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We should benchmark whether the 1-3 dimensional special functions are actually faster than the n-dimensional one. If not, we can just use one implementation function for all ranks, with simple wrappers for the 1, 2 and 3 dimensional cases. This would reduce the number of implemented functions from 72 to 18, plus 54 simple wrapper functions.
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Results on my laptop: they perform exactly the same! That means we could get rid of all the special 1, 2 and 3 dimensional functions, which will clear up the code a lot.
See commit message above; the general n-dimensional functions in the current simple numpy-like interface are exactly the same! Will have to test more with more high-performance planner flags, though (#7).
We should benchmark whether the 1-3 dimensional special functions are actually faster than the n-dimensional one. If not, we can just use one implementation function for all ranks, with simple wrappers for the 1, 2 and 3 dimensional cases. This would reduce the number of implemented functions from 72 to 18, plus 54 simple wrapper functions.
The text was updated successfully, but these errors were encountered: