[Numpy-discussion] ANN: carray 0.4 released

Francesc Alted faltet@pytables....
Fri Feb 11 13:21:43 CST 2011


Hi,

A new release of my new toy project is out.  Enjoy!

Announcing carray 0.4
=====================

What's new
----------

The most prominent feature in 0.4 is the support of multidimensional
carrays.  Than means that, for example, you can do::

    >>> a = ca.arange(6).reshape((2,3))

Now, you can access any element in any dimension::

    >>> a[:]
    array([[0, 1, 2],
           [3, 4, 5]])
    >>> a[1]
    array([3, 4, 5])
    >>> a[1,::2]
    array([3, 5])
    >>> a[1,1]
    4

Also, all the iterators in carray have received a couple of new
parameters that allows to `limit` or `skip` selected elements in
queries.

Finally, many performance improvements have been implemented (mainly
related with efficient zero-detection code).  This allows for improved
query times when using iterators.

See:
https://github.com/FrancescAlted/carray/wiki/query-compress
for an example on how fast the new iterators can do.

For more detailed info, see the release notes in:
https://github.com/FrancescAlted/carray/wiki/Release-0.4

What it is
----------

carray 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 needs.  The compression process
is carried out internally by Blosc, a high-performance compressor that
is optimized for binary data.

carray comes with an exhaustive test suite and fully supports both
32-bit and 64-bit platforms.  Also, it is typically tested on both UNIX
and Windows operating systems.

Resources
---------

Visit the main carray site repository at:
http://github.com/FrancescAlted/carray

You can download a source package from:
http://carray.pytables.org/download

Manual:
http://carray.pytables.org/docs/manual

Home of Blosc compressor:
http://blosc.pytables.org

User's mail list:
carray@googlegroups.com
http://groups.google.com/group/carray

-- 
Francesc Alted


More information about the NumPy-Discussion mailing list