NumPy Essentials电子书

NumPy Essentials

NumPy Essentials

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. An Introduction to NumPy

The scientific Python stack

The need for NumPy arrays

Representing of matrices and vectors

Efficiency

Ease of development

NumPy in Academia and Industry

Code conventions used in the book

Installation requirements

Using Python distributions

Using Python package managers

Using native package managers

Summary

2. The NumPy ndarray Object

Getting started with numpy.ndarray

Array indexing and slicing

Memory layout of ndarray

Views and copies

Creating arrays

Creating arrays from lists

Creating random arrays

Other arrays

Array data types

Summary

3. Using NumPy Arrays

Vectorized operations

Universal functions (ufuncs)

Getting started with basic ufuncs

Working with more advanced ufuncs

Broadcasting and shape manipulation

Broadcasting rules

Reshaping NumPy Arrays

Vector stacking

A boolean mask

Helper functions

Summary

4. NumPy Core and Libs Submodules

Introducing strides

Structured arrays

Dates and time in NumPy

File I/O and NumPy

Summary

5. Linear Algebra in NumPy

The matrix class

Linear algebra in NumPy

Decomposition

Polynomial mathematics

Application - regression and curve fitting

Summary

6. Fourier Analysis in NumPy

Before we start

Signal processing

Fourier analysis

Fourier transform application

Summary

7. Building and Distributing NumPy Code

Introducing Distutils and setuptools

Preparing the tools

Building the first working distribution

Adding NumPy and non-Python source code

Testing your package

Distributing your application

Summary

8. Speeding Up NumPy with Cython

The first step toward optimizing code

Setting up Cython

Hello world in Cython

Multithreaded code

NumPy and Cython

Summary

9. Introduction to the NumPy C-API

The Python and NumPy C-API

The basic structure of an extension module

The header segment

The initialization segment

The method structure array

The implementation segment

Creating an array squared function using Python C-API

Creating an array squared function using NumPy C-API

Building and installing the extension module

Summary

10. Further Reading

pandas

scikit-learn

netCDF4

SciPy

Summary