Word generation using an n-dimensional discrete hypercube

This algorithm is something a friend of mine and I have developed quite some time ago (probably a year or so). It might also be already known under some name and I’m not aware of it. None the less it’s an interesting solution to a quite interesting problem.
Suppose that you wanted to generate the words w \in \Sigma^n of the alphabet \Sigma = \{\alpha_0, \alpha_1, \dots, \alpha_m\}. And that you wanted to do that in a parallel manner, such that you had a set of threads where each thread has a unique number out of 0\dots \vert\Sigma\vert^n assigned.
In that case it would be favorable to have a mapping in the form \underbrace{\{k: 0 \leq k < \vert\Sigma\vert^n\}}_S\to\Sigma^n, so that each thread could easily (reading with less computational effort) generate the word it’s supposed to work on. Notice that implicit definition of S:=\{k: 0 \leq k < \vert\Sigma\vert^n\}.
To solve the problem described previously, we start with a function that maps elements of S to points in an n-dimensional discrete hypercube. That mapping V: S\to\{ k: 0\leq k < \vert\Sigma\vert \}^n is defined as follows: V(s) = \begin{bmatrix} \left\lfloor\frac{s}{l^0}\right\rfloor \mod l \\ \left\lfloor\frac{s}{l^1}\right\rfloor \mod l \\ \vdots \\ \left\lfloor\frac{s}{l^{n-1}}\right\rfloor \mod l \end{bmatrix} where l:=\vert\Sigma\vert. This mapping obviously maps a natural number s < \vert\Sigma\vert^n to a point in a discrete n-dimensional hypercube with an edge length of \vert\Sigma\vert. Example: Consider \vert\Sigma\vert = 3 and n = 3. Then we can visualize V as follows:
Now that we have a mapping from a natural number to a point in the hypercube, we need a mapping from a point in the hypercube to the word itself. Such a mapping W: \{ k: 0\leq k < \vert\Sigma\vert \}^n \to \Sigma^n is easy to find. Consider W(p) := \alpha_{p_0}\alpha_{p_1}\dots\alpha_{p_n} where the p_i are the components of the vector p and \alpha_i \in \Sigma.
So our final mapping F: S\to\Sigma^n is F:=W\circ V and exactly what we desired. One might notice that F must be surjective so that each word is computed if there are just enough threads. To prove that, we’ll prove that V as well as W is surjective (since the functional composition of two surjective functions is surjective as well).
Theorem: V is surjective, so that \forall v \in \{ k: 0\leq k < \vert\Sigma\vert \}^n : \exists x \in S : V(x) = v.
Proof: Let l:=\vert\Sigma\vert, u_i\in\mathbb{N}, y\in S and v:=\begin{bmatrix} v_1 & \dots & v_n\end{bmatrix}^T. Assume that y = v_1\cdot l^0 + \dots + v_n\cdot l^{n-1}, then

V(y) = 	\begin{bmatrix}  		v_1+\underbrace{\dots+v_{n}\cdot l^{n-1}}_{u_1\cdot l} \mod l \\ 		\vdots \\ 		\underbrace{\left\lfloor\frac{v_1\cdot l^0 + \dots}{l^{n-1}}\right\rfloor}_{u_n\cdot l} + v_n \mod l 	\end{bmatrix} (1)
= \begin{bmatrix}  		v_1 \mod l & \dots & v_n \mod l 	\end{bmatrix}^T (2)
= \begin{bmatrix} v_1 & \dots & v_n\end{bmatrix}^T = v (3)

The transition from (1) to (2) is allowed as u_i\cdot l\mod l = 0. Similar goes for the equivalence of (2) and (3): v_i \mod l = v_i as v_i \leq l.

Theorem: W is surjective, so that \forall w \in \Sigma^n : \exists v \in \{ k: 0\leq k < \vert\Sigma\vert \}^n : W(v) = w.
Proof: Let w:=\alpha_{v_1}\dots\alpha_{v_n} then the vector v=\begin{bmatrix}v_1 & \dots & v_n\end{bmatrix} (which obviously fullfils W(v)=w) must exist, since v_i < \vert\Sigma\vert and v\in \{ k: 0\leq k < \vert\Sigma\vert \}^n.
So the mapping F is surjective and does exactly what we want. I consider that solution to be a particular elegant one and wanted of post it for about a year now. Finally I found some spare time to do so. If you use that solution, find a mistake or find it somewhere else (maybe even previously described) please drop a comment.

Soap Bubble Bot

During my studies at the HFU, I have to participate in at least two semester projects. This time we built a new USB interface for some pretty old hardware. That old hardware is a robot arm built in 80′s (there is “Made in West Germany” written on it). I’ve blogged about it before.
Today we got to present our work. But how do you show something as abstract as interface hardware/software? So we came up with that demo which we consider pretty neat: we taught the robot arm to make soap bubbles. Well, we used a bunch of ruby scripts to grad the events generated by a gamepad (HID device) and interpreted them, so that one can control the arm. We also taped something (I’d call a soap bubble device) at the front of robot. Add some of the soap fluid and we could’ve made soap bubbles manually. But that’s too easy. So we added a sequence of positions (one of the firmware’s features) and used that to do the work. Video’s after the break.
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