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Mastering SciPy

You're reading from   Mastering SciPy Implement state-of-the-art techniques to visualize solutions to challenging problems in scientific computing, with the use of the SciPy stack

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781783984749
Length 404 pages
Edition 1st Edition
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Authors (2):
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Francisco Javier Blanco-Silva Francisco Javier Blanco-Silva
Author Profile Icon Francisco Javier Blanco-Silva
Francisco Javier Blanco-Silva
Francisco Javier B Silva Francisco Javier B Silva
Author Profile Icon Francisco Javier B Silva
Francisco Javier B Silva
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Toc

Analytic approximation methods


Analytic approximation methods try to compute approximations to the exact solutions on suitable domains, in the form of truncated series expansions over a system of basis functions. In the SciPy stack, we have an implementation based on the Taylor series, through the routine odefun in the module sympy.mpmath.

Note

mpmath is a Python library for arbitrary-precision floating-point arithmetic, hosted inside the sympy module. Although it is independent of the numpy machinery, they both work well together.

For more information about this library, read the official documentation at http://mpmath.org/doc/current/.

Let's see it in action, first with our trivial example y'(t) = y(t), y(0) = 1. The key here is to assess the speed and the accuracy of the approximation, as compared to the actual solution in the interval [0, 1]. Its syntax is very simple, we assume the equation is always in the form of y' = F, and we provide the routine odefun with this functional F and the...

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