Announcing BLZ 0.6 series
=
What it is
--
BLZ is a chunked container for numerical data. Chunking allows for
efficient enlarging/shrinking of data container. In addition, it can
also be compressed for reducing memory/disk needs. The compression
process is carrie
=
Announcing python-blosc 1.2.0
=
What is new?
This release adds support for the multiple compressors added in Blosc
1.3 series. The new compressors are:
* lz4 (http://code.google.com/p/lz4/): A very fast
compressor/decompr
==
Announcing Numexpr 2.3
==
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
It wears multi-th
On 24 January 2014 22:43, Chris Barker wrote:
> Oscar,
>
> Cool stuff, thanks!
>
> I'm wondering though what the use-case really is.
The use-case is precisely the use-case for dtype='S' on Py2 except
that it also works on Py3.
> The P3 text model
> (actually the py2 one, too), is quite clear th
On Sat, 25 Jan 2014 01:05:15 +0100, Sebastian Berg wrote:
> 1. Comparison with None will broadcast in the future, so that `arr ==
> None` will actually compare all elements to None. (A FutureWarning for
> now)
This is a very useful change in behavior--thanks!
Stéfan
_
I think I have said this before, but its worth a repeat:
Pickle (including cPickle) is a slow hog! That might not be the overhead
you see, you just haven't noticed it yet.
I saw this some years ago when I worked on shared memory arrays for Numpy
(cf. my account on Github). Shared memory really
On Thu, Jan 23, 2014 at 11:49 AM, Chris Barker wrote:
> Thanks for poking into this all. I've lost track a bit, but I think:
>
> The 'S' type is clearly broken on py3 (at least). I think that gives us
> room to change it, and backward compatibly is less of an issue because it's
> broken already --
On 24 January 2014 23:09, Dinesh Vadhia wrote:
> Francesc: Thanks. I looked at numexpr a few years back but it didn't
> support array slicing/indexing. Has that changed?
>
No, but you can do it yourself.
big_array = np.empty(2)
piece = big_array[30:-50]
ne.evaluate('sqrt(piece)')
Here, c
On Sat, 2014-01-25 at 00:18 +, Nathaniel Smith wrote:
> On 25 Jan 2014 00:05, "Sebastian Berg"
> wrote:
> >
> > Hi all,
> >
> > in https://github.com/numpy/numpy/pull/3514 I proposed some changes
> to
> > the comparison operators. This includes:
> >
> > 1. Comparison with None will broadcast i
