Practical Numerical Computing Using Python

An ideal book for introduction to practical numerical algorithms and programming for advanced undergraduate and beginning graduate students.

Introduces Python programming language and its modules related to numerical computing; Covers Numpy, Matplotlib, and Scipy modules in details; Illustrates how to make a variety of plots and animations; Detailed discussions on important numerical algorithms: Interpolation, Integration, Differentiation, ODE and PDE solvers, and Linear algebra solvers.

Practical implementation of the algorithms in Python.

Introduces Spectral and Finite-difference methods and applications to fluid mechanics and quantum mechanics.

Includes chapters on Monte Carlo methods and applications to statistical physics, as well as on error analysis.

A brief introduction to Computer hardware, complexity estimates, and nondimensionalization.