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103 lines
4.2 KiB
Plaintext
103 lines
4.2 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 CompatibilitySupport
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- \ref ChangeList
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- \ref CoefficientWiseOperations
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- \ref LazyVsNoalias
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\section CompatibilitySupport Eigen2 compatibility support
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In order to ease the 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 in the API
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<table>
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<tr><td>Eigen 2</td><td>Eigen 3</td><td>Comments</td></tr>
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<tr><td>\code
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vec.start(length)
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vec.start<length>()
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vec.end(length)
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vec.end<length>()
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\endcode</td><td>\code
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vec.head(length)
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vec.head<length>()
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vec.tail(length)
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vec.tail<length>()
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\endcode</td><td>Trivial "search and replace".</td></tr>
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<tr><td colspan="3"></td></tr>
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<tr><td>\code mat.cwise().XXX()\endcode</td><td>\code mat.array().XXX()\endcode</td><td>See \ref CoefficientWiseOperations. </td></tr>
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<tr><td colspan="3"></td></tr>
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<tr><td>\code c = (a * b).lazy();\endcode</td><td>\code c.noalias() = a * b;\endcode</td><td>See \ref LazyVsNoalias. </td></tr>
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<tr><td colspan="3"></td></tr>
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<tr><td>\code A.triangularSolveInPlace<XXX>(X);\endcode</td><td>\code A.triangularView<XXX>().solveInPlace(X);\endcode</td><td></td></tr>
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<tr><td colspan="3"></td></tr>
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<tr><td>\code
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UpperTriangular
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LowerTriangular
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UnitUpperTriangular
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UnitLowerTriangular
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StrictlyUpperTriangular
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StrictlyLowerTriangular
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\endcode</td><td>\code
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Upper
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Lower
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UnitUpper
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UnitLower
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StrictlyUpper
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StrictlyLower
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\endcode</td>
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<td>Trivial "search and replace".</td></tr>
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</table>
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\section CoefficientWiseOperations Coefficient wise operations
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In Eigen2, coefficient wise operations which have no proper mathematical definition (as a coefficient wise product)
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were achieved using the .cwise() prefix, e.g.:
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\code a.cwise() * b \endcode
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In Eigen3 this .cwise() prefix has been superseded 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 conversion to the array world. Therefore, for binary operations such as the coefficient 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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concatenate multiple coefficient 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 and noalias
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In Eigen all operations are performed in a lazy fashion except the matrix products which are always evaluated into 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 superseded 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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However, the noalias mechanism does not cover all the features of the old .lazy(). Indeed, in some extremely rare cases,
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it might be useful to explicit request for a lay product, i.e., for a product which will be evaluated one coefficient at once, on request,
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just like any other expressions. To this end you can use the MatrixBase::lazyProduct() function, however we strongly discourage you to
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use it unless you are sure of what you are doing, i.e., you have rigourosly measured a speed improvement.
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*/
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}
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