword">using</span> std::abs;</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  Scalar r,d;</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">if</span> (abs(yr) > abs(yi))</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  {</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  r = yi/yr;</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  d = yr + r*yi;</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">return</span> std::complex<Scalar>((xr + r*xi)/d, (xi - r*xr)/d);</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  }</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  {</div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  r = yr/yi;</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  d = yi + r*yr;</div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">return</span> std::complex<Scalar>((r*xr + xi)/d, (r*xi - xr)/d);</div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  }</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span> }</div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> </div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="keyword">template</span><<span class="keyword">typename</span> MatrixType></div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> <span class="keywordtype">void</span> EigenSolver<MatrixType>::doComputeEigenvectors()</div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span> {</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keyword">using</span> std::abs;</div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keyword">const</span> Index size = m_eivec.cols();</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keyword">const</span> Scalar eps = NumTraits<Scalar>::epsilon();</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="comment">// inefficient! this is already computed in RealSchur</span></div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  Scalar norm(0);</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keywordflow">for</span> (Index j = 0; j < size; ++j)</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  {</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  }</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  </div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="comment">// Backsubstitute to find vectors of upper triangular form</span></div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keywordflow">if</span> (norm == 0.0)</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  {</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  }</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">for</span> (Index n = size-1; n >= 0; n--)</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  {</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  Scalar p = m_eivalues.coeff(n).real();</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  Scalar q = m_eivalues.coeff(n).imag();</div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="comment">// Scalar vector</span></div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keywordflow">if</span> (q == Scalar(0))</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  {</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  Scalar lastr(0), lastw(0);</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  Index l = n;</div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  m_matT.coeffRef(n,n) = 1.0;</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordflow">for</span> (Index i = n-1; i >= 0; i--)</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  {</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  Scalar w = m_matT.coeff(i,i) - p;</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  Scalar r = m_matT.row(i).segment(l,n-l+1).dot(m_matT.col(n).segment(l, n-l+1));</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keywordflow">if</span> (m_eivalues.coeff(i).imag() < 0.0)</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  {</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  lastw = w;</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  lastr = r;</div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  }</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  {</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  l = i;</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keywordflow">if</span> (m_eivalues.coeff(i).imag() == 0.0)</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  {</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">if</span> (w != 0.0)</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  m_matT.coeffRef(i,n) = -r / w;</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  m_matT.coeffRef(i,n) = -r / (eps * norm);</div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  }</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">else</span> <span class="comment">// Solve real equations</span></div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  {</div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  Scalar x = m_matT.coeff(i,i+1);</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  Scalar y = m_matT.coeff(i+1,i);</div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  Scalar denom = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag();</div>
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  Scalar t = (x * lastr - lastw * r) / denom;</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  m_matT.coeffRef(i,n) = t;</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">if</span> (abs(x) > abs(lastw))</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  m_matT.coeffRef(i+1,n) = (-r - w * t) / x;</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  m_matT.coeffRef(i+1,n) = (-lastr - y * t) / lastw;</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  }</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span> </div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="comment">// Overflow control</span></div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  Scalar t = abs(m_matT.coeff(i,n));</div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordflow">if</span> ((eps * t) * t > Scalar(1))</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  m_matT.col(n).tail(size-i) /= t;</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  }</div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  }</div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  }</div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (q < Scalar(0) && n > 0) <span class="comment">// Complex vector</span></div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  {</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  Scalar lastra(0), lastsa(0), lastw(0);</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  Index l = n-1;</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="comment">// Last vector component imaginary so matrix is triangular</span></div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">if</span> (abs(m_matT.coeff(n,n-1)) > abs(m_matT.coeff(n-1,n)))</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  {</div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  m_matT.coeffRef(n-1,n-1) = q / m_matT.coeff(n,n-1);</div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  m_matT.coeffRef(n-1,n) = -(m_matT.coeff(n,n) - p) / m_matT.coeff(n,n-1);</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  }</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  {</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  std::complex<Scalar> cc = cdiv<Scalar>(0.0,-m_matT.coeff(n-1,n),m_matT.coeff(n-1,n-1)-p,q);</div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  m_matT.coeffRef(n-1,n-1) = numext::real(cc);</div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  m_matT.coeffRef(n-1,n) = numext::imag(cc);</div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  }</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  m_matT.coeffRef(n,n-1) = 0.0;</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  m_matT.coeffRef(n,n) = 1.0;</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="keywordflow">for</span> (Index i = n-2; i >= 0; i--)</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  {</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  Scalar ra = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n-1).segment(l, n-l+1));</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  Scalar sa = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n).segment(l, n-l+1));</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  Scalar w = m_matT.coeff(i,i) - p;</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">if</span> (m_eivalues.coeff(i).imag() < 0.0)</div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  {</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  lastw = w;</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  lastra = ra;</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  lastsa = sa;</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  }</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  {</div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  l = i;</div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordflow">if</span> (m_eivalues.coeff(i).imag() == RealScalar(0))</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  {</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  std::complex<Scalar> cc = cdiv(-ra,-sa,w,q);</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  m_matT.coeffRef(i,n-1) = numext::real(cc);</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  m_matT.coeffRef(i,n) = numext::imag(cc);</div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  }</div>
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  {</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="comment">// Solve complex equations</span></div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  Scalar x = m_matT.coeff(i,i+1);</div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  Scalar y = m_matT.coeff(i+1,i);</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  Scalar vr = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag() - q * q;</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  Scalar vi = (m_eivalues.coeff(i).real() - p) * Scalar(2) * q;</div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keywordflow">if</span> ((vr == 0.0) && (vi == 0.0))</div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  vr = eps * norm * (abs(w) + abs(q) + abs(x) + abs(y) + abs(lastw));</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span> </div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);</div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  m_matT.coeffRef(i,n-1) = numext::real(cc);</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  m_matT.coeffRef(i,n) = numext::imag(cc);</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordflow">if</span> (abs(x) > (abs(lastw) + abs(q)))</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  {</div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  m_matT.coeffRef(i+1,n-1) = (-ra - w * m_matT.coeff(i,n-1) + q * m_matT.coeff(i,n)) / x;</div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  m_matT.coeffRef(i+1,n) = (-sa - w * m_matT.coeff(i,n) - q * m_matT.coeff(i,n-1)) / x;</div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  }</div>
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  {</div>
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  cc = cdiv(-lastra-y*m_matT.coeff(i,n-1),-lastsa-y*m_matT.coeff(i,n),lastw,q);</div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  m_matT.coeffRef(i+1,n-1) = numext::real(cc);</div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  m_matT.coeffRef(i+1,n) = numext::imag(cc);</div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  }</div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  }</div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> </div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="comment">// Overflow control</span></div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keyword">using</span> std::max;</div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  Scalar t = (max)(abs(m_matT.coeff(i,n-1)),abs(m_matT.coeff(i,n)));</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordflow">if</span> ((eps * t) * t > Scalar(1))</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  m_matT.block(i, n-1, size-i, 2) /= t;</div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  }</div>
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  }</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  </div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <span class="comment">// We handled a pair of complex conjugate eigenvalues, so need to skip them both</span></div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  n--;</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  }</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  {</div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  eigen_assert(0 && <span class="stringliteral">"Internal bug in EigenSolver"</span>); <span class="comment">// this should not happen</span></div>
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  }</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  }</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span> </div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="comment">// Back transformation to get eigenvectors of original matrix</span></div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">for</span> (Index j = size-1; j >= 0; j--)</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  {</div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  m_tmp.noalias() = m_eivec.leftCols(j+1) * m_matT.col(j).segment(0, j+1);</div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  m_eivec.col(j) = m_tmp;</div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  }</div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span> }</div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> </div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> } <span class="comment">// end namespace Eigen</span></div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span> </div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span> <span class="preprocessor">#endif // EIGEN_EIGENSOLVER_H</span></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_aeb6c0eb89cc982629305f6c7e0791caf"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#aeb6c0eb89cc982629305f6c7e0791caf">Eigen::EigenSolver::MatrixType</a></div><div class="ttdeci">_MatrixType MatrixType</div><div class="ttdoc">Synonym for the template parameter _MatrixType. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:69</div></div>
<div class="ttc" id="classEigen_1_1RealSchur_html_a0c06d5c2034ebb329c54235369643ad2"><div class="ttname"><a href="classEigen_1_1RealSchur.html#a0c06d5c2034ebb329c54235369643ad2">Eigen::RealSchur::info</a></div><div class="ttdeci">ComputationInfo info() const </div><div class="ttdoc">Reports whether previous computation was successful. </div><div class="ttdef"><b>Definition:</b> RealSchur.h:193</div></div>
<div class="ttc" id="classEigen_1_1RealSchur_html"><div class="ttname"><a href="classEigen_1_1RealSchur.html">Eigen::RealSchur< MatrixType ></a></div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a8c287af80cfd71517094b75dcad2a31b"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a8c287af80cfd71517094b75dcad2a31b">Eigen::EigenSolver::EigenSolver</a></div><div class="ttdeci">EigenSolver(const MatrixType &matrix, bool computeEigenvectors=true)</div><div class="ttdoc">Constructor; computes eigendecomposition of given matrix. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:146</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a3f6fc00047c205ee590f676934aab28f"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a3f6fc00047c205ee590f676934aab28f">Eigen::EigenSolver::Scalar</a></div><div class="ttdeci">MatrixType::Scalar Scalar</div><div class="ttdoc">Scalar type for matrices of type MatrixType. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:80</div></div>
<div class="ttc" id="structEigen_1_1NumTraits_html"><div class="ttname"><a href="structEigen_1_1NumTraits.html">Eigen::NumTraits</a></div><div class="ttdoc">Holds information about the various numeric (i.e. scalar) types allowed by Eigen. ...</div><div class="ttdef"><b>Definition:</b> NumTraits.h:88</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a62dc35c9c355abf830869b1bad883c74"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a62dc35c9c355abf830869b1bad883c74">Eigen::EigenSolver::EigenvalueType</a></div><div class="ttdeci">Matrix< ComplexScalar, ColsAtCompileTime, 1, Options &~RowMajor, MaxColsAtCompileTime, 1 > EigenvalueType</div><div class="ttdoc">Type for vector of eigenvalues as returned by eigenvalues(). </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:97</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a4140972e2b45343d1ef1793c2824159c"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a4140972e2b45343d1ef1793c2824159c">Eigen::EigenSolver::pseudoEigenvalueMatrix</a></div><div class="ttdeci">MatrixType pseudoEigenvalueMatrix() const </div><div class="ttdoc">Returns the block-diagonal matrix in the pseudo-eigendecomposition. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:313</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a1165fd63a951c6afaf239174d22e9945"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a1165fd63a951c6afaf239174d22e9945">Eigen::EigenSolver::eigenvalues</a></div><div class="ttdeci">const EigenvalueType & eigenvalues() const </div><div class="ttdoc">Returns the eigenvalues of given matrix. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:243</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a50d070013a795db5621119f2b4a3d781"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a50d070013a795db5621119f2b4a3d781">Eigen::EigenSolver::EigenvectorsType</a></div><div class="ttdeci">Matrix< ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime > EigenvectorsType</div><div class="ttdoc">Type for matrix of eigenvectors as returned by eigenvectors(). </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:104</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a3236af3afbc89241aaed4fc868aa8435"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a3236af3afbc89241aaed4fc868aa8435">Eigen::EigenSolver::eigenvectors</a></div><div class="ttdeci">EigenvectorsType eigenvectors() const </div><div class="ttdoc">Returns the eigenvectors of given matrix. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:333</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a3b6c3b38f50c2372de195ff955a4e02d"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a3b6c3b38f50c2372de195ff955a4e02d">Eigen::EigenSolver::pseudoEigenvectors</a></div><div class="ttdeci">const MatrixType & pseudoEigenvectors() const </div><div class="ttdoc">Returns the pseudo-eigenvectors of given matrix. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:198</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_ab6f0a63ea1d26cef5e748207043eb43e"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#ab6f0a63ea1d26cef5e748207043eb43e">Eigen::EigenSolver::getMaxIterations</a></div><div class="ttdeci">Index getMaxIterations()</div><div class="ttdoc">Returns the maximum number of iterations. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:292</div></div>
<div class="ttc" id="classEigen_1_1RealSchur_html_ab6f0a63ea1d26cef5e748207043eb43e"><div class="ttname"><a href="classEigen_1_1RealSchur.html#ab6f0a63ea1d26cef5e748207043eb43e">Eigen::RealSchur::getMaxIterations</a></div><div class="ttdeci">Index getMaxIterations()</div><div class="ttdoc">Returns the maximum number of iterations. </div><div class="ttdef"><b>Definition:</b> RealSchur.h:211</div></div>
<div class="ttc" id="classEigen_1_1RealSchur_html_adcb20d95f17c74395f9a906e5a72ab6b"><div class="ttname"><a href="classEigen_1_1RealSchur.html#adcb20d95f17c74395f9a906e5a72ab6b">Eigen::RealSchur::setMaxIterations</a></div><div class="ttdeci">RealSchur & setMaxIterations(Index maxIters)</div><div class="ttdoc">Sets the maximum number of iterations allowed. </div><div class="ttdef"><b>Definition:</b> RealSchur.h:204</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_af3bf2ce4a17b33b9e298170677f2f0c0"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#af3bf2ce4a17b33b9e298170677f2f0c0">Eigen::EigenSolver::EigenSolver</a></div><div class="ttdeci">EigenSolver(Index size)</div><div class="ttdoc">Default constructor with memory preallocation. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:121</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_ab70fdf436af2c43b7174e2981f618fb3"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#ab70fdf436af2c43b7174e2981f618fb3">Eigen::EigenSolver::setMaxIterations</a></div><div class="ttdeci">EigenSolver & setMaxIterations(Index maxIters)</div><div class="ttdoc">Sets the maximum number of iterations allowed. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:285</div></div>
<div class="ttc" id="group__enums_html_gga51bc1ac16f26ebe51eae1abb77bd037bafdfbdf3247bd36a1f17270d5cec74c9c"><div class="ttname"><a href="group__enums.html#gga51bc1ac16f26ebe51eae1abb77bd037bafdfbdf3247bd36a1f17270d5cec74c9c">Eigen::Success</a></div><div class="ttdef"><b>Definition:</b> Constants.h:376</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html"><div class="ttname"><a href="classEigen_1_1EigenSolver.html">Eigen::EigenSolver</a></div><div class="ttdoc">Computes eigenvalues and eigenvectors of general matrices. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:64</div></div>
<div class="ttc" id="classEigen_1_1Matrix_html"><div class="ttname"><a href="classEigen_1_1Matrix.html">Eigen::Matrix< ComplexScalar, ColsAtCompileTime, 1, Options &~RowMajor, MaxColsAtCompileTime, 1 ></a></div></div>
<div class="ttc" id="group__enums_html_ga51bc1ac16f26ebe51eae1abb77bd037b"><div class="ttname"><a href="group__enums.html#ga51bc1ac16f26ebe51eae1abb77bd037b">Eigen::ComputationInfo</a></div><div class="ttdeci">ComputationInfo</div><div class="ttdef"><b>Definition:</b> Constants.h:374</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a1b9bc0a45616064df3a6168395e3cfcc"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a1b9bc0a45616064df3a6168395e3cfcc">Eigen::EigenSolver::ComplexScalar</a></div><div class="ttdeci">std::complex< RealScalar > ComplexScalar</div><div class="ttdoc">Complex scalar type for MatrixType. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:90</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a0e257dae8f1774fdda178482caa65be8"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a0e257dae8f1774fdda178482caa65be8">Eigen::EigenSolver::compute</a></div><div class="ttdeci">EigenSolver & compute(const MatrixType &matrix, bool computeEigenvectors=true)</div><div class="ttdoc">Computes eigendecomposition of given matrix. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:365</div></div>
<div class="ttc" id="classEigen_1_1EigenSolver_html_a838424bc2f923e06e7690965bf6d7769"><div class="ttname"><a href="classEigen_1_1EigenSolver.html#a838424bc2f923e06e7690965bf6d7769">Eigen::EigenSolver::EigenSolver</a></div><div class="ttdeci">EigenSolver()</div><div class="ttdoc">Default constructor. </div><div class="ttdef"><b>Definition:</b> EigenSolver.h:113</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_b3e8aad20632d7b7c332c11ff568cf95.html">Eigenvalues</a></li><li class="navelem"><b>EigenSolver.h</b></li>
<li class="footer">Generated on Mon Oct 28 2013 11:04:23 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) ? "https://stats.sylphide-consulting.com/piwik/" : "http://stats.sylphide-consulting.com/piwik/");
document.write(unescape("%3Cscript src='" + pkBaseURL + "piwik.js' type='text/javascript'%3E%3C/script%3E"));
</script><script type="text/javascript">
try {
var piwikTracker = Piwik.getTracker(pkBaseURL + "piwik.php", 20);
piwikTracker.trackPageView();
piwikTracker.enableLinkTracking();
} catch( err ) {}
</script><noscript><p><img src="http://stats.sylphide-consulting.com/piwik/piwik.php?idsite=20" style="border:0" alt="" /></p></noscript>
-->
<!-- End Piwik Tracking Code -->
</body>
</html>
