Scientific Computing: Python Hacking for Math Junkies

Contents: Python programs, iPython notebooks, expressions, statements, types, lists, arrays, functions, classes, plotting, list comprehension, recursion. Applications include linear systems, computational geometry, root finding, interpolation, polynomial least squares, discrete systems, differential equations, principal component analysis, singular value decomposition, fractals, chaos, and satellite orbit propagation. Also covers numpy, plotting with pyplot, and basics maps with basemap.

Now includes more than 200 exercises for students.

Target audience: undergraduate math and science students entering their upper level curriculum. Calculus and some linear algebra background is helpful; a review of linear algebra is included as an appendix. No prior programming experience is expected