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