[Numpy-discussion] Cross-covariance function

[Pierre Haessig]

Le 26/01/2012 16:50, Pauli Virtanen a écrit :
> the current behavior is not a bug,
I completely agree that numpy.cov(m,y) does what it says !

I (and apparently some other people) are only questioning why there is 
such a behavior ? Indeed, the second variable `y` is presented as "An 
additional set of variables and observations".

This raises for me two different questions :
* What is the use case for such an additional set of variables that 
could just be concatenated to the first set `̀m` ?
* Or, if indeed this sort of integrated concatenation is useful, why 
just add one "additional set" and not several "additional sets" like :
 >>> cov(m, y1, y2, y3, ....) ?

But I would understand that numpy responsibility to provide a stable 
computing API would prevent any change in cov behavior. You have the 
long term experience to judge that. (I certainly don't ;-) )

However, in the case this change is not possible, I would see this 
solution :
* add and xcov function that does what Elliot and Sturla and I 
described, because
* possibly deprecate the `y` 2nd argument of cov because I feel it 
brings more definition complication than real programming benefits

(but I still find that changing cov would lead to a leaner numpy API 
which was my motivation for reacting to Elliot's first message)

Pierre