Python for Scientists & Engineers: Python

The first day is devoted to understanding how to think in Python. We start by demonstrating the IPython interactive environment and how it can be used for rapid application development. The pace of this day is determined by previous exposure to Python. Even experienced Python programmers report learning new ideas from the experts that teach this course.

• Data-types (strings, lists, dictionaries, files)
• Syntax and language structure
• Creating and importing modules
• Reading and writing files
• Overview of the standard library
• Introduction to object oriented programming

Python for Scientists & Engineers: NumPy

On the second day, the NumPy extension module to Python is exposed as a tool for rapidly manipulating and processing large data-sets.

• Basic operations and manipulations on N-dimensional arrays
• Understanding the N-dimensional data structure
• Using vectorization to process arrays with implicit loops
• Understanding slicing and broadcasting
• Dealing with large data-sets
• Working with "structured" arrays
• Reading and writing data

Python for Scientists & Engineers: SciPy and extension modules

Overview of SciPy with examples chosen according to attendees' needs (interpolation, curve-fitting, optimization, etc.)

• Creating Extension modules
• Interacting with other languages: Weave, Cython, SWIG, f2py

Interfacing with C / C++ and Fortran

One of Python's greatest features is its ability to integrate seamlessly with C, C++, and Fortran. In this module you will learn how to use a variety of tools that have emerged for efficiently integrating with legacy code as well as optimizing new code with compiled modules. This module extends the material covered on the third day of the Python for Scientists and Engineers course. Topics to be covered can be modified to suit participants interest but can include:

• Integrating with Fortran using f2py
• Integrating legacy C / C++ code using SWIG
• In-lining C/C++ in a Python application using Weave
• Calling arbitrary shared-libraries with ctypes
• Creating new extension modules with Cython
• Overview of other tools
• Use of the NumPy C-API
• Managing memory and dealing with C++ objects
• Embedding Python in a C/C++ application.

Introduction to UIs and Visualization

This one day course is a condensed version of portions of the 3-day course which covers just the basics of Traits and Chaco. Students will learn the basics of Traits and how to build simple interactive visualizations with Chaco. Topics included:

Traits

• Notification
• Visualization
• Validation
• Initialization
• Delegation

Chaco

• Integration into Traits UI
• Scatter and line plots
• Image plots
• Containers for layout
• Simple tool creation for event handling
• Introduction to overlays