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INSTALL
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INSTALL
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.. -*- rest -*-
.. vim:syntax=rest
====================
Download and Install
====================
This page covers the necessary steps to install and run RegReg. Below
is a list of required dependencies, along with additional software
recommendations.
RegReg is currently *ALPHA* quality, but is rapidly improving. If you are
trying to get some work done wait until we have a stable release. For now,
the code will primarily be of interest to developers.
Dependencies
------------
Must Have
^^^^^^^^^
Python_ 2.7 or later
NumPy_ 1.3 or later
SciPy_ 0.7 or later
Numpy and Scipy are high-level, optimized scientific computing libraries.
gcc_
The package does contain a few C extensions for optimized
routines. Therefore, you must have a compiler to build from
source. XCode_ (OSX) and MinGW_ (Windows) both include gcc. (*Once
we have binary packages, this requirement will not be necessary.*)
cython_ 0.11.1 or later
Cython is a language that is a fusion of Python and C. It allows us
to write fast code using Python and C syntax, so that it easier to
read and maintain. You need Cython if you are building the
development source code (and that is what you have to do at the
moment, because we don't yet have a release).
sklearn 0.14.1 or later
sklearn is a package containing many machine learning algorithms.
The selection code uses it to fit the LASSO.
mpmath 0.18 or later
mpmath is a library for arbitrary precision calculations.
We use high-precision versions of standard distributions
as we look at their truncated distribution.
pyinter 0.1.6 or later
pyinter is a lightweight package to manipulate
subsets of the real line.
regreg
regreg is a package to solve convex problems in composite form
using proximal gradient methods (http://github.com/regreg/regreg)
Strong Recommendations
^^^^^^^^^^^^^^^^^^^^^^
iPython_
Interactive python environment.
Matplotlib_
2D python plotting library.
Installing from binary packages
-------------------------------
Currently we do not have binary packages. Until we do, the easiest
installation method is to download the source tarball and follow the
:ref:`building_source` instructions below.
.. _building_source:
Building from source code
-------------------------
Unpack the source tarball and change into the source directory. Once in the
source directory, you can build the `selection` package within the code
directory using::
python setup.py build
To install, simply do::
sudo python setup.py install
.. note::
As with any Python_ installation, this will install the modules
in your system Python_ *site-packages* directory (which is why you
need *sudo*). Many of us prefer to install development packages in a
local directory so as to leave the system python alone. This is
mearly a preference, nothing will go wrong if you install using the
*sudo* method. To install in a local directory, use the **--prefix**
option. For example, if you created a ``local`` directory in your
home directory, you would install `selection` like this::
python setup.py install --prefix=$HOME/local