Optimize natural_break on large inputs #562
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A uv array is being calculated that strips all NaNs and Infs from the input data, but then instead of the uv array we pass on the original data.
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Thanks! LGTM |
thuydotm
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Oct 8, 2021
* Fixes in CPU version of normal_breaks. * Made the code a bit more readable * Fixed a bug where due to input data array dtype we could end up with numeric overflow and produce invalid results * Removed parallel for as it produces wrong results. This algorithm is highly sequential and cannot be parallelized * Fixes for the linter * More fixes for the linter * Another attempt to please the linter * Fix a bug - we need to pass the full sample_data to _run_numpy_jenks instead of the filtered uv array. Unfortunately this costs most of the optimization that I was hoping for. * Add a determinism test for natural_breaks to the classify test suite * Style changes to conform to code style Co-authored-by: Alexander Soklev <[email protected]>
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Optimized natural break on CPU.
Initial performance I benchmarked took 11.27s to calculate
New version takes 3.2s