Presenters

Travis Oliphant and Eric Jones

Intended Audience

Scientist and developers familiar with Python and NumPy that would like to learn about advanced tools for science.

Attendee Requirements

Nothing is required, but, the following stack is very helpful to have on your machine.

• Python 2.5.x
• NumPy 1.0.4 or newer
• IPython
• matplotlib
• SciPy

Note

This is the second of two 3-hour tutorials. The first provided an introduction to NumPy. While it isn't a prerequisite to this course, it can serve as a nice introduction.

Description

This tutorial covers a number of advanced topics in scientific computing with Python. The first hour offers an introduction to SciPy (http://www.scipy.org/). SciPy provides a number of scientific algorithms including optimization, signal and image processing, statistics, integration, interpolation and more. The 2nd hour focuses on 2D and 3D visualization tools including MatPlotlib (http://www.scipy.org/), Chaco (http://code.enthought.com/chaco/), and Mayavi (https://svn.enthought.com/enthought/wiki/MayaVi). We'll cover the basics of each tool and when to use each. The third hour investigates discusses best practices in integrating libraries into Python. We introduce students to several tools such as f2py and weave that make this process easier.

Biographies

Travis Oliphant has worked extensively with Python for numerical and scientific programming for over 10 years. He is the primary developer of the NumPy package and the author of the definitive Guide to NumPy. He was an early contributor to the documentation for the Numeric package and was one of the original authors of the SciPy package. He has a Ph.D. in Biomedical Engineering from the Mayo Clinic. He was an Assistant Professor of Electrical and Computer Engineering at Brigham Young University from 2001 to 2007, and directed the BYU Biomedical Imaging Lab. Travis is a member of the Python Software Foundation.

Eric Jones has a broad background in engineering and software development, and leads Enthought's product engineering and software design. Prior to co-founding Enthought, Eric worked in the fields of numerical electromagnetics and genetic optimization in the Department of Electrical Engineering at Duke University. He has taught numerous courses about Python and it's use in scientific computing. Eric holds M.S. and Ph.D. degrees from Duke University in Electrical Engineering and a B.S.E. in Mechanical Engineering from Baylor University. He also is a member of the Python Software Foundation.