Here is the detailed abstract I have so far for a talk for SciPy. Any suggestions are welcome. The deadline is April 1 (probably 5 PM central or thereabouts). I roughly based it on the matplotlib talk from last year http://conference.scipy.org/scipy2013/presentation_detail.php?id=211.
Symbolic computation deals with manipulating mathematical expression symbolically (as opposed to numerically). For instance, representing sqrt(2) without evaluating it is symbolic: representing 1.41421 is numeric. Most software that deals with mathematical expressions symbolically are called computer algebra systems, or CASs for short. SymPy is a computer algebra system written entirely in Python. In this talk, we will look at - Why you should care about symbolic mathematics. Even if you are only interested in doing numerics, how can symbolic mathematics help you to solve your problems more efficiently and/or effectively? - Some of the design decisions that have guided SymPy, such as why we chose Python to write SymPy, and the importance of being able to use SymPy as a library. - How to solve some basic problems in SymPy. - How to interface SymPy with popular numeric libraries, like NumPy. Additionally, we will look at the most interesting recent developments of SymPy, and will also discuss some of our plans for the future. Finally, we will discuss some of what has made SymPy a success, both as a software product, and as a community. Aaron Meurer -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CAKgW%3D6K3OmDsdApN%3DOEvFrRQ4ohEQ1npVfwgUsyxd-K-TLaLOA%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
