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===================================================
 Practical Scientific Computing in Python - Agenda
===================================================

JDH/FP indicates who presents what.


Day 1 (Friday April 13)
=======================

900-905 Introduction 
Set up computers, introduce instructors.

905-945 FP: Python for scientific computing
A high-level overview of the topic of Python in a scientific context.

950-1045 JDH: Workflow.

Editor: (X)Emacs, Vi(m), etc.

ipython.  Saving and reloading files, interactive use of variables, %run,
%debug, %xmode verbose.

Getting help:
  - pydoc (-g, -p)

  - The standard docs (bookmark them)

  - ipython ?/??, help(), the tab key.  numpy.*cos*? search.

  - The open source process: mailing lists, wikis, svn.  Python
  cookbook. Participate!


Basic setup:
  - ipython
  - matplotlib (latex, etc).
  - Modules: import/reload, PYTHONPATH.


1045:1100 --- Coffee break ---


1100:1215 FP: Introductory examples.

* Qsort: lists, recursion.

* Define a simple function: Wallis' product for pi.  Illustrates arbitrary
size integers.

* Define a trapezoid rule integrator: function objects, arrays.

1215:1315 --- Lunch Break ---

1315:1400 JDH: Basic numpy/pylab

* Record arrays

* Timeseries

1400:1430 FP: Numerical integration and root finding: Find t such that

 \int_0^t{ f(s) ds} = u

for a known, monotonically increasing f(s) and a fixed u.


1430:1500 FP: Univariate polynomials, root finding: poly1d objects,
convolutions, plotting.

1500:1515 --- Coffee break ---

1515:1700: JDH/FP - Optional material (there's a colloquium talk)

* Word frequencies: use of dictionaries and text processing.

* Getbibtex: fetching bibliographic information from the net (networking,
  regular expressions, command-line scripting).

* Beautiful soup: screen-scraping HTML for data extraction.

* Possible 3d demos (not user exercises) using VPython and VTK/MayaVi.


Day 2 (Saturday April 14)
=========================

900:945 JDH: Data fitting/smoothing: least squares, cubic splines, polynomial
fitting.  Basic linear algebra.

945:1030 FP: FFTs: 2-d image denoising via FFT.

1030:1045 --- Coffee break ---

1045:1130 JDH: Logistic map

1130:1200 FP: Bessel functions: special functions library, array manipulations
to check recursion relation.

1200:1300 --- Lunch break ---

1300:1345 JDH: Statistics & distributions

1345:1445 FP:

* Montecarlo integration to compute pi.

* Speed: weave.blitz, weave.inline.

1445:1500 Wrapup, discussion, questions, coffee.



Unused examples and exercises, extra ideas
==========================================

* Prime numbers: the Sieve of Erathostenes.  Illustrates lists and sets.

* Visual (VPython): Show some examples, explain.  Target shooting exercise.

* Eigenfaces problem, part 1.

* Eigenfaces problem, part 2.

* One-dimensional FFT - Bode plot.

* Spectral interpolation.

* Steinman interpolation.

* Extended precision root finding: manually implement newton's method using
  clnum or mpfr.