Featurizing metal-organic frameworks (MOFs) made simple! This package builds on the power of matminer to make featurization of MOFs as easy as possible. Now, you can use features that are mostly used for porous materials in the same way as all other matminer featurizers. mofdscribe additionally includes routines that help with model validation.
from mofdscribe.featurizers.chemistry import RACS
from pymatgen.core import Structure
structure = Structure.from_file(<my_cif.cif>)
featurizer = RACS()
racs_features = featurizer.featurize(structure)
While we are in the process of trying to make mofdscribe work on all operating system (we're waiting for conda recipies getting merged), it is currently not easy on Windows (and there might be potential issues on ARM-based Macs). For this reason, we recommend installing mofdscribe on a UNIX machine.
To install in development mode, use the following:
git clone git+https://github.com/kjappelbaum/mofdscribe.git
cd mofdscribe
pip install -e .
if you want to use all utilities, you can use the all
extra: pip install -e ".[all]"
We depend on many other external tools. Currently, you need to manually install these dependencies (due to pending merges for conda-recipies):
# RASPA and Zeo++ (if you want to use energy grid/Henry coefficient and pore descriptors)
conda install -c conda-forge raspa2 zeopp-lsmo
# cgal dependency for moltda (if you want to use persistent-homology based features)
# on some systems, you might need to replace this with sudo apt-get install libcgal-dev or brew install cgal
conda install -c conda-forge cgal dionysus
# openbabel dependency for moffragmentor (if you want to use SBU-centered features)
conda install -c conda-forge openbabel
Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.rst for more information on getting involved.
The code in this package is licensed under the MIT License.
See the ChemRxiv preprint.
@article{Jablonka_2022,
doi = {10.26434/chemrxiv-2022-4g7rx},
url = {https://doi.org/10.26434%2Fchemrxiv-2022-4g7rx},
year = 2022,
month = {sep},
publisher = {American Chemical Society ({ACS})},
author = {Kevin Maik Jablonka and Andrew S. Rosen and Aditi S. Krishnapriyan and Berend Smit},
title = {An ecosystem for digital reticular chemistry}
}
The research was supported by the European Research Council (ERC) under the European Unionβs Horizon 2020 research and innovation programme (grant agreement 666983, MaGic), by the NCCR-MARVEL, funded by the Swiss National Science Foundation, and by the Swiss National Science Foundation (SNSF) under Grant 200021_172759.
This package was created with @audreyfeldroy's cookiecutter package using @cthoyt's cookiecutter-snekpack template.
See developer instructions
The final section of the README is for if you want to get involved by making a code contribution.
After cloning the repository and installing tox
with pip install tox
, the unit tests in the tests/
folder can be
run reproducibly with:
tox
Additionally, these tests are automatically re-run with each commit in a GitHub Action.
After installing the package in development mode and installing
tox
with pip install tox
, the commands for making a new release are contained within the finish
environment
in tox.ini
. Run the following from the shell:
tox -e finish
This script does the following:
- Uses BumpVersion to switch the version number in the
setup.cfg
andsrc/mofdscribe/version.py
to not have the-dev
suffix - Packages the code in both a tar archive and a wheel
- Uploads to PyPI using
twine
. Be sure to have a.pypirc
file configured to avoid the need for manual input at this step - Push to GitHub. You'll need to make a release going with the commit where the version was bumped.
- Bump the version to the next patch. If you made big changes and want to bump the version by minor, you can
use
tox -e bumpversion minor
after.