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
Description: 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
        
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
