Merged in larsmans/eigen (pull request PR-156)

Documentation fixes

3 files changed, 10 insertions, 12 deletions

diff --git a/Eigen/src/Core/Visitor.h b/Eigen/src/Core/Visitor.h
index 7aac0b6e1..d71dfc968 100644
--- a/Eigen/src/Core/Visitor.h
+++ b/Eigen/src/Core/Visitor.h
@@ -197,7 +197,7 @@ struct functor_traits<max_coeff_visitor<Scalar> > {
 /** \returns the minimum of all coefficients of *this and puts in *row and *col its location.
   * \warning the result is undefined if \c *this contains NaN.
   *
-  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
@@ -215,7 +215,7 @@ DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
 /** \returns the minimum of all coefficients of *this and puts in *index its location.
   * \warning the result is undefined if \c *this contains NaN. 
   *
-  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::minCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
@@ -233,7 +233,7 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
 /** \returns the maximum of all coefficients of *this and puts in *row and *col its location.
   * \warning the result is undefined if \c *this contains NaN. 
   *
-  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(), DenseBase::maxCoeff()
+  * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()
   */
 template<typename Derived>
 template<typename IndexType>
diff --git a/doc/TutorialReductionsVisitorsBroadcasting.dox b/doc/TutorialReductionsVisitorsBroadcasting.dox
index 6d25ff0ea..f5322b4a6 100644
--- a/doc/TutorialReductionsVisitorsBroadcasting.dox
+++ b/doc/TutorialReductionsVisitorsBroadcasting.dox
@@ -101,17 +101,16 @@ row and column position are to be stored. These variables should be of type
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_visitors.out
 </td></tr></table>
 
-Note that both functions also return the value of the minimum or maximum coefficient if needed,
-as if it was a typical reduction operation.
+Both functions also return the value of the minimum or maximum coefficient.
 
 \section TutorialReductionsVisitorsBroadcastingPartialReductions Partial reductions
 Partial reductions are reductions that can operate column- or row-wise on a Matrix or 
 Array, applying the reduction operation on each column or row and 
-returning a column or row-vector with the corresponding values. Partial reductions are applied 
+returning a column or row vector with the corresponding values. Partial reductions are applied 
 with \link DenseBase::colwise() colwise() \endlink or \link DenseBase::rowwise() rowwise() \endlink.
 
 A simple example is obtaining the maximum of the elements 
-in each column in a given matrix, storing the result in a row-vector:
+in each column in a given matrix, storing the result in a row vector:
 
 <table class="example">
 <tr><th>Example:</th><th>Output:</th></tr>
@@ -133,8 +132,7 @@ The same operation can be performed row-wise:
 \verbinclude Tutorial_ReductionsVisitorsBroadcasting_rowwise.out
 </td></tr></table>
 
-<b>Note that column-wise operations return a 'row-vector' while row-wise operations
-return a 'column-vector'</b>
+<b>Note that column-wise operations return a row vector, while row-wise operations return a column vector.</b>
 
 \subsection TutorialReductionsVisitorsBroadcastingPartialReductionsCombined Combining partial reductions with other operations
 It is also possible to use the result of a partial reduction to do further processing.
@@ -176,7 +174,7 @@ The concept behind broadcasting is similar to partial reductions, with the diffe
 constructs an expression where a vector (column or row) is interpreted as a matrix by replicating it in 
 one direction.
 
-A simple example is to add a certain column-vector to each column in a matrix. 
+A simple example is to add a certain column vector to each column in a matrix. 
 This can be accomplished with:
 
 <table class="example">
@@ -253,7 +251,7 @@ is a new matrix whose size is the same as matrix <tt>m</tt>: \f[
 \f]
 
   - <tt>(m.colwise() - v).colwise().squaredNorm()</tt> is a partial reduction, computing the squared norm column-wise. The result of
-this operation is a row-vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
+this operation is a row vector where each coefficient is the squared Euclidean distance between each column in <tt>m</tt> and <tt>v</tt>: \f[
   \mbox{(m.colwise() - v).colwise().squaredNorm()} =
   \begin{bmatrix}
      1 & 505 & 32 & 50
diff --git a/doc/UsingIntelMKL.dox b/doc/UsingIntelMKL.dox
index 84db992b6..02c62ad85 100644
--- a/doc/UsingIntelMKL.dox
+++ b/doc/UsingIntelMKL.dox
@@ -52,7 +52,7 @@ When doing so, a number of Eigen's algorithms are silently substituted with call
 These substitutions apply only for \b Dynamic \b or \b large enough objects with one of the following four standard scalar types: \c float, \c double, \c complex<float>, and \c complex<double>.
 Operations on other scalar types or mixing reals and complexes will continue to use the built-in algorithms.
 
-In addition you can coarsely select choose which parts will be substituted by defining one or multiple of the following macros:
+In addition you can choose which parts will be substituted by defining one or multiple of the following macros:
 
 <table class="manual">
 <tr><td>\c EIGEN_USE_BLAS </td><td>Enables the use of external BLAS level 2 and 3 routines (currently works with Intel MKL only)</td></tr>