Book Image

Learning SciPy for Numerical and Scientific Computing Second Edition - Second Edition

Book Image

Learning SciPy for Numerical and Scientific Computing Second Edition - Second Edition

Overview of this book

This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
Table of Contents (15 chapters)
Learning SciPy for Numerical and Scientific Computing Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 4. SciPy for Numerical Analysis

Practically all the different areas of numerical analysis are contemplated in some SciPy module. For example, in order to compute values of special functions, we use the scipy.special module. The scipy.interpolate module takes care of interpolation, extrapolation, and regression. For optimization, we have the scipy.optimize module, and finally, we have the scipy.integrate module for numerical evaluation of integrals. This last module serves as the interface to perform numerical solutions of ordinary differential equations as well.

Thus, in this chapter, we will first extensively explore how to use SciPy to numerically evaluate the special functions that are commonly found in the field of mathematical physics. Then, we will discuss the modules available in SciPy to tackle regression, interpolation, and optimization problems.

The chapter ends with a solution of the chaotic Lorenz system as an illustration of the capabilities included in SciPy to find...