NumPyEssentials - (EPUB全文下载)

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书籍内容：

NumPy Essentials
Table of Contents
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 ............

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