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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

History

NumPy is based on its predecessor Numeric. Numeric was first released in 1995 and has deprecated status now. Neither Numeric nor NumPy made it into the standard Python library for various reasons. However, you can install NumPy separately, which will be explained in Chapter 1, NumPy Quick Start.

In 2001, a number of people inspired by Numeric created SciPy, an open source scientific computing Python library that provides functionality similar to that of MATLAB, Maple, and Mathematica. Around this time, people were growing increasingly unhappy with Numeric. Numarray was created as an alternative to Numeric. That is also deprecated now. It was better in some areas than Numeric, but worked very differently. For that reason, SciPy kept on depending on the Numeric philosophy and the Numeric array object. As is customary with new latest and greatest software, the arrival of Numarray led to the development of an entire ecosystem around it, with a range of useful tools.

In 2005, Travis Oliphant, an early contributor to SciPy, decided to do something about this situation. He tried to integrate some of Numarray's features into Numeric. A complete rewrite took place, and it culminated in the release of NumPy 1.0 in 2006. At that time, NumPy had all the features of Numeric and Numarray, and more. Tools were available to facilitate the upgrade from Numeric and Numarray. The upgrade is recommended since Numeric and Numarray are not actively supported any more.

Originally, the NumPy code was a part of SciPy. It was later separated and is now used by SciPy for array and matrix processing.

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