This is a work in progress.

This is an implementation of a MCMC for estimation and non-parametric deconvolution of galactic kinematics from hyperspectral data cubes.

It is a python 2.7 module designed to be flexible, reliable and fast. It has not been tested under python 3.x, but feel free to make it compatible !

(still not available)

Install deconv3d system-wide,

$ sudo pip install deconv3d

or just for you :

$ pip install --user deconv3d

Running one of the above commands will download and install the module on your system, as deconv3d is referenced on the official [python package index] (https://pypi.python.org).

(still not available)

Running python setup.py install should do the trick.

• astropy : http://www.astropy.org
• hyperspectral : https://pypi.python.org/pypi/hyperspectral
• matplotlib : https://pypi.python.org/pypi/matplotlib

• bottleneck : https://pypi.python.org/pypi/Bottleneck

Most of the usual packages can be installed system-wise from repositories.

python2.7 python-numpy python-astropy python-matplotlib

You can also install them via pip, it's your choice.

Optional.

deconv3d provides a MUSELineSpreadFunction class that depends on mpdaf.MUSE.LSF.

Follow [MPDAF install instructions] (http://urania1.univ-lyon1.fr/mpdaf/chrome/site/DocCoreLib/installation.html).

deconv3d also accepts MPDAF's Cubes as input.

Simply run nosetests -v --nocapture --nologcapture from project's root :

• -v is verbose
• --nocapture means print statements will print
• --nologcapture means logging statements will print

These options are not mandatory for the tests to pass, but they are useful.

If you don't have nose, you can either

$ apt-get install python-nose

or

$ pip install --user nose

Install sphinx :

$ apt-get install python-sphinx

Make your changes into the doc/source files.

Once its done, go to doc directory, run make html.

Get the sources.

Create a virtualenv with python 2.7 :

$ virtualenv venv2.7 -p /usr/bin/python2.7

Activate that virtualenv :

$ source venv2.7/bin/activate

Install dependencies :

$ pip install -r requirements.txt

You're ready to run the test-suite !

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