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SciPy Recipes

You're reading from   SciPy Recipes A cookbook with over 110 proven recipes for performing mathematical and scientific computations

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788291460
Length 386 pages
Edition 1st Edition
Languages
Tools
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Authors (3):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Luiz Felipe Martins Luiz Felipe Martins
Author Profile Icon Luiz Felipe Martins
Luiz Felipe Martins
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting to Know the Tools FREE CHAPTER 2. Getting Started with NumPy 3. Using Matplotlib to Create Graphs 4. Data Wrangling with pandas 5. Matrices and Linear Algebra 6. Solving Equations and Optimization 7. Constants and Special Functions 8. Calculus, Interpolation, and Differential Equations 9. Statistics and Probability 10. Advanced Computations with SciPy

Choosing the solver used to find the solution of equations

How about having the functions for computing equations and finding the solutions? In this section, we will see how to do it.

Getting ready

This is a collection of general-purpose, non-linear multidimensional solvers. These solvers find x for which F(x) = 0. Both x and F can be multidimensional.

Functions

Parameters

newton_krylov(F, xin[, iter, rdiff, method, ...])

Find a root of a function, using Krylov approximation for inverse Jacobian.

anderson(F, xin[, iter, alpha, w0, M, ...])

Find a root of a function, using (extended) Anderson mixing.

General non-linear solvers:

Functions

Parameters

broyden1(F, xin[, iter, alpha, ...])

Find...

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