Metadata-Version: 1.1
Name: QInfer
Version: 1.0b4
Summary: Bayesian particle filtering for parameter estimation in quantum information applications.
Home-page: https://github.com/QInfer/python-qinfer
Author: Chris Granade and Chris Ferrie
Author-email: cgranade@cgranade.com
License: http://www.gnu.org/licenses/agpl-3.0.en.html
Download-URL: https://github.com/QInfer/python-qinfer/archive/v1.0b1.tar.gz
Description: =================
        Welcome to QInfer
        =================
        
        .. image:: https://zenodo.org/badge/19664/QInfer/python-qinfer.svg
           :target: https://zenodo.org/badge/latestdoi/19664/QInfer/python-qinfer
        
        .. image:: https://img.shields.io/badge/launch-binder-E66581.svg
            :target: http://mybinder.org/repo/qinfer/qinfer-examples
            :alt: Launch Binder
            
        .. image:: https://img.shields.io/pypi/v/QInfer.svg?maxAge=2592000
            :target: https://pypi.python.org/pypi/QInfer
            
        
        .. image:: https://travis-ci.org/QInfer/python-qinfer.svg?branch=master
            :target: https://travis-ci.org/QInfer/python-qinfer
        
        .. image:: https://coveralls.io/repos/github/QInfer/python-qinfer/badge.svg?branch=master
            :target: https://coveralls.io/github/QInfer/python-qinfer?branch=master 
        
        .. image:: https://codeclimate.com/github/QInfer/python-qinfer/badges/gpa.svg
           :target: https://codeclimate.com/github/QInfer/python-qinfer
           :alt: Code Climate
        
        **QInfer** is a library using Bayesian sequential Monte Carlo for quantum
        parameter estimation. Works with Python 2.7, 3.3, 3.4 and 3.5.
        
        Installing QInfer
        =================
        
        We recommend using **QInfer** with the
        `Anaconda distribution`_. Download and install
        Anaconda for your platform, either Python 2.7 or 3.5. We
        suggest using Python 3.5, but **QInfer**
        works with either. Next, ensure that you have Git installed. On Windows,
        we suggest the `official Git downloads <https://git-scm.com/downloads>`_.
        Once Anaconda and Git are installed, simply run ``pip`` to install **QInfer**::
        
            $ pip install git+https://github.com/QInfer/python-qinfer.git
        
        Alternatively, **QInfer** can be installed manually by downloading from GitHub,
        then running the provided installer::
        
            $ git clone git@github.com:QInfer/python-qinfer.git
            $ cd python-qinfer
            $ pip install -r requirements.txt
            $ python setup.py install
        
        More Information
        ================
        
        Full documentation for **QInfer** is
        `available on ReadTheDocs <http://python-qinfer.readthedocs.org/en/latest/>`_,
        or may be built locally by running the documentation
        build script in ``doc/``::
        
            $ cd /path/to/qinfer/doc/
            $ make html
            
        On Windows::
            
            C:\> cd C:\path\to\qinfer\
            C:\path\to\qinfer\> make.bat html
            
        The generated documentation can be viewed by opening
        ``doc/_build/html/index.html``.
        
        .. _Anaconda distribution: https://www.continuum.io/downloads
        .. _Sphinx: http://sphinx-doc.org/
        
Keywords: quantum,Bayesian,estimation
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Physics
