Before your first use, you may want to change the settings (on top of the file) to connect to your PostgreSQL server.
The script will create a table in your database, populate it with random groups of points, and then call the k-means algorithm on it. Finally, it will generate a PNG image, displaying the points and the centroids.
For a first run, use something like this:
./k-means_test.py --regen -o clustered_data.png
You can call "./k-means_test.py -h" for a list of available options.
In attachment are my script and an example of its output.
By the way, I'll have a lot of work next week, as I have several exams coming and a big project to do (about empirical orthogonal functions), so I'll probably be inactive for a few days! Then I'll be on holidays, so I will be able to focus on MADlib and GSoC :)
Regards,
Maxence
Very interesting! The results look encouraging,although this is on Python :)