Learning SciPy for Numerical and Scientific Computing - Second Edition电子书

Learning SciPy for Numerical and Scientific Computing Second Edition

Table of Contents

Learning SciPy for Numerical and Scientific Computing Second Edition

Credits

About the Authors

About the Reviewers

www.PacktPub.com

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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. Introduction to SciPy

What is SciPy?

Installing SciPy

Installing SciPy on Mac OS X

Installing SciPy on Unix/Linux

Installing SciPy on Windows

Testing the SciPy installation

SciPy organization

How to find documentation

Scientific visualization

How to open IPython Notebooks

Summary

2. Working with the NumPy Array As a First Step to SciPy

Object essentials

Using datatypes

Indexing and slicing arrays

The array object

Array conversions

Shape selection/manipulations

Object calculations

Array routines

Routines to create arrays

Routines for the combination of two or more arrays

Routines for array manipulation

Routines to extract information from arrays

Summary

3. SciPy for Linear Algebra

Vector creation

Vector operations

Addition/subtraction

Scalar/Dot product

Cross/Vector product – on three-dimensional space vectors

Creating a matrix

Matrix methods

Operations between matrices

Functions on matrices

Eigenvalue problems and matrix decompositions

Image compression via the singular value decomposition

Solvers

Summary

4. SciPy for Numerical Analysis

The evaluation of special functions

Convenience and test functions

Univariate polynomials

The gamma function

The Riemann zeta function

Airy and Bairy functions

The Bessel and Struve functions

Other special functions

Interpolation

Regression

Optimization

Minimization

Roots

Integration

Exponential/logarithm integrals

Trigonometric and hyperbolic trigonometric integrals

Elliptic integrals

Gamma and beta integrals

Numerical integration

Ordinary differential equations

Lorenz attractors

Summary

5. SciPy for Signal Processing

Discrete Fourier Transforms

Signal construction

Filters

The LTI system theory

Filter design

Window functions

Image interpolation

Morphology

Summary

6. SciPy for Data Mining

Descriptive statistics

Distributions

Interval estimation, correlation measures, and statistical tests

Distribution fitting

Distances

Clustering

Vector quantization and k-means

Hierarchical clustering

Clustering mammals by their dentition

Summary

7. SciPy for Computational Geometry

The structural model of oxides

A finite element solver for Laplace's equation

Summary

8. Interaction with Other Languages

Interaction with Fortran

Interaction with C/C++

Interaction with MATLAB/Octave

Summary

Index