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▲ crdrost 3 days ago

I'm really surprised at the whole filtering the rotation matrices thing, to me it is like, the long side of the piece is an arrow, that arrow can be pointed in one of six directions, I can rotate in one of four directions after that, so there's 24 orientations:

    orientations = concat [
      [
        [(0,0,0), (t,0,0), (2*t,0,0), (3*t,0,0), (2*t, a, b)],
        [(0,0,0), (0,t,0), (0,2*t,0), (0,3*t,0), (a,2*t,b)],
        [(0,0,0), (0,0,t), (0,0,2*t), (0,0,3*t), (a,b,2*t)]
     ] | (a, b) <- [(1,0), (-1, 0), (0, 1), (0, -1)], t <- [1, -1]]
With translations, okay, there's 40 of those per piece and figuring out the right direction to go with those requires a cross product, sure, let's just generate 5×5×5 = 125 of them and filter out the right 40. But doing 20,000 determinants and whatever it was, 10-15 paragraphs, to filter out the right 24 orientations doesn't make as much sense to me.
▲fn-mote 3 days ago | parent [-]

I am betting that the author came up with the filtering method in 5 minutes or less and quickly got it working.

The 10 paragraph blog post is the “hard” part: explaining to others who don’t have the same base knowledge.

If I read it correctly, they do even less human-powered work than your solution. It just looks hard because the machinery is unfamiliar.