Re: [Numpy-discussion] Windows wheels, built, but should we deploy?

[Carl Kleffner]

+1 from me. I could prepare scipy builds based on these numpy builds.

Carl

2016-03-05 19:40 GMT+01:00 Matthew Brett :

> Hi,
>
> On Fri, Mar 4, 2016 at 8:40 PM, Nathaniel Smith  wrote:
> > On Fri, Mar 4, 2016 at 7:30 PM,   wrote:
> > [...]
> >> AFAIK, numpy doesn't provide access to BLAS/LAPACK. scipy does.
> statsmodels
> >> is linking to the installed BLAS/LAPACK in cython code through scipy.
> So far
> >> we haven't seen problems with different versions. I think scipy
> development
> >> works very well to isolate linalg library version specific parts from
> the
> >> user interface.
> >
> > Yeah, it should be invisible to users of both numpy and scipy which
> > BLAS/LAPACK is in use under the hood.
>
> My impression is that the general mood here is positive, so I plan to
> deploy these wheels to pypi on Monday, with the change to the pypi
> text.   Please do let me know if there are any strong objections.
>
> Cheers,
>
> Matthew
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Re: [Numpy-discussion] GSoC?

[Sebastian Berg]

On Fr, 2016-03-04 at 21:20 +, Pauli Virtanen wrote:
> Thu, 11 Feb 2016 00:02:52 +0100, Ralf Gommers kirjoitti:
> [clip]
> > OK first version:
> > https://github.com/scipy/scipy/wiki/GSoC-2016-project-ideas I kept
> > some
> > of the ideas from last year, but removed all potential mentors as
> > the
> > same people may not be available this year - please re-add
> > yourselves
> > where needed.
> > 
> > And to everyone who has a good idea, and preferably is willing to
> > mentor
> > for that idea: please add it to that page.
> 
> I probably don't have bandwidth for mentoring, but as the Numpy 
> suggestions seem to be mostly "hard" problems, we can add another 
> one:
> 
> ## Dealing with overlapping input/output data
> 
> Numpy operations where output arrays overlap with 
> input arrays can produce unexpected results.
> A simple example is
> ```
> x = np.arange(100*100).reshape(100,100)
> x += x.T# <- undefined result!
> ```
> The task is to change Numpy so that the results
> here become similar to as if the input arrays
> overlapping with output were separate (here: `x += x.T.copy()`).
> The challenge here lies in doing this without sacrificing 
> too much performance or memory efficiency.
> 
> Initial steps toward solving this problem were taken in
> https://github.com/numpy/numpy/pull/6166
> where a simplest available algorithm for detecting
> if arrays overlap was added. However, this is not yet
> utilized in ufuncs. An initial attempt to sketch what 
> should be done is at https://github.com/numpy/numpy/issues/6272
> and issues referenced therein.
> 

Since I like the idea, I copy pasted it into the GSoC project ideas
wiki.

- Sebastian


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