[Numpy-discussion] Newbie Question, Probability
Mark Janikas
mjanikas at esri.com
Thu Dec 21 10:43:31 CST 2006
Thanks for all the input so far. The only thing that seems odd about
the omission of probability or quantile functions in NumPy is that all
the random number generators are present in RandomArray. At any rate,
hopefully this bit of functionality will be present in the future, but
for now, IMO the library is awesome..... I am used to using R for math
routines, and all my sparse matrix stuff is WAAAAAAY faster using the
Python-NumPy Combo! Thanks to all for their insight,
MJ
-----Original Message-----
From: numpy-discussion-bounces at scipy.org
[mailto:numpy-discussion-bounces at scipy.org] On Behalf Of Sven Schreiber
Sent: Thursday, December 21, 2006 7:10 AM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] Newbie Question, Probability
A. M. Archibald schrieb:
> On 20/12/06, Alan G Isaac <aisaac at american.edu> wrote:
>> This is my "most missed" functionality in NumPy.
>> (For now I feel cannot ask students to install SciPy.)
>> Although it is a slippery slope, and I definitely do not
>> want NumPy to slide down it, I would certainly not complain
>> if this basic functionaltiy were moved to NumPy...
...
> If numpy were to satisfy everyone who says, "I like numpy, but I wish
> it included [their favourite feature from scipy] because I don't want
> to install scipy", numpy would grow to include everything in scipy.
>
Well my package manager just reported something like 800K for numpy and
20M for scipy, so I think we're not quite at the point of numpy taking
over everything yet (if those numbers are actually meaningful, probably
I'm missing something ?).
I would also welcome if some functionality could be moved to numpy if
the size requirements are reasonably small. Currently I try to avoid to
depend on the scipy package to make my programs more portable, and I'm
mostly successful, but not always. The p-value stuff in numpy would be
helpful here, as Alan already said. Now I don't know if that stuff
passes the size criterion, some expert would know that. But if it does,
it would be nice if you could consider moving it over eventually.
Of course you need to strike a balance, and the optimum is debatable.
But again, if scipy is really more than 20 times the size of numpy, and
some frequently used things are not in numpy, is there really an urgent
need to freeze numpy's set of functionality?
just a user's thought,
sven
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