Metadata-Version: 2.1
Name: distl
Version: 0.2.0
Summary: Simple Distributions: math operations, serializing, covariances
Home-page: https://www.github.com/kecnry/distl
Author: Kyle Conroy
Author-email: kyleconroy@gmail.com
License: UNKNOWN
Download-URL: https://github.com/kecnry/distl/tarball/0.2.0
Description: <p align="center"><a href="http://distl.readthedocs.io"><img src="./docs/images/distl.png" alt="distl logo" width="300px" align="center"/></a></p>
        
        <p align="center" style="text-align:center"><i>simplified and condensed distributions</i></p>
        
        <pre align="center" style="text-align:center; font-family:monospace; margin: 30px">
          pip install distl
        </pre>
        
        
        
        [![badge](https://img.shields.io/badge/github-kecnry%2Fdistl-blue.svg)](https://github.com/kecnry/distl)
        [![badge](https://img.shields.io/badge/pip-distl-lightgray.svg)](https://pypi.org/project/distl/)
        ![badge](https://img.shields.io/badge/python-2.7+%20%7C%203.6+-blue.svg)
        [![badge](https://img.shields.io/badge/license-GPL3-blue.svg)](https://github.com/kecnry/distl/blob/master/LICENSE)
        [![badge](https://travis-ci.com/kecnry/distl.svg?branch=master)](https://travis-ci.com/kecnry/distl)
        [![badge](https://img.shields.io/codecov/c/github/kecnry/distl)](https://codecov.io/gh/kecnry/distl)
        [![badge](https://readthedocs.org/projects/distl/badge/?version=latest)](https://distl.readthedocs.io/en/latest/?badge=latest)
        
        
        **IMPORTANT**: **distl** is currently still under development, is not yet well-tested, and is subject to significant API changes.  Please keep posted until an official release is ready.
        
        Read the [latest documentation on readthedocs](https://distl.readthedocs.io) or [browse the current documentation](./docs/index.md).
        
        **distl** provides a python object-interface on top of several distribution (random variable) functions in [scipy.stats](https://docs.scipy.org/doc/scipy/reference/stats.html) and allows for:
        
          - serialization of distributions (so they can be saved to disk or pickled and sent to processors within MPI)
          - support for units and wrapping
          - conversion between different types of distributions
          - math between distributions, handling covariances from multivariate distributions wherever possible
          - plotting convenience functions
        
        ## Getting Started
        
        ### Dependencies
        
        **distl** requires the following dependencies:
        
          - python 2.7+ or 3.6+
          - scipy 1.0+
          - numpy 1.10+
        
        
        and the following optional dependencies:
        
          - matplotlib 2.2+ (required for plotting distributions)
          - [corner](https://corner.readthedocs.io) (required for plotting multivariate distributions and distribution collections)
          - astropy 1.0+ (required for units support)
          - dill (required for saving/loading Function distributions)
        
        
        You can see the [Travis testing matrix](https://travis-ci.com/kecnry/distl) for
        details on what exact versions have been tested and ensured to work.  If you run
        into any issues with dependencies, please [submit an issue](https://github.com/kecnry/distl/issues/new).
        
        ### Installation
        
        To install the latest release via pip:
        
        ```sh
        pip install distl
        ```
        
        To install from source locally for a single user:
        
        ```sh
        python setup.py build
        python setup.py install --user
        ```
        
        Or to install globally:
        
        ```sh
        python setup.py build
        sudo python setup.py install
        ```
        
        ### Import
        
        Now from within python we can import the `distl` package:
        
        ```py
        import distl
        ```
        
        and then create, sample from, and plot our first distribution:
        
        ```py
        g = distl.gaussian(10, 1)
        print(g.sample())
        print(g.sample(10))
        g.plot(show=True)
        ```
        
        ## Documentation and API Docs
        
        Read the [latest documentation on readthedocs](https://distl.readthedocs.io) or [browse the current documentation](./docs/index.md).
        
        ## Contributors
        
        [Kyle Conroy](https://github.com/kecnry)
        
        Contributions are welcome!  Feel free to file an issue or fork and create a pull-request.
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
