MOFClassifier: A Machine Learning Approach for Validating Computation-Ready Metal-Organic Frameworks
Installation
pip install MOFClassifier
Examples
from MOFClassifier import CLscore
result = CLscore.predict(root_cif="./example.cif", model="core")
- root_cif: the path of your structure
- model: the model name: a. "core": training with CoRE MOF DB; b. "qsp": training with CoRE MOF DB and QMOF DB; c. "h": training with ToBaCCo (Hypothetical MOFs)
- result: a. cifid: the name of structure; b. all_score: the CLscore predicted by 100 models (bags); c. mean_score: the mean CLscore of CLscores
from MOFClassifier import CLscore
results = CLscore.predict_batch(root_cifs=["./example1.cif""./example2.cif","./example3.cif"], model="core", batch_size=512)
- root_cifs: the path of your structures
- model: the model name: a. "core": training with CoRE MOF DB; b. "qsp": training with CoRE MOF DB and QMOF DB; c. "h": training with ToBaCCo (Hypothetical MOFs)
- batch_size: the number of samples
- results: a. cifid: the name of structure; b. all_score: the CLscore predicted by 100 models (bags); c. mean_score: the mean CLscore of CLscores
Citation
Acknowledgments
We thank henk789 for contribution to batch prediction.
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