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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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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
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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 1. Introduction to SciPy

There is no doubt that the labor of scientists in the twenty-first century is more comprehensive and interdisciplinary than in previous generations. Members of scientific communities connect in larger teams and work together on mission-oriented goals and across their fields. This paradigm on research is also reflected in the computational resources employed by researchers. No longer are researchers restricted to one type of commercial software, operating system, or vendor, but inspired by open source contributions made available and tested by research institutions and open source communities; research work often spans over various platforms and technologies.

This book presents the highly-recognized open source programming environment till date — a system based on two libraries of the computer language Python: NumPy and SciPy. In the following sections, we will guide you through examples from science and engineering on the usage of this system.

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Learning SciPy for Numerical and Scientific Computing Second Edition
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