[Numpy-discussion] Uncomfortable with matrix change

Bruce Southey bsouthey@gmail....
Fri May 9 09:51:54 CDT 2008


Charles R Harris wrote:
>
>
> On Fri, May 9, 2008 at 7:43 AM, Travis Oliphant <teoliphant@gmail.com 
> <mailto:teoliphant@gmail.com>> wrote:
>
>
>     Hi all,
>
>     I'm having trouble emailing this list from work, so I'm using a
>     different email address.
>
>     After Nathan Bell's recent complaints, I'm a bit more
>     uncomfortable with
>     the matrix change to scalar indexing.   It does and will break code in
>     possibly hard-to-track down ways.   Also, Nathan has been a *huge*
>     contributor to the Sparse matrix in scipy and so I value his opinion
>     about the NumPy matrix.  One of my goals is to have those two objects
>     work together a bit more seamlessly.
>
>     So, I think we need to:
>
>     1) Add a warning to scalar access
>     2) Back-out the change and fix all the places where NumPy assumes
>     incorrectly that the number of dimensions reduce on
>     PySequence_GetItem.
>
>
> -1.
>
> That said, the basic mistake is probably making Matrix a subclass of 
> ndarray, as it fails the "is a" test. There really aren't that many 
> places where inheritance is the right choice and  numpy itself wasn't 
> designed as a base class: it lacks a specification of what functions 
> can be "virtual" and is probably too big.
>
> I vote that we bring Nathan into the conversation and see how upset he 
> really is. Speaking for myself, I sometimes get angry upfront when 
> specifications change unexpectedly underfoot but then settle down and 
> find that it isn't all that bad. Being caught by surprise is probably 
> half the problem.
>
> Chuck
>
>
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>   
Hi,
+1

The prime reason is not whether or not it is a bad/good idea but because 
the actual change was introduced so late in the development of 1.0.5/1.1 
process. A lesser reason is that gives people like Nathan time to change 
their code to match the pending release. Unfortunately the other problem 
with this change is that any user now has to be careful of which NumPy 
version is being used. The result is that backwards compatibility is now 
broken in what was originally going to be a minor release.

Following Tim Hochberg's email on changing histogram, I  think that for 
at least NumPy version 1.1 that scalar indexing should provide a 
'PendingDeprecationWarning' or a 'DeprecationWarning' with the actual 
change happening in 1.2 or later.

Regards
Bruce


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