The documentation says:
... in Eigen, vectors are just a special case of matrices, with either 1 row or 1 column. The case where they have 1 column is the most common; such vectors are called column-vectors, often abbreviated as just vectors. In the other case where they have 1 row, they are called row-vectors.
However this program outputs unintuitive results:
#include <eigen3/Eigen/Dense>
#include <iostream>
typedef Eigen::Matrix<double, 1, Eigen::Dynamic> RowVector;
int main(int argc, char** argv)
{
RowVector row(10);
std::cout << "Rows: " << row.rows() << std::endl;
std::cout << "Columns: " << row.cols() << std::endl;
row.transposeInPlace();
std::cout << "Rows: " << row.rows() << std::endl;
std::cout << "Columns: " << row.cols() << std::endl;
}
Output:
Rows: 1
Columns: 10
Rows: 1
Columns: 10
Is this a bug, or am I using the library incorrectly?
The documentation for transposeInPlace
says:
Note
if the matrix is not square, then
*this
must be a resizable matrix.
You'll need your type to have both dynamic rows and columns:
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>
However, there's already a typedef
for this: MatrixXd
.
Alternatively, if you still want the compile-time sizes, you can use tranpose
rather than transposeInPlace
to give you a new transposed matrix rather than modify the current one:
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> ColumnVector;
ColumnVector column = row.transpose();