The latest version of evoMPS can be downloaded from GitHub <http://github.com/amilsted/evoMPS>.
On Windows, an easy way to obtain everything required is to download and install a numerics-oriented Python distribution such as
- pythonxy <http://www.pythonxy.com> (open source and a free download of 32-bit binaries)
- enthought python distribution <http://www.enthought.com/products/epd.php> (free for academic use, with optimized linear algerba, 64-bit available)
The full installation of either of these includes everything you need. Otherwise, the following are required:
- Python 2 <http://www.python.org> (tested on Python 2.7)
- Numpy <http://numpy.scipy.org> (tested on 1.6.1)
- Scipy <http://www.scipy.org> (version 0.7.0 or newer - tested on 0.10)
Numpy should be compiled with a LAPACK library, preferably an optimized one such as ATLAS <http://math-atlas.sourceforge.net/>. Scipy requires a LAPACK library to be present.
If present, Cython <http://www.cython.org/> will also be used to perform some (currently minor) optimizations.
To run the included examples, the following is also required:
- matplotlib <http://matplotlib.sourceforge.net/> (tested on 1.1.0)
To install the evoMPS package, go to the source directory and run:
python setup.py install
Alternatively, to install for the current user only, run:
python setup.py install --user
Installation is not strictly necessary, as scripts using evoMPS can also be run from the base source directory.
Examples have been provided in the examples/ subdirectory. After installing evoMPS as described above, they can be run using e.g.:
python transverse_ising.py
To run an example without installing, copy it to the base source directory first.