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Clean the manual page titles, links and intro.
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@ -2,12 +2,6 @@ namespace Eigen {
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/** \eigenManualPage TutorialMatrixClass The Matrix class
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\li \b Previous: \ref GettingStarted
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\li \b Next: \ref TutorialMatrixArithmetic
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We assume that you have already read the quick \link GettingStarted "getting started" \endlink tutorial.
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This page is the first one in a much longer multi-page tutorial.
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\eigenAutoToc
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In Eigen, all matrices and vectors are objects of the Matrix template class.
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@ -264,7 +258,6 @@ Where:
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defined for these five types doesn't mean that they are the only supported scalar types. For example,
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all standard integer types are supported, see \ref TopicScalarTypes "Scalar types".
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\li \b Next: \ref TutorialMatrixArithmetic
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*/
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@ -2,10 +2,7 @@ namespace Eigen {
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/** \eigenManualPage TutorialMatrixArithmetic Matrix and vector arithmetic
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\li \b Previous: \ref TutorialMatrixClass
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\li \b Next: \ref TutorialArrayClass
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This tutorial aims to provide an overview and some details on how to perform arithmetic
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This page aims to provide an overview and some details on how to perform arithmetic
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between matrices, vectors and scalars with Eigen.
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\eigenAutoToc
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@ -212,8 +209,6 @@ Eigen then uses runtime assertions. This means that the program will abort with
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For more details on this topic, see \ref TopicAssertions "this page".
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\li \b Next: \ref TutorialArrayClass
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*/
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}
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@ -2,10 +2,7 @@ namespace Eigen {
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/** \eigenManualPage TutorialArrayClass The Array class and coefficient-wise operations
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\li \b Previous: \ref TutorialMatrixArithmetic
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\li \b Next: \ref TutorialBlockOperations
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This tutorial aims to provide an overview and explanations on how to use
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This page aims to provide an overview and explanations on how to use
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Eigen's Array class.
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\eigenAutoToc
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@ -190,8 +187,6 @@ expression <tt>(m.array() * n.array()).matrix() * m</tt> computes the coefficien
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\verbinclude Tutorial_ArrayClass_interop.out
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</td></tr></table>
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\li \b Next: \ref TutorialBlockOperations
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*/
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}
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@ -2,10 +2,7 @@ namespace Eigen {
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/** \eigenManualPage TutorialBlockOperations Block operations
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\li \b Previous: \ref TutorialArrayClass
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\li \b Next: \ref TutorialAdvancedInitialization
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This tutorial page explains the essentials of block operations.
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This page explains the essentials of block operations.
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A block is a rectangular part of a matrix or array. Blocks expressions can be used both
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as rvalues and as lvalues. As usual with Eigen expressions, this abstraction has zero runtime cost
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provided that you let your compiler optimize.
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@ -226,8 +223,6 @@ An example is presented below:
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\verbinclude Tutorial_BlockOperations_vector.out
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</td></tr></table>
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\li \b Next: \ref TutorialAdvancedInitialization
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*/
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}
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@ -2,9 +2,6 @@ namespace Eigen {
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/** \eigenManualPage TutorialAdvancedInitialization Advanced initialization
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\li \b Previous: \ref TutorialBlockOperations
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\li \b Next: \ref TutorialLinearAlgebra
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This page discusses several advanced methods for initializing matrices. It gives more details on the
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comma-initializer, which was introduced before. It also explains how to get special matrices such as the
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identity matrix and the zero matrix.
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@ -160,8 +157,6 @@ The \link CommaInitializer::finished() finished() \endlink method is necessary h
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object once the comma initialization of our temporary submatrix is done.
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\li \b Next: \ref TutorialLinearAlgebra
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*/
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}
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@ -2,12 +2,9 @@ namespace Eigen {
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/** \eigenManualPage TutorialLinearAlgebra Linear algebra and decompositions
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\li \b Previous: \ref TutorialAdvancedInitialization
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\li \b Next: \ref TutorialReductionsVisitorsBroadcasting
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This tutorial explains how to solve linear systems, compute various decompositions such as LU,
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QR, %SVD, eigendecompositions... for more advanced topics, don't miss our special page on
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\ref TopicLinearAlgebraDecompositions "this topic".
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This page explains how to solve linear systems, compute various decompositions such as LU,
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QR, %SVD, eigendecompositions... After reading this page, don't miss our
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\link TopicLinearAlgebraDecompositions catalogue \endlink of dense matrix decompositions.
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\eigenAutoToc
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@ -253,8 +250,6 @@ decomposition after you've changed the threshold.
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</tr>
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</table>
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\li \b Next: \ref TutorialReductionsVisitorsBroadcasting
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*/
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}
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@ -2,10 +2,7 @@ namespace Eigen {
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/** \eigenManualPage TutorialReductionsVisitorsBroadcasting Reductions, visitors and broadcasting
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\li \b Previous: \ref TutorialLinearAlgebra
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\li \b Next: \ref TutorialGeometry
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This tutorial explains Eigen's reductions, visitors and broadcasting and how they are used with
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This page explains Eigen's reductions, visitors and broadcasting and how they are used with
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\link MatrixBase matrices \endlink and \link ArrayBase arrays \endlink.
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\eigenAutoToc
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@ -255,8 +252,6 @@ this operation is a row-vector where each coefficient is the squared Euclidean d
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- Finally, <tt>minCoeff(&index)</tt> is used to obtain the index of the column in <tt>m</tt> that is closest to <tt>v</tt> in terms of Euclidean
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distance.
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\li \b Next: \ref TutorialGeometry
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*/
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}
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@ -1,11 +1,8 @@
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namespace Eigen {
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/** \eigenManualPage TutorialGeometry Geometry
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/** \eigenManualPage TutorialGeometry Space transformations
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\li \b Previous: \ref TutorialReductionsVisitorsBroadcasting
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\li \b Next: \ref TutorialSparse
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In this tutorial, we will briefly introduce the many possibilities offered by the \ref Geometry_Module "geometry module", namely 2D and 3D rotations and projective or affine transformations.
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In this page, we will introduce the many possibilities offered by the \ref Geometry_Module "geometry module" to deal with 2D and 3D rotations and projective or affine transformations.
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\eigenAutoToc
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@ -239,8 +236,6 @@ m = AngleAxisf(angle1, Vector3f::UnitZ())
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\endcode</td></tr>
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</table>
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\li \b Next: \ref TutorialSparse
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*/
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}
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@ -2,13 +2,8 @@ namespace Eigen {
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/** \eigenManualPage TutorialSparse Sparse matrix manipulations
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\li \b Previous: \ref TutorialGeometry
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\li \b Next: \ref TutorialMapClass
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\eigeneigenAutoToc
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<hr>
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Manipulating and solving sparse problems involves various modules which are summarized below:
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<table class="manual">
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@ -436,8 +431,6 @@ sm2.selfadjointView<Lower>() = A.selfadjointView<Lower>().twistedBy(P); //
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sm1.middleCols(j, nb); // for column major matrices only, get a range of nb columns
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\endcode
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\li \b Next: \ref TutorialMapClass
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*/
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}
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@ -1,13 +1,9 @@
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namespace Eigen {
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/** \eigenManualPage TutorialMapClass Interfacing with C/C++ arrays and external libraries: the %Map class
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/** \eigenManualPage TutorialMapClass Interfacing with raw buffers: the Map class
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\ingroup Tutorial
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\li \b Previous: \ref TutorialSparse
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\li \b Next:
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This tutorial page explains how to work with "raw" C++ arrays. This can be useful in a variety of contexts, particularly when "importing" vectors and matrices from other libraries into Eigen.
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This page explains how to work with "raw" C/C++ arrays.
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This can be useful in a variety of contexts, particularly when "importing" vectors and matrices from other libraries into Eigen.
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\eigenAutoToc
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@ -85,8 +81,6 @@ for (int i = 0; i < n_matrices; i++)
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}
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\endcode
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\li \b Next:
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*/
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}
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@ -1,7 +1,9 @@
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namespace Eigen {
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/** \eigenManualPage TopicLinearAlgebraDecompositions Linear algebra and decompositions (catalogue)
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/** \eigenManualPage TopicLinearAlgebraDecompositions Catalogue of dense decompositions
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This page presents a catalogue of the dense matrix decompositions offered by Eigen.
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For an introduction on linear solvers and decompositions, check this \link TutorialLinearAlgebra page \endlink.
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\section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen
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@ -15,13 +15,17 @@ div.contents hr {
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/**** ****/
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/* limits the width of paragraphs */
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p, dl.warning, dl.attention, dl.note
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{
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max-width:60em;
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text-align:justify;
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}
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li {
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max-width:55em;
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text-align:justify;
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}
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img {
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border: 0;
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}
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<tab type="modules" visible="yes" title="Chapters" intro=""/>
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<tab type="mainpage" visible="yes" title=""/>
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<tab type="classlist" visible="yes" title="" intro=""/>
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<!-- <tab type="classmembers" visible="yes" title="" intro=""/> -->
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</navindex>
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<!-- Layout definition for a class page -->
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