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DESCENT | ||
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[](https://github.com/simonboothroyd/descent/actions/workflows/ci.yaml) | ||
[](https://lgtm.com/projects/g/SimonBoothroyd/descent/context:python) | ||
[](https://codecov.io/gh/simonboothroyd/descent/branch/main) | ||
[](https://opensource.org/licenses/MIT) | ||
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Optimize force field parameters against QC data using `pytorch`. | ||
The `descent` framework aims to offer a modern API for training classical force field parameters (either from a | ||
traditional format such as SMIRNOFF or from some ML model) against reference data using `pytorch`. | ||
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**Warning:** This code is currently experimental and under active development. If you are using this code, | ||
be aware that it is not guaranteed to provide the correct results, and the API can change without notice. | ||
***Warning**: This code is currently experimental and under active development. If you are using this it, please be | ||
aware that it is not guaranteed to provide correct results, the documentation and testing maybe be incomplete, and the | ||
API can change without notice.* | ||
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## Installation | ||
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The package and its dependencies can be installed into a new conda environment using the `conda` package manager: | ||
This package can be installed using `conda` (or `mamba`, a faster version of `conda`): | ||
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```shell | ||
conda env create --name descent --file devtools/conda-envs/meta.yaml | ||
mamba install -c conda-forge descent | ||
``` | ||
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The example notebooks further require you install `jupyter`: | ||
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```shell | ||
mamba install -c conda-forge jupyter | ||
``` | ||
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## Getting Started | ||
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Examples for using this framework can be found in the [`examples`](examples) directory. | ||
To get started, see the [examples](examples). | ||
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## Development | ||
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A development conda environment can be created and activated by running: | ||
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```shell | ||
make env | ||
conda activate descent | ||
``` | ||
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The environment will include all example and development dependencies, including linters and testing apparatus. | ||
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Unit / example tests can be run using: | ||
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```shell | ||
make test | ||
``` | ||
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The codebase can be formatted by running: | ||
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```shell | ||
make format | ||
``` | ||
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or checked for lint with: | ||
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```shell | ||
make lint | ||
``` | ||
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## License | ||
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The main package is release under the [MIT license](LICENSE). | ||
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### Copyright | ||
## Copyright | ||
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Copyright (c) 2021, Simon Boothroyd | ||
Copyright (c) 2023, Simon Boothroyd |