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path: root/src/python/gudhi/point_cloud/knn.py
AgeCommit message (Collapse)Author
2020-08-04Remove JAX from the documentationMarc Glisse
jax.grad does not work with our functions (I think it used to work...)
2020-05-12Merge remote-tracking branch 'origin/master' into dtmdensityMarc Glisse
2020-05-11Handle k=1 in KNearestNeighbors with SciPyMarc Glisse
2020-05-11Double underscore is not the correct syntaxROUVREAU Vincent
2020-05-11Fix #299ROUVREAU Vincent
2020-05-05fix use of threads and n_jobs in ParallelMarc Glisse
2020-04-22Document several optional dependencies of knnMarc Glisse
2020-04-20Add __license__Marc Glisse
2020-04-14Doc improvementsMarc Glisse
2020-04-13Tweak to detect fit_transformMarc Glisse
2020-04-13Remove left-over codeMarc Glisse
eagerpy is only used with enable_autodiff
2020-04-13Generalize enable_autodiff to more implementationsMarc Glisse
Still limited to L^p
2020-04-13Fix NaN gradient with pytorchMarc Glisse
2020-04-13Small autodiff tweaksMarc Glisse
2020-04-13enable_autodiff with keopsMarc Glisse
This doesn't seem like the best way to handle it, we may want to handle it like a wrapper that gets the indices from knn (whatever backend) and then computes the distances.
2020-04-12Parallelize the "precomputed" case of knnMarc Glisse
It is supposed to be possible to compile numpy with openmp, but it looks like it isn't done in any of the usual packages. It may be possible to refactor that code so there is less redundancy.
2020-04-11Use longer namesMarc Glisse
2020-03-28Optional sort_resultsMarc Glisse
2020-03-28docMarc Glisse
2020-03-28Doc tweaks, default DTM exponentMarc Glisse
2020-03-27docMarc Glisse
2020-03-26clean-up use of "implementation"Marc Glisse
2020-03-26licenseMarc Glisse
2020-03-26cmakeMarc Glisse