Learning SciPy for Numerical and Scientific Computing by G., Sergio J. Rojas -- Read -- Imperial Library of Trantor

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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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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