Metadata-Version: 1.2
Name: chemreps
Version: 0.0.3
Summary: Molecular machine learning representations
Home-page: https://github.com/dlf57/chemreps
Maintainer: Dakota Folmsbee, Amanda Dumi, Shiv Upadhyay
Maintainer-email: dfolmsbee@gmail.com, amandaedumi@gmail.com, shivnupadhyay@gmail.com
License: MIT License
Description: # chemreps
        [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        
        chemreps is a Python package for the creation of molecular representations for the purpose of machine learning. The molecular representations included in this library are implemented/adapted from current literature. The aim of chemreps is to provide an easy to use library for making molecular representations that can be then used with machine learning packages such as Scikit-Learn and Tensorflow.
        
        ## Current Implementations
        - Coulomb Matrix
        - Bag of Bonds
        - Bonds/Nonbonding, Angles, Torsions
        - Just Bonds
        
        The citations for the literature from which the representations are implemented/adapted from can be found in the source code for each representation.
        
        ## Representation requests
        Requests for new representations to be added can be made by raising an issue and labeling it as a feature request. Before requesting a new representation, please check under the Representation project in the Projects tab to see if that representation is included in the current work or progress.
        
        ## Install
        The latest release version can be installed with:  
        ```
        pip install chemreps
        ```
        
        The latest development version can be installed by:
        ```
        git clone https://github.com/dlf57/chemreps
        cd chemreps
        pip install -e .
        ```
        
        #### Dependencies
        chemreps requires:
        - Python
        - NumPy (>=1.12)
        - cclib (>=1.5)
        
        ## Contributing
        If you are interested in helping develop for this project, please check out [Contributing to chemreps](https://github.com/dlf57/chemreps/wiki/Contributing-to-chemreps) in the wiki for a guide on how how to get started.
        
        ## Disclaimers:
        - These are attempts at the recreation of molecular representations from literature and may not be implemented properly.
            - If we do not implement something properly, feel free to make an issue.
        - This is solely a representation library and will not perform machine learning.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Chemistry
