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      1 namespace Eigen {
      2 
      3 /** \eigenManualPage TutorialArrayClass The Array class and coefficient-wise operations
      4 
      5 This page aims to provide an overview and explanations on how to use
      6 Eigen's Array class.
      7 
      8 \eigenAutoToc
      9   
     10 \section TutorialArrayClassIntro What is the Array class?
     11 
     12 The Array class provides general-purpose arrays, as opposed to the Matrix class which
     13 is intended for linear algebra. Furthermore, the Array class provides an easy way to
     14 perform coefficient-wise operations, which might not have a linear algebraic meaning,
     15 such as adding a constant to every coefficient in the array or multiplying two arrays coefficient-wise.
     16 
     17 
     18 \section TutorialArrayClassTypes Array types
     19 Array is a class template taking the same template parameters as Matrix.
     20 As with Matrix, the first three template parameters are mandatory:
     21 \code
     22 Array<typename Scalar, int RowsAtCompileTime, int ColsAtCompileTime>
     23 \endcode
     24 The last three template parameters are optional. Since this is exactly the same as for Matrix,
     25 we won't explain it again here and just refer to \ref TutorialMatrixClass.
     26 
     27 Eigen also provides typedefs for some common cases, in a way that is similar to the Matrix typedefs
     28 but with some slight differences, as the word "array" is used for both 1-dimensional and 2-dimensional arrays.
     29 We adopt the convention that typedefs of the form ArrayNt stand for 1-dimensional arrays, where N and t are
     30 the size and the scalar type, as in the Matrix typedefs explained on \ref TutorialMatrixClass "this page". For 2-dimensional arrays, we
     31 use typedefs of the form ArrayNNt. Some examples are shown in the following table:
     32 
     33 <table class="manual">
     34   <tr>
     35     <th>Type </th>
     36     <th>Typedef </th>
     37   </tr>
     38   <tr>
     39     <td> \code Array<float,Dynamic,1> \endcode </td>
     40     <td> \code ArrayXf \endcode </td>
     41   </tr>
     42   <tr>
     43     <td> \code Array<float,3,1> \endcode </td>
     44     <td> \code Array3f \endcode </td>
     45   </tr>
     46   <tr>
     47     <td> \code Array<double,Dynamic,Dynamic> \endcode </td>
     48     <td> \code ArrayXXd \endcode </td>
     49   </tr>
     50   <tr>
     51     <td> \code Array<double,3,3> \endcode </td>
     52     <td> \code Array33d \endcode </td>
     53   </tr>
     54 </table>
     55 
     56 
     57 \section TutorialArrayClassAccess Accessing values inside an Array
     58 
     59 The parenthesis operator is overloaded to provide write and read access to the coefficients of an array, just as with matrices.
     60 Furthermore, the \c << operator can be used to initialize arrays (via the comma initializer) or to print them.
     61 
     62 <table class="example">
     63 <tr><th>Example:</th><th>Output:</th></tr>
     64 <tr><td>
     65 \include Tutorial_ArrayClass_accessors.cpp
     66 </td>
     67 <td>
     68 \verbinclude Tutorial_ArrayClass_accessors.out
     69 </td></tr></table>
     70 
     71 For more information about the comma initializer, see \ref TutorialAdvancedInitialization.
     72 
     73 
     74 \section TutorialArrayClassAddSub Addition and subtraction
     75 
     76 Adding and subtracting two arrays is the same as for matrices.
     77 The operation is valid if both arrays have the same size, and the addition or subtraction is done coefficient-wise.
     78 
     79 Arrays also support expressions of the form <tt>array + scalar</tt> which add a scalar to each coefficient in the array.
     80 This provides a functionality that is not directly available for Matrix objects.
     81 
     82 <table class="example">
     83 <tr><th>Example:</th><th>Output:</th></tr>
     84 <tr><td>
     85 \include Tutorial_ArrayClass_addition.cpp
     86 </td>
     87 <td>
     88 \verbinclude Tutorial_ArrayClass_addition.out
     89 </td></tr></table>
     90 
     91 
     92 \section TutorialArrayClassMult Array multiplication
     93 
     94 First of all, of course you can multiply an array by a scalar, this works in the same way as matrices. Where arrays
     95 are fundamentally different from matrices, is when you multiply two together. Matrices interpret
     96 multiplication as matrix product and arrays interpret multiplication as coefficient-wise product. Thus, two 
     97 arrays can be multiplied if and only if they have the same dimensions.
     98 
     99 <table class="example">
    100 <tr><th>Example:</th><th>Output:</th></tr>
    101 <tr><td>
    102 \include Tutorial_ArrayClass_mult.cpp
    103 </td>
    104 <td>
    105 \verbinclude Tutorial_ArrayClass_mult.out
    106 </td></tr></table>
    107 
    108 
    109 \section TutorialArrayClassCwiseOther Other coefficient-wise operations
    110 
    111 The Array class defines other coefficient-wise operations besides the addition, subtraction and multiplication
    112 operators described above. For example, the \link ArrayBase::abs() .abs() \endlink method takes the absolute
    113 value of each coefficient, while \link ArrayBase::sqrt() .sqrt() \endlink computes the square root of the
    114 coefficients. If you have two arrays of the same size, you can call \link ArrayBase::min(const Eigen::ArrayBase<OtherDerived>&) const .min(.) \endlink to
    115 construct the array whose coefficients are the minimum of the corresponding coefficients of the two given
    116 arrays. These operations are illustrated in the following example.
    117 
    118 <table class="example">
    119 <tr><th>Example:</th><th>Output:</th></tr>
    120 <tr><td>
    121 \include Tutorial_ArrayClass_cwise_other.cpp
    122 </td>
    123 <td>
    124 \verbinclude Tutorial_ArrayClass_cwise_other.out
    125 </td></tr></table>
    126 
    127 More coefficient-wise operations can be found in the \ref QuickRefPage.
    128 
    129 
    130 \section TutorialArrayClassConvert Converting between array and matrix expressions
    131 
    132 When should you use objects of the Matrix class and when should you use objects of the Array class? You cannot
    133 apply Matrix operations on arrays, or Array operations on matrices. Thus, if you need to do linear algebraic
    134 operations such as matrix multiplication, then you should use matrices; if you need to do coefficient-wise
    135 operations, then you should use arrays. However, sometimes it is not that simple, but you need to use both
    136 Matrix and Array operations. In that case, you need to convert a matrix to an array or reversely. This gives
    137 access to all operations regardless of the choice of declaring objects as arrays or as matrices.
    138 
    139 \link MatrixBase Matrix expressions \endlink have an \link MatrixBase::array() .array() \endlink method that
    140 'converts' them into \link ArrayBase array expressions\endlink, so that coefficient-wise operations
    141 can be applied easily. Conversely, \link ArrayBase array expressions \endlink
    142 have a \link ArrayBase::matrix() .matrix() \endlink method. As with all Eigen expression abstractions,
    143 this doesn't have any runtime cost (provided that you let your compiler optimize).
    144 Both \link MatrixBase::array() .array() \endlink and \link ArrayBase::matrix() .matrix() \endlink 
    145 can be used as rvalues and as lvalues.
    146 
    147 Mixing matrices and arrays in an expression is forbidden with Eigen. For instance, you cannot add a matrix and
    148 array directly; the operands of a \c + operator should either both be matrices or both be arrays. However,
    149 it is easy to convert from one to the other with \link MatrixBase::array() .array() \endlink and 
    150 \link ArrayBase::matrix() .matrix()\endlink. The exception to this rule is the assignment operator: it is
    151 allowed to assign a matrix expression to an array variable, or to assign an array expression to a matrix
    152 variable.
    153 
    154 The following example shows how to use array operations on a Matrix object by employing the 
    155 \link MatrixBase::array() .array() \endlink method. For example, the statement 
    156 <tt>result = m.array() * n.array()</tt> takes two matrices \c m and \c n, converts them both to an array, uses
    157 * to multiply them coefficient-wise and assigns the result to the matrix variable \c result (this is legal
    158 because Eigen allows assigning array expressions to matrix variables). 
    159 
    160 As a matter of fact, this usage case is so common that Eigen provides a \link MatrixBase::cwiseProduct const
    161 .cwiseProduct(.) \endlink method for matrices to compute the coefficient-wise product. This is also shown in
    162 the example program.
    163 
    164 <table class="example">
    165 <tr><th>Example:</th><th>Output:</th></tr>
    166 <tr><td>
    167 \include Tutorial_ArrayClass_interop_matrix.cpp
    168 </td>
    169 <td>
    170 \verbinclude Tutorial_ArrayClass_interop_matrix.out
    171 </td></tr></table>
    172 
    173 Similarly, if \c array1 and \c array2 are arrays, then the expression <tt>array1.matrix() * array2.matrix()</tt>
    174 computes their matrix product.
    175 
    176 Here is a more advanced example. The expression <tt>(m.array() + 4).matrix() * m</tt> adds 4 to every
    177 coefficient in the matrix \c m and then computes the matrix product of the result with \c m. Similarly, the
    178 expression <tt>(m.array() * n.array()).matrix() * m</tt> computes the coefficient-wise product of the matrices
    179 \c m and \c n and then the matrix product of the result with \c m.
    180 
    181 <table class="example">
    182 <tr><th>Example:</th><th>Output:</th></tr>
    183 <tr><td>
    184 \include Tutorial_ArrayClass_interop.cpp
    185 </td>
    186 <td>
    187 \verbinclude Tutorial_ArrayClass_interop.out
    188 </td></tr></table>
    189 
    190 */
    191 
    192 }
    193