[Numpy-discussion] deprecate numpy.matrix

josef.pktd at gmail.com josef.pktd at gmail.com
Mon Feb 10 14:44:16 EST 2014


On Mon, Feb 10, 2014 at 2:12 PM, eat <e.antero.tammi at gmail.com> wrote:

>
>
>
> On Mon, Feb 10, 2014 at 9:08 PM, alex <argriffi at ncsu.edu> wrote:
>
>> On Mon, Feb 10, 2014 at 2:03 PM, eat <e.antero.tammi at gmail.com> wrote:
>> > Rhetorical or not, but FWIW I'll prefer to take singular value
>> decomposition
>> > (u, s, vt= svd(x)) and then based on the singular values s I'll
>> estimate a
>> > "numerically feasible rank" r. Thus the diagonal of such hat matrix
>> would be
>> > (u[:, :r]** 2).sum(1).
>>
>> It's a small detail but you probably want svd(x, full_matrices=False)
>> to avoid anything NxN.
>>
> Indeed.
>

I meant the entire diagonal not the trace of the projection matrix.

My (not articulated) thought was that I use element wise multiplication
together with dot products instead of the three dot products, however
elementwise algebra is not very common in linear algebra based textbooks.

The question is whether students and new user coming from `matrix`
languages can translate formulas into code, or just copy formulas to code.
(It took me a while to get used to numpy and take advantage of it's
features coming from GAUSS and Matlab.)

OT since the precense or absence of matrix in numpy doesn't affect me.

Josef


>
> Thanks,
> -eat
>
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