http://www.evanmiller.org/mathematical-hacker.html

I reference that blog post pretty often.  I fully intend to reference it
again in my talk (if it is accepted).

The interesting thing about the Factorial / Gamma / loggamma example is
that to find the solution you need to find someone who knows both that n! =
Gamma(n+ 1) *and* who knows that a loggamma routine is commonly found in
lower level languages.  Those bits of information are usually held by
different experts.  Ondrej said "Of course, that's obvious" when I first
reposted the article on G+.

You're right that this is similar to my last talk.  The last one though was
mostly about an application (numerical linear algebra).  I actually want to
talk a bit more about the philosophy and some of the more abstract tools
that people might actually use.  Your first impression is a valuable one
though, I should go through my last talk and make sure that I'm not
repeating too much that shouldn't be repeated.


On Mon, Mar 31, 2014 at 6:03 PM, Aaron Meurer <asmeu...@gmail.com> wrote:

> That's a good point. One of the nicest things about symbolics, when you
> can get it, is that it can make things drastically more efficient by doing
> mathematical simplifications. Evaluating integrals symbolically is a nice
> example of this (especially for SymPy, which has some pretty nice
> algorithms to compute definite integrals).
>
> I'm reminded of a popular blog post (I can't find a link right now) about
> how know math is important for programmers. It has the example of how all
> these programming languages show how they they compute factorial, and how
> tail recursion can make it linear or whatever, but the actual best way to
> compute it is to use loggamma, which gives the answer in constant time.
>
> Aaron Meurer
>
>
> On Mon, Mar 31, 2014 at 7:51 PM, Tim Lahey <tim.la...@gmail.com> wrote:
>
>>
>>
>> On 31 Mar 2014, at 20:29, Aaron Meurer wrote:
>>
>>  On Mon, Mar 31, 2014 at 11:32 AM, Matthew Rocklin <mrock...@gmail.com
>>> >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.
>>>>
>>>>
>>> Yes, this was very intentional. I may need some help gathering up some
>>> nice
>>> motivating examples if this is accepted.
>>>
>>
>> One motivating example for me is the integration of products of functions
>> over areas and volumes. For finite elements, you'll get products of pairs
>> of trial functions (usually polynomials). It's even more useful for
>> products of trig functions. Performing the integration of any of theses is
>> easy enough with numerical integration, but it's much more efficient to
>> calculate the integrals symbolically and then perform the evaluation for
>> each element.
>>
>> Cheers,
>>
>> Tim.
>>
>>
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