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.
1 maintainer
Metadata
1 maintainer
Release files for mofclassifier 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| mofclassifier-0.1.2.tar.gz | 6.8 kB | Without provenance | Details for mofclassifier-0.1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| mofclassifier-0.1.2-py3-none-any.whl | Python 3 | none | any | Details for mofclassifier-0.1.2-py3-none-any.whl |
Total release size: 13.6 kB
Release files / mofclassifier-0.1.2.tar.gz
| Download URL | mofclassifier-0.1.2.tar.gz |
|---|---|
| Size | 6.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
02ba26c944ebcd0303fd259f7f3ae70f513d63d916cb450fb0e68753822c92c8
|
|
BLAKE2b-256 checksum How to use checksums |
a9a28ca2c81f43411e9af7f7e7eb537c1d690e69b0d1819110aa53bd969c0f06
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.25
|
Release files / mofclassifier-0.1.2-py3-none-any.whl
| Download URL | mofclassifier-0.1.2-py3-none-any.whl |
|---|---|
| Size | 6.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ad8ecaae4a2ab2bf067995054da024ad886140dfe62dd89cf113b3fcdce95ab5
|
|
BLAKE2b-256 checksum How to use checksums |
f7c17bb1de1149aaf7693df028295ab4b4338a880bfb30cadd9f311316cc6ca8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.25
|
Security for mofclassifier 0.1.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
