And regarding assumptions I agree with everything that you said.

On Mon, Mar 31, 2014 at 8:14 PM, Matthew Rocklin <[email protected]> wrote:

> 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 <[email protected]> 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 <[email protected]> wrote:
>>
>>>
>>>
>>> On 31 Mar 2014, at 20:29, Aaron Meurer wrote:
>>>
>>>  On Mon, Mar 31, 2014 at 11:32 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.
>>>>>
>>>>>
>>>> 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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