Greg Willden wrote:

Hello all,

The FAQ says if you want to help out drop you line. Here is my line:

I'm pretty new to numpy/scipy but I've been using Python for a while now. I have a long history of Matlab use but I'm gradually weaning myself.

I would like to contribute to this project by adding a few things to the docstrings that will help new people like myself get their bearings. I love Python and would really like to get really good with numpy/scipy/matplotlib.

Wonderful! Welcome!

I want to see more "See also:" portions on the end of the docstrings. This is something that Matlab does well that makes it easy to learn about new, related functions.

What is the best way for me to contribute?

This is a good way to start. If you want to start with actual code, we still have quite a ways to go with the "Statistics Review" that I started too long ago. http://projects.scipy.org/scipy/scipy/wiki/StatisticsReview There are plenty of bite-sized things to do in cleaning up scipy.stats .

Whom would I submit patches to? This list or an individual?

We use the Trac bug-tracking system for numpy and scipy. You will need to register accounts for them due to spammers. http://projects.scipy.org/scipy/numpy/register http://projects.scipy.org/scipy/scipy/register After you do that, click on "New Ticket" in the upper right-hand corner. Describe your changes and submit the ticket. After the ticket is created, there will be an "Attach file" button which you can use to add your patch. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco

Stefan van der Walt wrote:

Hi Robert

On Fri, Sep 29, 2006 at 11:19:28PM -0500, Robert Kern wrote:

...

This is a good way to start. If you want to start with actual code, we still have quite a ways to go with the "Statistics Review" that I started too long ago.

http://projects.scipy.org/scipy/scipy/wiki/StatisticsReview

There are plenty of bite-sized things to do in cleaning up scipy.stats .

I've been tempted to help with this, but I'm not sure I understand what "review" means exactly. When is a function sufficiently "reviewed" to close the ticket? Must it conform to new style numpy, must it be functionally accurate, functionally complete, or all of the above?

There is a checklist on that page that details the requirements for a function passing review. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco