QInfer 1.0

Creator: bradpython12

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Description:

QInfer 1.0

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.
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 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,
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.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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