Metadata-Version: 2.1
Name: ckbit
Version: 1.0.0
Summary: Kinetic Bayesian Inference
Home-page: https://github.com/VlachosGroup/ckbit
Author: Vlachos Research Group
Author-email: vlachos@udel.edu
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
Requires-Dist: numpy (>=1.16)
Requires-Dist: datetime
Requires-Dist: tabulate (>=0.8)
Requires-Dist: VUnits (>=0.0.3)
Requires-Dist: arviz (>=0.4)
Requires-Dist: pandas (>=0.25)
Requires-Dist: xlrd
Requires-Dist: openpyxl (>=3.0.0)
Requires-Dist: seaborn (>=0.9.0)
Requires-Dist: matplotlib (>=3.1)

Chemical Kinetic Bayesian Inference Toolbox (CKBIT)
===================================================

The **C**\hemical **K**\inetic **B**\ayesian **I**\nference
**T**\oolbox (CKBIT) is a Python library for applying
Bayesian inference to kinetic rate parameters developed
by the Vlachos Research Group at the University of Delaware.

Documentation
-------------
Documentation can be found at this webiste:
https://vlachosgroup.github.io/ckbit/

Examples
--------
There are examples of the code in the Github examples 
folder. The examples are provided in both Python scripts 
and in Jupyter notebooks. Ensure the accompanying Excel 
files are used as templates for data entry.

Developers
----------
Max Cohen (maxrc@udel.edu)

Dependencies
------------
* PyStan2: Interfaces with Stan for optimized Bayesian 
  inference computation - archieved repository
* Datetime: Measures computational runtime
* NumPy: Provides efficient array manipulation
* Pickle: Creates and stores portable, serialized 
  representations of Python objects for repeat model usage
* Hashlib: Interfaces to hash functions for naming stored 
  models
* Matplotlib: Visualizes data outputs
* Pandas: Interfaces with Excel for facile data processing 
  of inputs
* ArviZ: Provides specialized visualization of inference 
  outputs
* Vunits: Converts common physical units
* Tabulate: Generates tabulated displays of inference 
  outputs

Getting Started
---------------
See the installation html file in the docs folder 
for detailed instructions.

License
-------
This project is licensed under the MIT License - 
see the LICENSE file for details.

Contributing and Questions
--------------------------
If you have a suggestion, find a bug, or have a question,
please post to our Issues page on the Github.

Funding
-------
We acknowledge support by the RAPID manufacturing institute, 
supported by the Department of Energy (DOE) Advanced 
Manufacturing Office (AMO), award number DE-EE0007888-9.5. 
RAPID projects at the University of Delaware are also made 
possible in part by funding provided by the State of Delaware. 
The Delaware Energy Institute gratefully acknowledges the 
support and partnership of the State of Delaware in furthering 
the essential scientific research being conducted through the 
RAPID projects.

Special Thanks
--------------
* Dr. Jonathan Lym 
* Dr. Jeffrey Frey


