I'm trying to wrap some C code using cython. The C code can take
inputs in two modes: dense inputs and sparse inputs. For dense inputs
the array indexing is naive. I have wrappers for that. In the sparse
case the matrix entries are typically indexed via names. So, for
example, the library documenta
On Mon, Feb 10, 2014 at 9:01 PM, Alexander Belopolsky wrote:
>
> On Mon, Feb 10, 2014 at 11:31 AM, Nathaniel Smith wrote:
>
>> And in the long run, I
>> think the goal is to move people away from inheriting from np.ndarray.
>>
>
> This is music to my ears, but what is the future of numpy.ma? I
>
On Mon, Feb 10, 2014 at 11:31 AM, Nathaniel Smith wrote:
> And in the long run, I
> think the goal is to move people away from inheriting from np.ndarray.
>
This is music to my ears, but what is the future of numpy.ma? I understand
that numpy.oldnumeric.ma (the older version written without inh
On 2/10/2014 7:39 PM, Pauli Virtanen wrote:
> The issue here is semantics for basic linear algebra operations, such as
> matrix multiplication, that work for different matrix objects, including
> ndarrays.
I'll see if I can restate my suggestion in another way,
because I do not feel you are respo
On Mon, Feb 10, 2014 at 6:11 PM, Charles R Harris wrote:
>
>
>
> On Mon, Feb 10, 2014 at 5:39 PM, Pauli Virtanen wrote:
>
>> 11.02.2014 01:39, josef.p...@gmail.com kirjoitti:
>> [clip]
>> > Almost all the code in scipy.stats and statsmodels starts with
>> np.asarray.
>> > The numpy doc standard
On Mon, Feb 10, 2014 at 5:39 PM, Pauli Virtanen wrote:
> 11.02.2014 01:39, josef.p...@gmail.com kirjoitti:
> [clip]
> > Almost all the code in scipy.stats and statsmodels starts with
> np.asarray.
> > The numpy doc standard has the term `array_like` to indicate things that
> > can be converted to
11.02.2014 01:39, josef.p...@gmail.com kirjoitti:
[clip]
> Almost all the code in scipy.stats and statsmodels starts with np.asarray.
> The numpy doc standard has the term `array_like` to indicate things that
> can be converted to a usable object by ndasarray.
>
> ducktyping could be restricted to
On Mon, Feb 10, 2014 at 6:39 PM, wrote:
>
>
> On Mon, Feb 10, 2014 at 6:29 PM, Pauli Virtanen wrote:
>
>> 11.02.2014 00:31, Alan G Isaac kirjoitti:
>> > On 2/10/2014 5:11 PM, Pauli Virtanen wrote:
>> >> The existence of np.matrix messes up the general agreement on ndarray
>> >> semantics in Pyth
On Mon, Feb 10, 2014 at 6:29 PM, Pauli Virtanen wrote:
> 11.02.2014 00:31, Alan G Isaac kirjoitti:
> > On 2/10/2014 5:11 PM, Pauli Virtanen wrote:
> >> The existence of np.matrix messes up the general agreement on ndarray
> >> semantics in Python. The meaning of very basic code such as
> >>
> >>
11.02.2014 00:31, Alan G Isaac kirjoitti:
> On 2/10/2014 5:11 PM, Pauli Virtanen wrote:
>> The existence of np.matrix messes up the general agreement on ndarray
>> semantics in Python. The meaning of very basic code such as
>>
>> A * B
>> A.sum(0)
>> A[0]
>>
>> where A and B are NxN
Hi,
On Mon, Feb 10, 2014 at 2:33 PM, Pauli Virtanen wrote:
> 11.02.2014 00:17, Matthew Brett kirjoitti:
> [clip]
>> That is a very convincing argument.
>>
>> What would be the problems (apart from code compatibility) in making
>> scipy.sparse use the ndarray semantics?
>
> I'd estimate the effort
11.02.2014 00:17, Matthew Brett kirjoitti:
[clip]
> That is a very convincing argument.
>
> What would be the problems (apart from code compatibility) in making
> scipy.sparse use the ndarray semantics?
I'd estimate the effort it would take to convert scipy.sparse to ndarray
semantics is about a
On 2/10/2014 5:11 PM, Pauli Virtanen wrote:
> The existence of np.matrix messes up the general agreement on ndarray
> semantics in Python. The meaning of very basic code such as
>
> A * B
> A.sum(0)
> A[0]
>
> where A and B are NxN matrices of some sort now depends on the types
>
Hi,
On Mon, Feb 10, 2014 at 2:11 PM, Pauli Virtanen wrote:
> 10.02.2014 23:40, Alan G Isaac kirjoitti:
>> On 2/10/2014 4:28 PM, Pauli Virtanen wrote:
>>> Starting with asarray won't work: sparse matrices are not
>>> subclasses of ndarray.
>>
>> I was focused on the `matrix` object. For this objec
On Mon, Feb 10, 2014 at 1:13 PM, Alan G Isaac wrote:
> Do you mean one must start out with an 'asarray'?
> Or more than that?
>
maybe np.asanyarray()
It's nice, at least in principle for duck-typed functions to return the
type they were handed. And this really is the primary issu ewith np.matr
On Mon, Feb 10, 2014 at 4:42 PM, Alan G Isaac wrote:
> On 2/10/2014 4:40 PM, alex wrote:
>> I really want to remove it
>
> Can you articulate the problem created by its existence
> that leads you to this view?
In my opinion, Pauli has articulated these problems well in this thread.
__
10.02.2014 23:40, Alan G Isaac kirjoitti:
> On 2/10/2014 4:28 PM, Pauli Virtanen wrote:
>> Starting with asarray won't work: sparse matrices are not
>> subclasses of ndarray.
>
> I was focused on the `matrix` object. For this object, an initial
> asarray is all it takes to use array code. (Or ...
Hi,
On Mon, Feb 10, 2014 at 1:52 PM, Charles R Harris
wrote:
>
>
>
> On Mon, Feb 10, 2014 at 2:28 PM, Pauli Virtanen wrote:
>>
>> 10.02.2014 23:13, Alan G Isaac kirjoitti:
>> > On 2/10/2014 4:03 PM, Pauli Virtanen wrote:
>> >> What sparked this discussion (on Github) is that it is not
>> >> poss
On Mon, Feb 10, 2014 at 2:28 PM, Pauli Virtanen wrote:
> 10.02.2014 23:13, Alan G Isaac kirjoitti:
> > On 2/10/2014 4:03 PM, Pauli Virtanen wrote:
> >> What sparked this discussion (on Github) is that it is not
> >> possible to write duck-typed code that works correctly for:
> >
> > Do you mean o
On 2/10/2014 4:40 PM, alex wrote:
> I really want to remove it
Can you articulate the problem created by its existence
that leads you to this view?
Alan Isaac
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On Mon, Feb 10, 2014 at 3:47 PM, Matthew Brett wrote:
> Hi,
>
> On Mon, Feb 10, 2014 at 12:44 PM, Charles R Harris
> wrote:
>>
>>
>>
>> On Mon, Feb 10, 2014 at 1:23 PM, Alan G Isaac wrote:
>>>
>>> On 2/10/2014 3:04 PM, Matthew Brett wrote:
>>> > I teach psychologists and neuroscientists mainly
>
On 2/10/2014 4:28 PM, Pauli Virtanen wrote:
> Starting with asarray won't work: sparse matrices are not subclasses
> of ndarray.
I was focused on the `matrix` object.
For this object, an initial asarray is all it takes to use array code.
(Or ... not?) And it is a view, not a copy.
I don't have
10.02.2014 23:13, Alan G Isaac kirjoitti:
> On 2/10/2014 4:03 PM, Pauli Virtanen wrote:
>> What sparked this discussion (on Github) is that it is not
>> possible to write duck-typed code that works correctly for:
>
> Do you mean one must start out with an 'asarray'? Or more than
> that?
Starting
On 2/10/2014 4:08 PM, Matthew Brett wrote:
> I think the active questions here are:
> * Should we collect the discussion in coherent form somewhere?
> * Should we add something to the np.matrix docstring and if so what?
> * (Pauli's point): to what extent should we try to emulate the np.matrix API.
On 2/10/2014 4:03 PM, Pauli Virtanen wrote:
> What sparked this discussion (on Github) is that it is not possible to
> write duck-typed code that works correctly for:
Do you mean one must start out with an 'asarray'?
Or more than that?
As I detailed in past discussion, the one thing
I really do n
Hi,
On Mon, Feb 10, 2014 at 12:58 PM, wrote:
>
>
> On Mon, Feb 10, 2014 at 3:45 PM, alex wrote:
>>
>> On Mon, Feb 10, 2014 at 2:36 PM, Matthew Brett
>> wrote:
>> > Hi,
>> >
>> > On Mon, Feb 10, 2014 at 6:26 AM, Nathaniel Smith wrote:
>> >> On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
>> >>> H
10.02.2014 22:23, Alan G Isaac kirjoitti:
[clip]
> As far as I have been able to discern, the underlying
> motivation for eliminating the matrix class is that
> some developers want to stop supporting in any form
> the subclassing of numpy arrays. Do I have that right?
What sparked this discussio
On Mon, Feb 10, 2014 at 3:39 PM, wrote:
>
>
> On Mon, Feb 10, 2014 at 3:04 PM, Matthew Brett wrote:
>
>> Hi,
>>
>> On Mon, Feb 10, 2014 at 7:09 AM, Alan G Isaac
>> wrote:
>> [snip]
>> > Just to forestall the usual "just start them with arrays, eventually
>> they'll
>> > be grateful" reply, I wou
On Mon, Feb 10, 2014 at 3:45 PM, alex wrote:
> On Mon, Feb 10, 2014 at 2:36 PM, Matthew Brett
> wrote:
> > Hi,
> >
> > On Mon, Feb 10, 2014 at 6:26 AM, Nathaniel Smith wrote:
> >> On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
> >>> Hello list,
> >>>
> >>> I wrote this mini-nep for numpy but I've
Hi,
On Mon, Feb 10, 2014 at 12:39 PM, wrote:
>
>
> On Mon, Feb 10, 2014 at 3:04 PM, Matthew Brett
> wrote:
>>
>> Hi,
>>
>> On Mon, Feb 10, 2014 at 7:09 AM, Alan G Isaac
>> wrote:
>> [snip]
>> > Just to forestall the usual "just start them with arrays, eventually
>> > they'll
>> > be grateful"
Hi,
On Mon, Feb 10, 2014 at 12:44 PM, Charles R Harris
wrote:
>
>
>
> On Mon, Feb 10, 2014 at 1:23 PM, Alan G Isaac wrote:
>>
>> On 2/10/2014 3:04 PM, Matthew Brett wrote:
>> > I teach psychologists and neuroscientists mainly
>>
>>
>> I must suspect that notebook was not for
>> **undergraduate**
On Mon, Feb 10, 2014 at 2:36 PM, Matthew Brett wrote:
> Hi,
>
> On Mon, Feb 10, 2014 at 6:26 AM, Nathaniel Smith wrote:
>> On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
>>> Hello list,
>>>
>>> I wrote this mini-nep for numpy but I've been advised it is more
>>> appropriate for discussion on the li
On Mon, Feb 10, 2014 at 1:23 PM, Alan G Isaac wrote:
> On 2/10/2014 3:04 PM, Matthew Brett wrote:
> > I teach psychologists and neuroscientists mainly
>
>
> I must suspect that notebook was not for
> **undergraduate** psychology students.
> At least, not the ones I usually meet.
>
> SymPy is grea
On Mon, Feb 10, 2014 at 3:04 PM, Matthew Brett wrote:
> Hi,
>
> On Mon, Feb 10, 2014 at 7:09 AM, Alan G Isaac
> wrote:
> [snip]
> > Just to forestall the usual "just start them with arrays, eventually
> they'll
> > be grateful" reply, I would want to hear that suggestion only from
> someone
> > w
Hi,
On Mon, Feb 10, 2014 at 12:23 PM, Alan G Isaac wrote:
> On 2/10/2014 3:04 PM, Matthew Brett wrote:
>> I teach psychologists and neuroscientists mainly
>
> I must suspect that notebook was not for
> **undergraduate** psychology students.
> At least, not the ones I usually meet.
Well - in this
On 2/10/2014 3:04 PM, Matthew Brett wrote:
> I teach psychologists and neuroscientists mainly
I must suspect that notebook was not for
**undergraduate** psychology students.
At least, not the ones I usually meet.
SymPy is great but for those without background
it is at best awkward. It certainl
Hi,
On Mon, Feb 10, 2014 at 7:09 AM, Alan G Isaac wrote:
[snip]
> Just to forestall the usual "just start them with arrays, eventually they'll
> be grateful" reply, I would want to hear that suggestion only from someone
> who has used it successfully with undergraduates in the social sciences.
I
On Mon, Feb 10, 2014 at 2:49 PM, Matthew Brett wrote:
> Hi,
>
> On Mon, Feb 10, 2014 at 11:44 AM, wrote:
> >
> >
> > On Mon, Feb 10, 2014 at 2:12 PM, eat wrote:
> >>
> >>
> >>
> >>
> >> On Mon, Feb 10, 2014 at 9:08 PM, alex wrote:
> >>>
> >>> On Mon, Feb 10, 2014 at 2:03 PM, eat wrote:
> >>>
On Mon, Feb 10, 2014 at 2:49 PM, Matthew Brett wrote:
> Hi,
>
> On Mon, Feb 10, 2014 at 11:44 AM, wrote:
> >
> >
> > On Mon, Feb 10, 2014 at 2:12 PM, eat wrote:
> >>
> >>
> >>
> >>
> >> On Mon, Feb 10, 2014 at 9:08 PM, alex wrote:
> >>>
> >>> On Mon, Feb 10, 2014 at 2:03 PM, eat wrote:
> >>>
On Mon, Feb 10, 2014 at 10:09 AM, Alan G Isaac wrote:
> On 2/9/2014 5:55 PM, alex wrote:
> > I'm working on the same kinds of problems in scipy development
> > (functions involving sparse matrices and abstract linear operators)
>
>
> And how is numpy's matrix object getting in your way?
> Your in
Hi,
On Mon, Feb 10, 2014 at 11:44 AM, wrote:
>
>
> On Mon, Feb 10, 2014 at 2:12 PM, eat wrote:
>>
>>
>>
>>
>> On Mon, Feb 10, 2014 at 9:08 PM, alex wrote:
>>>
>>> On Mon, Feb 10, 2014 at 2:03 PM, eat wrote:
>>> > Rhetorical or not, but FWIW I'll prefer to take singular value
>>> > decompositi
On Mon, Feb 10, 2014 at 2:12 PM, eat wrote:
>
>
>
> On Mon, Feb 10, 2014 at 9:08 PM, alex wrote:
>
>> On Mon, Feb 10, 2014 at 2:03 PM, eat 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
Hi,
On Mon, Feb 10, 2014 at 6:26 AM, Nathaniel Smith wrote:
> On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
>> Hello list,
>>
>> I wrote this mini-nep for numpy but I've been advised it is more
>> appropriate for discussion on the list.
>>
>> """
>> The ``numpy.matrix`` API provides a low barrier
On Mon, Feb 10, 2014 at 9:08 PM, alex wrote:
> On Mon, Feb 10, 2014 at 2:03 PM, eat 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 t
On Mon, Feb 10, 2014 at 2:03 PM, eat 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).su
On Mon, Feb 10, 2014 at 7:00 PM, alex wrote:
> On Mon, Feb 10, 2014 at 11:27 AM, wrote:
> > How do we calculate the diagonal of the hat matrix without using N by N
> > matrices?
>
> Not sure if this was a rhetorical question or what, but this seems to work
> leverages = np.square(scipy.linalg.q
On Mon, Feb 10, 2014 at 12:16 PM, Nathaniel Smith wrote:
> On Mon, Feb 10, 2014 at 12:02 PM, Matthieu Brucher
> wrote:
>> Yes, but these will be scipy.sparse matrices, nothing to do with numpy
>> (dense) matrices.
>
> Unfortunately when scipy.sparse matrices interact with dense ndarrays
> (e.g.,
On Mon, Feb 10, 2014 at 12:02 PM, Matthieu Brucher
wrote:
> Yes, but these will be scipy.sparse matrices, nothing to do with numpy
> (dense) matrices.
Unfortunately when scipy.sparse matrices interact with dense ndarrays
(e.g., sparse matrix * dense vector), then you always get back
np.matrix obj
Yes, but these will be scipy.sparse matrices, nothing to do with numpy
(dense) matrices.
Cheers,
Matthieu
2014-02-10 Dinesh Vadhia :
> Scipy sparse uses matrices - I was under the impression that scipy sparse
> only works with matrices or have things moved on?
>
>
>
> ___
On Mon, Feb 10, 2014 at 11:27 AM, wrote:
> How do we calculate the diagonal of the hat matrix without using N by N
> matrices?
Not sure if this was a rhetorical question or what, but this seems to work
leverages = np.square(scipy.linalg.qr(X, mode='economic')[0]).sum(axis=1)
http://www4.ncsu.edu
Scipy sparse uses matrices - I was under the impression that scipy sparse only
works with matrices or have things moved on?
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On Mon, Feb 10, 2014 at 11:16 AM, Alexander Belopolsky wrote:
>
> On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
>>
>> On the other hand, it really needs to be deprecated.
>
>
> While numpy.matrix may have its problems, a NEP should list a better
> rationale than the above to gain acceptance.
>
> Pe
On Mon, Feb 10, 2014 at 10:09 AM, Alan G Isaac wrote:
> On 2/9/2014 5:55 PM, alex wrote:
> > I'm working on the same kinds of problems in scipy development
> > (functions involving sparse matrices and abstract linear operators)
>
>
> And how is numpy's matrix object getting in your way?
> Your in
On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
> On the other hand, it really needs to be deprecated.
While numpy.matrix may have its problems, a NEP should list a better
rationale than the above to gain acceptance.
Personally, I decided not to use numpy.matrix in production code about 10
years a
On 2/9/2014 5:55 PM, alex wrote:
> I'm working on the same kinds of problems in scipy development
> (functions involving sparse matrices and abstract linear operators)
And how is numpy's matrix object getting in your way?
Your initial post simply treated the desirability of
deprecation as a given
On Sun, Feb 9, 2014 at 4:59 PM, alex wrote:
> Hello list,
>
> I wrote this mini-nep for numpy but I've been advised it is more
> appropriate for discussion on the list.
>
> """
> The ``numpy.matrix`` API provides a low barrier to using Python
> for linear algebra, just as the pre-3 Python ``input`
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