QInfer is a library using Bayesian sequential Monte Carlo for quantum parameter estimation.

A stable version of QInfer has not yet been released. Until then, the latest version may always be obtained by cloning into the GitHub repository:

$ git clone [email protected]:csferrie/python-qinfer.git

Once obtained in this way, QInfer may be updated by pulling from GitHub:

$ git pull

QInfer provides a setup script, setup.py, for installing from source. On Unix-like systems, QInfer can be made available globally by running:

$ cd /path/to/qinfer/
$ sudo python setup.py install

On Windows, run cmd.exe, then run the setup script:

C:\> cd C:\path\to\qinfer\
C:\path\to\qinfer\> python setup.py install

Note that you may be prompted for permission by User Access Control.

QInfer depends on only a very few packages:

• Python 2.7 (may work with earlier, but not tested).
• NumPy and SciPy.
• [Optional] SciKit-Learn required for some advanced features.
• [Optional] Sphinx required to rebuild documentation.

On Windows, these packages can be provided by Python(x,y). Linux users may obtain the needed dependencies. Under Ubuntu:

$ sudo apt-get install python2.7 python-numpy python-scipy python-scikits-learn python-sphinx

On Fedora:

$ sudo yum install python numpy scipy python-sphinx
$ sudo easy_install -U scikit-learn

Alternatively, Enthought Python Distribution has been tested with QInfer, and may be used on Windows, Mac OS X or Linux.

Full documentation for QInfer is available on ReadTheDocs, 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.