We, NumPy users, live in exciting times. New NumPy-related developments seem to come
to our attention every week or maybe even daily. When this book was being written, NumPy
Foundation of Open Code for Usable Science was created. The Numba project—NumPy-aware,
dynamic Python compiler using LLVM—was announced. Also, Google added support to their
Cloud product Google App Engine.
In the future, we can expect improved concurrency support for clusters of GPUs and CPUs.
OLAP-like queries will be possible with NumPy arrays.
This is wonderful news, but we have to keep reminding ourselves that NumPy is not alone in
the scientific (Python) software ecosystem. There is Scipy, Matplotlib (a very useful Python
plotting library), IPython (an interactive shell), and Scikits. Outside of the Python ecosystem,
languages such as R, C, and Fortran are pretty popular. We will go into the details of
exchanging data with these environments.
Over 70 interesting recipes for learning the Python open source mathematical library, NumPy
Overview
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Do high performance calculations with clean and efficient NumPy code
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Analyze large sets of data with statistical functions
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Execute complex linear algebra and mathematical computations
In Detail
Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity.
"NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source.
"Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library.
You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects.
This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples.
"NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
What you will learn from this book
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Learn advanced Indexing and linear algebra
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Know reshaping automatically
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Dive into Broadcasting and Histograms
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Profile NumPy code and visualize your profiling results
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Speed up your code with Cython
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Use the array interface to expose foreign memory to NumPy
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Use universal functions and interoperability features
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Learn about Matplotlib and Scipy which is often used in conjunction with Numpy
Approach
Written in Cookbook style, the code examples will take your Numpy skills to the next level.
Who this book is written for
This book will take Python developers with basic Numpy skills to the next level through some practical recipes.
