Run the oximachine
Project description
oximachinerunner
Installation
Ideally, you install everything in a clean environment, e.g., using conda
conda create -n test_oximachine_runner python=3.7
Confirm with y
when asked to do so, then activate with conda activate test_oximachine_runner
.
Latest, development, version
pip install git+https://github.com/kjappelbaum/oximachinerunner.git
Latest stable release
pip install oximachinerunner
Note that the installation will require significant (>500 MB) storage space since the ensembles use k-nearest neighbors models.
Usage
Note that since version 1 the models are no longer shipped with the PyPi package. There is a dedicated function to download the models, which has to be run before the first use. Also, in contrast to version 0, the interface is now object-oriented
from oximachinerunner import OximachineRunner
runner = OximachineRunner()
runner.run_oximachine('oximachinerunner/assets/ACODAA.cif')
The function will print for how many sites it will run the model.
It will return a OrderedDict
with:
- A list of oxidation state predictions
- A list of indices of the metal sites
- Strings indicating the metal
- The predictions of the base estimators
- The estimated probabilites
The OximachineRunner
can be initialized with a modelname. To view which models are available in the current release, use runner.available_models
. By default, models will be automatically downloaded if there are not yet in the correct folder. You should output as follows
/Users/kevinmaikjablonka/opt/miniconda3/envs/test_oximachine_runner/lib/python3.7/site-packages/oximachinerunner/assets/all_202000830/classifier.joblib are not exist or md5 is wrong.
Download file from https://www.dropbox.com/s/lc2z4abaycjbbe1/classifier.joblib?dl=1
2.9% of 527.44M
If you want to turn this behavior of, you can set OximachineRunner(automatic_download=False)
. If you then need a model, you can manually download it using a function from the utils
module.
The run_oximachine
function accepts pymatgen.Structure
, ase.Atoms
and str
as well as os.PathLike
. Latter two are expected to be filepaths to a file that is then parsed with pymatgen
.
Reference
Jablonka, Kevin Maik; Ongari, Daniele; Moosavi, Seyed Mohamad; Smit, Berend (2020): Using Collective Knowledge to Assign Oxidation States. ChemRxiv. Preprint. https://doi.org/10.26434/chemrxiv.11604129.v1
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