The concept of views is one of the important topics you should have learned from this chapter. Missing this topic will give you a hard time when debugging your code. Boolean arrays occur at various places throughout this book. They are handy and compact tools for avoiding lengthy if constructions and loops when working with arrays. In nearly all large computational projects, sparse matrices become an issue. You saw how these are handled and which related methods are available.
Scientific Computing with Python 3
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Scientific Computing with Python 3
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Overview of this book
Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
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Scientific Computing with Python 3
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Table of Contents (23 chapters)
Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
Free Chapter
Getting Started
Variables and Basic Types
Container Types
Linear Algebra – Arrays
Advanced Array Concepts
Plotting
Functions
Classes
Iterating
Error Handling
Namespaces, Scopes, and Modules
Input and Output
Testing
Comprehensive Examples
Symbolic Computations - SymPy
References
Customer Reviews