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Clean the manual page titles, links and intro.

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This commit is contained in:
Gael Guennebaud 2013-01-06 23:48:59 +01:00
parent c71c06b71f
commit 091a49cad5
13 changed files with 21 additions and 69 deletions
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7
doc/C01_TutorialMatrixClass.dox
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@ -2,12 +2,6 @@ namespace Eigen {
/** \eigenManualPage TutorialMatrixClass The Matrix class /** \eigenManualPage TutorialMatrixClass The Matrix class
\li \b Previous: \ref GettingStarted
\li \b Next: \ref TutorialMatrixArithmetic
We assume that you have already read the quick \link GettingStarted "getting started" \endlink tutorial.
This page is the first one in a much longer multi-page tutorial.
\eigenAutoToc \eigenAutoToc
In Eigen, all matrices and vectors are objects of the Matrix template class. In Eigen, all matrices and vectors are objects of the Matrix template class.
@ -264,7 +258,6 @@ Where:
defined for these five types doesn't mean that they are the only supported scalar types. For example, defined for these five types doesn't mean that they are the only supported scalar types. For example,
all standard integer types are supported, see \ref TopicScalarTypes "Scalar types". all standard integer types are supported, see \ref TopicScalarTypes "Scalar types".
\li \b Next: \ref TutorialMatrixArithmetic
*/ */

7
doc/C02_TutorialMatrixArithmetic.dox
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@ -2,10 +2,7 @@ namespace Eigen {
/** \eigenManualPage TutorialMatrixArithmetic Matrix and vector arithmetic /** \eigenManualPage TutorialMatrixArithmetic Matrix and vector arithmetic
\li \b Previous: \ref TutorialMatrixClass This page aims to provide an overview and some details on how to perform arithmetic
\li \b Next: \ref TutorialArrayClass
This tutorial aims to provide an overview and some details on how to perform arithmetic
between matrices, vectors and scalars with Eigen. between matrices, vectors and scalars with Eigen.
\eigenAutoToc \eigenAutoToc
@ -212,8 +209,6 @@ Eigen then uses runtime assertions. This means that the program will abort with
For more details on this topic, see \ref TopicAssertions "this page". For more details on this topic, see \ref TopicAssertions "this page".
\li \b Next: \ref TutorialArrayClass
*/ */
} }

7
doc/C03_TutorialArrayClass.dox
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@ -2,10 +2,7 @@ namespace Eigen {
/** \eigenManualPage TutorialArrayClass The Array class and coefficient-wise operations /** \eigenManualPage TutorialArrayClass The Array class and coefficient-wise operations
\li \b Previous: \ref TutorialMatrixArithmetic This page aims to provide an overview and explanations on how to use
\li \b Next: \ref TutorialBlockOperations
This tutorial aims to provide an overview and explanations on how to use
Eigen's Array class. Eigen's Array class.
\eigenAutoToc \eigenAutoToc
@ -190,8 +187,6 @@ expression <tt>(m.array() * n.array()).matrix() * m</tt> computes the coefficien
\verbinclude Tutorial_ArrayClass_interop.out \verbinclude Tutorial_ArrayClass_interop.out
</td></tr></table> </td></tr></table>
\li \b Next: \ref TutorialBlockOperations
*/ */
} }

7
doc/C04_TutorialBlockOperations.dox
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@ -2,10 +2,7 @@ namespace Eigen {
/** \eigenManualPage TutorialBlockOperations Block operations /** \eigenManualPage TutorialBlockOperations Block operations
\li \b Previous: \ref TutorialArrayClass This page explains the essentials of block operations.
\li \b Next: \ref TutorialAdvancedInitialization
This tutorial page explains the essentials of block operations.
A block is a rectangular part of a matrix or array. Blocks expressions can be used both A block is a rectangular part of a matrix or array. Blocks expressions can be used both
as rvalues and as lvalues. As usual with Eigen expressions, this abstraction has zero runtime cost as rvalues and as lvalues. As usual with Eigen expressions, this abstraction has zero runtime cost
provided that you let your compiler optimize. provided that you let your compiler optimize.
@ -226,8 +223,6 @@ An example is presented below:
\verbinclude Tutorial_BlockOperations_vector.out \verbinclude Tutorial_BlockOperations_vector.out
</td></tr></table> </td></tr></table>
\li \b Next: \ref TutorialAdvancedInitialization
*/ */
} }

5
doc/C05_TutorialAdvancedInitialization.dox
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@ -2,9 +2,6 @@ namespace Eigen {
/** \eigenManualPage TutorialAdvancedInitialization Advanced initialization /** \eigenManualPage TutorialAdvancedInitialization Advanced initialization
\li \b Previous: \ref TutorialBlockOperations
\li \b Next: \ref TutorialLinearAlgebra
This page discusses several advanced methods for initializing matrices. It gives more details on the This page discusses several advanced methods for initializing matrices. It gives more details on the
comma-initializer, which was introduced before. It also explains how to get special matrices such as the comma-initializer, which was introduced before. It also explains how to get special matrices such as the
identity matrix and the zero matrix. identity matrix and the zero matrix.
@ -160,8 +157,6 @@ The \link CommaInitializer::finished() finished() \endlink method is necessary h
object once the comma initialization of our temporary submatrix is done. object once the comma initialization of our temporary submatrix is done.
\li \b Next: \ref TutorialLinearAlgebra
*/ */
} }

11
doc/C06_TutorialLinearAlgebra.dox
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@ -2,12 +2,9 @@ namespace Eigen {
/** \eigenManualPage TutorialLinearAlgebra Linear algebra and decompositions /** \eigenManualPage TutorialLinearAlgebra Linear algebra and decompositions
\li \b Previous: \ref TutorialAdvancedInitialization This page explains how to solve linear systems, compute various decompositions such as LU,
\li \b Next: \ref TutorialReductionsVisitorsBroadcasting QR, %SVD, eigendecompositions... After reading this page, don't miss our
\link TopicLinearAlgebraDecompositions catalogue \endlink of dense matrix decompositions.
This tutorial explains how to solve linear systems, compute various decompositions such as LU,
QR, %SVD, eigendecompositions... for more advanced topics, don't miss our special page on
\ref TopicLinearAlgebraDecompositions "this topic".
\eigenAutoToc \eigenAutoToc
@ -253,8 +250,6 @@ decomposition after you've changed the threshold.
</tr> </tr>
</table> </table>
\li \b Next: \ref TutorialReductionsVisitorsBroadcasting
*/ */
} }

7
doc/C07_TutorialReductionsVisitorsBroadcasting.dox
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@ -2,10 +2,7 @@ namespace Eigen {
/** \eigenManualPage TutorialReductionsVisitorsBroadcasting Reductions, visitors and broadcasting /** \eigenManualPage TutorialReductionsVisitorsBroadcasting Reductions, visitors and broadcasting
\li \b Previous: \ref TutorialLinearAlgebra This page explains Eigen's reductions, visitors and broadcasting and how they are used with
\li \b Next: \ref TutorialGeometry
This tutorial explains Eigen's reductions, visitors and broadcasting and how they are used with
\link MatrixBase matrices \endlink and \link ArrayBase arrays \endlink. \link MatrixBase matrices \endlink and \link ArrayBase arrays \endlink.
\eigenAutoToc \eigenAutoToc
@ -255,8 +252,6 @@ this operation is a row-vector where each coefficient is the squared Euclidean d
- 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 - 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
distance. distance.
\li \b Next: \ref TutorialGeometry
*/ */
} }

9
doc/C08_TutorialGeometry.dox
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@ -1,11 +1,8 @@
namespace Eigen { namespace Eigen {
/** \eigenManualPage TutorialGeometry Geometry /** \eigenManualPage TutorialGeometry Space transformations
\li \b Previous: \ref TutorialReductionsVisitorsBroadcasting 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.
\li \b Next: \ref TutorialSparse
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.
\eigenAutoToc \eigenAutoToc
@ -239,8 +236,6 @@ m = AngleAxisf(angle1, Vector3f::UnitZ())
\endcode</td></tr> \endcode</td></tr>
</table> </table>
\li \b Next: \ref TutorialSparse
*/ */
} }

7
doc/C09_TutorialSparse.dox
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@ -2,13 +2,8 @@ namespace Eigen {
/** \eigenManualPage TutorialSparse Sparse matrix manipulations /** \eigenManualPage TutorialSparse Sparse matrix manipulations
\li \b Previous: \ref TutorialGeometry
\li \b Next: \ref TutorialMapClass
\eigeneigenAutoToc \eigeneigenAutoToc
<hr>
Manipulating and solving sparse problems involves various modules which are summarized below: Manipulating and solving sparse problems involves various modules which are summarized below:
<table class="manual"> <table class="manual">
@ -436,8 +431,6 @@ sm2.selfadjointView<Lower>() = A.selfadjointView<Lower>().twistedBy(P); //
sm1.middleCols(j, nb); // for column major matrices only, get a range of nb columns sm1.middleCols(j, nb); // for column major matrices only, get a range of nb columns
\endcode \endcode
\li \b Next: \ref TutorialMapClass
*/ */
} }

12
doc/C10_TutorialMapClass.dox
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@ -1,13 +1,9 @@
namespace Eigen { namespace Eigen {
/** \eigenManualPage TutorialMapClass Interfacing with C/C++ arrays and external libraries: the %Map class /** \eigenManualPage TutorialMapClass Interfacing with raw buffers: the Map class
\ingroup Tutorial This page explains how to work with "raw" C/C++ arrays.
This can be useful in a variety of contexts, particularly when "importing" vectors and matrices from other libraries into Eigen.
\li \b Previous: \ref TutorialSparse
\li \b Next:
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.
\eigenAutoToc \eigenAutoToc
@ -85,8 +81,6 @@ for (int i = 0; i < n_matrices; i++)
} }
\endcode \endcode
\li \b Next:
*/ */
} }

4
doc/TopicLinearAlgebraDecompositions.dox
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@ -1,7 +1,9 @@
namespace Eigen { namespace Eigen {
/** \eigenManualPage TopicLinearAlgebraDecompositions Linear algebra and decompositions (catalogue) /** \eigenManualPage TopicLinearAlgebraDecompositions Catalogue of dense decompositions
This page presents a catalogue of the dense matrix decompositions offered by Eigen.
For an introduction on linear solvers and decompositions, check this \link TutorialLinearAlgebra page \endlink.
\section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen \section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen

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doc/eigendoxy.css
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@ -15,13 +15,17 @@ div.contents hr {
/**** ****/ /**** ****/
/* limits the width of paragraphs */
p, dl.warning, dl.attention, dl.note p, dl.warning, dl.attention, dl.note
{ {
max-width:60em; max-width:60em;
text-align:justify; text-align:justify;
} }
li {
max-width:55em;
text-align:justify;
}
img { img {
border: 0; border: 0;
} }

1
doc/eigendoxy_layout.xml.in
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@ -7,6 +7,7 @@
<tab type="modules" visible="yes" title="Chapters" intro=""/> <tab type="modules" visible="yes" title="Chapters" intro=""/>
<tab type="mainpage" visible="yes" title=""/> <tab type="mainpage" visible="yes" title=""/>
<tab type="classlist" visible="yes" title="" intro=""/> <tab type="classlist" visible="yes" title="" intro=""/>
<!-- <tab type="classmembers" visible="yes" title="" intro=""/> -->
</navindex> </navindex>
<!-- Layout definition for a class page --> <!-- Layout definition for a class page -->