Welcome to QInfer
QInfer is a library using Bayesian sequential Monte Carlo for quantum parameter estimation.
Obtaining QInfer
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 git@github.com:csferrie/python-qinfer.git
Once obtained in this way, QInfer may be updated by pulling from GitHub:
$ git pull
Installing QInfer
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.
Dependencies
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.
More Information
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.