SciPy09 Video page direct links

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SciPy09 Video page direct links

Eric S. Carlson
Hello,

I had some issues searching for SciPy 09 video files this morning.
Although the search was broken, at the same time it was still possible
to link directly to the video pages.

The attached basic html file (no javascript or images) has the tutorial
and conference schedule and direct links to corresponding videos. You
should be able to save the file and open locally.

Cheers,
Eric Carlson

SciPy 2009 Resources

Slides and data here

Introductory Tutorials (see bottom of this page for suggested pre-req's)

Morning:
8:30-10:20. Intro to Python: Gael Varoquaux, Christopher Burns
Quick IPython introduction: the workflow
Basic types:
scalar types: int, float, complex
Collections: list and dictionaries (and tuples, sets, ...)
Control flow: if, for, range, while, break, continue
Functions: definitions, arguments, docstrings, ...
10:20-10:40. Break.
10:40-12:30. Intro to Python (continued): Gael Varoquaux, Christopher Burns
Exceptions handling in Python
Reusing your code: creating modules, '__main__'.
Standalone scripts, command line arguments.
I/O, file handling
Standard library and general utilities.
Timing
Lunch break (on your own): 12:30-2:00.
Afternoon:
2:00-2:30. Debugging: Christopher Burns
effective strategies and effective debugger usage
print statements
%debug in IPython
2:30-3:00. Testing: Stefan van der Walt
the concept: using testing properties of code via a function
doctests
3:00-3:50. Basic numpy arrays: Stefan van der Walt
The array, an n-dimensional object
vectorizing for speed and ease
3:50-4:10. Break.
4:10-4:30. Basic plotting with matplotlib: Mike Droettboom
plotting 1D arrays: points and lines,
plotting 2D arrays: images
4:30-5:00. more numpy: Stefan van der Walt
The memory model
dtypes
views and copies
Array creation
5:00-6:00. Spill-over and Q & A session.
Wednesday
Morning:
8:00-8:30. Optional startup session where the organizers will try to assist with any last-minute setup or installation problems.
8:30-9:30. More matplotlib: Mike Droettboom
customizing colors, styles
legend
matplotlibrc
math text
9:30-10:20. More numpy: Perry Greenfield
advanced indexing
use of where
zen, examples of vectorizing
ieee special number and error handling (5 min)
masked arrays (10-15 min)
10:20-10:40. Break.
10:40-11:30. More numpy (continued) Perry Greenfield
11:30-12:00. Basic 3d plots with mlab: Gael Varoquaux
3D plotting functions
their keyword arguments
the GUI
Lunch break (on your own): 12:30-2:00.
Afternoon:
2:00-3:50. Using scipy for numerics: David Cournapeau, Eric Jones
Linear algebra
random numbers
FFT
special functions
Root finding
Quadrature
ODEs
3:50-4:10. Break.
4:10-5:30. The Whole Enchilada: Eric Jones
Largish assignment to tie all of the above together.
5:30-6:00. Q & A Session



Advanced Tutorials

Tuesday
Morning:
8:00-8:30. Optional startup session where the organizers will try to assist with any last-minute setup or installation problems.
8:30-10:20. Advanced numpy 1 and advanced numpy 2: Stefan van der Walt and David Cournapeau.
10:20-10:40. Break.
10:40-12:30. Advanced topics in matplotlib: John Hunter
Lunch break (on your own): 12:30-2:00.
Afternoon:
2:00-3:50. Symbolic computing with sympy: Ondrej Certik.
3:50-4:10. Break.
4:10-6:00. Statistics with Scipy: Robert Kern.

Wednesday
Morning:
8:00-8:30. Optional startup session where the organizers will try to assist with any last-minute setup or installation problems.
8:30-10:20. Cython: Dag Sverre Seljebotn.
10:20-10:40. Break.
10:40-12:30. Using GPUs with PyCUDA: Nicolas Pinto.
Lunch break (on your own): 12:30-2:00.
Afternoon:
2:00-3:50. Designing scientific interfaces with Traits: Enthought.
3:50-4:10. Break.
4:10-6:00. Mayavi/TVTK: Prabhu Ramachandran.


Conference

Thursday, August 20

9:00 - 9:10 Welcome (Jarrod Millman & Gael Varoquaux)

9:10 - 9:30 Update on the core projects (Charles Harrison, Fernando Perez, John Hunter, David Cournapeau)

9:30 - 10:30 Keynote: What to demand from a Scientific Computing Language -- Even if you don't care about computing or languages (Peter Norvig, Director of Research, Google)
BREAK (10:30 - 11:00)

11:00 - 11:10 nipy.timeseries: Neuroimaging time-series analysis (Ariel Rokem, UC Berkeley)

11:10 - 11:50 Virtual reality: a tool for the highly quantitative study of animal behavior (Andrew Straw, Caltech)

11:50 - 12:10 Parallel Kernels: An Architecture for Distributed Parallel Computing (Nikunj Patel, University of Maryland)

12:10 - 12:20 PaPy: Parallel and distributed data-processing pipelines in Python (Marcin Cieslik, University of Virginia)

12:20 - 12:30 High-Performance Code Generation Using CorePy (Andrew Friedley, Indiana University)
LUNCH (12:30 - 2:30) On your own.

2:30 - 3:00 Panel discussion (Python and Parallel computing, Michael Aivazis, Brian Granger, Nicolas Pinto, moderator: Gaël Varoquaux)

3:00 - 3:10 Sherpa: 1D/2D modeling and fitting in Python (Brian Refsdal, Harvard Smithsonian Center for Astrophysics)

3:10 - 3:20 Multiprocess System for Virtual Instruments in Python (Brian D'Urso, University of Pittsburgh)

3:20 - 3:30 ESPResSo++: A Python-controlled, Parallel Simulation Software for Soft Matter Research (Olaf Lenz, Max-Planck-Institute for polymer research, Mainz, Germany)
BREAK (3:30 - 4:00)

4:00 - 4:40 Sympy (Ondrej Certik, University of Nevada, Reno)

4:40 - 4:50 Python implementation of weno interpolation and reconstruction (Adrian Townsend, University of Washington)

4:50 - 5:00 Writing Safer NumPy Extensions in C++ with Templates and TooN (Damian Eads, University of California)

5:00 - 6:00 Lightning Talks
Talks 1-4 of the "lightening talks" (very brief talks) given at the SciPy 2009 conference. Speakers and topics are: 1. Olaf Lenz - Parallel Method Invocation (PMI) 2. John Wright - Software technologies used in EU "Total Crystallography" project. 3. Michael Ressler, "Python in the JWST/MIRI Project" 4. Daren Dale, Quantities: support for units and physical constants based on numpy.
Talks 5-8 of the "lightening talks" (very brief talks) given at the SciPy 2009 conference. Speakers and topics are: 5. James Turner, Astrodata - data reduction software for astronomy 6. Peter Wang of Enthought. Chaco Mayav bridge. 7. ? of Enthought. Analyzing investment options. 8. Luke Peterson, UC Davis. PyDy - derive equations of motions for mechanical systems.
Talks 9-13 of the "lightening talks" (very brief talks) given at the SciPy 2009 conference. Speakers and topics are: 9. John Hunter - sphinx sampledoc documentation system. 10. ?. Developing application using traits. 11. Jiao Lin, Caltech. Luban: a generic UI builder. http://dev.danse.us/trac/pyregui 12. Brian Grangers - running matplotlib without requiring -pylab at ipython startup. 13. Mike McKerns, Caltech


6:30 Informal reception (Location: Beckman Courtyard, in front of the conference room - map)

7:30 Astronomy BoF:. Gather together at reception to decide where to hold BoF (e.g., possibly combine with dinner)

8:30 - late BoFs.
Machine Learning/Probabilistic Modeling, Powell Booth, library (upstairs)
PDE BoF, Powell Booth room 120



Friday, August 21

The conference talks are held at the Beckman institute (map).

9:00 - 9:10 Welcome (Jarrod Millman & Gael Varoquaux)

9:10 - 10:10 Keynote: Modeling of Materials with Python (Jonathan Guyer, NIST)

10:10 - 10:30 Hermes and FEMhub Project (Pavel Solin, University of Nevada, Reno)
BREAK (10:30 - 11:00)

11:00 - 11:20 The PyMca Application and Toolkit (Armando Sole, ESRF, France)

11:20 - 11:30 Implementation of automatic script recording and network control for Mayavi (Prabhu Ramachandran, IIT Bombay, India)

11:30 - 12:10 Fast numerical computations with Cython (Dag Sverre Seljebotn, University of Oslo, Norway)

12:10 - 12:30 Fwrap: The Next-Generation Fortran-to-Python Interface Generator (Kurt Smith, University of Wisconsin-Madison)
LUNCH (12:30 - 2:30) On your own.

1:30-2:30: Documentation BoF, Powell Booth, room 100.

Brief presentation by Robert Kern? about stackOverflow (website for getting answers to technical questions), and by Nicolas Pinto about a script to make it easy to use Amazon EC2.

2:30 - 3:00 Panel discussion: State of Python visualization tools (John Hunter, Prabhu Ramachandran, Peter Wang. Moderator: Stefan van der Walt)

3:00 - 3:20 PySAL: A Python Library for Spatial Analysis and Geocomputation (Serge Rey, Arizona State University)

3:20 - 3:30 Neutron Scattering Data Acquisition and Experiment Automation with Python (Piotr Zolnierczuk, Oak Ridge National Lab)
BREAK (3:30 - 4:00)

4:00 - 4:20 Exploring the future of bioinformatics data sharing and mining with Pygr and Worldbase (Chris Lee, UCLA)

4:20 - 4:30 A full software stack for visualizing next-generation sequence information (Titus Brown, Michigan State University)

4:30 - 4:40 Pyclaw - The Evolution of Clawpack into Python (Kyle Mandli, University of Washington)

4:40 - 4:50 NumPy and SciPy Documentation in 2009 and Beyond (Joe Harrington, U. Central Florida)

4:50 - 5:00 Python in science and engineering education in India (Prabhu Ramachandran, IIT Bombay, India)

5:00 - 6:00 Next challenges for Python in Science (moderator: Jarrod Millman)
1st panel: The view of the pioneers (John Hunter, Eric Jones, Charles Harrison, Fernando Perez, Prabhu Ramachandran)
2nd panel: The view of the young generation (David Cournapeau, Pauli Virtanen, Gael Varoquaux, Stefan van der Walt)

Closing Comments




Introductory to Scientific computing with Python tutorial

UPDATE: Please note change of rooms below. The introductory tutorials will be held at Moore 070 and the advanced at Beckman (the original plan was the reverse). The Registration Desk will be open daily in the Beckman Institute Courtyard, 7:30 a.m. - 9:00 a.m. This is also where the coffee break service will be provided.

Audience

Scientists and engineers who are familiar with computers and basic numerical computing.

Location

The introductory tutorial will take place in 070 Moore (in the subbasement, two floors down from street level). You can see it marked on this map of the campus that lists all relevant buildings for the conference. Interactive and printable maps of the Caltech campus can also be found on Caltech's website, on those maps Moore is building #93.

Pre-requisites

  • Attendees are expected to bring along their laptops fully setup with the necessary software. We suggest installing EPD or Python(x,y). If you install Python(x,y) be sure to install the Full Edition which includes the Advanced Python Modules. The various software required are:
    • Python, version 2.5 or above,
    • numpy, version 1.2 or above,
    • scipy, version 0.7 or above,
    • IPython, version 0.8 or above,
    • matplotlib, version 0.9 or above,
    • Mayavi, version, 3.1 or above.
  • Once you have installed these packages, you may want to download and run this checklist script. It will do some sanity checks on your system, and if it finds a problem, it will generate a reasonably detailed report you can mail for help. We will try to assist you with fixing any problems you may run into before the actual conference starts, to save time and hassles.
  • Attendees are expected to be comfortable using the command line on their OS. If you are not comfortable with the command line, see this tutorial for an introductory lesson.
  • Attendees are expected to be comfortable using a programming editor of their choosing, which also supports Python. Some recommended editors:
    • Windows: notepad++
    • OSX: TextWrangler, TextMate
    • linux: gedit (gnome), kate (KDE)
    • All operating systems: Emacs, Vim.
  • The tutorials assume the audience has done some programming in Matlab (or similar) and is comfortable with basic numerical computing in these environments.
  • No prior programming experience with Python is expected. However, attendees are strongly encouraged to go through the official Python tutorial before attending the Introductory Tutorial. This material will be reviewed during the course, but only briefly. We recommend working through these chapters:
    • Chapter 1: Whetting Your Appetite
    • Chapter 2.1: The Python Interpreter
    • Chapter 3: Introduction to Python
    • Chapter 4.1-4.6: Python Flow Control
    • Chapter 5.1, 5.1.1, 5.1.2, 5.3, 5.5, 5.6: Python Data Structures
    • Chapter 6.0 (not 6.1): Basics on Python Modules
    • Chapter 7.0, 7.2, 7.2.1: Input and Output in Python
  • Attendees are encouraged to read the Numpy Tutorial.

Objectives

At the end of the course participants will be:

  1. able to write reasonable quality, procedural Python programs.
  2. broadly exposed to several of the relevant Python packages for numerical computing like ipython (interactive data exploration), numpy (arrays), scipy (numerics), matplotlib (high quality 2D plotting), and mayavi's mlab (simple 3D plotting) in order to write code for typical scientific computing tasks involving numerical algorithms, data analysis, data exploration and visualization.
  3. understand the general tools, workflow and best practices involved in writing good quality, tested, Python programs for scientific computing.

Structure of tutorial

The course will be completely hands on. All of the lecture material will expect users to type along and the sessions will be punctuated with exercises. The solutions for these exercises will also be discussed.



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Re: SciPy09 Video page direct links

John Hunter-4
On Tue, Aug 25, 2009 at 12:18 PM, Eric Carlson<[hidden email]> wrote:
> Hello,
>
> I had some issues searching for SciPy 09 video files this morning. Although
> the search was broken, at the same time it was still possible to link
> directly to the video pages.
>
> The attached basic html file (no javascript or images) has the tutorial and
> conference schedule and direct links to corresponding videos. You should be
> able to save the file and open locally.

Hey this is great - - the relevant sections of the scipy website are
written in ReST, I believe, so what would be most helpful would be a
ReST document that has the content you submitted in html.

  http://docutils.sourceforge.net/docs/ref/rst/introduction.html

The the website developers could just drop it into the conference pages.
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Re: SciPy09 Video page direct links

Alan G Isaac
On 8/27/2009 8:43 PM John Hunter apparently wrote:
> Hey this is great - - the relevant sections of the scipy website are
> written in ReST, I believe, so what would be most helpful would be a
> ReST document that has the content you submitted in html.
>
>   http://docutils.sourceforge.net/docs/ref/rst/introduction.html
>
> The the website developers could just drop it into the conference pages.


http://docutils.sourceforge.net/sandbox/cliechti/html2rst/html2rst.py

hth,
Alan Isaac

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Re: SciPy09 Video page direct links

David Warde-Farley-2
In reply to this post by John Hunter-4
On 27-Aug-09, at 8:43 PM, John Hunter wrote:

> Hey this is great - - the relevant sections of the scipy website are
> written in ReST, I believe, so what would be most helpful would be a
> ReST document that has the content you submitted in html.

They aren't, yet -- they're written in whatever awful wiki dialect  
Moin uses. Though that will be changing shortly.

I've put off announcing it to the list, but myself and a few others  
have been slowly converting all the useful (non-spam and non-personal  
page) content on the wiki to ReST, with the goal of moving the  
SciPy.org main page off of moin and onto Sphinx, and the Cookbook into  
pydocweb. You can take a look at the progress at http://github.com/dwf/rescued-scipy-wiki/

We'll certainly leave the current wiki intact for the time being, and  
there may be a fresh wiki instance (with CAPTCHAs to prevent the  
downward spiral we've seen within the current Moin instance) set up  
afterward, but it seems like the face of the community to the world  
ought to be one that is less of a mess, easily maintainable, and with  
comparatively little opportunity for vandalism.

David
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Re: SciPy09 Video page direct links

Gael Varoquaux
On Thu, Aug 27, 2009 at 11:04:47PM -0400, David Warde-Farley wrote:
> On 27-Aug-09, at 8:43 PM, John Hunter wrote:

> > Hey this is great - - the relevant sections of the scipy website are
> > written in ReST, I believe, so what would be most helpful would be a
> > ReST document that has the content you submitted in html.

> They aren't, yet -- they're written in whatever awful wiki dialect  
> Moin uses. Though that will be changing shortly.

The scipy conference website are, actually, eventhough it is hidden to
the user.

So, I can back what John said, if you give us a ReST file, we will be
able to add it easily to the conference website, and be much grateful.

Gaël
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Re: SciPy09 Video page direct links

David Warde-Farley-2
On 28-Aug-09, at 1:27 AM, Gael Varoquaux wrote:

> The scipy conference website are, actually, eventhough it is hidden to
> the user.

My bad!

As a side note, there are previous years' conference wiki pages which  
have been (mostly) converted into ReST, and would probably be more at  
home on the conference web page than anywhere else. We'll keep fixing  
them up, but feel free to take the ReST files and throw them somewhere  
in the conference website if you have some cycles to spare.

David
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Re: SciPy09 Video page direct links

Gael Varoquaux
On Fri, Aug 28, 2009 at 02:34:30AM -0400, David Warde-Farley wrote:
> On 28-Aug-09, at 1:27 AM, Gael Varoquaux wrote:

> > The scipy conference website are, actually, eventhough it is hidden to
> > the user.

> My bad!

> As a side note, there are previous years' conference wiki pages which  
> have been (mostly) converted into ReST, and would probably be more at  
> home on the conference web page than anywhere else. We'll keep fixing  
> them up, but feel free to take the ReST files and throw them somewhere  
> in the conference website if you have some cycles to spare.

I believe that you are overestimating the quality of the web application
behind the conference website. I don't think that we can easily to that.
The wiki engine powering the conference website is a very simple one, and
we can't add pages to the 'old conference' part :(.

Gaël
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Re: SciPy09 Video page direct links

Timmie
Administrator
In reply to this post by David Warde-Farley-2
> I've put off announcing it to the list, but myself and a few others  
> have been slowly converting all the useful (non-spam and non-personal  
> page) content on the wiki to ReST, with the goal of moving the  
> SciPy.org main page off of moin and onto Sphinx, and the Cookbook into  
> pydocweb. You can take a look at the progress at
http://github.com/dwf/rescued-scipy-wiki/
I have done something similar recently.

I had good success using pandoc for html2rest or wiki to rest.

Hope that helps.

You may drop me a note as PM. I can send you my humble script.

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Re: SciPy09 Video page direct links

Timmie
Administrator
> You may drop me a note as PM. I can send you my humble script.
Its actually here:
http://bazaar.launchpad.net/~timmie/web2py/web2py-appdocu/annotate/head%3A/doc/convert_faq.py

A very simple one. No science ;-(

here are the dialiects supported by pandoc:
http://johnmacfarlane.net/pandoc/


And taking this example: http://zwiki.org/MoinMoinMarkupExamples
moinmoin looks like mediawiki markup. But I am not shure I as I do not use wikis
that much...

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Re: SciPy09 Video page direct links

David Warde-Farley-2
In reply to this post by Timmie
On 28-Aug-09, at 4:09 AM, Tim Michelsen wrote:

> I have done something similar recently.
>
> I had good success using pandoc for html2rest or wiki to rest.
>
> Hope that helps.

Hi Tim,

Thanks for the pointer. I've used pandoc in the past to convert the  
numarray ndimage docs ( http://stsdas.stsci.edu/numarray/Doc/module-numarray.ndimage.html 
  ) to the version that currently appears in the SciPy Reference  
Guide, and it worked quite well for that purpose. It doesn't look like  
it supports Moin wiki dialect, but I've been using a MoinMoin plugin  
that I resurrected from terminal bit rot, my modified version is at http://github.com/dwf/moin2rst/tree/master 
  .

It does an okay job, but doesn't handle everything. I've been using  
lots of ad hoc regexps to do the cleanup, and have been a little  
astonished at how successfully I've been at automating a lot of things.

The nice thing about moin2rst is that it's a MoinMoin plugin and can  
use Moin's own parser; the trouble is that Moin seems to change their  
API quite frequently and I had to diddle a lot of imports to get it to  
work. Ideally I (or someone) would expand my fork of moin2rst so that  
it does a really bang-up job of converting Moin pages to ReST, but at  
this point I don't have the time or inclination for such an effort.

Cheers,

David
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Re: SciPy09 Video page direct links

Eric S. Carlson
In reply to this post by Alan G Isaac
Alan G Isaac wrote:

> On 8/27/2009 8:43 PM John Hunter apparently wrote:
>> Hey this is great - - the relevant sections of the scipy website are
>> written in ReST, I believe, so what would be most helpful would be a
>> ReST document that has the content you submitted in html.
>>
>>   http://docutils.sourceforge.net/docs/ref/rst/introduction.html
>>
>> The the website developers could just drop it into the conference pages.
>
>
> http://docutils.sourceforge.net/sandbox/cliechti/html2rst/html2rst.py
>
> hth,
> Alan Isaac
Per your request John, attached is an rst version that I think should
work. I got it to build in Sphinx with only one warning about this doc
not being in the TOC tree. To the best of my proofing, I think that all
the links work, but ...

I used Alan's link as a starting point for the translation, and got to
learn a considerable amount about string encoding (thanks to Gael's name
it seems). html2rst gave me a useful starting point, but still left me a
great opportunity to learn much about ReST. The program did a great job
with many parts, so I presume most problems arose from problems with the
original html.

Anyway, it was a good lesson for me and I hope the file will be helpful
for others.

Cheers,
EC

SciPy 2009 Videos, Other Links
==============================

`Slides and data here`_

Introductory Tutorials
======================
(see bottom of this page for suggested pre-req's)

**Tuesday**
Morning:
8:30-10:20. `Intro to Python`_: Gael Varoquaux, Christopher Burns

    - Quick IPython introduction: the workflow
    - Basic types: scalar types: int, float, complex
    - Collections: list and dictionaries (and tuples, sets, ...)
    - `Control flow`_: if, for, range, while, break, continue
    - `Functions`:_ definitions, arguments, docstrings, ...

10:20-10:40. Break.

10:40-12:30. Intro to Python (continued): Gael Varoquaux, Christopher Burns

    - `Exceptions handling in Python`_
    - Reusing your code: creating modules, '__main__'.
    - Standalone scripts, command line arguments.
    - `I/O`_, file handling
    - `Standard library`_ and general utilities.
    - Timing

Lunch break (on your own): 12:30-2:00.

Afternoon:

2:00-2:30. Debugging: Christopher Burns

    - effective strategies and effective debugger usage
    - print statements
    - %debug in IPython

2:30-3:00. Testing: Stefan van der Walt

    - the concept: using testing properties of code via a function doctests

3:00-3:50. Basic numpy arrays: Stefan van der Walt

    - The array, an n-dimensional object
    - vectorizing for speed and ease

3:50-4:10. Break.

4:10-4:30. Basic plotting with matplotlib: Mike Droettboom

    - plotting 1D arrays: points and lines,
    - plotting 2D arrays: images

4:30-5:00. more numpy: Stefan van der Walt

    - The memory model
    - dtypes
    - views and copies
    - Array creation

5:00-6:00. Spill-over and Q & A session.

**Wednesday**

Morning:

8:00-8:30. Optional startup session where the organizers will try to
assist with any last-minute setup or installation problems.

8:30-9:30. `More matplotlib`_ Mike Droettboom

    - customizing colors, styles
    - legend
    - matplotlibrc
    - math text

9:30-10:20. `More numpy`_: Perry Greenfield

    - advanced indexing
    - use of where
    - zen, examples of vectorizing
    - ieee special number and error handling (5 min)
    - masked arrays (10-15 min)

10:20-10:40. Break.

10:40-11:30. More numpy (continued) Perry Greenfield

11:30-12:00. `Basic 3d plots with mlab`_ : Gael Varoquaux
    - 3D plotting functions
    - their keyword arguments
    - the GUI

Lunch break (on your own): 12:30-2:00.

Afternoon:

2:00-3:50. `Using scipy for numerics`_: David Cournapeau, Eric Jones

    - Linear algebra
    - random numbers
    - FFT
    - special functions
    - Root finding
    - Quadrature
    - ODEs

3:50-4:10. Break.

4:10-5:30. `The Whole Enchilada`_: Eric Jones

    -Largish assignment to tie all of the above together.

5:30-6:00. Q & A Session



Advanced Tutorials
==================

**Tuesday**
Morning:
8:00-8:30. Optional startup session where the organizers will try to
assist with any last-minute setup or installation problems.

8:30-10:20. `Advanced numpy 1`_ and `advanced numpy 2`_: Stefan van der
    Walt and David Cournapeau.

10:20-10:40. Break.

10:40-12:30. `Advanced topics in matplotlib`_: John Hunter

Lunch break (on your own): 12:30-2:00.

Afternoon:

2:00-3:50. `Symbolic computing with sympy`_: Ondrej Certik.

3:50-4:10. Break.

4:10-6:00. `Statistics with Scipy`_: Robert Kern.

**Wednesday**
Morning:
8:00-8:30. Optional startup session where the organizers will try to
assist with any last-minute setup or installation problems.

8:30-10:20. `Cython`_: Dag Sverre Seljebotn.

10:20-10:40. Break.

10:40-12:30. `Using GPUs with PyCUDA`_: Nicolas Pinto.

Lunch break (on your own): 12:30-2:00.

Afternoon:

2:00-3:50. `Designing scientific interfaces with Traits`_: Enthought.

3:50-4:10. Break.

4:10-6:00. `Mayavi/TVTK`_ : Prabhu Ramachandran.


Conference
==========

**Thursday, August 20**

9:00 - 9:10 `Welcome`_ (Jarrod Millman & Gael Varoquaux)

9:10 - 9:30 `Update on the core projects`_ (Charles Harrison, Fernando
Perez, John Hunter, David Cournapeau)

9:30 - 10:30 `Keynote - What to demand from a Scientific Computing
Language -- Even if you don't care about computing or languages`_ (Peter
Norvig, Director of Research, Google)

BREAK (10:30 - 11:00)

11:00 - 11:10 `nipy.timeseries - Neuroimaging time-series analysis`_ (Ariel Rokem, UC Berkeley)

11:10 - 11:50 `Virtual reality - a tool for the highly quantitative study
of animal behavior`_ (Andrew Straw, Caltech)

11:50 - 12:10 `Parallel Kernels - An Architecture for Distributed Parallel
Computing`_ (Nikunj Patel, University of Maryland)

12:10 - 12:20 `PaPy - Parallel and distributed data-processing pipelines
in Python`_ (Marcin Cieslik, University of Virginia)

12:20 - 12:30 `High-Performance Code Generation Using CorePy`_ (Andrew
Friedley, Indiana University)
LUNCH (12:30 - 2:30) On your own.

2:30 - 3:00 `Panel discussion (Python and Parallel computing`_  (Michael
Aivazis, Brian Granger, Nicolas Pinto, moderator: Gael Varoquaux)

3:00 - 3:10 `Sherpa - 1D/2D modeling and fitting in Python`_ (Brian
Refsdal, Harvard Smithsonian Center for Astrophysics)

3:10 - 3:20 `Multiprocess System for Virtual Instruments in Python`_
(Brian D'Urso, University of Pittsburgh)

3:20 - 3:30 `ESPResSo++ - A Python-controlled, Parallel Simulation
Software for Soft Matter Research`_ (Olaf Lenz, Max-Planck-Institute for
polymer research, Mainz, Germany)

BREAK (3:30 - 4:00)

4:00 - 4:40 `Sympy`_ (Ondrej Certik, University of Nevada, Reno)

4:40 - 4:50 `Python implementation of weno interpolation and
reconstruction`_ (Adrian Townsend, University of Washington)

4:50 - 5:00 `Writing Safer NumPy Extensions in C++ with Templates and
TooN`_ (Damian Eads, University of California)

5:00 - 6:00 Lightning Talks

`Talks 1-4`_ of the "lightening talks" (very brief talks) given at the SciPy
2009 conference. Speakers and topics are: 1. Olaf Lenz - Parallel Method
Invocation (PMI) 2. John Wright - Software technologies used in EU "Total
Crystallography" project. 3. Michael Ressler, "Python in the JWST/MIRI
Project" 4. Daren Dale, Quantities: support for units and physical constants
based on numpy.

`Talks 5-8`_ of the "lightening talks" (very brief talks) given at the SciPy
2009 conference. Speakers and topics are: 5. James Turner, Astrodata - data
reduction software for astronomy 6. Peter Wang of Enthought. Chaco Mayav
bridge. 7. ? of Enthought. Analyzing investment options. 8. Luke Peterson, UC
Davis. PyDy - derive equations of motions for mechanical systems.

`Talks 9-13`_ of the "lightening talks" (very brief talks) given at the SciPy
2009 conference. Speakers and topics are: 9. John Hunter - sphinx sampledoc
documentation system. 10. ?. Developing application using traits. 11. Jiao
Lin, Caltech. Luban: a generic UI builder. http://dev.danse.us/trac/pyregui
12. Brian Grangers - running matplotlib without requiring -pylab at ipython
startup. 13. Mike McKerns, Caltech


6:30 Informal reception (Location: Beckman Courtyard, in front of the
conference room - map)

7:30 Astronomy BoF:. Gather together at reception to decide where to hold
BoF (e.g., possibly combine with dinner)

8:30 - late BoFs.
Machine Learning/Probabilistic Modeling, Powell Booth, library (upstairs)
PDE BoF, Powell Booth room 120



**Friday, August 21**

The conference talks are held at the Beckman institute (map).

9:00 - 9:10 `Welcome Day 2`_(Jarrod Millman & Gael Varoquaux)`

9:10 - 10:10 `Keynote - Modeling of Materials with Python`_ (Jonathan
Guyer, NIST)

10:10 - 10:30 `Hermes and FEMhub Project`_ (Pavel Solin, University of
    Nevada, Reno)

BREAK (10:30 - 11:00)

11:00 - 11:20 `The PyMca Application and Toolkit`_ (Armando Sole, ESRF,
France)

11:20 - 11:30 `Implementation of automatic script recording and network
control for Mayavi`_ (Prabhu Ramachandran, IIT Bombay, India)

11:30 - 12:10 `Fast numerical computations with Cython`_ (Dag Sverre
Seljebotn, University of Oslo, Norway)

12:10 - 12:30 `Fwrap - The Next-Generation Fortran-to-Python Interface
Generator`_ (Kurt Smith, University of Wisconsin-Madison)

LUNCH (12:30 - 2:30) On your own.

1:30-2:30: Documentation BoF, Powell Booth, room 100.

Brief presentation by Robert Kern? about `stackOverflow`_ (website for
getting answers to technical questions), and by Nicolas Pinto about a script
to make it easy to use Amazon EC2.

2:30 - 3:00 `Panel discussion - State of Python visualization tools`_
(John Hunter, Prabhu Ramachandran, Peter Wang. Moderator: Stefan van
der Walt)

3:00 - 3:20 `PySAL - A Python Library for Spatial Analysis and
Geocomputation`_ (Serge Rey, Arizona State University)

3:20 - 3:30 `Neutron Scattering Data Acquisition and Experiment
Automation with Python`_ (Piotr Zolnierczuk, Oak Ridge National Lab)

BREAK (3:30 - 4:00)

4:00 - 4:20 `Exploring the future of bioinformatics data sharing and
mining with Pygr and Worldbase`_ (Chris Lee, UCLA)

4:20 - 4:30 `A full software stack for visualizing next-generation
sequence information`_ (Titus Brown, Michigan State University)

4:30 - 4:40 `Pyclaw - The Evolution of Clawpack into Python`_ (Kyle
Mandli, University of Washington)

4:40 - 4:50 `NumPy and SciPy Documentation in 2009 and Beyond`_ (Joe
Harrington, U. Central Florida)

4:50 - 5:00 `Python in science and engineering education in India (Prabhu
Ramachandran`_ , IIT Bombay, India)

5:00 - 6:00 Next challenges for Python in Science (moderator: Jarrod
Millman)

1st panel:`The view of the pioneers`_ (John Hunter, Eric Jones, Charles
Harrison, Fernando Perez, Prabhu Ramachandran)

2nd panel: `The view of the young generation`_ (David Cournapeau, Pauli
    Virtanen, Gael Varoquaux, Stefan van der Walt)

`Closing Comments`_




Introductory to Scientific computing with Python tutorial
=========================================================

**Audience**


Scientists and engineers who are familiar with computers and basic numerical
computing.

**Objectives**

At the end of the course participants will be:

1.  able to write reasonable quality, procedural Python programs.
2.  broadly exposed to several of the relevant Python packages for
    numerical computing like ``ipython`` (interactive data exploration),
    ``numpy`` (arrays), ``scipy`` (numerics), ``matplotlib`` (high quality 2D
    plotting), and mayavi's ``mlab`` (simple 3D plotting) in order to write
    code for typical scientific computing tasks involving numerical
    algorithms, data analysis, data exploration and visualization.
3.  understand the general tools, workflow and best practices involved in
    writing good quality, tested, Python programs for scientific computing.


**Structure of tutorial**


The course will be **completely hands on**. All of the lecture material will
expect users to type along and the sessions will be punctuated with
exercises. The solutions for these exercises will also be discussed.


**Pre-requisites**

-   Attendees are expected to bring along their laptops **fully setup
    with the necessary software**. We suggest installing `EPD`_ or
    `Python(x,y)`_. If you install Python(x,y) be sure to install the *Full
    Edition* which includes the *Advanced Python Modules*. The various
    software required are:

    -   Python, version 2.5 or above,
    -   numpy, version 1.2 or above,
    -   scipy, version 0.7 or above,
    -   IPython, version 0.8 or above,
    -   matplotlib, version 0.9 or above,
    -   Mayavi, version, 3.1 or above.

-   Once you have installed these packages, you may want to download and
    run this `checklist`_ script. It will do some sanity checks on your
    system, and if it finds a problem, it will generate a reasonably detailed
    report you can mail for help. We will try to assist you with fixing any
    problems you may run into before the actual conference starts, to save
    time and hassles.

-   Attendees are expected to be comfortable using the command line on
    their OS. If you are not comfortable with the command line, see `this
    tutorial`_ for an introductory lesson.
-   Attendees are expected to be comfortable using a programming editor
    of their choosing, which also supports Python. Some recommended editors:

    -   Windows: notepad++
    -   OSX: TextWrangler, TextMate
    -   linux: gedit (gnome), kate (KDE)
    -   All operating systems: Emacs, Vim.

-   The tutorials assume the audience has done some programming in Matlab
    (or similar) and is comfortable with basic numerical computing in these
    environments.
-   No prior programming experience with Python is expected. However,
    attendees are **strongly encouraged** to go through the `official Python
    tutorial`_ before attending the Introductory Tutorial. This material will
    be reviewed during the course, but *only briefly*. We recommend working
    through these chapters:

    -   Chapter 1: Whetting Your Appetite
    -   Chapter 2.1: The Python Interpreter
    -   Chapter 3: Introduction to Python
    -   Chapter 4.1-4.6: Python Flow Control
    -   Chapter 5.1, 5.1.1, 5.1.2, 5.3, 5.5, 5.6: Python Data Structures
    -   Chapter 6.0 (not 6.1): Basics on Python Modules
    -   Chapter 7.0, 7.2, 7.2.1: Input and Output in Python

-   Attendees are encouraged to read the `Numpy Tutorial`_.






.. _Slides and data here:
    http://conference.scipy.org/slides
.. _Intro to Python:
    http://www.archive.org/details/scipy09_introTutorialDay1_1
.. _Control flow:
    http://www.archive.org/details/scipy09_introTutorialDay1_2
.. _Functions:
    http://www.archive.org/details/scipy09_introTutorialDay1_3
.. _Exceptions handling in Python:
    http://www.archive.org/details/scipy09_introTutorialDay1_4
.. _I/O: http://www.archive.org/details/scipy09_introTutorialDay1_5
.. _Standard library:
    http://www.archive.org/details/scipy09_introTutorialDay1_6
.. _More matplotlib:
    http://www.archive.org/details/scipy09_introTutorialDay2_1
.. _More numpy:
    http://www.archive.org/details/scipy09_introTutorialDay2_2
.. _Basic 3d plots with mlab:
    http://www.archive.org/details/scipy09_introTutorialDay2_3
.. _Using scipy for numerics:
    http://www.archive.org/details/scipy09_introTutorialDay2_4
.. _The Whole Enchilada:
    http://www.archive.org/details/scipy09_introTutorialDay2_5
.. _Advanced numpy 1:
    http://www.archive.org/details/scipy09_advancedTutorialDay1_1
.. _advanced numpy 2:
    http://www.archive.org/details/scipy09_advancedTutorialDay1_2
.. _Advanced topics in matplotlib:
    http://www.archive.org/details/scipy09_advancedTutorialDay1_3
.. _Symbolic computing with sympy:
    http://www.archive.org/details/scipy09_advancedTutorialDay1_4
.. _Statistics with Scipy:
    http://www.archive.org/details/scipy09_advancedTutorialDay1_5
.. _Cython: http://www.archive.org/details/scipy09_advancedTutorial_6
.. _Using GPUs with PyCUDA:
    http://www.archive.org/details/scipy09_advancedTutorial_7
.. _Designing scientific interfaces with Traits:
    http://www.archive.org/details/scipy09_advancedTutorial_8
.. _Mayavi/TVTK:
    http://www.archive.org/details/scipy09_advancedTutorial_9
.. _Welcome:
    http://www.archive.org/details/scipy09_day1_01-Welcome
.. _Update on the core projects:
    http://www.archive.org/details/scipy09_day1_02-Core_projects
.. _Keynote - What to demand from a Scientific Computing Language -- Even
    if you don't care about computing or languages:
    http://www.archive.org/details/scipy09_day1_03-Peter_Norvig
.. _nipy.timeseries - Neuroimaging time-series analysis:
    http://www.archive.org/details/scipy09_day1_04-Ariel_Rokem
.. _Virtual reality - a tool for the highly quantitative study of animal
    behavior:
    http://www.archive.org/details/scipy09_day1_05-Andrew_Straw
.. _Parallel Kernels - An Architecture for Distributed Parallel Computing:
    http://www.archive.org/details/scipy09_day1_06-Nikunj_Patel
.. _PaPy - Parallel and distributed data-processing pipelines in Python:
    http://www.archive.org/details/scipy09_day1_07-Marcin_Cieslik
.. _High-Performance Code Generation Using CorePy:
    http://www.archive.org/details/scipy09_day1_08-Andrew_Friedley
.. _Panel discussion (Python and Parallel computing:
    http://www.archive.org/details/scipy09_day1_09-Panel_parallel_computing
.. _Sherpa - 1D/2D modeling and fitting in Python:
    http://www.archive.org/details/scipy09_day1_10-Brian_Refsdal
.. _Multiprocess System for Virtual Instruments in Python:
    http://www.archive.org/details/scipy09_day1_11-Brian_DUrso
.. _ESPResSo++ - A Python-controlled, Parallel Simulation Software for
    Soft Matter Research:
    http://www.archive.org/details/scipy09_day1_12-Olaf_Lenz
.. _Sympy:
    http://www.archive.org/details/scipy09_day1_13-Ondrej_Certik
.. _Python implementation of weno interpolation and reconstruction:
    http://www.archive.org/details/scipy09_day1_14-Adrian_Townsend
.. _Writing Safer NumPy Extensions in C++ with Templates and TooN:
    http://www.archive.org/details/scipy09_day1_15-Damian_Eads
.. _Talks 1-4:
    http://www.archive.org/details/scipy09_day1_16-Lightning_talks_1-4
.. _Talks 5-8:
    http://www.archive.org/details/scipy09_day1_17-Lightning_talks_5-8
.. _Talks 9-13:
    http://www.archive.org/details/scipy09_day1_18-Lightning_talks_9-13
.. _Welcome Day 2: http://www.archive.org/details/scipy09_day2_01-Welcome
.. _Keynote - Modeling of Materials with Python:
    http://www.archive.org/details/scipy09_day2_02-Jonathan_Guyer
.. _Hermes and FEMhub Project:
    http://www.archive.org/details/scipy09_day2_03-Pavel_Solin
.. _The PyMca Application and Toolkit:
    http://www.archive.org/details/scipy09_day2_04-Armando_Sole
.. _Implementation of automatic script recording and network control for
    Mayavi:
    http://www.archive.org/details/scipy09_day2_05-Prabhu_Ramachandran
.. _Fast numerical computations with Cython:
    http://www.archive.org/details/scipy09_day2_06-Dag_Sverre_Seljebotn
.. _Fwrap - The Next-Generation Fortran-to-Python Interface Generator:
    http://www.archive.org/details/scipy09_day2_07-Kurt_Smith
.. _stackOverflow:
    http://www.archive.org/details/scipy09_day2_08-Brief_presentations
.. _Panel discussion - State of Python visualization tools:
    http://www.archive.org/details/scipy09_day2_09-Panel_visualization_tools
.. _PySAL - A Python Library for Spatial Analysis and Geocomputation:
    http://www.archive.org/details/scipy09_day2_10-Serge_Rey
.. _Neutron Scattering Data Acquisition and Experiment Automation with
    Python : http://www.archive.org/details/scipy09_day2_11-Piotr_Zolnierczuk
.. _Exploring the future of bioinformatics data sharing and mining with
    Pygr and Worldbase:
    http://www.archive.org/details/scipy09_day2_12-Chris_Lee
.. _A full software stack for visualizing next-generation sequence
    information: http://www.archive.org/details/scipy09_day2_13-Titus_Brown
.. _Pyclaw - The Evolution of Clawpack into Python:
    http://www.archive.org/details/scipy09_day2_14-Kyle_Mandli
.. _NumPy and SciPy Documentation in 2009 and Beyond:
    http://www.archive.org/details/scipy09_day2_15-Joe_Harrington
.. _Python in science and engineering education in India (Prabhu
    Ramachandran:
    http://www.archive.org/details/scipy09_day2_16-Prabhu_Ramachandran
.. _The view of the pioneers:
    http://www.archive.org/details/scipy09_day2_17-Panel_pioneers
.. _The view of the young generation:
    http://www.archive.org/details/scipy09_day2_18-Panel_young_generation
.. _Closing Comments:
    http://www.archive.org/details/scipy09_day2_19-Closing_comments
.. _this map:
    http://www.scipy.org/Conference?action=AttachFile&do=get&target=SciPy09
    -campus-map-final.pdf
.. _on Caltech's website: http://www.caltech.edu/map/
.. _EPD: http://www.enthought.com/products/epd.php
.. _Python(x,y): http://www.pythonxy.com/
.. _checklist:
    https://cirl.berkeley.edu/fperez/tmp/intro_tut_checklist.py
.. _this tutorial: http://swc.scipy.org/lec/shell01.html
.. _official Python tutorial: http://docs.python.org/tut
.. _Numpy Tutorial: http://www.scipy.org/Tentative_NumPy_Tutorial

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Re: SciPy09 Video page direct links

Fernando Perez
In reply to this post by David Warde-Farley-2
On Thu, Aug 27, 2009 at 11:34 PM, David Warde-Farley<[hidden email]> wrote:
> As a side note, there are previous years' conference wiki pages which
> have been (mostly) converted into ReST, and would probably be more at

As a side-side note, it's worth remembering that moin understands reST
already.  I've been recently making all new pages in moin wikis using
this:

{{{
#!rst

...

}}}

I'm not sure it catches 100% of reST and in the long run we do want to
transition to a native-reST solution, but tagging existing pages like
this may help contain the spread of Moin markup further...

Cheers,

f
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