Writing a composite transformation as a matrix multiplication I have two



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Writing a composite transformation as a matrix multiplication
I have two matrices, P and Q as follows:

Answer & Explanation



Beginner2022-02-02Added 21 answers

Step 1
Matrices work like functions. If you have functions f:AB and g:BC, and a element xA, we do first f(x), then g(f(x))=(g×f)(x). Notice that the order is different, we applied f, then g, but the result ended up being g×f. It is the same for matrices.
Extra info. for you: The matrix of rotation by a angle θ is given by
This way, P is rotation by 60 deg and Q is rotation by 120 deg.


Beginner2022-02-03Added 10 answers

Step 1
Here's the deal: operating on a point p by a transformation T is written T(p). That is, the point operated on goes to the right of the function being applied. If you wanted to then take the result,
nd apply a transformation S, you'd write S(q). Substituting, you'd find that this was
Many important transformations can be written in the form of multiplication by a matrix, and one might conjecture that the definition of matrix multiplication was made so that
where M is a matrix, would work out nicely. Given that, if T(p)=Mp and S(q)=Kq, you get that
So yes, either in applying transformations OR in multiplying matrices for transformations (at least when points are represented by column vectors), you write the matrix for the first operation to the left of the point; the matrix for th next operation to the left of that, and so on.
Foley and van Dam, in their Computer Graphics text (first edition), used ROW vectors for point-coordinates; in that situation, the matrices go on the right, and you can read operations/matrices from right to left, which seems nice. Unfortunately, if you do that, then operations on covectors (like the normal vector to a surface) end up reading left-to-right, so you don't really win. You also, in using row vectors, go against the conventions widely used in math courses, which just messes up your students. That's why in later editions (I confess I'm a co-author) we went with column vectors.

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