All matrix and vector classes are subclasses of the Matrix
class. There are also built-in types for commonly used matrix and vector types.
Eigen::MatrixXd A(2,4); // 2x4 double matrix
Eigen::Matrix4d B; // 4x4 double matrix
Eigen::Matrix3f C; // 3x3 float matrix
Eigen::VectorXf d(9); // 9x1 float vector
Eigen::Vector4f e; // 4x1 float vector
If you declare using namespace Eigen;
beforehand in your code, you don’t need to say Eigen::
in front of these and other Eigen types. If you do this, it is highly recommended that you do this in each .cpp
file and not in a .h
file, where it could potentially pollute multiple other files.
Use the <<
and ,
operators:
MatrixXd A(2,4); // 2x4 matrix
A << 1, 2, 3, 4,
5, 6, 7, 8;
The elements are specified row by row.
You can also initialize matrices to the zero and identity matrices.
Matrix4d B = Matrix4d::Zero(); // 4x4 zero matrix
Matrix3d C = Matrix3d::Identity(); // 3x3 identity matrix
...
B.setZero(); // back to zero
...
B.setIdentity(); // back to identity
See http://eigen.tuxfamily.org/dox/group__TutorialAdvancedInitialization.html for more information.
You can print the matrix to the screen by using cout
:
cout << A << endl;
will print out
1 2 3 4
5 6 7 8
You can access an element for read/write with the ()
operator. Rows and columns start with 0, not 1.
A(0,0) = 9;
double foo = A(1,3);
Eigen overloads the common operators, so you can add, subtract, and multiply matrices easily.
Matrix4d A, B; // 4x4 matrices
A << ...;
B << ...;
Matrix4d C = A + B; // 4x4 matrix
double s = 2.0;
Matrix4d D = s * C; // 4x4 matrix
MatrixXd E(4,3); // 4x3 matrix
E << ...
MatrixXd F(4,3); // 4x3 matrix
F = C * E;
The matrix sizes aren’t checked at compile time. If there is a mismatch, you’ll get a very complex looking runtime error - one drawback of template programming. Eigen warns against using the auto
keyword. See http://eigen.tuxfamily.org/dox/TopicPitfalls.html. In general, it is a good idea to compile and run your code often so that Eigen errors are easier to find.
You can read/write blocks of elements with the block
function.
Matrix2d B; // 2x2 matrix
B << -1, -2,
-3, -4;
A.block<2,2>(0,0) = B;
The code above writes B
into the upper 2x2 block of A
. The numbers in the angled bracket indicate the size of the block, and the numbers in parenthesis indicate the starting location. You can also read a block in the same way.
Matrix2d C = A.block<2,2>(0,2); // 2x2 matrix
This sets C
to be the right half of A
.
For vectors, use the segment
function.
Vector4d a; // 4x1 vector
a << 1, 2, 3, 4;
Vector2d b = a.segment<2>(0); // 2x1 vector
This sets b
to be the first two elements of a
.
You can create a rotation matrix from an axis-angle as follows. The input axis to the AngleAxis
constructor must be normalized.
#include <Eigen/Geometry>
...
float angle = M_PI/6.0f;
Vector3f axis(1.0f, 1.0f, 1.0f);
axis.normalize();
Matrix3f R(AngleAxisf(angle, axis));
Matrix4f M;
M.setIdentity();
M.block<3,3>(0,0) = R;
cout << M << endl;
Similarly, you can create a rotation matrix from a unit quaternion.
#include <Eigen/Geometry>
...
float x, y, z, w;
x = y = z = w = 1.0f;
Quaternionf q(w, x, y, z);
q.normalize();
Matrix3f R(q);
Matrix4f M;
M.setIdentity();
M.block<3,3>(0,0) = R;
cout << M << endl;
public: EIGEN_MAKE_ALIGNED_OPERATOR_NEW
.#define EIGEN_DONT_ALIGN_STATICALLY
before you #include <Eigen/Dense>
.For more hints, see http://eigen.tuxfamily.org/dox/group__DenseMatrixManipulation__Alignement.html.