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Small changes to tutorial page 1.
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@ -23,17 +23,17 @@ This page is the first one in a much longer multi-page tutorial.
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- \ref TutorialMatrixOptTemplParams
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- \ref TutorialMatrixTypedefs
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In Eigen, all matrices and vectors are object of the Matrix class.
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In Eigen, all matrices and vectors are objects of the Matrix template class.
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Vectors are just a special case of matrices, with either 1 row or 1 column.
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\section TutorialMatrixFirst3Params The first 3 template parameters of Matrix
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\section TutorialMatrixFirst3Params The first three template parameters of Matrix
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The Matrix class takes 6 template parameters, but for now it's enough to
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learn about the 3 first parameters. The 3 remaining parameters have default
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The Matrix class takes six template parameters, but for now it's enough to
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learn about the first three first parameters. The three remaining parameters have default
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values, which for now we will leave untouched, and which we
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\ref TutorialMatrixOptTemplParams "discuss below".
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The 3 mandatory template parameters of Matrix are:
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The three mandatory template parameters of Matrix are:
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\code
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Matrix<typename Scalar, int RowsAtCompileTime, int ColsAtCompileTime>
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\endcode
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@ -42,12 +42,14 @@ Matrix<typename Scalar, int RowsAtCompileTime, int ColsAtCompileTime>
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See \ref TopicScalarTypes "Scalar types" for a list of all supported
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scalar types and for how to extend support to new types.
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\li \c RowsAtCompileTime and \c ColsAtCompileTime are the number of rows
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and columns of the matrix as known at compile-time.
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and columns of the matrix as known at compile time (see
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\ref TutorialMatrixDynamic "below" for what to do if the number is not
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known at compile time).
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We offer a lot of convenience typedefs to cover the usual cases. For example, \c Matrix4f is
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a 4x4 matrix of floats. Here is how it is defined by Eigen:
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\code
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typedef Matrix<float,4,4> Matrix4f;
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typedef Matrix<float, 4, 4> Matrix4f;
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\endcode
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We discuss \ref TutorialMatrixTypedefs "below" these convenience typedefs.
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@ -58,11 +60,11 @@ matrices, with either 1 row or 1 column. The case where they have 1 column is th
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such vectors are called column-vectors, often abbreviated as just vectors. In the other case
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where they have 1 row, they are called row-vectors.
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For example, the convenience typedef \c Vector3f is defined as follows by Eigen:
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For example, the convenience typedef \c Vector3f is a (column) vector of 3 floats. It is defined as follows by Eigen:
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\code
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typedef Matrix<float, 3, 1> Vector3f;
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\endcode
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and we also offer convenience typedefs for row-vectors, for example:
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We also offer convenience typedefs for row-vectors, for example:
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\code
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typedef Matrix<int, 1, 2> RowVector2i;
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\endcode
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@ -70,18 +72,18 @@ typedef Matrix<int, 1, 2> RowVector2i;
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\section TutorialMatrixDynamic The special value Dynamic
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Of course, Eigen is not limited to matrices whose dimensions are known at compile time.
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The above-discussed \c RowsAtCompileTime and \c ColsAtCompileTime can take the special
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The \c RowsAtCompileTime and \c ColsAtCompileTime template parameters can take the special
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value \c Dynamic which indicates that the size is unknown at compile time, so must
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be handled as a run time variable. In Eigen terminology, such a size is referred to as a
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be handled as a run-time variable. In Eigen terminology, such a size is referred to as a
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\em dynamic \em size; while a size that is known at compile time is called a
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\em fixed \em size. For example, the convenience typedef \c MatrixXd, meaning
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a matrix of doubles with dynamic size, is defined as follows:
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\code
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typedef Matrix<double,Dynamic,Dynamic> MatrixXd;
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typedef Matrix<double, Dynamic, Dynamic> MatrixXd;
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\endcode
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And similarly, we define a self-explanatory typedef \c VectorXi as follows:
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\code
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typedef Matrix<int,Dynamic,1> VectorXi;
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typedef Matrix<int, Dynamic, 1> VectorXi;
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\endcode
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You can perfectly have e.g. a fixed number of rows with a dynamic number of columns, as in:
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\code
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@ -151,16 +153,16 @@ Matrix and vector coefficients can be conveniently set using the so-called \em c
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For now, it is enough to know this example:
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\include Tutorial_commainit_01.cpp
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Output: \verbinclude Tutorial_commainit_01.out
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The right hand side can also contains matrix expressions as discussed in \ref TutorialAdvancedInitialization "this page".
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The right-hand side can also contain matrix expressions as discussed in \ref TutorialAdvancedInitialization "this page".
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\section TutorialMatrixSizesResizing Resizing
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The current sizes can be retrieved by rows(), cols() and size(). Resizing a dynamic-size matrix is done by the resize() method.
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The current size of a matrix can be retrieved by \link EigenBase::rows() rows()\endlink, \link EigenBase::cols() cols() \endlink and \link EigenBase::size() size()\endlink. These methods return the number of rows, the number of columns and the number of coefficients, respectively. Resizing a dynamic-size matrix is done by the \link DenseStorageBase::resize(Index,Index) resize() \endlink method.
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For example: \include tut_matrix_resize.cpp
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Output: \verbinclude tut_matrix_resize.out
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The resize() method is a no-operation if the actual array size doesn't change; otherwise it is destructive.
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If you want a conservative variant of resize(), use conservativeResize(), see \ref TopicResizing "this page" for more details.
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The resize() method is a no-operation if the actual matrix size doesn't change; otherwise it is destructive: the values of the coefficients may change.
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If you want a conservative variant of resize() which does not change the coefficients, use \link DenseStorageBase::conservativeResize() conservativeResize()\endlink, see \ref TopicResizing "this page" for more details.
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All these methods are still available on fixed-size matrices, for the sake of API uniformity. Of course, you can't actually
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resize a fixed-size matrix. Trying to change a fixed size to an actually different value will trigger an assertion failure;
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@ -170,12 +172,11 @@ Output: \verbinclude tut_matrix_resize_fixed_size.out
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\section TutorialMatrixAssignment Assignment and resizing
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Assignment is the action of copying a matrix into another, using \c operator=. The only non-obvious thing to know here, is that
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Eigen does automatic resizing of the left hand side to match the right hand side's size. For example:
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Assignment is the action of copying a matrix into another, using \c operator=. Eigen resizes the matrix on the left-hand side automatically so that it matches the size of the matrix on the right-hand size. For example:
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\include tut_matrix_assignment_resizing.cpp
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Output: \verbinclude tut_matrix_assignment_resizing.out
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Of course, if the left hand side is of fixed size, resizing it is not allowed.
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Of course, if the left-hand side is of fixed size, resizing it is not allowed.
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If you do not want this automatic resizing to happen (for example for debugging purposes), you can disable it, see
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\ref TopicResizing "this page".
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@ -210,8 +211,8 @@ Finally, depending on circumstances, Eigen can also be more aggressive trying to
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\section TutorialMatrixOptTemplParams Optional template parameters
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We mentioned at the beginning of this page that the Matrix class takes 6 template parameters,
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but so far we only discussed the first 3. The remaining 3 parameters are optional. Here is
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We mentioned at the beginning of this page that the Matrix class takes six template parameters,
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but so far we only discussed the first three. The remaining three parameters are optional. Here is
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the complete list of template parameters:
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\code
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Matrix<typename Scalar,
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@ -221,18 +222,18 @@ Matrix<typename Scalar,
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int MaxRowsAtCompileTime = RowsAtCompileTime,
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int MaxColsAtCompileTime = ColsAtCompileTime>
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\endcode
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\li \c Options is a bit field; let us only mention here one bit: \c RowMajor. It specifies that the matrices
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of this type use row-major storage order; the default is column-major. See the page on
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\li \c Options is a bit field. Here, we discuss only one bit: \c RowMajor. It specifies that the matrices
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of this type use row-major storage order; by default, the storage order is column-major. See the page on
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\ref TopicStorageOrders "storage orders". For example, this type means row-major 3x3 matrices:
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\code
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Matrix<float,3,3,RowMajor>
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Matrix<float, 3, 3, RowMajor>
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\endcode
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\li \c MaxRowsAtCompileTime and \c MaxColsAtCompileTime are useful when you want to specify that, even though
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the exact sizes of your matrices are unknown at compile time, a fixed upper bound is known at
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the exact sizes of your matrices are not known at compile time, a fixed upper bound is known at
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compile time. The biggest reason why you might want to do that is to avoid dynamic memory allocation.
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For example the following matrix type uses a static array of 12 floats, without dynamic memory allocation:
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\code
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Matrix<float,Dynamic,Dynamic,0,3,4>
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Matrix<float, Dynamic, Dynamic, 0, 3, 4>
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\endcode
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\section TutorialMatrixTypedefs Convenience typedefs
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@ -243,10 +244,10 @@ Eigen defines the following Matrix typedefs:
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\li RowVectorNt for Matrix<type, 1, N>. For example, RowVector3d for Matrix<double, 1, 3>.
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Where:
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\li N can be any one of \c 2,\c 3,\c 4, or \c X (meaning \c Dynamic).
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\li N can be any one of \c 2, \c 3, \c 4, or \c X (meaning \c Dynamic).
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\li t can be any one of \c i (meaning int), \c f (meaning float), \c d (meaning double),
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\c cf (meaning complex<float>), or \c cd (meaning complex<double>). The fact that typedefs are only
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defined for these 5 types doesn't mean that they are the only supported scalar types. For example,
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defined for these five types doesn't mean that they are the only supported scalar types. For example,
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all standard integer types are supported, see \ref TopicScalarTypes "Scalar types".
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\li \b Next: \ref TutorialMatrixArithmetic
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@ -2,4 +2,4 @@ Matrix3f m;
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m << 1, 2, 3,
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4, 5, 6,
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7, 8, 9;
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cout << m;
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std::cout << m;
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MatrixXf a(2,2);
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cout << "a is of size " << a.rows() << "x" << a.cols() << std::endl;
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std::cout << "a is of size " << a.rows() << "x" << a.cols() << std::endl;
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MatrixXf b(3,3);
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a = b;
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cout << "a is now of size " << a.rows() << "x" << a.cols() << std::endl;
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std::cout << "a is now of size " << a.rows() << "x" << a.cols() << std::endl;
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