Open Courses

Python for Scientific Computing

Date: June 23-27, 2008
Location: Austin, Texas, at Enthought's offices
Cost: 3 days: $1500; 5 days: $2500. You can attend either the first three days of the course or the entire five days.
Registration: Contact Leah Jones at 1-512-536-1057 to register via credit card, or email info@enthought.com with any questions.

Enthought is offering an Open Course targeted for scientists and engineers who are using, or wishing to use Python. The course will be useful for those who want to interact with their data from a command line, write small scripts, build functional modules, or write large-scale scientific applications using Python. (Or some combination of all of these.)

By "open course" we mean that it is open for general admission (rather than the targeted internal training that we also do for our clients). The topics will therefore be wider-ranging and less targeted. We will, however, use specific examples from various domains to help illuminate the exercises. It is expected that participants have experience in programming or scripting (C, FORTRAN, Java, Matlab); familiarity with Python is good, but not necessary. We'll start with the basics and move fairly quickly.

Course participants will be expected to bring a laptop with EPD or equivalent installed. The format of the course will be short lectures followed by relevant participant exercises.

Day 1: Introduction to Python

Introduction to IPython (we use this throughout the course)
Basic Python data types: lists, dictionaries, and sets
Flow control (loops, if-then, etc.)
Functions and Modules
Classes
File I/O
Exceptions

Day 2: Numerical Python

Introduction to NumPy arrays and basic plotting
Multi-dimensional and fancy indexing
Shaping arrays
Array attributes and methods
Array construction
Math functions
Universal functions and selection functions
Broadcasting
Output formatting and error handling
Composite data structures

Day 3: Introduction to SciPy

Overview of the SciPy library
Linear algebra and FFT
Interpolation
Integration
Signal processing
Image processing
Optimization
Introduction to Weave

Day 4: Python as Glue

Overview of wrapping Python
Hand wrapping a library
Weave: in-lining C/C++ in Python
f2py: wrapping Fortran code using NumPy
SWIG: C/C++ wrapping
Pyrex/Cython: hybrid language for extensions
Ctypes: calling C-functions in shared library

Day 5: Introduction to the Enthought Tool Suite

Traits: event handling and rapid building of UIs
Chaco: interactive plotting
Mayavi and TVTK: 3-D visualization
Envisage: building pluggable applications