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92 lines
4.3 KiB
Plaintext
92 lines
4.3 KiB
Plaintext
namespace Eigen {
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/** \page TopicStorageOrders Storage orders
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There are two different storage orders for matrices and two-dimensional arrays: column-major and row-major.
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This page explains these storage orders and how to specify which one should be used.
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<b>Table of contents</b>
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- \ref TopicStorageOrdersIntro
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- \ref TopicStorageOrdersInEigen
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- \ref TopicStorageOrdersWhich
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\section TopicStorageOrdersIntro Column-major and row-major storage
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The entries of a matrix form a two-dimensional grid. However, when the matrix is stored in memory, the entries
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have to somehow be laid out linearly. There are two main ways to do this, by row and by column.
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We say that a matrix is stored in \b row-major order if it is stored row by row. The entire first row is
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stored first, followed by the entire second row, and so on. Consider for example the matrix
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\f[
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A = \begin{bmatrix}
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8 & 2 & 2 & 9 \\
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9 & 1 & 4 & 4 \\
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3 & 5 & 4 & 5
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\end{bmatrix}.
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\f]
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If this matrix is stored in row-major order, then the entries are laid out in memory as follows:
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\code 8 2 2 9 9 1 4 4 3 5 4 5 \endcode
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On the other hand, a matrix is stored in \b column-major order if it is stored column by column, starting with
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the entire first column, followed by the entire second column, and so on. If the above matrix is stored in
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column-major order, it is laid out as follows:
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\code 8 9 3 2 1 5 2 4 4 9 4 5 \endcode
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This example is illustrated by the following Eigen code. It uses the PlainObjectBase::data() function, which
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returns a pointer to the memory location of the first entry of the matrix.
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<table class="example">
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<tr><th>Example</th><th>Output</th></tr>
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<tr><td>
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\include TopicStorageOrders_example.cpp
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</td>
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<td>
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\verbinclude TopicStorageOrders_example.out
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</td></tr></table>
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\section TopicStorageOrdersInEigen Storage orders in Eigen
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The storage order of a matrix or a two-dimensional array can be set by specifying the \c Options template
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parameter for Matrix or Array. As \ref TutorialMatrixClass explains, the %Matrix class template has six
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template parameters, of which three are compulsory (\c Scalar, \c RowsAtCompileTime and \c ColsAtCompileTime)
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and three are optional (\c Options, \c MaxRowsAtCompileTime and \c MaxColsAtCompileTime). If the \c Options
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parameter is set to \c RowMajor, then the matrix or array is stored in row-major order; if it is set to
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\c ColMajor, then it is stored in column-major order. This mechanism is used in the above Eigen program to
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specify the storage order.
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If the storage order is not specified, then Eigen normally defaults to storing the entry in column-major
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order. This is also the case if one of the convenience typedefs (\c Matrix3f, \c ArrayXXd, etc.) is
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used. However, it is possible to change the default to row-major order by defining the
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\c EIGEN_DEFAULT_TO_ROW_MAJOR \ref TopicPreprocessorDirectives "preprocessor directive".
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Matrices and arrays using one storage order can be assigned to matrices and arrays using the other storage
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order, as happens in the above program when \c Arowmajor is initialized using \c Acolmajor. Eigen will reorder
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the entries automatically. More generally, row-major and column-major matrices can be mixed in an expression
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as we want.
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\section TopicStorageOrdersWhich Which storage order to choose?
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So, which storage order should you use in your program? There is no simple answer to this question; it depends
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on your application. Here are some points to keep in mind:
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- Your users may expect you to use a specific storage order. Alternatively, you may use other libraries than
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Eigen, and these other libraries may expect a certain storage order. In these cases it may be easiest and
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fastest to use this storage order in your whole program.
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- Algorithms that traverse a matrix row by row will go faster when the matrix is stored in row-major order
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because of better data locality. Similarly, column-by-column traversal is faster for column-major
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matrices. It may be worthwhile to experiment a bit to find out what is faster for your particular
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application.
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- The default in Eigen is column-major. Naturally, most of the development and testing of the Eigen library
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is thus done with column-major matrices. This means that, even though we aim to support column-major and
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row-major storage orders transparently, the Eigen library may well work best with column-major matrices.
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*/
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}
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