December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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How it works...
In [6]: p = np.poly1d([1,0,0,0,0,0]); \ ...: print (p) 51 xIn [7]: np.polyder(p,1)(1.0)In [7]: p.deriv()(1.0)Out[7]: 5.0 Out[7]: 5.0 In [8]: np.polyder(p,2)(1.0)In [8]: p.deriv(2)(1.0)Out[8]: 20.0Out[8]: 20.0
Symbolic differentiation is another way to achieve exact results:
In [9]: from sympy import diff, symbolsIn [10]: x = symbols('x', real=True)In [11]: diff(x**5, x)In [12]: diff(x**5, x, x)Out[11]: 5*x**4Out[12]: 20*x**3In [13]: diff(x**5, x).subs(x, 1.0) Out[13]: 5.00000000000000In [14]: diff(x**5, x, x).subs(x, 1.0)Out[14]: 20.0000000000000
Note the slight improvement (both in notation and simplicity of coding) when we differentiate more involved functions than simple polynomials. For example, for g(x) = e-xsinx at ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.