December 2016
Intermediate to advanced
332 pages
6h 2m
English
book
Scientific Computing with Python 3
by Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier
Content preview from Scientific Computing with Python 3Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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.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.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.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.
Chapter 15. Symbolic Computations - SymPy
In this chapter, we will give a brief introduction on using Python for symbolic computations. There is powerful software in the market for performing symbolic computations, for example, MapleTM or MathematicaTM. But sometimes, it might be favorable to make symbolic calculations in the language or framework you are used to. At this stage of this book, we assume that this language is Python, so we seek for a tool in Python - the SymPy module.
A complete description of SymPy - if possible, would fill an entire book, and that is not the purpose of this chapter. Instead, we will stake out a path into this tool by some guiding examples, giving a flavor of the potential of this tool as a complement to NumPy and ...
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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.