Book Image

NumPy Essentials

By : Leo (Liang-Huan) Chin, Tanmay Dutta, Shane Holloway
Book Image

NumPy Essentials

By: Leo (Liang-Huan) Chin, Tanmay Dutta, Shane Holloway

Overview of this book

In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features.
Table of Contents (16 chapters)
NumPy Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Setting up Cython


Cython is a compiler that converts Python code with the type definition to C code, which still runs in the Python environment. The final output is native machine code, which runs much faster than the bytecode produced by Python. The magnitude of speed-up for Python code is more evident in code that heavily uses loops. In order to compile C code, the first prerequisite is to have a C/C++ compiler such as gcc (Linux) or mingw (Windows) installed on the computer.

The second step is to install Cython. Cython comes just like any other library with a Python module and you can install it using any of your preferred methods (pip, easy_install, and so on). Once these two steps are done, you can test your setup by just trying to call Cython from the shell. If you get an error message, then you have missed the second step and you need to reinstall Cython or download the TAR archive from the Cython official website (http://cython.org/#download), then run the following command from the...