[Numpy-discussion] Newbie Question, Probability
faltet at carabos.com
Thu Dec 21 10:45:02 CST 2006
A Dijous 21 Desembre 2006 05:59, A. M. Archibald escrigué:
> On 20/12/06, Alan G Isaac <aisaac at american.edu> wrote:
> > On Wed, 20 Dec 2006, Robert Kern apparently wrote:
> > > We have a full complement of PDFs, CDFs, etc. in scipy.
> > 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...
> This is silly.
> If it were up to me I would rip out much of the fancy features from
> numpy and put them in scipy. It's really not very difficult to
> install, particularly if you don't much care how fast it is, or are
> using (say) a Linux distribution that packages it.
> It seems to me that numpy should include only tools for basic
> calculations on arrays of numbers. The ufuncs, simple wrappers (dot,
> for example). Anything that requires nontrivial amounts of math
> (matrix inversion, statistical functions, generating random numbers
> from exponential distributions, and so on) should go in scipy.
> 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.
> Perhaps an alternative criterion would be "it can go in numpy if it
> has no external requirements". I think this is a mistake, since it
> means users have a monstrous headache figuring out what is in which
> package (for example, some of scipy.integrate depends on external
> tools and some does not). Moreover it damages the performance of
> numpy. For example, dot would be faster (for arrays that happen to be
> matrix-shaped, and possibly in general) if it could use ATLAS' routine
> from BLAS.
> Of course, numpy is currently fettered by the need to maintain some
> sort of compatibility with Numeric and numarray; shortly it will have
> to worry about compatibility with previous versions of numpy as well.
I agree with most of the arguments above, so +1
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
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