update CSS to doxygen 1.7.2, new CSS and cleaning of the tutorial

1 files changed, 47 insertions, 31 deletions

diff --git a/doc/C07_TutorialReductionsVisitorsBroadcasting.dox b/doc/C07_TutorialReductionsVisitorsBroadcasting.dox
index 130514189..44e963424 100644
--- a/doc/C07_TutorialReductionsVisitorsBroadcasting.dox
+++ b/doc/C07_TutorialReductionsVisitorsBroadcasting.dox
@@ -13,7 +13,7 @@ This tutorial explains Eigen's reductions, visitors and broadcasting and how the
   - \ref TutorialReductionsVisitorsBroadcastingReductions
     - \ref TutorialReductionsVisitorsBroadcastingReductionsNorm
     - \ref TutorialReductionsVisitorsBroadcastingReductionsBool
-    - FIXME: .redux()
+    - \ref TutorialReductionsVisitorsBroadcastingReductionsUserdefined
   - \ref TutorialReductionsVisitorsBroadcastingVisitors
   - \ref TutorialReductionsVisitorsBroadcastingPartialReductions
     - \ref TutorialReductionsVisitorsBroadcastingPartialReductionsCombined
@@ -26,11 +26,13 @@ In Eigen, a reduction is a function taking a matrix or array, and returning a si
 scalar value. One of the most used reductions is \link DenseBase::sum() .sum() \endlink,
 returning the sum of all the coefficients inside a given matrix or array.
 
-<table class="tutorial_code"><tr><td>
-Example: \include tut_arithmetic_redux_basic.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include tut_arithmetic_redux_basic.cpp
 </td>
 <td>
-Output: \verbinclude tut_arithmetic_redux_basic.out
+\verbinclude tut_arithmetic_redux_basic.out
 </td></tr></table>
 
 The \em trace of a matrix, as returned by the function \c trace(), is the sum of the diagonal coefficients and can equivalently be computed <tt>a.diagonal().sum()</tt>.
@@ -48,11 +50,12 @@ If you want other \f$\ell^p\f$ norms, use the \link MatrixBase::lpNorm() lpNnorm
 
 The following example demonstrates these methods.
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.out
 </td></tr></table>
 
@@ -65,14 +68,20 @@ The following reductions operate on boolean values:
 
 These are typically used in conjunction with the coefficient-wise comparison and equality operators provided by Array. For instance, <tt>array > 0</tt> is an %Array of the same size as \c array , with \b true at those positions where the corresponding coefficient of \c array is positive. Thus, <tt>(array > 0).all()</tt> tests whether all coefficients of \c array are positive. This can be seen in the following example:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_reductions_bool.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_reductions_bool.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_reductions_bool.out
 </td></tr></table>
 
+\subsection TutorialReductionsVisitorsBroadcastingReductionsUserdefined User defined reductions
+
+TODO
+
+In the meantime you can have a look at the DenseBase::redux() function.
 
 \section TutorialReductionsVisitorsBroadcastingVisitors Visitors
 Visitors are useful when one wants to obtain the location of a coefficient inside 
@@ -86,11 +95,12 @@ The arguments passed to a visitor are pointers to the variables where the
 row and column position are to be stored. These variables should be of type
 \link DenseBase::Index Index \endlink (FIXME: link ok?), as shown below:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_visitors.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_visitors.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_visitors.out
 </td></tr></table>
 
@@ -106,21 +116,23 @@ with \link DenseBase::colwise() colwise() \endlink or \link DenseBase::rowwise()
 A simple example is obtaining the maximum of the elements 
 in each column in a given matrix, storing the result in a row-vector:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_colwise.out
 </td></tr></table>
 
 The same operation can be performed row-wise:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_rowwise.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_rowwise.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_rowwise.out
 </td></tr></table>
 
@@ -132,11 +144,12 @@ It is also possible to use the result of a partial reduction to do further proce
 Here is another example that aims to find the column whose sum of elements is the maximum
  within a matrix. With column-wise partial reductions this can be coded as:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_maxnorm.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_maxnorm.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_maxnorm.out
 </td></tr></table>
 
@@ -169,11 +182,12 @@ one direction.
 A simple example is to add a certain column-vector to each column in a matrix. 
 This can be accomplished with:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.out
 </td></tr></table>
 
@@ -184,11 +198,12 @@ The same applies for the Array class, where the equivalent for VectorXf is Array
 
 Therefore, to perform the same operation row-wise we can do:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.out
 </td></tr></table>
 
@@ -200,11 +215,12 @@ Now that broadcasting, reductions and partial reductions have been introduced, w
 the nearest neighbour of a vector <tt>v</tt> within the columns of matrix <tt>m</tt>. The Euclidean distance will be used in this example,
 computing the squared Euclidean distance with the partial reduction named \link MatrixBase::squaredNorm() squaredNorm() \endlink:
 
-<table class="tutorial_code"><tr><td>
-Example: \include Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp
+<table class="example">
+<tr><th>Example:</th><th>Output:</th></tr>
+<tr><td>
+\include Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp
 </td>
 <td>
-Output:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.out
 </td></tr></table>