[SciPy-Dev] Q-function

[Eran Hof]

Thanks Jose for your kind message.

Indeed you are right. However, if there is a place for erf definition in
the special functions of scipy, why not the Q thing?

Even if not, maybe there is a place to add a note in the documentations.
The trivial thing one new to scipy will do is to search for Q-function and
then if not for erf or erfc. At least, this would be done by an immigrant
from Matlab. I am rather new to scipy and just now learned from you the
gizmo of the norm object (a really cool one, thanks a lot for your message).

I must add that even in stackoverflow when searching for Q function in
python I did not tackle with these sf and isf methods (maybe I'll post a
question and you'll post the answer :-)).







On Wed, Feb 17, 2016 at 1:56 PM, José Vinícius <josevinicius at iecom.org.br>
wrote:

> From the Wikipedia page, we see that the Q-function is equal to the
> Gaussian Survival function (scipy.stats.norm.sf) as well.
>
> CVLattes: http://lattes.cnpq.br/3267230342393209
>
> On Wed, Feb 17, 2016 at 4:54 AM, Eran Hof <eran.hof at gmail.com> wrote:
>
>> Dear scipy devs
>>
>> If I may suggest, there is an interest in adding a new error function to
>> the scipy special functions. The Q-function (see please,
>> https://en.wikipedia.org/wiki/Q-function). This function is of great
>> interest and much in use within the communication engineering and error
>> correcting coding communities.
>>
>> There is a 1:1 mapping from Q-function to erf function. However, in
>> engineering, in contrast to statistics, most text book use the Q-function
>> instead and this is the very first function a new to python engineer will
>> try to look for.
>>
>> Also, the implementation is so fast, as Q(x) = 0.5 - 0.5 * erf (x /
>> sqrt(2)). So why not having this function aboard? It will be used
>> immediately by every communication engineer that adopts the scipy instead
>> of Matlab.
>>
>> Also, inverse is easily implemented as well since Qinv(y) = sqrt(2)
>> erfinv(1-2y).
>>
>> I think this small contribution may be of great service.
>>
>> Your comments are much appreciated. Thanks.
>>
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>>
>
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