Compilation error with template methods

See this page .

Aliasing

Don't miss this page on aliasing, especially if you got wrong results in statements where the destination appears on the right hand side of the expression.

Alignment Issues (runtime assertion)

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. Indeed, prior to C++17, C++ does not have quite good enough support for explicit data alignment. In that case your program hits an assertion failure (that is, a "controlled crash") with a message that tells you to consult this page:

http://eigen.tuxfamily.org/dox/group__TopicUnalignedArrayAssert.html

Have a look at it and see for yourself if that's something that you can cope with. It contains detailed information about how to deal with each known cause for that issue.

Now what if you don't care about vectorization and so don't want to be annoyed with these alignment issues? Then read how to get rid of them .

C++11 and the auto keyword

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 Matrix<> type. Here is an example:

MatrixXd A, B;
auto C = A*B;
for(...) { ... w = C * v;  ...}

In this example, the type of C is not a MatrixXd but an abstract expression representing a matrix product and storing references to A and B. Therefore, the product of A*B will be carried out multiple times, once per iteration of the for loop. Moreover, if the coefficients of A or B change during the iteration, then C will evaluate to different values as in the following example:

MatrixXd A = ..., B = ...;
auto C = A*B;
MatrixXd R1 = C;
A = ...;
MatrixXd R2 = C;

for which we end up with R1 ≠ R2.

Here is another example leading to a segfault:

auto C = ((A+B).eval()).transpose();
// do something with C

The problem is that eval() returns a temporary object (in this case a MatrixXd) which is then referenced by the Transpose<> expression. However, this temporary is deleted right after the first line, and then the C expression references a dead object. One possible fix consists in applying eval() on the whole expression:

auto C = (A+B).transpose().eval();

The same issue might occur when sub expressions are automatically evaluated by Eigen as in the following example:

VectorXd u, v;
auto C = u + (A*v).normalized();
// do something with C

Here the normalized() method has to evaluate the expensive product A*v to avoid evaluating it twice. Again, one possible fix is to call .eval() on the whole expression:

auto C = (u + (A*v).normalized()).eval();

In this case, C will be a regular VectorXd object. Note that DenseBase::eval() is smart enough to avoid copies when the underlying expression is already a plain Matrix<>.

Header Issues (failure to compile)

With all libraries, one must check the documentation for which header to include. The same is true with Eigen, but slightly worse: with Eigen, a method in a class may require an additional #include over what the class itself requires! For example, if you want to use the cross() method on a vector (it computes a cross-product) then you need to:

#include<Eigen/Geometry>

We try to always document this, but do tell us if we forgot an occurrence.

Ternary operator

In short: avoid the use of the ternary operator (COND ? THEN : ELSE) with Eigen's expressions for the THEN and ELSE statements. To see why, let's consider the following example:

Vector3f A;
A << 1, 2, 3;
Vector3f B = ((1 < 0) ? (A.reverse()) : A);

This example will return B = 3, 2, 1. Do you see why? The reason is that in c++ the type of the ELSE statement is inferred from the type of the THEN expression such that both match. Since THEN is a Reverse<Vector3f>, the ELSE statement A is converted to a Reverse<Vector3f>, and the compiler thus generates:

Vector3f B = ((1 < 0) ? (A.reverse()) : Reverse<Vector3f>(A));

In this very particular case, a workaround would be to call A.reverse().eval() for the THEN statement, but the safest and fastest is really to avoid this ternary operator with Eigen's expressions and use a if/else construct.

Pass-by-value

If you don't know why passing-by-value is wrong with Eigen, read this page first.

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.

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.

Using Eigen types with other third party libraries or even the STL can present the same problem. boost::bind for example uses pass-by-value to store arguments in the returned functor. This will of course be a problem.

There are at least two ways around this:

• 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.
• 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.

Matrices with boolean coefficients

The current behaviour of using Matrix with boolean coefficients is inconsistent and likely to change in future versions of Eigen, so please use it carefully!

A simple example for such an inconsistency is

template<int Size>
void foo() {
  Eigen::Matrix<bool, Size, Size> A, B, C;
  A.setOnes();
  B.setOnes();
 
  C = A * B - A * B;
  std::cout << C << "\n";
}

since calling foo<3>() prints the zero matrix while calling foo<10>() prints the identity matrix.