fix: sample training data after splitting #83
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This now uniformly samples training data after the train-test-split, meaning that we always have a constant test size of 3434 complexes
Only issue I would see here is that the current code does not consider the case where there is a ligand in the test set that is not part of the train set. That causesz the model to "never see such a ligand" and thus decrease performance significantly
For this, we would however need to build our own "iterative stratified sapling" which is rather a hassle to implement. We could just include it in the conclusion of our project for now!
https://stackoverflow.com/questions/45516424/sklearn-train-test-split-on-pandas-stratify-by-multiple-columns