Metadata-Version: 2.1
Name: probnum
Version: 0.1.2
Summary: Probabilistic Numerics in Python.
Home-page: https://github.com/probabilistic-numerics/probnum
Author: ProbNum Authors
Author-email: 
License: MIT
Description: # <a href="https://probnum.readthedocs.io"><img align="left" src="https://raw.githubusercontent.com/probabilistic-numerics/probnum/master/docs/source/img/pn_logo.png" alt="probabilistic numerics" width="64" style="padding-right: 10px; padding left: 10px;" title="Probabilistic Numerics in Python"/></a> ProbNum
        
        [![Build Status](https://img.shields.io/travis/probabilistic-numerics/probnum/master.svg?logo=travis%20ci&logoColor=white&label=Travis%20CI)](https://travis-ci.com/github/probabilistic-numerics/probnum)
        [![Coverage Status](https://img.shields.io/codecov/c/gh/probabilistic-numerics/probnum/master?label=Coverage&logo=codecov&logoColor=white)](https://codecov.io/gh/probabilistic-numerics/probnum/branch/master)
        [![Documentation](https://img.shields.io/readthedocs/probnum.svg?logo=read%20the%20docs&logoColor=white&label=Documentation)](https://probnum.readthedocs.io)
        [![Benchmarks](http://img.shields.io/badge/Benchmarks-asv-blueviolet.svg?style=flat&logo=swift&logoColor=white)](https://probabilistic-numerics.github.io/probnum-benchmarks/benchmarks/)
        [![PyPI](https://img.shields.io/pypi/v/probnum?label=PyPI&logo=pypi&logoColor=white)](https://pypi.org/project/probnum/)
        
        ---
        
        **ProbNum implements probabilistic numerical methods in Python.** Such methods solve numerical problems from linear
        algebra, optimization, quadrature and differential equations using _probabilistic inference_. This approach captures 
        uncertainty arising from _finite computational resources_ and _stochastic input_. 
        
        ---
        
        [Probabilistic Numerics](http://probabilistic-numerics.org/) (PN) aims to quantify uncertainty arising from 
        intractable or incomplete numerical computation and from stochastic input using the tools of probability theory. The 
        vision of probabilistic numerics is to provide well-calibrated probability measures over the output of a numerical 
        routine, which then can be propagated along the chain of computation.
        
        ## Installation
        To get started install ProbNum using `pip`.
        ```bash
        pip install probnum
        ```
        Alternatively, you can install the latest version from source.
        ```bash
        pip install git+https://github.com/probabilistic-numerics/probnum.git
        ```
        
        > Note: This package is currently work in progress, therefore interfaces are subject to change.
        
        ## Documentation and Examples
        For tips on getting started and how to use this package please refer to the
        [**documentation**](https://probnum.readthedocs.io). It contains a [quickstart guide](https://probnum.readthedocs.io/en/latest/introduction/quickstart.html) and Jupyter notebooks illustrating the basic usage of implemented probabilistic numerics routines.
        
        ## Package Development
        This repository is currently under development and benefits from contribution to the code, examples or documentation.
        Please refer to the [contribution guidelines](https://probnum.readthedocs.io/en/latest/development/contributing.html) before
        making a pull request.
        
        A list of core contributors to ProbNum can be found
        [here](https://probnum.readthedocs.io/en/latest/development/code_contributors.html).
        
        ## License and Contact
        This work is released under the [MIT License](https://github.com/probabilistic-numerics/probnum/blob/master/LICENSE.txt).
        
        Please submit an [issue on GitHub](https://github.com/probabilistic-numerics/probnum/issues/new) to report bugs or
        request changes.
        
Keywords: probabilistic-numerics
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: testing
