Re: [eigen] Assigning row vector expression to VectorXd

[Christoph Hertzberg <chtz@xxxxxxxxxxxxxxxxxxxxxxxx>]

Hi!

This is not a problem of implicitly converting a row-vector to a column 
vector, but that you are mixing a column and a row-vector in the same 
expression. I.e., expressions like

   row.cwiseQuotient(col);  row + col;

much more likely are user-errors, so they are prohibited (this has 
nothing to do with assigning them). Also, for `row+col` what should be 
the dimensions of the result (should it result in a row or column)?

If one of the dimensions is Dynamic, it is only possible to check this 
at run-time, since Dynamic could be 1 at runtime. And runtime checks are 
disabled when compiled with `-DNDEBUG` (or `-DEIGEN_NO_DEBUG`).

Allowing to assign row-expressions to VectorXd was an early 
design-decision which can't be changed without breaking a lot of 
existing code. I would generally suggest to always make sure that 
dimensions match exactly. Adding a `.transpose()` does not add any 
runtime overhead (when compiled with optimizations enabled).

I can't find the exact point where (or if) this behavior (the implicit 
transposition) is documented.
Related: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1218


Cheers,
Christoph


On 14/08/2019 11.30, Jean-Claude Monnin wrote:
> Hi,
>
> When assigning a row vector into VectorXd (eg. a column vector), it does an implicit transpose in most cases (like in the line `VectorXd tmp = m.row(i) - m.row(j);` below).
>
> I'm wondering why it doesn't behave the same way in line `VectorXd v3 = (m.row(i) - m.row(j)).cwiseQuotient(q);`. This gives the the wrong result in release mode (but calls`abort` in debug mode due to size mismatch).
>
> Why does the assignment of `v3` behaves differently than the assignment of `tmp` in the example below? Is this documented behavior?
>
> Cheers,
> Jean-Claude
>
>
>      {
>          using namespace Eigen;
>          MatrixXd m = MatrixXd::Random(10, 4);
>          VectorXd q = VectorXd::Random(m.cols());
>          Index i = 3;
>          Index j = 8;
>
>          VectorXd tmp = m.row(i) - m.row(j);
>          VectorXd v1 = tmp.cwiseQuotient(q);
>          VectorXd v2 = (m.row(i) - m.row(j)).transpose().cwiseQuotient(q);
>          VectorXd v3 = (m.row(i) - m.row(j)).cwiseQuotient(q);
>
>          std::cout << "v1 rows:" << v1.rows() << ", cols:" <<  v1.cols() << std::endl;
>          std::cout << "v2 rows:" << v2.rows() << ", cols:" <<  v2.cols() << std::endl;
>          std::cout << "v3 rows:" << v3.rows() << ", cols:" <<  v3.cols() << std::endl;
>
>          std::cout << "v1 = " << v1.transpose() << std::endl;
>          std::cout << "v2 = " << v2.transpose() << std::endl;
>          std::cout << "v3 = " << v3.transpose() << std::endl;
>      }
>
> Output in release mode:
>
> v1 rows:4, cols:1
> v2 rows:4, cols:1
> v3 rows:1, cols:1
> v1 = -0.0375015    1.61562    -1.3097  -0.394064
> v2 = -0.0375015    1.61562    -1.3097  -0.394064
> v3 = -0.0375015

--
 Dr.-Ing. Christoph Hertzberg

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