[Numpy-discussion] Deprecating matrices.

[Ralf Gommers]

On Sat, Jan 7, 2017 at 2:52 PM, Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
> On Fri, Jan 6, 2017 at 6:37 PM, <josef.pktd at gmail.com> wrote:
>
>>
>>
>>
>> On Fri, Jan 6, 2017 at 8:28 PM, Ralf Gommers <ralf.gommers at gmail.com>
>> wrote:
>>
>>>
>>>
>>> On Sat, Jan 7, 2017 at 2:21 PM, CJ Carey <perimosocordiae at gmail.com>
>>> wrote:
>>>
>>>>
>>>> On Fri, Jan 6, 2017 at 6:19 PM, Ralf Gommers <ralf.gommers at gmail.com>
>>>> wrote:
>>>>
>>>>> This sounds like a reasonable idea. Timeline could be something like:
>>>>>
>>>>> 1. Now: create new package, deprecate np.matrix in docs.
>>>>> 2. In say 1.5 years: start issuing visible deprecation warnings in
>>>>> numpy
>>>>> 3. After 2020: remove matrix from numpy.
>>>>>
>>>>> Ralf
>>>>>
>>>>
>>>> I think this sounds reasonable, and reminds me of the deliberate
>>>> deprecation process taken for scipy.weave. I guess we'll see how successful
>>>> it was when 0.19 is released.
>>>>
>>>> The major problem I have with removing numpy matrices is the effect on
>>>> scipy.sparse, which mostly-consistently mimics numpy.matrix semantics and
>>>> often produces numpy.matrix results when densifying. The two are coupled
>>>> tightly enough that if numpy matrices go away, all of the existing sparse
>>>> matrix classes will have to go at the same time.
>>>>
>>>> I don't think that would be the end of the world,
>>>>
>>>
>>> Not the end of the world literally, but the impact would be pretty
>>> major. I think we're stuck with scipy.sparse, and may at some point will
>>> add a new sparse *array* implementation next to it. For scipy we will have
>>> to add a dependency on the new npmatrix package or vendor it.
>>>
>>
>> That sounds to me like moving maintenance of numpy.matrix from numpy to
>> scipy, if scipy.sparse is one of the main users and still depends on it.
>>
>
Maintenance costs are pretty low, and are partly still for numpy (it has to
keep subclasses like np.matrix working. I'm not too worried about the
effort. The purpose here is to remove np.matrix from numpy so beginners
will never see it. Educating sparse matrix users is a lot easier, and there
are a lot less such users.


> What I was thinking was encouraging folks to use `arr.dot(...)` or `@`
> instead of `*` for matrix multiplication, keeping `*` for scalar
> multiplication.
>

I don't think that change in behavior of `*` is doable.


> If those operations were defined for matrices,
>

Why if? They are defined, and work as expected as far as I can tell.


> then at some point sparse could go to arrays and it would not be
> noticeable except for the treatment of 1-D arrays -- which admittedly might
> be a bit tricky.
>

I'd like that to be feasible, but especially given that any such change
would not break code but rather silently change numerical values, it's
likely not a healthy idea.

Ralf
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