Merge pull request #2 from StephenSzwiec/dev

Dev

README.md

@@ -1,8 +1,69 @@
-# pyQSARplus
-Library of tools for the analysis of QSAR/QSPR datasets and models. 
+# qsarify
 
-# What is included?
------------------
+qsarify is a library of tools for the analysis of QSAR/QSPR datasets and models. This library is intended to be used to produce models which relate a set of calculated chemical descriptors to a given numeric endpoint. Many great tools will take the geometry or string data of a given chemical and compute **descriptors**, which are numeric measures of the properties of these, but you can generate some of these with another one of my scripts, [Free Descriptors](https://github.com/StephenSzwiec/free_descriptors).
 
-- Data preprocessing: `data_tools`
+# Dependencies
+
+- Python 3
+- [numpy](https://numpy.org/)
+- [pandas](https://pandas.pydata.org/)
+- [scikit-learn](https://scikit-learn.org)
+- [matplotlib](https://matplotlib.org)
+
+
+# Installation
+
+`pip install qsarify`
+
+# What is included right now?
+
+- Data preprocessing tools: `data_tools`
 - Dimensionality reduction via clustering: `clustering`
+- Feature selection:
+	- Single threaded: `feature_selection_single`
+	- Multi-threaded: `feature_selection_multi`
+- Model Export and Visualization: `model_export`
+- Cross Valiidation: `cross_validation`
+
+# How to use
+
+The best way to learn how to use this library is to look at the example notebook in the `examples` folder. This notebook will walk you through the workflow of using this library to build a QSAR model.
+
+# Future Plans
+
+- Massively parallel feature selection methods:
+	- CUDA acceleration
+	- MPI acceleration
+- Include Shannon Entropy as a dimensionality reduction metric in clustering
+- Embedded kernel methods
+- More visualization tools
+- More cross validation tools
+- Feature selection tools for categorical data
+
+# Contributing
+
+
+If you would like to contribute to this project, please feel free to fork this repository and submit a pull request. Otherwise, you may also submit an issue. I will try to respond to issues as quickly as possible.
+
+# License
+
+
+This project is licensed under the GNU GPLv3 license. See the LICENSE file for more details.
+
+# Citation
+
+If you use this library in your work, please cite it as follows:
+
+Szwiec, Stephen. (2023). qsarify: A high performance library for QSAR model development.
+
+BibTex:
+```
+@misc{szwiec2023qsarify,
+  author = {Szwiec, Stephen},
+  title = {qsarify: A high performance library for QSAR model development},
+  year = {2023},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\url{https://github.com/stephenszwiec/qsarify}},
+  }
+```