<!--
<p align="center">
<img src="https://github.com/kjappelbaum/element-coder/raw/main/docs/source/logo.png" height="150">
</p>
-->
<h1 align="center">
element_coder
</h1>
<p align="center">
<a href="https://github.com/kjappelbaum/element-coder/actions?query=workflow%3ATests">
<img alt="Tests" src="https://github.com/kjappelbaum/element-coder/workflows/Tests/badge.svg" />
</a>
<a href="https://github.com/cthoyt/cookiecutter-python-package">
<img alt="Cookiecutter template from @cthoyt" src="https://img.shields.io/badge/Cookiecutter-python--package-yellow" />
</a>
<a href="https://pypi.org/project/element_coder">
<img alt="PyPI" src="https://img.shields.io/pypi/v/element_coder" />
</a>
<a href="https://pypi.org/project/element_coder">
<img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/element_coder" />
</a>
<a href="https://github.com/kjappelbaum/element-coder/blob/main/LICENSE">
<img alt="PyPI - License" src="https://img.shields.io/pypi/l/element_coder" />
</a>
<a href='https://element_coder.readthedocs.io/en/latest/?badge=latest'>
<img src='https://readthedocs.org/projects/element_coder/badge/?version=latest' alt='Documentation Status' />
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</p>
Encode chemical elements numerically and decode numerical representations of elements.
## 💪 Getting Started
```python
from element_coder import encode, decode
decode(encode('Si', 'mod_pettifor'), 'mod_pettifor')
>'Si'
```
### Command Line Interface
The `element_coder.encode` and `element_coder.decode` command line tools are automatically installed. They can
be used from the shell with the `--help` flag to show help:
```shell
$ element_coder.encode H
102
```
```shell
$ element_coder.decode 102
H
```
also works for vector-valued encodings
```shell
$ element_coder.decode 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 --property cgcnn
H
```
## 🚀 Installation
The most recent release can be installed from
[PyPI](https://pypi.org/project/element_coder/) with:
```bash
$ pip install element_coder
```
The most recent code and data can be installed directly from GitHub with:
```bash
$ pip install git+https://github.com/kjappelbaum/element-coder.git
```
To install in development mode, use the following:
```bash
$ git clone git+https://github.com/kjappelbaum/element-coder.git
$ cd element-coder
$ pip install -e .
```
## Background
For some applications (of ML in chemistry) elements must be numerically encoded. There are many libraries that do that. For most applications, even [pymatgen](www.pymatgen.org) can get the job done:
```python
from pymatgen.core import Element
def encode_element(element: Element, property: str):
return getattr(element, property)
```
However, this code has some issues, wherefore there are many other libraries that attempt to solve this issue including [mendeleev](https://github.com/lmmentel/mendeleev), [elementy](https://github.com/Robert-Forrest/elementy), [EIMD](https://github.com/lrcfmd/ElMD). However,
* none of these libraries supported all the properties I was interested in
* none of these libraries supported decoding of descriptors into Elements.
## 👐 Contributing
Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See
[CONTRIBUTING.rst](https://github.com/kjappelbaum/element-coder/blob/master/CONTRIBUTING.rst) for more information on getting involved.
## 👋 Attribution
### ⚖️ License
The code in this package is licensed under the MIT License.
<!--
### 📖 Citation
Citation goes here!
-->
<!--
### 🎁 Support
This project has been supported by the following organizations (in alphabetical order):
- [Harvard Program in Therapeutic Science - Laboratory of Systems Pharmacology](https://hits.harvard.edu/the-program/laboratory-of-systems-pharmacology/)
-->
<!--
### 💰 Funding
This project has been supported by the following grants:
| Funding Body | Program | Grant |
| ------------ | ----------------------------------------------------------------------------------------------------------------------------- | ------------- |
| DARPA | [Automating Scientific Knowledge Extraction (ASKE)](https://www.darpa.mil/program/automating-scientific-knowledge-extraction) | HR00111990009 |
-->
### 🍪 Cookiecutter
This package was created with [@audreyfeldroy](https://github.com/audreyfeldroy)'s
[cookiecutter](https://github.com/cookiecutter/cookiecutter) package using [@cthoyt](https://github.com/cthoyt)'s
[cookiecutter-snekpack](https://github.com/cthoyt/cookiecutter-snekpack) template.
## 🛠️ For Developers
<details>
<summary>See developer instrutions</summary>
The final section of the README is for if you want to get involved by making a code contribution.
### ❓ Testing
After cloning the repository and installing `tox` with `pip install tox`, the unit tests in the `tests/` folder can be
run reproducibly with:
```shell
$ tox
```
Additionally, these tests are automatically re-run with each commit in a [GitHub Action](https://github.com/kjappelbaum/element-coder/actions?query=workflow%3ATests).
### 📦 Making a Release
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:
```shell
$ tox -e finish
```
This script does the following:
1. Uses BumpVersion to switch the version number in the `setup.cfg` and
`src/element_coder/version.py` to not have the `-dev` suffix
2. Packages the code in both a tar archive and a wheel
3. Uploads to PyPI using `twine`. Be sure to have a `.pypirc` file configured to avoid the need for manual input at this
step
4. Push to GitHub. You'll need to make a release going with the commit where the version was bumped.
5. 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.
</details>
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They can\nbe used from the shell with the `--help` flag to show help:\n\n```shell\n$ element_coder.encode H\n102\n```\n\n```shell\n$ element_coder.decode 102\nH\n```\n\nalso works for vector-valued encodings\n\n```shell\n$ element_coder.decode 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 --property cgcnn\nH\n```\n\n## \ud83d\ude80 Installation\n\n\nThe most recent release can be installed from\n[PyPI](https://pypi.org/project/element_coder/) with:\n\n```bash\n$ pip install element_coder\n```\n\nThe most recent code and data can be installed directly from GitHub with:\n\n```bash\n$ pip install git+https://github.com/kjappelbaum/element-coder.git\n```\n\nTo install in development mode, use the following:\n\n```bash\n$ git clone git+https://github.com/kjappelbaum/element-coder.git\n$ cd element-coder\n$ pip install -e .\n```\n\n## Background\nFor some applications (of ML in chemistry) elements must be numerically encoded. There are many libraries that do that. For most applications, even [pymatgen](www.pymatgen.org) can get the job done: \n\n```python\nfrom pymatgen.core import Element\ndef encode_element(element: Element, property: str): \n return getattr(element, property)\n```\n\nHowever, this code has some issues, wherefore there are many other libraries that attempt to solve this issue including [mendeleev](https://github.com/lmmentel/mendeleev), [elementy](https://github.com/Robert-Forrest/elementy), [EIMD](https://github.com/lrcfmd/ElMD). However, \n\n* none of these libraries supported all the properties I was interested in \n* none of these libraries supported decoding of descriptors into Elements.\n\n## \ud83d\udc50 Contributing\n\nContributions, whether filing an issue, making a pull request, or forking, are appreciated. See\n[CONTRIBUTING.rst](https://github.com/kjappelbaum/element-coder/blob/master/CONTRIBUTING.rst) for more information on getting involved.\n\n## \ud83d\udc4b Attribution\n\n### \u2696\ufe0f License\n\nThe code in this package is licensed under the MIT License.\n\n<!--\n### \ud83d\udcd6 Citation\n\nCitation goes here!\n-->\n\n<!--\n### \ud83c\udf81 Support\n\nThis project has been supported by the following organizations (in alphabetical order):\n\n- [Harvard Program in Therapeutic Science - Laboratory of Systems Pharmacology](https://hits.harvard.edu/the-program/laboratory-of-systems-pharmacology/)\n\n-->\n\n<!--\n### \ud83d\udcb0 Funding\n\nThis project has been supported by the following grants:\n\n| Funding Body | Program | Grant |\n| ------------ | ----------------------------------------------------------------------------------------------------------------------------- | ------------- |\n| DARPA | [Automating Scientific Knowledge Extraction (ASKE)](https://www.darpa.mil/program/automating-scientific-knowledge-extraction) | HR00111990009 |\n-->\n\n### \ud83c\udf6a Cookiecutter\n\nThis package was created with [@audreyfeldroy](https://github.com/audreyfeldroy)'s\n[cookiecutter](https://github.com/cookiecutter/cookiecutter) package using [@cthoyt](https://github.com/cthoyt)'s\n[cookiecutter-snekpack](https://github.com/cthoyt/cookiecutter-snekpack) template.\n\n## \ud83d\udee0\ufe0f For Developers\n\n<details>\n <summary>See developer instrutions</summary>\n\n \nThe final section of the README is for if you want to get involved by making a code contribution.\n\n### \u2753 Testing\n\nAfter cloning the repository and installing `tox` with `pip install tox`, the unit tests in the `tests/` folder can be\nrun reproducibly with:\n\n```shell\n$ tox\n```\n\nAdditionally, these tests are automatically re-run with each commit in a [GitHub Action](https://github.com/kjappelbaum/element-coder/actions?query=workflow%3ATests).\n\n### \ud83d\udce6 Making a Release\n\nAfter installing the package in development mode and installing\n`tox` with `pip install tox`, the commands for making a new release are contained within the `finish` environment\nin `tox.ini`. 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