python - Colission testing with numpy -


let's have cell-matrix , coordinates x, y denote top-left cell of tetronimo , matrix b corresponding tetris well:

t = [[2,2,2],      [2,0,0],      [0,0,0]]  y,x = (1,0)  b = [[0,0,0,0,0],      [0,0,0,0,0],      [1,0,0,0,0],]

currently i'm using simple comparison find collision:

def testcollision(x,y, t, b):     dx in xrange(3):         dy in xrange(3):             if t[dy][dx] == 0:                 continue             else:                 if b[y+dy][x + dx] != 0:                     return false     return true

can speed use of numpy?

if not mistaken, of form should work

return (b[x:x+3,y:y+3] * t).sum() == 0

you should test correctness; in case algorithmically optimal, within numpy paradigm. note however, operations on small arrays such these not terribly efficient either. still lot better c-style iteration, overhead of array abstraction noticeable. is, insofar performance issue in first place, when comes tetris. ;)

return (b[x:,y:][:3,:3] * t).sum() == 0

btw, think cleaner, more readable indexing these kind of operations; though marginally (o(1)) slower since view constructed.


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