Last minute (this morning) I decided to submit a talk based around some of my more esoteric programming projects, multiple dispatch, pattern matching, strategies. I drew a lot of inspiration from SymPy when I was thinking about these things so if accepted then I'll probably use SymPy heavily for example use cases. Here is the description and abstract.
I'll add a disclaimer to this talk that the ideas contained within it are my own and not necessarily adopted by the SymPy community. As I said, this is mostly about some of my more wacky projects. I'll probably call upon uses of multiple dispatch (if we include it), fu trig simplification with @smichr, and my matrix expressions work with pattern matching (not in master). DescriptionGood solutions to hard problems require both domain and algorithmic expertise. Domain experts know what to do and computer scientists know how to do it well. This talk discusses challenges and experiences trying to reconcile these two groups, particularly within SymPy. It proposes concrete approaches including multiple dispatch, pattern matching, and programmatic strategies. Abstract Good solutions to hard problems require both domain and algorithmic expertise. Domain experts know *what* to do and computer scientists know *how* to do it well. Coordination between the algorithmic and domain programmer is challenging to do well and difficult to scale. It is also arguably one of the most relevant blocks to scientific progress today. This talk draws from experience supporting mathematical programmers in the SymPy project. SymPy is a computer algebra system, a complex problem that requires the graph manipulation algorithms of a modern compiler alongside the mathematics of several PhD theses. SymPy draws from a broad developer base with experienced and novice developers alike and so struggles to maintain a cohesive organized codebase. We approach this development problem by separating software engineering into a collection of small functions, written by domain experts, alongside an abstract control system, written by algorithmic programmers. We facilitate this division with techniques taken from other languages and compiler technologies. Notably we motivate the use of a few general purpose libraries for multiple dispatch, pattern matching, and programmatic control. On Mon, Mar 31, 2014 at 9:32 AM, Matthew Rocklin <[email protected]> wrote: > I like that you emphasized the utility for numerics, I think that this is > likely to be a selling point for the SciPy crowd. I think that it's > correct to inform the reader about what symbolics are but I think that the > first couple of sentences (which do this) could be stronger/more direct. > Right now they sound conversational. It's not clear to me how to fix this > though. > > Maybe start with something like "SymPy is a computer algebra system. It > provides easy access to a wealth of automated mathematics that helps > programmers to reason about their problem producing more clear and > efficient numeric solutions." and then go into what symbolics are? > > I would cut the top bullet point, e.g. > > - Why you should care about symbolic mathematics, even if you are only > interested in doing numerics. > - How symbolic mathematics can help you solve problems more effectively > > I have a pretty cynical view about people when they're reading text though > (perhaps this comes from teaching freshmen :)) As a result sentences that > carry more than one idea seem dirty to me. > > Hope this helps, > -Matt > > > On Sat, Mar 29, 2014 at 6:01 PM, Aaron Meurer <[email protected]> wrote: > >> 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<https://groups.google.com/d/msgid/sympy/CAKgW%3D6K3OmDsdApN%3DOEvFrRQ4ohEQ1npVfwgUsyxd-K-TLaLOA%40mail.gmail.com?utm_medium=email&utm_source=footer> >> . >> For more options, visit https://groups.google.com/d/optout. >> > > -- 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/CAJ8oX-Ei01ZAgWSJmb2Cdm6Q%2BOovh4L4C25c7p2PwQc2shB5qw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
