oximachinerunner

oximachine for AiiDA lab: Core functionalities of oximachine with stripped dependencies.

Warning: This model works excellent on a test set but it might give fully unphysical predictions in some cases when it is used outside the domain of applicability (structures similar to the ones in the MOF subset of the CSD). This is currently estimated with an uncertainty vote. Consider it in alpha phase

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+git@github.com:kjappelbaum/oximachinerunner.git

Latest stable release

pip install oximachinerunner

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 tuple with three elements:

• A list of oxidation states
• A list of indices of the metal sites
• Strings indicating the metal

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.