swan

Statistical models to predict new materials

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

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Statistical models to predict new materials

README.rst

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#####################################
Screening Workflows And Nanomaterials
#####################################

🦢 **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/

Owner

Citation (CITATION.cff)

# YAML 1.2
---
title: "swan"
abstract: "Workflows and statistical models to predict numerical properties for nanomaterials"
authors:
  -
    family-names: Zapata
    given-names: Felipe
    orcid: "https://orcid.org/0000-0001-8286-677X"
  -
    family-names: Nicolas
    given-names: Renaud
    orcid: "https://orcid.org/0000-0001-9589-2694"
cff-version: 1.2.0
keywords:
  - "quantum-chemistry"
  - "materials-science"
  - "machine-learning"
license: "Apache-2.0"
message: "If you use this software, please cite it using these metadata."

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