Preface

While maintaining the main structure of the first edition, this revised edition of Learning SciPy for Numerical and Scientific Computing includes a set of companion IPython Notebooks. This will help students, researchers, and practitioners modify and incorporate in their own work, the set of tested code snippets that are presented in the book, as the pedagogical strategy. This will also show and illustrate the computing power that SciPy brings to the fingertips of anyone interested in performing numerical computation via the unique flexibility offered by the Python computer language.

We should mention, however, that the IPython Notebooks will make sense to anyone starting in the field only if they are read alongside the corresponding section in the book, helping you to develop skills in the use of SciPy to solve large scale numerical problems while gaining understanding of the conditions and limitations associated with the modules contained in SciPy. Certainly, the already knowledgeable reader will find pleasure as they encounter material they already know, but will be challenged to devise better ways to accomplish with the same level of clarity presented in the book with the many computational tasks used to illustrate the functionality of SciPy.

SciPy has been an integral part of the computational environment of choice for many scientists for years. One of our challenges today is to bring together professionals with different backgrounds, technologies, and expertise in software (from the pure mathematician, to the hardcore engineer) to contribute independent of their working environments.

SciPy in Python is a perfect platform to coordinate projects in a smooth, reliable, and coherent environment. It allows performing most tasks with ease; reason being that many dedicated software tools easily integrate with the core features of SciPy, therefore, interfacing with non-Python-based software packages and tools is becoming increasingly simple.

In summary, this book presents the most robust programming environment to date. We will show you how to use this system from basic manipulation of data, to a very detailed exposition through examples in different branches of science and engineering.