[SciPy-user] SciPy 2005 - thanks, accolades and suggestions

Simon Hook simon.j.hook at jpl.nasa.gov
Sun Sep 25 12:45:50 CDT 2005


Many thanks to Enthought and all the speakers/developers for putting on 
an excellent SciPy 2005. As a someone who is  fairly new to both Python 
and SciPy, I found this a tremendous opportunity to learn more about 
what can be done with Python for scientific computing (just about 
everything!).

At the meeting there was a request for suggestions on how increase the 
usability and audience. Here are more thoughts:

1. The Enthought distribution of Python (Enthon) which includes many of 
the scientific packages, tested to make sure they work together is 
extremely valuable to someone like me who does not know what tools are 
out there and does not want to do dozens of downloads and installs only 
to find that package "a" conflicts with "b". I realize that such a 
distribution is a significant contribution and I would be happy to pay a 
modest sum for such a package. If someone puts together such a package 
please make the payment easy - i..e. credit card over the net. If you 
work in/with government there are certain methods that are 
straighforward to pay for stuff and others that require much more 
paperwork, e.g. check, paypal, ebay. The best method is credit card over 
the net. Given the rapid rate of improvement, another approach might be 
to buy the first distribution, then get free new distributions for a 
year and then buy the next distribution. Note setting up service 
contracts is also a hassle so better to have a new distribution to buy 
once per year or so.

2. I would like to suggest the following packages be added to the Enthon 
distribution:
mxtime (www.egenix.com)
ipython (ipython.scipy.org)
matplotlib (matplotlib.sourceforge.net)
inotebook (shown at scipy - not sure where to download)
vision (www.scripps.edu/~sanner/python/viper)

3. Many of the packages have excellent tutorials but they are package 
centric. What I mean by this is instead of taking a scientific problem 
and showing how you solve it, each package carefully describes its 
capabilities largely in isolation. It would be great if there was a 
simple tutorial(s) that tried to show how the tools could be used 
together. For example, say you want to read in some air temperature 
data, produce a plot of the data, create and fit a model to the data, 
generate an inotebook and then create a vision type model to interact 
with the data - you would have to know about all the packages and have 
read all the tutorials for each of the packages - too much time would be 
spent on the tools and not enough on the problem. Incidentally there is 
an example of something headed along these lines in the scipy tutorial. 
I am happy to help try and put something like this together, perhaps it 
could be a tutorial, perhaps a book - it would benefit from help from 
each of the people developing the different packages. On that note it 
would be nice if the package tutorials were on the scipy site under docs 
and if package developers called their guides "package-name_users_guide" 
rather than just "users_guide".

4. More examples. I find it much easier to follow examples than read 
manuals. It would be great if there were more user contributed examples 
in scipy. Matplotlib does an excellent job with examples. I just sent an 
example in on using read_array for scipy.

5. If there were some  tutorials  that showed how the tools could be 
used to solve scientific problems it  may be worthwhile trying to have a 
morning at scipy for new users that worked them through the tutorials.  
Alternatively these could be at science conferences. In my research 
area, before a conference starts there are usually classes which people 
pay for that teach them new tools.  The classes tend to be geared 
towards a particular research area, in my case geologic remote sensing. 
I have run a few classes and it would be good way to introduce students 
to scipy+ in the context of what they need to do.

Again many thanks again to the organizers, developers and presenters.

Simon

-- 

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Simon J. Hook, MSc, PhD
Jet Propulsion Laboratory  
MS 183-501
Pasadena, CA 91109
Office: 818-354-0974
Fax: 818-354-0966
Email: simon.j.hook at jpl.nasa.gov
http://asterweb.jpl.nasa.gov
http://masterweb.jpl.nasa.gov
http://laketahoe.jpl.nasa.gov
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