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namespace Eigen {
/** \page Eigen2ToEigen3 Porting from Eigen2 to Eigen3
The goals of this page is to enumerate the API changes between Eigen2 and Eigen3,
and to help porting an application from Eigen2 to Eigen3.
\b Table \b of \b contents
- \ref summary
- \ref modules
- \ref core
\section CompatibilitySupport Eigen2 compatibility support
In order to ease th switch from Eigen2 to Eigen3, Eigen3 features a compatibility mode which can be enabled by defining the EIGEN2_SUPPORT preprocessor token \b before including any Eigen's header (typically it should be set in your project options).
\section ChangeList List of changes
<table>
<tr><td>Eigen 2</td><td>Eigen 3</td></tr>
<tr><td>vec.start(length)</td><td>vec.head(length)</td></tr>
<tr><td>vec.start<length>()</td><td>vec.head<length>()</td></tr>
<tr><td>vec.end(length)</td><td>vec.tail(length)</td></tr>
<tr><td>vec.end<length>()</td><td>vec.tail<length>()</td></tr>
<tr></tr>
<tr><td>mat.cwise().XXX()</td><td>mat.array().XXX() \redstar</td></tr>
<tr></tr>
<tr><td>\code c = (a * b).lazy();\endcode</td><td>\code c.noalias() = a * b;\endcode</td></tr>
</table>
\redstar See \ref CoefficientWiseOperations for details.
\section CoefficientWiseOperations Coefficient wise operations
In Eigen2, coefficient wise operations which have no proper mathematical definiton (as a coeff wise product)
were achied using the .cwise() prefix, e.g.:
\code a.cwise() * b \code
In Eigen3 this .cwise() prefix has been supersed by a new kind of matrix type called
Array for which all operations are performed coefficient wise. You can easily view a matrix as an array and vice versa using
the MatrixBase::array() and ArrayBase::matrix() functions respectively. Here is an example:
\code
Vector4f a, b, c;
c = a.array() * b.array();
\endcode
Note that the .array() function is not at all a synonym of the deprecated .cwise() prefix.
While the .cwise() prefix changed the behavior of the following operator, the array() function performs
a permanent convertion to the array world. Therefore, for binary operations such as the coeff wise product,
both sides must be converted to an \em array as in the above example. On the other hand, when you
concatenates multiple coeff wise operations you only have to do the conversion once, e.g.:
\code
Vector4f a, b, c;
c = a.array().abs().pow(3) * b.array().abs().sin();
\endcode
With Eigen2 you would have written:
\code
c = (a.cwise().abs().cwise().pow(3)).cwise() * (b.cwise().abs().cwise().sin());
\endcode
\section LazyVsNoalias Lazy evaluation versus noalias
In Eigen all operations are performed in a lazy fashion expected the matrix products which are always evaluated to a temporary by default.
In Eigen2, lazy evaluation could be enforced by tagging a product using the .lazy() function. However, in complex expressions it was not
easy to determine where to put the lazy() function. In Eigen3, the lazy() feature has been supersed by the MatrixBase::noalias() function
which can be used on the left hand side of an assignment when no aliasing can occur. Here is an example:
\code
MatrixXf a, b, c;
...
c.noalias() += 2 * a.transpose() * b;
\endcode
*/
}
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