Seeking help and support for next-gen math modeling tools using Python

R

Rob Clewley

Hi all, and apologies for a little cross-posting:

First, thanks to those of you who have used and contributed to the
PyDSTool math modeling environment [1]. This project has greatly
benefitted from the underlying platform of numpy / scipy / matplotlib
/ ipython. Going forward I have three goals, for which I would like
the urgent input and support of existing or potential users.

(i) I have ideas for expanding PyDSTool with innovative tools in my
research area, which is essentially for the reverse engineering of
complex mechanisms in multi-scale dynamic systems [2]. These tools
have already been prototyped and show promise, but they need a lot of
work.
(ii) I want to grow and develop the community of users who will help
drive new ideas, provide feedback, and collaborate on writing and
testing code for both the core and application aspects of PyDSTool.
(iii) The first two goals will help me to expand the scientific /
engineering applications and use cases of PyDSTool as well as further
sustain the project in the long-term.

I am applying for NSF funding to support these software and
application goals over the next few years [3], but the proposal
deadline is in just four weeks! If you are interested in helping in
any way I would greatly appreciate your replies (off list) to either
of the following queries:

I need to better understand my existing and potential users, many of
whom may not be registered on the sourceforge users list. Please tell
me who you are and what you use PyDSTool for. If you are not using it
yet but you’re interested in this area then please provide feedback
regarding what you would like to see change.

If you are interested in these future goals, even if you are not an
existing user but may be in the future, please write a brief letter of
support on a letterhead document that I will send in with the proposal
as PDFs. I have sample text that I can send you, as well as my draft
proposal’s introduction and specific aims. These letters can make a
great deal of difference during review.

Without funding, collaborators, user demand and community support,
these more ambitious goals for PyDSTool will not happen, although I am
committed to a basic level of maintenance. For instance, based on user
feedback I am about to release an Ubuntu-based Live CD [4] that will
allow users to try PyDSTool on any OS without having to install it.
PyDSTool will also acquire an improved setup procedure and will be
added to the NeuroDebian repository [5], among others. I am also
finalizing an integrated interface to CUDA GPUs to perform fast
parallel ODE solving [6].

Thanks for your time,
Rob Clewley

[1] http://pydstool.sourceforge.net
[2] http://www.ni.gsu.edu/~rclewley/Research/index.html, and in
particular http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002628
[3] NSF Software Infrastructure for Sustained Innovation (SI2-SSE)
program solicitation:
http://www.nsf.gov/pubs/2013/nsf13525/nsf13525.htm
[4] http://help.ubuntu.com/community/LiveCD
[5] http://neuro.debian.net/
[6] http://www.nvidia.com/object/cuda_home_new.html




--
Robert Clewley, Ph.D.
Assistant Professor
Neuroscience Institute and
Department of Mathematics and Statistics
Georgia State University
PO Box 5030
Atlanta, GA 30302, USA

tel: 404-413-6420 fax: 404-413-5446
http://neuroscience.gsu.edu/rclewley.html
 

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