3. Installation

Dana is a python package and depends on a number of python components that can be easily installed (see instructions on respective homepages):

  • numpy, http://numpy.scipy.org

    NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

  • scipy, http://www.scipy.org

    SciPy is a collection of mathematical algorithms and convenience functions built on the Numpy extension for Python. It adds significant power to the interactive Python session by exposing the user to high-level commands and classes for the manipulation and visualization of data. With SciPy, an interactive Python session becomes a data-processing and system-prototyping environment rivaling sytems such as Matlab, IDL, Octave, R-Lab, and SciLab.

Optionaly, here are also some components and tools you might consider installing:

  • matplotlib, http://matplotlib.sourceforge.net

    matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python scripts, the python and ipython shell (ala matlab or mathematica), web application servers, and six graphical user interface toolkits.

  • IPython, http://ipython.scipy.org/moin/FrontPage

    The goal of IPython is to create a comprehensive environment for interactive and exploratory computing. To support, this goal, IPython has two main components: An enhanced interactive Python shell. An architecture for interactive parallel computing. All of IPython is open source (released under the revised BSD license). You can see what projects are using IPython here, or check out the talks and presentations we have given about IPython.

3.1. Using DANA in-place

Dana can be ran in-place without any installation and thus you might want to experiment first with dana before you install it on your development machine. To do this, add either the extracted dana source archive directory or the compressed runtime egg to your PYTHONPATH.

On Windows you can specify this from a command line:

set PYTHONPATH c:\path\to\dana\;%PYTHONPATH%

On Mac OS X, Linux or on Windows under cygwin using bash:

export PYTHONPATH=/path/to/dana/:$PYTHONPATH

or, using tcsh (or a variant):

setenv PYTHONPATH /path/to/dana/:$PYTHONPATH

If you have downloaded a runtime egg instead of the source archive, you would specify the filename of the egg in place of dana/.

3.2. Quick installation

If you have setuptools installed, you can install or upgrade to the latest version of dana using easy_install:

easy_install -U dana

On Mac OS X and Linux you may need to run the above as a priveleged user; for example:

sudo easy_install -U dana

3.3. Manual installation

To avoid having to set the PYTHONPATH for each session, you can install DANA into your personal Python’s site-packages directory if you have one. If you do not have one yet, you can create it anywhere on your disk and add this directory to your PYTHONPATH.

From a command prompt on Windows, change into the extracted dana source archive directory and type:

python setup.py install --prefix=C:\path\to\local\site-packages\;

On Mac OS X and Linux you will need to do the same:

sudo python setup.py install --prefix=/path/to/local/site-packages

Once installed you should be able to import dana from any terminal without setting the PYTHONPATH.

To make dana available to all users you can install it into your Python’s site-packages directory.

From a command prompt on Windows, change into the extracted dana source archive directory and type:

python setup.py install

On Mac OS X and Linux you will need to do the above as a priveleged user; for example using sudo:

sudo python setup.py install

3.4. Testing installation

Once you’ve installed DANA, it is very important you start the test procedure to check all is properly installed and function as expected. From a python shell, you can type:

>>> import dana
>>> dana.test()
Ran 149 tests in 2.950s

If an error is detected, you should save the output and file a bug report at: https://gforge.inria.fr/tracker/?group_id=628 giving your python, numpy and scipy versions:

>>> import sys, numpy, scipy
>>> print sys.version
2.7.1 (r271:86882M, Nov 30 2010, 10:35:34)
[GCC 4.2.1 (Apple Inc. build 5664)]
>>> print numpy.__version__
>>> print scipy.__version__
>>> print dana.__version__

Hopefully, some maintainer will take care of the problem and contact you if necessary.