mirror of https://github.com/rdk/p2rank.git synced 2026-06-04 12:44:24 +08:00

Files

rdk 2de315e9e0 Rename API: PocketCriterium->PocketCriterion, getLigandAtoms->getAtoms, centroid->center

- Rename PocketCriterium to PocketCriterion (fix Latin spelling)
- Revert getLigandAtoms() back to getAtoms() in BindingSite interface
- Rename getCentroidForEval() to getCenterForEval()
- Rename explicitCentroid to explicitCenter in ResidueSite
- Rename SiteCentroidMethod values: explicit_centroid->explicit,
  sas_points_center_of_mass->sas_points_centroid
- Rename site_centroid_method param to site_eval_center_method
- Ligand.getCentroid() now delegates to getCenterForEval()

2026-03-10 02:02:47 +01:00

p2rank_output/predict_1fbl

Rename API: PocketCriterium->PocketCriterion, getLigandAtoms->getAtoms, centroid->center

2026-03-10 02:02:47 +01:00

analyze_p2rank_output.ipynb

Add example Jupyter notebook for analyzing P2Rank output

2026-03-09 12:05:00 +01:00

readme.md

Add example Jupyter notebook for analyzing P2Rank output

2026-03-09 12:05:00 +01:00

readme.md

P2Rank Notebooks

Example Jupyter notebooks for working with P2Rank output.

Notebooks

analyze_p2rank_output.ipynb - Load and explore _predictions.csv and _residues.csv output files using pandas.

Requirements

pip install pandas matplotlib jupyter

Running

cd documentation/notebooks
jupyter notebook

Then open analyze_p2rank_output.ipynb.

The notebook uses example output in p2rank_output/predict_1fbl/ which is included in this directory.