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

netCDF4


netCDF4 is the fourth version of the netCDF library that's implemented on top of HDF5 (Hierarchical Data Format, designed to store and organize large amounts of data), which makes it possible to manage extremely large and complex multidimensional data. The greatest advantage of netCDF4 is that it is a completely portable file format with no limit on the number or size of data objects in a collection, and it's appendable while being archivable as well. Many scientific research organizations use it for data storage. Python also has an interface to access and create this type of data format.

You can download and install the module from its official documentation page at http://unidata.github.io/netcdf4-python/, or clone it from its GitHub repository at https://github.com/Unidata/netcdf4-python. It's not included in the standard Python Scientific distribution, but it's built into NumPy and can build with Cython (this is recommended but not required).

For the following example, we are going...