Updated pip install requirements

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2020 Benjamin Shields
+Copyright (c) 2020 Benjamin J. Shields
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

LICENSE.txt

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2020 Benjamin J. Shields
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,32 +1,42 @@
 # edbo
-Experimental Design via Bayesian Optimization: *edbo* is a practical implimentaiton of Bayesian optimization for chemical synthesis.
+
+Experimental Design via Bayesian Optimization: *edbo* is a practical implementation of Bayesian optimization for chemical synthesis.
 
 **Reference:** Shields, Benjamin J.; Stevens, Jason; Li, Jun; Parasram, Marvin; Damani, Farhan, Janey, Jacob; Adams, Ryan P.; Doyle, Abigail G. "Bayesian Reaction Optimization as A Tool for Chemical Synthesis" Manuscript Submitted.
 
 **Documentation:** https://b-shields.github.io/edbo/index.html
 
 ## Installation
 
-**Requirements:**
-- anaconda
-- an internet connecton
-- a copy of install.sh
+(0) Create anaconda environment
+
+```
+conda create --name edbo python=3.7.5
+```
 
-0. Install conda (if you haven't already):
+(1) Install rdkit, Mordred, and PyTorch
 
-```bash
-https://docs.conda.io/projects/conda/en/latest/user-guide/install/
+```
+conda activate edbo
+conda install -c rdkit rdkit
+conda install -c rdkit -c mordred-descriptor mordred
+conda install -c pytorch pytorch=1.3.1
 ```
 
-1. Copy install.sh to desired directory (or just copy text into a new text file called install.sh):
+(2) Install EDBO
 
-2. Open a terminal (linux) or anaconda prompt (windows), navigate to the directory containing install.sh:
+```
+pip install edbo
+```
 
-```bash
-cd path/to/install.sh/directory
-sh install.sh
+### Running Notebooks
 
-# Note: if OS is Linux based you may need to chmod + install.sh
 ```
+conda install jupyterlab
+```
+
+### GPU Integration
 
-3. (optional) Test edbo. See tests directory for details.
+```
+conda install cudatookit=10.1, torchvision -c pytorch
+```

setup.cfg

@@ -0,0 +1,2 @@
+[metadata]
+description-file = README.md

setup.py

@@ -1,21 +1,34 @@
-from setuptools import setup, find_packages
+from setuptools import setup
 
 setup(
    name='edbo',
-   version='0.0.0',
-   author='Ben Shields',
-   packages=find_packages(),
-   url='https://github.com/b-shields/edbo.git',
-   license='LICENSE',
+   packages=['edbo'], 
+   version='0.1.0',
+   author='Benjamin J. Shields',
+   author_email='[email protected]',
+   url='https://github.com/b-shields/edbo',
+   download_url = 'https://github.com/b-shields/edbo/archive/edbo.tar.gz',
+   keywords=['Bayesian Optimization', 'Chemical Reaction Optimization'],
+   license='MIT',
    description='Experimental design via Bayesian optimization',
    install_requires=[
-        'pandas==0.25.3',
-        'numpy==1.17.4',
-        'pytorch==1.3.1',
+        'pandas',
+        'numpy',
+        'xlrd',
         'scikit-learn>=0.22.1',
         'matplotlib',
         'seaborn',
+        'dill',
         'gpytorch==1.0.0',
-        'pyclustering==0.9.3.1'
-    ]
+        'pyclustering==0.9.3.1',
+        'pyro-ppl==1.1',
+        'ipython', ###
+    ],
+   classifiers=[
+    'Development Status :: 3 - Alpha',
+    'Intended Audience :: Chemists', 
+    'Topic :: Bayesian Optimization :: Chemistry',
+    'License :: OSI Approved :: MIT License', 
+    'Programming Language :: Python :: 3.7',
+  ],
 )