“Guide to NumPy”, written by Travis E. Oliphant, is a complete reference to NumPy (the replacement for Numeric and Numarray). NumPy builds on (and is a successor to) the successful Numeric array object. Its goal is to create the corner-stone for a useful environment for scientific computing.
Book Description
This book only briefly outlines some of the infrastructure that surrounds the basic objects in NumPy to provide the additional functionality contained in the older Numeric package (i.e. LinearAlgebra, RandomArray, FFT). This infrastructure in NumPy includes basic linear algebra routines, Fourier transform capabilities, and random number generators. In addition, the f2py module is described in its own documentation, and so is only briefly mentioned in the second part of the book.
There are also extensions to the standard Python distutils and testing frameworks included with NumPy that are useful in constructing your own packages built on top of NumPy. The central purpose of this book, however, is to describe and document the basic NumPy system that is available under the numpy namespace.
Table of Contents
- Origins of NumPy
- Object Essentials
- The Array Object
- Basic Routines
- Additional Convenience Routines
- Scalar objects
- Data-type (dtype) Objects
- Standard Classes
- Universal Functions
- Basic Modules
- Testing and Packaging
- New Python Types and C-Structures
- Complete API
- How to extend NumPy
- Beyond the Basics
- Using Python as glue
- Code Explanations
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Format(s): PDF
File size: 2.05 MB
Number of pages: 378
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