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Copyedit documentation: typos, spelling

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Lars Buitinck
2016-01-24 15:50:36 +01:00
parent 34340458cb
commit 19e437daf0
2 changed files with 7 additions and 9 deletions
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doc/TutorialReductionsVisitorsBroadcasting.dox
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@@ -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