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Pitfalls.dox (7018B)


      1 namespace Eigen {
      2 
      3 /** \page TopicPitfalls Common pitfalls
      4 
      5 
      6 \section TopicPitfalls_template_keyword Compilation error with template methods
      7 
      8 See this \link TopicTemplateKeyword page \endlink.
      9 
     10 
     11 \section TopicPitfalls_aliasing Aliasing
     12 
     13 Don't miss this \link TopicAliasing page \endlink on aliasing,
     14 especially if you got wrong results in statements where the destination appears on the right hand side of the expression.
     15 
     16 
     17 \section TopicPitfalls_alignment_issue Alignment Issues (runtime assertion)
     18 
     19 %Eigen does explicit vectorization, and while that is appreciated by many users, that also leads to some issues in special situations where data alignment is compromised.
     20 Indeed, prior to C++17,  C++ does not have quite good enough support for explicit data alignment.
     21 In that case your program hits an assertion failure (that is, a "controlled crash") with a message that tells you to consult this page:
     22 \code
     23 http://eigen.tuxfamily.org/dox/group__TopicUnalignedArrayAssert.html
     24 \endcode
     25 Have a look at \link TopicUnalignedArrayAssert it \endlink and see for yourself if that's something that you can cope with.
     26 It contains detailed information about how to deal with each known cause for that issue.
     27 
     28 Now what if you don't care about vectorization and so don't want to be annoyed with these alignment issues? Then read \link getrid how to get rid of them \endlink.
     29 
     30 
     31 \section TopicPitfalls_auto_keyword C++11 and the auto keyword
     32 
     33 In short: do not use the auto keywords with %Eigen's expressions, unless you are 100% sure about what you are doing. In particular, do not use the auto keyword as a replacement for a \c Matrix<> type. Here is an example:
     34 
     35 \code
     36 MatrixXd A, B;
     37 auto C = A*B;
     38 for(...) { ... w = C * v;  ...}
     39 \endcode
     40 
     41 In this example, the type of C is not a \c MatrixXd but an abstract expression representing a matrix product and storing references to \c A and \c B.
     42 Therefore, the product of \c A*B will be carried out multiple times, once per iteration of the for loop.
     43 Moreover, if the coefficients of `A` or `B` change during the iteration, then `C` will evaluate to different values as in the following example:
     44 
     45 \code
     46 MatrixXd A = ..., B = ...;
     47 auto C = A*B;
     48 MatrixXd R1 = C;
     49 A = ...;
     50 MatrixXd R2 = C;
     51 \endcode
     52 for which we end up with `R1` &ne; `R2`.
     53 
     54 
     55 Here is another example leading to a segfault:
     56 \code
     57 auto C = ((A+B).eval()).transpose();
     58 // do something with C
     59 \endcode
     60 The problem is that \c eval() returns a temporary object (in this case a \c MatrixXd) which is then referenced by the \c Transpose<> expression.
     61 However, this temporary is deleted right after the first line, and then the \c C expression references a dead object.
     62 One possible fix consists in applying \c eval() on the whole expression:
     63 \code
     64 auto C = (A+B).transpose().eval();
     65 \endcode
     66 
     67 The same issue might occur when sub expressions are automatically evaluated by %Eigen as in the following example:
     68 \code
     69 VectorXd u, v;
     70 auto C = u + (A*v).normalized();
     71 // do something with C
     72 \endcode
     73 Here the \c normalized() method has to evaluate the expensive product \c A*v to avoid evaluating it twice.
     74 Again, one possible fix is to call \c .eval() on the whole expression:
     75 \code
     76 auto C = (u + (A*v).normalized()).eval();
     77 \endcode
     78 In this case, \c C will be a regular \c VectorXd object.
     79 Note that DenseBase::eval() is smart enough to avoid copies when the underlying expression is already a plain \c Matrix<>.
     80 
     81 
     82 \section TopicPitfalls_header_issues Header Issues (failure to compile)
     83 
     84 With all libraries, one must check the documentation for which header to include.
     85 The same is true with %Eigen, but slightly worse: with %Eigen, a method in a class may require an additional \c \#include over what the class itself requires!
     86 For example, if you want to use the \c cross() method on a vector (it computes a cross-product) then you need to:
     87 \code
     88 #include<Eigen/Geometry>
     89 \endcode
     90 We try to always document this, but do tell us if we forgot an occurrence.
     91 
     92 
     93 \section TopicPitfalls_ternary_operator Ternary operator
     94 
     95 In short: avoid the use of the ternary operator <code>(COND ? THEN : ELSE)</code> with %Eigen's expressions for the \c THEN and \c ELSE statements.
     96 To see why, let's consider the following example:
     97 \code
     98 Vector3f A;
     99 A << 1, 2, 3;
    100 Vector3f B = ((1 < 0) ? (A.reverse()) : A);
    101 \endcode
    102 This example will return <code>B = 3, 2, 1</code>. Do you see why?
    103 The reason is that in c++ the type of the \c ELSE statement is inferred from the type of the \c THEN expression such that both match.
    104 Since \c THEN is a <code>Reverse<Vector3f></code>, the \c ELSE statement A is converted to a <code>Reverse<Vector3f></code>, and the compiler thus generates:
    105 \code
    106 Vector3f B = ((1 < 0) ? (A.reverse()) : Reverse<Vector3f>(A));
    107 \endcode
    108 In this very particular case, a workaround would be to call A.reverse().eval() for the \c THEN statement, but the safest and fastest is really to avoid this ternary operator with %Eigen's expressions and use a if/else construct.
    109 
    110 
    111 \section TopicPitfalls_pass_by_value Pass-by-value
    112 
    113 If you don't know why passing-by-value is wrong with %Eigen, read this \link TopicPassingByValue page \endlink first.
    114 
    115 While you may be extremely careful and use care to make sure that all of your code that explicitly uses %Eigen types is pass-by-reference you have to watch out for templates which define the argument types at compile time.
    116 
    117 If a template has a function that takes arguments pass-by-value, and the relevant template parameter ends up being an %Eigen type, then you will of course have the same alignment problems that you would in an explicitly defined function passing %Eigen types by reference.
    118 
    119 Using %Eigen types with other third party libraries or even the STL can present the same problem.
    120 <code>boost::bind</code> for example uses pass-by-value to store arguments in the returned functor.
    121 This will of course be a problem.
    122 
    123 There are at least two ways around this:
    124   - If the value you are passing is guaranteed to be around for the life of the functor, you can use boost::ref() to wrap the value as you pass it to boost::bind. Generally this is not a solution for values on the stack as if the functor ever gets passed to a lower or independent scope, the object may be gone by the time it's attempted to be used.
    125   - The other option is to make your functions take a reference counted pointer like boost::shared_ptr as the argument. This avoids needing to worry about managing the lifetime of the object being passed.
    126 
    127 
    128 \section TopicPitfalls_matrix_bool Matrices with boolean coefficients
    129 
    130 The current behaviour of using \c Matrix with boolean coefficients is inconsistent and likely to change in future versions of Eigen, so please use it carefully!
    131 
    132 A simple example for such an inconsistency is 
    133 
    134 \code
    135 template<int Size>
    136 void foo() {
    137   Eigen::Matrix<bool, Size, Size> A, B, C;
    138   A.setOnes();
    139   B.setOnes();
    140 
    141   C = A * B - A * B;
    142   std::cout << C << "\n";
    143 }
    144 \endcode
    145 
    146 since calling \c foo<3>() prints the zero matrix while calling \c foo<10>() prints the identity matrix.
    147 
    148 */
    149 }