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

Chapter 4. NumPy Core and Libs Submodules

After covering so many NumPy ufuncs in the previous chapter, I hope you still remember the very core of NumPy, which is the ndarray object. We are going to finish the last important attribute of ndarray: strides, which will give you the full picture of memory layout. Also, it's time to show you that NumPy arrays can deal not only with numbers but also with various types of data; we will talk about record arrays and date time arrays. Lastly, we will show how to read/write NumPy arrays from/to files, and start to do some real-world analysis using NumPy.

The topics that will be covered in this chapter are:

  • The core of NumPy arrays: memory layout
  • Structure arrays (record arrays)
  • Date-time in NumPy arrays
  • File I/O in NumPy arrays