@zitoun said:
I have no clue what these are yet, but I guess I somehow can retrieve my rotation matrix from such component...
Note that a transformation has the .to_a method as well which gives you exactly the information you're looking for. The array it returns is 16 floats for the four by four matrix which defines the transformation from the components defining coordinate system to the current coordinate system. Since you mentioned quaternions I'll assume you're familiar with with the essentials of matrices and linear transformations. First, we can interpret the scaling and rotation of a component as the action of a matrix on the basis vectors of the component definition. Say for example you define your component relative to the standard basis of x=[1,0,0], y=[0,1,0], z=[0,0,1]. Rather than keeping these vectors separately, you can just encode them as the 3x3 identity matrix, and then define all the entities in the component relative to this matrix. From here, any sort of rotation/scaling can be interpreted as a change of basis. The trouble of course is that any linear transformation preserves the zero vector, so you can't model a translation in this way. This means to fully describe the relative coordinates you require a an equation of the form Ax + b where A is an invertible 3x3 change of basis matrix and b is the translation vector with x being the "defining" vector of some entity internal to the component.
This is where the clever bit comes in. You can model an affine transformation of the form Ax + b as a single matrix transformation by embedding it into a space with one higher dimension. This is why the transformation.to_a method returns a 16 entry array, it's a 4x4 matrix with the first four entries being the first column, the second four entries being the second column and so on. It's easy enough to extract the original 3x3 matrix and the translation vector as well, the "upper-left" 3x3 block matrix is exactly the change of basis matrix A, and the final column vector is of the form [b, 1] where b is the translation vector. From here extracting the rotation matrix is a simple matter of matrix algebra since any change of basis matrix A can be decomposed as A = QS where Q is a rotation matrix and S is a diagonal matrix representing the scaling of each axis.
It's worth getting to know the 4x4 representation if you haven't before since it's also the way the OpenGL standard models the objects. The ability to model vector addition as matrix multiplication is only one of the reason they do it, the other being that when you're rendering perspective views rather than simply orthographic views the value of the bottom right entry plays an important role in correcting the scale of the transformation after applying the perspective matrix.
