Recommended Books

The following are books which are recommended by users of Python for scientific computation.

LAPACK User's Guide; E. Anderson, Z. Bai, C. Bischof, Demmel J., J. Dongarra; Paperback.

"For those who want to know how the LinearAlgebra module really works."

Matrix Computations, 2nd edition; Gene H. Golub & Charles Van Loan; Paperback.

Numerical Recipes in C; William H. Press, Saul A. Teukolsky, William T. Vetterling; Hardcover.

"One of the big problems in computational science is that most users of numerical methods have no training at all in that business, whereas the experts in numerical analysis make no effort to explain their work to non-specialists. Numerical Recipes tries to be the bridge between the two worlds; it's not perfect, but there's nothing better. My recommendation is to read Numerical Recipes to learn about the methods, but not to use the code for real-life work. There are much better libraries around for almost any application. <anon.>"

Numerical Analysis; Richard L. Burden, J. Douglas Faires; 4th Edition; Hardcover. 1988. PWS-KENT Publishing Company; ISBN 0-53491-585-X; QA297.B84.

Computer Graphics: Principles and Practice; 2nd edition. James Foley, Andries van Dam, Steven Feiner, John Hugues. Addison-Wesley Publishing Company. (1990)

Everything by Edward R. Tufte:

The visual display of quantitative information. (1983).
Envisioning Information. (1990)
Visual Explanations: Images and quantities, evidence and narrative. (1997).

All are published by Graphics Press, Cheshire, CT and are hardback.