[Numpy-discussion] Maturing the Matrix class in NumPy
Alan G Isaac
aisaac@american....
Fri Jun 5 16:14:39 CDT 2009
On 6/5/2009 3:49 PM Stéfan van der Walt apparently wrote:
> If the Matrix class is to remain, we need to take the steps
> necessary to integrate it into NumPy properly.
I think this requires a list of current problems.
Many of the problems for NumPy have been addressed over time.
I believe the remaining problems center more on SciPy rather than NumPy.
This requires that users report difficulties.
For example, Jason Rennie says he ran into problems with
scipy.optimize.fmin_cg, although I do not recall him reporting
these (I do recall an optimization problem he reported using
ndarrays). Has he filed a bug report detailing his problem?
> To get going we'll need a list of changes required (i.e. "in an ideal
> world, how would matrices work?").
The key anomaly concerning matrices comes with indexing.
See the introduction here: http://www.scipy.org/MatrixIndexing
However changing this for the current matrix object was rejected
in the last (exhausting) go round.
> There should be a set protocol for
> all numpy functions that guarantees compatibility with ndarrays,
> matrices and other derived classes.
My impression was that this was resolved as follows:
handle all ndarray based objects as arrays (using asarray)
in any NumPy function, but return the subclass when possible.
(E.g., using asmatrix, return a matrix output for a matrix input.)
This seems fine to me.
> Being one of the most vocal proponents of the Matrix class, would you
> be prepared to develop your Matrix Proposal at
> http://scipy.org/NewMatrixSpec further?
I consider my proposal to have the following status: rejected.
I consider the core reason to be: creates a backwards incompatibility.
That was a very long and exhausting discussion that was productive
in laying out the issues, but I do not think we can progress in that
direction.
The existing matrix object is very usable.
It's primary problem is some indexing anomalies,
http://www.scipy.org/MatrixIndexing
and not everyone saw those as problems.
In terms of NumPy functions, I think the asarray/asmatrix
protocol fits the bill. (Altho perhaps I am overlooking
something as a user that is obvious to a developer.)
Cheers,
Alan
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