Bayesian particle filtering for parameter estimation in quantum information applications.
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.
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.
If using Anaconda, you should go ahead now and install from their repository all the dependencies that we can. If you are using “regular”-Python then you can ignore this step. Replace python=3.5 with your version (typically either 2.7 or 3.5).
$ conda install python=3.5 numpy scipy matplotlib scikit-learn
If you are not using Anaconda, but are instead using “regular”-Python, and you are on Linux, you will need the Python development package:
$ sudo apt-get install python-dev
Where python-dev might be python3.5-dev depending on your package manager and which version of Python you are using.
The latest release of QInfer can now be installed from PyPI with pip:
$ pip install qinfer
Alternatively, QInfer can be installed using pip and Git. Ensure that you have Git installed. On Windows, we suggest the official Git downloads. Once Anaconda and Git are installed, simply run pip to install QInfer:
$ pip install git+https://github.com/QInfer/python-qinfer.git
Lastely, QInfer can be installed manually by downloading from GitHub, then running the provided installer:
$ git clone email@example.com:QInfer/python-qinfer.git $ cd python-qinfer $ pip install -r requirements.txt $ python setup.py install
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
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.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.