[ENH] Much faster mahal cleaning #982
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This is awesome! Probably also more memory efficient (?). Can you write a test that compares it against the slow implementation? We should definitely push this upstream to DIPY. |
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Good call. I was incorrectly oversimplifying the covariance calculation, but now I fixed that. It is now around 8 seconds on my test datasets, so still a significant improvement on the dipy code, and with the same result! It is probably more memory efficient, or at least as memory efificent. |
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TODO: rename and conform to dipy api and system (already 90% of the way there), then just import from fixes so there is no change to the clean_bundles code |
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It my case, it reduced the clean time from around 15 minutes to around 4 seconds (225x speedup).
We do this by using numpy functions instead of for loops. In _fixes for now, but can be moved to dipy later.