December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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How to do it...
These are some types of differentiation that we will follow in this recipe:
- Numerical differentiation.
- The most basic scheme for numerical differentiation is performed with the central difference formula with uniformly spaced nodes. To maintain symmetry, an odd number of nodes is required to guarantee smaller round-off errors. An implementation of this simple algorithm is available in the scipy.misc module.
For information about the module scipy.misc and enumeration of its basic routines, refer to the online documentation at: http://docs.scipy.org/doc/scipy-0.13.0/reference/misc.html.
- To approximate the first and second derivatives of the polynomial function, for example, f(x) = x5 at x=1 with 15 equally spaced nodes (centered ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.