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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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Summary

In this chapter, we have mastered all the different methods to compute differentiation and integration of functions. We learned that the scipy libraries have very robust routines to compute approximations of all these operations numerically (wrapping efficient Fortran libraries when necessary). We also learned that it is possible to access other libraries in the SciPy stack to perform the operations in a symbolic or an automatic way.

In the next chapter, we will explore the theory and methodology to solve equations or systems of equations, in the context of nonlinear functions, as well as computing extrema for optimization purposes.

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