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  • Book Overview & Buying Learning SciPy for Numerical and Scientific Computing Second Edition
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Learning SciPy for Numerical and Scientific Computing Second Edition

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

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Learning SciPy for Numerical and Scientific Computing Second Edition

Learning SciPy for Numerical and Scientific Computing Second Edition

4.3 (10)
Buy this Book

Overview of this book

This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to SciPy
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1. Introduction to SciPy
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What is SciPy?
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Installing SciPy
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SciPy organization
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How to find documentation
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Scientific visualization
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How to open IPython Notebooks
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Summary
2
2. Working with the NumPy Array As a First Step to SciPy
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2. Working with the NumPy Array As a First Step to SciPy
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Object essentials
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Using datatypes
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Indexing and slicing arrays
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The array object
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Array routines
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Summary
3
3. SciPy for Linear Algebra
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3. SciPy for Linear Algebra
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Vector creation
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Vector operations
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Creating a matrix
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Matrix methods
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Summary
4
4. SciPy for Numerical Analysis
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4. SciPy for Numerical Analysis
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The evaluation of special functions
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Convenience and test functions
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Univariate polynomials
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The gamma function
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The Riemann zeta function
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Airy and Bairy functions
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The Bessel and Struve functions
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Other special functions
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Interpolation
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Regression
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Optimization
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Integration
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Ordinary differential equations
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Lorenz attractors
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Summary
5
5. SciPy for Signal Processing
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5. SciPy for Signal Processing
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Discrete Fourier Transforms
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Signal construction
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Filters
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Summary
6
6. SciPy for Data Mining
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6. SciPy for Data Mining
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Descriptive statistics
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Distributions
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Interval estimation, correlation measures, and statistical tests
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Distribution fitting
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Distances
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Clustering
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Summary
7
7. SciPy for Computational Geometry
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7. SciPy for Computational Geometry
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The structural model of oxides
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A finite element solver for Laplace's equation
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Summary
8
8. Interaction with Other Languages
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8. Interaction with Other Languages
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Interaction with Fortran
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Interaction with C/C++
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Interaction with MATLAB/Octave
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Summary
9
Index
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Index

Chapter 7. SciPy for Computational Geometry

In this chapter, we will be covering the fundamentals of SciPy to develop programs in this very specialized topic: Computational Geometry. Two examples will be used to illustrate the use of SciPy functions in this area. To be able to profit from the first example, you might want to have handy a copy of Computational Geometry: Algorithms and Applications Third Edition, de Berg M., Cheong O., van Kreveld M., and Overmars M., Springer Publishing. The second example, on which the Finite Element Method is used to solve a two-dimensional problem involving the numerical solution of the Laplace Equation, could be followed without trouble with knowledge on the topic described in Introduction to the Finite Element Method, Ottosen N. S. and Petersson H., Prentice Hall.

Let's start by covering the routines in the scipy.spatial module that deal with the construction of triangulations of points in spaces of any dimension, and the corresponding...

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