https://github.com/nlesc-nano/swan

Statistical models to predict new materials
https://github.com/nlesc-nano/swan

machine-learning material-science python quantum-chemistry

Last synced: 6 months ago
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Statistical models to predict new materials

• Host: GitHub
• URL: https://github.com/nlesc-nano/swan
• Owner: nlesc-nano
• License: apache-2.0
• Created: 2019-06-14T14:29:57.000Z (over 6 years ago)
• Default Branch: main
• Last Pushed: 2023-05-09T13:36:29.000Z (over 2 years ago)
• Last Synced: 2025-03-25T12:22:04.277Z (7 months ago)
• Topics: machine-learning, material-science, python, quantum-chemistry
• Language: Python
• Homepage:
• Size: 152 MB
• Stars: 14
• Watchers: 4
• Forks: 1
• Open Issues: 7
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.rst
  • Citation: CITATION.cff

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README

          

.. image:: https://github.com/nlesc-nano/swan/workflows/build%20with%20conda/badge.svg

   :target: https://github.com/nlesc-nano/swan/actions

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.. image:: https://readthedocs.org/projects/swan/badge/?version=latest

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Screening Workflows And Nanomaterials

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🦢 **Swan** is a Python pacakge to create statistical models using machine learning to predict molecular properties. See Documentation_.

🛠 Installation

===============

- Download miniconda for python3: miniconda_ (also you can install the complete anaconda_ version).

- Install according to: installConda_.

- Create a new virtual environment using the following commands:

  - ``conda create -n swan``

- Activate the new virtual environment

  - ``conda activate swan``

To exit the virtual environment type  ``conda deactivate``.

.. _dependecies:

Dependencies installation

-------------------------

- Type in your terminal:

  ``conda activate swan``

Using the conda environment the following packages should be installed:

- install RDKit_ and H5PY_:

  - `conda install -y -q -c conda-forge h5py rdkit`

- install Pytorch_ according to this_ recipe

- install `Pytorch_Geometric dependencies `_.

- install `DGL using conda `_

.. _installation:

Package installation

--------------------

Finally install the package:

- Install **swan** using pip:

  - ``pip install git+https://github.com/nlesc-nano/swan.git``

Now you are ready to use *swan*.

  **Notes:**

  - Once the libraries and the virtual environment are installed, you only need to type

    ``conda activate swan`` each time that you want to use the software.

.. _Documentation: https://swan.readthedocs.io/en/latest/

.. _miniconda: https://docs.conda.io/en/latest/miniconda.html

.. _anaconda: https://www.anaconda.com/distribution/#download-section

.. _installConda: https://conda.io/projects/conda/en/latest/user-guide/install/index.html

.. _Pytorch: https://pytorch.org

.. _RDKit: https://www.rdkit.org

.. _H5PY: https://www.h5py.org/

.. _this: https://pytorch.org/get-started/locally/