Wed, 09 Sep 2009 13:08:22 +0200, Ruben Salvador wrote:
Perfect! Thank you very much :D
It's not obvious, though...I think I should read more deeply into
Python/NumPy...but for the use I'm giving to it...
Anyway, I thought the pythonic way would be faster, but after trying
with a size
in your CFLAGS. Just
unset CFLAGS
or so before compilation. Yes, comma at the end of enum list is not
strictly valid C89, although it is valid C99 and already passes for most
compilers.
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su, 2009-09-13 kello 01:47 +0300, Pauli Virtanen kirjoitti:
[clip]
The error you get from the comma at the end of the enum must be because
you have
-pedantic -Werror
in your CFLAGS. Just
unset CFLAGS
or so before compilation. Yes, comma at the end of enum list
Mon, 14 Sep 2009 09:08:34 +0200, Mads Ipsen wrote:
[clip]
Well, I don't know you consider this as a valid argument, but to me its
a matter of removing a single comma, which will make the source less
sensitive to compilers and compiler flags.
That's done.
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to apply
buttons, to flag those changes that are better than SVN.
Also, check that no unwanted or dangerous code (eg. careless handling of
temporary files, etc) is added to the examples -- they may eventually be
executed after committed to SVN.
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.
The work scales linearly with the size of the diff to SVN, so it's not
extremely bad. Of course, it's a bit of a work to go through hundreds of
potential docstrings in one sitting.
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-overhead, especially as there is no completely reliable
way to detect when a new page is moved, or just new.
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.
Also, avoid touching git-svn as much as possible. If you want to
preserve interoperability, git-svn dcommit to SVN always from a
separate commit branch, to which you cherry-pick changes from the branch
you use to collaborate. This is because git-svn rewrites the commits you
dcommit to SVN.
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. If the documentation says the opposite, it's wrong.
That it's the closest base also causes crashes when the base chain
becomes longer than the stack limit.
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http
that the immediate base is alive afterwards, but that seems unlikely, so
I believe there's no reason not to make this change.
Some (bad) code might be broken if this was changed, for example
y = x[::-1]
y.base is x
but in practice this is probably negligible.
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your module.
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` extension is not enabled, so the testcode::
etc. directives are not available. I'm not sure if it should be enabled
-- it would be cleaner to just replace the testcode:: stuff with the
ordinary example markup.
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Mon, 21 Sep 2009 18:49:47 -0700, Fernando Perez wrote:
On Mon, Sep 21, 2009 at 11:32 AM, Pauli Virtanen p...@iki.fi wrote:
The `sphinx.ext.doctest` extension is not enabled, so the testcode::
etc. directives are not available. I'm not sure if it should be enabled
-- it would be cleaner
extension and its support for those.
What Fernando said about them being more clumsy to write and copy than
separate code directives is of course true. I wonder if there's a
technical fix that could be made in Sphinx, at least for HTML, to correct
this...
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:
Please file a bug ticket in the Trac, thanks!
Here is a simpler way, although one more difficult to accidentally:
a = numpy.frombuffer(A, dtype='S1')
a.flags.writeable = True
b = A
a[0] = B
b
'B'
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somehow, not going through strings. If not, then a copy can't
be avoided.
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to, 2009-09-24 kello 11:51 -0600, Charles R Harris kirjoitti:
Would it be appropriate to add a class similar to poly but instead
using chebyshev polynomials? That is, where we currently have
[clip]
Yes, I think. scipy.special.orthogonal would be the best place for this,
I think. Numpy would
to, 2009-09-24 kello 14:31 -0500, Robert Kern kirjoitti:
On Thu, Sep 24, 2009 at 14:18, Pauli Virtanen p...@iki.fi wrote:
As a side note, should the cheby* versions of `polyval`, `polymul` etc.
just be dropped to reduce namespace clutter? You can do the same things
already within just class
to, 2009-09-24 kello 13:53 -0600, Charles R Harris kirjoitti:
[clip]
I was thinking of storing the chebyshev internally as the values at
the chebyschev points. This makes multiplication, differentiation and
such quite easy (resample and multiply/divide appropriatately). Its
equivalent to
]
KeyError: 'numbered'
No ideas. I think I've seen KeyErrors before, but not from inside
docutils.
My only guess would be to remove the build directory and try again. If
that does not help, I'd look into if there's some known issue with the
current version of Sphinx's hg branch.
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docstring as numpy.transpose. So it would be very helpful to first
correct the numpy.array.transpose documentation.
numpy.numarray.transpose is numpy.transpose, so fixing this would involve
implementing the numarray-style transpose, too.
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the main problem becomes a wontfix.
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Tue, 29 Sep 2009 09:53:40 -0700, Christopher Barker wrote:
[clip]
How can I identify -0.0?
signbit
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if there is some way to
do some of these as a generic 'mixin'?)
The usual approach is to use __getattr__, to forward many routines with
little extra work.
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by Numpy and cannot be
modified.
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didn't commit yet. Mostly, they can be fixed by adding necessary
entries to add_newdocs.py. However, some of these may be objects
assigning docstrings to which may be technically difficult and requires
larger changes. The second error may also indicate a bug in patch
generation.
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'sphinx.ext.autodoc', 'numpydoc' to extensions ...
$ cp /some/path/modulename.py modulename.py
$ vi index.rst
...
add
.. automodule:: modulename
:members:
...
$ make PYTHONPATH=$PWD html
Could be automated.
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not to use Google Groups. IMO, gmane.org offers an
equivalent if not superior service.
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of this for avoiding unnecessary copies in
this scenario.
I suppose this kind of check is easiest to do at compile-time, and
defining a -DFORCE_ALIGNED? This wouldn't cause performance penalties for
those architectures for which they are not necessary.
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hooks into sphinx.ext.autodoc's docstring mangling. So if you
just need to have docstrings formatted, you can use Sphinx's auto*::
directives.
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meant the stuff output by default to class docstrings. Currently,
there's no way to turn this off, unfortunately. It seems there should be,
though...
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Mon, 26 Oct 2009 08:15:51 -0400, Neal Becker wrote:
This link:
http://docs.scipy.org/doc/scipy/reference/generated/
scipy.stats.var.html#scipy.stats.var
gives 500 internal server error
Now that's strange. It's a static page.
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Mon, 26 Oct 2009 14:26:20 -0400, Michael Droettboom wrote:
I know David Cournapeau has done some work on using gcov for coverage
with Numpy.
Unaware of this, (doh! -- I should have Googled first), I wrote a small
C code-coverage tool built on top of valgrind's callgrind tool, so it
problems is scipy.linalg.eig or numpy.linalg.eig, and, much less likely,
scipy.special.gamma. The former are thin wrappers around LAPACK
routines.)
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the C99 functions with our npy_math implementations.
This'd be great for scipy.special.
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Fri, 30 Oct 2009 18:34:07 +0900, David Cournapeau wrote:
[clip]
Actually, I am in the process of cleaning my numpy branches for review,
and intend to push them into svn as fast as possible. Complex is pretty
high on the list.
Great!
The missing piece in complex support in npymath is mostly
pe, 2009-10-30 kello 18:57 +0900, David Cournapeau kirjoitti:
[clip: struct return values]
Is this a problem in practice ? If two compilers differ in this,
wouldn't they have incompatible ABI ?
Yep, it would be an incompatible ABI. I don't really know how common
this in practice -- but there
what to do.
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12.10.2014, 20:19, Mads Ipsen kirjoitti:
Is there any way for me to detect (on the Python side) that transpose()
has been invoked on the matrix, and thereby only do the copy operation
when it really is needed?
The correct way to do this is to, either:
In your C code check
12.10.2014, 22:16, Eric Firing kirjoitti:
On 2014/10/12, 8:29 AM, Pauli Virtanen wrote:
12.10.2014, 20:19, Mads Ipsen kirjoitti:
Is there any way for me to detect (on the Python side) that transpose()
has been invoked on the matrix, and thereby only do the copy operation
when it really
there with complex inout arrays, and I think no-one
uses special aligned allocators...
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.
Source tarballs and full release notes are available at
https://sourceforge.net/projects/scipy/files/SciPy/0.15.0b1/
Binary installers should also be up soon.
Best regards,
Pauli Virtanen
-
SciPy 0.15.0 is the culmination of 6 months of hard work
that is out there.
Everyone who uses double complex, intent(inout) in their f2py wrapped
code will start getting random exceptions on Windows. Users of double
complex, intent(in) pay a performance penalty.
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15.12.2014, 02:12, Stefan van der Walt kirjoitti:
Since the topic of context managers recently came up, what do you think
of adding a context manager for seterr?
with np.seterr(divide='ignore'):
frac = num / denom
There's this:
with np.errstate(divide='ignore'):
...
with numpy relaxed
strides
- - gh-4225 Off-by-one error in PPoly shape checks
- - gh-4248 Fix issue with incorrect use of closure for slsqp
Source tarballs and binaries are available at
https://sourceforge.net/projects/scipy/files/SciPy/0.14.1/
Best regards,
Pauli Virtanen
-BEGIN PGP SIGNATURE
it is
available again in Scipy 0.15.1, using it is deprecated and it may be
removed again in a future Scipy release.
Source tarballs, binaries, and full release notes are available at
https://sourceforge.net/projects/scipy/files/scipy/0.15.1/
Best regards,
Pauli Virtanen
==
SciPy
11.02.2015, 21:57, Alan G Isaac kirjoitti:
[clip]
I think gains could be in lazy evaluation structures (e.g.,
a KroneckerProduct object that never actually produces the product
unless forced to.)
This sounds like an abstract linear operator interface. Several attempts
have been made to this
notes are available at
https://sourceforge.net/projects/scipy/files/scipy/0.15.0/
Best regards,
Pauli Virtanen
==
SciPy 0.15.0 Release Notes
==
SciPy 0.15.0 is the culmination of 6 months of hard work. It contains
several new features, numerous bug
06.03.2015, 22:23, Pauli Virtanen kirjoitti:
06.03.2015, 20:00, Benjamin Root kirjoitti:
A slightly different way to look at this is one of sharing data. If I am
working on a system with 3.4 and I want to share data with others who may
be using a mix of 2.7 and 3.3 systems, this problem makes
06.03.2015, 22:43, Eric Firing kirjoitti:
On 2015/03/06 10:23 AM, Pauli Virtanen wrote:
06.03.2015, 20:00, Benjamin Root kirjoitti:
A slightly different way to look at this is one of sharing data. If I am
working on a system with 3.4 and I want to share data with others who may
be using a mix
Arnd Baecker arnd.baecker at web.de writes:
[clip]
Still I would have thought that this should be working out-of-the box,
i.e. without the pickle.loads trick?
Pickle files should be considered incompatible between Python 2 and Python 3.
Python 3 interprets all bytes objects saved by Python 2
06.03.2015, 20:00, Benjamin Root kirjoitti:
A slightly different way to look at this is one of sharing data. If I am
working on a system with 3.4 and I want to share data with others who may
be using a mix of 2.7 and 3.3 systems, this problem makes npz format much
less attractive.
pickle is
07.03.2015, 01:29, Julian Taylor kirjoitti:
On 07.03.2015 00:20, Pauli Virtanen wrote:
06.03.2015, 22:43, Eric Firing kirjoitti:
On 2015/03/06 10:23 AM, Pauli Virtanen wrote:
06.03.2015, 20:00, Benjamin Root kirjoitti:
A slightly different way to look at this is one of sharing data. If I am
25.02.2015, 19:59, Pauli Virtanen kirjoitti:
25.02.2015, 07:11, Nathaniel Smith kirjoitti:
Not sure if this is a full GSoC but it would be good to get the benchmarks
into the numpy repository, so we can start asking people who submit
optimizations to submit new benchmarks as part of the PR
03.04.2015, 04:09, josef.p...@gmail.com kirjoitti:
[clip]
I think numpy indexing is not too difficult and follows a consistent
pattern, and I completely avoid mixing slices and index arrays with
ndim 2.
I think it should be DOA, except as a discussion topic for numpy 3000.
If you change
12.04.2015, 17:15, Peter Kerpedjiev kirjoitti:
[clip]
numpy/random/mtrand/distributions.c:892:1: internal compiler error:
Illegal instruction
An internal compiler error means your compiler (in this case, gcc) is
broken. The easiest solution is to use a newer version of the compiler,
assuming
15.06.2015, 12:00, Nathaniel Smith kirjoitti:
[clip]
http://homu.io/
One thing to consider is the disadvantage from security POV: this gives
full write access to the Numpy repository to that someone who is running
the bot. I don't see information on who this person (or these persons)
is and
28.05.2015, 20:35, Sturla Molden kirjoitti:
Pauli Virtanen p...@iki.fi wrote:
Is it possible to host them on github? I think there's an option to add
release notes and (apparently) to upload binaries if you go to the
Releases section --- there's one for each tag.
And then Sourceforge
28.05.2015, 20:05, David Cournapeau kirjoitti:
[clip]
In any case I've always been surprised that NumPy is distributed
through SourceForge, which has been sketchy for years now. Could it
simply be hosted on PyPI?
They don't accept arbitrary binaries like SF does, and some of our
installer
28.05.2015, 21:52, Julian Taylor kirjoitti:
there is no guarantee that github will not do this stuff in future too,
also PyPI or self hosting do not necessarily help as those resources can
be compromised.
The main thing that should be learned this and the many similar
incidents in the past is
24.08.2015, 01:02, Chris Laumann kirjoitti:
[clip]
Is there documentation about the limits and workarounds for py2/py3
pickle/np.save/load compatibility? I haven't found anything except
developer bug tracking discussions (eg. #4879 in github numpy).
Not sure if it's written down somewhere
14.08.2015, 20:45, Allan Haldane kirjoitti:
[clip]
Related to this, does anyone know how to debug numpy in gdb with proper
symbols/source lines, like I can do with other C extensions? I've tried
modifying numpy distutils to try to add the right compiler/linker flags,
without success.
15.08.2015, 01:44, Chris Barker kirjoitti:
[clip]
numpy doesn't use namespace packages, so develop mode works there.
The develop mode is mainly useful with a virtualenv.
Otherwise, you install work-in-progress development version into your
~/.local which then breaks everything else. In addition
13.07.2015, 20:08, Nathaniel Smith kirjoitti:
[clip]
Keep in mind that any solution needs to support weird systems too,
including Windows. I'm not sure we can assume that all BLAS libraries are
ABI compatible either. Debian/Ubuntu make sure that this is true for the
ones they ship, but not all
13.07.2015, 19:44, Eric Martin kirjoitti:
It seems to me that a potentially better route than add code to Numpy to
support BLAS library for each library is to make Numpy easy to configure
to compile with an arbitrary BLAS library (like what I've been doing).
Does this work:
export ATLAS=None
25.08.2015, 01:15, Chris Laumann kirjoitti:
Would it be possible then (in relatively short order) to create
a py2 - py3 numpy pickle converter?
You probably need to modify the pickle stream directly, replacing
*STRING opcodes with *BYTES opcodes when it comes to objects that are
needed for
mmit/832baa20f0b5
so you may have better luck with the dev version.
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26.08.2015, 14:14, Francesc Alted kirjoitti:
[clip]
2015-08-25 12:03 GMT+02:00 Nathaniel Smith n...@pobox.com:
Let's focus on evolving numpy as far as we can without major
break-the-world changes (no numpy 2.0, at least in the foreseeable
future).
And, as a target for that evolution,
However, since it's piecewise, there's purposefully support only
for real-valued roots.
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Hi,
In case someone is interested in getting notifications of performance
regressions in the Numpy and Scipy benchmarks, this is available as Atom
feeds at:
https://pv.github.io/numpy-bench/regressions.xml
https://pv.github.io/scipy-bench/regressions.xml
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10.02.2016, 04:09, Charles R Harris kirjoitti:
> I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
[clip]
> Please test, hopefully this will be that last beta needed.
FWIW, https://travis-ci.org/pv/testrig/builds/108384173
___
05.02.2016, 19:55, Nathaniel Smith kirjoitti:
> On Feb 5, 2016 8:28 AM, "Chris Barker - NOAA Federal"
> wrote:
>>
>>> An extra ~2 hours of tests / 6-way parallelism is not that big a deal
>>> in the grand scheme of things (and I guess it's probably less than
>>> that if we
atrix, eg.
https://travis-ci.org/pv/testrig/
Of course, if the suggestion is that the results are generated on
somewhere else than on travis, then that's a different matter.
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e some
understanding of the downstream package, but this would at least ensure
we are aware of stuff breaking. Provided it's covered by downstream test
suite, of course.
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31.01.2016, 14:41, Daπid kirjoitti:
> On 31 Jan 2016 13:08, "Pauli Virtanen" <p...@iki.fi> wrote:
>> For example, automated test rig that does the following:
>>
>> - run tests of a given downstream project version, against
>> previous numpy version,
cessarily volunteering to maintain the setup, though, but
if it seems useful, move it under numpy org.
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agmentation in the 2GB address space available? If dt==float64,
that requires 250MB contiguous.
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23.02.2016, 03:47, Charles R Harris kirjoitti:
> I'm delighted to announce the release of Numpy 1.11.0rc1. Hopefully the
> issues discovered in 1.11.0b3 have been dealt with and this release can go
> on to become the official release. Source files and documentation can be
> found on Sourceforge
>
fy the build to avoid
> them?
Maybe the ATLAS binaries supplied were compiled with g77 instead of
gfortran. If so, they should not be used with gfortran --- need to
recompile.
Also, in the past ATLAS binaries shipped by distributions had severe
bugs. However, 3.8.x may be a new enough version.
--
unting.
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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
course, working on that requires a somewhat
different level of committment than editing what's essentially
Stackexchange-provided wiki (where content gets relicensed with
attribution clauses where you have to reference stackexchange and not the
original author directly).
--
emory alignment --- not in dot
products, but in other computations.
Out of curiosity, what is the application where this is necessary?
Maybe there is a numerically stable formulation?
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Fri, 05 Aug 2016 10:06:02 +0300, Matti Picus kirjoitti:
[clip]
> I can submit a pull request to skip on pypy, or should this be solved in
> a more substantial way?
Should also be safe to just skip it on Pypy, it's testing that the wrong
way to use np.load also works on CPython.
--
Hi,
In the end some further API additions turn out to appear needed:
* NPY_ITER_COPY_IF_OVERLAP, NPY_ITER_OVERLAP_NOT_SAME
flags for NpyIter_New.
* New API function PyArray_MapIterArrayCopyIfOverlap,
as ufunc.at needs to check overlaps for index arrays
before constructing iterators, and
Mon, 12 Sep 2016 11:31:07 +0200, Sebastian Berg kirjoitti:
>> * NPY_ITER_COPY_IF_OVERLAP, NPY_ITER_OVERLAP_NOT_SAME
>> flags for NpyIter_New.
>>
>> * New API function PyArray_MapIterArrayCopyIfOverlap,
>> as ufunc.at needs to check overlaps for index arrays before
>> constructing iterators,
sumptions also there.
It might be possible to turn it on by default for operands with COPY or
UPDATEIFCOPY flags --- but I'm not sure if that's helpful (now you'd need
to set the flags to all input operands).
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Mon, 03 Oct 2016 15:07:28 -0400, Benjamin Root kirjoitti:
> With regards to arguments about holding onto large arrays, I would like
> to emphasize that my original suggestion mentioned weakref'ed numpy
> arrays.
> Essentially, the idea is to claw back only the raw memory blocks during
> that limbo
Sat, 12 Nov 2016 17:00:07 +, Pavlyk, Oleksandr kirjoitti:
[clip]
> if x_arr is not x:
>in_place = 1 # a copy was made, so we can work in place.
>
> The logic is of the last line turns out to be incorrect, because the
> input x can be a class with an array interface.
Please see:
Thu, 16 Mar 2017 08:15:08 +0100, Didrik Pinte kirjoitti:
>> The advantage of something like github pages is that it's big enough
>> that it *does* have dedicated ops support.
>
> Agreed. One issue is that we are working with a lot of legacy. Github
> will more than likely be a great solution to
Wed, 15 Mar 2017 12:11:09 -0400, Marten van Kerkwijk kirjoitti:
> Astropy uses readthedocs quite happily (auto-updates on merges to master
> too).
AFAIK, scipy cannot be built on readthedocs.
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Wed, 15 Mar 2017 14:56:52 -0700, Nathaniel Smith kirjoitti:
[clip]
> As long as we can fit under the 1 gig size limit then GH pages seems
> like the best option so far... it's reliable, widely understood, and all
> of the limits besides the 1 gig size are soft limits where they say
> they'll work
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