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Project description
Hyper Shape recognition (HSR): a general framework for moment-based similarity measures
HSR is a versatile, moment-based similarity measure tailored for three-dimensional (3D) chemical representations annotated with atomic features. It enhances the robustness and versatility of the Ultrafast Shape Recognition (USR) method by incorporating multidimensional features for each atom, such as protons, neutrons, and formal charges.
Getting Started
Installing HSR
You can install HSR using either pip or conda:
pip install hsr
or
conda install hsr -c conda-forge
Build from source
Clone this repository on your machine. Move inside it and create the conda environment:
conda env create -f environment.yml
conda activate HSR_devel
Verify the correct creation of the environment by running:
pytest
To use HSR from CLI you can run:
python -m hsr.hsr_cli
If HSR is installed with pip or conda, the above command is replace by the simple use of hsr
Basic Usage
Run the folowing command to get help in using HSR from CLI:
hsr -h
For a detailed overview of HSR's methodology check our documentation.
Licensing
HSR is licensed under the GNU Affero General Public License Version 3. For more details, see the LICENSE file.
Citing HSR
If you use HSR in your research, please cite it as follows:
[TODO: Add citation]
Contributing
Contributions to HSR are welcome! Please read our Contributing Guidelines for information on how to get started.
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