@vtlim This pull request I think adds everything you need to finish your pipeline.
This PR adds clustering using scikit-learn's BayesianGaussianMixture as a default, but would support any clustering function that can call .fit and .predict.
It builds on PRs #45, #48, and #50 so those should be merged in that order first and then I will deal with it if conflicts arise.
I will add an example notebook here eventually, but it will require, I think being able to interact externally with OpenEye or RDKit so I need to find a way to skip those notebooks while testing if a tool isn't installed.
These tests will fail because I still haven't fixed the tests that I intentionally broke in PR #50, but that should just be two tests in test_graphs_output.py otherwise everything else should still be working.
@vtlim This pull request I think adds everything you need to finish your pipeline.
This PR adds clustering using scikit-learn's
BayesianGaussianMixture
as a default, but would support any clustering function that can call.fit
and.predict
.It builds on PRs #45, #48, and #50 so those should be merged in that order first and then I will deal with it if conflicts arise.
I will add an example notebook here eventually, but it will require, I think being able to interact externally with OpenEye or RDKit so I need to find a way to skip those notebooks while testing if a tool isn't installed.